124 citations · 1k across the 27 of their papers we have counts for
27 papers
Ferroelectric Domain and Switching Dynamics in Curved In2Se3: First Principle and Deep Learning Molecular Dynamics Simulations
Dongyu Bai, Yihan Nie, Jing Shang +5
Complex strain status can exist in 2D materials during their synthesis process, resulting in significant impacts on the physical and chemical properties. Despite their prevalence i…
Physics-informed neural network for friction-involved nonsmooth dynamics problems
Zilin Li, Jinshuai Bai, Huajing Ouyang +8
Friction-induced vibration (FIV) is very common in engineering areas. Analysing the dynamic behaviour of systems containing a multiple-contact point frictional interface is an impo…
Utilising physics-guided deep learning to overcome data scarcity
Jinshuai Bai, Laith Alzubaidi, Qingxia Wang +3
Deep learning (DL) relies heavily on data, and the quality of data influences its performance significantly. However, obtaining high-quality, well-annotated datasets can be challen…
An introduction to programming Physics-Informed Neural Network-based computational solid mechanics
Jinshuai Bai, Hyogu Jeong, C. P. Batuwatta-Gamage +6
Physics-informed neural network (PINN) has recently gained increasing interest in computational mechanics. In this work, we present a detailed introduction to programming PINN-base…
Reversible Gas Sensing by Ferroelectric Switch and 2D Molecule Multiferroics in In2Se3 Monolayer
Xiao Tang, Jing Shang, Yuantong Gu +2
Two-dimensional ferroelectrics are important quantum materials which have found novel application in nonvolatile memories, however, the effects of reversible polarization on chemic…
Multiferroic Decorated Fe2O3 Monolayer Predicted from First Principles
Jing Shang, Chun Li, Aijun Du +5
Two-dimensional (2D) multiferroics exhibit cross-control capacity between magnetic and electric responses in reduced spatial domain, making them well suited for next-generation nan…