首页|Findings from University of Groningen in the Area of Machine Learning Described (Efficiency, Accuracy, and Transferability of Machine Learning Potentials: To Di slocations and Cracks In Iron)
Findings from University of Groningen in the Area of Machine Learning Described (Efficiency, Accuracy, and Transferability of Machine Learning Potentials: To Di slocations and Cracks In Iron)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting from Groningen, Netherlands , by NewsRx journalists, research stated, “Machine learning interatomic potentia ls (ML-IAPs) enable quantum -accurate, classical molecular dynamics simulations of large systems, beyond reach of density functional theory (DFT). Yet, their ef ficiency and ability to predict systems larger than DFT supercells are not fully explored, posing a question regarding transferability to large-scale simulation s with defects (e.g. dislocations, cracks).” Financial supporters for this research include Center for Information Technology of the University of Groningen (UG), Faculty of Science and Engineering at the University of Groningen.
GroningenNetherlandsEuropeCyborgsEmerging TechnologiesMachine LearningUniversity of Groningen
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