@article{6ed4fbb343fc420ca5cb13e762ca8f9a,
title = "Multi-modal Dataset of a Polycrystalline Metallic Material: 3D Microstructure and Deformation Fields",
abstract = "The development of high-fidelity mechanical property prediction models for the design of polycrystalline materials relies on large volumes of microstructural feature data. Concurrently, at these same scales, the deformation fields that develop during mechanical loading can be highly heterogeneous. Spatially correlated measurements of 3D microstructure and the ensuing deformation fields at the micro-scale would provide highly valuable insight into the relationship between microstructure and macroscopic mechanical response. They would also provide direct validation for numerical simulations that can guide and speed up the design of new materials and microstructures. However, to date, such data have been rare. Here, a one-of-a-kind, multi-modal dataset is presented that combines recent state-of-the-art experimental developments in 3D tomography and high-resolution deformation field measurements.",
author = "Stinville, {J. C.} and Hestroffer, {J. M.} and Charpagne, {M. A.} and Polonsky, {A. T.} and Echlin, {M. P.} and Torbet, {C. J.} and V. Valle and Nygren, {K. E.} and Miller, {M. P.} and O. Klaas and A. Loghin and Beyerlein, {I. J.} and Pollock, {T. M.}",
note = "Sebastien Stinville is acknowledged for his contribution and discussion of figure designs. Patrick Villechaise, Jonathan Cormier and Damien Texier are acknowledged for providing the Inconel 718 material. Toby Francis is acknowledged for his support during 3D dataset collection. This work is funded by the U.S. Dept. of Energy, Office of Basic Energy Sciences Program DE-SC0018901. Use was made of computational facilities purchased with funds from the National Science Foundation (CNS-1725797) and administered by the Center for Scientific Computing (CSC). The CSC is supported by the California NanoSystems Institute and the Materials Research Science and Engineering Center (MRSEC; NSF DMR 1720256) at UC Santa Barbara. The NSF OAC Grant 1925717 is also acknowledged for GPU compute resources for data reindexing. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy{\textquoteright}s National Nuclear Security Administration under contract DE-NA-0003525. J.C.S. is grateful for financial support from start-up fund from the Materials Science and Engineering department at the University of Illinois at Urbana-Champaign. Sebastien Stinville is acknowledged for his contribution and discussion of figure designs. Patrick Villechaise, Jonathan Cormier and Damien Texier are acknowledged for providing the Inconel 718 material. Toby Francis is acknowledged for his support during 3D dataset collection. This work is funded by the U.S. Dept. of Energy, Office of Basic Energy Sciences Program DE-SC0018901. Use was made of computational facilities purchased with funds from the National Science Foundation (CNS-1725797) and administered by the Center for Scientific Computing (CSC). The CSC is supported by the California NanoSystems Institute and the Materials Research Science and Engineering Center (MRSEC; NSF DMR 1720256) at UC Santa Barbara. The NSF OAC Grant 1925717 is also acknowledged for GPU compute resources for data reindexing. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy{\textquoteright}s National Nuclear Security Administration under contract DE-NA-0003525. J.C.S. is grateful for financial support from start-up fund from the Materials Science and Engineering department at the University of Illinois at Urbana-Champaign.",
year = "2022",
month = dec,
doi = "10.1038/s41597-022-01525-w",
language = "English (US)",
volume = "9",
journal = "Scientific Data",
issn = "2052-4463",
publisher = "Nature Publishing Group",
number = "1",
}