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Sapna Sarupria

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#machine learning Preprint Sep 2026

Riemannian Flow Models with Reinforcement Learning for Molecular Crystal Structure Prediction

Crystal structure governs material properties, making crystal structure prediction (CSP) a fundamental problem in materials science. Generative models are a promising approach for solving this problem, but the prevalence of polymorphism, coupled with large unit cells and complex packing geometry, makes the molecular CS...

T. Egg, Harry W. Sullivan, Maya M. Martirossyan et al. · 0 citations
Preprint Sep 2026

The Role of Concentration in Determining NaCl Nucleation Mechanism: A Story of Pathways Coexistence

Deciphering the microscopic details of crystal nucleation remains a key open problem in chemical physics. For aqueous sodium chloride (NaCl), the extent to which nucleation involves amorphous ion aggregation, and the supersaturation regime in which two-step-like behavior emerges, remains actively debated. In this work,...

Porhouy Minh, Sapna Sarupria · 0 citations

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