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Modeling process–structure–property relationships in metal additive manufacturing: a review on physics-driven versus data-driven approaches

https://doi.org/10.1088/2515-7639/abca7b
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inferred← citeshttps://doi.org/10.1007/s40192-021-00211-wopenalex-snapshot
The AFRL Additive Manufacturing Modeling Challenge: Predicting Micromechanical Fields in AM IN625 Using an FFT-Based Method with Direct Input from a 3D Microstructural Image
inferred← citeshttps://doi.org/10.1007/s40192-022-00252-9openalex-snapshot
A Numerical Approach to Model Microstructure Evolution for NiTi Shape Memory Alloy in Laser Powder Bed Fusion Additive Manufacturing
inferred← citeshttps://doi.org/10.1007/s40192-023-00303-9openalex-snapshot
A Process-Structure-Property Simulation Framework for Quantifying Uncertainty in Additive Manufacturing: Application to Fatigue in Ti-6Al-4V
inferred← citeshttps://doi.org/10.1007/s40194-026-02335-zopenalex-snapshot
Selected applications of artificial intelligence and machine learning in metal additive manufacturing
inferred← citeshttps://doi.org/10.1007/s40430-026-06308-7openalex-snapshot
Process-structure linkage for laser powder bed fusion using simulated microstructure images and deep learning
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Effect of pore defects on fatigue behavior in additively manufactured nickel-based alloys
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Laser welding monitoring techniques based on optical diagnosis and artificial intelligence: a review
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Stronger, lighter, and faster: multi-objective Bayesian optimization for fused filament fabrication
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A thematic review of AI-driven computational modeling and optimization for ceramic additive manufacturing
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A review of recent machine learning advances for predicting and optimizing mechanical and tribological properties of fiber-reinforced thermoset polymer nanocomposites
inferred← citeshttps://doi.org/10.1016/b978-0-323-88664-2.00007-5openalex-snapshot
Rapid alloying in additive manufacturing using integrated computational materials engineering
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Data-driven approaches for computational modeling for plasticity, fatigue, and fracture behavior of alloys
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Characterization of porous membranes using artificial neural networks
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PSP-GEN: Stochastic inversion of the Process–Structure–Property chain in materials design through deep, generative probabilistic modeling
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A comprehensive Ai-driven framework for predictive design of grained materials: Case study on nanoglass
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Polymer metallization via cold spray additive manufacturing: A review of process control, coating qualities, and prospective applications
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Reliability of metal additive manufactured materials from modeling the microstructure at different length scales
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Research and application of machine learning for additive manufacturing
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Using machine learning to predict dimensions and qualify diverse part designs across multiple additive machines and materials
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Metal AM process-structure-property relational linkages using Gaussian process surrogates
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Interpretable machine learning approach for exploring process-structure-property relationships in metal additive manufacturing
inferred← citeshttps://doi.org/10.1016/j.addma.2024.104415openalex-snapshot
Digital Twins for Rapid In-Situ Qualification of Part Quality in Laser Powder Bed Fusion Additive Manufacturing
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Exploring spatial beam shaping in laser powder bed fusion: High-fidelity simulation and in-situ monitoring
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Transfer Learning Enabled Geometry, Process, and Material Agnostic Rgnn for Temperature Prediction in Directed Energy Deposition
inferred← citeshttps://doi.org/10.1016/j.amf.2025.200258openalex-snapshot
Additive manufacturing method of lattice structure based on material manufacturing performance driven: Using machine learning to optimize manufacturing process
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Machine learning-driven control of heterogeneous structures in additive manufacturing: Challenges and perspectives
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Physics-guided deep learning for driving force estimation in synchronous tunnel boring machines under missing cylinders
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Roadmap for Additive Manufacturing: Toward Intellectualization and Industrialization
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An efficient discrete physics-informed neural networks for geometrically nonlinear topology optimization
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Application of metal additive manufacturing in oral dentistry
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Data-driven models for structure-property prediction in additively manufactured steels
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Multi-model Monte Carlo estimation for crystal plasticity structure–property simulations of additively manufactured metals
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Data-driven reference trajectory optimization for precision motion systems
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Multi-objective robust parameter optimization using the extended and weighted k-means (EWK-means) clustering in laser powder bed fusion (LPBF)
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A historical and mathematical review and revision of the MultiStage Fatigue (MSF) model
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Durability and damage tolerance analysis methods for lightweight aircraft structures: Review and prospects
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In-situ experimental and high-fidelity modeling tools to advance understanding of metal additive manufacturing
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Elastic properties of additively manufactured steel produced with different scan strategies
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A physics-informed machine learning approach for temperature field prediction in metallic additive manufacturing
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Process modeling in laser powder bed fusion towards defect detection and quality control via machine learning: The state-of-the-art and research challenges
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Progress and perspectives of in-situ optical monitoring in laser beam welding: Sensing, characterization and modeling
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Data-driven modeling of process, structure and property in additive manufacturing: A review and future directions
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System identification and closed-loop control of laser hot-wire directed energy deposition using the parameter-signature-quality modeling scheme
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Application of data-driven methods for laser powder bed fusion of Ni-based superalloys: A review
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A review on physics-informed machine learning for process-structure-property modeling in additive manufacturing
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“In-situ” x-ray imaging technology for material and manufacturing science: A review
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A data-efficient sequential learning framework for melt pool defect classification in Laser Powder Bed Fusion
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Long-horizon spatiotemporal thermal propagation for directed energy deposition: A data-driven geometry-aware liquid neural algorithm
inferred← citeshttps://doi.org/10.1016/j.jmatprotec.2021.117435openalex-snapshot
Processability and cracking behaviour of novel high-alloyed tool steels processed by Laser Powder Bed Fusion
inferred← citeshttps://doi.org/10.1016/j.jmatprotec.2022.117541openalex-snapshot
A part-scale, feature-based surrogate model for residual stresses in the laser powder bed fusion process
inferred← citeshttps://doi.org/10.1016/j.jmatprotec.2022.117703openalex-snapshot
Physics-driven modeling of electron beam welding of Al-Cu alloys from molten pool flow, microstructure to mechanical properties
inferred← citeshttps://doi.org/10.1016/j.jmbbm.2022.105428openalex-snapshot
Printability for additive manufacturing with machine learning: Hybrid intelligent Gaussian process surrogate-based neural network model for Co-Cr alloy
inferred← citeshttps://doi.org/10.1016/j.jmmm.2026.174387openalex-snapshot
Machine learning based estimation of eddy current damping in magnetic vibration absorbers
inferred← citeshttps://doi.org/10.1016/j.jmrt.2025.05.207openalex-snapshot
Melt-based additive manufacturing of refractory metals and alloys: Experiments and modeling
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Post-Processing as a Design Variable in Additive Manufacturing: A Review on Thermodynamic, Kinetic, and Defect-Driven Perspectives
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Machine learning for metal additive manufacturing: Towards a physics-informed data-driven paradigm
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Four Rs Framework for the development of a digital twin: The implementation of Representation with a FDM manufacturing machine
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Data-driven inpainting for full-part temperature monitoring in additive manufacturing
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Machine learning-aided material selection, parameter optimization, and process monitoring in laser powder bed fusion and laser directed energy deposition with powder feed
inferred← citeshttps://doi.org/10.1016/j.matchemphys.2025.130618openalex-snapshot
Physics-Assisted Machine-Learning Approach for Modeling the Temperature-Dependent Ultimate Strengths of Superalloys, with Comparison to Medium- and High-Entropy Alloys
inferred← citeshttps://doi.org/10.1016/j.matdes.2022.111351openalex-snapshot
Feedforward control of thermal history in laser powder bed fusion: Toward physics-based optimization of processing parameters
inferred← citeshttps://doi.org/10.1016/j.matdes.2023.112540openalex-snapshot
Predicting meltpool depth and primary dendritic arm spacing in laser powder bed fusion additive manufacturing using physics-based machine learning
inferred← citeshttps://doi.org/10.1016/j.matdes.2025.114119openalex-snapshot
Predicting mechanical properties of elastomer honeycombs using fast image-based measurements
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An integrated computational materials engineering framework for process–structure–property mapping in laser powder bed fusion
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A state-of-the-art review on implementation of digital twin in additive manufacturing to monitor and control parts quality
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MFC-PINN: A method to improve the accuracy and robustness of acoustic emission source planar localization
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Machine learning for laser powder bed fusion of Ti-6Al-4V: A review of forming quality, microstructure, and mechanical properties prediction
inferred← citeshttps://doi.org/10.1016/j.mfglet.2023.08.099openalex-snapshot
Surrogate-based model chains for establishing process-structure-property linkages with quantified uncertainties in metal additive manufacturing
inferred← citeshttps://doi.org/10.1016/j.mfglet.2024.09.091openalex-snapshot
Thermal profile modeling and microstructural evolution in laser processing of Inconel 625 plates by comparison of analytical and numerical methods
inferred← citeshttps://doi.org/10.1016/j.msea.2023.144832openalex-snapshot
Prediction of high cycle fatigue strength for additive manufactured metals by defects incorporated crystal plasticity modeling
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Crystal plasticity model for cyclic hardening-softening of 316L steel produced by laser-powder bed fusion including the role of sub-grain structures
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An integrated computation framework for predicting mechanical performance of single-phase alloys manufactured using laser powder bed fusion: A case study of CoCrFeMnNi high-entropy alloy
inferred← citeshttps://doi.org/10.1016/j.mtcomm.2024.110557openalex-snapshot
Deep learning-aided inverse analysis framework to accelerate the exploration of DP steel microstructures
inferred← citeshttps://doi.org/10.1016/j.mtcomm.2024.110691openalex-snapshot
Microstructural material design of pearlitic steel lamella for desired mechanical properties
inferred← citeshttps://doi.org/10.1016/j.optlastec.2022.108839openalex-snapshot
3-Dimensional heat transfer modeling for laser powder bed fusion additive manufacturing using parallel computing and adaptive mesh
inferred← citeshttps://doi.org/10.1016/j.optlastec.2025.112461openalex-snapshot
DBSCAN clustering model for parameter inversion using laser cutting edge morphology characteristic in Zr-4 alloy
inferred← citeshttps://doi.org/10.1016/j.procir.2026.02.046openalex-snapshot
Late fusion for resource-efficient analysis of DED process parameters on coating characteristics
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Numerical modeling of coaxial wire-powder laser directed energy deposition process in dissimilar metal additive manufacturing
inferred← citeshttps://doi.org/10.1016/j.rser.2025.115609openalex-snapshot
Review of surrogate model assisted multi-objective design optimization of electrical machines: New opportunities and challenges
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Multiphysics Modeling Framework to Predict Process-Microstructure-Property Relationship in Fusion-Based Metal Additive Manufacturing
inferred← citeshttps://doi.org/10.1038/s41467-023-38738-5openalex-snapshot
Machine learning-assisted crystal engineering of a zeolite
inferred← citeshttps://doi.org/10.1039/d6ja00238bopenalex-snapshot
Plasma emission spectroscopy for online monitoring of laser processing: signals, models and critical perspectives
inferred← citeshttps://doi.org/10.1063/5.0272317openalex-snapshot
Data-physics sequentially driven deep neural network for predicting flow and acoustics fields
inferred← citeshttps://doi.org/10.1063/5.0287936openalex-snapshot
Recent advances toward damage-tolerant 3D-printed titanium alloys: Alloy design perspective
inferred← citeshttps://doi.org/10.1080/09349847.2024.2440353openalex-snapshot
Applying Digital Twin Methods for Process-Structure-Property Correlation Assessment in Metal Additive Manufacturing with Limited Experimental Data
inferred← citeshttps://doi.org/10.1080/09500839.2024.2372497openalex-snapshot
Prediction of material toughness using ensemble learning and data augmentation
inferred← citeshttps://doi.org/10.1080/09506608.2023.2169501openalex-snapshot
Multiphysics multi-scale computational framework for linking process–structure–property relationships in metal additive manufacturing: a critical review
inferred← citeshttps://doi.org/10.1080/17452759.2023.2181192openalex-snapshot
Topology optimization for metal additive manufacturing: current trends, challenges, and future outlook
inferred← citeshttps://doi.org/10.1080/17452759.2025.2604453openalex-snapshot
A critical review on additive manufacturing of refractory alloys from a data analytics perspective- beyond nickel-based superalloys
inferred← citeshttps://doi.org/10.1080/21663831.2024.2316204openalex-snapshot
Exploring chemistry and additive manufacturing design spaces: a perspective on computationally-guided design of printable alloys
inferred← citeshttps://doi.org/10.1080/21663831.2026.2702018openalex-snapshot
Applications and challenges of machine learning in metal additive manufacturing
inferred← citeshttps://doi.org/10.1080/24725854.2024.2443592openalex-snapshot
Advancing additive manufacturing through deep learning: A comprehensive review of current progress and future challenges
inferred← citeshttps://doi.org/10.1088/2515-7639/ae409eopenalex-snapshot
Data-driven multiphysics modeling and optimization of dual-phase spinodoid metamaterials
inferred← citeshttps://doi.org/10.1089/3dp.2023.0051openalex-snapshot
Review on Multiscale Transport Phenomena in the Metal-Based Additive Manufacturing Process
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An Image-Based Transfer Learning Approach for Using In Situ Processing Data to Predict Laser Powder Bed Fusion Additively Manufactured Ti-6Al-4V Mechanical Properties
inferred← citeshttps://doi.org/10.1109/jsen.2022.3220733openalex-snapshot
Nanostructured Silicon-Based Surface Acoustic Wave Sensor for CO2 Gas Detection
inferred← citeshttps://doi.org/10.1115/1.4062852openalex-snapshot
Accelerating Thermal Simulations in Additive Manufacturing by Training Physics-Informed Neural Networks With Randomly Synthesized Data
inferred← citeshttps://doi.org/10.1115/1.4065316openalex-snapshot
Capturing Local Temperature Evolution During Additive Manufacturing Through Fourier Neural Operators
inferred← citeshttps://doi.org/10.1115/1.4069150openalex-snapshot
Detection of Part Porosity in Additive Manufacturing Using Machining
inferred← citeshttps://doi.org/10.20517/jmi.2022.18openalex-snapshot
Process parameter optimization of metal additive manufacturing: a review and outlook
inferred← citeshttps://doi.org/10.21203/rs.3.rs-10564290/v1openalex-snapshot
Testing predictive-state sufficiency and recursive closure in additive-manufacturing microstructure models
inferred← citeshttps://doi.org/10.2320/jinstmet.ja202407openalex-snapshot
Modulated Structure Formation in Dislocation Cells in 316L Stainless Steel Fabricated by Laser Powder Bed Fusion
inferred← citeshttps://doi.org/10.2320/materia.64.720openalex-snapshot
Super Thermal Field Digital Twin (DT) Science: Fusion of Simulation and Monitoring
inferred← citeshttps://doi.org/10.2320/materia.64.726openalex-snapshot
Super Thermal Field Materials Informatics: Data-Driven Discovery and Optimization
inferred← citeshttps://doi.org/10.2320/matertrans.mt-me2022004openalex-snapshot
Modulated Structure Formation in Dislocation Cells in 316L Stainless Steel Fabricated by Laser Powder Bed Fusion
inferred← citeshttps://doi.org/10.2351/7.0001108openalex-snapshot
Prediction of single track clad quality in laser metal deposition using dissimilar materials: Comparison of machine learning-based approaches
inferred← citeshttps://doi.org/10.26868/25222708.2023.1585openalex-snapshot
Challenges in modelling thermo-optical performance of 3D-printed facades: a cross-domain review
inferred← citeshttps://doi.org/10.31399/asm.hb.v24a.a0006988openalex-snapshot
Material Modeling in Additive Manufacturing
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Results on data-driven controllers for unknown nonlinear systems
inferred← citeshttps://doi.org/10.3390/coatings12091277openalex-snapshot
A Review on Modelling and Simulation of Laser Additive Manufacturing: Heat Transfer, Microstructure Evolutions and Mechanical Properties
inferred← citeshttps://doi.org/10.3390/coatings16080952openalex-snapshot
Editorial: Advances in Alloy Surface Mechanics—The Effects of Coating Technologies on Performance
inferred← citeshttps://doi.org/10.3390/jmmp8020076openalex-snapshot
Computer-Aided Optimisation in Additive Manufacturing Processes: A State of the Art Survey
inferred← citeshttps://doi.org/10.3390/ma13245683openalex-snapshot
Investigating the Linear Thermal Expansion of Additively Manufactured Multi-Material Joining between Invar and Steel
inferred← citeshttps://doi.org/10.3390/ma15134674openalex-snapshot
Hardness Prediction of Laser Powder Bed Fusion Product Based on Melt Pool Radiation Intensity
inferred← citeshttps://doi.org/10.3390/ma16237293openalex-snapshot
A Data-Driven Framework for Direct Local Tensile Property Prediction of Laser Powder Bed Fusion Parts
inferred← citeshttps://doi.org/10.3390/ma19020426openalex-snapshot
Advanced Numerical Modeling of Powder Bed Fusion: From Physics-Based Simulations to AI-Augmented Digital Twins
inferred← citeshttps://doi.org/10.3390/met12111913openalex-snapshot
On the Microstructure Development under Cyclic Temperature Conditions during WAAM of Microalloyed Steels
inferred← citeshttps://doi.org/10.3390/met13050842openalex-snapshot
Optimization of Process Parameters in Laser Powder Bed Fusion of SS 316L Parts Using Artificial Neural Networks
inferred← citeshttps://doi.org/10.3390/met16010124openalex-snapshot
Cellular Automata and Phase-Field Modeling of Microstructure Evolution in Metal Additive Manufacturing: Recent Advances, Hybrid Frameworks, and Pathways to Predictive Control
inferred← citeshttps://doi.org/10.3390/powders2010013openalex-snapshot
Multiple-Instance Regression for Metal Powder Hall Flow Rate Prediction Using Augmented Particle Size and Shape Data
inferred← citeshttps://doi.org/10.3390/powders5020020openalex-snapshot
The Influence of Chemical Heterogeneity on the Tribological Properties of High-Alloy Sintered Steels
inferred← citeshttps://doi.org/10.3390/s23115313openalex-snapshot
Di-CNN: Domain-Knowledge-Informed Convolutional Neural Network for Manufacturing Quality Prediction
inferred← citeshttps://doi.org/10.3390/technologies14040218openalex-snapshot
From Mechanics to Machine Learning in Additive Manufacturing: A Review of Deformation, Fatigue, and Fracture
inferred← citeshttps://doi.org/10.5772/intechopen.100760openalex-snapshot
Renewable Energy - Recent Advances
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Structural Design Strategies for the Production of Internal Combustion Engine Components by Additive Manufacturing: A Case Study of a Connecting Rod
inferred← citeshttps://doi.org/10.70675/177df798z18ecz44d3zadfcz1d64e0752b16openalex-snapshot
Multiscale study of the intelligent optimization of dimensional stability and mechanical properties of structures obtained by additive manufacturing
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.