Determining Chemical Microheterogeneity from the Analysis of Absorption and Luminescence Transient Signals

The characterization of chemical microheterogeneity is compelling due to its relevant role in soft materials, high-entropy materials, and systems chemistry, to cite just a few instances. This work investigates the microheterogeneity of photochromic samples and metal oxide solid solutions by fitting time-resolved absorption and luminesce signals recorded after photoexcitation. The transient spectroscopic signals have been analyzed using polyexponential functions determined through the Maximum Entropy Method (MEM) and discrete exponential, Kohlrausch, and Becquerel functions through the Levenberg-Marquardt algorithm. The outputs of the different fitting functions and algorithms are compared and exploited to characterize chemical microheterogeneity quantitatively. The practical relevance of chemical microheterogeneity is supported by the demonstration that photochromic samples are transformed from binary to multistate systems, capable of encoding much more information, and that microheterogeneous photocatalysts are provided with several structural defects that guarantee the coexistence of many active sites and higher catalytic activity.