Austin McDannald

National Institute of Standards and Technology — United States

Materials Science · Physical Sciences

16h-index946citations55works3.72yr avg
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Research Topics

Machine Learning in Materials Science(16), Multiferroics and related materials(13), Magnetic and transport properties of perovskites and related materials(10), Carbon Dioxide Capture Technologies(6), Advanced Condensed Matter Physics(6)

Publications55 total

Agent, Agentic, and Distributed Artificial Intelligence: From Managing Next-Generation Labs to the Philosophy of Science
2025Open Access
Real-time experiment-theory closed-loop interaction for autonomous materials science
Science Advances·2025· 10 citedOpen Access
Autonomous Small-Angle Scattering for Accelerated Soft Material Formulation Optimization
Chemistry of Materials·2025· 2 citedOpen Access
Intrinsic Direct Air Capture
arXiv (Cornell University)·2025Open Access
Intrinsic direct air capture
Chemical Science·2025· 1 citedOpen Access
Microstructure and mechanical properties of laser powder bed fusion Ti-6Al-4V after HIP treatments with varied temperatures and cooling rates
Materials & Design·2024· 12 citedOpen Access
NIST Workshop: Integrating Crystallographic and Computational Approaches to Carbon-Capture Materials for the Mitigation of Climate Change (October 31–November 1, 2023)
Powder Diffraction·2024
Human-in-the-loop for Bayesian autonomous materials phase mapping
Matter·2024· 12 cited
Integrating crystallographic and computational approaches to carbon-capture materials for the mitigation of climate change
Journal of Materials Chemistry A·2024Open Access
Autonomous cementitious materials formulation platform for critical infrastructure repair
Digital Discovery·2024· 1 citedOpen Access
Learning material synthesis–process–structure–property relationship by data fusion: Bayesian co-regionalization N-dimensional piecewise function learning
Digital Discovery·2024· 3 citedOpen Access
Learning material synthesis-process-structure-property relationship by data fusion: Bayesian Coregionalization N-Dimensional Piecewise Function Learning
arXiv (Cornell University)·2023· 1 citedOpen Access
Human-In-the-Loop for Bayesian Autonomous Materials Phase Mapping
arXiv (Cornell University)·2023· 2 citedOpen Access
A framework for materials informatics education through workshops
MRS Bulletin·2023· 5 citedOpen Access
Leveraging uncertainty estimates and derivative information in Gaussian process regression for efficient collection and use of molecular simulation data
The Journal of Chemical Physics·2023· 5 citedOpen Access
Scalable multi-agent lab framework for lab optimization
Matter·2023· 31 cited
ANDiE the Autonomous Neutron Diffraction Explorer
Neutron News·2023· 3 citedOpen Access
Autonomous Cementitious Materials Formulation for Critical Infrastructure Repair
SSRN Electronic Journal·2023Open Access
Human-in-The-Loop for Bayesian Autonomous Materials Phase Mapping
SSRN Electronic Journal·2023Open Access
Working around microanalytical data gaps to make multiscale predictions- exploring the Bon Accord nickel mineral species
2023Open Access
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Frequent Co-authors

M. Jain(17), A. Gilad Kusne(15), Ichiro Takeuchi(11), Brian DeCost(7), Kamal Choudhary(5), Taner Yildirim(5), Diana L. Ortiz‐Montalvo(5), Haotong Liang(5), Lukasz Kuna(4), Daniel W. Siderius(4), Howie Joress(4), A. Gilad Kusne(4), W. Wong‐Ng(4), Margo Staruch(3), Efrain E. Rodriguez(3), F. Adams(3), Vinit Sharma(2), M. S. Seehra(2), Steven J. Woltornist(2), Fahad Alhashmi Alamer(2)