Microfluidics and Nanofluidics, Journal Year: 2024, Volume and Issue: 28(8)
Published: July 6, 2024
Language: Английский
Lab on a Chip, Journal Year: 2024, Volume and Issue: 24(5), P. 1135 - 1153
Published: Jan. 1, 2024
This review introduces the development of droplet microfluidics by explaining physical mechanisms generation, discussing various approaches in manipulating droplets, and summarizing key applications material science biological analyses.
Language: Английский
Citations
61
Lab on a Chip, Journal Year: 2024, Volume and Issue: 24(5), P. 1307 - 1326
Published: Jan. 1, 2024
This review outlines the current advances of high-throughput microfluidic systems accelerated by AI. Furthermore, challenges and opportunities in this field are critically discussed as well.
Language: Английский
Citations
19
Applied Physics Reviews, Journal Year: 2025, Volume and Issue: 12(1)
Published: Jan. 21, 2025
Droplet microfluidics has emerged as highly relevant technology in diverse fields such nanomaterials synthesis, photonics, drug delivery, regenerative medicine, food science, cosmetics, and agriculture. While significant progress been made understanding the fundamental mechanisms underlying droplet generation microchannels fabricating devices to produce droplets with varied functionality high throughput, challenges persist along two important directions. On one side, generalization of numerical results obtained by computational fluid dynamics would be deepen comprehension complex physical phenomena microfluidics, well capability predicting device behavior. Conversely, truly three-dimensional architectures enhance microfluidic platforms terms tailoring enhancing flow properties. Recent advancements artificial intelligence (AI) additive manufacturing (AM) promise unequaled opportunities for simulating behavior, precisely tracking individual droplets, exploring innovative designs. This review provides a comprehensive overview recent applying AI AM microfluidics. The basic properties multiphase flows production are discussed, current fabrication methods related introduced, together their applications. Delving into use technologies topics covered include AI-assisted simulations real-time within systems, AM-fabrication systems. synergistic combination is expected active matter expediting transition toward fully digital
Language: Английский
Citations
3
Microsystems & Nanoengineering, Journal Year: 2023, Volume and Issue: 9(1)
Published: Sept. 21, 2023
In this paper, we review the integration of microfluidic chips and computer vision, which has great potential to advance research in life sciences biology, particularly analysis cell imaging data. Microfluidic enable generation large amounts visual data at single-cell level, while vision techniques can rapidly process analyze these extract valuable information about cellular health function. One key advantages integrative approach is that it allows for noninvasive low-damage characterization, important studying delicate or fragile microbial cells. The use provides a highly controlled environment growth manipulation, minimizes experimental variability improves accuracy analysis. Computer be used recognize target species within heterogeneous populations, understanding physiological status cells complex biological systems. As hardware artificial intelligence algorithms continue improve, expected become an increasingly powerful tool situ microelectromechanical devices combination with could development label-free, automatic, low-cost, fast recognition high-throughput responses different compounds, broad applications fields such as drug discovery, diagnostics, personalized medicine.
Language: Английский
Citations
31
Lab on a Chip, Journal Year: 2023, Volume and Issue: 23(11), P. 2497 - 2513
Published: Jan. 1, 2023
This review summarizes the implementations of droplet microfluidics based on AI, including generation, biological analysis, and material synthesis.
Language: Английский
Citations
24
Micromachines, Journal Year: 2023, Volume and Issue: 14(4), P. 826 - 826
Published: April 8, 2023
Microfluidics is a rapidly growing discipline that involves studying and manipulating fluids at reduced length scale volume, typically on the of micro- or nanoliters. Under larger surface-to-volume ratio, advantages low reagent consumption, faster reaction kinetics, more compact systems are evident in microfluidics. However, miniaturization microfluidic chips introduces challenges stricter tolerances designing controlling them for interdisciplinary applications. Recent advances artificial intelligence (AI) have brought innovation to microfluidics from design, simulation, automation, optimization bioanalysis data analytics. In microfluidics, Navier-Stokes equations, which partial differential equations describing viscous fluid motion complete form known not general analytical solution, can be simplified fair performance through numerical approximation due inertia laminar flow. Approximation using neural networks trained by rules physical knowledge new possibility predict physicochemical nature. The combination automation produce large amounts data, where features patterns difficult discern human extracted machine learning. Therefore, integration with AI potential revolutionize workflow enabling precision control analysis. Deployment smart may tremendously beneficial various applications future, including high-throughput drug discovery, rapid point-of-care-testing (POCT), personalized medicine. this review, we summarize key integrated discuss outlook possibilities combining
Language: Английский
Citations
23
ACS Applied Materials & Interfaces, Journal Year: 2024, Volume and Issue: 16(30), P. 38832 - 38851
Published: July 17, 2024
Phenotypic drug discovery (PDD), which involves harnessing biological systems directly to uncover effective drugs, has undergone a resurgence in recent years. The rapid advancement of artificial intelligence (AI) over the past few years presents numerous opportunities for augmenting phenotypic screening on microfluidic platforms, leveraging its predictive capabilities, data analysis, efficient processing, etc. Microfluidics coupled with AI is poised revolutionize landscape discovery. By integrating advanced platforms algorithms, researchers can rapidly screen large libraries compounds, identify novel candidates, and elucidate complex pathways unprecedented speed efficiency. This review provides an overview advances challenges AI-based microfluidics their applications We discuss synergistic combination high-throughput AI-driven analysis phenotype characterization, drug-target interactions, modeling. In addition, we highlight potential AI-powered achieve automated system. Overall, represents promising approach shaping future by enabling rapid, cost-effective, accurate identification therapeutically relevant compounds.
Language: Английский
Citations
9
Water Research, Journal Year: 2025, Volume and Issue: 274, P. 123161 - 123161
Published: Jan. 18, 2025
Language: Английский
Citations
1
Frontiers in Bioengineering and Biotechnology, Journal Year: 2023, Volume and Issue: 11
Published: June 7, 2023
Droplet microfluidics has gained widespread attention in recent years due to its advantages of high throughput, integration, sensitivity and low power consumption droplet-based micro-reaction. Meanwhile, with the rapid development computer technology over past decade, deep learning architectures have been able process vast amounts data from various research fields. Nowadays, interdisciplinarity plays an increasingly important role modern research, contributed greatly advancement many professions. Consequently, intelligent emerged as times require, possesses broad prospects automated devices for integrating merits microfluidic artificial intelligence. In this article, we provide a general review evolution some applications related learning, mainly droplet generation, control, analysis. We also present challenges emerging opportunities field.
Language: Английский
Citations
20
Microsystems & Nanoengineering, Journal Year: 2024, Volume and Issue: 10(1)
Published: Sept. 27, 2024
Language: Английский
Citations
7