Latest Research in Machine Learning in Materials Science
35 research papers · 2026 median publication year
Top Research Topics in Machine Learning in Materials Science
- Machine Learning in Materials Science — 6 papers
- Artificial Intelligence — 3 papers
- Software Engineering — 3 papers
- Geographic Information Systems Studies — 3 papers
- Computer Vision and Pattern Recognition — 2 papers
- Materials Science — 2 papers
- Databases — 2 papers
- Machine Learning — 2 papers
- Software Testing and Debugging Techniques — 2 papers
- Environmental Monitoring and Data Management — 1 papers
Highest-Cited Papers
- PVmatAgent: A Large Language Model (LLM) Agent for Perovskite Photovoltaic Material Design and Analysis
- HydroSuite-AI: a web-based LLM environment for hydrological code generation and execution for the hydrosuite open-source ecosystem
- Can MiniMax-H3 Reason About the Physical World? An Evaluation of Omni-Modal Generative Model
- Extracting ontology-compliant knowledge from scientific text describing irradiated materials using large language models
- Scaling LLM Agents for Materials Design through Hierarchical Collective Reasoning
- Large language model-enabled automated data extraction for concrete materials informatics
- IUU+DB: Tracking Illegal, Unreported, and Unregulated Fishing, Seafood Fraud, and Labor Abuse through LLM-driven Information Extraction
- Knowledge Graphs for Railway Accident Profiling: Research and Applications
- Data Engineering First Principles: A Constraint-Driven Framework for Designing Reliable, Scalable, and AI-Native Data Systems
- An analysis of the relationship of input metrics
- pykci: A Compact Urban Knowledge Graph for Semantic and Spatial Queries using LLMs
- QDAG: Declarative Composition of Reusable Analytics Methodologies at LinkedIn
- DataEX‐Sc: A Specialized Parsing Model for Materials Science Scatter Plots Based on Multi‐Strategy Fusion and Bidirectional Optimization
- Generative artificial intelligence for reliable mechanistic reasoning for corrosion
- The Potential of Granular Spatial Data
- Table-Based Text Parsing Methods for Polymer Science: A Comparative Study
- A Structure-Aware Hybrid Scheduling Framework for Mixed-Dependency Workflow Scheduling in V2X Testing
- Towards intelligent geospatial data discovery: a knowledge graph-driven multi-agent framework powered by large language models
- GeoNatureAgent Benchmark: Benchmarking LLM Agents for Environmental Geospatial Analysis Across Frontier and Open-Weight Foundation Models
- PeroMAS: A Multi-agent System of Perovskite Material Discovery