Papers citing A Critical Review of Machine Learning of Energy Materials
Machine Learning‐Based and Experimentally Validated Optimal Adhesive Fibril Designs
Small · 2021
Donghoon Son, Ville Liimatainen, Metin Sitti
Read original paper ↗ ·Machine Learning in Chemical Product Engineering: The State of the Art and a Guide for Newcomers
Processes · 2021
Cindy Trinh, Dimitrios Meimaroglou, Sandrine Hoppe
Read original paper ↗ ·Nanoarchitectonics for Hierarchical Fullerene Nanomaterials
Nanomaterials · 2021
Subrata Maji, Lok Kumar Shrestha, Katsuhiko Ariga
Read original paper ↗ ·Leveraging Transfer Learning and Chemical Principles toward Interpretable Materials Properties
Journal of Chemical Information and Modeling · 2021
Liyuan Huang, Chen Ling
Read original paper ↗ ·Use of metamodels for rapid discovery of narrow bandgap oxide photocatalysts
iScience · 2021
Haoxin Mai, Tu C. Le, Takashi Hisatomi, Dehong Chen, Kazunari Domen, David Alan Winkler, Rachel A. Caruso
Read original paper ↗ ·Neural network potential for studying the thermal conductivity of Sn
Computational Materials Science · 2021
Lihong Han, Xingrun Chen, Qian Wang, Yingjie Chen, Mingfei Xu, Liyuan Wu, Changcheng Chen, Pengfei Lu, Pengfei Guan
Read original paper ↗ ·Machine Learning: An Advanced Platform for Materials Development and State Prediction in Lithium‐Ion Batteries
Advanced Materials · 2021
Chade Lv, Xin Zhou, Lixiang Zhong, Chunshuang Yan, Madhavi Srinivasan, Zhi Wei Seh, Chuntai Liu, Hongge Pan, Shuzhou Li, Yonggang Wen, Qingyu Yan
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 ↗ ·Artificial Intelligence Applied to Battery Research: Hype or Reality?
Chemical Reviews · 2021
Teo Lombardo, Marc Duquesnoy, Hassna El-Bouysidy, Fabian Årén, A. Gallo‐Bueno, Peter Bjørn Jørgensen, Arghya Bhowmik, Arnaud Demortière, Elixabete Ayerbe, Francisco Alcaide, Marine Reynaud, Javier Carrasco, Alexis Grimaud, Chao Zhang, Tejs Vegge, Patrik Johansson, Alejandro A. Franco
Read original paper ↗ ·Extrapolative Bayesian Optimization with Gaussian Process and Neural Network Ensemble Surrogate Models
Advanced Intelligent Systems · 2021
Yee‐Fun Lim, Chee Koon Ng, U. S. Vaitesswar, Kedar Hippalgaonkar
Read original paper ↗ ·Multiobjective Stepwise Design Strategy-Assisted Design of High-Performance Perovskite Oxide Photocatalysts
The Journal of Physical Chemistry C · 2021
Qiuling Tao, Dongping Chang, Tian Lu, Long Li, Huimin Chen, Xue Yang, Xiujuan Liu, Minjie Li, Wencong Lu
Read original paper ↗ ·Perspectives for next generation lithium-ion battery cathode materials
APL Materials · 2021
Samuel Guy Booth, Alisyn J. Nedoma, Nirmalesh N. Anthonisamy, Peter J. Baker, Rebecca Boston, Hugo A. Bronstein, Simon J. Clarke, Edmund J. Cussen, Venkateswarlu Daramalla, Michael F. L. De Volder, Siân E. Dutton, Viktoria Falkowski, Norman Andrew Fleck, Harry S. Geddes, Naresh Gollapally, Andrew L. Goodwin, John M. Griffin, Abby R. Haworth, Michael A. Hayward, S. Hull, Beverley J. Inkson, Beth J. Johnston, Ziheng Lu, Judith L. MacManus‐Driscoll, Xabier Martínez de Irujo-Labalde, Innes McClelland, Kirstie S. McCombie, Beth E. Murdock, Debasis Nayak, Seung-Kyu Park, Gabriel E. Pérez, Chris J. Pickard, Louis F. J. Piper, Helen Y. Playford, Simon Price, David O. Scanlon, Joe C. Stallard, Nuria Tapia‐Ruiz, Anthony R. West, Laura Wheatcroft, Megan Wilson, Li Zhang, Xuan Zhi, Bonan Zhu, Serena A. Cussen
Read original paper ↗ ·Ab initio molecular dynamics with enhanced sampling in heterogeneous catalysis
Catalysis Science & Technology · 2021
GiovanniMaria Piccini, Mal‐Soon Lee, Simuck F. Yuk, Difan Zhang, Greg Collinge, Loukas Kollias, Manh‐Thuong Nguyen, Vassiliki‐Alexandra Glezakou, Roger J. Rousseau
Read original paper ↗ ·Machine Learning Accelerates the Discovery of Light-Absorbing Materials for Double Perovskite Solar Cells
The Journal of Physical Chemistry C · 2021
Zhenqing Yang, Yanbing Liu, Yun‐Qian Zhang, Liqun Wang, Chundan Lin, Yuzhuo Lv, Yuhang Ma, Changjin Shao
Read original paper ↗ ·AtomSets as a hierarchical transfer learning framework for small and large materials datasets
npj Computational Materials · 2021
Chi Chen, Shyue Ping Ong
Read original paper ↗ ·Analysis and Prediction of Hydrothermally Synthesized ZnO-Based Dye-Sensitized Solar Cell Properties Using Statistical and Machine-Learning Techniques
ACS Omega · 2021
Santosh Shashikant Sutar, Suvarna M. Patil, Sunil J. Kadam, Rajanish K. Kamat, Deok‐kee Kim, Tukaram Dattatray Dongale
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 ↗ ·spectrapepper: A Python toolbox for advanced analysis of spectroscopic data for materials and devices.
The Journal of Open Source Software · 2021
Enric Grau‐Luque, Fabien Atlan, Ignacio Becerril‐Romero, Alejandro Pérez-Rodríguez, Maxim Guc, Víctor Izquierdo‐Roca
Read original paper ↗ ·Optimising the photovoltaic parameters in donor–acceptor–acceptor ternary polymer solar cells using Machine Learning framework
Solar Energy · 2021
Fiyanshu Kaka, Manjeet Keshav, Praveen C. Ramamurthy
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 ↗ ·Δ-Machine learning-driven discovery of double hybrid organic–inorganic perovskites
Journal of Materials Chemistry A · 2021
Jialu Chen, Wenjun Xu, Rui-Qin Zhang
Read original paper ↗ ·On the Problem of Bimetallic Nanostructures Optimization: An Extended Two-Stage Monte Carlo Approach
Studies in computational intelligence · 2021
Rossen Mikhov, Владимир Сергеевич Мясниченко, Leoneed M. Kirilov, Nickolay Yu. Sdobnyakov, Павел Викторович Матренин, Денис Николаевич Соколов, Stefka Stoyanova Fidanova
Read original paper ↗ ·Sparse modeling for small data: case studies in controlled synthesis of 2D materials
Digital Discovery · 2021
Yuri Haraguchi, Yasuhiko Igarashi, Hiroaki Imai, Yuya Oaki
Read original paper ↗ ·Accelerating the theoretical study of Li-polysulphide adsorption on single-atom catalysts via machine learning approaches
arXiv (Cornell University) · 2021
Eleftherios I. Andritsos, Kevin Rossi
Read original paper ↗ ·Data-Driven Methods for Accelerating Polymer Design
ACS Polymers Au · 2021
Tarak K. Patra
Read original paper ↗ ·Applications of machine learning in computational nanotechnology
Nanotechnology · 2021
Wenxiang Liu, Yongqiang Wu, Yang Hong, Zhongtao Zhang, Yanan Yue, Jingchao Zhang
Read original paper ↗ ·Accelerated exploration of efficient ternary solar cells with PTB7:PC 71 BM:SMPV1 using machine-learning methods
Physical Chemistry Chemical Physics · 2022
Chaorong Guo, Zhennan Li, Kuo Wang, Xunchen Zhou, Di Huang, Jiaojiao Liang, Ling Zhao
Read original paper ↗ ·Adaptive Learning-Driven High-Throughput Synthesis of Oxygen Reduction Reaction Fe-N-C Electrocatalysts
Journal of Power Sources · 2022
Wilton J. M. Kort-Kamp, Magali S. Ferrandon, Xiaoping P. Wang, Jae Hyung Park, Rajesh K. Malla, Towfiq Ahmed, Edward F. Holby, Deborah J. Myers, Piotr Zelenay
Read original paper ↗ ·Failure, Uncertainty, and Risk in Materials AI — How Negative Outcomes Are Handled Across the Literature: A Review Study
Journal of Artificial Intelligence for Materials Science · 2022
Ravi Menon, Arjun Nair, Meera Pillai, Suresh Varma
Read original paper ↗ ·Health Monitoring, Machine Learning, and Digital Twin for LED Degradation Analysis
Springer eBooks · 2022
Mesfin Seid Ibrahim, Zhou Jing, Jiajie Fan
Read original paper ↗ ·High-temperature ionic logic gates composed of an ionic rectifying solid–electrolyte interface
RSC Advances · 2022
Takashi Nakamura, Miri Honda, Yuta Kimura, Koji Amezawa
Read original paper ↗ ·Limitations of machine learning models when predicting compounds with completely new chemistries: possible improvements applied to the discovery of new non-fullerene acceptors
Digital Discovery · 2022
Zhi‐Wen Zhao, Marcos del Cueto, Alessandro Troisi
Read original paper ↗ ·Machine learning enabled characterization of charge transport in organic semiconducting devices
Venue not supplied by source · 2022
Madhavkrishnan Lakshminarayanan
Read original paper ↗ ·Machine learning-driven advanced development of carbon-based luminescent nanomaterials
Journal of Materials Chemistry C · 2022
Diva Addini Maghribi Muyassiroh, Fitri Aulia Permatasari, Ferry Iskandar
Read original paper ↗ ·Manufacturing improvement capabilities of machine learning algorithms: Evaluation using an electrode-separator compound handling demonstrator
Procedia CIRP · 2022
Sören Dittmann, Arne Glodde, Franz Dietrich
Read original paper ↗ ·Materials property prediction using feature selection based machine learning technique
Materials Today Proceedings · 2022
K. Valli Priyadharshini, A. Vijay, K. Swaminathan, T. Avudaiappan, V Banupriya
Read original paper ↗ ·Na superionic conductor-type LiZr 2 (PO 4 ) 3 as a promising solid electrolyte for use in all-solid-state Li metal batteries
Chemical Communications · 2022
Masanobu Nakayama, K. Nakano, Maho Harada, Naoto Tanibata, Hayami Takeda, Yusuke Noda, Ryo Kobayashi, Masayuki Karasuyama, Ichiro Takeuchi, Masashi Kotobuki
Read original paper ↗ ·Opportunities and challenges for machine learning to select combination of donor and acceptor materials for efficient organic solar cells
Journal of Materials Chemistry C · 2022
Prateek Malhotra, Kanupriya Khandelwal, Subhayan Biswas, Fang‐Chung Chen, Ganesh Datt Sharma
Read original paper ↗ ·Prediction of material property using optimized augmented graph-attention layer in GNN
Materials Today Proceedings · 2022
V. Sathana, M. Mathumathi, K. Makanyadevi
Read original paper ↗ ·Progress, challenges and perspectives of computational studies on glassy superionic conductors for solid-state batteries
Journal of Materials Chemistry A · 2022
Zhenming Xu, Yongyao Xia
Read original paper ↗ ·Prospects and challenges for autonomous catalyst discovery viewed from an experimental perspective
Catalysis Science & Technology · 2022
Annette Trunschke
Read original paper ↗ ·Recent progress in the data-driven discovery of novel photovoltaic materials
Journal of Materials Informatics · 2022
Lu Tian, Minjie Li, Wencong Lu, Tong‐Yi Zhang
Read original paper ↗ ·The Role of Surprise in AI-Driven Materials Discovery
Journal of Artificial Intelligence for Materials Science · 2022
Claire Martin, Sophie Bernard, Julien Robert
Read original paper ↗ ·Unraveling the importance of fabrication parameters of copper oxide-based resistive switching memory devices by machine learning techniques
Scientific Reports · 2022
Suvarna M. Patil, Somnath Suhas Kundale, Santosh Shashikant Sutar, Pramod J. Patil, Aviraj Mahadev Teli, Sonali Ajay Beknalkar, Rajanish K. Kamat, Jinho Bae, Jae Cheol Shin, Tukaram Dattatray Dongale
Read original paper ↗ ·When Models Agree for the Wrong Reasons: A Conceptual Analysis of Consensus in Materials AI
Journal of Artificial Intelligence for Materials Science · 2022
Nguyen Thanh Huy, Pham Quang Minh, Le Thi Bich
Read original paper ↗ ·High‐Efficiency Non‐Fullerene Acceptors Developed by Machine Learning and Quantum Chemistry
Advanced Science · 2022
Qi Zhang, Yujie Zheng, Wenbo Sun, Zeping Ou, Omololu Odunmbaku, Meng Li, Shanshan Chen, Yongli Zhou, Jing Li, Bo Qin, Kuan Sun
Read original paper ↗ ·Three-dimensional modeling of Lithium-ion battery electrode manufacturing
Venue not supplied by source · 2022
Teo Lombardo
Read original paper ↗ ·Design high-entropy carbide ceramics from machine learning
npj Computational Materials · 2022
Jun Zhang, Biao Xu, Yaoxu Xiong, Shihua Ma, Zhe Wang, Zhenggang Wu, Shijun Zhao
Read original paper ↗ ·Electrocatalytic Oxygen Evolution Reaction
Venue not supplied by source · 2022
Guanyu Liu, Joel W. Ager
Read original paper ↗ ·Performance Predictors for Organic Cathodes of Lithium-Ion Battery
ACS Applied Energy Materials · 2022
Kosuke Sakano, Yasuhiko Igarashi, Hiroaki Imai, Shuntaro Miyakawa, Takaya Saito, Yoshiki Takayanagi, Koji Nishiyama, Yuya Oaki
Read original paper ↗ ·