A Complete AI-Accelerated Workflow for Superconductor Discovery

A Data Structure and Collection System for Experimental Processes in Materials Science

A Generalizable, Accelerated, and Interpretable Artificial Intelligence Framework for Predicting Evolution of Materials Microstructure

A Generative Deep Learning Initialization Strategy to Accelerate Genetic Algorithms for Crystal Structure Prediction

A Machine Learning Approach to Optimize T5 Heat Treatment Conditions for Al-Si Alloys

A Materials Informatics Approach to Quantify Processing – Structure – Property Relationship in Boron Carbide Ceramics

A Novel Physics Informed Neural Network Framework for Solid State Phase Transformations

Accelerating Creep-Resistant Aluminum Alloy Design Through Generative AI-Driven Computational Models and Robust Validation

Accelerating Semiconductor Design with DFT and Deep Learning: Multiscale Modeling with Quantum Mechanical Accuracy

Adaptive Latent Space Tuning to Enable Characterizing Materials Dynamics Using Bragg Coherent Diffraction Imaging

Advanced Prediction of Crystalline Material Behavior Using Physics-Informed Neural Networks and Object-Oriented Crystal Plasticity Finite Element

Advancing Alloy Design: A Parameter-Free Statistical Approach to Predicting Stress Strain Curves of BCC Polycrystals

Advancing Automated Classification of Crystallographic Structures Using Synthetic Two-Dimensional X-Ray Diffraction Patterns and Deep Learning

AI-Powered Interface: Fully Automated Tool for LAMMPS Simulation and Analysis

AtomGPT: Atomistic Generative Pre-Trained Transformer for Forward and Inverse Materials Design

Bayesian Prediction and Optimization of Al-Ce-La-Nd-Mg-Ni Alloys’ Mechanical Properties Post Heat Treatment

Boosting Recyclable Plastic Sorting with AI-Generated Images and Vision Technology

Borides as Promising M2AX Phase Materials with High Elastic Modulus using Machine Learning and Optimization

Charting the Large Chemical Space of Zintl Phases Using Graph Neural Networks

Closed-Loop Discovery of Lunar In Situ Resource Utilization (ISRU) Constrained Manufacturable Materials

Comparison of Phenomenological and Machine Learning Approaches to Model Inconel 718 Recrystallization Mechanisms

Computational Design and Optimization of 2D Spinodal Metallic Metamaterials for Improved Structural Behavior

Construction of Physical Property Temperature-Dependency Benchmarks for High-Accuracy Machine Learning Models

Criteria for Statistical Equivalence of Predicted and Experimentally Observed Microstructures: Validation and Uncertainty Propagation

Data-Centric Engineering of Materials and Structures - Dissimilar Metal Welds as Use Case

Data-Driven Assessment and Selection of Magnetocaloric Materials by Grey Relational Analysis

Data-Driven Discovery of Materials Science Formulas via Neural Symbolic Regression

Data-Driven Study on Multi-Target Prediction of Mechanical Properties of Aluminum Alloys

Data Assimilation for Columnar Dendrite Growth Coupled with Large-Scale Phase-Field Simulations

Data Management of Through-Life Structural Integrity Assessment of Dissimilar Metal Welds for Nuclear Application

Decoratypes: A New Materials Taxonomy for ML-Guided Materials Discovery

Deep Gaussian Process Based Bayesian Optimization for Materials Discovery in High Entropy Alloy Space

Deep Learning-Based Image Denoising for Enhanced CT Image Reconstruction

Deep Learning Framework for Prediction of Phase Transformation Temperatures in Multicomponent Shape Memory Alloys

Determination of Phase-Field Model Parameters Using Machine Learning Approach

Developing an Oxidation Materials Ontology for Data-Driven Materials Design

Digital Twin Application for Carbon Fiber Reinforced Polymer Composite Manufacturing

Digital Twin Enhanced Spectral CT Imaging

Discovery of Quaternary Structural Materials Using Constrained Generative Models

Enhancing Computational Materials Research Through Large Language Model (LLM) Interfaces

Enhancing Materials Discovery in Complex Composition Spaces: FUSE Meets Generative ML

Extracting Complex Concentrated Alloys Properties from Scientific Literature with LLMs

First-Principles Database of Multi-Principal Element Alloys for High-Performance Structural Applications

Forward Prediction and Inverse Design of Additively Manufacturable Alloys via Autoregressive Language Models

From Pure Metals to Multi-Principal Element Alloys – A Physics-Informed Data-Driven Approach for Alloy Design

Generative Priors for Regularizing Ill-Posed Problems: Applications to 3D Polycrystalline RVE's

GrainPaint - A Multi-Scale Diffusion-Based Generative Model for Microstructure Reconstruction of Large-Scale Objects

High-Throughput Bayesian Calibration of Elastic-Plastic-Damage Model Parameters Using a Small Punch Test

Implications of X-CT Reliability to Determine Anomaly Distribution for Fatigue Assessment

Incorporating Field-Specific Physical Constraints into Machine Learning for Materials Science

Intelligent Optimization Algorithm-Based Optimization Model of Water Volume in Secondary Cooling Zone of Continuous Casting

Inverse Design of Architected Composite Materials with Desired Mechanical Behavior Based on Conditional Diffusion Model

Investigation of Phase-Field Data Assimilation System for Dendrite Growth Problem

KnowMat: Transforming Unstructured Material Science Literature into Structured Knowledge

Machine-Learning Structural Stability of Complex Intermetallic Phases

Machine Learning-Based Constitutive Model Parameter Estimation

MatFold: Systematic Evaluation of Generalization Errors in Materials Discovery Models

Minimizing Hysteresis in NiTi-Based Non-Platinum Group Metal (PGM) High Temperature Shape Memory Alloys via Experimentally Validated Neural Network Machine Learning

ML-DiCE: A Machine Learning Framework for Predicting Diffusion Coefficients in Impure Metallic and Multi-Component Alloy Media

Models of Magnetic Properties for Rapid Screening of Alternative Materials

Multi-Fidelity Deep Learning Approach for Designing Single-Phase BCC Refractory Multi-Principal Element Alloys (RMPEA) Across Various Temperatures

Navigating High-Dimensional Formulation Spaces with GP-Latent Variable Models for Dental Composites

Novel Superhard Materials Synthesis Using Generative ML

Ontology-Based Digital Representations of Materials Testing in the MaterialDigital Initiative

Optimizing Microstructure Prediction and Control in Advanced Structural Materials Using Deep Generative Models and Physics-Based Methods

Physics-Based Priors for Phase Classification in Alloy Design

Physics-Informed Machine Learning of Thermal Stress Evolution in Laser Metal Deposition

Predicting Microstructure-Property Linkage in Alloys Using Graph Neural Network

Prediction of Nitrogen Content in Converter Based on an LLE-RF Model

Quantifying Error and Uncertainty in Transmission Electron Microscopy Images of Irradiation Defects

Quantifying Uncertainty of Object Detection Models in Electron Microscopy

Rapid Crystal Structure Prediction with the Aid of AI Generative Model and Descriptor Based Optimization

Self-Supervised Learning (SSL) for Crystal Property Prediction via Structure Denoising

Sensitivity Analysis and Uncertainty Quantification in Process-Structure-Property of IN718

Structural Causal Learning with Atomistic Simulations for Advanced Materials

Structural Constraint Integration in Generative Model for Discovery of Quantum Material Candidates

Student’s T Process for Optimizing Material Properties

The Unsaturation Effect: Balanced Data Aggregation for Materials Informatics via Acquisition Functions

Towards a Digital Material Twin: Data-Oriented Microstructure-Property Relationships

Towards an Interpretable and Reliable Framework for Alloy Design in Thermomechanical Processing

Uncertainty Quantification In Crystal Plasticity Simulations Using Multimodal High-Energy Synchrotron X-Ray Experiments

Utilization of Neural Networks and Numerical Modeling for Microstructural Analysis of Aluminum 6060 Alloy Composites

Verification, Validation, and Uncertainty Quantification for Self-Driving Labs - Proof of Concept with Chocolate as Frugal Twin

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