Anion and Temperature Responsive Molecular Switches Based on Trimetallic Complexes of Ru(II) and Os(II) That Demonstrate Advanced Boolean and Fuzzy Logic Functions

Abstract

Anion- and temperature-induced alteration of the photoredox behaviors of our recently reported trimetallic complexes was carried out to fabricate potential molecular switches. The triads [(phen)2Ru­(d-HIm-t)­M­(t-HIm-d)­Ru­(phen)2]6+ (phen = 1,10-phenanthroline, d-HIm-t = heterotopic bipyridine–terpyridne type bridging ligand, and M = RuII and OsII) possess two acidic imidazole NH protons that upon interaction with anions give rise to considerable changes in their photophysical and electrochemical behaviors. Red-shifts of the absorption and emission maximum and a decrease in the M3+/M2+ potential occur when the triads are treated with basic anions. In fact, the triads can function as triple-channel sensors for F–, AcO–, CN–, OH–, and H2PO4 – in acetonitrile and as selective probes for CN– and SCN– in water. The equilibrium constants for the receptor–anion interaction are on the order of 106 M–1, while the limit of detection was on the order of 10–9 M. Temperature plays a key role in the luminescence properties of the triads by adjusting the energy barrier between the emitting triplet metal-to-ligand charge transfer and non-emitting triplet metal-centered levels. A decrease in temperature leads to increases in the emission intensity and lifetime of the triads displaying the “on state”, whereas an increase in temperature leads to a decrease in their emission characteristics and thus indicates the “off state” and that the process is fully reversible. In essence, the triads could function as potential switches on the basis of the reversible change in their spectral and redox behaviors under the influence of anion, acid, and temperature. The most important outcome of this study is mimicking several advanced Boolean and fuzzy logic functions by utilizing the spectral response of the triads upon the action of said external stimuli.

Neural network and decision tree-based machine learning tools to analyse the anion-responsive behaviours of emissive Ru(ii)–terpyridine complexes

“…In the following section, we will use their spectral, electrochemical and spectroelectrochemical outputs upon the action of anions to mimic the roles of YES-NOT and set-reset flip-flop logic gates. [17][18][19][20][21][22][23][24][25][26][27][28][29][30] We will also apply machine learning tools, such as ANNs, ANFIS, and Decision tree (DT) regression to analyze the experimental data and also to predict many intermediate states. Thus, we can reduce the time and expenditures associated with the execution of comprehensive sensing experiments.…”

Fluorescent Probes as a Tool in Diagnostic and Drug Delivery Systems

“…The recent progress in this field has resulted in a large number of different architectures. Among them, fluorescent probes have been the subject of major research interest [ 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 ]. Mainly, their attractiveness lies in their fluorescence signaling output, which provides a rapid response time, high efficiency and sensitivity, great spatial resolution, and cheap and affordable equipment suitable for field analysis.…”

Human brain-inspired chemical artificial intelligence tools for the analysis and prediction of the anion-sensing characteristics of an imidazole-based luminescent Os(ii)-bipyridine complex

“…[46][47][48][49][50][51][52][53] The action of Boolean logic depends on the extending of the outputs among the two ends, either "0" or "1". [54][55][56][57][58][59][60][61][62] But the practical systems are mostly consisting of numerous intermediate situations. Hence, we employed various soft computing tools such as fuzzy logic, artificial neural network, and adaptive neuro-fuzzy inference system as well as decision treebased regression analysis for a complete understanding of the anion-sensing behavior of the complex.…”