Papers citing ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition
Extracting Knowledge from DFT: Experimental Band Gap Predictions Through Ensemble Learning
Integrating materials and manufacturing innovation · 2020-07-24
Steven K. Kauwe, Taylor Welker, Taylor D. Sparks
Read original paper ↗ ·Deep Neural Networks for Multicomponent Molecular Systems
ACS Omega · 2020-08-10
Kyohei Hanaoka
Read original paper ↗ ·A Genetic Algorithmic Approach to Determine the Structure of Li–Al Layered Double Hydroxides
Journal of Chemical Information and Modeling · 2020-08-14
Josiah Roberts, Yang Song, Mark Crocker, Chad M. Risko
Read original paper ↗ ·Using Machine Learning to Generate Novel Hypotheses: Increasing Optimism about Covid-19 Makes People Less Willing to Justify Unethical Behaviors
Unknown journal · 2020-08-25
Krishna Savani
Read original paper ↗ ·Using Machine Learning to Generate Novel Hypotheses: Increasing Optimism about Covid-19 Makes People Less Willing to Justify Unethical Behaviors
Unknown journal · 2020-08-25
Krishna Savani
Read original paper ↗ ·Is Domain Knowledge Necessary for Machine Learning Materials Properties?
Integrating materials and manufacturing innovation · 2020-08-27
Ryan Murdock, Steven K. Kauwe, Anthony Wang, Taylor D. Sparks
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 ↗ ·Artificial intelligence for photonics and photonic materials
Reports on Progress in Physics · 2020-09-02
Davide Piccinotti, Kevin F. MacDonald, Simon A. Gregory, Ian J. Youngs, Nikolay I. Zheludev
Read original paper ↗ ·Machine learning formation enthalpies of intermetallics
Journal of Applied Physics · 2020-09-08
Zhaohan Zhang, Mu Li, Katharine M. Flores, Rohan Mishra
Read original paper ↗ ·Using Machine Learning to Generate Novel Hypotheses: Increasing Optimism About COVID-19 Makes People Less Willing to Justify Unethical Behaviors
Psychological Science · 2020-09-14
Abhishek Sheetal, Zhiyu Feng, Krishna Savani
Read original paper ↗ ·Clathrate XI K58Zn122Sb207: A New Branch on the Clathrate Family Tree
Angewandte Chemie International Edition · 2020-09-16
Tori Cox, Volodymyr Gvozdetskyi, Mark Bertolami, Shannon Lee, Kristian Shipley, Oleg I. Lebedev, Julia V. Zaikina
Read original paper ↗ ·Clathrate XI K58Zn122Sb207: A New Branch on the Clathrate Family Tree
Angewandte Chemie · 2020-09-16
Tori Cox, Volodymyr Gvozdetskyi, Mark Bertolami, Shannon Lee, Kristian Shipley, Oleg I. Lebedev, Julia V. Zaikina
Read original paper ↗ ·Practicing deep learning in materials science: An evaluation for predicting the formation energies
Journal of Applied Physics · 2020-09-23
Liyuan Huang, Ling Chen
Read original paper ↗ ·A Combined DFT/Machine Learning Framework for Materials Discovery: Application to Spinels and Assessment of Search Completeness and Efficiency
ChemRxiv · 2020-10-11
Elif Ertekin, Joshua A. Schiller
Read original paper ↗ ·A Combined DFT/Machine Learning Framework for Materials Discovery: Application to Spinels and Assessment of Search Completeness and Efficiency
ChemRxiv · 2020-10-12
Elif Ertekin, Joshua A. Schiller
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 ↗ ·Deep Learning Total Energies and Orbital Energies of Large Organic Molecules Using Hybridization of Molecular Fingerprints
Journal of Chemical Information and Modeling · 2020-10-29
Obaidur Rahaman, Alessio Gagliardi
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 ↗ ·Modeling process–structure–property relationships in metal additive manufacturing: a review on physics-driven versus data-driven approaches
Journal of Physics Materials · 2020-11-13
Nadia Kouraytem, Xuxiao Li, Wenda Tan, Branden B. Kappes, Ashley D. Spear
Read original paper ↗ ·Learning Representations of Inorganic Materials from Generative Adversarial Networks
Symmetry · 2020-11-17
Tiantian Hu, Hui Song, Tao Jiang, Shaobo Li
Read original paper ↗ ·A critical examination of compound stability predictions from machine-learned formation energies
eScholarship (California Digital Library) · 2020-12-01
Bartel, CJ, Trewartha, A, Wang, Q, Dunn, A, Anubhav Jain, Gerbrand Ceder
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 ↗ ·The Earth Mover’s Distance as a Metric for the Space of Inorganic Compositions
Chemistry of Materials · 2020-12-02
Cameron J. Hargreaves, Matthew Stephen Dyer, Michael W. Gaultois, Vitaliy A. Kurlin, Matthew J. Rosseinsky
Read original paper ↗ ·Predicting materials properties without crystal structure: deep representation learning from stoichiometry
Nature Communications · 2020-12-08
Rhys E. A. Goodall, Alpha A. Lee
Read original paper ↗ ·Residual Neural Network Architectures to Improve Prediction Accuracy of Properties of Materials
IEEE International Conference on Big Data (BigData) · 2020-12-10
David Tatis Posada, Heidy Sierra, Emmanuel Arzuaga
Read original paper ↗ ·Predictive Modeling of Critical Temperatures in Superconducting Materials
Molecules · 2020-12-22
Natalia Sizochenko, Markus Hofmann
Read original paper ↗ ·Machine Learning in Predictive Toxicology: Recent Applications and Future Directions for Classification Models
Chemical Research in Toxicology · 2020-12-23
Marcus W. H. Wang, Jonathan M. Goodman, Timothy E. H. Allen
Read original paper ↗ ·Active learning and element-embedding approach in neural networks for infinite-layer versus perovskite oxides
Universitätsbibliographie, Universität Duisburg-Essen · 2021-01-01
Armin Sahinovic, Benjamin Geisler
Read original paper ↗ ·Atomic descriptors generated from coordination polyhedra in crystal structures
Science and Technology of Advanced Materials Methods · 2021-01-01
Yuki Inada, Yukari Katsura, Masaya Kumagai, Kaoru Kimura
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 ↗ ·Deep Learning for Medical Materials: Review and Perspective
ES Materials & Manufacturing · 2021-01-01
Yangjie Qi, Chang Liu
Read original paper ↗ ·Modelling IF Steels Using Artificial Neural Networks and Automated Machine Learning
Advances in intelligent systems and computing · 2021-01-01
Douglas Macedo Sgrott, Fabrício Moreira Cerqueira, Fabiano J. F. Miranda, José Francisco Silva Filho, Rafael Stubs Parpinelli
Read original paper ↗ ·Monitoring the role of site chemistry on the formation energy of perovskites via deep learning analysis of Hirshfeld surfaces
Journal of Materials Chemistry C · 2021-01-01
Logan Williams, Arpan Mukherjee, Aparajita Dasgupta, Krishna Rajan
Read original paper ↗ ·Predicting phosphorescence energies and inferring wavefunction localization with machine learning
Chemical Science · 2021-01-01
Andrew E. Sifain, Levi Lystrom, Richard A. Messerly, Justin S. Smith, Benjamin T. Nebgen, Kipton M. Barros, Sergei Tretiak, Nicholas Lubbers, Brendan J. Gifford
Read original paper ↗ ·Interpretable discovery of new semiconductors with machine learning
arXiv (Cornell University) · 2021-01-12
Hitarth Choubisa, Petar Todorović́, João M. Pina, Darshan H. Parmar, Li, Ziliang, Oleksandr Voznyy, Isaac Tamblyn, Edward Hartley Sargent
Read original paper ↗ ·A general and transferable deep learning framework for predicting phase formation in materials
npj Computational Materials · 2021-01-25
Shuo Feng, Huadong Fu, Huiyu Zhou, Yuan Wu, Zhaoping Lü, Hongbiao Dong
Read original paper ↗ ·Transfer learning for materials informatics using crystal graph convolutional neural network
Computational Materials Science · 2021-01-29
Joohwi Lee, Ryoji Asahi
Read original paper ↗ ·Materials discovery through machine learning formation energy
Journal of Physics Energy · 2021-02-09
Gordon G. C. Peterson, Jakoah Brgoch
Read original paper ↗ ·Enabling deeper learning on big data for materials informatics applications
Scientific Reports · 2021-02-19
Dipendra Jha, Vishu Gupta, Logan T. Ward, Zijiang Yang, Christopher Wolverton, Ian T Foster, Wei‐keng Liao, Alok Choudhary, Ankit Agrawal
Read original paper ↗ ·Transfer learning for solvation free energies: From quantum chemistry to experiments
Chemical Engineering Journal · 2021-03-11
Florence H. Vermeire, William H. Green
Read original paper ↗ ·Taking the leap between analytical chemistry and artificial intelligence: A tutorial review
Analytica Chimica Acta · 2021-03-15
Lucas B. Ayres, Federico J.V. Gómez, Jeb R. Linton, María Fernanda Silva, Carlos D. García
Read original paper ↗ ·AptaNet as a deep learning approach for aptamer–protein interaction prediction
Scientific Reports · 2021-03-16
Neda Emami, Reza Ferdousi
Read original paper ↗ ·Machine Learning for Transition-Metal-Based Hydrogen Generation Electrocatalysts
ACS Catalysis · 2021-03-16
Min Wang, Hongwei Zhu
Read original paper ↗ ·Deep Learning Optical Spectroscopy Based on Experimental Database: Potential Applications to Molecular Design
JACS Au · 2021-03-17
Joonyoung F. Joung, Minhi Han, Jinhyo Hwang, Minseok Jeong, Dong Hoon Choi, Sungnam Park
Read original paper ↗ ·Progress in the Theory of X-ray Spectroscopy: From Quantum Chemistry to Machine Learning and Ultrafast Dynamics
The Journal of Physical Chemistry A · 2021-03-17
Conor D. Rankine, Thomas J. Penfold
Read original paper ↗ ·Using Social Media in Tourist Sentiment Analysis: A Case Study of Andalusia during the Covid-19 Pandemic
Sustainability · 2021-03-31
David Flores Ruíz, Adolfo Hernán Elizondo Saltos, María de la O Barroso González
Read original paper ↗ ·Efficient few-shot machine learning for classification of EBSD patterns
Scientific Reports · 2021-04-14
Kevin Kaufmann, Hobson Lane, Xiao Liu, Kenneth S. Vecchio
Read original paper ↗ ·CrysXPP:An Explainable Property Predictor for Crystalline Material
arXiv (Cornell University) · 2021-04-22
Kishalay Das, Bidisha Samanta, Pawan Goyal, Seung‐Cheol Lee, Satadeep Bhattacharjee, Niloy Ganguly
Read original paper ↗ ·Artificial Intelligence-Based Optimization of Industrial Membrane Processes
Earth Systems and Environment · 2021-05-05
Maria Teresa Gaudio, Gerardo Coppola, Lorenzo Zangari, Stefano Curcio, Sergio Greco, Sudip Chakraborty
Read original paper ↗ ·Machine Learning in Magnetic Materials
physica status solidi (b) · 2021-05-05
Georgios Katsikas, C. Sarafidis, Joseph Kioseoglou
Read original paper ↗ ·