5 citations · 5 across the 1 of their papers we have counts for
3 papers
cond-mat.mtrl-sci2025
Improving atomic force microscopy structure discovery via style-translation
Jie Huang, Niko Oinonen, Fabio Priante +4
Atomic force microscopy (AFM) is a key tool for characterising nanoscale structures, with functionalised tips now offering detailed images of the atomic structure. In parallel, AFM…
cond-mat.soft2021★ 5 cited
Neural Network Model for Structure Factor of Polymer Systems
Jie Huang, Xinghua Zhang, Gang Huang +1
As an important physical quantity to understand the internal structure of polymer chains, the structure factor is being studied both in theory and experiment. Theoretically, the st…
cond-mat.dis-nn2021
A machine learning model to classify dynamic processes in liquid water
Jie Huang, Gang Huang, Shiben Li
The dynamics of water molecules plays a vital role in understanding water. We combined computer simulation and deep learning to study the dynamics of H-bonds between water molecule…