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Droplet and Digital Microfluidics
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Droplet and Digital Microfluidics : Ideation to Implementation

Book Details

Format Paperback / Softback
ISBN-10 0443154163
ISBN-13 9780443154164
Publisher Elsevier Science Publishing Co Inc
Imprint Academic Press Inc
Country of Manufacture GB
Country of Publication GB
Publication Date Mar 25th, 2024
Print length 274 Pages
Weight 440 grams
Dimensions 15.20 x 22.70 x 1.40 cms
Ksh 30,600.00
Werezi Extended Catalogue 0 in stock

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Droplet and Digital Microfluidics: Ideation to Implementation is a detailed introduction to the dynamics of droplet and digital microfluidics, also featuring coverage of new methods and applications. The explosion of applications of microelectromechanical systems (MEMS) in recent years has driven demand for expertise and innovation in fluid flow in the microchannels they contain. In this book, detailed descriptions of methods for biological and chemical applications of microfluidics are provided, along with supporting foundational knowledge. In addition, the principles of droplet and digital microfluidics are explained, along with their different applications and governing physics. New additions to the technological knowledgebase that enable advances in droplet and digital microfluidics include machine learning and exciting future avenues for research.

Droplet and Digital Microfluidics: Ideation to Implementation is a detailed introduction to the dynamics of droplet and digital microfluidics, also featuring coverage of new methods and applications. The explosion of applications of microelectromechanical systems (MEMS) in recent years has driven demand for expertise and innovation in fluid flow in the microchannels they contain. In this book, detailed descriptions of methods for biological and chemical applications of microfluidics are provided, along with supporting foundational knowledge. In addition, the principles of droplet and digital microfluidics are explained, along with their different applications and governing physics.

New additions to the technological knowledgebase that enable advances in droplet and digital microfluidics include machine learning and exciting future avenues for research.


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