Microfluidics in Planar Microchannels: Synthesis of Chemical Compounds On-Chip

  • Valentina ArimaEmail author
  • Paul Watts
  • Giancarlo Pascali


Microreactors are a wide class of devices that are currently playing a prominent role in several research fields such as biology, medicine, food chemistry, environmental analysis, up to the production of compounds in organic chemistry. Several typologies of microreactors have been produced with tubular or planar shapes, of different materials and designs. In this chapter, an overview of planar microchannel-based microreactors and their application to organic chemistry is given. Initially, after recalling the main theoretical parameters of microfluidics, an introduction of the proposed technology and the main requirements to perform mixing, which is essential to perform chemical synthesis on-chip, is presented. Silicon and glass microreactors, the most common planar systems for organic chemistry, are described with the aim of pointing out the most important parameters to be taken into consideration in the planning of a specific microreactor to be used for mixing, purification or crystallization of chemicals at the microscale. Then, several applications of initially described microreactors to organic chemistry for research applications are given. In the next section, the use of planar microchannel microreactors in the field of radiochemistry is reported. The radiopharmaceutical application is not casual, being a sector in which the microreactor technology is very promising, due to the need of quickly producing small and fresh amounts of products in a controlled environment. Finally, for completeness, other approaches beyond planar microchannels are mentioned: mesoreactors towards industrial level synthesis and micro-vessels for radiochemistry.


Positron Emission Tomography Pressure Drop Microfluidic System Chaotic Advection Passive Mixer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Valentina Arima
    • 1
    Email author
  • Paul Watts
    • 2
  • Giancarlo Pascali
    • 3
  1. 1.CNR-NANO, Institute of Nanoscience, U.O.S. LecceLecceItaly
  2. 2.InnoVenton: NMMU Institute for Chemical TechnologyNelson Mandela Metropolitan UniversityPort ElizabethSouth Africa
  3. 3.ANSTO LifesciencesCamperdownAustralia

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