Abstract
The development and manufacturing of sensors are of great importance to modern engineering, as sensors are essential for detecting environmental changes and for the monitoring of various systems. While conventional manufacturing is the most common method for fabricating sensors, additive manufacturing (commonly known as 3D printing) has gained popularity as an efficient alternative. Although additively manufactured sensors are applicable in many engineering fields, building an entire sensor (including the housing structure and sensing components) by additive manufacturing remains challenging. This work presents a comprehensive analysis of the additive manufacturing processes, materials, and applications for sensors that are either fully or partially produced by additive manufacturing. Key issues in material development and processes that limit the development of fully 3D-printed sensors are highlighted. Additionally, the role of additively manufactured sensors plays in green technology has been explored. This review is expected to provide the researchers with a comprehensive understanding of the processes and materials used to produce sensors for various applications.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
1 Introduction
Sensors are widely used to detect environmental changes and for condition monitoring [1], and they have broad applications in a multitude of modern devices and systems where data acquisition and processing are required [1,2,3]. Advances in technology have brought about various methods for manufacturing sensors. Additive manufacturing (AM), also known as 3D printing, is an advanced manufacturing process that has enabled fabrication capabilities that were unachievable by conventional methods [3, 4]. The ISO/ASTM (International Organization for Standardization/American Society for Testing and Materials) 52,900 standard defines additive manufacturing, as the "process of joining materials to make parts from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing methodologies" [5]. This standard establishes terminology that provides a consistent language and a framework for the additive manufacturing industry. In additive manufacturing technology, complex 3D structures are sliced into many 2D layers, making it easier to fabricate parts with complex geometries [6], reducing the need for assembly, and reducing material waste in the fabrication process. These features increase the feasibility of producing a more complex architecture of sensors [7].
Research on additive manufacturing has focused on finding ways to transcend the limitations of traditional manufacturing and realize the Fourth Industrial Revolution (Industry 4.0) [8]. Lack of customization is one limitation that AM technologies can help to address. For example, conventional manufacturing techniques can accurately produce parts only on planar surfaces, whereas additive manufacturing allows for fabrication directly on complex nonplanar structures [9]. AM technologies used for this purpose can generally be classified into several processes, such as material extrusion (MEX) [10], vat photopolymerization (VPP) [11], powder bed fusion (PBF) [12], sheet lamination (SHL) [13], binder jetting (BJT) [14], material jetting (MJT) [15], and directed energy deposition (DED) [16]. A variety of materials can be 3D-printed, including polymers, ceramics, metals, and their composites in a different state such as liquid or solid, depending on the process. Examples include silicon rubber [17], polymer composite [18], nanocomposite [19], polylactic acid (PLA) [20], acrylonitrile butadiene styrene (ABS) [21], exfoliated graphite [14], and hydrogels [22].
Additive manufacturing technologies have been widely used for fabricating sensing components [23, 24], molds [25, 26], and sensor housing [27]. Because various parts of a sensor are often made from different materials, it is necessary to develop additive manufacturing systems that are capable of fabrication with multiple materials. As not many additive manufacturing systems are currently capable of fulfilling this requirement, it has been challenging to produce an entire sensor by additive manufacturing. The hybrid manufacturing process combines AM with other manufacturing methods as a secondary process to improve the accuracy of the fabricated parts, their physical properties, and their architecture [6].
Additive manufacturing can be applied for sensor fabrication by either directly printing all sensor components or by additive manufacturing a housing in which sensor components can be embedded. An extensive review of the existing literature [1, 7, 9, 27,28,29,30,31,32,33,34] reveals that the differences between fully 3D-printed sensors and hybrid manufactured sensors—in terms of the applications, printing processes, and materials—have not been comprehensively investigated or discussed. Therefore, in this review, the authors aim to provide a detailed analysis of these two types of sensors by comparing their performance, functionality, and potential applications. This article is expected to be helpful for researchers, engineers, and manufacturers who are aiming to develop fully 3D-printed sensors. Additionally, this review has also attempted to clarify and understand the various contributions related to the use of additive manufacturing technologies in the development and fabrication of sensors specifically designed for applications in the realm of sustainable and green technologies.
1.1 General Process for Additive Manufacturing
In the additive manufacturing process, materials are bonded layer by layer through the fusion, binding, or solidification of materials [28, 35]. The general process for additive manufacturing includes the following steps: 1) creating a computer-aided design (CAD) file for the part, 2) converting the CAD file to a AM format such as Standard Tessellation Language(STL) or Additive Manufacturing File(AMF), 3) transmitting the AM file to the additive manufacturing system, where the structure is built, 4) removing the part from the build plate, and 5) post-processing the fabricated part [6].
1.2 Fully 3d-printed Sensors vs. Hybrid 3d-printed Sensors
The phrase “fully 3D-printed sensor” in this review refers to a sensor that was manufactured in its entirety using AM techniques, which may exclude interconnects between a sensor and external signal processing device. A hybrid 3D-printed sensor (or hybrid additively manufactured sensors), on the other hand, uses the technology to fabricate certain portions (such as the housing or sensing element) but still needs other components (related to sensor structure) that are not fabricated by additive manufacturing.
An example of a fully 3D-printed sensor is a stretchable, soft pressure sensor using a multi-material additive manufacturing system that has three extrusion heads for printing three different materials. The sensor (Fig. 1) is comprised of a polymer insulation material and an ionic liquid–based pressure sensitive layer that is sandwiched between carbon nanotube–based electrodes, creating a sensitive zone in the sensor that serves as a sensing mechanism [36]. As this sensor is designed to be subjected to bending, flexing, and impact, it can be applied to conformal surfaces as well as flat surfaces [37].
In contrast, the inductive proximity sensor shown in Fig. 2 is an example of a sensor fabricated by a hybrid additive manufacturing process. Embedding a pre-made sensing coil into an additively manufactured ceramic package can allow functionality in a wider range of applications, because the ceramic package enables the sensor to maintain its functionality in a high-temperature environment [38]. This paper will focus on the processes, materials, applications, and characteristics of sensors produced by both additive manufacturing and hybrid additive manufacturing.
2 Additive Manufacturing Processes
Conventional methods used for sensor manufacturing suffer from disadvantages such as high cost, long processing time, and low flexibility in design [39, 40]. AM technology has proven the ability to overcome these problems, and various AM methods can be used to create highly accurate structures with complex geometries [41,42,43]. Table 1 provides a comprehensive summary of the additive manufacturing techniques investigated in this study, detailing their fundamental concepts. The next sections provide literature reviews of each manufacturing technique, examining in depth the fabrication of sensors using various approaches.
2.1 Vat Photopolymerization
Vat photopolymerization (VPP) technology has been used to fabricate sensors for biomedical and engineering applications such as microfluidic devices [44, 58, 59], wearable sensors [60,61,62], chemical sensors [63], mechanical sensors [64], and gas sensor [65]. In this process, a photosensitive resin is solidified when the resin surface is exposed to light. Different radiation sources such as electron beams, visible light, ultraviolet (UV) light, and x-ray radiation can be applied for photopolymerization. Each layer can be manufactured in one of three ways: two-photon polymerization, vector scanning, and mask projection [66]. VPP systems are also classified into two configurations based on the location of the light source. One configuration applies a bottom-up approach where the light source is placed beneath the resin vat. The build platform moves up by one layer thickness to allow a new layer to be cured. In some cases, a blade is used to flatten the resin surface (Fig. 3). The second configuration uses a top-down configuration where the optical source is located above the resin vat [6].
Support structures are required to attach the printed part to the build platform in cases of sustaining the overhanging parts [67], and a VPP-printed part may also require post-processing (using heat or ultraviolet (UV) light, for example) to obtain suitable mechanical properties [68]. VPP is an efficient method for creating parts with complex geometries and excellent surface finishing. In particular, ultra-high-resolution nanoscale structures can be fabricated using the two-photon photopolymerization technique [6, 56], which primarily uses photopolymers. Therefore, the printing speeds using this technique are relatively low, since photopolymers require more time to cure. Kadimisetty et al. [44] developed a hybrid 3D-printed microfluidic device for rapid molecular diagnosis, including nucleic acid amplification tests (NAATs) play an important role in the identification and treatment of infections. The device has four different amplification reactors to support multiple analyses. The reactor arrays are fabricated using stereolithography technology, static coating technology was used to improve biocompatibility, and methacrylate-based resin was used to detect nucleic acid. The ionic skin proposed by Yin et al. [22] is an example of a highly sensitive and stretchable capacitive strain/pressure sensor that was partially fabricated by AM. Digital light processing (DLP) was used to fabricate two electrode layers made from ionically conductive hydrogel [22]. The finished sensor has five layers: two electrode layers and three insulating layers made from 3 M VHB 4905 double-sided high-strength pressure-sensitive foam tapes that use acrylic adhesives. In another study, Zega et al. [45] designed and fabricated an accelerometer for measuring acceleration in three orthogonal axes using a combination of stereolithography and metallization processes. Two layers of copper are applied step by step through metallization, and the electrodes are then mounted on the outside surface of the structure to sense the differential capacity. There is another study in the literature [46] as an example of a hybrid 3D-printed sensor that was produced using the VPP method. The microreactor of the sensor was 3D-printed, while the ZnIn2S4-ZIS electrode was screen-printed and attached externally. This device has been designed to detect alpha-fetoprotein using both colorimetric and photoelectrochemical methods.
2.2 Material Extrusion
Material extrusion has become one of the most common additive manufacturing methods ever since fused deposition modeling from Stratasys (FDM) was introduced [56]. In the material extrusion process, material is pushed through the print head or nozzle by an extruder (screw-based, pneumatic-based, plunger-based, or filament-based mechanism). The material is solidified after deposition on the substrate (i.e., build platform) [42], as shown in Fig. 4. The diameter and shape of the nozzle tip determine the size and shape of the extruded filament. The mechanical properties of the fabricated part significantly depend on the layer thickness, the width and orientation of the filaments, and the gap between layers or within a layer [56, 69]. While extrusion-based machines are generally inexpensive and can be used to fabricate functional parts with different materials, the parts fabricated by this method can suffer from low resolution and poor surface finish [70].
2.2.1 Fully 3D-printed Sensors by Material Extrusion
Christ et al. [47] developed fully 3D-printed strain sensors using a multi-material material extrusion method. In this study, thermoplastic urethane (TPU) and multiwalled carbon nanotubes (MWCNT) were used to build the insulating part and electrodes. The resulting sensors showed excellent piezoresistive responses and high reliability. A glove for measuring finger flexure was also 3D-printed to demonstrate the potential of the proposed sensor for applications such as wearable electronics. Emon et al. [36] developed a fully 3D-printed sensor composed of three different materials using a direct-ink-writing (DIW) system with three different extruders. A combination of high-precision motorized linear stages and extruders (syringes) were used in this system. Figure 5 shows the setup of the multi-material DIW printing system.
A stretchable tactile sensor with the ability to detect human movements such as finger motion, developed by Guo et al. [48], is another example where a material extrusion system was employed to fabricate all sensor components conformally. The sensor consists of six layers: one base layer, two electrodes (one on top and one on the bottom), a dielectric layer, a sensing layer, and a supporting layer. Figure 6 shows the steps involved in fabricating the fully 3D-printed sensor.
Overview of a tactile sensor’s additive manufacturing process, highlighting the layered composition (a, b, c) and sequential steps (d) on a glass substrate, from base creation to final drying after support removal (Reproduced with permission from [48], Copyright 2017. Wiley)
2.2.2 Hybrid 3D-printed Sensors by Material Extrusion
In Zhu et al., a soft electrical impedance tomography sensor was fabricated on a porcine lung by using an in situ DIW process [49]. In the customized additive manufacturing system in their study, offline shape learning and real-time computer vision–based tracking was applied to approximate the surface deformation to create an online toolpath (Fig. 7). The sensor consists of a thin sensing layer made from hydrogel and some copper electrodes. To prepare the ionic hydrogel for the matrix, they used lithium chloride for ion conductivity as well as polyacrylamide (PAM), a UV-curable and stretchable material. The electrodes were embedded in a silicone ring, which was attached to the hydrogel layer by treating it with benzophenone photo-initiator during UV irradiation, leading to hydrogel–electrode interface stability during large deformations (Fig. 8) [49].
A sensor is fabricated in situ on a lung during respiration-induced lung deformation. Illustrations showing: (A) conformal printing of a hydrogel ink on the lung surface; (B) marker tracking; (C) 3D scanning; and (D) monitoring with a 3D-printed sensor. (Reproduced with permission from [49])
Schematic of an electrical impedance tomography sensor (Reproduced with permission from [49])
Material extrusion has been used for several other applications. Ruan et al. fabricated a sensor device that is capable of simultaneously detecting the immunogens atrazine and acetochlor, which are two commonly used herbicides that can cause environmental pollution [71]. The fused filament fabrication (FFF) process was used to construct accessory devices with poly (lactic acid) (PLA). A wearable sensor was developed by Katseli et al. to measure sweat glucose noninvasively [50], in which a ring-shaped sensor consisting of three plastic electrodes was embedded into the inner side of a plastic ring (Fig. 9). The housing of the electrode (e-ring) was 3D-printed in a single step using a FFF printer. The electrochemical ring (e-ring) was coupled to a potentiostat after a coating of gold film was applied to the electrodes to increase their sensitivity.
Dimensions, flexibility, and schematic of a wearable sensor manufactured via additive manufacturing. (Reprinted with permission from [50].
In yet another application, Lei et al. [72] designed and fabricated an ionic hydrogel–based skin for sensing body temperature and motion. The sensor incorporates two grid-structured hydrogel layers that were 3D-printed (using the DIW process) onto a capacitor circuit in order to magnify any change in the capacitive area upon external stimuli. This work verified excellent pressure sensitivity (within 1 kPa) and stable capacitance–temperature response of the fabricated ionic skin, which is promising for the development of artificially intelligent skins based on stimuli-responsive hydrogels. Valentine et al. [73] designed and created a soft strain sensor by combining additive manufacturing and pick-and-place methods (Fig. 10). This work uses TPU and AgTPU for DIW of a dielectric matrix and conductive electrodes. Next, electrical components such as a light emitting diode (LED), a resistor, and a microprocessor chip were mounted by pick-and-place approach in which an empty nozzle is used to pick up a part and place it in the desired location on the circuit. Conductive traces are then 3D-printed to connect the electrical components. The proposed hybrid approach can be applied for fabrication of soft robotics and wearable sensors.
Schematic of a hybrid 3D-printed strain sensor (Reproduced from [73].
2.3 Material Jetting
Material jetting is another AM process used in sensor fabrication to create parts with high resolution in which droplets of material are deposited on a substrate (Fig. 11) [42]. In this regard, the materials must be in liquid form to be printable or heated or solved in a proper solvent to decrease the viscosity. The droplet size, droplet speed, droplet viscosity, material surface tension, and the gap between the nozzle and substrate can affect the quality of the fabricated parts [56].
In the material jetting process, two major approaches exist to form and expel the material droplets: drop-on-demand and continuous stream (Fig. 12). The drop-on-demand approach uses thermal, electrostatic, and piezoelectric actuators to apply pressure, resulting in the ejection of the droplet from the nozzle. In a continuous stream printing system, consistent pressure on the material in the reservoir is used to create a continuous stream of liquid. Although the material jetting process suffers from nozzle blockage as a main drawback, it is an effective way to fabricate parts with high resolution with an insignificant amount of material waste which makes it a good candidate for fabrication of sensors including biomedical sensors [51, 74, 75], RF harvesting sensor [76], chemical sensor [77], temperature sensor [78], tactile sensor and electronics [26, 52].
Mojena-Medina et al. developed a bioimpedance sensor produced using material jetting printer for real-time observation of cultured cells (Fig. 13) [53]. The materials used for fabricating the interdigitated electrode sensors (IDEs) included silver nanoparticles as a conductive component, dielectric-based ink as an insulating layer, and polyethylene terephthalate film as a substrate.
a Schematics (b-e) and manufacturing strategies for inkjet printing coplanar capacitors, depicting the materials utilized and curing parameters employed in the sensor development. (Reproduced with permission from [53])
Arshavsky-Graham et al. [54] presented a microfluidic device with an optical aptasensor to detect a target protein. Material jetting with a polyacrylate-based photopolymer was used to fabricate the microfluidic platform. The 3D-printed microfluidic platform and a porous silicon–based aptasensor were attached carefully using a UV-curable adhesive. The device includes two different microchannels located at the bottom of the fabricated part that allow the fluid to come into contact with a porous silicon–based aptasensor (Fig. 14).
Integration of silicon aptasensor and microfluidic device. (a) a 3D-printed microfluidic device with a built-in porous silicon (Psi) aptasensor; (b) a schematic diagram illustrating the device's distinct layers in cross-section. (reproduced with permission from [54])
Khan et al. [79] demonstrated an approach for sensor fabrication in which a single substrate accommodates both the soft and hard electrical components. They created a wearable sensor patch that included electrodes to record an electrocardiography signal and a thermistor to measure body temperature. The electrodes were fabricated by inkjet printing using gold ink, while the thermistor was fabricated by stencil printing using nickel oxide.
2.4 Binder Jetting
In the binder jetting process, a liquid binder is sprayed on a bed of material powder selectively to create a cross section of the part (Fig. 15) [56]. The mechanical properties of the binder, the size and shape of the powder particles, the powder–binder interaction, the wettability of the powder, and the post-processing all play a vital role in the quality of the finished part [80,81,82]. Some binder jetting–based printers have multiple nozzles by that allow multicolor parts to be fabricated rapidly [6]. While parts manufactured using binder jetting do not suffer from shrinkage issues (since there is no need for high temperature in this process), the parts require post-processing in some cases to achieve the proper mechanical properties, as rough surface finish is a main disadvantage of this technology.
A few studies have reported the use of binder jetting for fabricating 3D-printed sensors. Achille et al. [83] demonstrated the fabrication of capillarity-based microfluidic devices using this technology. Faller et al. [55] used binder jetting and material jetting to fabricate a capacitor-based sensor designed to measure forces and pressure in harsh environments. Steel and aluminum oxide (Al2O3) ceramic materials are used for this purpose [55].
2.5 Powder Bed Fusion
Powder bed fusion (PBF) is a technology used for additive manufacturing mainly with polymers. In this method, an energy source (such as laser light or an electron beam) is focused on a uniformly spread powder to selectively melt the powder according to a 3D model to build the finished part [84]. The PBF process can be classified into three types: selective laser sintering, selective laser melting, and electron beam melting [85]. No studies reporting the creation of fully 3D-printed sensors using PBF were found. However, PBF has been used in some hybrid methods for manufacturing sensors.
Two research groups have reported using PBF in fabricating sensors that are hybrid 3D-printed. Hossain et al. were successful in embedding piezoelectric ceramic materials using the electron beam additive manufacturing process [12]. This technology makes it possible to embed sensors in locations on parts that were previously inaccessible. Ambrosi et al. fabricated helical stainless-steel electrodes with a selective laser melting method which were used as several electrochemical systems (pseudo capacitors, oxygen evolution catalyst, and pH sensors) [57].
3 Materials for 3D Printable Sensors
3.1 Materials for Fully 3D-printed Sensors
Carbon-based inks are one of the essential materials for printing soft electronics and sensors. One of the most common carbon-based conductive inks is graphene [86]. The graphene composition consists of a flat layer of sp2-hybridized carbon particles (in which each carbon atom is bound by two single bonds and one double bond in a triangular arrangement where bonds are at 120° to one another), producing an excellent structure for printing composite nanomaterials. Graphene-MWCNT composite electrodes exhibit good performance in terms of sensor conductivity [87]. One limitation pertaining to graphene is its relatively high expense. In response, scientists are looking into using carbon nanotubes (CNT) as an alternative in soft electronics. In particular, a three-component soft pressure sensor is constructed. First, the upper and lower surfaces of the pressure sensor are covered in a commercially available insulating material (photopolymer TangoPlus™ FLX930; Stratasys, Eden Prairie, Minn., USA). The insulating layer is then covered with CNT electrodes. The CNT is subsequently covered with an ionic layer (1-ethyl-3-methyl-imidazolium tetrafluoroborate). Sensitive units are established at the electrode intersections when the resulting structure is positioned between two electrodes [88]. Wearable electronics and robotics both benefit from flexible sensors and soft actuators made of photopolymer resin. Sensors made for lightweight and customizable electronics use a variety of polymer compositions, such as functional resins, hydrogels, elastomers, blends, composites, and biological materials [89]. Different 3D-printed structures can be made using different polymers. For example, the full additive manufacturing of microfluidic devices is made possible by methacrylate-based resin using a VPP technique [44]. Polylactic Acid (PLA) is one of the most common 3D-printable materials. PLA can also be mixed with copper particles to produce a composite filament in 3D-printed gas sensors for ammonia detection [20]. Furthermore, a prior work shown that a combination of PLA and copper pallets can be used to fabricate fully 3D-printed gas sensors [20].
3.2 Materials for Hybrid 3D-printed Sensors
Silicon rubber is a material used for various types of sensors (including pressure sensors). When using this material in material extrusion, it is necessary to control multiple parameters, such as the ratio of the silicon rubber, the nozzle diameter, and the thickness of the overall material. Silicon rubber-based pressure sensors are increasingly utilized in various fields such as construction, aerospace device monitoring, and machinery. Silicon rubber is mainly used to fabricate optical fiber Fabry–Perot pressure sensors used in industrial environments. Some silicon rubber material is used for biomedical purposes to manufacture specific artificial organs [17]. Moreover, silicon rubber/carbon black nanocomposite is used to create another type of flexible pressure sensors that can be used in aerospace, robotics, and the automobile industry, as these sensors have better stretchability [90]. Additionally, another study showed that silicon rubber is a strong candidate for strain sensors that detects changes in electrical response whenever there is a change in resistance [91]. Most nanocomposites—which combine two or more materials (where at least one is a nanomaterial) having different physical/chemical properties—or bio-nanocomposites are used for electrochemical sensors. Nanocomposites are mainly used in sensors for the detection of ultra-trace amounts of arsenic, as recent studies show that more than 100 million individuals have been impacted by arsenic poisoning; typical materials used for this purpose are carbon electrodes of various forms, such as carbon paste and graphene electrodes [92].
Hydrogel exhibits versatile applicability in diverse sensor types, including temperature, motion detection, ions, ionic strength (and pH), molecules, biosensing, gas detection, and humidity sensors [93]. It can be combined with other materials such as particle-reinforced, fiber, and anisotropic hydrogel filler composites [94]. Adding these composites will improve the rheological properties of the ink for better printability as well as increase the mechanical stability of the hydrogel [94]. Additionally, the functional hydrogel can be enhanced when adding carbomer, which has excellent rheological properties (such as temperature sensitivity) in network hydrogel and shows good printing performance. The resulting multifunctional hydrogels can be used in different applications such as soft electronics, 4D printing (where additive manufacturing techniques are used to create parts that can change their structure over time when exposed to specific conditions), and soft devices [95]. Hydrogel has been used previously for 3D-printed sensing layers [22, 72] and protective layers for electrodes [49] in sensors.
Micro tensile testing guidelines provided by ASTM indicate that polylactide acid (PLA), a common material in additive manufacturing, has strong mechanical strength [96]. PLA is the material most commonly used in FFF. It is widely used in many different industries, including aerospace, biomedical, and automotive. Furthermore, PLA is the material of choice for commercial additive manufacturing process, especially when using inexpensive machines [97]. 3D-printed PLA filaments can be used to construct low-cost and lightweight split ring resonators (SSR) for chemical sensing purposes. For this sensor, the SSR and the cavity were fabricated through the FFF process. However, the Teflon tube was manufactured conventionally [98].
Polyvinylidene fluoride (PVDF) is used in films and piezoelectric sensors, which are used in organic materials, quartz, and ceramics, to detect vibrations. Its exceptional qualities—such as flexibility, acoustic impedance, thermal conductivity, chemical resistance, and mechanical strength—make it suitable for vibration applications in a variety of industries, such as health monitoring and mechanical equipment evaluations [99]. PVDF is advantageous because it has a lower cost than other fluorinated polymers [100]. According to the previous study, additive manufacturing of polyvinylidene fluoride (PVDF) inside a PVDF-2D molybdenum disulfide composite significantly increases piezoelectricity by eight times. Increased β phase volume, filler fraction, and heterogeneous strain distribution are responsible for the improved performance. For sensors and conformal applications, this offers a potential route for high-performance 3D-printed piezoelectric devices [101].
Acrylonitrile butadiene styrene (ABS) material is generally used with the FFF process to create sensors for many applications. Previous research employs ABS based carbon black (CB) filament in additive manufacturing a low-cost concave capacitive sensor for measuring void fraction in two-phase flow, demonstrating enhanced mechanical and thermal properties, conductivity from graphene, CNT, CB, with capacitance values compared to copper sensors and a regression model developed for void fraction prediction [21].
3D-printing with metals opens a new door for providing high-quality metallic parts with highly complex designs. This process is used in a hybrid technique with other AM processes to fabricate metallic structures with embedded sensors [102]. In order to monitor strain at high temperatures, a previous work investigates the use of AM to embed copper-coated optical fibers in nickel layers on stainless steel components. Temperature-induced strains up to 400 °C are investigated in this study with minimum signal attenuation and evident compressive strain achieved [103].
The material extrusion process with binder-coated zirconia is used in combination with other production techniques to fabricate an inductive proximity sensor through ceramic additive manufacturing [38]. Using a composite slurry including BaTiO3 nanoparticles and Mask-Image-Projection-based Stereolithography (MIP-SL) technology, a previous study focuses on the additive manufacturing of piezoelectric ceramics. With a density of 93.7% of bulk BaTiO3, the post-process exhibits notable piezoelectric qualities [104].
4 Application of 3D-Printed Sensors
4.1 Mechanical Sensors
Mechanical sensors are used to detect physical quantities and phenomena through mechanical means by detecting changes in the electrical resistance of the sensor material [105]. Mechanical sensors can have electrical properties such as conductivity and band structure as well as mechanical properties such as elasticity. The sensor can be entirely 3D-printed with materials responsible for structural support, signal communication, and pressure sensitivity. The resulting 3D-printed mechanical sensors are evaluated based on their accuracy, resolution, surface finish, and whether or not the mechanical properties of the sensor material enable it to maintain excellent sensing capabilities [106]. The following subsections present different types of fully 3D-printed and partially 3D-printed mechanical sensors.
4.1.1 Fully 3D-printed Mechanical Sensors
Different materials and additive manufacturing processes can be used to fabricate sensors that are fully 3D-printed [107]. A prospective sector for capacitive sensors is established by 3D-printed capacitive sensors, which serve as examples of mechanical sensors suitable for temperature monitoring and liquid level sensing. They also show appropriateness for applications such as swimming soft robots [108].
Flexible strain sensors can also be 3D-printed using MWCNT and an elastomer composite to create a strain sensor that can detect a maximum strain of ~ 60% and a subtle strain of 0.01% as well as a sensitivity of 8.939 and durability of 10,000 cycles [109]. One study showed an affordable method for fabricating monolithic dual-material 3D-printed stretchable and wearable ionic skin sensors that can be used for various applications [110]. Another study reported successful additive manufacturing of a transparent hydrogel and a conductive heterogeneous material for elastomer-based systems to produce a sensor (Fig. 16) that can estimate a change in resistance of up to 30% when bending [111].
Illustration of an additive manufactured hydrogel-elastomer device showcasing adaptability in shape and design. (a) a resistance-based strain gauge, (b) its application in a flexible glove, and (c) resistance change over time for various hand gestures. (Reproduced with permission from [111].
Dual-head additive manufacturing enables the fabrication of piezoresistive and wearable sensors using elastomer composite fiber; the resulting sensor shows capabilities of detecting individual joint movements when bending, and the sensor can be upgraded for future applications such as electronic skin, soft robotics, and wearable devices [112]. Guo et al. [48] prepared 3D-printed conformal multi-material, multi-scale, and multi-functional parts under ambient conditions; the resulting sensor has the capabilities of detecting finger motions and monitoring pulse rates. Another study showed that additive manufacturing that utilizes DLP could be used to make fully 3D-printed tactile sensors for robotics applications; these tactile sensors can detect the bending and grip of the finger [113].
4.1.2 Hybrid 3D-printed Mechanical Sensors
A case in point is a flexible mechanical sensor produced through screen printing (an ionic liquid polymer to form the piezoresistive intermediate sensing layer encapsuled with two insulating layers) is used on 3D-printed tire to measure force [114]. In another similar application, a rubber-based strain sensor attached to a tire is used to detect changes the sensor’s capacitance when a force is exerted on the tire [115]. Additive manufacturing can be used to build complex and intelligent structures, as it enables wires and capacitive sensors to be embedded in a 3D-printed part [116]. Highly stretchable and sensitive 3D-printed strain sensors can also be made from graphene composites with excellent mechanical and electrical properties [117]. Strain sensors can also be embedded inside a rigid structure (Fig. 26) to create smart static and dynamic sensing mechanisms [118]. Another distinguishing material for mechanical sensors is hydrogel, which can be used to fabricate 3D-printed soft electronics such as actuators and sensors. Additive manufacturing enables the use of a wide range of composite materials; for example, a hydrogel can be modified to be rigid, conductive, and 3D printable for 3D-printed wearable strain sensors [119].
Another type of mechanical sensor is a capacitive force sensor that combines fiber encapsulation and thermoplastic elastomer for additive manufacturing and includes embedded wires to characterize the sensor capacitance when force is applied [120]. One study presented a flexible force sensor fabricated using additive manufacturing that utilized graphite (a conductive allotrope of carbon) for sensing forces ranging from 3.5 mN to 17.5 mN [121]. In another study, a piezoresistive force sensor fabricated using carbon black composite was used to detect a wide range of strain under compressive loads; as this sensor was capable of detecting forces as low as 0.1 N, it might eventually be used in soft robotics [122]. Another study presented an extrusion-based printing system to create a flexible pressure sensor with CNT coated with elastomer fiber for microstructures; the resulting sensor is suitable for many applications, such as biomedical devices, robotics, and wearable electronics [123]. Rahman et al. [124] designed and demonstrated an interdigitated capacitive touch sensor using aerosol jet technology, in which silver nanoparticles were used for printing the electrodes and where the fabricated part was placed in an oven at 200 ºC for 30 min for sintering. The developed sensor can conform to curved surfaces. In this work, the sensing element was 3D-printed only.
Temperature sensors can also be produced using hybrid additive manufacturing methods. A mechanical sensor that uses luminescence as a sensing mechanism for temperature measurements can be fabricated using micro additive manufacturing [125]. Additive manufacturing that utilizes inkjet printing with silver nanoparticles and a Kapton® flexible polymer substrate can also be used to produce a flexible temperature sensor that can estimate human body temperature [78].
oIn another study, a coating technique was developed by Sauerbrunn et al. to fabricate a temperature sensor. The sensor included a carbon fiber substrate, two layers of primer, and a mixed solution of exfoliated graphite and latex as a conductive material for obtaining temperature measurements from an object [14]. Figure 17 shows the method for fabricating the thin film sensor using a polymer/carbon composite.
Fabrication of a twelve-array temperature sensor. Primer (b) is applied to the substrate (a). In order to pattern the latex/exfoliated graphite composite sensors (designated as "R"), spray coating is applied over a stencil (c). Leads and thermocouples (TC) attachment (d), and a Peltier heater/cooler is placed beneath one corner of the sensor (e) (Reproduced with permission from [14].
A displacement sensor is one type of mechanical sensor that can be produced using a hybrid technique of additive manufacturing. In one study, a sensor that could detect small displacements (up to 0.1 mm) was fabricated using a hybrid technique of additive manufacturing [126]. In another study, a 3D-printed biomimetic angular acceleration sensor was introduced; this mechanical sensor was made from two 3D-printed structures that were combined to form a channel for electromagnetic flow [127]. An eddy current position sensor was developed, which includes a flexible inductor fabricated by an inkjet printer with silver ink on a substrate. It can measure the displacement of a large conductive target in a direction perpendicular to the inductor plane and the displacement of a small steel ball parallel to the inductor plane [128].
Angular velocity and position measurements are also crucial for many applications. One study introduced a fabricated capacitance sensor for angular velocity/position estimation. The sensor uses inkjet technology to fabricate electrodes on a flexible substrate; the electrodes are then attached to the inner wall of the stator and to the perimeter of the rotor cylinder for angular velocity and position measurements [129]. In another study, different substrates were used to produce high-performance stretchable capacitive sensors using a photopolymer extrusion additive manufacturing systems with carbon black electrodes on a barium titanate elastomer composite surface. The resulting capacitive sensor showed excellent consistency and repeatability while stretching for more than 1,000 cycles [130].
A mechanical sensor can measure multiple parameters simultaneously. One study showed a sensor for estimating temperature and humidity that was 3D-printed by inkjet printing with silver nanoparticles (AgNPs) as a conductive ink. The resulting sensor can estimate the temperature within the range from 25–75 °C and relative humidity within the range of 0–90% [131].
A recent study introduced the use of a material extrusion process with two driving wheels and a filament base to fabricate using additive manufacturing process a fiber Bragg grating sensor inside polylactic acid (PLA) to produce a sensor that measures the vertical pressure on an object [132]. Fiber Bragg grating pressure sensors produced by a material extrusion process can also be used to detect temperature, displacement, stress, and strain [133]. Additive manufacturing technologies can also be utilized to fabricate an optical fiber Bragg grating pressure sensor having a cylindrical rigid structure that can be used to detect pressure in response to deformation [134].
Additive manufacturing also be used to create a fully functional flexible pressure sensor for electrical skins by first using the stereolithography process to fabricate a hollow microstructure and then attaching a pressure sensor. The resulting sensor aids in identifying physiological signals such as specific movements, heart pulses, and swallowing movements in the esophagus process [107]. A recent study showed that a process combining additive manufacturing with a coating technique can be used to create radio frequency antennas and strain sensors; the sensors showed excellent radiation frequency and good performance under bending [135]. In another study, the FFF process was used to fabricate rigid structures with embedded strain sensors to make intelligent systems and showed how dynamic measurements could be utilized with embedded 3D-printed strain sensors [136]. Another application involved tactile sensors that were conformally manufactured on a freeform surface in a layer-by-layer fashion utilizing the DIW process with a CNT nanocomposite [19]. A partially 3D-printed pressure sensor has also been fabricated using a selective laser sintering (SLS) method, fabricated on a polyamide substrate utilizing aerosol jet printing, and mixed with screen printing for a complete piezoresistive pressure sensor. Such a sensor may have future applications in the medical field to allow disabled individuals to have better mobility, or it could be used to develop innovative insole products [137].
Additionally, a three-axis accelerometer has been manufactured by Zega et al. [138] by the VPP process and following metallization processes. It includes a test mass hung from the springs and provides translations of the acceleration of the mass along three axes: forward and back (x axis), left and right (y axis), and up and down (z axis). The experimental results verified the high performance and sensitivity of the proposed accelerometer, suggesting that it shows promise for wearable sensors and robotics.
4.2 Chemical Sensors
Chemical sensors are used to measure the chemical properties of an analyte in measurable signals such as voltage output [139]. Depending on the operating principles of the transducers, chemical sensors are able to measure the changes in an analyte via optical, electrochemical, electrical, mass sensitivity, magnetic, thermometric, and radiational effects [140].
4.2.1 Fully 3D-printed Chemical Sensors
Guo et al. [24] fabricated liquid sensors from a PLA/MWCNT nanocomposite in a freeform helical geometry, in which solvent-cast additive manufacturing was used to fabricate the helical sensor. As the resulting sensor showed good sensitivity and selectivity in a short immersion time (1 s) in a solvent, it shows promise for obtaining precise measurements in microscale and nanoscale systems. Metal additive manufacturing can also be used to fabricate bespoke electrochemical stainless-steel electrodes that can have applications in pH sensors, electrochemical capacitors, and oxygen evolution catalysts utilizing the deposition of iridium oxide films [57]. Figure 18 shows the difference between the electrodes with and without iridium oxide. Figure 18(b) summarizes the resulting cyclic voltammograms after different scans, which show the successive deposition of iridium oxide layers on the electrode surface.
Iridium oxide (IrO2) layer modification of steel electrode. A) 200 images of a steel electrode taken before and after iridium oxide (IrO2) coating was deposited. B) Cyclic voltammograms acquired following 50, 100, and 200 potential scans from steel electrodes (of the identical dimensions). (Reproduced with permission from [57].
Chaloeipote et al. [20] developed a fully 3D-printed gas sensor using a blended composite of PLA pellets and copper powder. The composite was turned into a filament of 1.75 mm diameter. The sensor was fabricated by the FFF process and was later sintered to obtain the final part. The sensing mechanism of this sensor is based on the reaction from surface-absorbed direct electron transfer (oxygen species) between NH3 molecules and copper oxide. [20]Liquid leakage can also be detected using a 3D-printed liquid sensor, as shown in a study where Li et al. [141] developed a 3D-printed mesh-shaped liquid sensor (Fig. 19) using multi-material stereolithography that can be used to identify the position and volume of liquid leakage. In the presence of polyethylene glycol diacrylate (PEGDA) and MWCNT composite, the resistivity increases and the resistance of pure PEGDA hydrogel decreases with the absorption of liquid droplets [141].
A 40% PEGDA hydrogel-based liquid sensor (a) Circuit diagram of the sensor (b) electrical sensitivity test for the post 4 µL water absorption (c) resistance change in branch 2 after water diffusion across two tests (d) resistance variations across all branches during electrical sensitivity test. (Reproduced from [141].
Liquid sensors have also been manufactured through the DIW process [142]. The electrical conductivity of carbon nanotube and the shape memory behavior of poly(D,L-lactide-co-trimethylene carbonate) (PLMC) were combined to detect fast electro-responsive shape-changing behavior.
In addition, additive manufacturing of pH-sensitive hydrogels based on poly(3,4-ethylenedioxythiophene) (PEDOT) doped with negatively charged poly(styrenesulfonate) (PSS) and robust hydrophilic polyurethane (HPU) inks has also been demonstrated [143]. In this method, PEDOT:PSS was selected for pH sensitivity, HPU served as a reinforcement material, and the electrodes were fabricated by the direct ink writing method. Here, the rehydration process is used to release the pattern from the plastic substrates (Fig. 20).
Additive manufacturing of pH-sensitive hydrogels illustrating (a) ink appropriate for 3D gel extrusion printing, (b) extrusion process on dry HPU films, (c, d) resultant free standing HPU hydrogel films with PEDOT:PSS/HPU tracks post-hydration 10 mm scale bar in (c) (Reproduced with permission from [143].
4.2.2 Hybrid 3D-printed Chemical Sensors
In hybrid-manufactured sensors, additive manufacturing technologies are used to fabricate a portion of the sensor. Typically, this involved additive manufacturing of customized housings that are designed to hold electrodes [144, 145]. Shallan et al. developed a transparent 3D microfluidic device that can detect nitrate concentration in tap water [146]. Stefanov et al. demonstrated a setup for gas phase photocatalytic reactions in which the reactor was 3D-printed [147]. The sensor was used for air pollution monitoring. Phillip et al. [148] have carried out a three-step organic reaction sequence in 3D-printed reactors, in which the reactors provided performance similar to glassware reactors but required less chemical handling. Gowers et al. [149] developed a robust 3D-printed microfluidic analysis system that incorporates microdialysis probes for monitoring glucose and lactate.
Hong et al. [150] adopted an AM process to fabricate a microfluidic electrochemical sensor to detects the electrochemical phenomena of metal ions. The VPP process was used to fabricate a microfluidic cell, and a screen-printing process to fabricate a flexible electrode (Fig. 21). Figure 21(a) and b show the transparent microfluidic device before and after an electrode is inserted into the cavity, and Fig. 21(c) includes a photo showing how sensor can be easily bent. The schematic in Fig. 21(d) shows the computational domain for calculating the fluid velocity at the inlet. Finally, in Fig. 21(e) shows a side view of the mock flow distribution diagram from a microchannel simulation using COMSOL Multiphysics software.
Microfluidic device screen printed electrode (SPE) integration (a, b): optical representations of the devices with and without the SPE. (c) The SPE's flexibility. (d) The work electrode-equipped microfluidic cell's computational domain. (e) velocity profile side view. (reproduced with permission from [150].
Kit-Anan et al. [151] developed paper-based disposable sensors for detecting ascorbic acid by using inkjet-printed polyaniline–modified screen-printed carbon electrode for pre-screening purposes. In the cyclic voltammetry experiments, the sensors produced a current peak that was ten times more prominent than that of bare carbon graphite paste electrodes. Lu et al. [152] fabricated a quartz micro electrical–mechanical system (MEMS) catalytic methane sensor with a back-etched cone cavity manufactured by abrasive sand blasting, together with lift-off, screen printing, and inkjet printing processes (a process that is simpler than that for silicon-based gas sensors); the resulting sensor showed good mechanical stability because of the cone-shaped structure. Salim et al. [98] 3D-printed a resonator for chemical sensing applications that replaced copper with PLA and Styrofoam. The 3D-printed split ring resonator and cavity provided 61% and 85% weight reduction as compared to their previous work in [153]. Additive manufacturing (using DIW) of CuO/Cu2O/Cu microparticles on the sensor substrate has also been reported by Siebert et al. [154]. The physicochemical reactions on the sensor surface dictate the gas sensing mechanism based on ionosorption, decomposition, and/or oxidation of gas vapor molecules. For p-type sensing, the holes accumulation layer in each CuO/Cu2O/Cu microparticle explains the mechanism for gas sensing [155, 156]. Fabrication of flexible ion selective field effect transistors by hybridization of fabricated organic ion selective electrodes and inorganic transistors has also been reported in the literature [157], in which hybrid 3D-printed transistors were used in sensors to measure chemicals in human saliva. Ruan et al. [71] used an FFF printing process to fabricate accessories for their immunosensors that provided a platform to detect the presence of atrazine and acetochlor. Hossain and Podder [158] proposed 3D-printed structures made from hollow core photonic crystal fibers to detect components in blood.
4.3 Biomedical Sensors
Many studies have been conducted to explore the capabilities of AM technology in biomedical applications such biochemical sensors, tactile sensors, bioelectronic probes, and microfluidic devices [48, 159,160,161]. During the past several decades, the general direction in which biomedical sensors tend to move is toward smaller devices with high functionality and elasticity near human tissue that can be customized based on customer needs [162]. The capability of additive manufacturing to produce miniature parts (even on nano/micro scale), integrate multi-materials seamlessly, and allow customization of parts using computer-aided design programs is driving the development of biomedical sensors [163,164,165]. The subsections below provide a review of the state of the art in biomedical sensors produced using additive manufacturing.
4.3.1 Fully 3D-printed Biomedical Sensors
A number of studies have reported fully 3D-printed sensors for use in biomedical applications. The bionic ear developed by Mannoor et al. [166] has clarified the capability of AM for fabricating bioelectronics and functional structures where conventional methods were limited in terms of integrating electronic components with biological cells; in their study, an extrusion-based additive manufacturing systems was used to build the hydrogel matrix in which cartilage tissue and a silver nanoparticle polymer were cultured. Yi et al. [167] introduced a patient-customized glioblastoma (GBM) tumor model fabricated by DIW using three inks (patient tumor cells, vascular cells, and silicone).
4.3.2 Hybrid 3D-printed Biomedical Sensors
Ali et al. [168] designed and fabricated a biosensor using an aerosol jet process to detect COVID-19 antibodies rapidly within a few seconds. The biosensing element, which consists of an array of micropillars, was fabricated using an aerosol containing gold micro-droplets. The micropillars were then coated with reduced graphene oxide and viral antigens. A sensing platform with a microfluidic device made of PDMS was then incorporated. Upon contact with the electrode surface, the antibodies selectively attach to antigens, causing a change in the impedance of the equivalent electrical circuit as captured by impedance spectroscopy. Figure 22 shows the fabrication process for the 3D-printed COVID-19 test chip. Figure 23 presents the setup showing a smartphone connected to a test chip by a USB-C connection, which allows the output signal to be read by the smartphone.
Manufacturing process of the 3D-printed COVID-19 test chip (3DcC). (a) A glass substrate forms the base for the electrodes. (b) Gold ink is aerosolized and printed via a CAD-controlled process. (c) A 10 × 10 gold micropillar array is formed. (d) Micropillars are built through layer-by-layer stacking. (e) A PDMS structure is created from a PMMA master mold. (f) The PDMS housing is assembled with the substrate to complete the device. (Reproduced with permission from [168].
Signal detection by a smartphone-based user interface (Reproduced with permission from [168].
Kim et al. [169] used a material extrusion-based method to fabricate a flexible wearable bioelectric patch for continuous and noninvasive analysis of electrolytes in human sweat. As shown in Fig. 24(a), the developed device consists of a PDMS substrate, wearable 3D-printed silver-based electrodes, a membrane, and a wearable-microfluidic sample handling unit. The performance of the device was evaluated by attaching the patch to the forearm with a band of double-sided adhesive and collecting measurements of levels of three ions (Ca2+, Na+, and K+), as shown in Fig. 24(b).
Diagram shows the components of the bioelectric patch (a) and the measurement of the Ca2 + , Na + , and K + levels in sweat using a bioelectric patch affixed to the forearm (b) (Reproduced from [169].
Click or tap here to enter text.Papadakis et al. [170] introduced a point-of-care platform to detect DNA from human samples (including blood, nasal swabs, and saliva), which is crucial for diagnosing infectious diseases. The housing was built by using the FFF method, and the platform incorporated an acoustic wave sensor.
5 Role of Additive Manufacturing in Sensor Development for Green Technology
The convergence of green technology with additive manufacturing has opened up new avenues for inventive developments in the search for sustainable solutions, especially in the field of eco-friendly technology. The application of additive manufacturing technology has emerged as a catalyst for good change as industries work to lower their carbon footprint and adopt eco-friendly practices. Precise customization and design optimization is one of 3D-printing’s inherent qualities. Conventional carbon electrodes have restricted shapes and are composed of glassy carbon or carbon fibers. Whereas 3D-printing of carbon electrodes offers more flexibility in shape and size [171]. Researchers have used 3D-printing to fabricate electrodes of different shape and size previously [36]. Furthermore, microlevel printing of sensing material (PLA/MWCNT) has allowed for precise production by printing complicated shapes like helices [24]. Having complex design on electrodes increases the applicability of any sensor. One area where additive manufacturing produces less waste than traditional manufacturing methods is sensor housing [50]. This aligns seamlessly with green technology, emphasizing sustainability though resource optimization [172]. Recyclable materials play a vital role in reducing waste in the applications of 3D-printing in sensor manufacturing. Pyrolysis of plastic and polymer degradation pose a significant environmental risk [173]. Although plastic is used for many household items, comparatively smaller amount of plastic waste is recycled [173]. Here, 3D-printing (FFF) plays a role in reducing plastic waste by manufacturing filaments from waste materials [173]. Recycled materials help to improve sustainability in manufacturing of sensors. Silva-Neto et al. [174] constructed a conductive paste using graphite flakes and ABS waste from AM. After being dissolved in acetone, the graphite particles were effectively added to the recycled thermoplastic composite. The mixture showed increased adhesion to various substrates, including cellulose, which allowed for the development of an electrochemical sensor (PES) based on paper. Similarly, Jain et al. [175] reported 3D-printing of primary recycled PVDF-based sensors. A low loss tangent (~ 0.003) and a dielectric constant of 3.3 are shown by the PVDF substrate, which was manufactured via fused filament fabrication. Promising lower C-band applications in additive manufacturing, the sensor has a return loss of about − 20 dB at 4.1 GHz and good conformability up to 70 mm bending. Although additive manufacturing is helping to improve sustainability, many of the sensors that are manufactured using this technology are made of non-biodegradable polymers such as PLA. There is ongoing research going on to reduce the use of PLA in sensors. Shergill et al. [176] studied an eco-friendly way to fabricate electro-chemical sensors. This study looks into how different degrees of infill material—carbon black (CB) and poly (lactic acid) (PLA)—affect the electrochemical performance of 3D-printed electrodes. The results show that there are no appreciable variations between electrodes with 30% and 100% infill in terms of anodic current, electron transfer kinetics, sensitivity, or dopamine detection limit. Notably, using 30% infill results in a 44% reduction in CB/PLA consumption, offering a sustainable method for creating 3D-printed electrochemical sensors that may have positive environmental effects.
6 Challenges and Limitations
Based on the studies included in this review, several challenges are observed that limit the scope of fully 3D-printed sensors. Table 1 provides a concise summary of the benefits and drawbacks associated with each additive manufacturing process. Overcoming these challenges may increase their applications in various fields. The limitations and challenges include the following:
Lack of multi-material systems
Sensors often require multi-material additive manufacturing systems. Sensors include a sensing element, electrodes, and insulating (or protecting) layers that need to be fabricated, and the literature shows that different materials are typically used for the sensing and insulating layers. For different types of sensors, it is observed that the sensing layers and/or the sensor housing parts are 3D-printed separately, and assembly of the sensor components is required. While additive manufacturing systems capable of multi-material printing can be used to fully print sensors, few additive manufacturing systems can fabricate multi-materials according to the sensor development requirements.
Lack of printability of materials
Material extrusion-based additive manufacturing processes are widely used to fabricate sensors. FFF systems only use filaments made from plastics (such as polylactic acid, acrylonitrile butadiene styrene, polyamide, polycarbonate), flexible materials (such as thermoplastic polyurethane, thermoplastic elastomer), composite materials, etc. But in current scenarios, sensors are typically made of multiple types of materials (for example, sensing materials may be made from polymers, while insulating materials or housing materials are made of plastic). As a result, researchers were required to adopt hybrid manufacturing techniques to produce a complete sensor. Even for fully 3D-printable sensors, printing with only one type of material may limit the performance of sensors. Moreover, many materials required for printing sensing layers are not optimized for additive manufacturing.
Sensor integration
Both hybrid manufactured or fully 3D-printed sensors need to be connected to electronic devices. However, there are no standardized procedures for connecting fully 3D-printed sensors to electronic device readouts. Interconnects between a sensor and external signal processing device are always problematic, where materials for interconnects are usually general wires which sometimes are not compatible with sensor materials.
7 Conclusion
This review provides information on both fully 3D-printed sensors and hybrid 3D-printed sensors, discusses the challenges in creating sensors, and its role in green technology. Several additive manufacturing techniques that have been used to fabricate sensors are highlighted. Commercial additive manufacturing systems often cannot fabricate the required sensing or sensor housing materials. Therefore, researchers have successfully adapted adequate customizations to fabricate sensors using additive manufacturing. However, commercially available additive manufacturing systems are used widely for hybrid-manufactured sensors. Several materials have been used to fabricate sensors (sensing material and housing), including hydrogels, photopolymers, polymers, metals, and ceramics. Material optimization plays a crucial role in sensor development. Finally, the sensors' mechanical, biomedical and chemical applications have been discussed. There has been a significant increase in the number of research papers regarding hybrid 3D-printed sensors in the last few years. However, this is an opportunity to find out why it was not possible in most cases to fully 3D-print the sensor. Addressing the correct issue will open doors to fully 3D-printed sensors. Generally, the effectiveness of fully 3D-printed, and hybrid-manufactured sensors are similar. However, hybrid 3D-printed sensors are missing out on the benefits of additive manufacturing processes. Additive manufacturing of functional materials (shape-changing materials) has opened several research opportunities in the field of sensors.
References
Han,T., Kundu, S., Nag, A., & Xu, Y. (2019). 3D printed sensors for biomedical applications: A review. Sensors (Switzerland), 19(7). MDPI AG. https://doi.org/10.3390/s19071706.
Taraba, M., Adamec, J., Danko, M., & Drgona, P. (2018). Utilization of modern sensors in autonomous vehicles. In: 12th International Conference ELEKTRO 2018, 2018 ELEKTRO Conference Proceedings, Institute of Electrical and Electronics Engineers Inc, 1–5. https://doi.org/10.1109/ELEKTRO.2018.8398279.
Berman, B. (2012). 3-D printing: The new industrial revolution. Business Horizons, 55(2), 155–162. https://doi.org/10.1016/j.bushor.2011.11.003
Lin, D., et al. (2014). Three-dimensional printing of complex structures: man made or toward nature? ACS Nanotechnology, 8. https://doi.org/10.1021/nn504894j.
ISO. (n.d.) ISO/ASTM 52900:2021(en) Additive manufacturing — General principles — Fundamentals and vocabulary [Internet].” Geneva:ISO. Accessed: Mar. 15, 2024. [Online]. Available: https://www.iso.org/standard/74514.html
Gibson, I., Rosen, D., Stucker, B., Khorasani, M. (2021). Introduction and Basic Principles. In: Additive Manufacturing Technologies. Springer, Cham. https://doi.org/10.1007/978-3-030-56127-7_1
Schouten, M., Wolterink, G., Dijkshoorn, A., Kosmas, D., Stramigioli, S., & Krijnen, G. (2021). A Review of extrusion-based 3D printing for the fabrication of electro- and biomechanical sensors. IEEE Sensors Journal Institute of Electrical and Electronics Engineers Inc, 21(11), 12900–12912. https://doi.org/10.1109/JSEN.2020.3042436
Stefano, J. S., et al. (2022). Electrochemical (Bio)sensors enabled by fused deposition modeling-based 3d printing: a guide to selecting designs, printing parameters, and post-treatment protocols. Analytical Chemistry, 94(17), 6417–6429. https://doi.org/10.1021/acs.analchem.1c05523
Rachim, V. P., & Park, S. (2021). Review of 3D-printing technologies for wearable and implantable bio-integrated sensors. Essays Biochem.
Kim, K., Park, J., Suh, J., Kim, M., Jeong, Y., & Park, I. (2017). 3D printing of multiaxial force sensors using carbon nanotube (CNT)/thermoplastic polyurethane (TPU) filaments. Sensors and Actuators, A: Physical, 263, 493–500. https://doi.org/10.1016/j.sna.2017.07.020
Venkateswaran, P. S., Sharma, A., Dubey, S., Agarwal, A., & Goel, S. (2016). Rapid and automated measurement of milk adulteration using a 3D printed optofluidic microviscometer (OMV). IEEE Sensors Journal, 16(9), 3000–3007. https://doi.org/10.1109/JSEN.2016.2527921
Hossain, M. S., et al. (2016). Fabrication of smart parts using powder bed fusion additive manufacturing technology. Additive Manufacturing, 10, 58–66. https://doi.org/10.1016/j.addma.2016.01.001
Hehr, A., et al. (2018). Integrating fiber optic strain sensors into metal using ultrasonic additive manufacturing. JOM Journal of the Minerals Metals and Materials Society, 70(3), 315–320. https://doi.org/10.1007/s11837-017-2709-8
Sauerbrunn, E., Chen, Y., Didion, J., Yu, M., Smela, E., & Bruck, H. (2015). Thermal imaging using polymer nanocomposite temperature sensors. Physica Status Solidi, (a):212. https://doi.org/10.1002/pssa.201532114.
Philamore, H., Rossiter, J., Walters, P., Winfield, J., & Ieropoulos, I. (2015). Cast and 3D printed ion exchange membranes for monolithic microbial fuel cell fabrication. Journal of Power Sources, 289, 91–99. https://doi.org/10.1016/j.jpowsour.2015.04.113
Ding, H., Zou, B., Wang, X., Liu, J., & Li, L. (2023). Microstructure, mechanical properties and machinability of 316L stainless steel fabricated by direct energy deposition. International Journal of Mechanical Sciences, 243, 108046. https://doi.org/10.1016/j.ijmecsci.2022.108046
Jiang, C., Lei, X., Chen, Y., Lv, S., Liu, X., & Zhang, P. (2022). Silicone rubber fabry-perot pressure sensor based on a spherical optical fiber end face. Sensors, 22(5), 1862. https://doi.org/10.3390/s22051862
Mamanpush, S. H., Li, H., Tabatabaei, B. T., & Englund, K. (2023). The impact of wood fibers in composite panels made from recycled fiberglass wind turbine blades. Waste Biomass Valorization. https://doi.org/10.1007/s12649-023-02038-2
Vatani, M., Engeberg, E. D., & Choi, J.-W. (2015). Conformal direct-print of piezoresistive polymer/nanocomposites for compliant multi-layer tactile sensors. Additive Manufacturing, 7, 73–82. https://doi.org/10.1016/j.addma.2014.12.009
Chaloeipote, G., Prathumwan, R., Subannajui, K., Wisitsoraat, A., & Wongchoosuk, C. (2021). 3D printed CuO semiconducting gas sensor for ammonia detection at room temperature. Materials Science in Semiconductor Processing, 123, 105546. https://doi.org/10.1016/j.mssp.2020.105546
Jayanth, N., & Senthil, P. (2019). Application of 3D printed ABS based conductive carbon black composite sensor in void fraction measurement. Compos B Engineering, 159, 224–230. https://doi.org/10.1016/j.compositesb.2018.09.097
Yin, X. Y., Zhang, Y., Cai, X., Guo, Q., Yang, J., & Wang, Z. L. (2019). 3D printing of ionic conductors for high-sensitivity wearable sensors. Materials Horizons, 6(4), 767–780. https://doi.org/10.1039/c8mh01398e
Haque, R. I., Ogam, E., Loussert, C., Benaben, P., & Boddaert, X. (2015). Fabrication of capacitive acoustic resonators combining 3D printing and 2D inkjet printing techniques. Sensors (Switzerland), 15(10), 26018–26038. https://doi.org/10.3390/s151026018
Guo, S. Z., Yang, X., Heuzey, M. C., & Therriault, D. (2015). 3D printing of a multifunctional nanocomposite helical liquid sensor. Nanoscale, 7(15), 6451–6456. https://doi.org/10.1039/c5nr00278h
Ragones, H., et al. (2015). Disposable electrochemical sensor prepared using 3D printing for cell and tissue diagnostics. Sensors and Actuators, B: Chemical, 216, 434–442. https://doi.org/10.1016/j.snb.2015.04.065
Laszczak, P., Jiang, L., Bader, D. L., Moser, D., & Zahedi, S. (2015). Development and validation of a 3D-printed interfacial stress sensor for prosthetic applications. Medical Engineering & Physics, 37(1), 132–137. https://doi.org/10.1016/j.medengphy.2014.10.002
Ni, Y., Ji, R., Long, K., Bu, T., Chen, K., & Zhuang, S. (2017). A review of 3D-printed sensorss. Applied Spectroscopy Reviews, 52(7), 623–652. https://doi.org/10.1080/05704928.2017.1287082. Taylor and Francis Inc.
Cardoso, R. M., et al. (2020). Additive-manufactured (3D-printed) electrochemical sensors: A critical review. Analytica Chimica Acta, 1118. Elsevier B.V. 73–91. https://doi.org/10.1016/j.aca.2020.03.028.
Xu, Y., et al. (2017). The Boom in 3D-printed sensor technology. Sensors (Basel, Switzerland), 17(5). NLM (Medline). https://doi.org/10.3390/s17051166.
Liu, H., et al. (2021) 3D Printed flexible strain sensors: from printing to devices and signals. Advanced Materials, 33(8). Wiley-VCH Verlag. https://doi.org/10.1002/adma.202004782.
Khosravani, M. R., & Reinicke, T. (2020). 3D-printed sensors: Current progress and future challenges. Sensors and Actuators, A: Physical, 305. Elsevier B.V., Apr. 15, 2020. https://doi.org/10.1016/j.sna.2020.111916.
He, S., Feng, S., Nag, A., Afsarimanesh, N., Han, T., & Mukhopadhyay, S. C. (2020). Recent progress in 3D printed mold-based sensors. Sensors (Switzerland), 20(3). MDPI AG. https://doi.org/10.3390/s20030703.
Jiang, Y., et al. (2022). Recent Advances in 3D Printed Sensors: Materials, Design, and Manufacturing. Advanced Materials Technology, 8, 2200492. https://doi.org/10.1002/admt.202200492
Hassan, M. S., et al. (2023). 3D Printed Integrated Sensors: From Fabrication to Applications-A Review. Nanomaterials, 13(24). https://doi.org/10.3390/nano13243148.
Guo, N., & Leu, M. C. (2013). Additive manufacturing: Technology, applications and research needs. Frontiers of Mechanical Engineering, 8(3), 215–243. https://doi.org/10.1007/s11465-013-0248-8
Emon, M. O. F., Alkadi, F., Philip, D. G., Kim, D.-H., Lee, K.-C., & Choi, J.-W. (2019). Multi-material 3D printing of a soft pressure sensor. Additive Manufacturing, 28, 629–638. https://doi.org/10.1016/j.addma.2019.06.001
Emon, O. F., Alkadi, F., Kiki, M., & Choi, J.-W. (2022). Conformal 3D printing of a polymeric tactile sensor. Additive Manufacturing Letters, 2, 100027. https://doi.org/10.1016/j.addlet.2022.100027
Huang, R., Urban, A., Jiao, D., Zhe, J., & Choi, J. W. (2022). Inductive proximity sensors within a ceramic package manufactured by material extrusion of binder-coated zirconia. Sensors Actuators A Physics, 338. https://doi.org/10.1016/j.sna.2022.113497.
Niu, X., Peng, S., Liu, L., Wen, W., & Sheng, P. (2007). Characterizing and patterning of PDMS-based conducting composites. Advanced Materials, 19(18), 2682–2686. https://doi.org/10.1002/adma.200602515
O’Neill, P. F., et al. (2014) Advances in three-dimensional rapid prototyping of microfluidic devices for biological applications. Biomicrofluidics, 8(5). https://doi.org/10.1063/1.4898632.
Aremu, A. O., et al. (2017). A voxel-based method of constructing and skinning conformal and functionally graded lattice structures suitable for additive manufacturing. Additive Manufacturing, 13, 1–13. https://doi.org/10.1016/j.addma.2016.10.006
Tofail, S. A. M., Koumoulos, E. P., Bandyopadhyay, A., Bose, S., O’Donoghue, L., & Charitidis, C. (2018). Additive manufacturing: scientific and technological challenges, market uptake and opportunities. Materials Today, 21(1):2–37. Elsevier B.V. https://doi.org/10.1016/j.mattod.2017.07.001.
Vilardell, A. M., et al., (2019). Topology optimization and characterization of Ti6Al4V ELI cellular lattice structures by laser powder bed fusion for biomedical applications. Materials Science and Engineering A, 766. https://doi.org/10.1016/j.msea.2019.138330.
Kadimisetty, K., et al. (2018). Fully 3D printed integrated reactor array for point-of-care molecular diagnostics. Biosensors & Bioelectronics, 109, 156–163. https://doi.org/10.1016/j.bios.2018.03.009
Zega, V., et al. (2018). The first 3-d-printed z-axis accelerometers with differential capacitive sensing. IEEE Sensors Journal, 18(1), 53–60. https://doi.org/10.1109/JSEN.2017.2768299
Li, X., Pan, X., Lu, J., Zhou, Y., & Gong, J. (2020). Dual-modal visual/photoelectrochemical all-in-one bioassay for rapid detection of AFP using 3D printed microreactor device. Biosensors and Bioelectronics, 158. https://doi.org/10.1016/j.bios.2020.112158.
Christ, J. F., Aliheidari, N., Pötschke, P., Ameli, A. (2019). Bidirectional and stretchable piezoresistive sensors enabled by multimaterial 3D printing of carbon nanotube/thermoplastic polyurethane nanocomposites. Polymers (Basel), 11(1). https://doi.org/10.3390/polym11010011.
Guo, S.-Z., Qiu, K., Meng, F., Park, S. H., & McAlpine, M. C. (2017). 3D Printed Stretchable Tactile Sensors. Advanced Materials, 29(27), 1701218. https://doi.org/10.1002/adma.201701218
Zhu, Z., Park, H. S., Mcalpine, M. C. (2020). Applied sciences and engineering 3D printed deformable sensors. Available: https://www.science.org
Katseli, V., Economou, A., & Kokkinos, C. (2021). Smartphone-Addressable 3D-Printed Electrochemical Ring for Nonenzymatic Self-Monitoring of Glucose in Human Sweat. Analytical Chemistry, 93(7), 3331–3336. https://doi.org/10.1021/acs.analchem.0c05057
Parate, K., et al. (2020). Aerosol-Jet-Printed Graphene Immunosensor for Label-Free Cytokine Monitoring in Serum. ACS Applied Materials & Interfaces, 12(7), 8592–8603. https://doi.org/10.1021/acsami.9b22183
Paulsen, J. A., Renn, M., Christenson, K., & Plourde, R. (2012). Printing conformal electronics on 3D structures with aerosol jet technology. In: FIIW 2012 - 2012 Future of Instrumentation International Workshop Proceedings, pp. 47–50. https://doi.org/10.1109/FIIW.2012.6378343.
Mojena-Medina, D., Hubl, M., Bäuscher, M., Jorcano, J. L., Ngo, H. D., & Acedo, P. (2020). Real-time impedance monitoring of epithelial cultures with inkjet-printed interdigitated-electrode sensors. Sensors (Switzerland), 20(19), 1–22. https://doi.org/10.3390/s20195711
Arshavsky-Graham, S., Enders, A., Ackerman, S., Bahnemann, J., & Segal, E. 3D-printed microfluidics integrated with optical nanostructured porous aptasensors for protein detection. https://doi.org/10.1007/s00604-021-04725-0/Published.
Faller, L.-M., Granig, W., Krivec, M., Abram, A., & Zangl, H. (2018). Rapid prototyping of force/pressure sensors using 3D- and inkjet-printing. Journal of Micromechanics and Microengineering, 28(10), 104002. https://doi.org/10.1088/1361-6439/aaadf4
Tabatabaei, B., Huang, R., & Choi, J. W. (2022). 3D Printing and Additive Manufacturing,” in Smart Manufacturing, A. Tarantino, Ed., Wiley, pp. 267–309. https://doi.org/10.1002/9781119846642.
Ambrosi, A., Moo, J. G. S., & Pumera, M. (2016). Helical 3D-printed metal electrodes as custom-shaped 3D platform for electrochemical devices. Advanced Functional Materials, 26(5), 698–703. https://doi.org/10.1002/adfm.201503902
Sharafeldin, M., Jones, A., & Rusling, J. F. (2018). 3D-printed biosensor arrays for medical diagnostics, Micromachines 9(8). MDPI AG. https://doi.org/10.3390/mi9080394.
Valentin, T. M., et al. (2017). Stereolithographic printing of ionically-crosslinked alginate hydrogels for degradable biomaterials and microfluidics. Lab on a Chip, 17(20), 3474–3488. https://doi.org/10.1039/c7lc00694b
Yin, X. Y., Zhang, Y., Xiao, J., Moorlag, C., & Yang J. (2019). Monolithic Dual-Material 3D Printing of Ionic Skins with Long-Term Performance Stability. Advanced Functions Materials 29(39). https://doi.org/10.1002/adfm.201904716.
Vatani, M., Lu, Y., Engeberg, E. D., & Choi, J. W. (2015). Combined 3D printing technologies and material for fabrication of tactile sensors. International Journal of Precision Engineering and Manufacturing, 16(7), 1375–1383. https://doi.org/10.1007/s12541-015-0181-3
MacDonald, E., et al. (2014). 3D printing for the rapid prototyping of structural electronics. IEEE Access, 2, 234–242. https://doi.org/10.1109/ACCESS.2014.2311810
Comina, G., Suska, A., & Filippini, D. (2015). Autonomous Chemical Sensing Interface for Universal Cell Phone Readout. Angewandte Chemie - International Edition, 54(30), 8708–8712. https://doi.org/10.1002/anie.201503727
Tiller B. et al. (2019). Piezoelectric microphone via a digital light processing 3D printing process. Materials Design 165. https://doi.org/10.1016/j.matdes.2019.107593.
Bauer, R., Stewart, G., Johnstone, W., Boyd, E., & Lengden, M. (2014). 3D-printed miniature gas cell for photoacoustic spectroscopy of trace gases. Optics Letters, 39(16), 4796. https://doi.org/10.1364/ol.39.004796
Wong, K. v., & Hernandez, A. (2012). A Review of Additive Manufacturing. ISRN Mechanical Engineering, 1–10. https://doi.org/10.5402/2012/208760.
Huang, S. H., Liu, P., Mokasdar, A., & Hou, L. (2013). Additive manufacturing and its societal impact: A literature review. International Journal of Advanced Manufacturing Technology, 67(5–8), 1191–1203. https://doi.org/10.1007/s00170-012-4558-5
Ngo, T. D., Kashani, A., Imbalzano, G., Nguyen, K. T. Q., & Hui, D. (2018). Additive manufacturing (3D printing): A review of materials, methods, applications and challenges. Composites Part B: Engineering, vol. 143. Elsevier Ltd, pp. 172–196. https://doi.org/10.1016/j.compositesb.2018.02.012.
Mohamed, O. A., Masood, S. H., & Bhowmik, J. L. (2015). Optimization of fused deposition modeling process parameters: A review of current research and future prospects. Advanced Manufacturing, 3(1), 42–53. https://doi.org/10.1007/s40436-014-0097-7
Chohan, J. S., Singh, R., Boparai, K. S., Penna, R., & Fraternali, F. (2017). Dimensional accuracy analysis of coupled fused deposition modeling and vapour smoothing operations for biomedical applications. Composites Part B Engineering, 117, 138–149. https://doi.org/10.1016/j.compositesb.2017.02.045
Ruan, X., et al. (2021). Nanomaterial-enhanced 3D-printed sensor platform for simultaneous detection of atrazine and acetochlor. Biosensors & Bioelectronics, 184, 113238. https://doi.org/10.1016/j.bios.2021.113238
Lei, Z., Wang, Q., & Wu, P. (Jul.2017). A multifunctional skin-like sensor based on a 3D printed thermo-responsive hydrogel. Materials Horizons, 4(4), 694–700. https://doi.org/10.1039/c7mh00262a
Valentine, A. D. et al. (2017). Hybrid 3D Printing of Soft Electronics. Advanced Materials, 29(40). https://doi.org/10.1002/adma.201703817.
Alapan, Y., Hasan, M. N., Shen, R., & Gurkan U. A. (2015). Three-Dimensional Printing Based Hybrid Manufacturing of Microfluidic Devices. Journal Nanotechnology Engineering Medicine 6(2). https://doi.org/10.1115/1.4031231.
Chen, J., et al. (2020). 3D printed microfluidic devices for circulating tumor cells (CTCs) isolation. Biosensors Bioelectronics, 150. https://doi.org/10.1016/j.bios.2019.111900.
Kimionis, J., Isakov, M., Koh, B. S., Georgiadis, A., & Tentzeris, M. M. (2015). 3D-Printed Origami Packaging with Inkjet-Printed Antennas for RF Harvesting Sensors. IEEE Transactions on Microwave Theory and Techniques, 63(12), 4521–4532. https://doi.org/10.1109/TMTT.2015.2494580
Rivadeneyra, A., Fernández-Salmerón, J., Agudo-Acemel, M., López-Villanueva, J. A., Palma, A. J., & Capitan-Vallvey, L. F. (2015). A printed capacitive-resistive double sensor for toluene and moisture sensing. Sensors and Actuators, B: Chemical, 210, 542–549. https://doi.org/10.1016/j.snb.2015.01.036
Dankoco, M. D., Tesfay, G. Y., Benevent, E., & Bendahan, M. (2016). Temperature sensor realized by inkjet printing process on flexible substrate. Materials Science and Engineering: B, 205, 1–5. https://doi.org/10.1016/j.mseb.2015.11.003
Khan, Y., et al. (2016). Flexible Hybrid Electronics: Direct Interfacing of Soft and Hard Electronics for Wearable Health Monitoring. Advanced Functional Materials, 26(47), 8764–8775. https://doi.org/10.1002/adfm.201603763
Utela, B., Storti, D., Anderson, R., & Ganter, M. (2008) A review of process development steps for new material systems in three dimensional printing (3DP). Journal of Manufacturing Processes, vol. 10, no. 2. Elsevier BV, pp. 96–104. https://doi.org/10.1016/j.jmapro.2009.03.002.
Amirkhani, S., Bagheri, R., & Zehtab Yazdi, A. (2012). Effect of pore geometry and loading direction on deformation mechanism of rapid prototyped scaffolds. Acta Materialis, 60(6–7), 2778–2789. https://doi.org/10.1016/j.actamat.2012.01.044.
Wang, X., Jiang, M., Zhou, Z., Gou, J., & Hui, D. (2017) 3D printing of polymer matrix composites: A review and prospective. Composites Part B: Engineering, vol. 110. Elsevier Ltd, pp. 442–458. https://doi.org/10.1016/j.compositesb.2016.11.034.
Achille, C., et al. (2021) 3D Printing of Monolithic Capillarity-Driven Microfluidic Devices for Diagnostics. Advanced Materials, 33(25). https://doi.org/10.1002/adma.202008712.
Sanchez, S., et al. (2021). Powder bed fusion of nickel-based superalloys: A review. International Journal of Machine Tools and Manufacture, 165, 103729. https://doi.org/10.1016/j.ijmachtools.2021.103729
Awad, A., Fina, F., Goyanes, A., Gaisford, S., & Basit, A. W. (2021). Advances in powder bed fusion 3D printing in drug delivery and healthcare. Advanced Drug Delivery Reviews, 174, 406–424. https://doi.org/10.1016/j.addr.2021.04.025
Distler, T., & Boccaccini, A. R. (2020). 3D printing of electrically conductive hydrogels for tissue engineering and biosensors – A review. Acta Biomaterialia, 101, 1–13. https://doi.org/10.1016/J.ACTBIO.2019.08.044
Woo, S., Kim, Y.-R., Chung, T. D., Piao, Y., & Kim, H. (2012). Synthesis of a graphene–carbon nanotube composite and its electrochemical sensing of hydrogen peroxide. Electrochimica Acta, 59, 509–514. https://doi.org/10.1016/j.electacta.2011.11.012
Emon, Md. O. F., Lee, J., Choi, U. H., Kim, D.-H., Lee, K.-C., & Choi, J.-W. (2019). Characterization of a soft pressure sensor on the basis of ionic liquid concentration and thickness of the piezoresistive layer. IEEE Sensors Journal, 19(15), 6076–6084. https://doi.org/10.1109/JSEN.2019.2911859
Zhao, W., et al. (2021). Vat photopolymerization 3D printing of advanced soft sensors and actuators: from architecture to function. Advanced Materials Technology, 6(8), 2001218. https://doi.org/10.1002/admt.202001218
Wang, L., Ding, T., & Wang, P. (2009). Thin flexible pressure sensor array based on carbon black/silicone rubber nanocomposite. IEEE Sensors Journal, 9(9), 1130–1135. https://doi.org/10.1109/JSEN.2009.2026467
Huang, P., Xia, Z., & Cui, S. (2018). 3D printing of carbon fiber-filled conductive silicon rubber. Materials and Design, 142, 11–21. https://doi.org/10.1016/j.matdes.2017.12.051
Lalmalsawmi, J., Tiwari, D., & Kim, D. J. (2020). Role of nanocomposite materials in the development of electrochemical sensors for arsenic: Past, present and future. Journal of Electroanalytical Chemistry, 877, 114630. https://doi.org/10.1016/j.jelechem.2020.114630
Sun, X., Agate, S., Salem, K. S., Lucia, L., & Pal, L. (2021). Hydrogel-based sensor networks: compositions, properties, and applications—a review. ACS Applied Biotechnology Materials, 4(1), 140–162. https://doi.org/10.1021/acsabm.0c01011
Jang, T.-S., Jung, H.-D., Pan, H. M., Han, W. T., Chen, S., & Song, J. (2018). 3D printing of hydrogel composite systems: Recent advances in technology for tissue engineering. International Journal of Bioprinting, 4(1). https://doi.org/10.18063/ijb.v4i1.126.
Chen, Z., et al. (2019). 3D Printing of Multifunctional Hydrogels. Advanced Functional Materials, 29(20), 1900971. https://doi.org/10.1002/adfm.201900971
Raj, S. A., Muthukumaran, E., & Jayakrishna, K. (2018). A Case Study of 3D Printed PLA and Its Mechanical Properties. Materials Today Proceedings, 5(5), 11219–11226. https://doi.org/10.1016/j.matpr.2018.01.146
Liu, Z., Wang, Y., Wu, B., Cui, C., Guo, Y., & Yan, C. (2019). A critical review of fused deposition modeling 3D printing technology in manufacturing polylactic acid parts. The International Journal of Advanced Manufacturing Technology, 102(9–12), 2877–2889. https://doi.org/10.1007/s00170-019-03332-x
Salim, A., Ghosh, S., & Lim, S. (2018). Low-cost and lightweight 3D-printed split-ring resonator for chemical sensing applications. Sensors, 18(9). https://doi.org/10.3390/s18093049.
Xin, Y., et al. (2016). The use of polyvinylidene fluoride (PVDF) films as sensors for vibration measurement: A brief review. Ferroelectrics, 502(1), 28–42. https://doi.org/10.1080/00150193.2016.1232582
Inderherbergh, J. (1991). Polyvinylidene fluoride (PVDF) Appearance, general properties and processing. Ferroelectrics, 115(4), 295–302. https://doi.org/10.1080/00150193.1991.11876614
Islam, M. N., et al. (2023). Boosting piezoelectricity by 3D printing PVDF-MoS2 composite as a conformal and high-sensitivity piezoelectric sensor. Advanced Functional Materials, 33(42). https://doi.org/10.1002/adfm.202302946.
Tang, Z., et al. (2020). A review on in situ monitoring technology for directed energy deposition of metals. The International Journal of Advanced Manufacturing Technology, 108(11–12), 3437–3463. https://doi.org/10.1007/s00170-020-05569-3
Petrie, C. M., Sridharan, N., Hehr, A., Norfolk, M., & Sheridan, J. (2019). High-temperature strain monitoring of stainless steel using fiber optics embedded in ultrasonically consolidated nickel layers∗. Smart Materials and Structures, 28(8), 85041. https://doi.org/10.1088/1361-665X/ab2a27
Chen, Z., et al. (2016). 3D printing of piezoelectric element for energy focusing and ultrasonic sensing. Nanotechnology Energy, 27, 78–86. https://doi.org/10.1016/j.nanoen.2016.06.048
Cochrane, C., & Cayla, A. (2013). Polymer-based resistive sensors for smart textiles. In Multidisciplinary Know-How for Smart-Textiles Developers, Elsevier, 2013, pp. 129–153. https://doi.org/10.1533/9780857093530.1.129.
Alkadi, F., Lee, K. C., Bashiri, A. H., & Choi, J. W. (2020). Conformal additive manufacturing using a direct-print process. Additive Manufacturing, 32, 100975. https://doi.org/10.1016/j.addma.2019.100975
Xia, T., et al. (2021). Ultrahigh sensitivity flexible pressure sensors based on 3D-printed hollow microstructures for electronic skins. Advanced Materials Technology, 6(3), 2000984. https://doi.org/10.1002/admt.202000984
Ragolia, M. A., Lanzolla, A. M. L., Percoco, G., Stano, G., & di Nisio, A. (2021). Thermal characterization of new 3D-printed bendable, coplanar capacitive sensors. Sensors, 21(19), 6324. https://doi.org/10.3390/s21196324
Xiao, T., Qian, C., Yin, R., Wang, K., Gao, Y., & Xuan, F. (2021). 3D printing of flexible strain sensor array based on UV-curable multiwalled carbon nanotube/elastomer composite. Advanced Materials Technology, 6(1), 2000745. https://doi.org/10.1002/admt.202000745
Yin, X., Zhang, Y., Xiao, J., Moorlag, C., & Yang, J. (2019). Monolithic dual-material 3D printing of ionic skins with long-term performance stability. Advanced Functional Materials, 29(39), 1904716. https://doi.org/10.1002/adfm.201904716
Tian, K., et al. (2017). 3D printing of transparent and conductive heterogeneous hydrogel-elastomer systems. Advanced Materials, 29(10), 1604827. https://doi.org/10.1002/adma.201604827
Tang, Z., Jia, S., Shi, X., Li, B., & Zhou, C. (2019). Coaxial printing of silicone elastomer composite fibers for stretchable and wearable piezoresistive sensors. Polymers (Basel), 11(4), 666. https://doi.org/10.3390/polym11040666
Pei, Z., Zhang, Q., Yang, K., Yuan, Z., Zhang, W., & Sang, S. (2021). A fully 3D-printed wearable piezoresistive strain and tactile sensing array for robot hand. Advanced Materials Technology, 6(7), 2100038. https://doi.org/10.1002/admt.202100038
Emon, M., & Choi, J. W. (2017). Flexible piezoresistive sensors embedded in 3d printed tires. Sensors, 17(3), 656. https://doi.org/10.3390/s17030656
Matsuzaki, R., & Todoroki, A. (2008). Wireless monitoring of automobile tires for intelligent tires. Sensors, 8(12), 8123–8138. https://doi.org/10.3390/s8128123
Shemelya, C., et al. (2015). Encapsulated copper wire and copper mesh capacitive sensing for 3-D printing applications. IEEE Sensors Journal, 15(2), 1280–1286. https://doi.org/10.1109/JSEN.2014.2356973
Alsharari, M., Chen, B., Shu, W. (2018). 3D Printing of highly stretchable and sensitive strain sensors using graphene based composites. In: Eurosensors 2018, Basel Switzerland: MDPI 792. https://doi.org/10.3390/proceedings2130792.
Nassar, H., Ntagios, M., Navaraj, W. T., & Dahiva, R. (2018). Multi-material 3D printed bendable smart sensing structures. IEEE, 2018, 1–4. https://doi.org/10.1109/ICSENS.2018.8589625
Wang, J., et al. (2019). Ultrasensitive wearable strain sensors of 3D printing tough and conductive hydrogels. Polymers (Basel), 11(11). https://doi.org/10.3390/polym11111873.
Saari, M., Xia, B., Cox, B., Krueger, P. S., Cohen, A. L., & Richer, E. (2016). Fabrication and analysis of a composite 3D printed capacitive force sensor. 3D Printing and Additive Manufacturing, 3(3):136–141. https://doi.org/10.1089/3dp.2016.0021.
Nag, A., Feng, S., Mukhopadhyay, S. C., Kosel, J., & Inglis, D. (2018). 3D printed mould-based graphite/PDMS sensor for low-force applications. Sensors and Actuators, A: Physical, 280, 525–534. https://doi.org/10.1016/j.sna.2018.08.028
Devaraj, H., Yellapantula, K., Stratta, M., McDaid, A., & Aw, K. (2019). Embedded piezoresistive pressure sensitive pillars from piezoresistive carbon black composites towards a soft large-strain compressive load sensor. Sensors and Actuators, A: Physical, 285, 645–651. https://doi.org/10.1016/j.sna.2018.12.006
Gao, Y., Xu, M., Yu, G., Tan, J., & Xuan, F. (2019). Extrusion printing of carbon nanotube-coated elastomer fiber with microstructures for flexible pressure sensors. Sensors and Actuators, A: Physical, 299, 111625. https://doi.org/10.1016/j.sna.2019.111625
Rahman, M. T., Rahimi, A., Gupta, S., & Panat, R. (2016). Microscale additive manufacturing and modeling of interdigitated capacitive touch sensors. Sensors and Actuators, A: Physical, 248, 94–103. https://doi.org/10.1016/j.sna.2016.07.014
Wickberg, A., Mueller, J. B., Mange, Y. J., Fischer, J., Nann, T., & Wegener, M. (2015). Three-dimensional micro-printing of temperature sensors based on up-conversion luminescence. Applied Physics Letters, 106(13), 133103. https://doi.org/10.1063/1.4916222
Bodnicki, M., Pakuła, P., Zowade, M. (2016). Miniature displacement sensor. pp. 313–318. https://doi.org/10.1007/978-3-319-23923-1_47.
van Tiem, J., Groenesteijn, J., Sanders, R., Krijnen, G., & “3D printed bio-inspired angular acceleration sensor”, in,. (2015). IEEE SENSORS. IEEE, Nov., 2015, 1–4. https://doi.org/10.1109/ICSENS.2015.7370543
Jeranče, N., Bednar, N., & Stojanović, G. (2013). An Ink-Jet Printed Eddy Current Position Sensor. Sensors, 13(4), 5205–5219. https://doi.org/10.3390/s130405205
Krkljes, D. B., & Stojanovic, G. M. (2016). An Ink-Jet Printed Capacitive Sensor for Angular Position/Velocity Measurements. Advances in Electrical and Computer Engineering, 16(4), 77–82. https://doi.org/10.4316/AECE.2016.04012
Cholleti, E., Stringer, J., Assadian, M., Battmann, V., Bowen, C., & Aw, K. (2018). Highly Stretchable Capacitive Sensor with Printed Carbon Black Electrodes on Barium Titanate Elastomer Composite. Sensors, 19(1), 42. https://doi.org/10.3390/s19010042
Barmpakos, D., Segkos, A., Tsamis, C., & Kaltsas, G. (2018). A disposable inkjet-printed humidity and temperature sensor fabricated on paper. In: EUROSENSORS 2018, Basel Switzerland: MDPI, p 977. https://doi.org/10.3390/proceedings2130977.
Hong, C., Zhang, Y., & Borana, L. (2019). Design, fabrication and testing of a 3D printed fbg pressure sensor. IEEE Access, 7, 38577–38583. https://doi.org/10.1109/ACCESS.2019.2905349
Hong, C., Yuan, Y., Yang, Y., Zhang, Y., & Abro, Z. A. (2019). A simple FBG pressure sensor fabricated using fused deposition modelling process. Sensors and Actuators, A: Physical, 285, 269–274. https://doi.org/10.1016/j.sna.2018.11.024
Lin, T. H. L. T. S. W. C. C. Y. (2016). Using three-dimensional printing technology to produce a novel optical fiber bragg grating pressure sensor. Sensors and Materials, 28(2016), 389–394.
Li, X., et al. (2017). Self-reinforcing graphene coatings on 3D printed elastomers for flexible radio frequency antennas and strain sensors. Flexible and Printed Electronics, 2(3), 035001. https://doi.org/10.1088/2058-8585/aa73c9
Maurizi, M., et al. (2019). Dynamic measurements using FDM 3D-printed embedded strain sensors. Sensors, 19(12), 2661. https://doi.org/10.3390/s19122661
Verma, A., Goos, R., de Weerdt, J., Pelgrims, P., & Ferraris, E. (2022). Design, fabrication, and testing of a fully 3D-printed pressure sensor using a hybrid printing approach. Sensors, 22(19), 7531. https://doi.org/10.3390/s22197531
Zega, V., et al. (2019). The first 3D-Printed and wet-metallized three-axis accelerometer with differential capacitive sensing. IEEE Sensors Journal, 1. https://doi.org/10.1109/JSEN.2019.2924473.
Ohashi, T., Dai, L. (2006). C60 and carbon nanotube sensors. Carbon Nanotechnology: Recent Developments in Chemistry, Physics, Materials Science and Device Applications, 525–575. https://doi.org/10.1016/B978-044451855-2/50018-8.
Hulanicki, A., Glab, S., & Ingman, F. (1991). Chemical sensors: definitions and classification. 63(9):1247–1250. https://doi.org/10.1351/pac199163091247.
Li, X., et al. (2019). 3D Printing of flexible liquid sensor based on swelling behavior of hydrogel with carbon nanotubes. Advanced Materials Technologies, 4(2). https://doi.org/10.1002/admt.201800476.
Wan, X., Zhang, F., Liu, Y., & Leng, J. (2019). CNT-based electro-responsive shape memory functionalized 3D printed nanocomposites for liquid sensors. Carbon N Y, 155, 77–87. https://doi.org/10.1016/j.carbon.2019.08.047
Naficy, S., Oveissi, F., Patrick, B., Schindeler, A., & Dehghani, F. (2018). Printed, flexible pH sensor hydrogels for wet environments. Advanced Materials Technologies, 3(11). https://doi.org/10.1002/admt.201800137.
Erkal, J. L., et al. (2014). 3D printed microfluidic devices with integrated versatile and reusable electrodes. Lab on a Chip, 14(12), 2023–2032. https://doi.org/10.1039/C4LC00171K
Bishop, G. W., Satterwhite-Warden, J. E., Bist, I., Chen, E., & Rusling, J. F. (2016). Electrochemiluminescence at bare and DNA-coated graphite electrodes in 3D-printed fluidic devices. ACS Sensors, 1(2), 197–202. https://doi.org/10.1021/acssensors.5b00156
Shallan, A. I., Smejkal, P., Corban, M., Guijt, R. M., & Breadmore, M. C. (2014). Cost-effective three-dimensional printing of visibly transparent microchips within minutes. Analytical Chemistry, 86(6), 3124–3130. https://doi.org/10.1021/ac4041857
Stefanov, B. I., Lebrun, D., Mattsson, A., & Granqvist, C. G. (2014). Demonstrating Online monitoring of air pollutant photodegradation in a 3D printed gas-phase photocatalysis reactor. https://doi.org/10.1021/ed500604e.
Kitson, P. J., Symes, M. D., Dragone, V., & Cronin, L. (n.d.). Combining 3D printing and liquid handling to produce user-friendly reactionware for chemical synthesis and purification †. https://doi.org/10.1039/c3sc51253c.
Gowers, S. A. N., et al. (2015) 3D Printed microfluidic device with integrated biosensors for online analysis of subcutaneous human microdialysate. https://doi.org/10.1021/acs.analchem.5b01353.
Hong, Y., et al. (2016). 3D Printed Microfluidic Device with Microporous Mn2O3-Modified Screen Printed Electrode for Real-Time Determination of Heavy Metal Ions. ACS Applied Materials & Interfaces, 8(48), 32940–32947. https://doi.org/10.1021/acsami.6b10464
Kit-Anan, W., et al. (2012). Disposable paper-based electrochemical sensor utilizing inkjet-printed Polyaniline modified screen-printed carbon electrode for Ascorbic acid detection. Journal of Electroanalytical Chemistry, 685, 72–78. https://doi.org/10.1016/j.jelechem.2012.08.039
Lu, W., Jing, G., Bian, X., Yu, H., & Cui, T. (2016). Micro catalytic methane sensors based on 3D quartz structures with cone-shaped cavities etched by high-resolution abrasive sand blasting. Sensors and Actuators, A: Physical, 242, 9–17. https://doi.org/10.1016/j.sna.2016.02.017
Hamzah, H., Lees, J., & Porch, A. (2018). Split ring resonator with optimised sensitivity for microfluidic sensing. Sensors and Actuators, A: Physical, 276, 1–10. https://doi.org/10.1016/j.sna.2018.03.023
Siebert, L., et al. (2019). 3D-Printed Chemiresistive Sensor Array on Nanowire CuO/Cu2O/Cu Heterojunction Nets. ACS Applied Materials & Interfaces, 11(28), 25508–25515. https://doi.org/10.1021/acsami.9b04385
Yoon, J.-W., Choi, J.-K., & Lee, J.-H. (2012). Design of a highly sensitive and selective C2H5OH sensor using p-type Co3O4 nanofibers. Sensors and Actuators, B: Chemical, 161(1), 570–577. https://doi.org/10.1016/j.snb.2011.11.002
Wan, X., Wang, J., Zhu, L., & Tang, J. (2014). Gas sensing properties of Cu2O and its particle size and morphology-dependent gas-detection sensitivity. Journal of Material Chemistry A, 2(33), 13641–13647. https://doi.org/10.1039/C4TA02659D
Bao, C., Kaur, M., & Kim, W. S. (2019). Toward a highly selective artificial saliva sensor using printed hybrid field effect transistors. Sensors and Actuators, B: Chemical, 285, 186–192. https://doi.org/10.1016/j.snb.2019.01.062
Hossain, Md. B., & Podder, E. (2019). Design and investigation of PCF-based blood components sensor in terahertz regime. Applied Physics A, 125(12), 861. https://doi.org/10.1007/s00339-019-3164-x
Shi, J., & Fang, Y. (2019). Flexible and implantable microelectrodes for chronically stable neural interfaces. Advanced Materials, 3(45). https://doi.org/10.1002/adma.201804895.
Tarantino, A. (2022). Smart Manufacturing. Wiley. https://doi.org/10.1002/9781119846642
Ali, M. A., Tabassum, S., Wang, Q., Wang, Y., Kumar, R., & Dong, L. (2018). Integrated dual-modality microfluidic sensor for biomarker detection using lithographic plasmonic crystal. Lab on a Chip, 18(5), 803–817. https://doi.org/10.1039/c7lc01211j
Mahajan, R., et al. (2019). Embedded Multidie Interconnect Bridge - A Localized, High-Density Multichip Packaging Interconnect. IEEE Trans Compon Packaging Manufacturing Technology, 9(10), 1952–1962. https://doi.org/10.1109/TCPMT.2019.2942708
Paterson, A. M., Donnison, E., Bibb, R. J., & Ian Campbell, R. (2014). Computer-aided design to support fabrication of wrist splints using 3D printing: A feasibility study. Hand Therapy, 9(4). https://doi.org/10.1177/1758998314544802.
Khare, V., Sonkaria, S., Lee, G.-Y., Ahn, S.-H., & Chu, W.-S. (2017). From 3D to 4D printing – design, material and fabrication for multi-functional multi-materials. International Journal of Precision Engineering and Manufacturing-Green Technology, 4(3), 291–299. https://doi.org/10.1007/s40684-017-0035-9
Ali, M. A., Hu, C., Yttri, E. A., & Panat, R. (2022) Recent advances in 3D printing of biomedical sensing devices. Advanced Functional Materials, 32(9). John Wiley and Sons Inc. https://doi.org/10.1002/adfm.202107671.
Mannoor, M. S., et al. (2013). 3D Printed Bionic Ears. Nanotechnolgy Letters, 13(6), 2634–2639. https://doi.org/10.1021/nl4007744
Yi, H. G., et al. (2019). A bioprinted human-glioblastoma-on-a-chip for the identification of patient-specific responses to chemoradiotherapy. Nature Biomedical Engineering, 3(7), 509–519. https://doi.org/10.1038/s41551-019-0363-x
Ali, M. A., et al. (2021). Sensing of COVID-19 antibodies in seconds via aerosol jet nanoprinted reduced-graphene-oxide-coated 3D electrodes. Advanced Materials, 33(7). https://doi.org/10.1002/adma.202006647.
Kim, T., Yi, Q., Hoang, E., & Esfandyarpour, R. (2021). A 3D printed wearable bioelectronic patch for multi-sensing and in situ sweat electrolyte monitoring. Advanced Materials Technologies, 6(4). https://doi.org/10.1002/admt.202001021.
Papadakis, G., et al. (2019). 3D-printed Point-of-Care Platform for Genetic Testing of Infectious Diseases Directly in Human Samples Using Acoustic Sensors and a Smartphone. ACS Sensors, 4(5), 1329–1336. https://doi.org/10.1021/acssensors.9b00264
Chang, Y., Cao, Q., & Venton, B. J. (2023). 3D printing for customized carbon electrodes. Current Opinion in Electrochemistry, 38, 101228. https://doi.org/10.1016/j.coelec.2023.101228
Sadollah, A., Nasir, M., & Geem, Z. W. (2020). Sustainability and optimization: from conceptual fundamentals to applications. Sustainability, 12(5). https://doi.org/10.3390/su12052027.
Madhu, N. R., Erfani, H., Jadoun, S., Amir, M., Thiagarajan, Y., & Chauhan, N. P. S. (2022). Fused deposition modelling approach using 3D printing and recycled industrial materials for a sustainable environment: A review. The International Journal of Advanced Manufacturing Technology, 122(5), 2125–2138. https://doi.org/10.1007/s00170-022-10048-y
Silva-Neto, H. A., Duarte-Junior, G. F., Rocha, D. S., Bedioui, F., Varenne, A., & Coltro, W. K. T. (2023). Recycling 3D Printed Residues for the Development of Disposable Paper-Based Electrochemical Sensors. ACS Applied Materials & Interfaces, 15(11), 14111–14121. https://doi.org/10.1021/acsami.3c00370
Jain, C., Dhaliwal, B. S., & Singh, R. (2023). On 3D Printing of Primary Recycled Polyvinylidene-Fluoride-Based Miniaturized, Flexible, and Wearable Sensor. Journal of Materials Engineering and Performance, 32(24), 11381–11392. https://doi.org/10.1007/s11665-023-07911-8
Shergill, R. S., Bhatia, P., Johnstone, L., & Patel, B. A. (2024). Eco-Friendly Approach to Making 3D-Printed Electrochemical Sensors. ACS Sustainable Chemistry & Engineering, 12(1), 416–422. https://doi.org/10.1021/acssuschemeng.3c06200
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest Statement
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Hossain, M.J., Tabatabaei, B.T., Kiki, M. et al. Additive Manufacturing of Sensors: A Comprehensive Review. Int. J. of Precis. Eng. and Manuf.-Green Tech. (2024). https://doi.org/10.1007/s40684-024-00629-5
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1007/s40684-024-00629-5