On strong-scaling and open-source tools for analyzing atom probe tomography data

Abstract The development of strong-scaling computational tools for high-throughput methods with an open-source code and transparent metadata standards has successfully transformed many computational materials science communities. While such tools are mature already in the condensed-matter physics co...

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Autores principales:	Markus Kühbach, Priyanshu Bajaj, Huan Zhao, Murat H. Çelik, Eric A. Jägle, Baptiste Gault
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765
Acceso en línea:	https://doaj.org/article/328cc6f77e2f4ed29ea06821a8d086d9
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spelling	oai:doaj.org-article:328cc6f77e2f4ed29ea06821a8d086d92021-12-02T10:48:12ZOn strong-scaling and open-source tools for analyzing atom probe tomography data10.1038/s41524-020-00486-12057-3960https://doaj.org/article/328cc6f77e2f4ed29ea06821a8d086d92021-01-01T00:00:00Zhttps://doi.org/10.1038/s41524-020-00486-1https://doaj.org/toc/2057-3960Abstract The development of strong-scaling computational tools for high-throughput methods with an open-source code and transparent metadata standards has successfully transformed many computational materials science communities. While such tools are mature already in the condensed-matter physics community, the situation is still very different for many experimentalists. Atom probe tomography (APT) is one example. This microscopy and microanalysis technique has matured into a versatile nano-analytical characterization tool with applications that range from materials science to geology and possibly beyond. Here, data science tools are required for extracting chemo-structural spatial correlations from the reconstructed point cloud. For APT and other high-end analysis techniques, post-processing is mostly executed with proprietary software tools, which are opaque in their execution and have often limited performance. Software development by members of the scientific community has improved the situation but compared to the sophistication in the field of computational materials science several gaps remain. This is particularly the case for open-source tools that support scientific computing hardware, tools which enable high-throughput workflows, and open well-documented metadata standards to align experimental research better with the fair data stewardship principles. To this end, we introduce paraprobe, an open-source tool for scientific computing and high-throughput studying of point cloud data, here exemplified with APT. We show how to quantify uncertainties while applying several computational geometry, spatial statistics, and clustering tasks for post-processing APT datasets as large as two billion ions. These tools work well in concert with Python and HDF5 to enable several orders of magnitude performance gain, automation, and reproducibility.Markus KühbachPriyanshu BajajHuan ZhaoMurat H. ÇelikEric A. JägleBaptiste GaultNature PortfolioarticleMaterials of engineering and construction. Mechanics of materialsTA401-492Computer softwareQA76.75-76.765ENnpj Computational Materials, Vol 7, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765
spellingShingle	Materials of engineering and construction. Mechanics of materials TA401-492 Computer software QA76.75-76.765 Markus Kühbach Priyanshu Bajaj Huan Zhao Murat H. Çelik Eric A. Jägle Baptiste Gault On strong-scaling and open-source tools for analyzing atom probe tomography data
description	Abstract The development of strong-scaling computational tools for high-throughput methods with an open-source code and transparent metadata standards has successfully transformed many computational materials science communities. While such tools are mature already in the condensed-matter physics community, the situation is still very different for many experimentalists. Atom probe tomography (APT) is one example. This microscopy and microanalysis technique has matured into a versatile nano-analytical characterization tool with applications that range from materials science to geology and possibly beyond. Here, data science tools are required for extracting chemo-structural spatial correlations from the reconstructed point cloud. For APT and other high-end analysis techniques, post-processing is mostly executed with proprietary software tools, which are opaque in their execution and have often limited performance. Software development by members of the scientific community has improved the situation but compared to the sophistication in the field of computational materials science several gaps remain. This is particularly the case for open-source tools that support scientific computing hardware, tools which enable high-throughput workflows, and open well-documented metadata standards to align experimental research better with the fair data stewardship principles. To this end, we introduce paraprobe, an open-source tool for scientific computing and high-throughput studying of point cloud data, here exemplified with APT. We show how to quantify uncertainties while applying several computational geometry, spatial statistics, and clustering tasks for post-processing APT datasets as large as two billion ions. These tools work well in concert with Python and HDF5 to enable several orders of magnitude performance gain, automation, and reproducibility.
format	article
author	Markus Kühbach Priyanshu Bajaj Huan Zhao Murat H. Çelik Eric A. Jägle Baptiste Gault
author_facet	Markus Kühbach Priyanshu Bajaj Huan Zhao Murat H. Çelik Eric A. Jägle Baptiste Gault
author_sort	Markus Kühbach
title	On strong-scaling and open-source tools for analyzing atom probe tomography data
title_short	On strong-scaling and open-source tools for analyzing atom probe tomography data
title_full	On strong-scaling and open-source tools for analyzing atom probe tomography data
title_fullStr	On strong-scaling and open-source tools for analyzing atom probe tomography data
title_full_unstemmed	On strong-scaling and open-source tools for analyzing atom probe tomography data
title_sort	on strong-scaling and open-source tools for analyzing atom probe tomography data
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/328cc6f77e2f4ed29ea06821a8d086d9
work_keys_str_mv	AT markuskuhbach onstrongscalingandopensourcetoolsforanalyzingatomprobetomographydata AT priyanshubajaj onstrongscalingandopensourcetoolsforanalyzingatomprobetomographydata AT huanzhao onstrongscalingandopensourcetoolsforanalyzingatomprobetomographydata AT murathcelik onstrongscalingandopensourcetoolsforanalyzingatomprobetomographydata AT ericajagle onstrongscalingandopensourcetoolsforanalyzingatomprobetomographydata AT baptistegault onstrongscalingandopensourcetoolsforanalyzingatomprobetomographydata
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On strong-scaling and open-source tools for analyzing atom probe tomography data

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