81-92% of chemically valid and metastable crystals from generative models are training duplicates or substitution-derived, with low-symmetry cases showing interpolation and high-symmetry cases showing memorization.
A generative model for inorganic materials design
4 Pith papers cite this work, alongside 367 external citations. Polarity classification is still indexing.
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A physics-plus-AI pipeline recovers crystal structures from powder X-ray diffraction on most of a hard benchmark set, but success drops sharply for low-symmetry cases.
LEGO-MOF maps MOF linkers to an equivariant latent space for continuous editing and uses test-time optimization to achieve a 147.5% average boost in pure CO2 uptake while preserving structural validity.
SMC-AI scales Monte Carlo simulations to 4 trillion atoms on AI hardware clusters, achieving 32 times larger systems and 1.3 times higher throughput than prior records while decoupling ML models from the simulation core.
citing papers explorer
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Substitution-Based Analysis of Structural Novelty for Generative Models of Materials
81-92% of chemically valid and metastable crystals from generative models are training duplicates or substitution-derived, with low-symmetry cases showing interpolation and high-symmetry cases showing memorization.
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Ab-initio Crystal Structure Determination from Powder X-Ray Diffraction
A physics-plus-AI pipeline recovers crystal structures from powder X-ray diffraction on most of a hard benchmark set, but success drops sharply for low-symmetry cases.
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LEGO-MOF: Equivariant Latent Manipulation for Editable, Generative, and Optimizable MOF Design
LEGO-MOF maps MOF linkers to an equivariant latent space for continuous editing and uses test-time optimization to achieve a 147.5% average boost in pure CO2 uptake while preserving structural validity.
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SMC-AI: Scaling Monte Carlo Simulation to Four Trillion Atoms with AI Accelerators
SMC-AI scales Monte Carlo simulations to 4 trillion atoms on AI hardware clusters, achieving 32 times larger systems and 1.3 times higher throughput than prior records while decoupling ML models from the simulation core.