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. Atom-JEPA: Joint-Embedding Predictive Architecture for 3D Atomistic Systems

    Oct 6, 2026Kasper Helverskov Petersen, Rasmus Hannibal Tirsgaard, François R J Cornet +2Joint-Embedding Predictive ArchitectureMaterials Property Prediction

    Department of Applied Mathematics and Computer Science Technical University of Denmark

  2. Mathematical Invariant-Enabled Topological Neural Networks for Molecular and Materials Property Prediction

    Oct 6, 2026Yiming Ren, Xiang Liu, Mustafa Hajij +2Materials Property PredictionMolecular Property Prediction

    Department of Mathematics, University of Georgia, Athens, GA 30602, USA. · Department of Data Science, University of San Francisco, CA 94117, USA. · Department of Computer Science and Technology, Cambridge University, Cambridge, United Kingdom. +2

  3. ImpactMat: Continuous Material Estimation for Inverse Impact Sound Rendering

    Oct 5, 2026Hyebin Cho, Bumsoo Kim, Joon Son ChungInverse RenderingMaterials Property Prediction

    Korea Advanced Institute of Science and Technology, South Korea · Chung-Ang University, South Korea

  4. ElectrolyteFM: Unifying Electrolyte Property Prediction through Cross-Property Knowledge Learning

    Sep 30, 2026Jiaxin Yu, Shuo Wang, Peng Wang +2Multi-Task LearningMaterials Property Prediction

    VoltaAI, Beijing, China · Renmin University of China, Beijing, China

  5. Measuring trainable degrees of freedom in materials graph neural networks: a random-subspace intrinsic dimension analysis

    Sep 28, 2026Shehroz Ahmad Shoaib, Kangming LiIntrinsic DimensionalityGraph Neural Networks

    Physical Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. · Department of Electrical Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.

  6. Growth-Inspired Graph Generation and Inverse Design of Mechanical Lattices via Dot Matrices Database Augmentation and GCNN

    Sep 24, 2026Weiyun Xu, Jiamu LiuGraph GenerationStructural Mechanics

    Department of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, USA · State Key Laboratory of Clean and Efficient Turbomachinery Power Equipment, Department of Mechanical Engineering, Tsinghua University, Beijing, 100084, China

  7. An open benchmark for machine learning-based polymer property prediction

    Sep 22, 2026Robert W. Learsch, Nicholas Liesen, Daniel S. Levine +2Materials Property Prediction

    Lawrence Livermore National Laboratory · FAIR at Meta

  8. Physics-residual machine learning predicts oxygen-evolution catalyst activity beyond the training range from sparse polarization measurements

    Sep 20, 2026Yong-Woon Kim, Jihyeok Lee, Sungtae Park +2OOD GeneralizationMaterials Property Prediction

    Department of Computer Engineering, Jeju National University, Jeju 63243, South Korea · Green Hydrogen Global Leading Research Center, Jeju National University, Jeju 63243, South Korea · Faculty of Applied Energy System, Jeju National University, Jeju 63243, South Korea +2

  9. Physics-based prediction, uncertainty quantification and decision-making for IN718 crystallographic texture intensity across LPBF defocus regimes

    Sep 16, 2026Yisheng Lu, John Riris, Jie Song +2Materials Property PredictionPhysics-Informed ML

    Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA 24061, USA · Department of Aerospace & Ocean Engineering, Virginia Tech, Blacksburg, VA 24061, USA · VT Made, Virginia Tech, Blacksburg, VA 24061, USA +1

  10. Robust and Efficient AI Frameworks for Scalable Material Design and Property Prediction

    Sep 15, 2026Kishalay DasGraph SSLMaterials Property Prediction

  11. Neural-Network Solutions to Real-Space Charge Density and Generalization

    Sep 14, 2026Yuxuan Zeng, Taoyuze Lv, Zhicheng ZhongNeural Surrogate ModelingEquivariant Neural Networks

    School of Artificial Intelligence & Data Science, University of Science and Technology of China · Suzhou Institute for Advanced Research, University of Science and Technology of China

  12. Prescreening Point Defects in Semiconductors With Machine Learning

    Sep 13, 2026Paul Karlsson, Joel Davidsson, Rickard ArmientoMaterials Property PredictionPhysics-Informed ML

    Department of Physics, Chemistry and Biology, Linköping University, Linköping, Sweden

  13. A Large Open Multi-Energy Corpus of Soil Compaction Tests, with Machine-Learning Baselines

    Sep 3, 2026Sompote Youwai, Chana Phutthananon, Warat KongkitkulBenchmark ConstructionMaterials Property Prediction

    AI Research Group, Department of Civil Engineering King Mongkut’s University of Technology Thonburi 126 Pracha Uthit Road, Bang Mod, Thung Khru, Bangkok 10140, Thailand

  14. HiPoly: a hierarchical polymer-native AI framework for property prediction and generative design

    Sep 2, 2026Ge Sun, Gervasio Zaldivar, Yuan Tian +5Materials Property PredictionMaterials Science

    Department of Chemical and Biomolecular Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, USA · Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL, USA · Department of Computer Science, Courant Institute of Mathematical Sciences, New York University, New York, NY, USA +3

  15. CAHR-Net: Condition-Adaptive Hysteresis Reconstruction for Compact and Interpretable Magnetic Core Loss Modeling

    Sep 2, 2026Chunye Gong, Cong YaoMaterials Property PredictionPhysics-Informed ML

    College of Computing, National University of Defense Technology, Changsha 410073, China · National Supercomputer Center in Tianjin, Tianjin 300457, China · Laboratory of Digitizing Software for Frontier Equipment, National University of Defense Technology, Changsha 410073, China

  16. Analytic Dynamics: Learning Physics-Grounded Representation for Fast Intrinsic Dynamics Inference from Monocular Videos

    Aug 31, 2026Jailing Lin, Jikuan Zhang, Jianhua SunMaterials Property PredictionVideo Representation Learning

    School of Artificial Intelligence, Shanghai Jiao Tong University

  17. Learning Materials Properties from Scarce Labels and Unlabeled Crystals

    Aug 31, 2026Wentao Li, Yizhe Chen, Jiangjie Qiu +3Materials Property PredictionPseudo-Labeling

    1Beijing Key Laboratory of Artificial Intelligence for Advanced Chemical Engineering Materials, State Key Laboratory of Chemical Engineering and Low-Carbon Technology, Department of Chemical Engineering, Tsinghua University

  18. The parity gap in crystal tensor prediction

    Aug 19, 2026Can Polat, Mustafa Kurban, Erchin Serpedin +1Equivariant Neural NetworksMaterials Property Prediction

    Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas, USA · Department of Electrical and Computer Engineering, Texas A&M University at Qatar, Doha, Qatar · Department of Prosthetics and Orthotics, Ankara University, Ankara, Turkey +1

  19. Temperature-Driven Sequential Modeling for the Prediction of Annual Power Conversion Efficiency Profiles of Organic Photovoltaic Materials: Douala Case Study

    Aug 9, 2026Steve Cabrel Teguia Kouam, Rockefeller Rockefeller, Raoult Dabou Teukam +4Surrogate ModelingTime Series Forecasting

    Department of Physics, Faculty of Science, University of Douala, Douala, PO. Box 24157, Littoral, Cameroon. · Division of Applied Mathematics, Faculty of Science, Stellenbosch University, Stellenbosch, South Africa. · Department of Engineering, University of Quebec in Abitibi-T´emiscamingue, Quebec, Canada. +1

  20. Vision Meets WiFi: Physics-Grounded Estimation of Volumetric Mechanical Properties

    Aug 7, 2026Ali Bahri, Hongliang Li, Soufiane Lamghari +2Object-Centric Representation LearningMaterials Property Prediction

    Huawei Noah’s Ark Lab, Canada · Huawei Noah’s Ark Lab, Hong Kong SAR, China

  21. Symbolic Machine Learning for Vapor-Liquid Equilibrium Prediction in Cx-N2 Binary Mixtures

    Aug 6, 2026Bongseok Kim, Suman Chakraborty, Gary Huang +3Materials Property PredictionSymbolic Regression

    Purdue University, School of Mechanical Engineering, 47906, IN, United States · Purdue University, School of Aeronautics and Astronautics, 47906, IN, United States · Purdue University, Department of Mathematics, 47906, IN, United States

  22. Accelerating nanodrug development in continuous flow systems using informed prediction models based on low-cost surrogate nanoparticles

    Aug 6, 2026Kai Dahms, Eilien Heinrich, Jochen Schmid +3Surrogate ModelingMaterials Property Prediction

    Fraunhofer Institute for Microengineering and Microsystems (IMM), 55129 Mainz, Germany · Fraunhofer Institute for Industrial Mathematics (ITWM), 67663 Kaiserslautern, Germany

  23. Distribution-Free Conformal Prediction for Steel Fatigue Strength: Marginal Validity Is Not Enough

    Aug 5, 2026Irene BoruahConformal PredictionMaterials Property Prediction

    Department of Mechanical Engineering, Dibrugarh University Institute of Engineering and Technology, Dibrugarh, 786004, Assam, India.

  24. A Physics-Informed Hybrid Neural Operator for Transient Magnetization Prediction in Power Magnetics

    Aug 3, 2026Yachao Zhu, Qiujie Huang, Sinan Li +3Materials Property PredictionPhysics-Informed Neural Operators

    School of Electrical and Computer Engineering, the University of Sydney, Darlington, NSW, 2008, Australia · National Railway Research and Design Institute of Signal and Communication, Beijing 100070, China

  25. Interpretable machine learning for predicting splitting strength of asphalt concrete: insights from SHAP analysis

    Aug 2, 2026Jianglei Xing, Xiao Tan, Dongzhao Jin +3Materials Property PredictionMaterials Science

    College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing, Jiangsu, 210024, China · State Key Laboratory of Water Disaster Prevention, Nanjing, Jiangsu, 210024, China · Department of Civil, Environmental, and Geospatial Engineering, Michigan Technological University, Houghton, Michigan, 49931, United States +3

  26. Ordered-to-disordered transfer learning with graph neural networks for formation-energy and HOMO-LUMO gap prediction in high-entropy perovskite oxides

    Jul 31, 2026Panupol Untarabut, Narjes Jomaa, Sylvian Cadars +4Graph Neural NetworksMaterials Property Prediction

    University of Limoges, CNRS, IRCER, UMR 7315, F-87000, Limoges, France

  27. Predicting Steel Fatigue Life from Micrographs Using Physics-Informed Deep Learning

    Jul 30, 2026Aryuemaan Kumar ChowdhuryMaterials Property PredictionMicroscopy Image Analysis

    Department of Lightweighting Engineering, Indian Institute of Technology Hyderabad, India · Research & Development, Oscowl AI, Hyderabad, India

  28. MatCreatioNN: Machine learning-guided computational discovery of photocatalysts for environmental applications

    Jul 29, 2026Satya KokondaMaterials Property PredictionMaterials Science

    Department of Chemistry, School of Engineering, Charter School of Wilmington, 100 N Dupont Rd, Wilmington, DE 19807, United States of America

  29. Generative and multimodal AI for materials prediction and design: Progress, challenges, and perspectives

    Jul 22, 2026Xianyuan Liu, Charles Anjah, Benjamin E. Jolly +9Materials Property PredictionMaterials Science

    School of Computer Science, University of Sheffield, Sheffield, UK · Centre for Machine Intelligence, University of Sheffield, Sheffield, UK · School of Chemical, Materials and Biological Engineering, University of Sheffield, Sheffield, UK +3

  30. PhysCoRe: Physics-Corrected Residual World Models for Material-Aware Deformable Dynamics

    Jul 22, 2026Haocheng Yin, Shuohan Tao, Yongsheng Chen +1World Models for RoboticsDeformable Object Manipulation

    Georgia Institute of Technology

  31. 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

  32. 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

  33. 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

  34. 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

  35. 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

  36. 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

  37. 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

  38. 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

  39. 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.

  40. 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

  41. 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

  42. 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

  43. 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

  44. 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

  45. 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

  46. 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

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

    Jun 19, 2026Krishna Teja VepaMaterials Property PredictionVirtual Screening

    Independent Researcher†

  48. 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

  49. 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

  50. 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

  51. 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

  52. 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

  53. 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

  54. 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

  55. 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

  56. 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

  57. 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

  58. 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

  59. 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

  60. 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