183 citations · 2.1k across the 63 of their papers we have counts for
67 papers
NEMORA: Neural Equivariant Multipole Operators for Long-Range Atomistic Learning
Jay L. Kaplan, Samuel Varner, Rebecca Willett +1
Equivariant graph neural networks have emerged as foundational architectures for machine-learned interatomic potentials, approaching quantum-chemical accuracy at a fraction of the…
HiPoly: a hierarchical polymer-native AI framework for property prediction and generative design
Ge Sun, Gervasio Zaldivar, Yuan Tian +5
Polymeric materials are central to modern technologies, with applications ranging from energy to health and transportation. Although AI has made significant advances in materials d…
Over what length scale does an inorganic substrate perturb the structure of a glassy organic semiconductor?
Kushal Bagchi, Chuting Deng, Camille Bishop +6
While the bulk structure of vapor-deposited glasses has been extensively studied, structure at buried interfaces has received little attention, despite being important for organic…
Characterizing Defect Dynamics in Silicon Carbide Using Symmetry-Adapted Collective Variables and Machine Learning Interatomic Potentials
Soumajit Dutta, Cunzhi Zhang, Gustavo Perez Lemus +4
Silicon carbide (SiC) divacancies are attractive candidates for spin defect qubits possessing long coherence times and optical addressability. The high activation barriers associat…
Omnidirectionally manipulated skyrmions in an orientationally chiral system
Jiahao Chen, Wentao Tang, Xingzhou Tang +7
Skyrmions, originally from condensed matter physics, have been widely explored in various physical systems, including soft matter. A crucial challenge in manipulating topological s…
Attention-Based Functional-Group Coarse-Graining: A Deep Learning Framework for Molecular Prediction and Design
Ming Han, Ge Sun, Juan J. de Pablo
Machine learning (ML) offers considerable promise for the design of new molecules and materials. In real-world applications, the design problem is often domain-specific, and suffer…