5 Result(s)
within
Lixin Sun
Characterization and Evaluation of Materials
-
Article
Open AccessComplexity of many-body interactions in transition metals via machine-learned force fields from the TM23 data set
This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases of d-block elements. In exhaustive detail, we contrast the performance of force,...
-
Article
Enhancement of Strength and Plasticity by Nanoprecipitation Strengthening and Stacking Fault Deformation in a High Entropy Alloy
Precipitation strengthening can effectively improve the strength of high entropy alloys (HEAs), but usually severely reduces the ductility. In this study, a new interstitial carbon-doped HEA with a nominal com...
-
Article
Cross-linked γ-cyclodextrin metal-organic framework—a new stationary phase for the separations of benzene series and polycyclic aromatic hydrocarbons
The cross-linked γ-cyclodextrin metal-organic framework (CL-CD-MOF) was synthesized by crosslinking γ-cyclodextrin metal-organic framework (γ-CD-MOF) with diphenyl carbonate to separate benzene series and poly...
-
Article
Open AccessBayesian force fields from active learning for simulation of inter-dimensional transformation of stanene
We present a way to dramatically accelerate Gaussian process models for interatomic force fields based on many-body kernels by map** both forces and uncertainties onto functions of low-dimensional features. ...
-
Article
Open AccessOn-the-fly active learning of interpretable Bayesian force fields for atomistic rare events
Machine learned force fields typically require manual construction of training sets consisting of thousands of first principles calculations, which can result in low training efficiency and unpredictable error...
