Integrating electronic structure into generative modeling of inorganic materials
Junkil Park, Junyoung Choi, Yousung Jung

TL;DR
ChargeDIFF is a novel generative model for inorganic materials that explicitly incorporates electronic structure, specifically charge density, enabling more accurate and controllable inverse design of materials with desired properties.
Contribution
This work introduces ChargeDIFF, the first model to integrate electronic structure into generative modeling of inorganic materials, improving design accuracy and enabling electronic property control.
Findings
ChargeDIFF outperforms baseline models in generation tasks.
Incorporating electronic structure improves material stability predictions.
Charge density control enables targeted inverse design of battery materials.
Abstract
Recent advances in generative models have introduced a new paradigm for the inverse design of inorganic materials, enabling the discovery of new crystalline structures with desired properties. However, existing generative models focus solely on structural aspects of materials during generation, while overlooking the underlying electronic behavior that fundamentally governs materials' stability and functionality. In this work, we present ChargeDIFF, the first generative model for inorganic materials that explicitly incorporates electronic structure into the generation process. Specifically, ChargeDIFF leverages charge density, a direct spatial representation of a material's electronic structure, as an additional modality for generation. ChargeDIFF demonstrates exceptional performance in both unconditional and conditional generation tasks compared to baseline models, with ablation studies…
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Taxonomy
TopicsMachine Learning in Materials Science · Block Copolymer Self-Assembly · Quasicrystal Structures and Properties
