MDDM: A Molecular Dynamics Diffusion Model to Predict Particle Self-Assembly

• URL: http://arxiv.org/abs/2501.17319v1
• Date: Tue, 28 Jan 2025 22:21:45 GMT
• Title: MDDM: A Molecular Dynamics Diffusion Model to Predict Particle Self-Assembly
• Authors: Kevin Ferguson, Yu-hsuan Chen, Levent Burak Kara,
• Abstract summary: The Molecular Dynamics Diffusion Model is capable of predicting a valid output for a given input pair potential function. The model significantly outperforms the baseline point-cloud diffusion model for both unconditional and conditional generation tasks.
• Score: 0.0
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• Abstract: The discovery and study of new material systems relies on molecular simulations that often come with significant computational expense. We propose MDDM, a Molecular Dynamics Diffusion Model, which is capable of predicting a valid output conformation for a given input pair potential function. After training MDDM on a large dataset of molecular dynamics self-assembly results, the proposed model can convert uniform noise into a meaningful output particle structure corresponding to an arbitrary input potential. The model's architecture has domain-specific properties built-in, such as satisfying periodic boundaries and being invariant to translation. The model significantly outperforms the baseline point-cloud diffusion model for both unconditional and conditional generation tasks.

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