Papers citing A Critical Review of Machine Learning of Energy Materials
Electrocatalyst design for aprotic Li–CO 2 batteries
Energy & Environmental Science · 2020
Zhen Zhang, Wen-Long Bai, Kai‐Xue Wang, Jie-Sheng Chen
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 ↗ ·Recent Advances in Platinum-based Intermetallic Nanocrystals: Controlled Synthesis and Electrocatalytic Applications
Acta Physico-Chimica Sinica · 2020
Tianyi Yang, Cheng Cui, Hongpan Rong, Jiatao Zhang, Dingsheng S. Wang
Read original paper ↗ ·Searching for stable perovskite solar cell materials using materials genome techniques and high-throughput calculations
Journal of Materials Chemistry C · 2020
Qingde Sun, Wan‐Jian Yin, Su‐Huai Wei
Read original paper ↗ ·AI Fast Track to Battery Fast Charge
Joule · 2020
Arghya Bhowmik, Tejs Vegge
Read original paper ↗ ·Benchmark Synthetic Training Data for Artificial Intelligence-based Li-ion Diagnosis and Prognosis
Journal of Power Sources · 2020
Matthieu Dubarry, David Beck
Read original paper ↗ ·Quantum Chemistry-Informed Active Learning to Accelerate the Design and Discovery of Sustainable Energy Storage Materials
Chemistry of Materials · 2020
Hieu Anh Doan, Garvit Agarwal, Hai Qian, Michael John Counihan, Joaquín Rodríguez‐López, Jeffrey S. Moore, Rajeev S. Assary
Read original paper ↗ ·Accelerating Battery Manufacturing Optimization by Combining Experiments, In Silico Electrodes Generation and Machine Learning
ChemRxiv · 2020
Marc Duquesnoy, Teo Lombardo, Mehdi Chouchane, Emiliano N. Primo, Alejandro A. Franco
Read original paper ↗ ·Accelerating Battery Manufacturing Optimization by Combining Experiments, In Silico Electrodes Generation and Machine Learning
ChemRxiv · 2020
Marc Duquesnoy, Teo Lombardo, Mehdi Chouchane, Emiliano N. Primo, Alejandro A. Franco
Read original paper ↗ ·Importance of structural deformation features in the prediction of hybrid perovskite bandgaps
Computational Materials Science · 2020
Heesoo Park, Raghvendra Mall, Adnan Ali, Stefano Sanvito, Halima Bensmail, Fedwa El‐Mellouhi
Read original paper ↗ ·Deep learning and knowledge-based methods for computer-aided molecular design—toward a unified approach: State-of-the-art and future directions
Computers & Chemical Engineering · 2020
Abdulelah S. Alshehri, Rafiqul Gani A, Fengqi You
Read original paper ↗ ·Machine learning assisted materials design and discovery for rechargeable batteries
Energy storage materials · 2020
Yue Liu, Biru Guo, Xinxin Zou, Yajie Li, Siqi Shi
Read original paper ↗ ·Data-Driven Materials Discovery from Large Chemistry Spaces
Matter · 2020
Isao Tanaka
Read original paper ↗ ·Modelling and understanding battery materials with machine-learning-driven atomistic simulations
Journal of Physics Energy · 2020
Volker L. Deringer
Read original paper ↗ ·Machine learning in experimental materials chemistry
Catalysis Today · 2020
Balaranjan Selvaratnam, Ranjit T. Koodali
Read original paper ↗ ·Effect of Increasing the Descriptor Set on Machine Learning Prediction of Small Molecule-Based Organic Solar Cells
Chemistry of Materials · 2020
Zhi‐Wen Zhao, Marcos del Cueto, Yun Geng, Alessandro Troisi
Read original paper ↗ ·Machine learning for halide perovskite materials
Nano Energy · 2020
Lei Zhang, Mu He, Shaofeng Shao
Read original paper ↗ ·Exchange Spin Coupling from Gaussian Process Regression
The Journal of Physical Chemistry A · 2020
Marc Philipp Bahlke, Natnael Mogos, Jonny Proppe, Carmen Herrmann
Read original paper ↗ ·A Two-Stage Monte Carlo Approach for Optimization of Bimetallic Nanostructures
Annals of Computer Science and Information Systems · 2020
Rossen Mikhov, Владимир Сергеевич Мясниченко, Leoneed M. Kirilov, Nickolay Yu. Sdobnyakov, Павел Викторович Матренин, Денис Николаевич Соколов, Stefka Stoyanova Fidanova
Read original paper ↗ ·Element Code from Pseudopotential as Efficient Descriptors for a Machine Learning Model to Explore Potential Lead-Free Halide Perovskites
The Journal of Physical Chemistry Letters · 2020
Meng‐Huan Jao, Shun‐Hsiang Chan, Ming‐Chung Wu, Chao‐Sung Lai
Read original paper ↗ ·Design of Polymer Blend Electrolytes through a Machine Learning Approach
Macromolecules · 2020
Bill K. Wheatle, Erick F. Fuentes, Nathaniel A. Lynd, Venkat Ganesan
Read original paper ↗ ·Machine Learning and Digital Twin Driven Diagnostics and Prognostics of Light‐Emitting Diodes
Laser & Photonics Review · 2020
Mesfin Seid Ibrahim, Jiajie Fan, Winco K. C. Yung, Alexandru Prisacaru, Willem Dirk van Driel, Xuejun Fan, Guoqi Zhang
Read original paper ↗ ·Critical review of machine learning applications in perovskite solar research
Nano Energy · 2020
Beyza Yılmaz, Ramazan Yıldırım
Read original paper ↗ ·Machine Learning for Atomic Simulation and Activity Prediction in Heterogeneous Catalysis: Current Status and Future
ACS Catalysis · 2020
Sicong Ma, Zhi‐Pan Liu
Read original paper ↗ ·Data-driven assessment of electrode calendering process by combining experimental results, in silico mesostructures generation and machine learning
Journal of Power Sources · 2020
Marc Duquesnoy, Teo Lombardo, Mehdi Chouchane, Emiliano N. Primo, Alejandro A. Franco
Read original paper ↗ ·Ultra-fast and accurate binding energy prediction of shuttle effect-suppressive sulfur hosts for lithium-sulfur batteries using machine learning
Energy storage materials · 2020
Haikuo Zhang, Zhilong Wang, Jiahao Ren, Jinyun Liu, Jinjin Li
Read original paper ↗ ·Accelerating Discovery of Metal–Organic Frameworks for Methane Adsorption with Hierarchical Screening and Deep Learning
ACS Applied Materials & Interfaces · 2020
Ruihan Wang, Yeshuang Zhong, Leming Bi, Mingli Yang, Dingguo Xu
Read original paper ↗ ·Enabling robust offline active learning for machine learning potentials using simple physics-based priors
Machine Learning Science and Technology · 2020
Muhammed Shuaibi, Saurabh Sivakumar, Rui Qi Chen, Zachary W. Ulissi
Read original paper ↗ ·Inverse design of composite metal oxide optical materials based on deep transfer learning and global optimization
Computational Materials Science · 2020
Rongzhi Dong, Yabo Dan, Xiang Li, Jianjun Hu
Read original paper ↗ ·Machine learning for high performance organic solar cells: current scenario and future prospects
Energy & Environmental Science · 2020
Asif Mahmood, Jin‐Liang Wang
Read original paper ↗ ·Disorder in energy materials and strategies to model it
Advances in Physics X · 2020
Josè Carlos Madrid Madrid, Kulbir Kaur Ghuman
Read original paper ↗ ·Accelerated discovery of stable spinels in energy systems via machine learning
Nano Energy · 2020
Zhilong Wang, Haikuo Zhang, Jinjin Li
Read original paper ↗ ·Machine learning toward advanced energy storage devices and systems
iScience · 2020
Tianhan Gao, Wei D. Lu
Read original paper ↗ ·The Application of Data-Driven Methods and Physics-Based Learning for Improving Battery Safety
Joule · 2020
Donal P. Finegan, Juner Zhu, Xuning Feng, Matthew A. Keyser, Marcus Ulmefors, Wei Li, Martin Z. Bazant, Samuel J. Cooper
Read original paper ↗ ·Accelerated discovery of boron-dipyrromethene sensitizer for solar cells by integrating data mining and first principle
Journal of Materiomics · 2020
Tian Lu, Minjie Li, Zhenpeng Yao, Wencong Lu
Read original paper ↗ ·A data-driven XRD analysis protocol for phase identification and phase-fraction prediction of multiphase inorganic compounds
Inorganic Chemistry Frontiers · 2021
Jin-Woong Lee, Woon Bae Park, Minseuk Kim, Satendra Pal Singh, Myoungho Pyo, Kee‐Sun Sohn
Read original paper ↗ ·Accelerating evaluation of the mobility of ionic liquid-modulated PEDOT flexible electronics using machine learning
Journal of Materials Chemistry A · 2021
Wei‐Lu Ding, Yumiao Lu, Xing‐Liang Peng, Hao Dong, Weijie Chi, Xiaoqing Yuan, Zhu‐Zhu Sun, Hongyan He
Read original paper ↗ ·Bandgap tuning strategy by cations and halide ions of lead halide perovskites learned from machine learning
RSC Advances · 2021
Yaoyao Li, Yao Lu, Xiaomin Huo, Dong Wei, Juan Meng, Jie Dong, Bo Qiao, Suling Zhao, Zheng Xu, Dandan Song
Read original paper ↗ ·Classification of Retroviruses Based on Genomic Data Using RVGC
Computers, materials & continua/Computers, materials & continua (Print) · 2021
Khalid Mahmood Aamir, Muhammad Bilal, Muhammad Ramzan, Muhammad Attique Khan, Yunyoung Nam, Seifedine Kadry
Read original paper ↗ ·Designing positive electrodes with high energy density for lithium-ion batteries
Journal of Materials Chemistry A · 2021
Masashi Okubo, Seongjae Ko, Debasmita Dwibedi, Atsuo Yamada
Read original paper ↗ ·Determining usefulness of machine learning in materials discovery using simulated research landscapes
Physical Chemistry Chemical Physics · 2021
Marcos del Cueto, Alessandro Troisi
Read original paper ↗ ·Generative models for inverse design of inorganic solid materials
Journal of Materials Informatics · 2021
Litao Chen, Wentao Zhang, Zhiwei Nie, Shunning Li, Feng Ming Pan
Read original paper ↗ ·High-throughput virtual screening for organic electronics: a comparative study of alternative strategies
Journal of Materials Chemistry C · 2021
Ömer H. Omar, Marcos del Cueto, Tahereh Nematiaram, Alessandro Troisi
Read original paper ↗ ·Machine Learning in X-ray Imaging and Microscopy Applications
Springer eBooks · 2021
Guoxu Zhang
Read original paper ↗ ·Modelling of phase stability: integrating computational materials science and materials informatics
Journal of Materials Informatics · 2021
Xiaoyan Song, Kai Guo, Hao Lu, Dong Liu, Fawei Tang
Read original paper ↗ ·Nanoarchitectonics on living cells
RSC Advances · 2021
Katsuhiko Ariga, Rawil F. Fakhrullin
Read original paper ↗ ·Machine learned features from density of states for accurate adsorption energy prediction
Nature Communications · 2021
Victor Fung, Guoxiang Hu, Panchapakesan Ganesh, Bobby G. Sumpter
Read original paper ↗ ·Digital Transformation in Materials Science: A Paradigm Change in Material's Development
Advanced Materials · 2021
Julian Kimmig, Stefan Zechel, Ulrich S. Schubert
Read original paper ↗ ·Doping-Induced Charge Localization Suppresses Electron–Hole Recombination in Copper Zinc Tin Sulfide: Quantum Dynamics Combined with Deep Neural Networks Analysis
The Journal of Physical Chemistry Letters · 2021
Zhaosheng Zhang, Yan Zhang, Jiazheng Wang, Jianzhong Xu, Run Long
Read original paper ↗ ·Opportunities for Next-Generation Luminescent Materials through Artificial Intelligence
The Journal of Physical Chemistry Letters · 2021
Ya Zhuo, Jakoah Brgoch
Read original paper ↗ ·