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We applied denoising and normalization to regions of interest and estimated relative R<jats:sub>2<\/jats:sub> for each relevant nanoparticle array or nanocluster array. We determined significance using an unpaired two\u2010tailed <jats:italic>t<\/jats:italic>\u2010test or one\u2010way analysis of variance and performed curve fitting.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We measured a density\u2010dependent T<jats:sub>2<\/jats:sub> effect (<jats:italic>p<\/jats:italic>\u2009=\u20098.9976\u2009\u00d7\u200910<jats:sup>\u221220<\/jats:sup>, one\u2010way analysis of variance) and insignificant effect of cluster anisotropy (<jats:italic>p<\/jats:italic>\u2009=\u20090.5924, unpaired <jats:italic>t<\/jats:italic>\u2010test) on T<jats:sub>2<\/jats:sub> relaxation. We found negative quadratic relationships (\u22120.0045[log \u03c4<jats:sub>D<\/jats:sub>]<jats:sup>2<\/jats:sup>\u20130.0655[log \u03c4<jats:sub>D<\/jats:sub>]\u22122.7800) for single nanoparticles of varying sizes and for clusters (\u22120.0045[log \u03c4<jats:sub>D<\/jats:sub>]<jats:sup>2<\/jats:sup>\u20130.0827[log \u03c4<jats:sub>D<\/jats:sub>]\u22122.3249) for diffusional correlation time <jats:italic>\u03c4<\/jats:italic><jats:sub><jats:italic>D<\/jats:italic><\/jats:sub>\u2009=\u2009<jats:italic>r<\/jats:italic><jats:sub><jats:italic>p<\/jats:italic><\/jats:sub><jats:sup><jats:italic>2<\/jats:italic><\/jats:sup>\/<jats:italic>D<\/jats:italic>. Clusters show positive quadratic relationships for large (3.8615\u2009\u00d7\u200910<jats:sup>\u22126<\/jats:sup> [<jats:italic>d<\/jats:italic><jats:sub><jats:italic>pp<\/jats:italic><\/jats:sub>\/<jats:italic>r<\/jats:italic><jats:sub><jats:italic>p<\/jats:italic><\/jats:sub>]<jats:sup>2<\/jats:sup>\u20139.3853\u2009\u00d7\u200910<jats:sup>\u22125<\/jats:sup> [<jats:italic>d<\/jats:italic><jats:sub><jats:italic>pp<\/jats:italic><\/jats:sub>\/<jats:italic>r<\/jats:italic><jats:sub><jats:italic>p<\/jats:italic><\/jats:sub>]\u22122.0393) and exponential relationships for small (\u22122.0050[<jats:italic>d<\/jats:italic><jats:sub><jats:italic>pp<\/jats:italic><\/jats:sub>\/<jats:italic>r<\/jats:italic><jats:sub><jats:italic>p<\/jats:italic><\/jats:sub>]<jats:sup>0.0010<\/jats:sup>) clusters. Calculated R<jats:sub>2<\/jats:sub> peak values also align well with in silico predictions (7.85\u2009\u00d7\u200910<jats:sup>\u22124<\/jats:sup>\u2009ms compared with 1.47\u2009\u00d7\u200910<jats:sup>\u22124<\/jats:sup>, 4.23\u2009\u00d7\u200910<jats:sup>\u22124<\/jats:sup>, and 5.02\u2009\u00d7\u200910<jats:sup>\u22124<\/jats:sup>\u2009ms for single iron oxide nanoparticles, 7.88\u2009\u00d7\u200910<jats:sup>\u22124<\/jats:sup>\u2009ms compared with 5.24\u2009\u00d7\u200910<jats:sup>\u22124<\/jats:sup>\u2009ms for nanoparticle clusters).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Our verification affirms longstanding in silico predictions and demonstrates aggregation\u2010dependent behavior in agreement with previous Monte Carlo simulation studies.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mrm.29898","type":"journal-article","created":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T08:04:17Z","timestamp":1698048257000},"page":"687-698","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Direct observation of NMR transverse relaxation in nanopatterned clusters of iron oxide particles"],"prefix":"10.1002","volume":"91","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4481-7843","authenticated-orcid":false,"given":"Ilhan","family":"Bok","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering University of Wisconsin\u2013Madison  Madison Wisconsin USA"},{"name":"Department of Electrical and Computer Engineering University of Wisconsin\u00a0\u2013\u00a0Madison  Madison Wisconsin USA"},{"name":"Wisconsin Institute for Translational Neuroengineering (WITNe)  Madison Wisconsin 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