6 papers
CrystalGRPO: Target-Aligned and Coverage-Preserving Reinforcement Learning for Flow-Based Crystal Structure Prediction
Kaixiang Su, Hongfei Xue, Qiang Zhu
Flow-based generative models can efficiently produce candidate structures for crystal structure prediction (CSP), but their pretrained objectives do not directly optimize downstrea…
Ab-initio Crystal Structure Determination from Powder X-Ray Diffraction
Kaixiang Su, Osman Goni Ridwan, Hongfei Xue +1
Determining crystal structures from powder X-ray diffraction (PXRD) has been a significant challenge in materials science, particularly when experimental data contain noise or the…
Crystal Representation in the Reciprocal Space
Osman Goni Ridwan, Hongfei Xue, Youxing Chen +2
In crystallography, a structure is typically represented by the arrangement of atoms in the direct space. Furthermore, space group symmetry and Wyckoff site notations are applied t…
Crystal Generation using the Fully Differentiable Pipeline and Latent Space Optimization
Osman Goni Ridwan, Gilles Frapper, Hongfei Xue +1
We present a materials generation framework that couples a symmetry-conditioned variational autoencoder (CVAE) with a differentiable SO(3) power spectrum objective to steer candida…
AI-Assisted Rapid Crystal Structure Generation Towards a Target Local Environment
Osman Goni Ridwan, Sylvain Pitié, Monish Soundar Raj +4
In the field of material design, traditional crystal structure prediction approaches require extensive structural sampling through computationally expensive energy minimization met…
SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models
Daniel Levy, Siba Smarak Panigrahi, Sékou-Oumar Kaba +5
Generating novel crystalline materials has the potential to lead to advancements in fields such as electronics, energy storage, and catalysis. The defining characteristic of crysta…