1 Introduction

Molecular modelling concepts are frequently utilized to investigate the studied structures on the molecular gaseous state. The constructed computational model aims also to boost the resulting experimental data on theoretical basis as it can investigate both physical and biological characteristics of the structures under investigation depending on computer software packages which are always able to offer valuable data in many interdisciplinary fields of science (Abdel-Karim et al. 2020; Morsy et al. 2020; Refaat et al. 2020). Not only do computational models play significant roles when the experimental work is inaccessible, but they can present also logic explanations for the already running infield work depending on theoretical aspects (Ezzat et al. 2019; Ibrahim et al. 2019). Conducting geometry optimization calculations is of great deal in describing chemical, physical and electronic features as well as quantifying geometrical parameters of chemical structures (Bayoumy et al. 2019). For example, having quantitative data of energy state enables researchers to assess structures’ stability and the favourable conditions for their formulation from their proposed candidates as well (El-Naggar et al. 2021). Furthermore, the calculated dipole moment plays a significant role in evaluating the reactivity of such structures (Ibrahim et al. 2011; Ibrahim and Mahmoud 2009; Sabry et al. 2018). HOMO/LUMO bandgap energy can offer a quantitative description of the electrical conductivity of chemical structures, since it represents the electron transfer processes from valence band to conduction one (El-Sayed et al. 2021). In addition, quantitative structure-activity relationship (QSAR) parameters are usually calculated for the optimized structures to investigate some of their physical and electronic features related to biological applications (Bulat et al. 2010; Fahim et al. 2019; Saleh et al. 2017). They frequently offer a positive promising way for investigating the chemical structures because they present a simple strategy for anticipating their biological reactivity.

Utilization of biopolymers and/or their derivatives has become a worldwide trend in the scientific community as they own several merits, such as being renewable materials, easy to be processed, cost effectiveness, eco-friendly and their promising potential for biological applications as well as industrial ones. Chitosan is always considered the second most abundant polymer in our planet after cellulose (Ali et al. 2012; Bayoumy et al. 2020b). It is the main derivative of chitin biopolymer which presents in the exoskeleton of crustaceans, crabs, shrimps…etc (El Knidri et al. 2018). A deacetylation process of chitin is frequently carried out to produce chitosan from chitin (Rivero et al. 2010; Tănase et al. 2014). It is well-known by its biocompatibility, biodegradability, being economically, and has a great ability to form composites with wide range of both natural and synthetic structures due to its various functional groups (Suginta et al. 2013). It owns both antibacterial and antimicrobial activities, as well (Jarmila and Eva 2011). Hence, it has been emerged in multiple applications (Aljawish et al. 2016; Rinaudo 2006), including biomedical as a drug delivery carrier (Agnihotri et al. 2004; Kim et al. 2006; Sabnis and Block 2000; Zhang et al. 2015), agricultural (Hadwiger 2013), and electrochemical applications (Hassan et al. 2014a). However, it has quite low conductivity. Like chitosan, carboxymethyl cellulose (CMC) is one of the common derivatives of cellulose biopolymer. It is formed by replacing the hydrogen atom in cellulose by a carboxymethyl group instead in order to be soluble in water. Due to its ease in processing and its viscous nature, it has been extensively enrolled in different appliances including 3D biocompatible scaffolds (Chen and Fan 2007; Singh et al. 2016), tissue engineering (Chen et al. 2020; Mohan et al. 2020; Verma et al. 2021; Zheng et al. 2021), bone-grafting implants (Matinfar et al. 2019; Sarkar et al. 2020; Sharmila et al. 2020) and wound healing dressings (Koneru et al. 2020; Sadeghi et al. 2020; Saladino et al. 2020). Contrary to chitosan, CMC has higher electrical conductivity, hence many reports have been published for its usage in enhancing electrical conductivity of various structures. For example, it was blended with polyaniline conducting polymer in order to enhance its electrical conductivity for biosensing applications (Basavaraja et al. 2012). CMC was reported to enhance conductivity as well as thermal stability of the formulated blends in high temperatures up to 500 K. Furthermore, CMC was emerged in the fabrication of Li-ion batteries (LIBs) (Lee and Oh 2013) due to its high viscosity to act as a binder to the active ingredients of anode. A composite was formulated of Li4Ti5O12 (LTO) and CMC to enhance its overall performance where it could support the binding affinity between LTOs as well as boost their ion conductivity.

Recently, nanotechnology is one of the uprising research trends. It always provides magic clues to control the preparation procedures of different chemical structures and manage their physicochemical features, as well (Bayoumy et al. 2020a). Hence, preparation of nanomaterials has become the first choice for numerous researchers, and it has been the main concern in many recent advanced applications (Maruyama et al. 2003; Ferreira et al. 2019). Not only do scientists concentrate on boosting preparation and characterization techniques of these nanomaterials, but they focus also on proposing the theories that can describe the interaction between chemical structures on this small scale (Thiruvengadam et al. 2018; Bayoumy et al. 2020b). Hence, various scientific publications have reported the utilization of nanomaterials in wide range of applications including medical and clinical applications (Singh and Amiji 2022; Phillips and Mousa 2022), environmental (Di Tinno et al. 2022; Nitschke and Marangon 2022), and sensing/biosensing ones (Sohrabi et al. 2022; Cancelliere et al. 2021). Carbon-based nanosized structures always succeed in surprising researchers due to their salient features for interdisciplinary fields. Such large category includes carbon nanotubes (CNTs) (Sakki et al. 2022), graphene (Hadad et al. 2021), fullerenes (Waite et al. 2021) and nano-diamonds (Mydlova et al. 2022). Graphene is frequently used in various applications due to its unique physicochemical features, such as electrical conductivity, flexibility, ease of functionalization…etc (Gamil et al. 2014). Therefore, it has been emerged in several electrochemical applications (Hassan et al. 2014b; Rashed and El-Moneim 2017). Therefore, to enhance the electrical conductivity of both chitosan and CMC polymers, some modifications need to be carried out. Several materials were reported to form composites with them, such as conducting polymers (polyaniline, polypyrrole) and carbonaceous materials (graphene, CNTs and GO). Such composites are urgently needed for various bio-electronic products. For example, a composite ink was formulated of chitosan, graphite and glycerol for printing conductive electrodes for biosensing uric acid (Camargo et al. 2022). In addition, graphene-chitosan composite was utilized to immobilize glucose oxidase enzyme (Kang et al. 2009). It was employed to detect glucose biomolecule with high accuracy. On the same manner, a bending sensor was fabricated of graphene-CMC composite (Liu et al. 2020). It was useful in detecting strains for wearable devices.

Regarding the fabrication technique, additive manufacturing (AM) or solid freeform (SFF) techniques have been intensively investigated in the fabrication procedures of the various components of electronic and bio-electronic devices in microscale and even in nanoscale (Zhu et al. 2016; Wei et al. 2017). Specifically, InkJet printing (IJP) is always considered one of the most utilized techniques in the manufacturing of flexible electronics (Pinto et al. 2022). This can be related to the ease of its processing steps where it only requires the homogenous dispersion of the effective material in the proper solvent media in order to have an ink formulation with the optimum rheological characteristics (Sajedi-Moghaddam et al. 2020). In addition, IJP has various salient features including its high-resolution capabilities to print elements in both 2D as well as 3D manner (Choi et al. 2016), its low cost, being template-free technique and its drop-on-demand nature, which makes it wastes the least amount of the active material. This attitude makes it the first choice for researchers when asking for an eco-friendly fabrication technique (Singh et al. 2010; Hutchings and Martin 2012).

This work aimed to investigate the feasibility of modifying two biopolymers (chitosan and CMC) by their interaction with graphene to formulate potential biocomposite formulations for bio-electronic applications. The study was based mainly on a computational molecular model calculated via semiemprical quantum mechanical calculations. Then, it was supported by an experimental setup including printing a simple electrode of each biocomposite ink via InkJet printing technique and measuring their sheet resistance as well as charge mobility via Hall Effect measurement.

2 Calculation details

Structures were built up and their geometries were optimized using semiemprical quantum mechanical calculations at PM6 method (Stewart 2007) utilizing SCIGRESS 3.0 software that is executed at Spectroscopy Department, Physics Division, National Research Centre, NRC (Stewart 2009). Some physical and electronic features were extracted, such as total energy (E), total dipole moment (TDM), HOMO/LUMO bandgap energy (\(\varDelta\)E). Then, these optimized structures were utilized to calculate quantitative structure-activity relationship (QSAR) descriptors, such as charge, final heat of formation (FF), ionization potential (IP), Log P, molar refractivity (MR), molecular weight (Mwt) and polarizability (P).

3 Experimental section

3.1 Materials

Graphite (Fisher; general purpose grade, MW: 12.01 g/mol.), Sodium Citrate (Fisher, Anhydrous, Powder, 99-100.5%), Chitosan (ACROS ORGANIC; MW: 100,000-300,000 g/mol, (C6H11NO4)n), CMC (Sodium Salt, ACROS ORGANIC; MW: 250,000 g/mol), Ethanol (Fisher; absolute, 99.8% HPLC grade), Ultrapure water (Resistivity of > 18 MΩ.cm). All received chemicals were used without additional purification.

3.2 Graphene/Biopolymer ink formulation

The formulation steps of graphene-biopolymer ink composites have recently published in Bayoumy et al. 2023. In brief, the graphite powder was mechanically exfoliated in first via ball mill technique in order to get mechanically exfoliated graphene powder. The milling process was conducted in the presence of sodium citrate as a milling agent. Secondly, the resulting powder was rinsed numerous times with ultrapure water to get rid of any unnecessary ions (such as Na ions). Then, graphene was dispersed in a mixture of water and ethanol and probe sonicated for two hours to boost its dispersion. Individually, solutions of Cs and CMC were prepared and then mixed with graphene dispersion with 1:3 v/v ratio.

3.3 Microdrop InkJet printing of G-Cs and G-CMC biocomposites

The printing process was conducted via a microdrop InkJet printer (Autodrop Professional System; Microdrop Technologies GmbH, Norderstedt, Germany). One simple electrode was printed for each prepared sample in order to compare their electrical properties and investigate the effect of modifying Cs and CMC biopolymers with graphene structure.

3.4 Sheet resistance and charge mobility measurements

The sheet resistance of the printed electrodes of the G-Cs and G-CMC composites was measured utilizing four-point probe technique via Ossila Four-Point Probe System at 2D and 3D Printing Lab, Graphene Center of Excellence for Energy and Electronic Applications (GCEE), Egypt-Japan University of Science and Technology (E-JUST). Besides, the charge mobility in the printed samples was measured via Hall-effect using Ecopia 7000 in Energy Materials Lab, E-JUST.

4 Results and discussion

4.1 Building Model Molecules

A modified graphene monolayer structure with two hydroxyl and two carboxyl groups (G) was built up. A monomer structure of Cs and CMC biopolymers were constructed. Cs structure has four functional groups (three OH and one NH2 groups), while CMC contains four OH groups and one terminal sodium atom. Figure 1(a, b and c) demonstrates the model molecules of the three proposed candidates. Then, G is chosen to modify the structure of these biopolymers in order to enhance their electrical features for bio-electronic applications. Therefore, four interaction probabilities were suggested for each composite structure. For example, chitosan could interact with G through physical interactions between its OH group and both OH and COOH of G. Other two possibilities could occur between Cs amine group and OH and COOH ones of G, as illustrated in Fig. 1(d, e, f and g). On the same manner, CMC with its OH and terminal Na active sites could interact with the OH and COOH ones of G, as shown in Fig. 1(h, i, j and k). Designing the computational model based on single layer of graphene and monomers of the biopolymer candidates always proves its feasibility to represent somehow the experimental work (Abdel-Karim et al. 2021; Bayoumy et al. 2020b; El-Naggar et al. 2021). This is frequently conducted in order to make the calculations much easier and represent an indicator for the planned work either via higher theoretical models or even experimentally.

Fig. 1
figure 1

Model molecules of (a) graphene (G), (b) chitosan (Cs), (c) CMC, (d) G(COOH)-Cs(NH2), (e) G(COOH)-Cs(OH), (f) G(OH)-Cs(NH2), (g) G(OH)-Cs(OH), (h) G(COOH)-CMC(OH), (i) G(COOH)-CMC(Na), (j) G(OH)-CMC(OH), (k) G(OH)-CMC(Na) calculated at PM6 level. [C in grey, H in white, O in red, Na in violet and N in blue]

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4.2 Calculated physical parameters

The chemical structures and their proposed interactions were geometrically optimized at PM6 level of theory. Some electronic and physical parameters were extracted from the optimized files, such as total energy (E), TDM and HOMO/LUMO bandgap energy (∆E) as listed in Table 1.

Table 1 Calculated total energy (E) as kcal/mol, total dipole moment (TDM) as Debye and HOMO/LUMO bandgap energy (∆E) as eV for G, Cs, CMC and their interaction possibilities at PM6 theoretical level
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The listed parameters in Table 1 include total energy, dipole moment and bandgap energy that offer valuable information about the stability, reactivity and electrical conductivity of the investigated structures and their proposed interactions; respectively. Here, a comparison was made between two formulations of graphene composites with biopolymers (Cs and CMC) in order to investigate the most suitable one for bio-electronic applications in biological entities. Regarding stability of the studied structures, the calculated energy can present considerable indication of such important side. Resulting energy of G, Cs and CMC are − 248944.799, -70857.321 and − 104404.98 kcal/mol; respectively referring to highly stable structures. The calculated energy of the proposed eight interactions reflect that the interaction site plays no significant role in the resulting energy values where all the computed energy data for the G-Cs composites are nearly the same. Likewise, all the resulting data are almost the same for all the G-CMC possibilities. The calculated energies for the G-Cs composites are about − 319,795 kcal/mol and they are roughly − 353,609 kcal/mol for the G-CMC ones. It is obvious that the resulting energy for the G-CMC interactions are quite lower than those for the G-Cs ones which indicates quite higher stability for the former group.

Turning to reactivity, TDM is always utilized as one of the considerable physical parameters for reactivity of chemical structures. Modification of graphene enhances the chemical reactivity of the resulting graphene structure with 5.006 Debye. TDM results of chitosan and CMC are 2.875 and 6.861 Debye; respectively ensuring that CMC monomer has much higher reactivity than chitosan one. This can be attributed to the presence of an extra OH group and a terminal alkali metal (Na atom) in CMC than chitosan structure. Therefore, the G-CMC composites have higher TDM results than those for G-Cs ones. TDM data of the G-Cs interactions range from 4.886 to 6.254 Debye. The most reactive interaction between G and Cs occurs between the most reactive functional groups of both structures (NH2 of Cs and COOH of G) which ensures their ability to rise the reactivity of the formulated structure. However, TDM values of the G-CMC composites starts from 5.59 and ends at 12.963 Debye for G(OH)-CMC(OH) interaction probability. These high results are reasonable since both G and CMC show high reactivity in their individual forms. On contrary to the calculated energy, the proposed active site for interaction has a significant part in determining the TDM and hence the reactivity of the resulting structures.

The calculated HOMO/LUMO bandgap energy reflects the required energy for transferring an electron from the valence band to the conduction one transferring a chemical substance from the ground state to the excited one to be more electrically conductive. It is always considered to describe one of the electronic features of the studied chemical structures on a theoretical basis. Chitosan and CMC biopolymers have values of 10.865 and 9.615 eV, respectively. The resulting bandgap values of these structures ensure their low electrical conductivity; hence graphene was chosen, for its unique electrical features, to enhance such poor behaviour. As previously expected, modification of Cs and CMC with graphene has a significant positive impact on their electrical features where their bandgap decreases to more than the half of their original results (~ 4.4 eV). G(COOH)-CMC(OH) interaction probability has the lowest calculated bandgap value indicating a much easier way for electron transfer from valence to conduction band, hence a structure with the highest conductivity with respect to others. Its calculated bandgap is 4.358 eV. Hence, their interactions with graphene boost their potential for emerging in bio-electronic applications. Since the resulting bandgap data are quite similar to each other, a further experimental study is required to differentiate between the two biocomposites on a real infield scale. Therefore, an experimental section was extended in the following sections.

4.3 Calculated QSAR descriptors

Quantitative structure-activity relationship (QSAR) parameters are usually computed as one of the promising computational methods in assessing various chemical entities having biological applications. This can be attributed to that they are characterized by being simple and easy to be accessible for researchers to predict biological activity of structures under investigation. That is why they always success in being the main focus of several latest articles (Bayoumy et al. 2020a; El-Sayed et al. 2018; Ma et al. 2019; Muthukumaran and Rajiniraja 2019; Omar et al. 2022). Table 2 presents some of the calculated QSAR descriptors, such as total charge (C), final heat of formation (FF), ionization potential (IP), Log P, molar refractivity (MR), molecular weight (Mwt) and polarizability (P) for structures under study at PM6 level.

Table 2 QSAR parameters including final heat of formation (FF) as kcal/mol, ionization potential (IP) as eV, Log P and molar refractivity (MR), molecular weight (Mwt) as a.u. and polarizability (P) as A3 for G, Cs, CMC and their interaction possibilities at PM6 theoretical level
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The calculated total charge of all the proposed chemical structures is zero since they are all in the ground state. The second considered QSAR descriptor is final heat of formation (FF) which is the amount of heat either released or absorbed as a result of chemical structure formation (Elhaes et al. 2014). FF of G, Cs and CMC are calculated to be 8.205, -231.267 and − 399.309 kcal/mol. The computed FF of all the proposed interactions is of negative sign referring to exothermal reactions which are spontaneous and thermodynamically favourable. Similar to the the calculated total energy, FF is not affected significantly by the active site of interaction in either G-Cs or G-CMC composites. FF values of the G-Cs range from − 227.413 to -236.336 kcal/mol, while they start from − 416.822 to -453.521 kcal/mol for the G-CMC ones. Releasing more energy for the G-CMC composites than those for the other group, ensuring the ease of their formation relative to the latter group. After that, ionization potential (IP) is presented as the amount of energy needed for ejecting an electron from the outermost shell of a chemical structure and its conversion from a stable structure to a reactive one. IP data are − 7.222, -10.047 and − 9.454 eV for G, Cs and CMC; respectively. G addition to either Cs or CMC has no substantial impact on its IP. Table 2 confirms that all the calculated IP values are nearly equal to that of G ranging from − 7.04 to -7.444 eV. These results are like that of bandgap energies listed in Table 1. Regarding the behaviour of chemical structures in either aqueous or organic solvents, Log P or partition coefficient descriptor is considered as one of the most potential parameters. It is the ratio between the substance amount dissolved in organic solvent to that in aqueous one. Hence, its negative result reflects hydrophilic structure and vice versa. High positive Log P value for G structure indicates its high hydrophobic nature (10.593) while negative ones for the selected biopolymers reflect their hydrophilicity (-2.108 for Cs and − 2.076 for CMC). Addition of G to either Cs or CMC decreases its hydrophobicity to a small extent with 8.485 for the G-Cs and 8.517 for G-CMC. Furthermore, the site of interaction has no role on the calculated Log P values. Molar reflectivity (MR) is always considered among QSAR parameters. It is 235.031 for G structure and 37.581 and 55.651 for Cs and CMC; respectively. The calculated MR values equal 272.612 for all G-Cs composites and 290.683 for G-CMC ones. Then, molecular weight (Mwt) values are listed in Table 2. It is 786.739 a.u. for G, 179.171 a.u. for Cs and 288.227 a.u. for CMC. They are 965.91 and 1074.965 a.u. for the G-Cs and G-CMC; respectively. Finally, polarizability (P) is considered to reflect the ease of a substance to be polarized as a result of its exposure to an external field. It equals 134.666 A3 for G, 10.167 and 15.585 A3 for Cs and CMC; respectively. It ranges from 147.2 to 148.334 A3 for the G-Cs structures and from 146.86 to 154.997 A3 for G-CMC ones.

4.4 Measured electrodes resistance and charge carrier mobility

The formulated G-biopolymer ink formulations were utilized in an experimental setup via a microdrop InkJet printer. Printing parameters were optimized in order to print continuous and homogenous patterns as the illustrated example in figure S1. It was used to print a sixty-layer simple electrode of both biocomposite inks in order to have a simple electrode of both. Then, some electrical features were measured to evaluate the formulated biocomposites. Sheet resistance of both G-Cs and G-CMC printed electrodes was measured via four-point probe technique. In addition, Hall Effect measurement was utilized to determine the charge mobility in both electrodes. Figure 2 demonstrates the resulting sheet resistance and charge mobility data of both G-Cs and G-CMC electrodes.

Fig. 2
figure 2

Comparison of sheet resistance (kΩ/Sq.) and charge mobility (cm2/V.s) of the G-Cs and G-CMC printed simple electrodes

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Sheet resistance is one of the electrical measurements that can be utilized as an indicator for the electrical conductivity of the investigated samples. It refers to the impedance facing the electrons to flow through them. Likewise, charge mobility is another indicator for the ability of electrons to stream and the ease of their movement. Figure 2 illustrates that the measured sheet resistance of the G-Cs printed electrode is about five times higher than that of the G-CMC one. It is 6.8 ± 0.0624 kΩ/Sq. for the G-Cs while it is only 1.457 ± 0.0124 kΩ/Sq. for the other. Such result was confirmed by the measured Hall Effect test which showed that the charge mobility in the G-CMC electrode equals 24.8 cm2/V.s which is much greater than that in G-Cs one (1.3 cm2/V.s). This may refer to that CMC could emerge between graphene layers to a much more extent than Cs does reducing the graphene inter-sheet separation reducing G-CMC electrode resistance for electrons flow enhancing its electrical features (Rahman et al. 2020). These experimental results confirm the resulting theoretical data of the proposed model. Both parts agree that the G-CMC biocomposite has much more electrical conductivity than G-Cs one. Such results propose that the G-CMC biocomposite can be considered as a potential candidate for bio-electronic applications.

5 Conclusion

In conclusion, molecular modelling concepts were utilized for investigating the interaction of chitosan and carboxymethyl cellulose biopolymers with a monolayer of graphene. Geometry optimization calculations were carried out using PM6 method. Results illustrate that all interactions are stable, but the interaction site plays no role in determining the resulting energy values. The calculated energies for the G-Cs interactions are quite higher than those for the G-CMC ones indicating quite lower stability. The calculated QSAR parameters show that the addition of these biopolymers to the graphene structure lowers its hydrophobicity. On contrary to the calculated energy, the proposed active site for interaction has a significant part in determining the TDM, and hence reactivity of the resulting structures. Modification of Cs and CMC with graphene has a significant positive impact on enhancing their electrical features. The resulting bandgap of the proposed structures is lower than half of their original values. However, the chosen level of theory could not differentiate truthfully between the two proposed groups regarding their bandgap energies. Therefore, an experimental trial was carried out by printing a sixty-layer simple electrode of both biocomposite inks via a microdrop InkJet printer. Then, sheet resistance and charge mobility measurements were conducted. Results illustrate that the sheet resistance of the G-Cs printed electrode is about five times higher than that of G-CMC one (However, the resulting values are still quite high which need further enhancement). Such result was confirmed by the measured Hall Effect measurement which showed that the charge mobility in the G-CMC electrode is much greater compared to that in G-Cs one. These experimental results confirm the resulting theoretical data of the proposed model. Both parts agree that the G-CMC biocomposite has much more electrical conductivity proposing it as a potential candidate for bio-electronic applications.