Machine learning for microfluidic design and control

D McIntyre, A Lashkaripour, P Fordyce, D Densmore - Lab on a Chip, 2022 - pubs.rsc.org
Microfluidics has developed into a mature field with applications across science and
engineering, having particular commercial success in molecular diagnostics, next …

Combinatorial synthesis for AI-driven materials discovery

JM Gregoire, L Zhou, JA Haber - Nature Synthesis, 2023 - nature.com
Combinatorial synthesis of solid-state materials comprises the use of automation or
parallelization to systematically vary synthesis parameters. This approach to materials …

AI-powered microfluidics: sha** the future of phenotypic drug discovery

J Liu, H Du, L Huang, W **e, K Liu… - … Applied Materials & …, 2024 - ACS Publications
Phenotypic drug discovery (PDD), which involves harnessing biological systems directly to
uncover effective drugs, has undergone a resurgence in recent years. The rapid …

Deep learning detector for high precision monitoring of cell encapsulation statistics in microfluidic droplets

K Gardner, MM Uddin, L Tran, T Pham, S Vanapalli… - Lab on a Chip, 2022 - pubs.rsc.org
Encapsulation of cells inside microfluidic droplets is central to several applications involving
cellular analysis. Although, theoretically the encapsulation statistics are expected to follow a …

Integrating machine learning and biosensors in microfluidic devices: a review.

G Antonelli, J Filippi, M D'Orazio, G Curci… - Biosensors and …, 2024 - Elsevier
Microfluidic devices are increasingly widespread in the literature, being applied to numerous
exciting applications, from chemical research to Point-of-Care devices, passing through drug …

Fast Bayesian optimization of Needle-in-a-Haystack problems using zooming memory-based initialization (ZoMBI)

AE Siemenn, Z Ren, Q Li, T Buonassisi - npj Computational Materials, 2023 - nature.com
Needle-in-a-Haystack problems exist across a wide range of applications including rare
disease prediction, ecological resource management, fraud detection, and material property …

Applications of Artificial Intelligence Models for Computational Flow Dynamics and Droplet Microfluidics

JGC Ramírez, M Hassan… - Journal of Sustainable …, 2022 - publications.dlpress.org
Microfluidics allows for the manipulation and analysis of minuscule amounts of liquid within
a system that contains multiple channels, ports, and samples. Advanced microfluidic …

Functions and applications of artificial intelligence in droplet microfluidics

H Liu, L Nan, F Chen, Y Zhao, Y Zhao - Lab on a Chip, 2023 - pubs.rsc.org
Droplet microfluidics has emerged as a powerful technology to perform high-throughput
experiments, while artificial intelligence (AI) serves as a functional tool to analyze a large set …

High-throughput microfluidic systems accelerated by artificial intelligence for biomedical applications

J Zhou, J Dong, H Hou, L Huang, J Li - Lab on a Chip, 2024 - pubs.rsc.org
High-throughput microfluidic systems are widely used in biomedical fields for tasks like
disease detection, drug testing, and material discovery. Despite the great advances in …

Deep Learning-Based Inkjet Droplet Detection for Jetting Characterizations and Multijet Synchronization

E Choi, S Choi, K An, KT Kang - ACS Applied Materials & …, 2024 - ACS Publications
Inkjet printing is a powerful direct material writing process. It can be used to deposit
microfluidic droplets in designated patterns at submicrometer resolution, which reduces …