3 citations · 3 across the 6 of their papers we have counts for
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Benchmarking Universal Machine Learning Force Fields for Crystal Structure Prediction of High-Energy Molecular Systems
Musiha Mahfuza Mukta, Osman Goni Ridwan, Romain Perriot +1
Recent developments of universal machine learning interatomic potentials (UMLIPs) offer a fast route for screening molecular crystals based on geometry relaxation and energy rankin…
High-throughput Discovery of Magnetic Rare Earth Transition Metal Alloys
Shuo Tao, Osman Goni Ridwan, Liqin Ke +1
We present an accelerated materials discovery framework that combines diffusion-based crystal structure generation with hierarchical screening to identify new rare-earth--transitio…
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…