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RESEARCH PAPER · npj Computational Materials · 2024

MLMD: a programming-free AI platform to predict and design materials

Jiaxuan Ma, Bin Cao, Shuya Dong, Yuan Tian, Menghuan Wang, Jie Xiong, Sheng Sun

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MLMD: a programming-free AI platform to predict and design materialsOriginalRepresentation Drift in Iterative Materials Learning Systems0Determinants of saturation magnetic flux density in Fe‐based metallic glasses: insights from machine‐learning models20Translating strain to stress: a single-layer Bi-LSTM approach to predicting stress-strain curves in alloys during hot deformation12Active learning-based research of foaming agent for EPB shield soil conditioning in gravel stratum7Crystal structure graph neural networks for high-performance superconducting critical temperature prediction5Predicting the properties of metamaterials consisting of curved-wall triangles using ensemble neural networks with interpretability9High‐Throughput Screening Technologies of Efficient Catalysts for the Ammonia Economy6Research on predicting the thermocompression deformation behavior of Mg–Li matrix composite using machine learning and traditional techniques6Recent machine learning-driven investigations into high entropy alloys: A comprehensive review37Machine learning-assisted creep life prediction and empirical formula generation for 9-12% Cr steel12Active learning-enabled the discovery of ultra-high saturation magnetization soft magnetic alloys5Large language models enabled intelligent microstructure optimization and defects classification of welded titanium alloys13AI4Materials: Transforming the landscape of materials science and enigneering25Algorithmic Curiosity as Scientific Method: A Conceptual Proposal for Exploration-Driven Materials AI0Introduction to AI in Research1Machine Learning Algorithms for Applications in Materials Science I2Wet chemistry nanoarchitectonics for nanocrystal-based films3Accelerated design of age-hardened Mg-Ca-Zn alloys with enhanced mechanical properties via machine learning9Research on glass-forming ability based on transformer and tabular data transformation4Interpretable Active Learning Identifies Iron‐Doped Carbon Dots With High Photothermal Conversion Efficiency for Antitumor Synergistic Therapy5DSMR: an AI framework for exploring combinations of data and algorithm to overcome efficiency-accuracy trade-off2Advances in Graphene-Based Flame-Retardant for Polystyrene Applications: Synthesis, Mechanisms, and Future Perspectives10Rare earth elements as emerging catalysts: A review of their role in enhancing DLFC and PEMFC performance5Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space4Self-Driving Laboratory for Accelerated On-Surface Synthesis under Ultrahigh Vacuum6Artificial intelligence-assisted next-generation biomaterials: From design and preparation to medical applications29Artificial Intelligence for Materials Discovery, Development, and Optimization171Evaluation of deep learning models applied to reservoir outflow prediction under extreme flood events1Materials informatics: A review of AI and machine learning tools, platforms, data repositories, and applications to architectured porous materials41Review: Recent progress in titanium alloys development via machine learning and high-throughput preparation4High-Performance Alloy Design of 10Cr Ferrite Steel: An Integrated Approach of Single-Objective Optimization and Machine Learning0Data‐Driven Design of Bimodal Networked Dielectric Elastomers for High‐Performance Artificial Muscles3Optimization of Johnson-Cook constitutive parameters of titanium alloy based on a machine learning-accelerated genetic algorithm3A survey of AI-supported materials informatics7A Computational Renaissance in High-Energy Density Materials (HEDMs) Research38Design of rust layer stabilizers for weathering steel guided by interpretable machine learning and Bayesian optimization7Potential applications of artificial intelligence in spent nuclear fuel reprocessing research: A review1Deep learning methods for 2D material electronic properties9Advances in structural engineering through artificial intelligence: methods, challenges and opportunities0Energy catalysis through high-entropy materials by experiment, computation, and artificial intelligence7Machine Learning’s Emergence in Predictive and Prescriptive Materials Design Modeling0Design of shape memory alloys with enhanced thermal management properties via adaptively constrained multi-objective optimization8Synergistic optimization of battery thermal management system manifolds utilizing Bezier surface and multi-objective Bayesian optimization0Advanced applications of triboelectric sensors across human body regions0Application of artificial intelligence in predicting and optimizing material properties3Machine Learning-Enhanced Molecular Dynamics: Current State, Challenges and Perspectives5Organic–Inorganic Metal Halide Perovskites: Toward Stability, Chirality, and AI-Guided Discovery1A comprehensive review of machine learning for superalloys: from data-driven prediction to intelligent design2Bioinspired Nanostructures for Combined Hydrophobicity and Light Propagation: From Natural Prototypes to Applications1Prediction of uranium adsorption performance by machine learning for sustainable seawater extraction4Machine learning applications in the design, optimization, and manufacturing of perovskite solar cells3Enhancing multi-component alloy composition prediction based on generative adversarial networks and proximal policy optimization2Accelerating Computational Material Discovery and Learning: First Experiences with MatterSim0Hierarchical microstructure-informed constitutive modeling of composite electrodes via transfer learning under multiaxial non-monotonic histories0Artificial Intelligence for Sustainable Ceramic and Refractory Materials: A PRISMA-Guided Systematic Review of Emerging Design Strategies, Industrial Applications, and Circular Raw Material Utilization0A Comparative Study of Structural Representations for 2D Materials: Insights from Dynamic Collision Fingerprint and Matminer Library0Towards sustainable pharmaceutical manufacturing: The rise of supercritical fluid technology0Improving predictive modeling in materials science based on data augmentation approach0Fatigue Data Infrastructure for Reliability Analytics: A Relational Database Framework for Traceable Fatigue Knowledge Integration0Autonomous laboratories for sustainable nanomaterials discovery0Microstructure analysis of corundum spinel material based on AI models0Advanced engineering of inorganic semiconductor nanowires: Materials-by-design for next-generation green energy technologies0

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