Papers citing Deep materials informatics: Applications of deep learning in materials science
Property Prediction of Organic Donor Molecules for Photovoltaic Applications Using Extremely Randomized Trees
Molecular Informatics · 2019
Arindam Paul, Al’ona Furmanchuk, Wei‐keng Liao, Alok Choudhary, Ankit Agrawal
Read original paper ↗ ·A Real-Time Iterative Machine Learning Approach for Temperature Profile Prediction in Additive Manufacturing Processes
IEEE International Conference on Data Science and Advanced Analytics (DSAA) · 2019
Arindam Paul, Mojtaba Mozaffar, Zijiang Yang, Wei‐keng Liao, Alok Choudhary, Jian Feng Cao, Ankit Agrawal
Read original paper ↗ ·Martensite Start Temperature Predictor for Steels Using Ensemble Data Mining
IEEE International Conference on Data Science and Advanced Analytics (DSAA) · 2019
Ankit Agrawal, Abhinav Saboo, Wei Xiong, Greg Olson, Alok Choudhary
Read original paper ↗ ·Enhancing materials property prediction by leveraging computational and experimental data using deep transfer learning
Nature Communications · 2019
Dipendra Jha, Kamal Kumar Choudhary, Francesca Tavazza, Wei‐keng Liao, Alok Choudhary, Carelyn E. Campbell, Ankit Agrawal
Read original paper ↗ ·Automated Classification of Helium Ingress in Irradiated X-750
arXiv (Cornell University) · 2019
Anderson, Chris, Jacob Klein, Heygaan Rajakumar, C. D. Judge, Laurent Karim Béland
Read original paper ↗ ·Graph convolutional neural networks with global attention for improved materials property prediction
Physical Chemistry Chemical Physics · 2020
Steph-Yves Louis, Yong Zhao, Alireza Nasiri, Xiran Wang, Yuqi Song, Fei Liu, Jianjun Hu
Read original paper ↗ ·Integrating Deep Learning in Domain Sciences at Exascale
Communications in computer and information science · 2020
Richard K. Archibald, Edmond Chow, Eduardo F. D'Azevedo, Jack J. Dongarra, Markus Eisenbach, Rocco Febbo, Florent Lopez, Daniel Nichols, Stanimire Z. Tomov, Kwai Lam Wong, Junqi Yin
Read original paper ↗ ·Design space visualization for guiding investments in biodegradable and sustainably sourced materials
MRS Communications · 2020
James S. Peerless, Emre Sevgen, Stephen D. Edkins, Jason Koeller, Edward Kim, Yoolhee Kim, Astha Gargt, Erin Antono, Julia Ling
Read original paper ↗ ·A handle on the scandal: Data driven approaches to structure prediction
APL Materials · 2020
Shobhana Narasimhan
Read original paper ↗ ·Evolving the Materials Genome: How Machine Learning Is Fueling the Next Generation of Materials Discovery
Annual Review of Materials Research · 2020
Changwon Suh, Clyde Fare, James A. Warren, Edward O. Pyzer‐Knapp
Read original paper ↗ ·Theory-training deep neural networks for an alloy solidification benchmark problem
Computational Materials Science · 2020
M. Torabi Rad, Alexandre Viardin, Georg J. Schmitz, Markus Apel
Read original paper ↗ ·Deep learning analysis on microscopic imaging in materials science
Materials Today Nano · 2020
M. Ge, Fei Su, Zhicheng Zhao, Dong Su
Read original paper ↗ ·Automated Detection of Helium Bubbles in Irradiated X-750
Ultramicroscopy · 2020
Chris M. Anderson, Jacob Klein, Heygaan Rajakumar, C. D. Judge, Laurent Karim Béland
Read original paper ↗ ·Crystal symmetry classification from powder X-ray diffraction patterns using a convolutional neural network
Materials Today Communications · 2020
А. Н. Залога, Становов Владимир Вадимович, Oksana E. Bezrukovа, Petr S. Dubinin, Igor S. Yakimov
Read original paper ↗ ·Advances in neural networks and potential for their application to steel metallurgy
Materials Science and Technology · 2020
James L. Smith
Read original paper ↗ ·Deep Learning-based Phase Prediction of High-Entropy Alloys
IOP Conference Series Materials Science and Engineering · 2020
Zeyad Yousif Abdoon Al-Shibaany, Nadia Alkhafaji, Yaser Al-Obaidi, Alaa Abdulhasan Atiyah
Read original paper ↗ ·Statistical characterization and reconstruction of heterogeneous microstructures using deep neural network
Computer Methods in Applied Mechanics and Engineering · 2020
Jinlong Fu, Shaoqing Cui, Song Cen, Chenfeng Li
Read original paper ↗ ·Emerging materials intelligence ecosystems propelled by machine learning
Nature Reviews Materials · 2020
Rohit Batra, Le Song, Rampi Ramprasad
Read original paper ↗ ·Polymer informatics: Current status and critical next steps
Materials Science and Engineering R Reports · 2020
Lihua Chen, Ghanshyam Pilania, Rohit Batra, Tran Doan Huan, Chiho Kim, Christopher Kuenneth, Rampi Ramprasad
Read original paper ↗ ·Active learning and element-embedding approach in neural networks for infinite-layer versus perovskite oxides
Universitätsbibliographie, Universität Duisburg-Essen · 2021
Armin Sahinovic, Benjamin Geisler
Read original paper ↗ ·Deep Learning Approach for Chemistry and Processing History Prediction From Materials Microstructure: Application to Spinodal Decomposition
SSRN Electronic Journal · 2021
Amir Abbas Kazemzadeh Farizhandi, Omar Betancourt, Mahmood Mamivand
Read original paper ↗ ·Heterogeneous Feature Fusion Based Machine Learning on Shallow-Wide and Heterogeneous-Sparse Industrial Datasets
Lecture notes in computer science · 2021
Zijiang Yang, Tetsushi Watari, Daisuke Ichigozaki, Akita Mitsutoshi, Hiroaki Takahashi, Yoshinori Suga, Wei‐keng Liao, Alok Choudhary, Ankit Agrawal
Read original paper ↗ ·Machine Learning-based Microstructure Prediction During Laser Sintering of Alumina: A Conditional Generative Approach
Research Square · 2021
Jianan Tang, Xiao Geng, Dongsheng Li, Yunfeng Shi, Jianhua Tong, Hai Xiao, Fei Peng
Read original paper ↗ ·Machine learning for materials design and discovery
Journal of Applied Physics · 2021
Rama Krishnan Vasudevan, Ghanshyam Pilania, Prasanna V. Balachandran
Read original paper ↗ ·Surface science of cosmetic substrates, cleansing actives and formulations
Advances in Colloid and Interface Science · 2021
Gustavo S. Luengo, Anne‐Laure Fameau, Fabien Léonforte, Andrew J. Greaves
Read original paper ↗ ·Enabling deeper learning on big data for materials informatics applications
Scientific Reports · 2021
Dipendra Jha, Vishu Gupta, Logan T. Ward, Zijiang Yang, Christopher Wolverton, Ian T Foster, Wei‐keng Liao, Alok Choudhary, Ankit Agrawal
Read original paper ↗ ·A micromechanics-based artificial neural networks model for elastic properties of short fiber composites
Composites Part B Engineering · 2021
Noah Mentges, Behdad Dashtbozorg, Mohsen Mirkhalaf
Read original paper ↗ ·Machine Learning for Transition-Metal-Based Hydrogen Generation Electrocatalysts
ACS Catalysis · 2021
Min Wang, Hongwei Zhu
Read original paper ↗ ·Deep Learning-based Face Mask Detection Using Automated GUI for COVID-19
International Conference on Machine Learning Technologies (ICMLT) · 2021
Bhuwan Bhattarai, Yagya Raj Pandeya, Joonwhoan Lee
Read original paper ↗ ·Casting Microstructure Inspection Using Computer Vision: Dendrite Spacing in Aluminum Alloys
Metals · 2021
Filip Nikolić, Ivan Štajduhar, Marko Čanađija
Read original paper ↗ ·Machine learning-based microstructure prediction during laser sintering of alumina
Scientific Reports · 2021
Jianan Tang, Xiao Geng, Dongsheng Li, Yunfeng Shi, Jianhua Tong, Hai Xiao, Fei Peng
Read original paper ↗ ·Bandgap Engineering in the Configurational Space of Solid Solutions via Machine Learning: (Mg,Zn)O Case Study
The Journal of Physical Chemistry Letters · 2021
Scott D. Midgley, Said Hamad, Keith T. Butler, Ricardo Grau‐Crespo
Read original paper ↗ ·From microstructural images to properties - an interpretable deep learning approach to predict elastic-plastic properties of fiber composites
Venue not supplied by source · 2021
Sathiskumar Anusuya Ponnusami
Read original paper ↗ ·Deep learning-based estimation of Flory–Huggins parameter of A–B block copolymers from cross-sectional images of phase-separated structures
Scientific Reports · 2021
Katsumi Hagita, Takeshi Aoyagi, Yuto Abe, Shinya Genda, T. Honda
Read original paper ↗ ·Convolutional neural network model for synchrotron radiation imaging datasets to automatically detect interfacial microstructure: An in situ process monitoring tool during solar PV ribbon fabrication
Solar Energy · 2021
Anil Kunwar, Prafulla Bahadur Malla, Junhao Sun, Lin Qu, Haitao Ma
Read original paper ↗ ·Computational discovery of energy materials in the era of big data and machine learning: A critical review
Materials Reports Energy · 2021
Ziheng Lu
Read original paper ↗ ·Catalyze Materials Science with Machine Learning
ACS Materials Letters · 2021
Jaehyun Kim, Donghoon Kang, Sang‐Bum Kim, Ho Won Jang
Read original paper ↗ ·Analysis on Microstructure–Property Linkages of Filled Rubber Using Machine Learning and Molecular Dynamics Simulations
Polymers · 2021
Takashi Kojima, Takashi Washio, Satoshi Hara, Masataka KOISHI, Naoya Amino
Read original paper ↗ ·Automated stopping criterion for spectral measurements with active learning
npj Computational Materials · 2021
Tetsuro Ueno, Hideaki Ishibashi, Hideitsu Hino, Kanta Ono
Read original paper ↗ ·Exploration of the Underlying Space in Microscopic Images via Deep Learning for Additively Manufactured Piezoceramics
ACS Applied Materials & Interfaces · 2021
Wenhua Yang, Zhuo Wang, Tiannan Yang, Li He, Xuan Song, Yucheng Liu, Lei Chen
Read original paper ↗ ·ChemDataExtractor 2.0: Autopopulated Ontologies for Materials Science
Journal of Chemical Information and Modeling · 2021
Juraj Mavračić, Callum J. Court, Taketomo Isazawa, Stephen R. Elliott, Jacqueline M. Cole
Read original paper ↗ ·Machine learning and materials informatics approaches in the analysis of physical properties of carbon nanotubes: A review
Computational Materials Science · 2021
Luis Enrique Vivanco-Benavides, Claudia Lizbeth Martínez‐González, C. Mercado-Zúñiga, C. Torres-Torres
Read original paper ↗ ·Performance, Successes and Limitations of Deep Learning Semantic Segmentation of Multiple Defects in Transmission Electron Micrographs
arXiv (Cornell University) · 2021
Ryan M. Jacobs, Mingren Shen, Yuhan Liu, Hao, Wei, Xiaoshan Li, He, Ruoyu, Jacob R.C. Greaves, Donglin Wang, Zeming Xie, Zitong Huang, Chao Wang, Kevin G. Field, Dane D. Morgan
Read original paper ↗ ·An Incremental Learning for Plant Disease classification
International Conference on Information and Communication Technology Convergence (ICTC) · 2021
Bhuwan Bhattarai, Yagya Raj Pandeya, Joonwhoan Lee
Read original paper ↗ ·Review of machine learning‐driven design of polymer‐based dielectrics
IET Nanodielectrics · 2021
Ming‐Xiao Zhu, Ting Deng, Lei Dong, Jiming Chen, Zhi‐Min Dang
Read original paper ↗ ·Featurization Strategies for Polymer Sequence or Composition Design by Machine Learning
Venue not supplied by source · 2021
Roshan Patel, Carlos H. Borca, Michael A. Webb
Read original paper ↗ ·Cross-property deep transfer learning framework for enhanced predictive analytics on small materials data
Nature Communications · 2021
Vishu Gupta, Kamal Kumar Choudhary, Francesca Tavazza, Carelyn E. Campbell, Wei‐keng Liao, Alok Choudhary, Ankit Agrawal
Read original paper ↗ ·Data-driven thermoelectric modeling: Current challenges and prospects
Journal of Applied Physics · 2021
Mamadou T. Mbaye, Sangram K. Pradhan, Messaoud J. Bahoura
Read original paper ↗ ·Practical Aspects of the Design and Use of the Artificial Neural Networks in Materials Engineering
Metals · 2021
Wojciech Sitek, Jacek Trzaska
Read original paper ↗ ·Estimating the performance of a material in its service space via Bayesian active learning: a case study of the damping capacity of Mg alloys
Journal of Materials Informatics · 2022
Bofeng Shi, Yumei Zhou, Daqing Fang, Yuan Tian, Xiangdong Ding, Jun Sun, Turab Lookman, Dezhen Xue
Read original paper ↗ ·