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FIRE‐GNN: Force‐Informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties

Advanced Intelligent Discovery, EarlyView.
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler   +5 more
wiley   +1 more source

Exploring the Association Between Time Dedicated to Lifelong Learning and Volunteering Among Older Adults: Socioeconomic Status as a Moderator. [PDF]

J Appl Gerontol
Cho JK, Lee J.
europepmc   +1 more source

What if I die? Existential crises when caring for persons with severe mental disorders in rural South Africa. [PDF]

PLOS Ment Health
Silaule O, Nkosi NG, Adams F.
europepmc   +1 more source

Controllable protein design via autoregressive direct coupling analysis conditioned on principal components. [PDF]

PLoS Comput Biol
Caredda F, Gennai L, De Los Rios P, Pagnani A.   +3 more
europepmc   +1 more source