Machine learning for microfluidic design and control
Microfluidics has developed into a mature field with applications across science and
engineering, having particular commercial success in molecular diagnostics, next …
engineering, having particular commercial success in molecular diagnostics, next …
Combinatorial synthesis for AI-driven materials discovery
Combinatorial synthesis of solid-state materials comprises the use of automation or
parallelization to systematically vary synthesis parameters. This approach to materials …
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 …
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
Encapsulation of cells inside microfluidic droplets is central to several applications involving
cellular analysis. Although, theoretically the encapsulation statistics are expected to follow a …
cellular analysis. Although, theoretically the encapsulation statistics are expected to follow a …
Integrating machine learning and biosensors in microfluidic devices: a review.
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 …
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)
Needle-in-a-Haystack problems exist across a wide range of applications including rare
disease prediction, ecological resource management, fraud detection, and material property …
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 …
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 …
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 …
disease detection, drug testing, and material discovery. Despite the great advances in …
Deep Learning-Based Inkjet Droplet Detection for Jetting Characterizations and Multijet Synchronization
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 …
microfluidic droplets in designated patterns at submicrometer resolution, which reduces …