Quantitative estimation of chemical microheterogeneity through the determination of fuzzy entropy
Chemical micro-heterogeneity is an attribute of all living systems and most of the soft and crystalline materials. Its characterization requires a plethora of techniques. This work proposes a strategy for quantifying the degree of chemical micro-heterogeneity. First of all, our approach needs the co...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Chemistry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fchem.2022.950769/full |
| _version_ | 1817995206588366848 |
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| author | Pier Luigi Gentili Juan Perez-Mercader Juan Perez-Mercader |
| author_facet | Pier Luigi Gentili Juan Perez-Mercader Juan Perez-Mercader |
| author_sort | Pier Luigi Gentili |
| collection | DOAJ |
| description | Chemical micro-heterogeneity is an attribute of all living systems and most of the soft and crystalline materials. Its characterization requires a plethora of techniques. This work proposes a strategy for quantifying the degree of chemical micro-heterogeneity. First of all, our approach needs the collection of time-evolving signals that can be fitted through poly-exponential functions. The best fit is determined through the Maximum Entropy Method. The pre-exponential terms of the poly-exponential fitting function are used to estimate Fuzzy Entropy. Related to the possibility of implementing Fuzzy sets through the micro-heterogeneity of chemical systems. Fuzzy Entropy becomes a quantitative estimation of the Fuzzy Information that can be processed through micro-heterogeneous chemical systems. We conclude that our definition of Fuzzy Entropy can be extended to other kinds of data, such as morphological and structural distributions, spectroscopic bands and chromatographic peaks. The chemical implementation of Fuzzy sets and Fuzzy logic will promote the development of Chemical Artificial Intelligence. |
| first_indexed | 2024-04-14T02:03:40Z |
| format | Article |
| id | doaj.art-83fd5eac0d2a4856ad762252cfdc38b2 |
| institution | Directory Open Access Journal |
| issn | 2296-2646 |
| language | English |
| last_indexed | 2024-04-14T02:03:40Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Chemistry |
| spelling | doaj.art-83fd5eac0d2a4856ad762252cfdc38b22022-12-22T02:18:46ZengFrontiers Media S.A.Frontiers in Chemistry2296-26462022-08-011010.3389/fchem.2022.950769950769Quantitative estimation of chemical microheterogeneity through the determination of fuzzy entropyPier Luigi Gentili0Juan Perez-Mercader1Juan Perez-Mercader2Department of Chemistry, Biology, and Biotechnology, Università Degli Studi di Perugia, Perugia, ItalyDepartment of Earth and Planetary Sciences and Origins of Life Initiative, Harvard University, Cambridge, MA, United StatesSanta Fe Institute, Santa Fe, NM, United StatesChemical micro-heterogeneity is an attribute of all living systems and most of the soft and crystalline materials. Its characterization requires a plethora of techniques. This work proposes a strategy for quantifying the degree of chemical micro-heterogeneity. First of all, our approach needs the collection of time-evolving signals that can be fitted through poly-exponential functions. The best fit is determined through the Maximum Entropy Method. The pre-exponential terms of the poly-exponential fitting function are used to estimate Fuzzy Entropy. Related to the possibility of implementing Fuzzy sets through the micro-heterogeneity of chemical systems. Fuzzy Entropy becomes a quantitative estimation of the Fuzzy Information that can be processed through micro-heterogeneous chemical systems. We conclude that our definition of Fuzzy Entropy can be extended to other kinds of data, such as morphological and structural distributions, spectroscopic bands and chromatographic peaks. The chemical implementation of Fuzzy sets and Fuzzy logic will promote the development of Chemical Artificial Intelligence.https://www.frontiersin.org/articles/10.3389/fchem.2022.950769/fullmicro-heterogeneous chemical systemstime-resolved signalsmaximum entropy method (MEM)molecular informationmolecular computingfuzzy sets |
| spellingShingle | Pier Luigi Gentili Juan Perez-Mercader Juan Perez-Mercader Quantitative estimation of chemical microheterogeneity through the determination of fuzzy entropy Frontiers in Chemistry micro-heterogeneous chemical systems time-resolved signals maximum entropy method (MEM) molecular information molecular computing fuzzy sets |
| title | Quantitative estimation of chemical microheterogeneity through the determination of fuzzy entropy |
| title_full | Quantitative estimation of chemical microheterogeneity through the determination of fuzzy entropy |
| title_fullStr | Quantitative estimation of chemical microheterogeneity through the determination of fuzzy entropy |
| title_full_unstemmed | Quantitative estimation of chemical microheterogeneity through the determination of fuzzy entropy |
| title_short | Quantitative estimation of chemical microheterogeneity through the determination of fuzzy entropy |
| title_sort | quantitative estimation of chemical microheterogeneity through the determination of fuzzy entropy |
| topic | micro-heterogeneous chemical systems time-resolved signals maximum entropy method (MEM) molecular information molecular computing fuzzy sets |
| url | https://www.frontiersin.org/articles/10.3389/fchem.2022.950769/full |
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