Generative design of crystal structures by point cloud representations and diffusion model
Summary: Efficiently generating energetically stable crystal structures has long been a challenge in material design, primarily due to the immense arrangement of atoms in a crystal lattice. To facilitate the discovery of stable materials, we present a framework for the generation of synthesizable ma...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | iScience |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004224028864 |
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| author | Zhelin Li Rami Mrad Runxian Jiao Guan Huang Jun Shan Shibing Chu Yuanping Chen |
| author_facet | Zhelin Li Rami Mrad Runxian Jiao Guan Huang Jun Shan Shibing Chu Yuanping Chen |
| author_sort | Zhelin Li |
| collection | DOAJ |
| description | Summary: Efficiently generating energetically stable crystal structures has long been a challenge in material design, primarily due to the immense arrangement of atoms in a crystal lattice. To facilitate the discovery of stable materials, we present a framework for the generation of synthesizable materials leveraging a point cloud representation to encode intricate structural information. At the heart of this framework lies the introduction of a diffusion model as its foundational pillar. To gauge the efficacy of our approach, we employed it to reconstruct input structures from our training datasets, rigorously validating its high reconstruction performance. Furthermore, we demonstrate the profound potential of point cloud-based crystal diffusion (PCCD) by generating materials, emphasizing their synthesizability. Our research stands as a noteworthy contribution to the advancement of materials design and synthesis through the cutting-edge avenue of generative design instead of conventional substitution or experience-based discovery. |
| format | Article |
| id | doaj-art-b036779cc44341cbacee079344131e34 |
| institution | Kabale University |
| issn | 2589-0042 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | iScience |
| spelling | doaj-art-b036779cc44341cbacee079344131e342025-01-09T06:14:25ZengElsevieriScience2589-00422025-01-01281111659Generative design of crystal structures by point cloud representations and diffusion modelZhelin Li0Rami Mrad1Runxian Jiao2Guan Huang3Jun Shan4Shibing Chu5Yuanping Chen6School of Physics and Electronic Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, P.R. China; Jiangsu Engineering Research Center on Quantum Perception and Intelligent Detection of Agricultural Information, Zhenjiang 212013, ChinaSchool of Physics and Electronic Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, P.R. China; Jiangsu Engineering Research Center on Quantum Perception and Intelligent Detection of Agricultural Information, Zhenjiang 212013, ChinaSchool of Physics and Electronic Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, P.R. China; Jiangsu Engineering Research Center on Quantum Perception and Intelligent Detection of Agricultural Information, Zhenjiang 212013, ChinaSchool of Physics and Electronic Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, P.R. China; Jiangsu Engineering Research Center on Quantum Perception and Intelligent Detection of Agricultural Information, Zhenjiang 212013, ChinaSchool of Physics and Electronic Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, P.R. China; Jiangsu Engineering Research Center on Quantum Perception and Intelligent Detection of Agricultural Information, Zhenjiang 212013, ChinaSchool of Physics and Electronic Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, P.R. China; Jiangsu Engineering Research Center on Quantum Perception and Intelligent Detection of Agricultural Information, Zhenjiang 212013, China; Corresponding authorSchool of Physics and Electronic Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, P.R. China; Jiangsu Engineering Research Center on Quantum Perception and Intelligent Detection of Agricultural Information, Zhenjiang 212013, China; Corresponding authorSummary: Efficiently generating energetically stable crystal structures has long been a challenge in material design, primarily due to the immense arrangement of atoms in a crystal lattice. To facilitate the discovery of stable materials, we present a framework for the generation of synthesizable materials leveraging a point cloud representation to encode intricate structural information. At the heart of this framework lies the introduction of a diffusion model as its foundational pillar. To gauge the efficacy of our approach, we employed it to reconstruct input structures from our training datasets, rigorously validating its high reconstruction performance. Furthermore, we demonstrate the profound potential of point cloud-based crystal diffusion (PCCD) by generating materials, emphasizing their synthesizability. Our research stands as a noteworthy contribution to the advancement of materials design and synthesis through the cutting-edge avenue of generative design instead of conventional substitution or experience-based discovery.http://www.sciencedirect.com/science/article/pii/S2589004224028864Natural sciencesPhysicsComputer scienceMaterials science |
| spellingShingle | Zhelin Li Rami Mrad Runxian Jiao Guan Huang Jun Shan Shibing Chu Yuanping Chen Generative design of crystal structures by point cloud representations and diffusion model iScience Natural sciences Physics Computer science Materials science |
| title | Generative design of crystal structures by point cloud representations and diffusion model |
| title_full | Generative design of crystal structures by point cloud representations and diffusion model |
| title_fullStr | Generative design of crystal structures by point cloud representations and diffusion model |
| title_full_unstemmed | Generative design of crystal structures by point cloud representations and diffusion model |
| title_short | Generative design of crystal structures by point cloud representations and diffusion model |
| title_sort | generative design of crystal structures by point cloud representations and diffusion model |
| topic | Natural sciences Physics Computer science Materials science |
| url | http://www.sciencedirect.com/science/article/pii/S2589004224028864 |
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