Papers citing On-the-fly closed-loop materials discovery via Bayesian active learning
Machine Learning Spectral Indicators of Topology
Springer theses · 2022
Nina Andrejevic
Read original paper ↗ ·Spinel nitride solid solutions: charting properties in the configurational space with explainable machine learning
Digital Discovery · 2022
Pablo Sánchez-Palencia, Said Hamad, Pablo Palacios, Ricardo Grau‐Crespo, Keith T. Butler
Read original paper ↗ ·The Attention Economy of Materials AI: How Model Focus Shapes Scientific Attention Allocation
Journal of Artificial Intelligence for Materials Science · 2022
Michael Turner, Sophia Nguyen, David Clark, Emma Wilson
Read original paper ↗ ·The Measurement Problem in Materials Informatics: When Observing Changes in the System
Journal of Artificial Intelligence for Materials Science · 2022
Ravi Kumar, Neha Sharma, Aniket Deshmukh, Arjun Nair, Meera Pillai
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 ↗ ·The Treatment of Absence and Null Results in Materials Machine Learning Literature: A Review Study
Journal of Artificial Intelligence for Materials Science · 2022
Nguyen Thanh Huy, Pham Quang Minh, Le Thi Bich
Read original paper ↗ ·Improving prediction accuracy of high-performance materials via modified machine learning strategy
Computational Materials Science · 2022
Wei Yong, Hongtao Zhang, Huadong Fu, Yaliang Zhu, Jie He, Jianxin Xie
Read original paper ↗ ·Predicting the property contour-map and optimum composition of Cu-Co-Si alloys via machine learning
Materials Today Communications · 2022
Feng Zhao, Chenhui Lei, Qingkun Zhao, Huiya Yang, Guoping Ling, Jiabin Liu, Haofei Zhou, Hongtao Wang
Read original paper ↗ ·Identifying nonadditive contributions to the hydrophobicity of chemically heterogeneous surfaces via dual-loop active learning
The Journal of Chemical Physics · 2022
Atharva Kelkar, Bradley C. Dallin, Reid C. Van Lehn
Read original paper ↗ ·Dimensional Control over Metal Halide Perovskite Crystallization Guided by Active Learning
Chemistry of Materials · 2022
Zhi Li, Philip W. Nega, Mansoor Ani Najeeb, Chaochao Dun, Matthias Zeller, Jeffrey J. Urban, Wissam Abdo Saidi, Joshua Schrier, Alexander J. Norquist, Emory M. Chan
Read original paper ↗ ·Toward autonomous materials research: Recent progress and future challenges
Applied Physics Reviews · 2022
Joseph H. Montoya, Muratahan Aykol, Abraham Anapolsky, Chirranjeevi Balaji Gopal, Patrick K. Herring, Jens S. Hummelshøj, Linda Hung, Ha-Kyung Kwon, Daniel Schweigert, Shijing Sun, Santosh K. Suram, Steven B. Torrisi, Amalie Trewartha, Brian D. Storey
Read original paper ↗ ·Active meta-learning for predicting and selecting perovskite crystallization experiments
The Journal of Chemical Physics · 2022
Venkateswaran Shekar, Gareth Nicholas, Mansoor Ani Najeeb, Margaret Zeile, Vincent Yu, Xiaorong Wang, Dylan Slack, Zhi Li, Philip W. Nega, Emory M. Chan, Alexander J. Norquist, Joshua Schrier, Sorelle A. Friedler
Read original paper ↗ ·Photonic and optoelectronic neuromorphic computing
APL Photonics · 2022
Luis El Srouji, A. Krishnan, R. Ravichandran, Y. Lee, Mehmet Berkay On, Xian Xiao, S. J. Ben Yoo
Read original paper ↗ ·Sample-efficient parameter exploration of the powder film drying process using experiment-based Bayesian optimization
Scientific Reports · 2022
Kohei Nagai, Takayuki Osa, Gen Inoue, Takuya Tsujiguchi, Takuto Araki, Yoshiyuki Kuroda, Morio Tomizawa, Keisuke Nagato
Read original paper ↗ ·Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping
Frontiers in Physics · 2022
Aaron Gilad Kusne, Austin McDannald, Brian DeCost, Corey Oses, Cormac Toher, Stefano Curtarolo A, Apurva Mehta, Ichiro Takeuchi
Read original paper ↗ ·Roadmap on Machine learning in electronic structure
Electronic Structure · 2022
Heather J. Kulik, Thomas Hammerschmidt, Jonathan Schmidt, Silvana Botti, Miguel A. L. Marques, Mario Boley, Matthias Scheffler, Milica Todorović, Patrick Rinke, Corey Oses, Andriy Smolyanyuk, Stefano Curtarolo A, Alexandre Tkatchenko, Albert P. Bartók, Sergei Manzhos, Manabu Ihara, Tucker Carrington, Jörg Behler, Olexandr Isayev, Max Veit, Andrea Grisafi, Jigyasa Nigam, Michele Ceriotti, Kristof T. Schütt, Julia Westermayr, Michael Gastegger, Reinhard J. Maurer, Bhupalee Kalita, Kieron Burke, R Nagai, Ryosuke Akashi, Osamu Sugino, Jan Hermann, Frank Noé, Sebastiano Pilati, Claudia Draxl, M Kuban, Santiago Rigamonti, Markus Scheidgen, Marco Esters, David Hicks, Cormac Toher, Prasanna V. Balachandran, Isaac Tamblyn, Steve Whitelam, Colin Bellinger, Luca M. Ghiringhelli
Read original paper ↗ ·Hypothesis Learning in Automated Experiment: Application to Combinatorial Materials Libraries
Advanced Materials · 2022
Maxim A Ziatdinov, Yongtao Liu, Anna N. Morozovska, Eugene А. Eliseev, Xiaohang Zhang, Ichiro Takeuchi, Sergei V. Kalinin
Read original paper ↗ ·Agents for sequential learning using multiple-fidelity data
Scientific Reports · 2022
Aini Palizhati, Steven B. Torrisi, Muratahan Aykol, Santosh K. Suram, Jens S. Hummelshøj, Joseph H. Montoya
Read original paper ↗ ·Materials, physics and systems for multicaloric cooling
Nature Reviews Materials · 2022
Huilong Hou, Suxin Qian, Ichiro Takeuchi
Read original paper ↗ ·Materials structure–property factorization for identification of synergistic phase interactions in complex solar fuels photoanodes
npj Computational Materials · 2022
Dan Guevarra, Lan Zhou, Matthias Hermann Richter, Aniketa Shinde, Di Chen, Carla Pedro Gomes, John M. Gregoire
Read original paper ↗ ·Active learning and molecular dynamics simulations to find high melting temperature alloys
Computational Materials Science · 2022
David E. Farache, Juan C. Verduzco, Zachary D. McClure, Saaketh Desai, Alejandro H. Strachan
Read original paper ↗ ·Phase control of heterogeneous Hf x Zr (1− x ) O 2 thin films by machine learning
Japanese Journal of Applied Physics · 2022
Zeyuan Ni, H. Matsui
Read original paper ↗ ·Deep machine learning unravels the structural origin of mid‐gap states in chalcogenide glass for high‐density memory integration
InfoMat · 2022
Meng Kai Xu, Meng Kai Xu, Ming Xu, Ming Xu, Xiangshui Miao
Read original paper ↗ ·Accelerated materials design using batch Bayesian optimization: A case study for solving the inverse problem from materials microstructure to process specification
Computational Materials Science · 2022
Pejman Honarmandi, Vahid Attari, Raymundo Arróyave
Read original paper ↗ ·The case for data science in experimental chemistry: examples and recommendations
Nature Reviews Chemistry · 2022
Junko Yano, Kelly J. Gaffney, John M. Gregoire, Linda Hung, A. Ourmazd, Joshua Schrier, James A. Sethian, Francesca Maria Toma
Read original paper ↗ ·Accelerating materials discovery using artificial intelligence, high performance computing and robotics
npj Computational Materials · 2022
Edward O. Pyzer‐Knapp, Jed W. Pitera, Peter Staar, Seiji Takeda, Teodoro Laino, Daniel P. Sanders, James Sexton, John R. Smith, Alessandro Curioni
Read original paper ↗ ·Discovery of Pb-free hybrid organic–inorganic 2D perovskites using a stepwise optimization strategy
npj Computational Materials · 2022
Byung Do Lee, Jin-Woong Lee, Minseuk Kim, Woon Bae Park, Kee‐Sun Sohn
Read original paper ↗ ·Deep learning to catalyze inverse molecular design
Chemical Engineering Journal · 2022
Abdulelah S. Alshehri, Fengqi You
Read original paper ↗ ·On-the-fly autonomous control of neutron diffraction via physics-informed Bayesian active learning
Applied Physics Reviews · 2022
Austin McDannald, Matthias Frontzek, Andrei T. Savici, Mathieu Doucet, Efrain E. Rodriguez, Kate Meuse, Jessica Opsahl‐Ong, Daniel V. Samarov, Ichiro Takeuchi, William Ratcliff, Aaron Gilad Kusne
Read original paper ↗ ·MODEL, GUESS, CHECK: Wordle as a primer on active learning for materials research
npj Computational Materials · 2022
Keith A. Brown
Read original paper ↗ ·Autonomous high-throughput screening technology for accelerating drug molecule discovery and synthesis
Scientia Sinica Chimica · 2022
Jie Chen, Xian Zheng, Yixiang Ruan, Yiming Mo
Read original paper ↗ ·Exploring “No Man's Land”—Arrhenius Crystallization of Thin‐Film Phase Change Material at 1 000 000 K s−1 via Nanocalorimetry
Advanced Materials Interfaces · 2022
Jie Zhao, Jian Hui, Zichao Ye, Tianxing Lai, Mikhail Y. Efremov, Hong Wang, L. H. Allen
Read original paper ↗ ·Autonomous materials discovery and manufacturing (AMDM): A review and perspectives
IISE Transactions · 2022
Satish Bukkapatnam
Read original paper ↗ ·Recent Trends and Future Prospects of Materials and Process Informatics
Seikei-Kakou · 2022
Shun Muroga
Read original paper ↗ ·Towards Automated Design of Corrosion Resistant Alloy Coatings with an Autonomous Scanning Droplet Cell
JOM · 2022
Brian DeCost, Howie Joress, Suchismita Sarker, Apurva Mehta, Jason R. Hattrick-Simpers
Read original paper ↗ ·Application of machine learning to reflection high-energy electron diffraction images for automated structural phase mapping
Physical Review Materials · 2022
Haotong Liang, Valentin Stanev, Aaron Gilad Kusne, Yuto Tsukahara, Kaito Ito, Ryota Takahashi, Mikk Lippmaa, Ichiro Takeuchi
Read original paper ↗ ·XGBoost model for electrocaloric temperature change prediction in ceramics
npj Computational Materials · 2022
Jie Gong, Sharon Chu, Rohan K. Mehta, Alan J. H. McGaughey
Read original paper ↗ ·A comparison of explainable artificial intelligence methods in the phase classification of multi-principal element alloys
Scientific Reports · 2022
Kyungtae Lee, Mukil V. Ayyasamy, Yangfeng Ji, Prasanna V. Balachandran
Read original paper ↗ ·Designing lattices for impact protection using transfer learning
Matter · 2022
Aldair E. Gongora, Kelsey L. Snapp, Richard Pang, Thomas Tiano, Kristofer G. Reyes, Emily Whiting, Timothy J. Lawton, Elise Feng‐i Morgan, Keith A. Brown
Read original paper ↗ ·Computer Simulation and Artificial Intelligence Driven Frameworks for Stability Analysis of Spacecraft Phase Plane Control Systems
IEEE Data Driven Control and Learning Systems Conference (DDCLS) · 2022
Zhihua Chen, Ruizhi Luo, Wangkui Liu, Jin-hua Guo, Yong Li, Yong Feng Guo, Kai Zhang, Yongchun Xie
Read original paper ↗ ·Swarm intelligence for new materials
Computational Materials Science · 2022
Zhiwei Liu, Jialong Guo, Ziyi Chen, Zongguo Wang, Zhenan Sun, Xianwei Li, Yangang Wang
Read original paper ↗ ·Bayesian optimization with experimental failure for high-throughput materials growth
npj Computational Materials · 2022
Yuki K. Wakabayashi, Takuma Otsuka, Yoshiharu Krockenberger, Hiroshi Sawada, Yoshitaka Taniyasu, Hideki Yamamoto
Read original paper ↗ ·Machine learning algorithms in the environmental corrosion evaluation of reinforced concrete structures - A review
Cement and Concrete Composites · 2022
Hanxi Jia, Guofu Qiao, Peng Han
Read original paper ↗ ·Why big data and compute are not necessarily the path to big materials science
Communications Materials · 2022
Naohiro Fujinuma, Brian DeCost, Jason R. Hattrick-Simpers, S. E. Lofland
Read original paper ↗ ·The LEGOLAS Kit: A low-cost robot science kit for education with symbolic regression for hypothesis discovery and validation
MRS Bulletin · 2022
Logan Saar, Haotong Liang, Alex Y. Wang, Austin McDannald, Efrain E. Rodriguez, Ichiro Takeuchi, Aaron Gilad Kusne
Read original paper ↗ ·Neural network training method for materials science based on multi-source databases
Scientific Reports · 2022
Jialong Guo, Ziyi Chen, Zhiwei Liu, Xianwei Li, Z. Y. Xie, Zongguo Wang, Yangang Wang
Read original paper ↗ ·Autonomous optimization of non-aqueous Li-ion battery electrolytes via robotic experimentation and machine learning coupling
Nature Communications · 2022
Adarsh Dave, Jared Mitchell, Sven Anders Burke, Hongyi Lin, Jay F. Whitacre, Venkatasubramanian Viswanathan
Read original paper ↗ ·AutoMat: Automated materials discovery for electrochemical systems
MRS Bulletin · 2022
Emil Jonathan Annevelink, Rachel C. Kurchin, Eric S. Muckley, Lance Kavalsky, Vinay I. Hegde, Valentin Sulzer, Shang Zhu, Jiankun Pu, David Farina, Matthew S. Johnson, Dhairya Gandhi, Adarsh Dave, Hongyi Lin, Alan S. Edelman, Bharath Ramsundar, James E. Saal, Christopher Rackauckas, Viral B. Shah, Bryce Meredig, Venkatasubramanian Viswanathan
Read original paper ↗ ·Linking scientific instruments and computation: Patterns, technologies, and experiences
Patterns · 2022
Rafael Vescovi, Ryan Chard, Nickolaus Saint, Ben J. Blaiszik, Jim Pruyne, Tekin Biçer, Alex Lavens, Zhengchun Liu, Michael E. Papka, Suresh Narayanan, Nicholas Schwarz, Kyle Chard, Ian T Foster
Read original paper ↗ ·Machine‐Learning Spectral Indicators of Topology
Advanced Materials · 2022
Nina Andrejevic, Jovana Andrejevic, Bogdan Andrei Bernevig, Nicolas Regnault, Fei Han, G. Fabbris, Thanh Nguyen, Nathan C. Drucker, Chris H. Rycroft, Mingda Li
Read original paper ↗ ·