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New Crys-JEPA model accelerates discovery of stable, novel crystals

Researchers have developed Crys-JEPA, a novel generative model designed to accelerate the discovery of new crystalline materials. Existing models struggle with a trade-off between stability and novelty, often producing materials that are either too similar to known ones or unstable. Crys-JEPA addresses this by learning an energy-aware latent space, allowing for more efficient stability assessment and a refined screening process that reintroduces promising generated crystals to improve the model. This approach has shown significant improvements in identifying stable and novel crystals on benchmark datasets. AI

影响 Introduces a new generative model that could accelerate materials science research by improving the discovery of stable and novel crystals.

排序理由 Publication of a new academic paper detailing a novel generative model for material science. [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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New Crys-JEPA model accelerates discovery of stable, novel crystals

报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Xavier Bresson ·

    Crys-JEPA:通过嵌入筛选和生成式精炼加速晶体发现

    De novo crystal generation seeks to discover materials that are not merely realistic, but also stable and novel. However, most existing generative models are trained to maximize the likelihood of observed crystals, which encourages samples to stay close to known materials yet not…