Methods and applications of autonomous experimentation / edited by Marcus M. Noack and Daniela Ushizima.

Format:

Book

Contributor:

Noack, Marcus M., editor.

Ushizima, Daniela, editor.

Taylor & Francis eBooks

Series:

Chapman & Hall/CRC computational science series

Language:

English

Subjects (All):

Research--Methodology.

Research.

Physical Description:

1 online resource (xlii, 402 pages).

Edition:

First edition.

Place of Publication:

Boca Raton : CRC Press, Taylor & Francis Group, 2024.

Biography/History:

Marcus M. Noack received his Ph.D. in applied mathematics from Oslo University, Norway. At Lawrence Berkeley National Laboratory, he is working on stochastic function approximation, optimization and uncertainty quantification, applied to Autonomous Experimentation. Daniela Ushizima, Ph.D. in physics from the University of Sao Paulo, Brazil after majoring in computer science, has been associated with Lawrence Berkeley National Laboratory since 2007, where she investigates machine learning algorithms applied to image processing. Her primary focus has been on developing computer vision software to automate scientific data analysis.

Contents:

PrefaceContributorsChapter 1 Autonomous Experimentation in PracticeKevin G. YagerChapter 2 A Friendly Mathematical Perspective on Autonomous ExperimentationMarcus M. NoackChapter 3 A Perspective on Machine Learning for Autonomous ExperimentationJoshua Schrier and Alexander J. NorquistChapter 4 Gaussian ProcessesMarcus M. NoackChapter 5 Uncertainty QuantificationMark D. Risser and Marcus M. NoackChapter 6 Surrogate Model Guided OptimizationJuliane MuellerChapter 7 Artificial Neural NetworksDaniela UshizimaChapter 8 NSLS2Philip M. Maffettone, Daniel B. Allan, Andi Barbour, Thomas A. Caswell, Dmitri Gavrilov, Marcus D. Handwell, Thomas Morris, Daniel Olds, Maksim Rakitin, Stuart I. Campbell and Bruce RavelChapter 9 Reinforcement LearningYixuan Sun, Krishnan Raghavan and Prasanna BalaprakashChapter 10 Applications of Autonomous Methods to Synchrotron X-ray Scattering and Diffraction ExperimentsMasafumi Fukuto, Yu-Chen Wiegart, Marcus M. Noack and Kevin G. YagerChapter 11 Autonomous Infrared Absorption SpectroscopyHoi-Ying Holman, Steven Lee, Liang Chen, Petrus H. Zwart and Marcus M. NoackChapter 12 Autonomous Hyperspectral Scanning Tunneling SpectroscopyAntonio Rossi, Darian Smalley, Masahiro Ishigami, Eli Rotenberg, Alexander Weber-Barigoni and John C. ThomasChapter 13 Autonomous Control and Analyses of Fabricated EcosystemsTrent R. Northern, Peter Andeer, Marcus M. Noack, Ptrus H. Zwart and Daniela UshizimaChapter 14 Autonomous Neutron ExperimentsMartin Boehm, David E. Perryman, Alessio De Francesco, Luisa Scaccia, Alessandro Cunsolo, Tobias Weber, Yannick LeGoc and Paolo MuttiChapter 15 Material Discovery in Poorly Explored High-Dimensional Targeted SpacesSuchismita Sarker and Apurva MehtaChapter 16 Autonomous Optical Microscopy for Exploring Nucleation and Growth of DNA CrystalsAaron N. MichelsonChapter 17 Constratined Autonomous Modelin of Metal-Mineral AdsorptionElliot Chang, Linda Beverly and Haruko WainwrightChapter 18 Physics-In-The-LoopAaron Gilad KusneChapter 19 A Closed Loop of Diverse DisciplinesMarucs M. Noack and Kevin G. YagerChapter 20 Analysis of Raw DataMarcus M. Noack and Kevin G. YagerChapter 21 Autonomous Intelligent Decision MakingMarcus M. Noack and Kevin G. YagerChapter 22 Data InfrastructureMarcus M. Noack and Kevin G. YagerBibliographyIndex

Notes:

Includes bibliographical references and index.

Electronic reproduction. London Available via World Wide Web.

Online resource; title from PDF title page (Taylor & Francis, viewed December 13. 2023).

ISBN:

9781003359593

1003359590

9781003821267

100382126X

9781003821281

1003821286

Publisher Number:

40032099995

Access Restriction:

Restricted for use by site license.