Improving Perovskite Solar Cells: Insights From a Validated Device Model

To improve the efficiency of existing perovskite solar cells (PSCs), a detailed understanding of the underlying device physics during their operation is essential. Here, a device model has been developed and validated that describes the operation of PSCs and quantitatively explains the role of contacts, the electron and hole transport layers, charge generation, drift and diffusion of charge carriers and recombination. The simulation to the experimental data of vacuum‐deposited CH₃NH₃PbI₃ solar cells over multiple thicknesses has been fit and the device behavior under different operating conditions has been studied to delineate the influence of the external bias, charge‐carrier mobilities, energetic barriers for charge injection/extraction and, different recombination channels on the solar cell performance. By doing so, a unique set of material parameters and physical processes that describe these solar cells is identified. Trap‐assisted recombination at material interfaces is the dominant recombination channel limiting device performance and passivation of traps increases the power conversion efficiency (PCE) of these devices by 40%. Finally, guidelines to increase their performance have been issued and it is shown that a PCE beyond 25% is within reach.     

Radiofrequency interaction with conductive colloids: Permittivity and electrical conductivity of single‐wall carbon nanotubes in saline

Conductive nanoparticles may enhance tissue heating during radiofrequency (RF) irradiation. Specific absorption rate (SAR) is known to rise with the electrical conductivity of tissue. However, no studies to date have measured the relationship between complex permittivity and nanoparticle concentration in tissue‐like samples. The complex permittivities of colloids containing single‐wall carbon nanotubes (SWCNTs) in normal (0.9%) saline were measured from 20 MHz to 1 GHz. Carbon concentrations ranged from 0 to 93 mM (0.06% volume), based on SWCNT weight per volume. Measurements were made with 0.02% Pluronic F108 surfactant added to the colloids to prevent SWCNT flocculation. The data were fit to the Cole–Cole relaxation model with an added constant phase angle element to correct for electrode polarization effects at low RF frequencies. Electrode polarization effects increased with carbon concentration. The real parts of the permittivities of the colloids increased with carbon concentration. The static conductivity rose linearly with carbon concentration, doubling from 0 to 93 mM. The SAR of the colloids is expected to increase with RF frequency, based on the properties of the imaginary part of the permittivity. Bioelectromagnetics 31:582–588, 2010. © 2010 Wiley‐Liss, Inc.     

Evaluation of genetic diversity and population structure of west‐central Indian cattle breeds

Evaluations of genetic diversity in domestic livestock populations are necessary to implement region‐specific conservation measures. We determined the genetic diversity and evolutionary relationships among eight geographically and phenotypically diverse cattle breeds indigenous to west‐central India by genotyping these animals for 22 microsatellite loci. A total of 326 alleles were detected, and the expected heterozygosity ranged from 0.614 (Kenkatha) to 0.701 (Dangi). The mean number of alleles among the cattle breeds ranged from 7.182 (Khillar) to 9.409 (Gaolao). There were abundant genetic variations displayed within breeds, and the genetic differentiation was also high between the Indian cattle breeds, which displayed 15.9% of the total genetic differentiation among the different breeds. The genetic differentiation (pairwise F_ST) among the eight Indian breeds varied from 0.0126 for the Kankrej–Malvi pair to 0.2667 for Khillar–Kenkatha pair. The phylogeny, principal components analysis, and structure analysis further supported close grouping of Kankrej, Malvi, Nimari and Gir; Gaolao and Kenkatha, whereas Dangi and Khillar remained at distance from other breeds.     

Explicit Separation of Growth and Motility in a New Tumor Cord Model

We investigate a new model of tumor growth in which cell motility is considered an explicitly separate process from growth. Bulk tumor expansion is modeled by individual cell motility in a density-dependent diffusion process. This model is implemented in the context of an in vivo system, the tumor cord. We investigate numerically microscale density distributions of different cell classes and macroscale whole tumor growth rates as functions of the strength of transitions between classes. Our results indicate that the total tumor growth follows a classical von Bertalanffy growth profile, as many in vivo tumors are observed to do. This provides a quick validation for the model hypotheses. The microscale and macroscale properties are both sensitive to fluctuations in the transition parameters, and grossly adopt one of two phenotypic profiles based on their parameter regime. We analyze these profiles and use the observations to classify parameter regimes by their phenotypes. This classification yields a novel hypothesis for the early evolutionary selection of the metastatic phenotype by selecting against less motile cells which grow to higher densities and may therefore induce local collapse of the vascular network.