Papers citing Material structure-property linkages using three-dimensional convolutional neural networks
Structure–property linkage in shocked multi-material flows using a level-set-based Eulerian image-to-computation framework
Shock Waves · 2020-06-12
S. Roy, N. K. Rai, O. Sen, H. S. Udaykumar
Read original paper ↗ ·Analytical transport network theory & structural mechanics: Towards computationally inexpensive multi-functional materials design
Applied Materials Today · 2020-06-24
Alex P. Cocco, Kyle N. Grew
Read original paper ↗ ·Mechanical Characterization of Polysilicon MEMS Devices: a Stochastic, Deep Learning-based Approach
International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE) · 2020-07-01
José Pablo Quesada-Molina, Luca Rosafalco, Stefano Mariani
Read original paper ↗ ·A data-driven surrogate model to rapidly predict microstructure morphology during physical vapor deposition
Applied Mathematical Modelling · 2020-07-09
Elizabeth Herman, James A. Stewart, Rémi Dingreville
Read original paper ↗ ·3DMaterialGAN: Learning 3D Shape Representation from Latent Space for Materials Science Applications
arXiv (Cornell University) · 2020-07-27
Devendra K. Jangid, Neal R. Brodnik, Amil Khan, McLean P. Echlin, Tresa M. Pollock, Sam Daly, B. S. Manjunath
Read original paper ↗ ·Feature engineering of material structure for AI-based materials knowledge systems
Journal of Applied Physics · 2020-07-28
Surya R. Kalidindi
Read original paper ↗ ·Better, Faster, and Less Biased Machine Learning: Electromechanical Switching in Ferroelectric Thin Films
Advanced Materials · 2020-08-14
Lee A. Griffin, Iaroslav Gaponenko, Nazanin Bassiri‐Gharb
Read original paper ↗ ·Machine learning materials physics: Multi-resolution neural networks learn the free energy and nonlinear elastic response of evolving microstructures
Computer Methods in Applied Mechanics and Engineering · 2020-08-22
Xiaoxuan Zhang, Krishna C. Garikipati
Read original paper ↗ ·Prediction of uniaxial tensile flow using finite element-based indentation and optimized artificial neural networks
Materials & Design · 2020-08-27
Kyeongjae Jeong, Hyukjae Lee, Oh Min Kwon, Jinwook Jung, Dongil Kwon, Heung Nam Han
Read original paper ↗ ·Mining the Correlations Between Optical Micrographs and Mechanical Properties of Cold-Rolled HSLA Steels Using Machine Learning Approaches
Integrating materials and manufacturing innovation · 2020-09-01
Berkay Yucel, Sezen Yucel, A. Ray, Lode Duprez, Surya R. Kalidindi
Read original paper ↗ ·Knowledge-Based Descriptor for the Compositional Dependence of the Phase Transition in BaTiO3-Based Ferroelectrics
ACS Applied Materials & Interfaces · 2020-09-14
Ruihao Yuan, Deqing Xue, Deqing Xue, Dezhen Xue, Dezhen Xue, Jinshan Li, Xiangdong Ding, Jun Sun, Turab Lookman
Read original paper ↗ ·Reduced-Order Models for Ranking Damage Initiation in Dual-Phase Composites Using Bayesian Neural Networks
JOM · 2020-10-13
Aditya Venkatraman, David Montes de Oca Zapiain, Surya R. Kalidindi
Read original paper ↗ ·Prediction of Energetic Material Properties from Electronic Structure Using 3D Convolutional Neural Networks
Journal of Chemical Information and Modeling · 2020-10-15
Alex Casey, Steven Forrest Son, Ilias Bilionis, Brian C. Barnes
Read original paper ↗ ·Machine learning based surrogate modeling approach for mapping crystal deformation in three dimensions
Scripta Materialia · 2020-10-21
Anup Pandey, Reeju Pokharel
Read original paper ↗ ·Emerging materials intelligence ecosystems propelled by machine learning
Nature Reviews Materials · 2020-11-09
Rohit Batra, Le Song, Rampi Ramprasad
Read original paper ↗ ·Surrogate Model via Artificial Intelligence Method for Accelerating Screening Materials and Performance Prediction
Advanced Functional Materials · 2020-12-01
Tian Wang, Mingqi Shao, Rong Guo, Fei Tao, Gang Zhang, Hichem Snoussi, Xingling Tang
Read original paper ↗ ·Deep learning model for predicting phase diagrams of block copolymers
Computational Materials Science · 2020-12-10
Takeshi Aoyagi
Read original paper ↗ ·Impact performance of an annular shaped charge designed by convolutional neural networks
Thin-Walled Structures · 2020-12-13
Wenlong Xu, Cheng Wang, Jianming Yuan
Read original paper ↗ ·Artificial intelligence and machine learning in design of mechanical materials
Materials Horizons · 2020-12-17
Kai Guo, Zhenze Yang, Chi‐Hua Yu, Markus J. Buehler
Read original paper ↗ ·A Deep Learning Approach for Polycrystalline Microstructure-Statistical Property Prediction
Lecture notes in computer science · 2021-01-01
José Pablo Quesada-Molina, Stefano Mariani
Read original paper ↗ ·A multi-task learning-based optimization approach for finding diverse sets of material microstructures with desired properties and its application to texture optimization
arXiv (Cornell University) · 2021-01-01
Tarek Iraki, Lukas Morand, Johannes Dornheim, Norbert Link, Dirk Helm
Read original paper ↗ ·A Two-Scale Multi-Physics Deep Learning Model for Smart MEMS Sensors
Journal of Materials Science and Chemical Engineering · 2021-01-01
José Pablo Quesada-Molina, Stefano Mariani
Read original paper ↗ ·Biomaterialomics: Data-Driven Pathways to Next-Generation Biomaterials
SSRN Electronic Journal · 2021-01-01
Bikramjit Basu, N. H. Gowtham, Yang Xiao, Surya R. Kalidindi, Kam W. Leong
Read original paper ↗ ·Deep Learning Approach for Chemistry and Processing History Prediction From Materials Microstructure: Application to Spinodal Decomposition
SSRN Electronic Journal · 2021-01-01
Amir Abbas Kazemzadeh Farizhandi, Omar Betancourt, Mahmood Mamivand
Read original paper ↗ ·Towards the digitalisation of porous energy materials: evolution of digital approaches for microstructural design
Energy & Environmental Science · 2021-01-01
Zhiqiang Niu, Valerie J. Pinfield, Billy Wu, Huizhi Wang, Kui Jiao, Dennis Y.C. Leung, Jin Xuan
Read original paper ↗ ·Computational design of structured chemical products
Frontiers of Chemical Science and Engineering · 2021-01-02
Faheem Mushtaq, Xiang Zhang, Ka Yip Fung, Ka Ming Ng
Read original paper ↗ ·Bayesian neural networks for weak solution of PDEs with uncertainty quantification
arXiv (Cornell University) · 2021-01-13
Xiaoxuan Zhang, Krishna C. Garikipati
Read original paper ↗ ·High-throughput prediction of stress–strain curves of thermoplastic elastomer model block copolymers by combining hierarchical simulation and deep learning
MRS Advances · 2021-02-05
Takeshi Aoyagi
Read original paper ↗ ·A micromechanics-based artificial neural networks model for elastic properties of short fiber composites
Composites Part B Engineering · 2021-02-26
Noah Mentges, Behdad Dashtbozorg, Mohsen Mirkhalaf
Read original paper ↗ ·Abnormal Behavior Recognition in Classroom Pose Estimation of College Students Based on Spatiotemporal Representation Learning
Traitement du signal · 2021-02-28
Yunfang Xie, Su Zhang, Yingdi Liu
Read original paper ↗ ·Bacterial streamers as colloidal systems: Five grand challenges
Journal of Colloid and Interface Science · 2021-03-09
Udita Uday Ghosh, Hessein Ali, Ranajay R. Ghosh, Aloke Kumar
Read original paper ↗ ·Teaching Solid Mechanics to Artificial Intelligence: a fast solver for heterogeneous solids
arXiv (Cornell University) · 2021-03-16
Jaber Rezaei Mianroodi, Nima Hamidi Siboni, Dierk Raabe
Read original paper ↗ ·A contemporary approach to the MSE paradigm powered by Artificial Intelligence from a review focused on Polymer Matrix Composites
Mechanics of Advanced Materials and Structures · 2021-03-19
C. Gomez, A. Guardia, J. L. Mantari, Alberto M. Coronado, Junuthula Narasimha Reddy
Read original paper ↗ ·Hybrid Modelling by Machine Learning Corrections of Analytical Model Predictions towards High-Fidelity Simulation Solutions
Materials · 2021-04-10
Frederic E. Bock, Sören Keller, Norbert W. Huber, Benjamin Klusemann
Read original paper ↗ ·Searching for Optimal Patterns of Magnetoelectric Multi-Phase Composites with Machine Learning Method
Symposium on Piezoelectricity, Acoustic Waves and Device Applications · 2021-04-16
Weihao Zhu, Chen Yang, Bin Huang
Read original paper ↗ ·Self-supervised learning and prediction of microstructure evolution with convolutional recurrent neural networks
Patterns · 2021-04-22
Kaiqi Yang, Yifan Cao, Youtian Zhang, Shaoxun Fan, Ming Y. Tang, Daniel Åberg, Babak Sadigh, Fei Zhou
Read original paper ↗ ·Prediction and Optimization of Ion Transport Characteristics in Nanoparticle-Based Electrolytes Using Convolutional Neural Networks
The Journal of Physical Chemistry B · 2021-04-29
Sanket Kadulkar, Michael P. Howard, Thomas M. Truskett, Venkat Ganesan
Read original paper ↗ ·Machine Learning in Magnetic Materials
physica status solidi (b) · 2021-05-05
Georgios Katsikas, C. Sarafidis, Joseph Kioseoglou
Read original paper ↗ ·Convolutional Neural Networks for the Localization of Plastic Velocity Gradient Tensor in Polycrystalline Microstructures
Journal of Engineering Materials and Technology · 2021-05-08
David Montes de Oca Zapiain, Apaar Shanker, Surya R. Kalidindi
Read original paper ↗ ·The Application of Convolutional Neural Networks (CNNs) to Recognize Defects in 3D-Printed Parts
Materials · 2021-05-15
Hao Wen, Chang Huang, Shengmin Guo
Read original paper ↗ ·Predicting elastic modulus of porous La0.6Sr0.4Co0.2Fe0.8O3-δ cathodes from microstructures via FEM and deep learning
International Journal of Hydrogen Energy · 2021-05-18
Xuhao Liu, Zilin Yan, Zheng Zhong
Read original paper ↗ ·Predicting and optimizing coupling effect in magnetoelectric multi-phase composites based on machine learning algorithm
Composite Structures · 2021-05-26
Weihao Zhu, Yang Chen, Bin Huang, Yan Shu Guo, Longtao Xie, Yangyang Zhang, Ji Wang
Read original paper ↗ ·Integrated deep learning neural network and desirability analysis in biogas plants: A powerful tool to optimize biogas purification
Energy · 2021-06-02
Mahmood Mahmoodi‐Eshkaftaki, Rahim Ebrahimi
Read original paper ↗ ·Transregional spatial correlation revealed by deep learning and implications for material characterisation and reconstruction
Materials Characterization · 2021-06-19
Junlin Lin, Shu-Jian Chen, Wei Wang, Chathurdara Sri Nadith Pathirage, Ling Li, Kwesi Sagoe‐Crentsil, Wenhui Duan
Read original paper ↗ ·Super-resolving material microstructure image via deep learning for microstructure characterization and mechanical behavior analysis
npj Computational Materials · 2021-06-25
Jaimyun Jung, Juwon Na, Hyung Keun Park, Jeong Min Park, Gyuwon Kim, Seung‐Chul Lee, Hyoung Seop Kim
Read original paper ↗ ·Teaching solid mechanics to artificial intelligence—a fast solver for heterogeneous materials
npj Computational Materials · 2021-07-01
Jaber Rezaei Mianroodi, Nima Hamidi Siboni, Dierk Raabe
Read original paper ↗ ·Machine Learning Based Methods for Obtaining Correlations between Microstructures and Thermal Stresses
Metals · 2021-07-22
Akshay Bhutada, Sunni Kumar, Dayalan Gunasegaram, Alankar Alankar
Read original paper ↗ ·Reduced-order models for microstructure-sensitive effective thermal conductivity of woven ceramic matrix composites with residual porosity
Composite Structures · 2021-07-22
Adam P. Generale, Surya R. Kalidindi
Read original paper ↗ ·Data‐Driven Approaches Toward Smarter Additive Manufacturing
Advanced Intelligent Systems · 2021-07-23
Chenxi Tian, Tianjiao Li, Jenniffer Bustillos, Shonak Bhattacharya, Talia Turnham, Jingjie Yeo, Atieh Moridi
Read original paper ↗ ·Adaptive active subspace-based efficient multifidelity materials design
Materials & Design · 2021-07-24
Danial Khatamsaz, Abhilash Molkeri, Richard Couperthwaite, Jaylen James, Raymundo Arróyave, Ankit Srivastava, Douglas Allaire
Read original paper ↗ ·