Materials Science

Follow this field Ask about this field

Recent momentum

emerging

0 papers in the last 28 days · 0.0% of indexed attention

Twelve weeks of publication activity for this topic as it is defined today.

Weekly history

Recent digests

What was published in this field, kept on the site without email delivery.

Period ending 2026-09-21

8 new papers

A weekly snapshot of new work published in Materials Science.

Period ending 2026-09-14

3 new papers

A weekly snapshot of new work published in Materials Science.

Period ending 2026-09-07

1 new paper

A weekly snapshot of new work published in Materials Science.

Inside this field

Focused directions

Focused topic

Data-Driven Materials Discovery

Within Materials Science

51 papersExplore

Focused topic

Materials Science

Within Materials Science

40 papersExplore

Focused topic

Crystal Structure

Within Materials Science

27 papersExplore

Focused topic

Cryo-Electron Microscopy

Within Materials Science

26 papersExplore

Focused topic

Crystal

Within Materials Science

26 papersExplore

Focused topic

Crystallographic Plane Indices

Within Materials Science

17 papersExplore

155 papers

Latest in Materials Science

Browse all topics →

Unlocking the Visual Record of Materials Science: A Large-Scale Multimodal Dataset from Scientific Literature
Jun 29, 2026Subham Ghosh, Shubham Tiwari, Mohammad Ibrahim +1Materials Science Image-Text Pairs
SFBench: The SciFy Scientific Feasibility Benchmark
Jun 28, 2026Cash Costello, James Mayfield, Elsbeth Turcan +7Benchmark Datasets Feasibility
Surrogate-Gated Generation and Foundation-Model Embeddings for Bayesian Materials Design
Jun 26, 2026Sk Md Ahnaf Akif Alvi, Jan Janssen, Danny Perez +2Data-Driven Materials Discovery Crystal
Substitution-Based Analysis of Structural Novelty for Generative Models of Materials
Jun 22, 2026Masahiro Negishi, Aron WalshCrystal Structure Crystal
Discovering Crystal Structure Prediction Algorithms with an AI Co-Scientist
Jun 22, 2026Kiyoung Seong, Nayoung Kim, Sungsoo AhnCrystal Structure Artificial Intelligence Scientists
SVGym (SciVerseGym): An Environment for Reinforcement Learning and Bayesian Optimization in Crystal Discovery
Jun 21, 2026Bin CaoCrystal Interatomic Potentials
ARIA: A Causal-Aware Framework for Rescuing LLM Reasoning in Trustworthy Materials Discovery
Jun 21, 2026Yi Cao, Liaoyaqi Wang, Jieneng Chen +3Data-Driven Materials Discovery Large Language Model Reasoning
Mat-Pref: Verifiable-Reward Training Improves Compositional Reasoning in Inorganic Materials
Jun 20, 2026Sarrah R. Mikhail Leung, Taehan Kim, Jeongbin ParkVast Chemical Space Verifiable Rewards
Atomistic Language Models Understand and Generate Materials
Jun 19, 2026Sathya Edamadaka, Krithik Ramesh, Ju Li +1Crystal Structure Graph Language Models
Speeding up the annotation process in semantic segmentation industrial applications
Jun 18, 2026Marta Fernandez-Moreno, Margarita Guerrero, Rosalia Rementeria +2Human Annotations Porous Media
Equivariant Graph Neural Networks Improve Optical Spectra Prediction for Materials Screening
Jun 17, 2026Kasper Helverskov Petersen, François R J Cornet, Martin Ovesen +3Graph Neural Networks Spectra
InvDesMobility: a reliability-gated first-principles feedback framework for closed-loop materials discovery
Jun 15, 2026Wen-Kao Li, Ze-Feng Gao, Peng-Jie Guo +2Data-Driven Materials Discovery Generative Inverse Design
NIMO: A Software Platform for Closed-Loop Materials Exploration with Diverse AI Algorithms
Jun 14, 2026Ryo Tamura, Naruki Yoshikawa, Koji Tsuda +1Data-Driven Materials Discovery Autoresearch
A Multi-Level Architecture for Reusable Materials Ontologies -- The OntoCrafter Ceramics Ontology (OCO) as Reference Implementation
Jun 12, 2026Thomas Pannek, Wolfgang GrondMaterials Science Ontology
LapidaryEngine: Fully Conversational Crystal Generation
Jun 12, 2026Yusei Ito, Yuta Suzuki, Tomoya Murata +1Crystal Generative Models
XRDiff: Crystal Structure Prediction from Powder X-Ray Diffraction Data Using Diffusion Models
Jun 12, 2026Nofit Segal, Mingda Li, Benjamin Kurt Miller +1Crystallographic Plane Indices Cryo-Electron Microscopy
Closed-loop discovery of out-of-distribution processing protocols by evolutionary search and uncertainty-aware learning
Jun 11, 2026Yu Liu, Stanislav Udovenko, Ching-Che Lin +4Data-Driven Materials Discovery Evolutionary Search
A green solvent screening tool for emerging materials via uncertainty aware, transformer enhanced transfer learning
Jun 11, 2026Ioannis Kouroudis, Simon Ternes, Zhaosu Gu +5Previous Machine-Learning-Based Implicit Solvent Data-Driven Materials Discovery
Range-Aware Bayesian Optimization for Discovering Diverse Designs within Target Property Windows
Jun 10, 2026Shengli Jiang, Jason Wu, Charles M. Schroeder +1Bayesian Optimization Multi-Objective Optimization
POPSICLE: Benchmark Datasets for Segmentation and Localization in CryoET
Jun 8, 2026Jonathan Schwartz, Utz Heinrich Ermel, C. Braxton Owens +6Cryo-Electron Microscopy Pixel-Level Annotation
Context-Aware Deep Learning for Defect Classification in Atomic-Resolution STEM
Jun 8, 2026Jiadong Dan, Cheng Zhang, Leyi Loh +5Transmission Electron Microscopy Scalable Defect Detection
Physics-Guided Sequence-Based Generative Framework for Acoustic Metamaterial Inverse Design
Jun 8, 2026Yijie Li, Jiahao Xu, Ching-Chih Tsao +2Metamaterials Acoustic
MechLens: Late Crystallization of Factual Knowledge Explains Intervention Effectiveness in Language Models
Jun 6, 2026Xueping GaoFactual Recall Hallucination Mitigation
A physical adaptive material motor unit neural network: a hygromorph composite material machine
Jun 5, 2026Charles de Kergariou, David Correa, Adam W. Perriman +2Composites Soft Pneumatic Actuators
MatMind: A Structure-Activity Knowledge-Driven Generative Foundation Model for Materials Science
Jun 5, 2026Zhan'ao Yao, Boxuan Zhang, Jingyuan Shu +10Data-Driven Materials Discovery Materials Science
Towards Automated Discovery: A Review of Generative Models, Multimodal Learning and Closed-Loop Workflows in Inverse Materials Design
Jun 1, 2026Anand Babu, Rogério Almeida Gouvêa, Gian-Marco RignaneseData-Driven Materials Discovery Generative Inverse Design
Self-Revising Discovery Systems for Science: A Categorical Framework for Agentic Artificial Intelligence
May 31, 2026Fiona Y. Wang, Markus J. BuehlerScientific Discovery Generalized Category Discovery
Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach
May 31, 2026An Vuong, Minh-Hao Van, Chen Zhao +1Materials Science
CryoProt: A Protein Pretraining Framework with Cross-Box Interactions on Cryo-EM Density Maps
May 31, 2026Dan Luo, Xuan Lin, Peng Zhou +4Cryo-Electron Microscopy Protein Data Bank
Benchmark Dataset for Catalysis on 2D MXenes
May 30, 2026Pavlo Melnyk, Anmar Karmush, Mårten Wadenbäck +4Heterogeneous Catalysis First-Principles Calculation
Latent Diffusion Pretraining for Crystal Property Prediction
May 30, 2026Shrimon Mukherjee, Kishalay Das, Partha Basuchowdhuri +2Crystal Structure Crystal
Coupling Language Models with Physics-based Simulation for Synthesis of Inorganic Materials
May 29, 2026Edward W. Staley, Tom Arbaugh, Michael Pekala +6Data-Driven Materials Discovery Automated Synthesis Techniques
A Padding Method for Enhanced Encoding of Inorganic Structures with Varying Chemical Compositions
May 29, 2026Thang Dang, Haderbache Amir, Tzanakakis Alexandros +1Crystallographic Plane Indices Molecular Generation
OmniMatBench: A Human-Calibrated Multimodal Reasoning Benchmark Across 19 Materials Science Subfields
May 28, 2026Wanhao Liu, Jiaqing Xie, Qian Tan +10Materials Science Multimodal Reasoning Benchmarks
From Blind Guess to Informed Judgment: Teaching LLMs to Evaluate Materials by Building Knowledge-Augmented Preference Signals
May 28, 2026Yeyong Yu, Wenya Hu, Xing Wu +1Data-Driven Materials Discovery Large Language Model Evaluation
CrystalXRD-Bench: Benchmarking Vision-Language Models for XRD Peak Indexing Across Diverse Crystalline Materials
May 28, 2026Chengliang Xu, Xiaogang Li, Peiyao Xiao +3Cryo-Electron Microscopy Multimodal Benchmarks
MatFormBench: A Benchmarking Evaluation Framework for Target-Driven Materials Formulation
May 26, 2026Linhan Wu, Chenxi Wang, Chuhan Yang +2Data-Driven Materials Discovery Generative Inverse Design
UNATE: UNsupervised ATomic Embedding for crystal structures property prediction
May 25, 2026Laura Solà-Garcia, Àlex Solé, Javier Ruiz-HidalgoCrystal Structure Molecular Property Prediction
AutoDFT: A Closed-Loop Multi-Agent Framework for Autonomous DFT Calculations
May 25, 2026Penghui Yang, Zhonghan Zhang, Yue Li +6Density Functional Theory First-Principles Calculation
LLM-driven design of physics-constrained constitutive models: two agents are better than one
May 22, 2026Marius Tacke, Matthias Busch, Kian Abdolazizi +4Physics-Aware Models Artificial Intelligence Models
AIMBio-Mat: An AI-Native FAIR Platform for Closed-Loop Materials Discovery and Biomedical Translation
May 20, 2026D. -M. Mei, K. Acharya, C. M. Adhikari +51Data-Driven Materials Discovery Biomedical Knowledge
Miller-Index-Based Latent Crystallographic Fracture Plane Reasoning and generation with Vision-Language Models
May 19, 2026Qinwu Xu, Xiaofu Ma, Yifan JiangCrystallographic Plane Indices Latent Variable
Atomistic Modeling of Chemical Disorder in Materials: Bridging Classical Methods and AI-Assisted Approaches
May 18, 2026Jiayu Peng, Peichen ZhongData-Driven Materials Discovery Molecular Dynamics
Qumus: Realization of An Embodied AI Quantum Material Experimentalist
May 18, 2026Lihan Shi, Zhaoyi Joy Zheng, Xinzhe Juan +14Materials Science Artificial Intelligence Scientists
Real-time Multi-instrument Autonomous Discovery of Novel Phase-change Memory Materials
May 18, 2026Chih-Yu Lee, Haotong Liang, Ryan Kim +4Data-Driven Materials Discovery Resistive Random Access Memory
Universal Magnetic Structure Prediction from Atomic Coordinates with Near-Experimental Accuracy
May 15, 2026Abhijatmedhi Chotrattanapituk, Ryotaro Okabe, Eunbi Rha +6Magnetic Tunnel Junction Crystal Structure
CrystalBoltz: End-to-End Protein Structure Determination via Experiment-Guided Diffusion for X-Ray Crystallography
May 15, 2026Minseo Kim, Huanghao Mai, Jay Shenoy +3Crystallographic Plane Indices Protein Data Bank
Composable Crystals: Controllable Materials Discovery via Concept Learning
May 14, 2026Nian Liu, Yuwei Zeng, Ryoji Kubo +7Crystal Data-Driven Materials Discovery
Crys-JEPA: Accelerating Crystal Discovery via Embedding Screening and Generative Refinement
May 14, 2026Nian Liu, Nikita Kazeev, Stephen Gregory Dale +8Crystal Molecular Generation
Agentic Design of Compositional Descriptors via Autoresearch for Materials Science Applications
May 14, 2026Matteo Cobelli, Stefano SanvitoData-Driven Materials Discovery Materials Science
CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation
May 14, 2026Yuyang Wu, Stefano Falletta, Delia McGrath +1Crystal Structure Crystallographic Plane Indices
OpenAaaS: An Open Agent-as-a-Service Framework for Distributed Materials-Informatics Research
May 13, 2026Peng Kang, Bixuan Li, Xiaoya Huang +5Data-Driven Materials Discovery Scientific Workflows
KadiAssistant: A conversational AI Agent for information retrieval in Kadi4Mat
May 13, 2026Adrian Cierpka, Mohammad Shafiqul Islam, Johannes Steinhülb +3Retrieval Task Knowledge Graphs
Generating Symmetric Materials using Latent Flow Matching
May 11, 2026Anmar Karmush, Cedric Mathieu Brandenburg, Soheil Ershadrad +3Crystal Structure Molecular Generation
Modeling Atomic Conformational Ensembles of Proteins via Test-Time Supervision of Boltz-2 on Cryo-EM Density Maps
May 11, 2026Jay Shenoy, Miro Astore, Axel Levy +3Conformational Ensembles Cryo-Electron Microscopy
CrystalREPA: Transferring Physical Priors from Universal MLIPs to Crystal Generative Models
May 9, 2026Chengqian Zhang, Yucheng Jin, Duo Zhang +2Crystal Interatomic Potentials
From Holo Pockets to Electron Density: GPT-style Drug Design with Density
May 9, 2026Jiahao Chen, Letian Gao, Yanhao Zhu +4Drug Design Molecular Generation
SLayerGen: a Crystal Generative Model for all Space and Layer Groups
May 7, 2026Rees Chang, Andrew Novick, Ryan P Adams +1Crystal Structure Crystal
LLM-Guided Open Hypothesis Learning from Autonomous Scanning Probe Microscopy Experiments
May 7, 2026Boris Slautin, Utkarsh Pratiush, Yu Liu +2Hypothesis Generation Data-Driven Materials Discovery
XDecomposer: Learning Prior-Free Set Decomposition for Multiphase X-ray Diffraction
May 7, 2026Hanyu Gao, Bin Cao, Yunyue Su +2Cryo-Electron Microscopy Crystallographic Plane Indices

Jun 29, 2026 · cs.CVJ/K move · Enter open · S save

Unlocking the Visual Record of Materials Science: A Large-Scale Multimodal Dataset from Scientific Literature

Subham Ghosh, Shubham Tiwari, Mohammad Ibrahim, Abhishek Tewari

Mehta Family School of Data Science and Artificial Intelligence Indian Institute of Technology Roorkee, Uttarakhand, India-247667 · Department of Metallurgical and Materials Engineering Indian Institute of Technology Roorkee, Uttarakhand, India-247667

The materials science literature encodes decades of experimental knowledge in figures, yet this visual record remains locked away and inaccessible to AI at scale. The core difficulty is structural: most scientific figures are compound, with a single caption describing multiple sub-panels simultaneously, making direct image-text pairing unreliable. We present MatMMExtract, an end-to-end open-source pipeline that resolves this by decomposing compound figures into individual sub-panels and generating structured, grounded annotations using a large language model guided by a curated materials science taxonomy. Applied to 14,810 open-access articles, MatMMExtract produces MatSciFig; 391,606 panel-level image-text pairs from 180,571 figures, each annotated with a sub-caption, a two-level visualisation category spanning 19 classes and over 100 subtypes, and a scientific summary. To enable accurate panel localisation, we introduce MaterialScope, a domain-specific detection dataset of 2,811 manually annotated materials science figures, on which a fine-tuned YOLO12-m detector achieves mAP_50 of 0.9227. Among six benchmarked language models, Gemini 3.1 Flash Lite delivers the best cost-quality trade-off for annotation generation, with 82% of outputs rated good and a hallucination rate of 4.8%. A dual-encoder retrieval baseline on MatSciFig achieves a 4.4 times improvement in R@1 over zero-shot CLIP, demonstrating the dataset's immediate utility for vision-language learning. All resources are released openly to the community.

Materials Science Image-Text Pairs Multimodal Dataset Scientific Discovery Annotations

Open paper Ask about it PDF