AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy

Horwath, James P.; Lin, Xiao-Min; He, Hongrui; Zhang, Qingteng; Dufresne, Eric M.; Chu, Miaoqi; Sankaranarayanan, Subramanian K. R. S.; Chen, Wei; Narayanan, Suresh; Cherukara, Mathew J.

doi:10.1038/s41467-024-49381-z

Title: AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy

Journal Article · 15 July 2024 · Nature Communications

DOI: https://doi.org/10.1038/s41467-024-49381-z · OSTI ID:2440099

;

; He, Hongrui;

;

; Sankaranarayanan, Subramanian K. R. S.;

; Narayanan, Suresh;

Abstract Understanding and interpreting dynamics of functional materials in situ is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales. However, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work, we have developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. We demonstrate how this method can be used to accelerate exploration of large datasets to identify samples of interest, and we apply this approach to directly correlate microscopic dynamics with macroscopic properties of a model system. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.

View Journal Article

Cite

Export

Save

Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States). Advanced Photon Source (APS); Argonne National Laboratory (ANL), Argonne, IL (United States). Center for Nanoscale Materials (CNM)

Sponsoring Organization:: USDOE; USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division (MSE)

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 2440099

Journal Information:: Nature Communications, Journal Name: Nature Communications Journal Issue: 1 Vol. 15; ISSN 2041-1723

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United Kingdom

Language:: English

References (79)

Machine‐Learning‐Based Image Similarity Analysis for Use in Materials Characterization Wang, Zhi‐Lei; Ogawa, Toshio; Adachi, Yoshitaka Advanced Theory and Simulations, Vol. 3, Issue 3 https://doi.org/10.1002/adts.201900237	journal	January 2020
Dynamic Light Scattering Chu, B. Soft Matter Characterization, p. 335-372 https://doi.org/10.1007/978-1-4020-4465-6_7	book	January 2008
Computer Vision and Machine Learning for Autonomous Characterization of AM Powder Feedstocks DeCost, Brian L.; Jain, Harshvardhan; Rollett, Anthony D. JOM, Vol. 69, Issue 3 https://doi.org/10.1007/s11837-016-2226-1	journal	December 2016
Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda Kumar, Yogesh; Koul, Apeksha; Singla, Ruchi Journal of Ambient Intelligence and Humanized Computing, Vol. 14, Issue 7 https://doi.org/10.1007/s12652-021-03612-z	journal	January 2022
Structure and rheology of colloidal particle gels: Insight from computer simulation Dickinson, Eric Advances in Colloid and Interface Science, Vol. 199-200 https://doi.org/10.1016/j.cis.2013.07.002	journal	November 2013
Dynamics in hard condensed matter probed by X-ray photon correlation spectroscopy: Present and beyond Zhang (张庆腾), Qingteng; Dufresne, Eric M.; Sandy, Alec R. Current Opinion in Solid State and Materials Science, Vol. 22, Issue 5 https://doi.org/10.1016/j.cossms.2018.06.002	journal	October 2018
The saga of MAX IV, the first multi-bend achromat synchrotron light source Martensson, Nils; Eriksson, Mikael Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 907 https://doi.org/10.1016/j.nima.2018.03.018	journal	November 2018
Five High-Impact Research Areas in Machine Learning for Materials Science Meredig, Bryce Chemistry of Materials, Vol. 31, Issue 23 https://doi.org/10.1021/acs.chemmater.9b04078	journal	December 2019
Latent Representation Learning for Structural Characterization of Catalysts Routh, Prahlad K.; Liu, Yang; Marcella, Nicholas The Journal of Physical Chemistry Letters, Vol. 12, Issue 8 https://doi.org/10.1021/acs.jpclett.0c03792	journal	February 2021
Deep Learning and Infrared Spectroscopy: Representation Learning with a β-Variational Autoencoder Grossutti, Michael; D’Amico, Joseph; Quintal, Jonathan The Journal of Physical Chemistry Letters, Vol. 13, Issue 25 https://doi.org/10.1021/acs.jpclett.2c01328	journal	June 2022
Measurement of growing dynamical length scales and prediction of the jamming transition in a granular material Keys, Aaron S.; Abate, Adam R.; Glotzer, Sharon C. Nature Physics, Vol. 3, Issue 4 https://doi.org/10.1038/nphys572	journal	March 2007
Recent advances and applications of machine learning in solid-state materials science Schmidt, Jonathan; Marques, Mário R. G.; Botti, Silvana npj Computational Materials, Vol. 5, Issue 1 https://doi.org/10.1038/s41524-019-0221-0	journal	August 2019
Machine learning enabled autonomous microstructural characterization in 3D samples Chan, Henry; Cherukara, Mathew; Loeffler, Troy D. npj Computational Materials, Vol. 6, Issue 1 https://doi.org/10.1038/s41524-019-0267-z	journal	January 2020
Theoretical prediction of high melting temperature for a Mo–Ru–Ta–W HCP multiprincipal element alloy Hong, Qi-Jun; Schroers, Jan; Hofmann, Douglas npj Computational Materials, Vol. 7, Issue 1 https://doi.org/10.1038/s41524-020-00473-6	journal	January 2021
Two-dimensional Stiefel-Whitney insulators in liganded Xenes Pan, Mingxiang; Li, Dexin; Fan, Jiahao npj Computational Materials, Vol. 8, Issue 1 https://doi.org/10.1038/s41524-021-00695-2	journal	January 2022
Coherent X-ray spectroscopy reveals the persistence of island arrangements during layer-by-layer growth Ju, Guangxu; Xu, Dongwei; Highland, Matthew J. Nature Physics, Vol. 15, Issue 6 https://doi.org/10.1038/s41567-019-0448-1	journal	March 2019
Fast and accurate data collection for macromolecular crystallography using the JUNGFRAU detector Leonarski, Filip; Redford, Sophie; Mozzanica, Aldo Nature Methods, Vol. 15, Issue 10 https://doi.org/10.1038/s41592-018-0143-7	journal	October 2018
Real-time coherent diffraction inversion using deep generative networks Cherukara, Mathew J.; Nashed, Youssef S. G.; Harder, Ross J. Scientific Reports, Vol. 8, Issue 1 https://doi.org/10.1038/s41598-018-34525-1	journal	November 2018
Noise reduction in X-ray photon correlation spectroscopy with convolutional neural networks encoder–decoder models Konstantinova, Tatiana; Wiegart, Lutz; Rakitin, Maksim Scientific Reports, Vol. 11, Issue 1 https://doi.org/10.1038/s41598-021-93747-y	journal	July 2021
The fractal correlation between relaxation dynamics and atomic-level structures observed in metallic glasses by computer simulation Yang, M. H.; Li, J. H.; Liu, B. X. Physical Chemistry Chemical Physics, Vol. 19, Issue 25 https://doi.org/10.1039/C7CP02205K	journal	January 2017
Heterogeneities in granular materials Mehta, Anita; Barker, Gary C.; Luck, Jean-Marc Physics Today, Vol. 62, Issue 5 https://doi.org/10.1063/1.3141940	journal	May 2009
A new framework for X-ray photon correlation spectroscopy analysis from polycrystalline materials Lewis, Ronald M.; Jackson, Grayson L.; Maher, Michael J. Review of Scientific Instruments, Vol. 89, Issue 12 https://doi.org/10.1063/1.5051451	journal	December 2018
AI-enabled high-resolution scanning coherent diffraction imaging Cherukara, Mathew J.; Zhou, Tao; Nashed, Youssef Applied Physics Letters, Vol. 117, Issue 4 https://doi.org/10.1063/5.0013065	journal	July 2020
Rapid 3D nanoscale coherent imaging via physics-aware deep learning Chan, Henry; Nashed, Youssef S. G.; Kandel, Saugat Applied Physics Reviews, Vol. 8, Issue 2 https://doi.org/10.1063/5.0031486	journal	June 2021
Diffusive dynamics during the high-to-low density transition in amorphous ice Perakis, Fivos; Amann-Winkel, Katrin; Lehmkühler, Felix Proceedings of the National Academy of Sciences, Vol. 114, Issue 31 https://doi.org/10.1073/pnas.1705303114	journal	June 2017
Emergence of anomalous dynamics in soft matter probed at the European XFEL Lehmkühler, Felix; Dallari, Francesco; Jain, Avni Proceedings of the National Academy of Sciences, Vol. 117, Issue 39 https://doi.org/10.1073/pnas.2003337117	journal	September 2020
Cross-correlation analysis of X-ray photon correlation spectroscopy to extract rotational diffusion coefficients Hu, Zixi; Donatelli, Jeffrey J.; Sethian, James A. Proceedings of the National Academy of Sciences, Vol. 118, Issue 34 https://doi.org/10.1073/pnas.2105826118	journal	August 2021
Microscopic dynamics underlying the stress relaxation of arrested soft materials Song, Jake; Zhang, Qingteng; de Quesada, Felipe Proceedings of the National Academy of Sciences, Vol. 119, Issue 30 https://doi.org/10.1073/pnas.2201566119	journal	July 2022
ESRF: Inside the Extremely Brilliant Source Upgrade Chenevier, D.; Joly, A. Synchrotron Radiation News, Vol. 31, Issue 1 https://doi.org/10.1080/08940886.2018.1409562	journal	January 2018
Advancing AI/ML at the Advanced Photon Source Benmore, Chris; Bicer, Tekin; Chan, Maria K. Y. Synchrotron Radiation News, Vol. 35, Issue 4 https://doi.org/10.1080/08940886.2022.2112500	journal	July 2022
The physics of jamming for granular materials: a review Behringer, Robert P.; Chakraborty, Bulbul Reports on Progress in Physics, Vol. 82, Issue 1 https://doi.org/10.1088/1361-6633/aadc3c	journal	November 2018
The LAMBDA photon-counting pixel detector Pennicard, D.; Lange, S.; Smoljanin, S. Journal of Physics: Conference Series, Vol. 425, Issue 6 https://doi.org/10.1088/1742-6596/425/6/062010	journal	March 2013
LAMBDA 2M GaAs—A multi-megapixel hard X-ray detector for synchrotrons Pennicard, D.; Smoljanin, S.; Pithan, F. Journal of Instrumentation, Vol. 13, Issue 01 https://doi.org/10.1088/1748-0221/13/01/C01026	journal	January 2018
https://doi.org/10.1093/acprof:oso/9780199691470.001.0001	book
Collimator irradiation studies in the Argonne Advanced Photon Source at energy densities expected in next-generation storage ring light sources Dooling, J.; Borland, M.; Berg, W. Physical Review Accelerators and Beams, Vol. 25, Issue 4 https://doi.org/10.1103/PhysRevAccelBeams.25.043001	journal	April 2022
Discovering phase transitions with unsupervised learning Wang, Lei Physical Review B, Vol. 94, Issue 19 https://doi.org/10.1103/PhysRevB.94.195105	journal	November 2016
Viscoelastic Effects in Avalanche Dynamics: A Key to Earthquake Statistics Jagla, E. A.; Landes, François P.; Rosso, Alberto Physical Review Letters, Vol. 112, Issue 17 https://doi.org/10.1103/PhysRevLett.112.174301	journal	April 2014
Thermal Fluctuations of Ferroelectric Nanodomains in a Ferroelectric-Dielectric PbTiO 3 / SrTiO 3 Superlattice Zhang, Qingteng; Dufresne, Eric M.; Chen, Pice Physical Review Letters, Vol. 118, Issue 9 https://doi.org/10.1103/PhysRevLett.118.097601	journal	February 2017
Unraveling the Role of Order-to-Disorder Transition in Shear Thickening Suspensions Lee, Jonghun; Jiang, Zhang; Wang, Jin Physical Review Letters, Vol. 120, Issue 2 https://doi.org/10.1103/PhysRevLett.120.028002	journal	January 2018
Dynamical Heterogeneity near Glass Transition Temperature under Shear Conditions Hoshino, Taiki; Fujinami, So; Nakatani, Tomotaka Physical Review Letters, Vol. 124, Issue 11 https://doi.org/10.1103/PhysRevLett.124.118004	journal	March 2020
Wave-Vector Dependence of the Dynamics in Supercooled Metallic Liquids Ruta, B.; Hechler, S.; Neuber, N. Physical Review Letters, Vol. 125, Issue 5 https://doi.org/10.1103/PhysRevLett.125.055701	journal	July 2020
Nanoscale Critical Phenomena in a Complex Fluid Studied by X-Ray Photon Correlation Spectroscopy Sheyfer, D.; Zhang, Qingteng; Lal, J. Physical Review Letters, Vol. 125, Issue 12 https://doi.org/10.1103/PhysRevLett.125.125504	journal	September 2020
de Gennes Narrowing and Relationship between Structure and Dynamics in Self-Organized Ion-Beam Nanopatterning Myint, Peco; Ludwig, Karl F.; Wiegart, Lutz Physical Review Letters, Vol. 126, Issue 1 https://doi.org/10.1103/PhysRevLett.126.016101	journal	January 2021
Microscopic Dynamics of Liquid-Liquid Phase Separation and Domain Coarsening in a Protein Solution Revealed by X-Ray Photon Correlation Spectroscopy Girelli, Anita; Rahmann, Hendrik; Begam, Nafisa Physical Review Letters, Vol. 126, Issue 13 https://doi.org/10.1103/PhysRevLett.126.138004	journal	April 2021
Universal Aging Features in the Restructuring of Fractal Colloidal Gels Cipelletti, Luca; Manley, S.; Ball, R. C. Physical Review Letters, Vol. 84, Issue 10 https://doi.org/10.1103/PhysRevLett.84.2275	journal	March 2000
X-Ray Intensity Fluctuation Spectroscopy Studies on Phase-Ordering Systems Fluerasu, Andrei; Sutton, Mark; Dufresne, Eric M. Physical Review Letters, Vol. 94, Issue 5 https://doi.org/10.1103/PhysRevLett.94.055501	journal	February 2005
Machine Learning for analysis of speckle dynamics: quantification and outlier detection Konstantinova, Tatiana; Wiegart, Lutz; Rakitin, Maksim Physical Review Research, Vol. 4, Issue 3 https://doi.org/10.1103/PhysRevResearch.4.033228	journal	September 2022
Homodyne and heterodyne X-ray photon correlation spectroscopy: latex particles and elastomers Livet, F.; Bley, F.; Ehrburger-Dolle, F. Journal of Applied Crystallography, Vol. 40, Issue s1 https://doi.org/10.1107/S0021889807003561	journal	February 2007
X-ray intensity fluctuation spectroscopy by heterodyne detection Livet, F.; Bley, F.; Ehrburger-Dolle, F. Journal of Synchrotron Radiation, Vol. 13, Issue 6 https://doi.org/10.1107/S0909049506030044	journal	October 2006
On the use of two-time correlation functions for X-ray photon correlation spectroscopy data analysis Bikondoa, Oier Journal of Applied Crystallography, Vol. 50, Issue 2 https://doi.org/10.1107/S1600576717000577	journal	February 2017
Automated matching of two-time X-ray photon correlation maps from phase-separating proteins with Cahn–Hilliard-type simulations using auto-encoder networks Timmermann, Sonja; Starostin, Vladimir; Girelli, Anita Journal of Applied Crystallography, Vol. 55, Issue 4 https://doi.org/10.1107/S1600576722004435	journal	June 2022
X-ray photon correlation spectroscopy Shpyrko, Oleg G. Journal of Synchrotron Radiation, Vol. 21, Issue 5 https://doi.org/10.1107/S1600577514018232	journal	August 2014
PETRA IV: the ultralow-emittance source project at DESY Schroer, Christian G.; Agapov, Ilya; Brefeld, Werner Journal of Synchrotron Radiation, Vol. 25, Issue 5 https://doi.org/10.1107/S1600577518008858	journal	August 2018
Ultra-small-angle X-ray photon correlation spectroscopy using the Eiger detector Zinn, T.; Homs, A.; Sharpnack, L. Journal of Synchrotron Radiation, Vol. 25, Issue 6 https://doi.org/10.1107/S1600577518013899	journal	October 2018
Characterization and performance evaluation of the XSPA-500k detector using synchrotron radiation Nakaye, Yasukazu; Sakumura, Takuto; Sakuma, Yasutaka Journal of Synchrotron Radiation, Vol. 28, Issue 2 https://doi.org/10.1107/S1600577520016665	journal	February 2021
AXEAP: a software package for X-ray emission data analysis using unsupervised machine learning Hwang, In-Hui; Solovyev, Mikhail A.; Han, Sang-Wook Journal of Synchrotron Radiation, Vol. 29, Issue 5 https://doi.org/10.1107/S1600577522006786	journal	July 2022
Microsecond hydrodynamic interactions in dense colloidal dispersions probed at the European XFEL Dallari, Francesco; Jain, Avni; Sikorski, Marcin IUCrJ, Vol. 8, Issue 5 https://doi.org/10.1107/S2052252521006333	journal	July 2021
BraggNN: fast X-ray Bragg peak analysis using deep learning Liu, Zhengchun; Sharma, Hemant; Park, Jun-Sang IUCrJ, Vol. 9, Issue 1 https://doi.org/10.1107/S2052252521011258	journal	December 2021
A Survey on Semi-, Self- and Unsupervised Learning for Image Classification Schmarje, Lars; Santarossa, Monty; Schroder, Simon-Martin IEEE Access, Vol. 9 https://doi.org/10.1109/ACCESS.2021.3084358	journal	January 2021
Fully convolutional networks for semantic segmentation Long, Jonathan; Shelhamer, Evan; Darrell, Trevor 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) https://doi.org/10.1109/CVPR.2015.7298965	conference	June 2015
Latent Space Sparse Subspace Clustering Patel, Vishal M.; Nguyen, Hien Van; Vidal, Rene 2013 IEEE International Conference on Computer Vision https://doi.org/10.1109/ICCV.2013.35	conference	December 2013
Medical Image Denoising Using Convolutional Denoising Autoencoders Gondara, Lovedeep 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW) https://doi.org/10.1109/ICDMW.2016.0041	conference	December 2016
Artificial intelligence applications in the development of autonomous vehicles: a survey Ma, Yifang; Wang, Zhenyu; Yang, Hong IEEE/CAA Journal of Automatica Sinica, Vol. 7, Issue 2 https://doi.org/10.1109/JAS.2020.1003021	journal	March 2020
Deep Convolutional AutoEncoder-based Lossy Image Compression Cheng, Zhengxue; Sun, Heming; Takeuchi, Masaru 2018 Picture Coding Symposium (PCS) https://doi.org/10.1109/PCS.2018.8456308	conference	June 2018
Deep Feature Learning for Medical Image Analysis with Convolutional Autoencoder Neural Network Chen, Min; Shi, Xiaobo; Zhang, Yin IEEE Transactions on Big Data, Vol. 7, Issue 4 https://doi.org/10.1109/TBDATA.2017.2717439	journal	October 2021
Dynamic light scattering Goldburg, W. I. American Journal of Physics, Vol. 67, Issue 12 https://doi.org/10.1119/1.19101	journal	December 1999
Microscopic pathways for stress relaxation in repulsive colloidal glasses Dallari, F.; Martinelli, A.; Caporaletti, F. Science Advances, Vol. 6, Issue 12 https://doi.org/10.1126/sciadv.aaz2982	journal	March 2020
Dynamics of Colloidal Glasses and Gels Joshi, Yogesh M. Annual Review of Chemical and Biomolecular Engineering, Vol. 5, Issue 1 https://doi.org/10.1146/annurev-chembioeng-060713-040230	journal	June 2014
Length scale dependence of dynamical heterogeneity in a colloidal fractal gel Duri, A.; Cipelletti, L. Europhysics Letters (EPL), Vol. 76, Issue 5 https://doi.org/10.1209/epl/i2006-10357-4	journal	December 2006
TomoGAN: low-dose synchrotron x-ray tomography with generative adversarial networks: discussion Liu, Zhengchun; Bicer, Tekin; Kettimuthu, Rajkumar Journal of the Optical Society of America A, Vol. 37, Issue 3 https://doi.org/10.1364/JOSAA.375595	journal	January 2020
Learning Deep Latent Space for Multi-Label Classification Yeh, Chih-Kuan; Wu, Wei-Chieh; Ko, Wei-Jen Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 31, Issue 1 https://doi.org/10.1609/aaai.v31i1.10769	journal	February 2017
UMAP: Uniform Manifold Approximation and Projection McInnes, Leland; Healy, John; Saul, Nathaniel Journal of Open Source Software, Vol. 3, Issue 29 https://doi.org/10.21105/joss.00861	journal	September 2018
How to Use t-SNE Effectively Wattenberg, Martin; Viégas, Fernanda; Johnson, Ian Distill, Vol. 1, Issue 10 https://doi.org/10.23915/distill.00002	journal	October 2016
Deconvolution and Checkerboard Artifacts Odena, Augustus; Dumoulin, Vincent; Olah, Chris Distill, Vol. 1, Issue 10 https://doi.org/10.23915/distill.00003	journal	October 2016
Is the deconvolution layer the same as a convolutional layer? Shi, Wenzhe; Caballero, Jose; Theis, Lucas arXiv https://doi.org/10.48550/arXiv.1609.07009	preprint	January 2016
Understanding disentangling in β-VAE Burgess, Christopher P.; Higgins, Irina; Pal, Arka https://doi.org/10.48550/arXiv.1804.03599	preprint	April 2018
jhorwath/XPCS_Clustering: Updated Analysis and Additional Clustering Evaluation Horwath, J. https://doi.org/10.5281/zenodo.10022423	journal	October 2023
Raw data for analysis in AI-NERD: Elucidation of Relaxation Dynamics Beyond Equilibrium Through AI-informed X-ray Photon Correlation Spectroscopy Horwath, James; Lin, Xiao-Min; He, Hongrui Zenodo https://doi.org/10.5281/zenodo.10059000	dataset	January 2023
scikit-image: image processing in Python van der Walt, Stéfan; Schönberger, Johannes L.; Nunez-Iglesias, Juan PeerJ, Vol. 2 https://doi.org/10.7717/peerj.453	journal	January 2014

Similar Records

CONTIN XPCS: software for inverse transform analysis of X-ray photon correlation spectroscopy dynamics

Journal Article · 2018 · Journal of Applied Crystallography (Online) · OSTI ID:1429091

Andrews, Ross N.; Narayanan, Suresh; Zhang, Fan; +2 more

Robotic pendant drop: containerless liquid for μs-resolved, AI-executable XPCS

Journal Article · 2023 · Light, Science & Applications · OSTI ID:1995837

Ozgulbas, Doga Yamac; Jensen, Jr., Don; Butler, Rory; +10 more

Computational approaches to model X-ray photon correlation spectroscopy from molecular dynamics

Journal Article · 2022 · Modelling and Simulation in Materials Science and Engineering · OSTI ID:1988773

Mohanty, Shaswat; Cooper, Christopher B.; Wang, Hui; +2 more

Related Subjects

36 MATERIALS SCIENCE

Title: AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy

Citation Formats

References (79)

Similar Records

Related Subjects