94 citations · 190 across the 20 of their papers we have counts for
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XRDiff: Crystal Structure Prediction from Powder X-Ray Diffraction Data Using Diffusion Models
Nofit Segal, Mingda Li, Benjamin Kurt Miller +1
Determining the crystal structure of a material from its powder X-ray diffraction (PXRD) pattern is a central challenge in materials science. PXRD is an accessible and widely used…
High-Throughput Transition-State Searches in Zeolite Nanopores
Pau Ferri-Vicedo, Alexander J. Hoffman, Avni Singhal +1
Zeolites are important for industrial catalytic processes involving organic molecules. Understanding molecular reaction mechanisms within the confined nanoporous environment can gu…
Accelerating and enhancing thermodynamic simulations of electrochemical interfaces
Xiaochen Du, Mengren Liu, Jiayu Peng +6
Electrochemical interfaces are crucial in catalysis, energy storage, and corrosion, where their stability and reactivity depend on complex interactions between the electrode, adsor…
Efficient Generation of Molecular Clusters with Dual-Scale Equivariant Flow Matching
Akshay Subramanian, Shuhui Qu, Cheol Woo Park +3
Amorphous molecular solids offer a promising alternative to inorganic semiconductors, owing to their mechanical flexibility and solution processability. The packing structure of th…
Flow Matching for Accelerated Simulation of Atomic Transport in Crystalline Materials
Juno Nam, Sulin Liu, Gavin Winter +3
Atomic transport underpins the performance of materials in technologies such as energy storage and electronics, yet its simulation remains computationally demanding. In particular,…
Learning Ordering in Crystalline Materials with Symmetry-Aware Graph Neural Networks
Jiayu Peng, James Damewood, Jessica Karaguesian +2
Graph convolutional neural networks (GCNNs) have become a machine learning workhorse for screening the chemical space of crystalline materials in fields such as catalysis and energ…