1 citations · 1 across the 8 of their papers we have counts for
10 papers
PXRD-Bench: How Close Are We to Determining Crystal Structures from Powder Diffraction?
Dongyeop Woo, Nofit Segal, Nayoung Kim +3
Determining crystal structures from powder X-ray diffraction (PXRD) would enable routine characterization of newly synthesized materials, including those absent from reference data…
Packora: Systematic Design for Generative Molecular Crystal Structure Prediction
Nayoung Kim, Kiyoung Seong, Sungsoo Ahn
Molecular crystal structure prediction (CSP) is important in pharmaceuticals, agrochemicals, and organic electronics, where subtle differences in molecular conformation and packing…
Discovering Crystal Structure Prediction Algorithms with an AI Co-Scientist
Kiyoung Seong, Nayoung Kim, Sungsoo Ahn
We introduce Human-AI Co-discovery system (HACO) for scientific algorithm discovery through cross-domain search and sparse human steering. Starting from the goal of generating crys…
AtomMOF: All-Atom Flow Matching for MOF-Adsorbate Structure Prediction
Nayoung Kim, Honghui Kim, Sihyun Yu +3
Metal-organic frameworks (MOFs) are promising materials for applications such as direct air capture, where performance depends on how adsorbates bind within the framework. Accurate…
Machine Learning Hamiltonians are Accurate Energy-Force Predictors
Seongsu Kim, Chanhui Lee, Yoonho Kim +7
Recently, machine learning Hamiltonian (MLH) models have gained traction as fast approximations of electronic structures such as orbitals and electron densities, while also enablin…
CatFlow: Co-generation of Slab-Adsorbate Systems via Flow Matching
Minkyu Kim, Nayoung Kim, Honghui Kim +1
Discovering heterogeneous catalysts tailored for specific reaction intermediates remains a fundamental bottleneck in materials science. While traditional trial-and-error methods an…
High-order Equivariant Flow Matching for Density Functional Theory Hamiltonian Prediction
Seongsu Kim, Nayoung Kim, Dongwoo Kim +1
Density functional theory (DFT) is a fundamental method for simulating quantum chemical properties, but it remains expensive due to the iterative self-consistent field (SCF) proces…
Flexible MOF Generation with Torsion-Aware Flow Matching
Nayoung Kim, Seongsu Kim, Sungsoo Ahn
Designing metal-organic frameworks (MOFs) with novel chemistries is a longstanding challenge due to their large combinatorial space and complex 3D arrangements of the building bloc…
MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks
Nayoung Kim, Seongsu Kim, Minsu Kim +2
Metal-organic frameworks (MOFs) are a class of crystalline materials with promising applications in many areas such as carbon capture and drug delivery. In this work, we introduce…
Decoupled Sequence and Structure Generation for Realistic Antibody Design
Nayoung Kim, Minsu Kim, Sungsoo Ahn +1
Recently, deep learning has made rapid progress in antibody design, which plays a key role in the advancement of therapeutics. A dominant paradigm is to train a model to jointly ge…