Papers citing Inverse design in search of materials with target functionalities
Prediction of low-Z collinear and noncollinear antiferromagnetic compounds having momentum-dependent spin splitting even without spin-orbit coupling
SEMI-IR · 2021
Lin‐Ding Yuan
Read original paper ↗ ·Designing heat transfer pathways for advanced thermoregulatory textiles
Materials Today Physics · 2021
X. Lan, Yang Wang, Jiebin Peng, Yang Si, Jie Ren, Bin Ding, Benhui Li
Read original paper ↗ ·Prediction of low-Z collinear and noncollinear antiferromagnetic compounds having momentum-dependent spin splitting even without spin-orbit coupling
Physical Review Materials · 2021
Lin-Ding Yuan, Zhi Wang, Jun-Wei Luo, Alex Zunger
Read original paper ↗ ·Adversarial Attacks on Uncertainty Enable Active Learning for Neural Network Potentials.
arXiv (Cornell University) · 2021
Daniel Schwalbe‐Koda, Aik Rui Tan, Rafael Gómez‐Bombarelli
Read original paper ↗ ·Inverse design of nonequilibrium steady states: A large-deviation approach
Physical review. E · 2021
William D. Piñeros, Tsvi Tlusty
Read original paper ↗ ·Artificial Intelligence based Autonomous Molecular Design for Medical Therapeutic: A Perspective
arXiv (Cornell University) · 2021
Rajendra Prasad Joshi, Neeraj Kumar
Read original paper ↗ ·Accelerating the development of new solar absorbers by photoemission characterization coupled with density functional theory
Journal of Physics Energy · 2021
Tim D. Veal, David O. Scanlon, Robert M. Kostecki, Elisabetta Arca
Read original paper ↗ ·Machine learning in materials science: From explainable predictions to autonomous design
Computational Materials Science · 2021
Ghanshyam Pilania
Read original paper ↗ ·Machine learning augmented predictive and generative model for rupture life in ferritic and austenitic steels
npj Materials Degradation · 2021
Osman Mamun, Madison Wenzlick, Arun V. Sathanur, Jeffrey A. Hawk, Ram Devanathan
Read original paper ↗ ·Reply on RC2
Venue not supplied by source · 2021
Emma Lumiaro
Read original paper ↗ ·Computational Discovery of New 2D Materials Using Deep Learning Generative Models
ACS Applied Materials & Interfaces · 2021
Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Yong Zhao, Jianjun Hu
Read original paper ↗ ·Heisenberg and anisotropic exchange interactions in magnetic materials with correlated electronic structure and significant spin-orbit coupling
Physical review. B./Physical review. B · 2021
Vladislav Borisov, Y. O. Kvashnin, Nikolaos Ntallis, Danny Thonig, Patrik Thunström, Manuel Pereiro, Anders Bergman, Erik Sjöqvist, Anna Delin, Lars Nordström, Olle Eriksson
Read original paper ↗ ·Analysis of Updated Literature Data up to 2019 on the Oxidative Coupling of Methane Using an Extrapolative Machine‐Learning Method to Identify Novel Catalysts
ChemCatChem · 2021
Shinya Mine, Motoshi Takao, Taichi Yamaguchi, Takashi Toyao, Zen Maeno, S. M. A. Hakim Siddiki, Satoru Takakusagi, Ken‐ichi Shimizu, Ichigaku Takigawa
Read original paper ↗ ·Machine learning approaches for feature engineering of the crystal structure: Application to the prediction of the formation energy of cubic compounds
Physical Review Materials · 2021
Prathik R. Kaundinya, Kamal Kumar Choudhary, Surya R. Kalidindi
Read original paper ↗ ·Accelerated Discovery of the Polymer Matrix for Cartilage Repair Through Machine Learning Algorithms
Research Square · 2021
Anusha Mairpady, Abdel‐Hamid I. Mourad, Mohammad Sayem Mozumder
Read original paper ↗ ·Perspective on integrating machine learning into computational chemistry and materials science
The Journal of Chemical Physics · 2021
Julia Westermayr, Michael Gastegger, Kristof T. Schütt, Reinhard J. Maurer
Read original paper ↗ ·The data-intensive scientific revolution occurring where two-dimensional materials meet machine learning
Cell Reports Physical Science · 2021
Hang Yin, Zhehao Sun, Zhuo Wang, Dawei Tang, Cheng Heng Pang, Xue‐Feng Yu, Amanda Susan Barnard, Haitao Zhao, Zongyou Yin
Read original paper ↗ ·Predictive Synthesis
Chemistry of Materials · 2021
Kirill A. Kovnir
Read original paper ↗ ·Crystal structure prediction using age-fitness multi-objective genetic algorithm and coordination number constraints
arXiv (Cornell University) · 2021
Wenhui Yang, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu
Read original paper ↗ ·Arc Synthesis, Crystal Structure, and Photoelectrochemistry of Copper(I) Tungstate
ACS Applied Materials & Interfaces · 2021
Miguel T. Galante, Aleksandar Živković, Jéssica Costa Alvim, Cinthia Cristina Calchi Kleiner, Márcio Sangali, S. F. Rebecca Taylor, Adam J. Greer, Christopher Hardacre, Krishnan Rajeshwar, Rubens Caram, Rodnei Bertazzoli, Robin T. Macaluso, Nora Henriette de Leeuw, Claudia Longo
Read original paper ↗ ·Autonomous reinforcement learning agent for chemical vapor deposition synthesis of quantum materials
npj Computational Materials · 2021
Pankaj Rajak, Aravind Krishnamoorthy, Ankit Mishra, Rajiv K. Kalia, Aiichiro Nakano, Priya D. Vashishta
Read original paper ↗ ·Active-Learning-Based Generative Design for the Discovery of Wide-Band-Gap Materials
The Journal of Physical Chemistry C · 2021
Rui Xin, Edirisuriya M. Dilanga Siriwardane, Yuqi Song, Yong Zhao, Steph-Yves Louis, Alireza Nasiri, Jianjun Hu
Read original paper ↗ ·Neural evolution structure generation: High entropy alloys
The Journal of Chemical Physics · 2021
Conrard Giresse Tetsassi Feugmo, Kevin Ryczko, Abu Anand, Chandra Veer Singh, Isaac Tamblyn
Read original paper ↗ ·The evolution of Materials Acceleration Platforms: toward the laboratory of the future with AMANDA
Journal of Materials Science · 2021
Jerrit Wagner, Christian G. Berger, Xiaoyan Du, Tobias Stubhan, Jens Hauch, Christoph J. Brabec
Read original paper ↗ ·Learning hidden elasticity with deep neural networks
Proceedings of the National Academy of Sciences · 2021
Chun‐Teh Chen, Grace X. Gu
Read original paper ↗ ·Can Metal Intermixing Cooperatively Improve Perovskites as Redox Materials for Thermochemical Ammonia Synthesis? A Case Study on (Sr,Y)(Ti,Ru)O3
The Journal of Physical Chemistry C · 2021
Qianli Si, Jack Y. Yang, Jiaxin Fan, Liang Qiao, Sean Li
Read original paper ↗ ·Machine learning for materials discovery: Two-dimensional topological insulators
Applied Physics Reviews · 2021
Gabriel Ravanhani Schleder, Bruno Focassio, A. Fazzio
Read original paper ↗ ·Crystal structure prediction of materials with high symmetry using differential evolution
Journal of Physics Condensed Matter · 2021
Wenhui Yang, Edirisuriya M. Dilanga Siriwardane, Rongzhi Dong, Yuxin Li, Jianjun Hu
Read original paper ↗ ·Differentiable sampling of molecular geometries with uncertainty-based adversarial attacks
Nature Communications · 2021
Daniel Schwalbe-Koda, Aik Rui Tan, Rafael Gómez-Bombarelli
Read original paper ↗ ·Computational methods for 2D materials modelling
Reports on Progress in Physics · 2021
Alexandra Carvalho, Paolo Emilio Trevisanutto, Simone Taioli, A. H. Castro Neto
Read original paper ↗ ·Inverse Design Framework With Invertible Neural Networks for Passive Vibration Suppression in Phononic Structures
Journal of Mechanical Design · 2021
Manaswin Oddiraju, Amir Behjat, Mostafa A. Nouh, Souma Chowdhury
Read original paper ↗ ·Predicting gas–particle partitioning coefficients of atmospheric molecules with machine learning
Atmospheric chemistry and physics · 2021
Emma Lumiaro, Milica Todorović, Theo Kurtén, Hanna Vehkamäki, Patrick Rinke
Read original paper ↗ ·Different shapes of spin textures as a journey through the Brillouin zone
Physical review. B./Physical review. B · 2021
Carlos Mera Acosta, Lin‐Ding Yuan, Gustavo M. Dalpian, Alex Zunger
Read original paper ↗ ·Inverse design of glass structure with deep graph neural networks
Nature Communications · 2021
Qi Wang, Longfei Zhang
Read original paper ↗ ·Discovery of complex oxides via automated experiments and data science
Proceedings of the National Academy of Sciences · 2021
Lusann Yang, Joel A. Haber, Zan Armstrong, Samuel Yang, Kevin Kan, Lan Zhou, Matthias Hermann Richter, C. Roat, Nicholas Wagner, Marc Coram, Marc Berndl, Patrick Riley, John M. Gregoire
Read original paper ↗ ·Relationships between Distortions of Inorganic Framework and Band Gap of Layered Hybrid Halide Perovskites
Chemistry of Materials · 2021
Ekaterina I. Marchenko, Vadim Korolev, Sergey A. Fateev, Artem A. Mitrofanov, Nikolay N. Eremin, Eugene Alekseevich Goodilin, Alexey B. Tarasov
Read original paper ↗ ·Photocatalytic Z‐Scheme Overall Water Splitting: Recent Advances in Theory and Experiments
Advanced Materials · 2021
Jamal Abdul Nasir, Akhtar Munir, Naveed Ahmad, Tanveer ul Haq, Zaibunisa Khan, Ziaur Rehman
Read original paper ↗ ·Data Science Applied to Carbon Materials: Synthesis, Characterization, and Applications
Advanced Theory and Simulations · 2021
Aaron Morelos‐Gómez, Mauricio Terrones, Morinobu Endo
Read original paper ↗ ·Enhancing spectral response towards high-performance dye-sensitised solar cells by multiple dye approach: A comprehensive review
Applied Materials Today · 2021
Md. Akhtaruzzaman, Md. Shahiduzzaman, Vidhya Selvanathan, Kamaruzzaman Sopian, Mohammad Ismail Hossain, Nowshad Amin, A. K. Mahmud Hasan
Read original paper ↗ ·Bayesian optimization for chemical products and functional materials
Current Opinion in Chemical Engineering · 2021
Ke Wang, Alexander W. Dowling
Read original paper ↗ ·Machine‐Learning Microstructure for Inverse Material Design
Advanced Science · 2021
Zongrui Pei, Kyle A. Rozman, Ömer N. Doğan, Youhai Wen, Nan Gao, Elizabeth A. Holm, Jeffrey A. Hawk, David E. Alman, Michael C. Gao
Read original paper ↗ ·Artificial Intelligence for Autonomous Molecular Design: A Perspective
Molecules · 2021
Rajendra Prasad Joshi, Neeraj Kumar
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 ↗ ·Iterative peak-fitting of frequency-domain data via deep convolution neural networks
Journal of the Korean Physical Society · 2021
Seong-Heum Park, Hyeongseon Park, Hyunbok Lee, Heung‐Sik Kim
Read original paper ↗ ·On-the-fly interpretable machine learning for rapid discovery of two-dimensional ferromagnets with high Curie temperature
Chem · 2021
Shuaihua Lu, Qionghua Zhou, Yilv Guo, Jinlan Wang
Read original paper ↗ ·Inverse Design of Nanoparticles Using Multi‐Target Machine Learning
Advanced Theory and Simulations · 2021
Sichao Li, Amanda Susan Barnard
Read original paper ↗ ·Inverse design of two-dimensional materials with invertible neural networks
npj Computational Materials · 2021
Victor Fung, Jiaxin Zhang, Guoxiang Hu, Panchapakesan Ganesh, Bobby G. Sumpter
Read original paper ↗ ·An invertible crystallographic representation for general inverse design of inorganic crystals with targeted properties
Matter · 2021
Zekun Ren, Siyu Isaac Parker Tian, Juhwan Noh, Felipe Oviedo, Guangzong Xing, Jiali Li, Qiaohao Liang, Ruiming Zhu, Armin Gerhard Aberle, Shijing Sun, Xiaonan Wang, Yi Liu, Qianxiao Li, J. Senthilnath, Kedar Hippalgaonkar, Yousung Jung, Tonio Buonassisi
Read original paper ↗ ·Advancing statistical learning and artificial intelligence in nanophotonics inverse design
Nanophotonics · 2021
Qizhou Wang, Maksim O. Makarenko, Arturo Burguete Lopez, Fedor Getman, Andrea Fratalocchi
Read original paper ↗ ·Two-dimensional oxides assembled by M4 clusters ( M=B , Al, Ga, In, Cr, Mo, and Te)
Physical Review Research · 2021
Yu Yang Guo, Qiuying Du, Pengju Wang, Si Zhou, Jijun Zhao
Read original paper ↗ ·