Extracting film thickness and optical constants from spectrophotometric data by evolutionary optimization.

In this paper, we propose a simple and elegant method to extract the thickness and the optical constants of various films from the reflectance and transmittance spectra in the wavelength range of 350 - 1000 nm. The underlying inverse problem is posed here as an optimization problem. To find unique solutions to this problem, we adopt an evolutionary optimization approach that drives a population of candidate solutions towards the global optimum. An ensemble of Tauc-Lorentz Oscillators (TLOs) and an ensemble of Gaussian Oscillators (GOs), are leveraged to compute the reflectance and transmittance spectra for different candidate thickness values and refractive index profiles. This model-based optimization is solved using two efficient evolutionary algorithms (EAs), namely genetic algorithm (GA) and covariance matrix adaptation evolution strategy (CMAES), such that the resulting spectra simultaneously fit all the given data points in the admissible wavelength range. Numerical results validate the effectiveness of the proposed approach in estimating the optical parameters of interest.

Comparing data driven and physics inspired models for hopping transport in organic field effect transistors.

The past few decades have seen an uptick in the scope and range of device applications of organic semiconductors, such as organic field-effect transistors, organic photovoltaics and light-emitting diodes. Several researchers have studied electrical transport in these materials and proposed physical models to describe charge transport with different material parameters, with most disordered semiconductors exhibiting hopping transport. However, there exists a lack of a consensus among the different models to describe hopping transport accurately and uniformly. In this work, we first evaluate the efficacy of using a purely data-driven approach, i.e., symbolic regression, in unravelling the relationship between the measured field-effect mobility and the controllable inputs of temperature and gate voltage. While the regressor is able to capture the scaled mobility well with mean absolute error (MAE) ~ O(10-2), better than the traditionally used hopping transport model, it is unable to derive physically interpretable input-output relationships. We then examine a physics-inspired renormalization approach to describe the scaled mobility with respect to a scale-invariant reference temperature. We observe that the renormalization approach offers more generality and interpretability with a MAE of the ~ O(10-1), still better than the traditionally used hopping model, but less accurate as compared to the symbolic regression approach. Our work shows that physics-based approaches are powerful compared to purely data-driven modelling, providing an intuitive understanding of data with extrapolative ability.

Scrambling of disulfide bond scaffolds in neurotoxin AuIB: A molecular dynamics simulation study.

AuIB, a neurotoxic conopeptide, is a "selective antagonist" of the α3-ß4 subtype of the nicotinic acetylcholine receptors in human brain and is investigated extensively for its immense potency in the treatment of pain. It contains two disulfide linkages, which are decisive in maintaining its structure and functional selectivity. Here we report, a molecular dynamics simulation study of the role of disulfide bonds on the secondary structure of AuIB in water. The native form of AuIB (N) is found to be significantly stable in water with very robust 310 and α-helical domains, featuring ∼47% of the total structure. The partially reduced AuIB (P2-8 ), with the disulfide bond between cysteine 2, 8 broken, shows significantly perturbed secondary structural features with almost total loss in helicity. Breaking of the disulfide bond between cysteine 3, 15 (P3-15 ), on the other hand, has almost no effect on the helical region of the peptide, although the weightage of ß-turn increased at the cost of random coil. Intriguingly, when both the disulfide bonds are broken (D), the helical region is affected, but the loss in helicity is less than that observed in the P2-8 case. To understand the disulfide scrambling process, the relative probabilities of forming three disulfide-bond isoforms of AuIB in water are estimated from the sulfur-sulfur (SS) distance distributions of the four cysteine residues present in AuIB (D). Simulations show that the native globular form dominates ∼73% of the isoform population, with the beads form being the second most populated one. © 2015 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 106: 196-209, 2016.