On-the-fly closed-loop materials discovery via Bayesian active learning
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
On-the-fly closed-loop materials discovery via Bayesian active learning
Authors
Keywords
-
Journal
Nature Communications
Volume 11, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-11-24
DOI
10.1038/s41467-020-19597-w
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Beyond Ternary OPV: High‐Throughput Experimentation and Self‐Driving Laboratories Optimize Multicomponent Systems
- (2020) Stefan Langner et al. ADVANCED MATERIALS
- Closed-loop optimization of fast-charging protocols for batteries with machine learning
- (2020) Peter M. Attia et al. NATURE
- Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy
- (2020) Ben Shneiderman INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
- Accelerated discovery of CO2 electrocatalysts using active machine learning
- (2020) Miao Zhong et al. NATURE
- Self-driving laboratory for accelerated discovery of thin-film materials
- (2020) B. P. MacLeod et al. Science Advances
- Robot-Accelerated Perovskite Investigation and Discovery
- (2020) Zhi Li et al. CHEMISTRY OF MATERIALS
- A mobile robotic chemist
- (2020) Benjamin Burger et al. NATURE
- Occurrence of the potent mutagens 2- nitrobenzanthrone and 3-nitrobenzanthrone in fine airborne particles
- (2019) Aldenor G. Santos et al. Scientific Reports
- The machine learning revolution in materials?
- (2019) Kristofer G. Reyes et al. MRS BULLETIN
- Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management
- (2019) Ian M. Pendleton et al. MRS Communications
- Unavoidable disorder and entropy in multi-component systems
- (2019) Cormac Toher et al. npj Computational Materials
- Phase-change materials: Empowered by an unconventional bonding mechanism
- (2019) J. Pries et al. MRS BULLETIN
- Phase-change heterostructure enables ultralow noise and drift for memory operation
- (2019) Keyuan Ding et al. SCIENCE
- A Kriging-Based Approach to Autonomous Experimentation with Applications to X-Ray Scattering
- (2019) Marcus M. Noack et al. Scientific Reports
- Accelerated Discovery of Large Electrostrains in BaTiO3 -Based Piezoelectrics Using Active Learning
- (2018) Ruihao Yuan et al. ADVANCED MATERIALS
- Experimental search for high-temperature ferroelectric perovskites guided by two-step machine learning
- (2018) Prasanna V. Balachandran et al. Nature Communications
- Accelerating the discovery of materials for clean energy in the era of smart automation
- (2018) Daniel P. Tabor et al. Nature Reviews Materials
- Fast and reliable storage using a 5 bit, nonvolatile photonic memory cell
- (2018) Xuan Li et al. Optica
- Phase-change materials for non-volatile photonic applications
- (2017) M. Wuttig et al. Nature Photonics
- Reducing the stochasticity of crystal nucleation to enable subnanosecond memory writing
- (2017) Feng Rao et al. SCIENCE
- On-the-Fly Data Assessment for High-Throughput X-ray Diffraction Measurements
- (2017) Fang Ren et al. ACS Combinatorial Science
- Accelerated search for materials with targeted properties by adaptive design
- (2016) Dezhen Xue et al. Nature Communications
- Autonomy in materials research: a case study in carbon nanotube growth
- (2016) Pavel Nikolaev et al. npj Computational Materials
- High-throughput determination of structural phase diagram and constituent phases using GRENDEL
- (2015) A G Kusne et al. NANOTECHNOLOGY
- Bonding Nature of Local Structural Motifs in Amorphous GeTe
- (2014) Volker L. Deringer et al. ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
- On-the-fly machine-learning for high-throughput experiments: search for rare-earth-free permanent magnets
- (2014) Aaron Gilad Kusne et al. Scientific Reports
- AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations
- (2012) Stefano Curtarolo et al. COMPUTATIONAL MATERIALS SCIENCE
- Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting
- (2012) Niranjan Srinivas et al. IEEE TRANSACTIONS ON INFORMATION THEORY
- Interfacial phase-change memory
- (2011) R. E. Simpson et al. Nature Nanotechnology
- Resonant bonding in crystalline phase-change materials
- (2008) Kostiantyn Shportko et al. NATURE MATERIALS
- A map for phase-change materials
- (2008) Dominic Lencer et al. NATURE MATERIALS
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started