DISO: A Domain Ontology for Modeling Dislocations in Crystalline Materials
Fuente:
arXiv
Guardado en:
| Autores principales: | Ihsan, Ahmad Zainul, Fathalla, Said, Sandfeld, Stefan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Ontology-based knowledge graph infrastructure for interoperable atomistic simulation data
por: Guzman, Abril Azocar, et al.
Publicado: (2026)
por: Guzman, Abril Azocar, et al.
Publicado: (2026)
Ontology-aligned structuring and reuse of multimodal materials data and workflows towards automatic reproduction
por: Ravari, Sepideh Baghaee, et al.
Publicado: (2026)
por: Ravari, Sepideh Baghaee, et al.
Publicado: (2026)
Self-Supervised Learning with Generative Adversarial Networks for Electron Microscopy
por: Kazimi, Bashir, et al.
Publicado: (2024)
por: Kazimi, Bashir, et al.
Publicado: (2024)
Towards knowledge-based workflows: a semantic approach to atomistic simulations for mechanical and thermodynamic properties
por: Guzman, Abril Azocar, et al.
Publicado: (2026)
por: Guzman, Abril Azocar, et al.
Publicado: (2026)
AtomWorld: A Benchmark for Evaluating Spatial Reasoning in Large Language Models on Crystalline Materials
por: Lv, Taoyuze, et al.
Publicado: (2025)
por: Lv, Taoyuze, et al.
Publicado: (2025)
A Generative Model for Accelerated Inverse Modelling Using a Novel Embedding for Continuous Variables
por: Bompas, Sébastien, et al.
Publicado: (2023)
por: Bompas, Sébastien, et al.
Publicado: (2023)
Capturing thin-film microstructure contributions during ultrafast laser-metal interactions using atomistic simulations
por: Ganesan, Hariprasath, et al.
Publicado: (2024)
por: Ganesan, Hariprasath, et al.
Publicado: (2024)
Delineating the interplay effects of microstructure topology and residual stresses in ultrafast laser irradiated thin films
por: Ganesan, Hariprasath, et al.
Publicado: (2026)
por: Ganesan, Hariprasath, et al.
Publicado: (2026)
Design Topological Materials by Reinforcement Fine-Tuned Generative Model
por: Xu, Haosheng, et al.
Publicado: (2025)
por: Xu, Haosheng, et al.
Publicado: (2025)
MSP-LLM: A Unified Large Language Model Framework for Complete Material Synthesis Planning
por: Noh, Heewoong, et al.
Publicado: (2026)
por: Noh, Heewoong, et al.
Publicado: (2026)
Coupling Language Models with Physics-based Simulation for Synthesis of Inorganic Materials
por: Staley, Edward W., et al.
Publicado: (2026)
por: Staley, Edward W., et al.
Publicado: (2026)
From Data to Theory: Autonomous Large Language Model Agents for Materials Science
por: Alfred, Samuel Onimpa, et al.
Publicado: (2026)
por: Alfred, Samuel Onimpa, et al.
Publicado: (2026)
TopoMAS: Large Language Model Driven Topological Materials Multiagent System
por: Zhang, Baohua, et al.
Publicado: (2025)
por: Zhang, Baohua, et al.
Publicado: (2025)
AI-Driven Phase Identification from X-ray Hyperspectral Imaging of cycled Na-ion Cathode Materials
por: Adrar, Fayçal, et al.
Publicado: (2026)
por: Adrar, Fayçal, et al.
Publicado: (2026)
Artificial Intelligence in Concrete Materials: A Scientometric View
por: Li, Zhanzhao, et al.
Publicado: (2022)
por: Li, Zhanzhao, et al.
Publicado: (2022)
Generative Hierarchical Materials Search
por: Yang, Sherry, et al.
Publicado: (2024)
por: Yang, Sherry, et al.
Publicado: (2024)
A Generation Framework with Strict Constraints for Crystal Materials Design
por: Huang, Chao, et al.
Publicado: (2024)
por: Huang, Chao, et al.
Publicado: (2024)
QMBench: A Research Level Benchmark for Quantum Materials Research
por: Wang, Yanzhen, et al.
Publicado: (2025)
por: Wang, Yanzhen, et al.
Publicado: (2025)
Materials Generation in the Era of Artificial Intelligence: A Comprehensive Survey
por: Li, Zhixun, et al.
Publicado: (2025)
por: Li, Zhixun, et al.
Publicado: (2025)
A multi-physics model for the evolution of grain microstructure
por: Tandogan, Izzet Tarik, et al.
Publicado: (2024)
por: Tandogan, Izzet Tarik, et al.
Publicado: (2024)
From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
por: Roy, Aritra, et al.
Publicado: (2026)
por: Roy, Aritra, et al.
Publicado: (2026)
An Agentic Framework for Autonomous Materials Computation
por: Xia, Zeyu, et al.
Publicado: (2025)
por: Xia, Zeyu, et al.
Publicado: (2025)
Towards Agentic Intelligence for Materials Science
por: Zhang, Huan, et al.
Publicado: (2026)
por: Zhang, Huan, et al.
Publicado: (2026)
Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach
por: Vuong, An, et al.
Publicado: (2026)
por: Vuong, An, et al.
Publicado: (2026)
Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models
por: Barroso-Luque, Luis, et al.
Publicado: (2024)
por: Barroso-Luque, Luis, et al.
Publicado: (2024)
Sustainable Materials Discovery in the Era of Artificial Intelligence
por: Mannan, Sajid, et al.
Publicado: (2026)
por: Mannan, Sajid, et al.
Publicado: (2026)
MatFormBench: A Benchmarking Evaluation Framework for Target-Driven Materials Formulation
por: Wu, Linhan, et al.
Publicado: (2026)
por: Wu, Linhan, et al.
Publicado: (2026)
Artificial Intelligence and Generative Models for Materials Discovery -- A Review
por: Handoko, Albertus Denny, et al.
Publicado: (2025)
por: Handoko, Albertus Denny, et al.
Publicado: (2025)
Research Paradigm of Materials Science Tetrahedra with Artificial Intelligence
por: Zhang, Shiyun, et al.
Publicado: (2026)
por: Zhang, Shiyun, et al.
Publicado: (2026)
"DIVE" into Hydrogen Storage Materials Discovery with AI Agents
por: Zhang, Di, et al.
Publicado: (2025)
por: Zhang, Di, et al.
Publicado: (2025)
Interpretable Nanoporous Materials Design with Symmetry-Aware Networks
por: Zhou, Zhenhao, et al.
Publicado: (2025)
por: Zhou, Zhenhao, et al.
Publicado: (2025)
PRISMat: Policy-Driven, Permutation-Invariant Autoregressive Material Generation
por: Schlesinger, Claire, et al.
Publicado: (2026)
por: Schlesinger, Claire, et al.
Publicado: (2026)
Probabilistic Phase Labeling and Lattice Refinement for Autonomous Material Research
por: Chang, Ming-Chiang, et al.
Publicado: (2023)
por: Chang, Ming-Chiang, et al.
Publicado: (2023)
Agentic Design of Compositional Descriptors via Autoresearch for Materials Science Applications
por: Cobelli, Matteo, et al.
Publicado: (2026)
por: Cobelli, Matteo, et al.
Publicado: (2026)
Born-Qualified: An Autonomous Framework for Deploying Advanced Energy and Electronic Materials
por: Spurgeon, Steven R., et al.
Publicado: (2026)
por: Spurgeon, Steven R., et al.
Publicado: (2026)
LLM-Fusion: A Novel Multimodal Fusion Model for Accelerated Material Discovery
por: Boyar, Onur, et al.
Publicado: (2025)
por: Boyar, Onur, et al.
Publicado: (2025)
Tensor Completion for Surrogate Modeling of Material Property Prediction
por: Pakala, Shaan, et al.
Publicado: (2025)
por: Pakala, Shaan, et al.
Publicado: (2025)
From Text to Test: AI-Generated Control Software for Materials Science Instruments
por: Fébba, Davi M, et al.
Publicado: (2024)
por: Fébba, Davi M, et al.
Publicado: (2024)
PDDFormer: Pairwise Distance Distribution Graph Transformer for Crystal Material Property Prediction
por: Shen, Xiangxiang, et al.
Publicado: (2024)
por: Shen, Xiangxiang, et al.
Publicado: (2024)
DREAMS: Density Functional Theory Based Research Engine for Agentic Materials Simulation
por: Wang, Ziqi, et al.
Publicado: (2025)
por: Wang, Ziqi, et al.
Publicado: (2025)
Ejemplares similares
-
Ontology-based knowledge graph infrastructure for interoperable atomistic simulation data
por: Guzman, Abril Azocar, et al.
Publicado: (2026) -
Ontology-aligned structuring and reuse of multimodal materials data and workflows towards automatic reproduction
por: Ravari, Sepideh Baghaee, et al.
Publicado: (2026) -
Self-Supervised Learning with Generative Adversarial Networks for Electron Microscopy
por: Kazimi, Bashir, et al.
Publicado: (2024) -
Towards knowledge-based workflows: a semantic approach to atomistic simulations for mechanical and thermodynamic properties
por: Guzman, Abril Azocar, et al.
Publicado: (2026) -
AtomWorld: A Benchmark for Evaluating Spatial Reasoning in Large Language Models on Crystalline Materials
por: Lv, Taoyuze, et al.
Publicado: (2025)