主講人： Dr. Chun-Wei Pao (Research Fellow, Research Center for Applied Sciences, Academia Sinica)
題目：Machine Learning-enabled Force Fields: solution toward complex material puzzles with atomistic resolution?
時間：111年6月30日(四) 18:00
報名網址： https://forms.gle/PNUTuopCLzBW82HT9
報名截止時間 ：111年6月30日中午12點止
大綱:
Complex materials are gaining increasing attentions from both industrial and academic community. Nevertheless, owing to the combinatorially complicate chemical space spanned, these complex materials have imposed grand challenge to both experimental and theoretical teams. In this talk, I will present our recent efforts in utilizing machine learning-enabled force fields to tackle the problems of revealing the microstructures of complex materials. I will firstly present our extensive Monte Carlo simulations to provide insights into the process-structure-property of complex perovskite using artificial neural network scheme; then, I will present our large-scale molecular dynamics simulations of the plastic deformation of ultraelastic complex alloy using the spectral neighbor analysis potential. I hope that these examples of applications could provide useful insights into both the pros and cons of the machine learning-enabled models brought to theoreticians for the problem of complex materials.
