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 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.

Automated summary

Chemical micro-heterogeneity is a common attribute of living systems and materials and can be evaluated quantitatively using time-evolving signals and the Maximum Entropy Method. The estimation of Fuzzy Entropy based on the pre-exponential terms of poly-exponential fitting can be extended to various types of data, promoting the development of Chemical Artificial Intelligence.