Integrating Materials and Manufacturing Innovation

Papers
(The median citation count of Integrating Materials and Manufacturing Innovation is 3. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-03-01 to 2024-03-01.)
ArticleCitations
Is Domain Knowledge Necessary for Machine Learning Materials Properties?34
Unsupervised Machine Learning Via Transfer Learning and k-Means Clustering to Classify Materials Image Data31
MAUD Rietveld Refinement Software for Neutron Diffraction Texture Studies of Single- and Dual-Phase Materials28
Effect of Particle Spreading Dynamics on Powder Bed Quality in Metal Additive Manufacturing27
Location-Specific Microstructure Characterization Within IN625 Additive Manufacturing Benchmark Test Artifacts27
Effects of Boundary Conditions on Microstructure-Sensitive Fatigue Crystal Plasticity Analysis24
Extracting Knowledge from DFT: Experimental Band Gap Predictions Through Ensemble Learning21
Model Selection and Evaluation for Machine Learning: Deep Learning in Materials Processing20
Numerical Evaluation of Advanced Laser Control Strategies Influence on Residual Stresses for Laser Powder Bed Fusion Systems19
AFRL Additive Manufacturing Modeling Series: Challenge 4, 3D Reconstruction of an IN625 High-Energy Diffraction Microscopy Sample Using Multi-modal Serial Sectioning18
Benchmark AFLOW Data Sets for Machine Learning18
Mining the Correlations Between Optical Micrographs and Mechanical Properties of Cold-Rolled HSLA Steels Using Machine Learning Approaches16
Crystal Plasticity Finite Element Modeling of Extension Twinning in WE43 Mg Alloys: Calibration and Validation16
Microstructure Characterization and Reconstruction in Python: MCRpy15
Model-Based Feature Information Network (MFIN): A Digital Twin Framework to Integrate Location-Specific Material Behavior Within Component Design, Manufacturing, and Performance Analysis14
A Harmony Search-Based Wrapper-Filter Feature Selection Approach for Microstructural Image Classification14
Estimation of Local Strain Fields in Two-Phase Elastic Composite Materials Using UNet-Based Deep Learning14
An Active Learning Approach for the Design of Doped LLZO Ceramic Garnets for Battery Applications13
A Probabilistic Fatigue Framework to Enable Location-Specific Lifing for Critical Thermo-mechanical Engineering Applications12
The AFRL Additive Manufacturing Modeling Challenge: Predicting Micromechanical Fields in AM IN625 Using an FFT-Based Method with Direct Input from a 3D Microstructural Image12
AFRL Additive Manufacturing Modeling Series: Challenge 4, In Situ Mechanical Test of an IN625 Sample with Concurrent High-Energy Diffraction Microscopy Characterization12
Temperature-Dependent Material Property Databases for Marine Steels—Part 1: DH3612
High-Throughput Exploration of the Process Space in 18% Ni (350) Maraging Steels via Spherical Indentation Stress–Strain Protocols and Gaussian Process Models10
AMB2018-03: Benchmark Physical Property Measurements for Material Extrusion Additive Manufacturing of Polycarbonate10
Benchmark Study of Melted Track Geometries in Laser Powder Bed Fusion of Inconel 6259
The Simulation of Post-Heat Treatment in Selective Laser Melting Additive Manufacturing9
A Novel Methodology for the Thermographic Cooling Rate Measurement during Powder Bed Fusion of Metals Using a Laser Beam8
Mechanical Responses of Primary-α Ti Grains in Polycrystalline Samples: Part II—Bayesian Estimation of Crystal-Level Elastic-Plastic Mechanical Properties from Spherical Indentation Measurements8
Uncertainty Quantified Parametrically Homogenized Constitutive Models for Microstructure-Integrated Structural Simulations8
Computer Vision Approaches for Segmentation of Nanoscale Precipitates in Nickel-Based Superalloy IN7188
Microscale Structure to Property Prediction for Additively Manufactured IN625 through Advanced Material Model Parameter Identification8
Advanced Acquisition Strategies for Lab-Based Diffraction Contrast Tomography8
3D Grain Shape Generation in Polycrystals Using Generative Adversarial Networks8
Uncertainty Quantification Accounting for Model Discrepancy Within a Random Effects Bayesian Framework8
ITKMontage: A Software Module for Image Stitching7
Temperature-Dependent Material Property Databases for Marine Steels—Part 2: HSLA-657
Random Generation of Lattice Structures with Short-Range Order7
Automated and Refined Application of Convolutional Neural Network Modeling to Metallic Powder Particle Satellite Detection7
A Numerical Approach to Model Microstructure Evolution for NiTi Shape Memory Alloy in Laser Powder Bed Fusion Additive Manufacturing7
Microstructure Image Classification: A Classifier Combination Approach Using Fuzzy Integral Measure7
A Computer Vision Approach to Evaluate Powder Flowability for Metal Additive Manufacturing7
Prediction of Glass Forming Ability of Bulk Metallic Glasses Using Machine Learning7
Mechanical Metrics of Virtual Polycrystals (MechMet)7
AFRL Additive Manufacturing Modeling Challenge Series: Overview7
Additive Manufacturing Melt Pool Prediction and Classification via Multifidelity Gaussian Process Surrogates7
Data-Driven Multi-Scale Modeling and Optimization for Elastic Properties of Cubic Microstructures6
A Comparison of Statistically Equivalent and Realistic Microstructural Representative Volume Elements for Crystal Plasticity Models6
Generative Adversarial Networks and Mixture Density Networks-Based Inverse Modeling for Microstructural Materials Design6
ICME Framework for Simulation of Microstructure and Property Evolution During Gas Metal Arc Welding in DP980 Steel6
Bi-directional Scan Pattern Effects on Residual Stresses and Distortion in As-built Nitinol Parts: A Trend Analysis Simulation Study6
An Open Combinatorial Diffraction Dataset Including Consensus Human and Machine Learning Labels with Quantified Uncertainty for Training New Machine Learning Models6
Digital Protocols for Statistical Quantification of Microstructures From Microscopy Images of Polycrystalline Nickel-Based Superalloys6
PRISMS-Plasticity TM: An Open-Source Rapid Texture Evolution Analysis Pipeline6
Interpretable Machine Learning for Texture-Dependent Constitutive Models with Automatic Code Generation for Topological Optimization6
Unsupervised Deep Learning for Laboratory-Based Diffraction Contrast Tomography5
Intrinsic Dimensionality of Microstructure Data5
Macroscale Property Prediction for Additively Manufactured IN625 from Microstructure Through Advanced Homogenization5
Data-Driven Modeling of Mechanical Properties for 17-4 PH Stainless Steel Built by Additive Manufacturing5
XtalMesh Toolkit: High-Fidelity Mesh Generation of Polycrystals5
Ontopanel: A Tool for Domain Experts Facilitating Visual Ontology Development and Mapping for FAIR Data Sharing in Materials Testing5
AFRL Additive Manufacturing Modeling Series: Challenge 2, Microscale Process-to-Structure Data Description5
Machine Learning-Enabled Uncertainty Quantification for Modeling Structure–Property Linkages for Fatigue Critical Engineering Alloys Using an ICME Workflow5
Optimizing Fractional Compositions to Achieve Extraordinary Properties5
A Comparative Study of Layer Heating and Continuous Heating Methods on Prediction Accuracy of Residual Stresses in Selective Laser Melted Tube Samples5
Data-Driven Constitutive Model for the Inelastic Response of Metals: Application to 316H Steel5
Temperature-Dependent Material Property Databases for Marine Steels—Part 3: HSLA-805
Time-Resolved Geometric Feature Tracking Elucidates Laser-Induced Keyhole Dynamics4
Data Mining and Visualization of High-Dimensional ICME Data for Additive Manufacturing4
Comparative Assessment of Physics-Based Computational Models on the NIST Benchmark Study of Molten Pool Dimensions and Microstructure for Selective Laser Melting of Inconel 6254
Universal Material Constants for MultiStage Fatigue (MSF) Modeling of the Process–Structure–Property (PSP) Relations of A000, 2000, 5000, and 7000 Series Aluminum Alloys4
Materials Abundance, Price, and Availability Data from the Years 1998 to 20154
Temperature-Dependent Material Property Databases for Marine Steels—Part 4: HSLA-1004
Physics-Informed Machine Learning and Uncertainty Quantification for Mechanics of Heterogeneous Materials4
The BAREFOOT Optimization Framework4
Compound Knowledge Graph-Enabled AI Assistant for Accelerated Materials Discovery4
Toward a Physical Basis for a Predictive Finite Element Thermal Model of the LENS™ Process Leveraging Dual-Wavelength Pyrometer Datasets4
Discrepancy Between Crystal Plasticity Simulations and Far-Field High-Energy X-ray Diffraction Microscopy Measurements4
On the Prediction of Uniaxial Tensile Behavior Beyond the Yield Point of Wrought and Additively Manufactured Ti-6Al-4V4
A Machine Learning Strategy for Race-Tracking Detection During Manufacturing of Composites by Liquid Moulding4
Accurate Effective Stress Measures: Predicting Creep Life for 3D Stresses Using 2D and 1D Creep Rupture Simulations and Data3
A Data-Driven Framework to Select a Cost-Efficient Subset of Parameters to Qualify Sourced Materials3
CrabNet for Explainable Deep Learning in Materials Science: Bridging the Gap Between Academia and Industry3
3D Non-Destructive Characterization of Electrical Steels for Quantitative Texture Analysis with Lab-Based X-ray Diffraction Contrast Tomography3
Imputation Method Based on Collaborative Filtering and Clustering for the Missing Data of the Squeeze Casting Process Parameters3
Integrated Computational Design of Three-Phase Mo–Si–B Alloy Turbine Blade for High-Temperature Aerospace Applications3
Sequential Machine Learning Applications of Particle Packing with Large Size Variations3
An ICME Method for Predicting Phase Dissolution During Solution Treatment in Advanced Super Vacuum Die Cast Magnesium Alloys3
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