2D Microstructure Reconstruction for SEM via Non-local Patch-based Image Inpainting

A Machine Learning Approach for Predicting Melt Pool Size in Wire-feed DED Process

A Quantitative Phase-field Model for Study of Shape Memory Behavior and Elastocaloric Effect in CuAlBe

A Simulation Survey of Recrystallization Behavior in Al-xSi Microstructures Under Shear Loading Conditions

Accelerating Atomistic Monte Carlo Simulations with Autoregressive Models

Advancements in Discrete Dislocation Modeling of Slip Transmission through Equilibrium and Non-equilibrium Grain Boundaries

AI-assisted Analysis of Flame Stability

Analysis of Dendrite Growth and Microstructure Evolution during Solidification of Al 6061 via 2D and 3D Phase Field Models

Application of a Shape Moment Descriptor Set Towards a Robust and Transferable Description of Local Atomic Environments

Automatic Segmentation of Microstructures in Steel Using Machine Learning Methods

Bayesian Data Assimilation for Phase-field Simulation of Solid-state Sintering

Characterizing Atomistic Geometries and Potential Functions Using Strain Functionals

Characterizing the Length Dependence of High-Peierls-Stress Dislocations’ Mobility in BCC Crystals under Deformation at Finite Temperature from the Atomistic to the Mesoscale

Comparison of Correction Schemes for Charged Point Defects in 2D Materials

Computational Synthesis of Substrates by Crystal Cleavage

Deep Learning for Characterization of Deformation Induced Damage

Development of Machine Learned SNAP Potentials for Studying Radiation Damage in Materials

Dislocation Dipole Study on Material Hardening/Softening

Exascale-motivated Algorithm Development for Nano and Mesoscale Materials Methods

Full-field Stress Computation from Measured Deformation Fields: A Hyperbolic Formulation

Global Local Modeling of Melt Pool Dynamics and Bead Formation in Laser Bed Powder Fusion Process Using a Comprehensive Multi-Physics Simulation

Grain Boundary Network Optimization through Human Computation and Machine Learning

High Speed Artificial Neural Network Implementation of Interatomic Force Fields in Metals

Low Dimensional Polynomial Chaos Expansion Performance at Assessing Uncertainty in Creep Life Prediction of Grade 91 Steel

Machine Learning and Supercomputing to Accelerate the Development of ReaxFF Interatomic Potentials

Mechanistic Modeling of Point Diffusion in Polycrystals to Capture Different Diffusion-deformation Mechanisms

Model and Improved Dynamic Programming Algorithm for Optimization of Unplanned Slab Allocation in the Steel Plant

Modeling Static Recrystallization within the SPParKS Kinetic Monte Carlo Framework for Polycrystalline Materials

Multi-Information Source Bayesian Optimization Applied to Materials Design

Multi-scale Modeling of Hierarchical Microstructure in Ceramic Composites

Neural Network Model of He Diffusion in W-based High Entropy Alloys

Phase Field Dislocation Dynamics (PFDD) Modeling of Non-Schmid Effects in BCC Metals

Predicting Mechanical Property Parameters from Load-displacement Curve of Nanoindentation Test by Using Machine Learning Model

Preparing for Exascale Phase-field Simulations: Scalable, Performance-portable Precipitation Simulations

Real Time Boundary Condition Acquisition and Integration of Heats of Fusion and Phase Transformation Using an Implicit Finite Element Newton Raphson Based Approach for Thermal Behavior Prediction in Additively Manufactured Parts

Theory-infused Machine Learning Algorithms of Chemisorption at Metal Surfaces

Tusas: A Modern Computational Approach for Microstructure Evolution Toward Exascale

Understanding Grain Boundary Metastability Using the SOAP Descriptor and Unsupervised Machine Learning Techniques

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