From the 1 of 17 linked papers with an AI index.
17 papers
DynaCrys: Crystal Generation with Dynamic Space-Group Diffusion
Zhuotao Jin, Xiaoyun Wang, Nicholas Brawand +5
The search for new crystalline materials spans an enormous compositional and structural space. Generating candidates in this space requires jointly modeling discrete crystallograph…
Fast and Accurate Foundation Models for Equivariant Machine-Learned Interatomic Potentials
Seán R. Kavanagh, Chuin Wei Tan, Menghang Wang +12
The paper presents fast and accurate equivariant machine‑learned interatomic potentials (NequIP and Allegro) as foundation models that scale to ultra‑large datasets while maintaini…
Beyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic Potentials
Gil Harari, Yoel Zimmermann, Ola Tangen Kulseng +4
Machine learning interatomic potentials (MLIPs) have become a hallmark of AI for scientific simulation. While efforts on new architectures and datasets have led to increasingly acc…
Can LLMs extract scientific consensus? A case study in high-temperature superconductivity
Mouyang Cheng, Wenhao He, Zhuotao Jin +9
Scientific knowledge is increasingly dispersed across vast and heterogeneous scientific literature, where important claims are often implicit, evolving, and internally debated. Whi…
Mixture of Experts Framework in Machine Learning Interatomic Potentials for Atomistic Simulations
Gabriel de Miranda Nascimento, Marc L. Descoteaux, Laura Zichi +9
First-principles atomistic simulations are essential for understanding complex material phenomena but are fundamentally limited by their computational cost. While Machine Learning…
Laser-driven ferroelectricity in via quantum fluctuation quenching
Francesco Libbi, Lorenzo Monacelli, Boris Kozinsky
Similar to other perovskites in its family, exhibits a significant softening of the ferroelectric mode with decreasing temperature, a behavior that typically h…