Papers citing Autonomous materials synthesis via hierarchical active learning of nonequilibrium phase diagrams
A Conceptual Theory of Model-Science Interface: Where AI Outputs Become Experimental Inputs
Journal of Artificial Intelligence for Materials Science · 2022
Wei Chen, Li Zhang
Read original paper ↗ ·Discovery without Understanding: A Systems Theory of Black-Box Optimization in Autonomous Materials Engineering
Journal of Computational and Data-Driven Materials Engineering · 2022
Daniel Brooks, Amelia Carter, Ethan Moore
Read original paper ↗ ·Integration of Constraint Programming, Artificial Intelligence, and Operations Research
Lecture notes in computer science · 2022
Read original paper ↗ ·Metalated covalent organic frameworks: from synthetic strategies to diverse applications
Chemical Society Reviews · 2022
Qun Guan, Lele Zhou, Yu‐Bin Dong
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 ↗ ·A self-driving laboratory advances the Pareto front for material properties
Nature Communications · 2022
Benjamin P. MacLeod, Fraser G. L. Parlane, Connor C. Rupnow, Kevan E. Dettelbach, Michael S. Elliott, Thomas D. Morrissey, Ted H. Haley, Oleksii Proskurin, Michael B. Rooney, Nina Taherimakhsousi, David Dvořák, Hsi Nien Chiu, Christopher E. B. Waizenegger, Karry Ocean, Mehrdad Mokhtari, Curtis P. Berlinguette
Read original paper ↗ ·Materials Data toward Machine Learning: Advances and Challenges
The Journal of Physical Chemistry Letters · 2022
Linggang Zhu, Jian Xin Zhou, Zhimei Sun
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 ↗ ·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 ↗ ·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 ↗ ·Artificial intelligence for materials research at extremes
MRS Bulletin · 2022
Benji Maruyama, Jason R. Hattrick-Simpers, William D. Musinski, Lori L. Graham-Brady, Kang Li, Jonathan D. Hollenbach, A. Singh, Mitra L. Taheri
Read original paper ↗ ·Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation
Progress in Materials Science · 2022
Yunchao Xie, Kianoosh Sattari, Chi Zhang, Jian Lin
Read original paper ↗ ·Upcoming Transformations in Integrated Energy/Chemicals Sectors: Some Challenges and Several Opportunities
The Journal of Physical Chemistry C · 2022
Alberto Striolo, Shanshan Huang
Read original paper ↗ ·Human-in-The-Loop for Bayesian Autonomous Materials Phase Mapping
SSRN Electronic Journal · 2023
Felix Adams, Austin McDannald, Ichiro Takeuchi, Aaron Gilad Kusne
Read original paper ↗ ·Multimodal, Physics-Informed Machine Learning for Accelerated Materials Design and Discovery
Journal of Computational and Data-Driven Materials Engineering · 2023
Lucas Meyer, Stefan Braun, Anna Schmid, David Keller
Read original paper ↗ ·Orchestrating nimble experiments across interconnected labs
Digital Discovery · 2023
Dan Guevarra, Kevin Kan, Yungchieh Lai, Ryan J. R. Jones, Lan Zhou, Phillip Donnelly, Matthias Hermann Richter, Helge Sören Stein, John M. Gregoire
Read original paper ↗ ·Simulation Priors in Machine Learning Materials Models: Hidden Physics Assumptions
Journal of Computational and Data-Driven Materials Engineering · 2023
Ahmed Mansour, Omar Saeed
Read original paper ↗ ·Tackling data scarcity with transfer learning: a case study of thickness characterization from optical spectra of perovskite thin films
Digital Discovery · 2023
Siyu Isaac Parker Tian, Zekun Ren, Selvaraj Venkataraj, Yuanhang Cheng, Daniil Bash, Felipe Oviedo, J. Senthilnath, Vijila Chellappan, Yee‐Fun Lim, Armin Gerhard Aberle, Benjamin P. MacLeod, Fraser G. L. Parlane, Curtis P. Berlinguette, Qianxiao Li, Tonio Buonassisi, Zhe Liu
Read original paper ↗ ·When Optimization Conflicts with Discovery: A Conceptual Tension in Materials AI
Journal of Artificial Intelligence for Materials Science · 2023
Wei Liu, Zhang Min
Read original paper ↗ ·Emerging Trends in Machine Learning: A Polymer Perspective
ACS Polymers Au · 2023
Tyler B. Martin, Debra J. Audus
Read original paper ↗ ·How to build an effective self-driving laboratory
MRS Bulletin · 2023
Benjamin P. MacLeod, Fraser G. L. Parlane, Curtis P. Berlinguette
Read original paper ↗ ·Next-generation intelligent laboratories for materials design and manufacturing
MRS Bulletin · 2023
Xiting Peng, Xiaonan Wang
Read original paper ↗ ·The Functional Materials Beamline at CHESS
Synchrotron Radiation News · 2023
Louisa Smieska, Kirt A. Page, Brian J. Ree, Bingqian Zheng, Hilmar Koerner, Arthur R. Woll
Read original paper ↗ ·Combinatorial synthesis for AI-driven materials discovery
Nature Synthesis · 2023
John M. Gregoire, Lan Zhou, Joel A. Haber
Read original paper ↗ ·ET-AL: Entropy-targeted active learning for bias mitigation in materials data
Applied Physics Reviews · 2023
James M. Rondinelli, Wei Chen
Read original paper ↗ ·Scalable multi-agent lab framework for lab optimization
Matter · 2023
Aaron Gilad Kusne, Austin McDannald
Read original paper ↗ ·Active learning-assisted neutron spectroscopy with log-Gaussian processes
Nature Communications · 2023
Mario Teixeira Parente, Georg Brandl, Christian Franz, U. Stuhr, Marina Ganeva, A. Schneidewind
Read original paper ↗ ·A self-driving laboratory optimizes a scalable process for making functional coatings
Cell Reports Physical Science · 2023
Connor C. Rupnow, Benjamin P. MacLeod, Mehrdad Mokhtari, Karry Ocean, Kevan E. Dettelbach, Daniel Lin, Fraser G. L. Parlane, Hsi Nien Chiu, Michael B. Rooney, Chris Waizenegger, Elija I. de Hoog, Abhishek Soni, Curtis P. Berlinguette
Read original paper ↗ ·Scientific discovery in the age of artificial intelligence
Nature · 2023
Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Animashree Anandkumar, Karianne J. Bergen, Carla Pedro Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie‐Yan Liu, Arjun Kumar Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Guo Tang, Petar Veličković, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Žitnik
Read original paper ↗ ·Robotic pendant drop: containerless liquid for μs-resolved, AI-executable XPCS
Light Science & Applications · 2023
Doga Ozgulbas, Don Jensen, Rory Butler, Rafael Vescovi, Ian T Foster, Michael Irvin, Yasukazu Nakaye, Miaoqi Chu, Eric M. Đufresne, Söenke Seifert, G. Babnigg, Arvind Ramanathan, Qingteng Zhang
Read original paper ↗ ·Discovery Precision: An effective metric for evaluating performance of machine learning model for explorative materials discovery
Computational Materials Science · 2023
Zhengheng Lian, Yingying Ma, Minjie Li, Wencong Lu, Wenyan Zhou
Read original paper ↗ ·Should We Teach AI a Better Scientific Method?
Chemistry of Materials · 2023
James Richmond Neilson
Read original paper ↗ ·Accelerating CALPHAD-Based Phase Diagram Predictions in Complex Alloys Using Universal Machine Learning Potentials: Opportunities and Challenges
SSRN Electronic Journal · 2024
Siya Zhu, Doğuhan Sarıtürk, Raymundo Arróyave
Read original paper ↗ ·Autonomous millimeter scale high throughput battery research system
Digital Discovery · 2024
Fuzhan Rahmanian, Stefan Fuchs, Bojing Zhang, Maximilian Fichtner, Helge Sören Stein
Read original paper ↗ ·Experimental Validation Bottlenecks in AI-Guided Materials Design
Journal of Computational and Data-Driven Materials Engineering · 2024
Oliver Grant, Daniel Brooks, Amelia Carter
Read original paper ↗ ·Learning material synthesis–process–structure–property relationship by data fusion: Bayesian co-regionalization N-dimensional piecewise function learning
Digital Discovery · 2024
Aaron Gilad Kusne, Austin McDannald, Brian DeCost
Read original paper ↗ ·Physics-driven discovery and bandgap engineering of hybrid perovskites
Digital Discovery · 2024
Sheryl L. Sanchez, Elham Foadian, Maxim A Ziatdinov, Jonghee Yang, Sergei V. Kalinin, Yongtao Liu, Mahshid Ahmadi
Read original paper ↗ ·Recent Advances in Machine Learning-Accelerated Materials Discovery — From Descriptors to Autonomous Experiments
Journal of Artificial Intelligence for Materials Science · 2024
Nguyen Thanh Huy, Le Thi Bich, Pham Quang Minh
Read original paper ↗ ·Representation Drift in Iterative Materials Learning Systems
Journal of Computational and Data-Driven Materials Engineering · 2024
Nguyen Thanh Huy, Pham Quang Minh, Le Thi Bich
Read original paper ↗ ·Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)
ChemRxiv · 2024
Fuzhan Rahmanian, Stefan Fuchs, Maximilian Fichtner, Helge Sören Stein
Read original paper ↗ ·Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)
ChemRxiv · 2024
Fuzhan Rahmanian, Stefan Fuchs, Maximilian Fichtner, Helge Sören Stein
Read original paper ↗ ·Autonomous millimeter scale high throughput battery research system (Auto-MISCHBARES)
ChemRxiv · 2024
Fuzhan Rahmanian, Stefan Fuchs, Bojing Zhang, Maximilian Fichtner, Helge Sören Stein
Read original paper ↗ ·Human-in-the-loop for Bayesian autonomous materials phase mapping
Matter · 2024
Felix Adams, Austin McDannald, Ichiro Takeuchi, Aaron Gilad Kusne
Read original paper ↗ ·Designing workflows for materials characterization
Applied Physics Reviews · 2024
Sergei V. Kalinin, Maxim A Ziatdinov, Mahshid Ahmadi, Ayana Ghosh, Kevin M. Roccapriore, Yongtao Liu, Rama Krishnan Vasudevan
Read original paper ↗ ·Navigating phase diagram complexity to guide robotic inorganic materials synthesis
Nature Synthesis · 2024
Jiadong Chen, Samuel R. Cross, Lincoln J. Miara, Jeong‐Ju Cho, Yan Eric Wang, Wenhao Q. Sun
Read original paper ↗ ·Artificial intelligence enabled smart design and manufacturing of advanced materials: The endless Frontier in AI + era
Materials Genome Engineering Advances · 2024
William Yi Wang, Suyang Zhang, Gaonan Li, Jiaqi Lu, Yong Sheng Ren, Xinchao Wang, Xingyu Gao, Yanjing Su, Haifeng Song, Jinshan Li
Read original paper ↗ ·Targeted materials discovery using Bayesian algorithm execution
npj Computational Materials · 2024
Sathya R. Chitturi, Akash Ramdas, Yue Wu, Brian A. Rohr, Stefano Ermon, Jennifer A. Dionne, Felipe H. da Jornada, Mike Dunne, Christopher J. Tassone, Willie Neiswanger, Daniel F. Ratner
Read original paper ↗ ·AIPHAD, an active learning web application for visual understanding of phase diagrams
Communications Materials · 2024
Ryo Tamura, Haruhiko Morito, Guillaume Deffrennes, Masanobu Naito, Yoshitaro Nose, Taichi Abe, Kei Terayama
Read original paper ↗ ·Classification Of Biomaterials and Their Applications
Journal Port Science Research · 2024
Nour Muhammad Salih Mahdi, Ayad K. Hassan, Fatimah J. Al-Hasani, Waleed Ameen Mahmoud Al-Jawher
Read original paper ↗ ·Self-Driving Laboratories for Chemistry and Materials Science
Chemical Reviews · 2024
Gary Tom, Stefan P. Schmid, Sterling G. Baird, Yang Cao, Kourosh Darvish, Han Hao, Stanley Lo, Sergio Pablo‐García, Ella Miray Rajaonson, Marta Skreta, Naruki Yoshikawa, Samantha Corapi, Gun Deniz Akkoc, Felix Strieth‐Kalthoff, Martin T. Seifrid, Alán Aspuru‐Guzik
Read original paper ↗ ·