14 citations · 15 across the 2 of their papers we have counts for
2 papers
cs.CE2023★ 14 cited
Analyzing drop coalescence in microfluidic device with a deep learning generative model
Kewei Zhu, Sibo Cheng, Nina Kovalchuk +4
Predicting drop coalescence based on process parameters is crucial for experiment design in chemical engineering. However, predictive models can suffer from the lack of training da…
physics.chem-ph2023★ 1 cited
Optimization of microfluidic synthesis of silver nanoparticles: a generic approach using machine learning
Konstantia Nathanael, Sibo Cheng, Nina M. Kovalchuk +2
The properties of silver nanoparticles (AgNPs) are affected by various parameters, making optimisation of their synthesis a laborious task. This optimisation is facilitated in this…