Materials Property Prediction

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9 papers in the last four weeks, up 50% on the four weeks before. 0.1% of all new papers.

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  1. GQD-AdsNet: Graph Neural Networks Unlock Rapid Exploration of Transition Metal Adsorption on Graphene Quantum Dots

    Jul 20, 2026Lara Goncebat, Rodrigo Echeveste, Matías Gerard +3Materials Property PredictionMaterials Science

    Instituto de Química Aplicada del Litoral IQAL · Instituto de Qu´ımica Aplicada del Litoral IQAL (UNL-CONICET) Santa Fe, Argentina · Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional sinc +3

  2. Harnessing disorder to decouple extension and shear in kirigami metamaterials

    Jul 18, 2026Haomin Yu, Hanxun Jin, Mingxuan Bi +5Structural MechanicsMaterials Property Prediction

    NSF Science and Technology Center for Engineering MechanoBiology, Washington University in St. Louis, St. Louis, Missouri, 63130, USA. · Department of Mechanical Engineering & Materials Science, Washington University in St. Louis, St. Louis, Missouri, 63130, USA. · Department of Mechanical and Materials Engineering, University of Cincinnati, Cincinnati, Ohio, 45221, USA. +2

  3. Dual-Level Atomic and Coordination Geometry Learning for Crystal Property Prediction Using Graph Neural Networks

    Jul 17, 2026Sanjay ChakrabortyGraph Neural NetworksMaterials Property Prediction

    Department of Computer and Information Science (IDA), REAL, AIICS, Linköping University, Linköping, Sweden

  4. Probabilistic Physics-Informed Neural Networks for Estimating Heterogeneous Elastic Properties from Low-Resolution and Noisy Displacement Data

    Jul 16, 2026Tatthapong Srikitrungruang, Jaesung LeeStructural MechanicsMaterials Property Prediction

    Wm Michael Barnes 64 Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, 77843, USA

  5. AutoMatBench: An Automatic Optimization Toolkit for the Acceleration of Material Properties Prediction Benchmarking

    Jul 13, 2026Hongxiao Li, Wanling GaoBenchmark DesignOOD Generalization

    Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China · University of Chinese Academy of Sciences, Beijing, China

  6. Incremental Transformer for Surrogate-Based Inverse Design of Geopolymer Mixtures

    Jul 12, 2026Giansalvo Cirrincione, Filippo GrassiaSurrogate ModelingMaterials Property Prediction

    Laboratory of Innovative Technologies (LTI, EA 3899) University of Picardie Jules Verne, Amiens, 80025, Hauts-de-France, France

  7. Machine Learning-based Correlation of Charpy Impact Properties Between Sub-sized and Standard-sized Specimens for Nuclear Structural Materials

    Jul 11, 2026Yugandhar Kasala Sreenivasulu, Isshu Lee, John W. Merickel +5Materials Property PredictionMaterials Science

    University of Idaho, Department of Computer Science, Moscow, ID 83843, USA · Idaho National Laboratory, Idaho Falls, ID 83415, USA · Department of Computer Science, University of Texas at El Paso, El Paso, TX, United States

  8. Model Agnostic Graph Prompt Learning for Crystal Property Prediction

    Jul 9, 2026Shrimon Mukherjee, Kishalay Das, Partha Basuchowdhuri +2Graph Neural NetworksPrompt Learning

    School of Mathematical & Computational Sciences, Indian Association for the Cultivation of Science, Kolkata, India · Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, India

  9. Beyond Thermal Imaging: Inferring Thermophysical Properties from Time-Resolved Thermal Observations

    Jul 8, 2026Chenghao Xu, Malcolm Mielle, Olga FinkThermal Imaging3D Reconstruction

    Intelligent Maintenance and Operations Systems, ´Ecole polytechnique f´ed´erale de Lausanne, Station 18, Lausanne, 1015, Vaud, Switzerland. · Schindler Lab EPFL, Schindler Holding AG, Station 18, Lausanne, 1015, Vaud, Switzerland.

  10. Accurate, Interdisciplinary and Transparent Structure-property Understanding with Deep Native Structural Reasoning

    Jul 8, 2026Chen Tang, Yizhou Wang, Jianyu Wu +26Scientific ReasoningMaterials Property Prediction

    Shanghai Artificial Intelligence Laboratory, China. · The Chinese University of Hong Kong, Hong Kong. · Shanghai Jiao Tong University, China. +8

  11. Optimizing Expert-Designed Crystal Graph Networks for Band-Gap Prediction with an Autonomous LLM Research Loop

    Jun 29, 2026Chenmu Zhang, Boris I. YakobsonGraph Neural NetworksLarge Language Model-Guided Optimization

    Department of Materials Science and NanoEngineering Rice University Houston, TX 77005, USA

  12. On Surrogate Modeling of Static Response of AM Short-Fiber Thermoplastics Using Graph Neural Networks

    Jun 27, 2026Pharindra Pathak, Vipin Kumar, Trenton M. Ricks +2Neural Surrogate ModelingStructural Mechanics

    Auburn University, Oakridge National Lab, NASA Glenn Research Center, Auburn University, Auburn University · Graduate Student, Department of Aerospace Engineering, Auburn University, Auburn, AL · Sr. R&D Staff Member, Manufacturing Science Division, ORNL, Knoxville, TN +3

  13. Surrogate-Gated Generation and Foundation-Model Embeddings for Bayesian Materials Design

    Jun 26, 2026Sk Md Ahnaf Akif Alvi, Jan Janssen, Danny Perez +2Surrogate-Assisted OptimizationBayesian Optimization

    Department of Materials Science and Engineering, Texas A&M University, College Station, TX 77843, USA · Theoretical Division T-1, Los Alamos National Laboratory, Los Alamos, NM 87544, USA · Max-Planck-Institute for Sustainable Materials, Düsseldorf, Germany 40237 +3

  14. Physics-Informed Modeling for Wood Thermal Analysis and Prediction

    Jun 22, 2026Jingren Xie, Alex John Buckthal, Ryan Anthony O'Connor +2Thermal ImagingMaterials Property Prediction

    Technical University of Denmark Denmark · Pioneer Centre for AI Denmark · The Royal Danish Academy Denmark

  15. ARIA: A Causal-Aware Framework for Rescuing LLM Reasoning in Trustworthy Materials Discovery

    Jun 21, 2026Yi Cao, Liaoyaqi Wang, Jieneng Chen +3Knowledge Augmentation for Language ModelsMaterials Property Prediction

  16. Mat-Pref: Verifiable-Reward Training Improves Compositional Reasoning in Inorganic Materials

    Jun 20, 2026Sarrah R. Mikhail Leung, Taehan Kim, Jeongbin ParkCompositional ReasoningRL for Language Model Reasoning

    University of California, Berkeley · 2Machine Learning at Berkeley · University of Michigan

  17. Computational references are not experiments: pre-registered validation of machine-learned sodium-cathode voltages

    Jun 19, 2026Krishna Teja VepaMaterials Property PredictionVirtual Screening

    Independent Researcher†

  18. Multi-Head Attention-Based Feature Extractor Integration with Soft Actor-Critic for Porosity Prediction and Process Parameter Optimization in Additive Manufacturing

    Jun 18, 2026Kianoush Aqabakee, Leonardo StellaMaterials Property PredictionSoft Actor-Critic

    Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran, and Department of Mechanical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran · School of Computer Science, University of Birmingham, Birmingham B15 2TT, United Kingdom

  19. Equivariant Graph Neural Networks Improve Optical Spectra Prediction for Materials Screening

    Jun 17, 2026Kasper Helverskov Petersen, François R J Cornet, Martin Ovesen +3Materials Property PredictionEquivariant GNNs

    Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark · Department of Physics, Technical University of Denmark, Kongens Lyngby, Denmark

  20. Robust and Interpretable Adaptation of Equivariant Materials Foundation Models via Sparsity-promoting Fine-tuning

    Jun 17, 2026Youngwoo Cho, Seunghoon Yi, Wooil Yang +6Machine Learning Interatomic PotentialsEquivariant Neural Networks

    KAIST · Seoul National Univ. · KIAS +2

  21. Adaptive Volumetric Mechanical Property Fields Invariant to Resolution

    Jun 16, 2026Rishit Dagli, Donglai Xiang, Vismay Modi +4Materials Property Prediction3D Representation Learning

    NVIDIA · University of Toronto

  22. InvDesMobility: a reliability-gated first-principles feedback framework for closed-loop materials discovery

    Jun 15, 2026Wen-Kao Li, Ze-Feng Gao, Peng-Jie Guo +2Materials Property PredictionAutonomous Scientific Discovery

    School of Physics and Key Laboratory of Quantum State Construction (Ministry of Education), Renmin University of China, Beijing 100872, China

  23. Distilling latent electrostatics from foundation machine learning interatomic potentials

    Jun 12, 2026Xiaoyu Wang, Bingqing ChengMachine Learning Interatomic PotentialsMaterials Property Prediction

    Department of Chemistry, UC Berkeley, California 94720, United States · Bakar Institute of Digital Materials for the Planet, UC Berkeley, California 94720, United States · Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, 94720, United States

  24. Modelling magnetic material properties with uncertainty-aware neural networks

    Jun 10, 2026Clemens Wager, Heisam Moustafa, Alexander Kovacs +10Uncertainty QuantificationMaterials Property Prediction

    Christian Doppler Laboratory for magnet design through physics informed machine learning, University for Continuing Education Krems, Wr. Neustadt, 2700, Austria · Vienna Doctoral School in Physics, Vienna, Austria · Department for integrated sensor systems, University for Continuing Education Krems, Wr. Neustadt, 2700, Austria +1

  25. Physics-Distilled Neural Network enabled by Large Language Models for Manufacturing Process-Property Predictive Modeling

    Jun 10, 2026Ge Song, Kiarash Naghavi Khanghah, Anandkumar Patel +2Neural Surrogate ModelingMaterials Property Prediction

    School of Mechanical, Aerospace and Manufacturing Engineering, University of Connecticut, Storrs, CT 06269 · Department of Mechanical & Aerospace Engineering, Rutgers, the State University of New Jersey, Piscataway, NJ 08854

  26. GPT-Micro: A large language paradigm for accelerated, inexpensive, and thermodynamics-consistent discovery of constitutive models in manufacturing

    Jun 6, 2026Soumik Dutta, Kiarash Naghavi Khanghah, Sania Shree +4ManufacturingMaterials Property Prediction

    Department of Mechanical and Aerospace Engineering, Rutgers University, USA · Department of Mechanical, Aerospace & Manufacturing Engineering, University of Connecticut, USA · Edison Welding Institute, USA +2

  27. Inverse design of bespoke interatomic potentials via active learning by information-matching

    Jun 6, 2026Yonatan Kurniawan, Logan D. Williams, Amit Samanta +6Uncertainty QuantificationMachine Learning Interatomic Potentials

    Department of Physics and Astronomy, Brigham Young University, Provo, UT, USA · Department of Physics and Astronomy, Brigham Young University, Provo, UT, USA. · Lawrence Livermore National Laboratory, Livermore, CA, USA +7

  28. Agentic multi-fidelity learning of quasiparticle and excitonic properties

    Jun 5, 2026Arnab Neogi, Aaron Forde, Christopher A. Lane +2AI Agents for Scientific DiscoveryMaterials Property Prediction

    Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA · Center for Integrated Nanotechnologies, Materials Physics and Applications Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA

  29. MatMind: A Structure-Activity Knowledge-Driven Generative Foundation Model for Materials Science

    Jun 5, 2026Zhan'ao Yao, Boxuan Zhang, Jingyuan Shu +10Materials Property PredictionCrystal Structure Generation

    State Key Laboratory of High Performance Ceramics, Shanghai Institute of Ceramics, Chinese Academy of Sciences, 1295 Dingxi Road, Shanghai, 200050, China. · Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China. · State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing, 100190, China. +5

  30. Reactivity-Informed Machine Learning for Performance Prediction and Design Space Exploration of Alkali-Activated Slag

    Jun 4, 2026Qiyao He, Zhanzhao Li, Kai GongMaterials Property PredictionMaterials Science

    Department of Civil and Environmental Engineering, Rice University, Houston, Texas 77005, United States. · Rice Advanced Materials Institute, Rice University, Houston, Texas 77005, United States · Ken Kennedy Institute, Rice University, Houston, Texas 77005, United States