Development of an insilico model of eccrine sweat using molecular modelling techniques.

Eccrine sweat is an ideal surrogate diagnostic biofluid for physiological and metabolic biomarkers for wearable biosensor design. Its periodic and non-invasive availability for candidate analytes such as glucose and cortisol along with limited correlation with blood plasma is of significant research interest. An insilico model of eccrine sweat can assist in the development of such wearable biosensors. In this regard, molecular modelling can be employed to observe the most fundamental interactions. Here, we determine a suitable molecular model for building eccrine sweat. The basic components of sweat are water and sodium chloride, in which glucose and other analytes are present in trace quantities. Given the wide range of water models available in the molecular dynamics space, in this study, we first validate the water models. We use three compounds to represent the base to build bulk sweat fluid and validate the force fields. We compare the self-diffusivity of water, glucose, sodium, and chloride ions as well as bulk viscosity values and present the results which are > 90% accurate as compared with the available literature. This validated insilico eccrine sweat model can serve as an aid to expedite the development de novo biosensors by addition of other analytes of interest e.g. cortisol, uric acid etc., simulate various temperatures and salt concentrations, expand search space for screening candidate target receptors by their binding affinity and assess the interference between competing species via simulations.

Eccrine Sweat Molecular Model for Development of de novo Biosensors.

In this paper, we present a validated, novel, in silico molecular dynamics (MD) model of eccrine sweat with approx. 35k atoms developed using Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) program. CHARMMS36m force field for constituent atoms and SPC/E water model are used to develop this model. The model outputs transport properties such as self-diffusivity computed using mean squared displacement and bulk viscosity computed via Green-Kubo correlations, which are compared with existing literature values and experimental studies and presented. This validated model is intended to serve as a tool to develop eccrine sweat based biosensors.

Effect of temperature on concentrated electrolytes for advanced lithium ion batteries.

Salt-concentrated electrolytes are emerging as promising electrolytes for advanced lithium ion batteries (LIBs) that can offer high energy density and improved cycle life. To further improve these electrolytes, it is essential to understand their inherent behavior at various operating conditions of LIBs. Molecular dynamics (MD) simulations are extensively used to study various properties of electrolytes and explain the associated molecular-level phenomena. In this study, we use classical MD simulations to probe the properties of the concentrated electrolyte solution of 3 mol/kg lithium hexafluorophosphate (LiPF6) salt in the propylene carbonate solvent at various temperatures ranging from 298 to 378 K. Our results reveal that the properties such as ionic diffusivity and molar conductivity of a concentrated electrolyte are more sensitive to temperature compared to that of dilute electrolytes. The residence time analysis shows that temperature affects the Li+ ion solvation shell dynamics significantly. The effect of temperature on the transport and dynamic properties needs to be accounted carefully while designing better thermal management systems for batteries made with concentrated electrolytes to garner the advantages of these electrolytes.