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Poline V, Purushottam Raj Purohit RRP, Bordet P, Blanc N, Martinetto P. Neural networks for rapid phase quantification of cultural heritage X-ray powder diffraction data. J Appl Crystallogr 2024; 57:831-841. [PMID: 38846765 PMCID: PMC11151672 DOI: 10.1107/s1600576724003704] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 04/23/2024] [Indexed: 06/09/2024] Open
Abstract
Recent developments in synchrotron radiation facilities have increased the amount of data generated during acquisitions considerably, requiring fast and efficient data processing techniques. Here, the application of dense neural networks (DNNs) to data treatment of X-ray diffraction computed tomography (XRD-CT) experiments is presented. Processing involves mapping the phases in a tomographic slice by predicting the phase fraction in each individual pixel. DNNs were trained on sets of calculated XRD patterns generated using a Python algorithm developed in-house. An initial Rietveld refinement of the tomographic slice sum pattern provides additional information (peak widths and integrated intensities for each phase) to improve the generation of simulated patterns and make them closer to real data. A grid search was used to optimize the network architecture and demonstrated that a single fully connected dense layer was sufficient to accurately determine phase proportions. This DNN was used on the XRD-CT acquisition of a mock-up and a historical sample of highly heterogeneous multi-layered decoration of a late medieval statue, called 'applied brocade'. The phase maps predicted by the DNN were in good agreement with other methods, such as non-negative matrix factorization and serial Rietveld refinements performed with TOPAS, and outperformed them in terms of speed and efficiency. The method was evaluated by regenerating experimental patterns from predictions and using the R-weighted profile as the agreement factor. This assessment allowed us to confirm the accuracy of the results.
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Affiliation(s)
- Victor Poline
- Univ. Grenoble Alpes, CNRS, Grenoble INP, Institut Néel, 38000 Grenoble, France
| | | | - Pierre Bordet
- Univ. Grenoble Alpes, CNRS, Grenoble INP, Institut Néel, 38000 Grenoble, France
| | - Nils Blanc
- Univ. Grenoble Alpes, CNRS, Grenoble INP, Institut Néel, 38000 Grenoble, France
| | - Pauline Martinetto
- Univ. Grenoble Alpes, CNRS, Grenoble INP, Institut Néel, 38000 Grenoble, France
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2
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Magnussen OM, Drnec J, Qiu C, Martens I, Huang JJ, Chattot R, Singer A. In Situ and Operando X-ray Scattering Methods in Electrochemistry and Electrocatalysis. Chem Rev 2024; 124:629-721. [PMID: 38253355 PMCID: PMC10870989 DOI: 10.1021/acs.chemrev.3c00331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 10/02/2023] [Accepted: 11/13/2023] [Indexed: 01/24/2024]
Abstract
Electrochemical and electrocatalytic processes are of key importance for the transition to a sustainable energy supply as well as for a wide variety of other technologically relevant fields. Further development of these processes requires in-depth understanding of the atomic, nano, and micro scale structure of the materials and interfaces in electrochemical devices under reaction conditions. We here provide a comprehensive review of in situ and operando studies by X-ray scattering methods, which are powerful and highly versatile tools to provide such understanding. We discuss the application of X-ray scattering to a wide variety of electrochemical systems, ranging from metal and oxide single crystals to nanoparticles and even full devices. We show how structural data on bulk phases, electrode-electrolyte interfaces, and nanoscale morphology can be obtained and describe recent developments that provide highly local information and insight into the composition and electronic structure. These X-ray scattering studies yield insights into the structure in the double layer potential range as well as into the structural evolution during electrocatalytic processes and phase formation reactions, such as nucleation and growth during electrodeposition and dissolution, the formation of passive films, corrosion processes, and the electrochemical intercalation into battery materials.
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Affiliation(s)
- Olaf M. Magnussen
- Kiel
University, Institute of Experimental and
Applied Physics, 24098 Kiel, Germany
- Ruprecht-Haensel
Laboratory, Kiel University, 24118 Kiel, Germany
| | - Jakub Drnec
- ESRF,
Experiments Division, 38000 Grenoble, France
| | - Canrong Qiu
- Kiel
University, Institute of Experimental and
Applied Physics, 24098 Kiel, Germany
| | | | - Jason J. Huang
- Department
of Materials Science and Engineering, Cornell
University, Ithaca, New York 14853, United States
| | - Raphaël Chattot
- ICGM,
Univ. Montpellier, CNRS, ENSCM, 34095 Montpellier Cedex 5, France
| | - Andrej Singer
- Department
of Materials Science and Engineering, Cornell
University, Ithaca, New York 14853, United States
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Omori NE, Bobitan AD, Vamvakeros A, Beale AM, Jacques SDM. Recent developments in X-ray diffraction/scattering computed tomography for materials science. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2023; 381:20220350. [PMID: 37691470 PMCID: PMC10493554 DOI: 10.1098/rsta.2022.0350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 07/17/2023] [Indexed: 09/12/2023]
Abstract
X-ray diffraction/scattering computed tomography (XDS-CT) methods are a non-destructive class of chemical imaging techniques that have the capacity to provide reconstructions of sample cross-sections with spatially resolved chemical information. While X-ray diffraction CT (XRD-CT) is the most well-established method, recent advances in instrumentation and data reconstruction have seen greater use of related techniques like small angle X-ray scattering CT and pair distribution function CT. Additionally, the adoption of machine learning techniques for tomographic reconstruction and data analysis are fundamentally disrupting how XDS-CT data is processed. The following narrative review highlights recent developments and applications of XDS-CT with a focus on studies in the last five years. This article is part of the theme issue 'Exploring the length scales, timescales and chemistry of challenging materials (Part 2)'.
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Affiliation(s)
- Naomi E. Omori
- Finden Limited, Merchant House, 5 East St Helens Street,Abingdon OX14 5EG, UK
| | - Antonia D. Bobitan
- Finden Limited, Merchant House, 5 East St Helens Street,Abingdon OX14 5EG, UK
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK
- Research Complex at Harwell, Rutherford Appleton Laboratory, Harwell Science and Innovation Campus, Didcot, Oxon OX11 0FA, UK
| | - Antonis Vamvakeros
- Finden Limited, Merchant House, 5 East St Helens Street,Abingdon OX14 5EG, UK
- Dyson School of Design Engineering, Imperial College London, London SW7 2DB, UK
| | - Andrew M. Beale
- Finden Limited, Merchant House, 5 East St Helens Street,Abingdon OX14 5EG, UK
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK
- Research Complex at Harwell, Rutherford Appleton Laboratory, Harwell Science and Innovation Campus, Didcot, Oxon OX11 0FA, UK
| | - Simon D. M. Jacques
- Finden Limited, Merchant House, 5 East St Helens Street,Abingdon OX14 5EG, UK
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Jensen AB, Christensen TEK, Weninger C, Birkedal H. Very large-scale diffraction investigations enabled by a matrix-multiplication facilitated radial and azimuthal integration algorithm: MatFRAIA. JOURNAL OF SYNCHROTRON RADIATION 2022; 29:1420-1428. [PMID: 36345750 PMCID: PMC9641557 DOI: 10.1107/s1600577522008232] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 08/17/2022] [Indexed: 05/22/2023]
Abstract
As synchrotron facilities continue to generate increasingly brilliant X-rays and detector speeds increase, swift data reduction from the collected area detector images to more workable 1D diffractograms becomes of increasing importance. This work reports an integration algorithm that can integrate diffractograms in real time on modern laptops and can reach 10 kHz integration speeds on modern workstations using an efficient pixel-splitting and parallelization scheme. This algorithm is limited not by the computation of the integration itself but is rather bottlenecked by the speed of the data transfer to the processor, the data decompression and/or the saving of results. The algorithm and its implementation is described while the performance is investigated on 2D scanning X-ray diffraction/fluorescence data collected at the interface between an implant and forming bone.
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Affiliation(s)
| | - Thorbjørn Erik Køppen Christensen
- Department of Chemistry and iNANO, Aarhus University, Gustav Wieds Vej 14, 8000 Aarhus, Denmark
- Sino-Danish College (SDC), University of Chinese Academy of Sciences, People’s Republic of China
| | | | - Henrik Birkedal
- Department of Chemistry and iNANO, Aarhus University, Gustav Wieds Vej 14, 8000 Aarhus, Denmark
- Correspondence e-mail:
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Vamvakeros A, Matras D, Ashton TE, Coelho AA, Dong H, Bauer D, Odarchenko Y, Price SWT, Butler KT, Gutowski O, Dippel AC, Zimmerman MV, Darr JA, Jacques SDM, Beale AM. Cycling Rate-Induced Spatially-Resolved Heterogeneities in Commercial Cylindrical Li-Ion Batteries. SMALL METHODS 2021; 5:e2100512. [PMID: 34928070 DOI: 10.1002/smtd.202100512] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 06/29/2021] [Indexed: 06/14/2023]
Abstract
Synchrotron high-energy X-ray diffraction computed tomography has been employed to investigate, for the first time, commercial cylindrical Li-ion batteries electrochemically cycled over the two cycling rates of C/2 and C/20. This technique yields maps of the crystalline components and chemical species as a cross-section of the cell with high spatiotemporal resolution (550 × 550 images with 20 × 20 × 3 µm3 voxel size in ca. 1 h). The recently developed Direct Least-Squares Reconstruction algorithm is used to overcome the well-known parallax problem and led to accurate lattice parameter maps for the device cathode. Chemical heterogeneities are revealed at both electrodes and are attributed to uneven Li and current distributions in the cells. It is shown that this technique has the potential to become an invaluable diagnostic tool for real-world commercial batteries and for their characterization under operating conditions, leading to unique insights into "real" battery degradation mechanisms as they occur.
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Affiliation(s)
- Antonis Vamvakeros
- Finden Limited, Merchant House, 5 East St Helens Street, Abingdon, OX14 5EG, UK
| | - Dorota Matras
- The Faraday Institution, Quad One, Harwell Science and Innovation Campus, Didcot, OX11 0RA, UK
- Diamond Light Source, Harwell Science and Innovation Campus, Didcot, Oxfordshire, OX11 0DE, UK
| | - Thomas E Ashton
- Department of Chemistry, University College London, 20 Gordon Street, London, WC1H 0AJ, UK
| | - Alan A Coelho
- Coelho Software, 72 Cedar Street, Wynnum, Brisbane, Queensland, 4178, Australia
| | - Hongyang Dong
- Department of Chemistry, University College London, 20 Gordon Street, London, WC1H 0AJ, UK
| | - Dustin Bauer
- Department of Chemistry, University College London, 20 Gordon Street, London, WC1H 0AJ, UK
| | - Yaroslav Odarchenko
- Finden Limited, Merchant House, 5 East St Helens Street, Abingdon, OX14 5EG, UK
| | - Stephen W T Price
- Finden Limited, Merchant House, 5 East St Helens Street, Abingdon, OX14 5EG, UK
| | - Keith T Butler
- SciML, Scientific Computer Division, Rutherford Appleton Laboratory, Harwell, OX11 0QX, UK
| | - Olof Gutowski
- Deutsches Elektronen-Synchrotron DESY, Notkestraße 85, 22607, Hamburg, Germany
| | - Ann-Christin Dippel
- Deutsches Elektronen-Synchrotron DESY, Notkestraße 85, 22607, Hamburg, Germany
| | | | - Jawwad A Darr
- Department of Chemistry, University College London, 20 Gordon Street, London, WC1H 0AJ, UK
| | - Simon D M Jacques
- Finden Limited, Merchant House, 5 East St Helens Street, Abingdon, OX14 5EG, UK
| | - Andrew M Beale
- Finden Limited, Merchant House, 5 East St Helens Street, Abingdon, OX14 5EG, UK
- Department of Chemistry, University College London, 20 Gordon Street, London, WC1H 0AJ, UK
- Research Complex at Harwell, Rutherford Appleton Laboratory, Harwell Science and Innovation Campus, Didcot, Oxon, OX11 0FA, UK
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Mapping the coke formation within a zeolite catalyst extrudate in space and time by operando computed X-ray diffraction tomography. J Catal 2021. [DOI: 10.1016/j.jcat.2021.07.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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