Open hardware for microfluidics: exploiting raspberry Pi singleboard computer and camera systems for customisable laboratory instrumentation
Open hardware for microfluidics: exploiting raspberry Pi singleboard computer and camera systems for customisable laboratory instrumentation
The integration of Raspberry Pi miniature computer systems with microfluidics has revolutionised the development of low-cost and customizable analytical systems in life science laboratories. This review explores the applications of Raspberry Pi in microfluidics, with a focus on imaging, including microscopy and automated image capture. By leveraging the low cost, flexibility and accessibility of Raspberry Pi components, high-resolution imaging and analysis have been achieved in direct mammalian and bacterial cellular imaging and a plethora of image-based biochemical and molecular assays, from immunoassays, through microbial growth, to nucleic acid methods such as real-time-qPCR. The control of image capture permitted by Raspberry Pi hardware can also be combined with onboard image analysis. Open-source hardware offers an opportunity to develop complex laboratory instrumentation systems at a fraction of the cost of commercial equipment and, importantly, offers an opportunity for complete customisation to meet the users’ needs. However, these benefits come with a trade-off: challenges remain for those wishing to incorporate open-source hardware equipment in their own work, including requirements for construction and operator skill, the need for good documentation and the availability of rapid prototyping such as 3D printing plus other components. These advances in open-source hardware have the potential to improve the efficiency, accessibility, and cost-effectiveness of microfluidic-based experiments and applications.
Sarıyer, Rüya Meltem
12396c8e-9415-4be0-958b-bb419f3aef24
Edwards, Alexander Daniel
bc3d9b93-a533-4144-937b-c673d0a28879
Needs, Sarah Helen
24425556-99e3-4c46-995b-2381776a0a38
23 October 2023
Sarıyer, Rüya Meltem
12396c8e-9415-4be0-958b-bb419f3aef24
Edwards, Alexander Daniel
bc3d9b93-a533-4144-937b-c673d0a28879
Needs, Sarah Helen
24425556-99e3-4c46-995b-2381776a0a38
Sarıyer, Rüya Meltem, Edwards, Alexander Daniel and Needs, Sarah Helen
(2023)
Open hardware for microfluidics: exploiting raspberry Pi singleboard computer and camera systems for customisable laboratory instrumentation.
Biosensors, 13 (10), [948].
(doi:10.3390/bios13100948).
Abstract
The integration of Raspberry Pi miniature computer systems with microfluidics has revolutionised the development of low-cost and customizable analytical systems in life science laboratories. This review explores the applications of Raspberry Pi in microfluidics, with a focus on imaging, including microscopy and automated image capture. By leveraging the low cost, flexibility and accessibility of Raspberry Pi components, high-resolution imaging and analysis have been achieved in direct mammalian and bacterial cellular imaging and a plethora of image-based biochemical and molecular assays, from immunoassays, through microbial growth, to nucleic acid methods such as real-time-qPCR. The control of image capture permitted by Raspberry Pi hardware can also be combined with onboard image analysis. Open-source hardware offers an opportunity to develop complex laboratory instrumentation systems at a fraction of the cost of commercial equipment and, importantly, offers an opportunity for complete customisation to meet the users’ needs. However, these benefits come with a trade-off: challenges remain for those wishing to incorporate open-source hardware equipment in their own work, including requirements for construction and operator skill, the need for good documentation and the availability of rapid prototyping such as 3D printing plus other components. These advances in open-source hardware have the potential to improve the efficiency, accessibility, and cost-effectiveness of microfluidic-based experiments and applications.
Text
biosensors-13-00948
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Accepted/In Press date: 19 October 2023
Published date: 23 October 2023
Identifiers
Local EPrints ID: 493262
URI: http://eprints.soton.ac.uk/id/eprint/493262
ISSN: 0265-928X
PURE UUID: b7eb16ea-7003-4dfa-babd-ad06fcfea6b9
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Date deposited: 29 Aug 2024 16:37
Last modified: 30 Aug 2024 02:07
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Author:
Rüya Meltem Sarıyer
Author:
Alexander Daniel Edwards
Author:
Sarah Helen Needs
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