{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T19:32:54Z","timestamp":1784748774771,"version":"3.55.0"},"reference-count":34,"publisher":"National Academy of Sciences","issue":"51","license":[{"start":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T00:00:00Z","timestamp":1766102400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/100014013","name":"UK Research and Innovation","doi-asserted-by":"publisher","award":["EP\/X02394X\/1"],"award-info":[{"award-number":["EP\/X02394X\/1"]}],"id":[{"id":"10.13039\/100014013","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000006","name":"DOD | USN | Office of Naval Research","doi-asserted-by":"publisher","award":["N00014-23-1-2797"],"award-info":[{"award-number":["N00014-23-1-2797"]}],"id":[{"id":"10.13039\/100000006","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.pnas.org"],"crossmark-restriction":true},"short-container-title":["Proc. Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2025,12,23]]},"abstract":"<jats:p>Capturing high-rate spatiotemporal deformation of materials in three dimensions (3D) remains a significant challenge with current X-ray imaging techniques. We present a methodology that combines advances in neural rendering techniques with volume correlation methods to accurately reconstruct complex, high-rate 3D spatiotemporal structural evolutions. The fidelity and versatility of the method, which requires no pretraining, are demonstrated for a diverse set of intricate 3D-printed microarchitected solids. Using laboratory-based X-ray tomography, we capture the 3D growth of a high-rate crush band on a timescale of less than 100 ms. By broadening this idea to a stereo X-ray concept, we eliminate the need to rotate the image object, thereby extending the technique to significantly faster timescales. Our neural rendering framework opens possibilities for 3D observations of viscoelastic responses of biological materials to 3D investigations of numerous poorly understood dynamic processes, such as the runaway failure of batteries, all using laboratory X-ray systems.<\/jats:p>","DOI":"10.1073\/pnas.2521089122","type":"journal-article","created":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T17:27:48Z","timestamp":1766165268000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":3,"title":["High-speed X-ray tomography for 4D imaging"],"prefix":"10.1073","volume":"122","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0163-7009","authenticated-orcid":false,"given":"Ivan","family":"Grega","sequence":"first","affiliation":[{"name":"Department of Engineering, University of Cambridge","place":["Cambridge, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William","family":"Whitney","sequence":"additional","affiliation":[{"name":"Google DeepMind","place":["San Francisco"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3899-3573","authenticated-orcid":false,"given":"Vikram Sudhir","family":"Deshpande","sequence":"additional","affiliation":[{"name":"Department of Engineering, University of Cambridge","place":["Cambridge, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2025,12,19]]},"reference":[{"key":"e_1_3_4_1_2","doi-asserted-by":"publisher","DOI":"10.1098\/rsif.2013.0304"},{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1039\/C6CP04251A"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms7924"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-019-11521-1"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1038\/s43586-021-00015-4"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.1071\/PH560198"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/51\/13\/R03"},{"key":"e_1_3_4_8_2","first-page":"2495","article-title":"Micro-architectured materials: Past, present and future","volume":"466","author":"Fleck N. A.","year":"2010","unstructured":"N. A. Fleck, V. S. Deshpande, M. F. Ashby, Micro-architectured materials: Past, present and future. Proc. R. Soc. Lond. A Math. Phys. Eng. Sci. 466, 2495\u20132516 (2010).","journal-title":"Proc. R. Soc. Lond. A Math. Phys. Eng. Sci."},{"key":"e_1_3_4_9_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41563-021-01182-1"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11340-014-9871-5"},{"key":"e_1_3_4_11_2","first-page":"99","volume-title":"Optics, photonics and digital technologies for imaging applications IV","author":"Taillandier-Thomas T.","year":"2016","unstructured":"T. Taillandier-Thomas, C. Jailin, S. Roux, F. Hild, \u201cMeasurement of 3D displacement fields from few tomographic projections\u201d in Optics, photonics and digital technologies for imaging applications IV, (SPIE, 2016), vol. 9896, pp. 99\u2013110."},{"key":"e_1_3_4_12_2","doi-asserted-by":"publisher","DOI":"10.1115\/1.4064050"},{"key":"e_1_3_4_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.flowmeasinst.2007.09.003"},{"key":"e_1_3_4_14_2","unstructured":"A. Seeger K. Affeld U. Kertzscher L. Goubergrits E. Wellnhofer \u201cAssessment of flow structures in bubble columns by X-ray based particle tracking velocimetry\u201d in International Symposium on Particle Image Velocimetry Gottingen Germany (2001)."},{"key":"e_1_3_4_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/3503250"},{"key":"e_1_3_4_16_2","first-page":"10318","author":"Pumarola A.","year":"2021","unstructured":"A. Pumarola, E. Corona, G. Pons-Moll, F. Moreno-Noguer, \u201cD-nerf: Neural radiance fields for dynamic scenes\u201d in Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (2021), pp. 10318\u201310327.","journal-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition"},{"key":"e_1_3_4_17_2","first-page":"5865","author":"Park K.","year":"2021","unstructured":"K. Park , \u201cNerfies: Deformable neural radiance fields\u201d in Proceedings of The IEEE\/CVF International Conference on Computer Vision (2021), pp. 5865\u20135874.","journal-title":"Proceedings of The IEEE\/CVF International Conference on Computer Vision"},{"key":"e_1_3_4_18_2","doi-asserted-by":"crossref","unstructured":"J. T. Barron B. Mildenhall D. Verbin P. P. Srinivasan P. Hedman \u201cMip-nerf 360: Unbounded anti-aliased neural radiance fields\u201d in Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2022) pp. 5470\u20135479.","DOI":"10.1109\/CVPR52688.2022.00539"},{"key":"e_1_3_4_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/3528223.3530127"},{"key":"e_1_3_4_20_2","doi-asserted-by":"publisher","DOI":"10.1021\/acsami.3c06291"},{"key":"e_1_3_4_21_2","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/ad1d6c"},{"key":"e_1_3_4_22_2","first-page":"3843","volume-title":"2022 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","author":"Corona-Figueroa A.","year":"2022","unstructured":"A. Corona-Figueroa , \u201cMednerf: Medical neural radiance fields for reconstructing 3D-aware CT-projections from a single X-ray\u201d in 2022 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), (IEEE, 2022), pp. 3843\u20133848."},{"key":"e_1_3_4_23_2","first-page":"1","volume-title":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","author":"Hu J.","year":"2024","unstructured":"J. Hu , \u201cUMedNeRF: Uncertainty-aware single view volumetric rendering for medical neural radiance fields\u201d in 2024 IEEE International Symposium on Biomedical Imaging (ISBI) (IEEE, 2024), pp. 1\u20134."},{"key":"e_1_3_4_24_2","unstructured":"I. Grega W. F. Whitney V. S. Deshpande Neural rendering enables dynamic tomography (2024) https:\/\/doi.org\/10.48550\/arXiv.2410.20558."},{"key":"e_1_3_4_25_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11340-018-0390-7"},{"key":"e_1_3_4_26_2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2404205121"},{"key":"e_1_3_4_27_2","doi-asserted-by":"publisher","DOI":"10.1109\/42.796284"},{"key":"e_1_3_4_28_2","doi-asserted-by":"publisher","DOI":"10.1007\/s40799-021-00508-7"},{"key":"e_1_3_4_29_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0022-5096(01)00010-2"},{"key":"e_1_3_4_30_2","volume-title":"Metal Foams: A Design Guide","author":"Ashby M. F.","year":"2000","unstructured":"M. F. Ashby , Metal Foams: A Design Guide (Butterworth Heinemann, Stoneham, MA, 2000)."},{"key":"e_1_3_4_31_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.matchar.2015.07.012"},{"key":"e_1_3_4_32_2","first-page":"S4","article-title":"Dynamic CT imaging in the laboratory: Characterization of pore filling events in geological materials","volume":"29","author":"De Boever W.","year":"2021","unstructured":"W. De Boever , Dynamic CT imaging in the laboratory: Characterization of pore filling events in geological materials. Microsc. Microanal. 29, S4\u2013S6. (2021)","journal-title":"Microsc. Microanal."},{"key":"e_1_3_4_33_2","doi-asserted-by":"publisher","DOI":"10.1093\/micmic\/ozad067.1071"},{"key":"e_1_3_4_34_2","unstructured":"I. Grega neural_xray. GitHub. https:\/\/github.com\/igrega348\/neural_xray. Deposited 4 December 2025."}],"container-title":["Proceedings of the National Academy of Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pnas.org\/doi\/pdf\/10.1073\/pnas.2521089122","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/pnas.org\/doi\/pdf\/10.1073\/pnas.2521089122","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T17:27:54Z","timestamp":1766165274000},"score":1,"resource":{"primary":{"URL":"https:\/\/pnas.org\/doi\/10.1073\/pnas.2521089122"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,19]]},"references-count":34,"journal-issue":{"issue":"51","published-print":{"date-parts":[[2025,12,23]]}},"alternative-id":["10.1073\/pnas.2521089122"],"URL":"https:\/\/doi.org\/10.1073\/pnas.2521089122","relation":{},"ISSN":["0027-8424","1091-6490"],"issn-type":[{"value":"0027-8424","type":"print"},{"value":"1091-6490","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,19]]},"assertion":[{"value":"2025-08-03","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-11-12","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-12-19","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e2521089122"}}