The electrochemical impedance spectra (EIS) of tethered bilayer membranes (tBLMs) were analyzed, and the analytical solution for the spectral response of membranes containing natural or artificially introduced defects was derived. The analysis carried out in this work shows that the EIS features of an individual membrane defect cannot be modeled by conventional electrical elements. The primary reason for this is the complex nature of impedance of the submembrane ionic reservoir separating the phospholipid layer and the solid support. We demonstrate that its EIS response, in the case of radially symmetric defects, is described by the Hankel functions of a complex variable. Therefore, neither the impedance of the submembrane reservoir nor the total impedance of tBLMs can be modeled using the conventional elements of the equivalent electrical circuits of interfaces. There are, however, some limiting cases in which the complexity of the EIS response of the submembrane space reduces. In the high frequency limit, the EIS response of a submembrane space that surrounds the defect transforms into a response of a constant phase element (CPE) with the exponent (α) value of 0.5. The onset of this transformation is, beside other parameters, dependent on the defect size. Large-sized defects push the frequency limit lower, therefore, the EIS spectra exhibiting CPE behavior with α ≈ 0.5, can serve as a diagnostic criterion for the presence of such defects. In the low frequency limit, the response is dependent on the density of the defects, and it transforms into the capacitive impedance if the area occupied by a defect is finite. The higher the defect density, the higher the frequency edge at which the onset of the capacitive behavior is observed. Consequently, the presented analysis provides practical tools to evaluate the defect density in tBLMs, which could be utilized in tBLM-based biosensor applications. Alternatively, if the parameters of the defects, e.g., ion channels, such as the diameter and the conductance are known, the EIS data analysis provides a possibility to estimate other physical parameters of the system, such as thickness of the submembrane reservoir and its conductance. Finally, current analysis demonstrates a possibility to discriminate between the situations, in which the membrane defects are evenly distributed or clustered on the surface of tBLMs. Such sensitivity of EIS could be used for elucidation of the mechanisms of interaction between the proteins and the membranes.
A stochastic method of optimization of a white-light source that relies on additive color mixing of the emissions from colored light-emitting diodes (LEDs) was developed. The method allows for finding the optimal wavelengths of LEDs in order to obtain the best possible trade off between luminous efficacy and the general color rendering index (CRI) of the white source for an arbitrary number of primary LEDs. Optimal solid-state lamps composed of two, three, four, and five different LEDs were analyzed. We show that a dichromatic LED lamp can only provide high efficacy with a general CRI close to zero, whereas trichromatic and quadrichromatic lamps are able to cover the entire range of reasonable general CRI values. The optimization of quintichromatic LED lamps and lamps with a higher number of primary color LEDs yields a negligible benefit in improving CRI but provides for quasicontinuous spectra that might be required for special lighting needs.
A mathematical model of amperometric biosensors has been developed. The model is based on non-stationary diffusion equations containing a non-linear term related to Michaelis-Menten kinetics of the enzymatic reaction. Using digital simulation, the influence of the thickness of enzyme membrane on the biosensor response was investigated. The digital simulation of the biosensor operation showed the non-monotonous change of the maximal biosensor current versus the membrane thickness at the various maximal enzymatic rates. Digital simulation was carried out using the finite difference technique. Results of the numerical simulation was compared with known analytical solutions. This paper presents a framework for selection of the membrane thickness, ensuring the sufficiently stable sensitivity of a biosensor in a required range of the maximal enzymatic rate.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.