… polarizable force fields used as references in this work, not to mention the parameters of …
using the machine learning strategy to predict secondary structures of proteins192,193. For …

… is called machine learning, ML) has exhibited as an effective … network to obtain a ML force
field which maps configurations … identify the most critical parameters and then further speed …

… For instance, machine learning models trained on … ., using AI to optimize existing physics-based
simulation techniques and efficiently explore hundreds of millions of design parameters …

… , in which the accuracy of force field parameters play a criticl role in the … Machine learning
consisting of various algorithms is a … At last, the investigations on the utilization of HTCS in CH4 …

… the present review discusses challenges and opportunities in the applications of machine
learning methods to polymer glass formation and provides a perspective on glass informatics. …

… /hardware technology has greatly enhanced the efficiency of large-scale parallel computing
… polymer electrolytes by machine learning assisted coarse-grained molecular dynamics. …

… the specific field of contemporary design,however,it refers broadly to the utilization of parametric
… However,these techniques are highly efficient for remodeling forms,and afford greater …

… 40 years ago the same thing was said about using column … may be the only cost effective
means of separation. Remember… , York can determine parameters important for your separation …

… coarse grained have a small number of powerful configurable logic blocks, those with a
finer-grained … Effective utilization of a computing system is accomplished by creating a suitable …

… be fully saturated; (3) the effective stress due to static or dynamic … , and can be achieved using
a double drainage system, one … calculated using a coupled hydro-mechanical fine element …