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Automated Phase Mapping with AgileFD and its Application to Light Absorber Discovery in the V-Mn-Nb Oxide System

Suram, Santosh K. and Xue, Yexiang and Bai, Junwen and LeBras, Ronan and Rappazzo, Brendan H. and Bernstein, Richard and Bjorck, Johan and Zhou, Lan and van Dover, R. Bruce and Gomes, Carla P. and Gregoire, John M. (2017) Automated Phase Mapping with AgileFD and its Application to Light Absorber Discovery in the V-Mn-Nb Oxide System. ACS Combinatorial Science, 19 (1). pp. 37-46. ISSN 2156-8952. doi:10.1021/acscombsci.6b00153.

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Rapid construction of phase diagrams is a central tenet of combinatorial materials science with accelerated materials discovery efforts often hampered by challenges in interpreting combinatorial x-ray diffraction datasets, which we address by developing AgileFD, an artificial intelligence algorithm that enables rapid phase mapping from a combinatorial library of x-ray diffraction patterns. AgileFD models alloying-based peak shifting through a novel expansion of convolutional nonnegative matrix factorization, which not only improves the identification of constituent phases but also maps their concentration and lattice parameter as a function of composition. By incorporating Gibbs’ phase rule into the algorithm, physically meaningful phase maps are obtained with unsupervised operation, and more refined solutions are attained by injecting expert knowledge of the system. The algorithm is demonstrated through investigation of the V-Mn-Nb oxide system where decomposition of eight oxide phases, including two with substantial alloying, provides the first phase map for this pseudo-ternary system. This phase map enables interpretation of high-throughput band gap data, leading to the discovery of new solar light absorbers and the alloying-based tuning of the direct-allowed band-gap energy of MnV2O6. The open-source family of AgileFD algorithms can be implemented into a broad range of high throughput workflows to accelerate materials discovery.

Item Type:Article
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URLURL TypeDescription Information
Suram, Santosh K.0000-0001-8170-2685
Zhou, Lan0000-0002-7052-266X
Gregoire, John M.0000-0002-2863-5265
Additional Information:© 2016 American Chemical Society. ACS Editors' Choice. Received: October 6, 2016; Revised: November 15, 2016; Published: November 21, 2016. The experimental work was performed in the Joint Center for Artificial Photosynthesis (JCAP), a DOE Energy Innovation Hub supported through the Office of Science of the U.S. Department of Energy under Award No. DE-SC0004993. The algorithm development is supported by NSF awards CCF-1522054 and CNS-0832782 (Expeditions), CNS-1059284 (Infrastructure), and IIS-1344201 (INSPIRE); and ARO award W911-NF-14-1-0498. Use of the Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, is supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Contract No. DE-AC02-76SF00515. The authors thank Apurva Mehta and Douglas G. Van Campen for assistance with collection of synchrotron XRD data.
Funding AgencyGrant Number
Department of Energy (DOE)DE-SC0004993
Army Research Office (ARO)W911-NF-14-1-0498
Department of Energy (DOE)DE-AC02-76SF00515
Subject Keywords:High-throughput screening, machine learning, x-ray diffraction, combinatorial science, band gap tuning
Issue or Number:1
Record Number:CaltechAUTHORS:20161205-104618599
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Official Citation:Automated Phase Mapping with AgileFD and its Application to Light Absorber Discovery in the V–Mn–Nb Oxide System Santosh K. Suram, Yexiang Xue, Junwen Bai, Ronan Le Bras, Brendan Rappazzo, Richard Bernstein, Johan Bjorck, Lan Zhou, R. Bruce van Dover, Carla P. Gomes, and John M. Gregoire ACS Combinatorial Science 2017 19 (1), 37-46 DOI: 10.1021/acscombsci.6b00153
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:72553
Deposited By: Tony Diaz
Deposited On:06 Dec 2016 20:44
Last Modified:11 Nov 2021 05:03

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