Papers citing Machine learning for perovskite materials design and discovery
Perovskite micro-/nanoarchitecture for photonic applications
Matter · 2023
Yang Liu, Fushan Li, Wei Huang
Read original paper ↗ ·Reinforced active learning for CVD-grown two-dimensional materials characterization
IISE Transactions · 2023
Zebin Li, Fei Yao, Hongyue Sun
Read original paper ↗ ·Virtual sample generation in machine learning assisted materials design and discovery
Journal of Materials Informatics · 2023
Pengcheng Xu, Xiaobo Ji, Minjie Li, Wencong Lu
Read original paper ↗ ·Critical analysis of decision variables for high-throughput experimentation (HTE) with perovskite solar cells
Solar Energy · 2023
Naveen Bhati, Mohammad Khaja Nazeeruddin, Francois M. A. Marechal
Read original paper ↗ ·Interface State Density Prediction between an Insulator and a Semiconductor by Gaussian Process Regression Models for a Modified Process
ACS Omega · 2023
Kanta Matsunaga, Takuto Harada, Shintaro Harada, Akinori Sato, Shota Terai, Mutsunori Uenuma, Tomoyuki Miyao, Yukiharu Uraoka
Read original paper ↗ ·Passivation strategies for enhancing device performance of perovskite solar cells
Nano Energy · 2023
Zhifang Wu, Enbing Bi, Luis K. Ono, Deng‐Bing Li, Osman M. Bakr, Yanfa Yan, Yabing Qi
Read original paper ↗ ·Optimizing and extending ion dielectric polarizability database for microwave frequencies using machine learning methods
npj Computational Materials · 2023
Jincheng Qin, Zhifu Liu, Mingsheng Ma, Yongxiang Li
Read original paper ↗ ·Machine Learning Enhanced High‐Throughput Fabrication and Optimization of Quasi‐2D Ruddlesden–Popper Perovskite Solar Cells
Advanced Energy Materials · 2023
Nastaran Meftahi, Maciej Adam Surmiak, Sebastian O. Fürer, Kevin J. Rietwyk, Jianfeng Lu, Sonia R. Raga, C.C. Evans, Monika Michalska, Hao Deng, David P. McMeekin, Tuncay Alan, Dechan Angmo, Doojin Vak, Anthony Chesman, Andrew Joseph Christofferson, David A. Winkler, Udo Bach, Salvy P. Russo
Read original paper ↗ ·Assessing Performance and Limitations of a Device‐Level Machine Learning Approach for Perovskite Solar Cells with an Application to Hole Transport Materials
Solar RRL · 2023
Simone Sala, Eleonora Quadrivi, Paolo Biagini, Riccardo Pó
Read original paper ↗ ·High-Throughput Screening on Halide Perovskite Derivatives and Rational Design of Cs 3 LuCl 6
ACS Energy Letters · 2023
Hyeon Woo Kim, Joo Hyeong Han, Hyunseok Ko, Tuhin Samanta, Dong Geon Lee, Dong Won Jeon, Woongchan Kim, Yong‐Chae Chung, Won Bin Im, Sung Beom Cho
Read original paper ↗ ·Performance Enhancement and Stability Improvement in Perovskite Solar Cells via Interface Functionalization
Electronics · 2023
Christos Falaras, Elias Stathatos
Read original paper ↗ ·Meta-analysis of CO2 conversion, energy efficiency, and other performance data of plasma-catalysis reactors with the open access PIONEER database
Journal of Energy Chemistry · 2023
Toine P.W. Salden, Maik Budde, Carolina A. Garcia-Soto, Omar Biondo, Jairo Barauna, Marzia Faedda, Beatrice Musig, Chloé Fromentin, Minh Nguyen-Quang, Harry Philpott, Golshid Hasrack, Domenico Aceto, Yuxiang Cai, Federico Azzolina-Jury, Annemie Bogaerts, Patrick Da Costa, R. Engeln, María Elena Gálvez, Timo Gans, Tomás García, Vasco Guerra, Carlos Henriques, Monika Motak, M.V. Navarro, Vasile Ion Parvulescu, Gerard J. van Rooij, Bogdan Samojeden, Ana Sobota, Paolo Tosi, Xin Tu, Olivier Guaitella
Read original paper ↗ ·MIC-SHAP: An ensemble feature selection method for materials machine learning
Materials Today Communications · 2023
Junya Wang, Pengcheng Xu, Xiaobo Ji, Minjie Li, Wencong Lu
Read original paper ↗ ·Hot-Electron Dynamics Mediated Medical Diagnosis and Therapy
Chemical Reviews · 2023
Bing Luo, Wei Wang, Yuxin Zhao, Yanli Zhao
Read original paper ↗ ·Machine learning approach for predicting electrical features of Schottky structures with graphene and ZnTiO3 nanostructures doped in PVP interfacial layer
Scientific Reports · 2023
Ali Barkhordari, Hamid Reza Mashayekhi, Pari Amiri, Süleyman Özçelik, Ş. Altındal, Yashar Azizian‐Kalandaragh
Read original paper ↗ ·Revolutionizing Low‐Cost Solar Cells with Machine Learning: A Systematic Review of Optimization Techniques
Advanced Energy and Sustainability Research · 2023
Satyam Bhatti, Habib Ullah Manzoor, Bruno Michel, Ruy S. Bonilla, Richard Abrams, Ahmed Zoha, Sajjad Hussain, Rami Ghannam
Read original paper ↗ ·Importance of Structural Features and the Influence of Individual Structures of Graphene Oxide Using Shapley Value Analysis
Chemistry of Materials · 2023
Amanda Susan Barnard, Bronwyn Louise Fox
Read original paper ↗ ·Machine Learning Accelerated Prediction of Self‐Trapped Excitons in Double Halide Perovskites
Advanced Energy and Sustainability Research · 2023
Baian Chen, Rui Chen, Bolong Huang
Read original paper ↗ ·Machine Learning in Perovskite Solar Cells: Recent Developments and Future Perspectives
Energy Technology · 2023
Nitin Kumar Bansal, Snehangshu Mishra, Himanshu Dixit, Shivam Porwal, Paulomi Singh, Trilok Singh
Read original paper ↗ ·Active Learning the High-Dimensional Transferable Hubbard U and V Parameters in the DFT + U + V Scheme
Journal of Chemical Theory and Computation · 2023
Wei Yu, Zhaofu Zhang, Xuhao Wan, Hailing Guo, Qingzhong Gui, Peng Yuan, Yifei Li, Wenjie Fu, Dingyi Lu, Yuchen Ye, Yuzheng Guo
Read original paper ↗ ·An evolutionary variational autoencoder for perovskite discovery
Frontiers in Materials · 2023
Ericsson Tetteh Chenebuah, Michel Nganbe, Alain Tchagang
Read original paper ↗ ·Machine‐Learning Accelerating the Development of Perovskite Photovoltaics
Solar RRL · 2023
Tiantian Liu, Sen Wang, Yinguang Shi, Lei Wu, Ruiyu Zhu, Yong Wang, Jun Zhou, Wallace C. H. Choy
Read original paper ↗ ·Bandgap Prediction of Hybrid Organic–Inorganic Perovskite Solar Cell Using Machine Learning
Journal of The Institution of Engineers (India) Series D · 2023
Debmalya Sadhu, Debasis De, Devansh Dattatreya, Arjun Deo, Subir Gupta
Read original paper ↗ ·MatGPT: A Vane of Materials Informatics from Past, Present, to Future
Advanced Materials · 2023
Zhilong Wang, An Chen, Kehao Tao, Yanqiang Han, Jinjin Li
Read original paper ↗ ·Machine Learning-Assisted Low-Dimensional Electrocatalysts Design for Hydrogen Evolution Reaction
Nano-Micro Letters · 2023
Jin Li, Naiteng Wu, Jian Zhang, Hong‐Hui Wu, Kunming Pan, Yingxue Wang, Guilong Liu, Xianming Liu, Zhenpeng Yao, Qiaobao Zhang
Read original paper ↗ ·Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial
Mechanical Systems and Signal Processing · 2023
Venkat Pavan Nemani, Luca Biggio, Xun Huan, Zhen Yu Hu, Olga Fink, Anh Tran, Yan Wang, Xiaoge Zhang, Chao Kun Hu
Read original paper ↗ ·First-Principles Study Combined with Interpretable Machine-Learning Models of Bayesian Optimization for the Design of Ultrawide Bandgap Double Perovskites
The Journal of Physical Chemistry C · 2023
Hongtao Shen, Jiang Wu, Zhengxin Chen, Xu Fang, Jiawei Li, Wenhao Li, Jia Horng Lin, Fei Zhu, Xudong Wang, Yihang Chen
Read original paper ↗ ·Application of machine learning models in groundwater quality assessment and prediction: progress and challenges
Frontiers of Environmental Science & Engineering · 2023
Yanpeng Huang, Chao Wang, Yuanhao Wang, Guangfeng Lyu, Sijie Lin, Weijiang Liu, Haobo Niu, Qing Hu
Read original paper ↗ ·Active learning guides discovery of a champion four-metal perovskite oxide for oxygen evolution electrocatalysis
Nature Materials · 2023
Junseok Moon, Wiktor Beker, Marta Siek, Jiheon Kim, Hyeon Seok Lee, Taeghwan Hyeon, Bartosz A. Grzybowski
Read original paper ↗ ·Accelerated Discovery of Targeted Environmentally Friendly A(II)B(I)X3-Type Three-Dimensional Hybrid Organic–Inorganic Perovskites for Potential Light Harvesting via Machine Learning
ACS Applied Materials & Interfaces · 2023
Yiming Xu, Li Kai, Zhi-Bin Jian, Jie Bie, Meng Wei, Shuang Chen
Read original paper ↗ ·Exploring Data Augmentation and Dimension Reduction Opportunities for Predicting the Bandgap of Inorganic Perovskite through Anion Site Optimization
Photonics · 2023
Tri-Chan-Hung Nguyen, Young-Un Kim, Insung Jung, O–Bong Yang, Mohammad Shaheer Akhtar
Read original paper ↗ ·DiZyme: The Ultimate Resource for Nanozyme Multiple Catalytic Activity Prediction
Research Square · 2023
Vladimir V. Vinogradov, Julia Razlivina, Andrei Dmitrenko
Read original paper ↗ ·NestedAE: interpretable nested autoencoders for multi-scale materials characterization
Materials Horizons · 2023
Nikhil Thota, Maitreyee Sharma Priyadarshini, Rigoberto Hernandez
Read original paper ↗ ·Active learning-driven uncertainty reduction for in-flight particle characteristics of atmospheric plasma spraying of silicon
Engineering Applications of Artificial Intelligence · 2023
Halar Memon, Eskil Gjerde, Alex Lynam, Amiya Chowdhury, Geert De Maere, Grazziela Patrocinio Figueredo, Tanvir Hussain
Read original paper ↗ ·Comprehensive and Accurate Prediction of Band Gap for Lead-Free Double Perovskites through Self-Modified Machine Learning Strategy
The Journal of Physical Chemistry C · 2023
Jing Lan, Songyang Yuan, Huiqun Zheng, Wenjian Yang, Wenzhe Li, Jiandong Fan
Read original paper ↗ ·Machine Learning-Accelerated Discovery of A 2 BC 2 Ternary Electrides with Diverse Anionic Electron Densities
Journal of the American Chemical Society · 2023
Zhiqi Wang, Yutong Gong, Matthew L. Evans, Yujing Yan, Shiyao Wang, Nanxi Miao, Ruiheng Zheng, Gian‐Marco Rignanese, Junjie Wang
Read original paper ↗ ·Quantitative evaluation of collector flotation performance II: The creation of a collector property index based on molecular structure
Separation and Purification Technology · 2023
Wanjia Zhang, John Ralston, Renji Zheng, Wei Sun, Shihong Xu, Jian Cao, Xin Jin, Zhitao Feng, Zhiyong Gao
Read original paper ↗ ·Accelerating stability of ABX3 perovskites analysis with machine learning
Ceramics International · 2023
Yunlai Zhu, Jishun Zhang, Zihan Qu, Shuo Jiang, Yu Liu, Zuheng Wu, Fei Yang, Wei Hu, Zuyu Xu, Yuehua Dai
Read original paper ↗ ·An interpretable machine learning strategy for pursuing high piezoelectric coefficients in (K0.5Na0.5)NbO3-based ceramics
npj Computational Materials · 2023
Bowen Ma, Xiao Wu, Chunlin Zhao, Cong Lin, Min Tian Gao, Baisheng Sa, Zhimei Sun
Read original paper ↗ ·Machine learning aided design of Bi2WO6/MIL-53(Al) nanocomposites
Computational Materials Science · 2023
Xiuyun Zhai, Mingtong Chen
Read original paper ↗ ·Machine learning – informed development of high entropy alloys with enhanced corrosion resistance
Electrochimica Acta · 2023
Huseyin Can Ozdemir, Alireza Nazarahari, Bengisu Yılmaz, Demircan Canadinç, E. Bedir, Rifat Yilmaz, Uğur Ünal, Hans Jürgen Maier
Read original paper ↗ ·Predictive Design of Hybrid Improper Ferroelectric Double Perovskite Oxides
Chemistry of Materials · 2023
Palanichamy Gayathri, Saurabh Ghosh, Ayana Ghosh
Read original paper ↗ ·Combining component screening, machine learning and molecular engineering for the design of high-performance inverted perovskite solar cells
Energy & Environmental Science · 2024
Boxue Zhang, Huaibiao Zeng, Haomiao Yin, Daming Zheng, Zhongquan Wan, Chunyang Jia, Thijs Stuyver, Junsheng Luo, Thierry Pauporté
Read original paper ↗ ·Conceptual Foundations of Applied AI in Materials Science - Definitions, Assumptions, and Open Debates
Journal of Artificial Intelligence for Materials Science · 2024
Hiroshi Tanaka, Yuki Sato, Kenji Mori, Rina Okabe
Read original paper ↗ ·Instabilities and Degradation in Perovskite Materials and Devices
Engineering materials · 2024
Shaoni Kar, Krishanu Dey
Read original paper ↗ ·Machine Learning Prediction of Oer Activity for Pnma Perovskite Via Minimal Structure Relaxation
SSRN Electronic Journal · 2024
Chanseok Kim, Mina Yoon, Jun Hee Lee
Read original paper ↗ ·Machine learning-empowered study of metastable γ-CsPbI 3 under pressure and strain
Journal of Materials Chemistry A · 2024
Minkyung Han, Cheng Peng, Ruyi Song, Feng Ke, Youssef S. G. Nashed, Wendy L. Mao, Chunjing Jia, Yu Pin Lin
Read original paper ↗ ·Mechanistic vs. Predictive Success: A Theory of What “Understanding” Means for AI in Materials Science
Journal of Artificial Intelligence for Materials Science · 2024
Ahmed El-Kholy, Nour Abdelrahman, Karim Hassan, Mona Saad
Read original paper ↗ ·Applications of perovskite oxides for the cleanup and mechanism of action of emerging contaminants/steroid hormones in water
Journal of Water Process Engineering · 2024
Ajibola A. Bayode, Stephen Sunday Emmanuel, Andrea Osti, Chidinma G. Olorunnisola, Abisola Opeyemi Egbedina, Daniel Terlanga Koko, Demilade T. Adedipe, Brigitte Helmreich, Martins O. Omorogie
Read original paper ↗ ·Acceleration of optimizing the dielectric properties of (Ca 0.7 Nd 0.2 ) 1− x (Li 0.5 Nd 0.5 ) x Ti 1− y (Mg 1/3 Nb 2/3 ) y O 3 with the aid of machine learning
Journal of the American Ceramic Society · 2024
Ziqi Ni, Fenglin Wang, Yeqing Guan, Kaijia Hu, Fengyuan Zhao, Xingyu Chen, Yicong Ye, Weijun Zhang, Shuxin Bai
Read original paper ↗ ·