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Multiparametric quantification of thermal heterogeneity within aqueous materials by water (1)H NMR spectroscopy: Paradigms and algorithms
Processes involving heat generation and dissipation play an important role in the performance of numerous materials. The behavior of (semi-)aqueous materials such as hydrogels during production and application, but also properties of biological tissue in disease and therapy (e.g., hyperthermia) crit...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5446178/ https://www.ncbi.nlm.nih.gov/pubmed/28552959 http://dx.doi.org/10.1371/journal.pone.0178431 |
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author | Lutz, Norbert W. Bernard, Monique |
author_facet | Lutz, Norbert W. Bernard, Monique |
author_sort | Lutz, Norbert W. |
collection | PubMed |
description | Processes involving heat generation and dissipation play an important role in the performance of numerous materials. The behavior of (semi-)aqueous materials such as hydrogels during production and application, but also properties of biological tissue in disease and therapy (e.g., hyperthermia) critically depend on heat regulation. However, currently available thermometry methods do not provide quantitative parameters characterizing the overall temperature distribution within a volume of soft matter. To this end, we present here a new paradigm enabling accurate, contactless quantification of thermal heterogeneity based on the line shape of a water proton nuclear magnetic resonance ((1)H NMR) spectrum. First, the (1)H NMR resonance from water serving as a "temperature probe" is transformed into a temperature curve. Then, the digital points of this temperature profile are used to construct a histogram by way of specifically developed algorithms. We demonstrate that from this histogram, at least eight quantitative parameters describing the underlying statistical temperature distribution can be computed: weighted median, weighted mean, standard deviation, range, mode(s), kurtosis, skewness, and entropy. All mathematical transformations and calculations are performed using specifically programmed EXCEL spreadsheets. Our new paradigm is helpful in detailed investigations of thermal heterogeneity, including dynamic characteristics of heat exchange at sub-second temporal resolution. |
format | Online Article Text |
id | pubmed-5446178 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-54461782017-06-12 Multiparametric quantification of thermal heterogeneity within aqueous materials by water (1)H NMR spectroscopy: Paradigms and algorithms Lutz, Norbert W. Bernard, Monique PLoS One Research Article Processes involving heat generation and dissipation play an important role in the performance of numerous materials. The behavior of (semi-)aqueous materials such as hydrogels during production and application, but also properties of biological tissue in disease and therapy (e.g., hyperthermia) critically depend on heat regulation. However, currently available thermometry methods do not provide quantitative parameters characterizing the overall temperature distribution within a volume of soft matter. To this end, we present here a new paradigm enabling accurate, contactless quantification of thermal heterogeneity based on the line shape of a water proton nuclear magnetic resonance ((1)H NMR) spectrum. First, the (1)H NMR resonance from water serving as a "temperature probe" is transformed into a temperature curve. Then, the digital points of this temperature profile are used to construct a histogram by way of specifically developed algorithms. We demonstrate that from this histogram, at least eight quantitative parameters describing the underlying statistical temperature distribution can be computed: weighted median, weighted mean, standard deviation, range, mode(s), kurtosis, skewness, and entropy. All mathematical transformations and calculations are performed using specifically programmed EXCEL spreadsheets. Our new paradigm is helpful in detailed investigations of thermal heterogeneity, including dynamic characteristics of heat exchange at sub-second temporal resolution. Public Library of Science 2017-05-26 /pmc/articles/PMC5446178/ /pubmed/28552959 http://dx.doi.org/10.1371/journal.pone.0178431 Text en © 2017 Lutz, Bernard http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lutz, Norbert W. Bernard, Monique Multiparametric quantification of thermal heterogeneity within aqueous materials by water (1)H NMR spectroscopy: Paradigms and algorithms |
title | Multiparametric quantification of thermal heterogeneity within aqueous materials by water (1)H NMR spectroscopy: Paradigms and algorithms |
title_full | Multiparametric quantification of thermal heterogeneity within aqueous materials by water (1)H NMR spectroscopy: Paradigms and algorithms |
title_fullStr | Multiparametric quantification of thermal heterogeneity within aqueous materials by water (1)H NMR spectroscopy: Paradigms and algorithms |
title_full_unstemmed | Multiparametric quantification of thermal heterogeneity within aqueous materials by water (1)H NMR spectroscopy: Paradigms and algorithms |
title_short | Multiparametric quantification of thermal heterogeneity within aqueous materials by water (1)H NMR spectroscopy: Paradigms and algorithms |
title_sort | multiparametric quantification of thermal heterogeneity within aqueous materials by water (1)h nmr spectroscopy: paradigms and algorithms |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5446178/ https://www.ncbi.nlm.nih.gov/pubmed/28552959 http://dx.doi.org/10.1371/journal.pone.0178431 |
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