Papers citing Machine-learning-assisted materials discovery using failed experiments
Application of Artificial Neural Networks for Catalysis: A Review
Catalysts · 2017
Hao Li, Zhien Zhang, Zhijian Liu
Read original paper ↗ ·Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning
Chemistry of Materials · 2017
Edward Kim, Kevin J. Huang, Adam Saunders, Andrew McCallum, Gerbrand Ceder, Elsa Olivetti
Read original paper ↗ ·Bilinear generating functions in Kernel sparse modeling and learning: Towards the kernel engineering
IEEE Symposium Series on Computational Intelligence (SSCI) · 2017
Zhao Lu, Wen Yan, Qi Wu
Read original paper ↗ ·Disentangling Structural Confusion through Machine Learning: Structure Prediction and Polymorphism of Equiatomic Ternary Phases ABC
Journal of the American Chemical Society · 2017
Anton O. Oliynyk, Lawrence Asamoah Adutwum, Brent W. Rudyk, Harshil Pisavadia, Sogol Lotfi, Viktor H. Hlukhyy, James J. Harynuk, Arthur Mar, Jakoah Brgoch
Read original paper ↗ ·Virtual screening of inorganic materials synthesis parameters with deep learning
npj Computational Materials · 2017
Edward Kim, Kevin J. Huang, Stefanie Jegelka, Elsa Olivetti
Read original paper ↗ ·An materials informatics approach to Ni-based single crystal superalloys lattice misfit prediction
Computational Materials Science · 2017
Xue Feng Jiang, Haiqing Yin, Cong Zhang, Rui-Jie Zhang, Kai-Qi Zhang, Zhenghua Deng, Guoquan Liu, Xuanhui Qu
Read original paper ↗ ·Toward Machine Learning-based Data-driven Functional Protein Studies: Understanding Colour Tuning Rules and Predicting the Absorption Wavelengths of Microbial Rhodopsins
bioRxiv (Cold Spring Harbor Laboratory) · 2017
Masayuki Karasuyama, Keiichi Inoue, Hideki Kandori, Ichiro Takeuchi
Read original paper ↗ ·Quantum Machine Learning im chemischen Raum
Angewandte Chemie · 2017
O. Anatole von Lilienfeld
Read original paper ↗ ·Quantum Machine Learning in Chemical Compound Space
Angewandte Chemie International Edition · 2017
O. Anatole von Lilienfeld
Read original paper ↗ ·Wave Functions, Density Functionals, and Artificial Intelligence for Materials and Energy Research: Future Prospects and Challenges
ACS Energy Letters · 2017
Martín A. Mosquera, Bo Fu, Kevin L. Kohlstedt, George Chappell Schatz, Mark A. Ratner
Read original paper ↗ ·A statistical study of proton conduction in Nafion®-based composite membranes: Prediction, filler selection and fabrication methods
Journal of Membrane Science · 2017
Lunyang Liu, Wenduo Chen, Yunqi Li
Read original paper ↗ ·Discovery of Intermetallic Compounds from Traditional to Machine-Learning Approaches
Accounts of Chemical Research · 2017
Anton O. Oliynyk, Arthur Mar
Read original paper ↗ ·Optimizing Chemical Reactions with Deep Reinforcement Learning
ACS Central Science · 2017
Zhenpeng Zhou, Xiaocheng Li, Richard N. Zare
Read original paper ↗ ·Material structure-property linkages using three-dimensional convolutional neural networks
Acta Materialia · 2017
Ahmet Cecen, Hanjun Dai, Yuksel C. Yabansu, Surya R. Kalidindi, Le Song
Read original paper ↗ ·Emerging investigator series: design of hydrogel nanocomposites for the detection and removal of pollutants: from nanosheets, network structures, and biocompatibility to machine-learning-assisted design
Environmental Science Nano · 2018
Xuan Hou, Mu Li, Fang Chen, Xiangang Hu
Read original paper ↗ ·Machine learning material properties from the periodic table using convolutional neural networks
Chemical Science · 2018
Xiaolong Zheng, Peng Zheng, Ruizhi Zhang
Read original paper ↗ ·Machine learning meets volcano plots: computational discovery of cross-coupling catalysts
Chemical Science · 2018
Benjamin Meyer, Boodsarin Sawatlon, Stefan Heinen, O. Anatole von Lilienfeld, Clémence Corminbœuf
Read original paper ↗ ·Magnetism of new metastable cobalt-nitride compounds
Nanoscale · 2018
Balamurugan Balasubramanian, Xin Zhao, Shah R. Valloppilly, Sumit Beniwal, Ralph Skomski, Anandakumar Sarella, Yunlong Jin, Xingzhong Li, Xiaoshan Xu, Huibo B. Cao, Haohan Wang, Axel Enders, Cai‐Zhuang Wang, Kai-Ming Ho, D. J. Sellmyer
Read original paper ↗ ·Multiscale prediction of functional self-assembled materials using machine learning: high-performance surfactant molecules
Nanoscale · 2018
Takuya Inokuchi, Na Li, Kei Morohoshi, Noriyoshi Arai
Read original paper ↗ ·Prediction and understanding of AIE effect by quantum mechanics-aided machine-learning algorithm
Chemical Communications · 2018
Jia Qiu, Kun Wang, Zhouyang Lian, Xing Yang, Wenhui Huang, Anjun Qin, Qian Wang, Jie Tian, Ben Zhong Tang, Shuixing Zhang
Read original paper ↗ ·Recent Advances of Modeling in Applied and Natural Sciences
Journal of Ecology & Natural Resources · 2018
Read original paper ↗ ·Recent progress of the glassy materials and physics
Acta Physica Sinica · 2018
Sun Yi-tao, Chao Wang, L uuml Yu-Miao, Yuan‐Chao Hu, Luo Peng, Liu Ming, Xian Hai-Jie, Zhao De-Qian, Ding Da-Wei, Sun Bao-An, Pan Ming-Xiang, Wen Xiang Ping, Bai Hai-Yang, Yanhui Liu, Wang Weihua
Read original paper ↗ ·Towards operando computational modeling in heterogeneous catalysis
Chemical Society Reviews · 2018
Lukáš Grajciar, Christopher James Heard, A. A. Bondarenko, Mikhail V. Polynski, Jittima Meeprasert, Evgeny A. Pidko, Petr Nachtigall
Read original paper ↗ ·Understanding structural adaptability: a reactant informatics approach to experiment design
Molecular Systems Design & Engineering · 2018
Rosalind J. Xu, Jacob H. Olshansky, Philip Adler, Yongjia Huang, Matthew D. Smith, Matthias Zeller, Joshua Schrier, Alexander J. Norquist
Read original paper ↗ ·Accelerated Discovery of Large Electrostrains in BaTiO3‐Based Piezoelectrics Using Active Learning
Advanced Materials · 2018
Ruihao Yuan, Zhen Liu, Prasanna V. Balachandran, Deqing Xue, Deqing Xue, Yumei Zhou, Xiangdong Ding, Jun Sun, Dezhen Xue, Dezhen Xue, Turab Lookman
Read original paper ↗ ·Materials 4.0: Materials big data enabled materials discovery
Applied Materials Today · 2018
Rajan Jose, Seeram Ramakrishna
Read original paper ↗ ·Artificial intelligence exploration of unstable protocells leads to predictable properties and discovery of collective behavior
Proceedings of the National Academy of Sciences · 2018
Laurie J. Points, James Ward Taylor, Jonathan Grizou, Kevin Donkers, Leroy Cronin
Read original paper ↗ ·Firefly-like Water Splitting Cells Based on FRET Phenomena with Ultrahigh Performance over 12%
ACS Applied Materials & Interfaces · 2018
Yi‐Sheng Lai, Fei Pan, Yen‐Hsun Su
Read original paper ↗ ·Materials informatics
Journal of Intelligent Manufacturing · 2018
Seeram Ramakrishna, Tong‐Yi Zhang, Wencong Lu, Quan Qian, Jonathan Sze Choong Low, Jeremy H. Yune, Daren Zong Loong Tan, Stéphane Bressan, Stefano Sanvito, Surya R. Kalidindi
Read original paper ↗ ·Predicting reaction performance in C–N cross-coupling using machine learning
Science · 2018
Derek T. Ahneman, Jesús G. Estrada, Shishi Lin, Spencer D. Dreher, Abigail G. Doyle
Read original paper ↗ ·Development of models for classification of action between heat-clearing herbs and blood-activating stasis-resolving herbs based on theory of traditional Chinese medicine
Chinese Medicine · 2018
Chen Xi Zhao, Yanfeng Cao, Shuaibing He, Yanjiang Qiao
Read original paper ↗ ·Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules.
Cambridge University Engineering Department Publications Database · 2018
Rafael Gómez‐Bombarelli, Jennifer N. Wei, David Duvenaud, José Miguel Hernández-Lobato, Benjamín Sánchez-Lengeling, Dennis Sheberla, Jorge Aguilera‐Iparraguirre, Timothy D. Hirzel, Ryan Prescott Adams, Alán Aspuru‐Guzik
Read original paper ↗ ·Data mining for better material synthesis: The case of pulsed laser deposition of complex oxides
Journal of Applied Physics · 2018
Steven R. Young, Artem Maksov, Maxim A Ziatdinov, Ye Cao, Matthew Burch, Janakiraman Balachandran, Linglong Li, Suhas Somnath, Robert M. Patton, Sergei V. Kalinin, Rama K. Vasudevan
Read original paper ↗ ·Inverse design in search of materials with target functionalities
Nature Reviews Chemistry · 2018
Alex Zunger
Read original paper ↗ ·An open experimental database for exploring inorganic materials
Scientific Data · 2018
Andriy Zakutayev, Nick Wunder, Marcus Schwarting, John D. Perkins, Robert White, Kristin R. Munch, William Tumas, Caleb T. Phillips
Read original paper ↗ ·Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments
Science Advances · 2018
Fang Ren, Logan T. Ward, Travis Williams, Kevin James Laws, Christopher Wolverton, Jason R. Hattrick-Simpers, Apurva Mehta
Read original paper ↗ ·OCPMDM: Online computation platform for materials data mining
Chemometrics and Intelligent Laboratory Systems · 2018
Qing Zhang, Dongping Chang, Xiuyun Zhai, Wencong Lu
Read original paper ↗ ·Experimental search for high-temperature ferroelectric perovskites guided by two-step machine learning
Nature Communications · 2018
Prasanna V. Balachandran, Benjamin A. Kowalski, Alp Sehirlioglu, Turab Lookman
Read original paper ↗ ·Materials science and engineering: New vision in the era of artificial intelligence
arXiv (Cornell University) · 2018
Qiang, Tao, Honghong Gao
Read original paper ↗ ·Predicting the stability of ternary intermetallics with density functional theory and machine learning
The Journal of Chemical Physics · 2018
Jonathan Schmidt, Liming Chen, Silvana Botti, Miguel A. L. Marques
Read original paper ↗ ·Machine-Learning Energy Gaps of Porphyrins with Molecular Graph Representations
The Journal of Physical Chemistry A · 2018
Zheng Li, Noushin Omidvar, Wei Shan Chin, Esther Robb, Amanda J. Morris, Luke E. K. Achenie, Hongliang Xin
Read original paper ↗ ·Accelerating the discovery of materials for clean energy in the era of smart automation
Nature Reviews Materials · 2018
Daniel P. Tabor, Loı̈c M. Roch, Semion K. Saikin, Christoph Kreisbeck, Dennis Sheberla, Joseph H. Montoya, Shyam Dwaraknath, Muratahan Aykol, C. Ortiz, Hermann Tribukait, Carlos Amador‐Bedolla, Christoph Josef Brabec, Benji Maruyama, Kristin Aslaug Persson, Alán Aspuru‐Guzik
Read original paper ↗ ·Machine Learning in Computer-Aided Synthesis Planning
Accounts of Chemical Research · 2018
Connor W. Coley, William H. Green, Klavs F. Jensen
Read original paper ↗ ·A strategy to apply machine learning to small datasets in materials science
npj Computational Materials · 2018
Ying Zhang, Chen Ling
Read original paper ↗ ·Machine Learning and Energy Minimization Approaches for Crystal Structure Predictions: A Review and New Horizons
Chemistry of Materials · 2018
Jake Graser, Steven K. Kauwe, Taylor D. Sparks
Read original paper ↗ ·Combining theory and experiment in lithium–sulfur batteries: Current progress and future perspectives
Materials Today · 2018
Xiang Chen, Tingzheng Hou, Kristin Aslaug Persson, Qiang Zhang
Read original paper ↗ ·Less is more: Sampling chemical space with active learning
The Journal of Chemical Physics · 2018
Justin S. Smith, Benjamin T. Nebgen, Nicholas Lubbers, Olexandr Isayev, Adrián E. Roitberg
Read original paper ↗ ·Accelerated search for perovskite materials with higher Curie temperature based on the machine learning methods
Computational Materials Science · 2018
Xiuyun Zhai, Mingtong Chen, Wencong Lu
Read original paper ↗ ·Machine Detection of Enhanced Electromechanical Energy Conversion in PbZr0.2Ti0.8O3 Thin Films
Advanced Materials · 2018
Joshua Agar, Ye Cao, Brett Naul, Shishir A. Pandya, Stéfan van der Walt, Aileen Luo, Joshua T. Maher, Nina Balke, Stephen Jesse, Sergei V. Kalinin, Rama Krishnan Vasudevan, Lane W. Martin
Read original paper ↗ ·Machine-Learning-Assisted Accurate Band Gap Predictions of Functionalized MXene
Chemistry of Materials · 2018
Arunkumar Chitteth Rajan, Avanish Mishra, Swanti Satsangi, Rishabh Vaish, Hiroshi Mizuseki, Kwang‐Ryeol Lee, Abhishek Kumar Singh
Read original paper ↗ ·