A theoretical analysis of the current-voltage characteristics of solar cells

Various mechanisms which limit the conversion efficiency of silicon solar cells were studied. The effects of changes in solar cell geometry such as layer thickness on performance were examined. The effects of various antireflecting layers were also examined. It was found that any single film antireflecting layer results in a significant surface loss of photons. The use of surface texturing techniques or low loss antireflecting layers can enhance by several percentage points the conversion efficiency of silicon cells. The basic differences between n(+)-p-p(+) and p(+)-n-n(+) cells are treated. A significant part of the study was devoted to the importance of surface region lifetime and heavy doping effects on efficiency. Heavy doping bandgap reduction effects are enhanced by low surface layer lifetimes, and conversely, the reduction in solar cell efficiency due to low surface layer lifetime is further enhanced by heavy doping effects. A series of computer studies is reported which seeks to determine the best cell structure and doping levels for maximum efficiency

A theoretical analysis of the current-voltage characteristics of solar cells

The current-voltage characteristics and efficiencies of solar cells are discussed. For one solar cell structure detailed curves are presented which include carrier densities, current densities, potential, and quasi-Fermi levels at different voltage levels both with and without optically generated carriers (AMO conditions). In addition some results are presented concerning the influence of various parameter variations such as lifetime, cell thickness, and high-low junction width on solar cell performance

Gossip on Weighted Networks

We investigate how suitable a weighted network is for gossip spreading. The proposed model is based on the gossip spreading model introduced by Lind et.al. on unweighted networks. Weight represents "friendship." Potential spreader prefers not to spread if the victim of gossip is a "close friend". Gossip spreading is related to the triangles and cascades of triangles. It gives more insight about the structure of a network. We analyze gossip spreading on real weighted networks of human interactions. 6 co-occurrence and 7 social pattern networks are investigated. Gossip propagation is found to be a good parameter to distinguish co-occurrence and social pattern networks. As a comparison some miscellaneous networks and computer generated networks based on ER, BA, WS models are also investigated. They are found to be quite different than the human interaction networks.Comment: 8 pages, 4 figures, 1 tabl

RNNs Implicitly Implement Tensor Product Representations

Recurrent neural networks (RNNs) can learn continuous vector representations of symbolic structures such as sequences and sentences; these representations often exhibit linear regularities (analogies). Such regularities motivate our hypothesis that RNNs that show such regularities implicitly compile symbolic structures into tensor product representations (TPRs; Smolensky, 1990), which additively combine tensor products of vectors representing roles (e.g., sequence positions) and vectors representing fillers (e.g., particular words). To test this hypothesis, we introduce Tensor Product Decomposition Networks (TPDNs), which use TPRs to approximate existing vector representations. We demonstrate using synthetic data that TPDNs can successfully approximate linear and tree-based RNN autoencoder representations, suggesting that these representations exhibit interpretable compositional structure; we explore the settings that lead RNNs to induce such structure-sensitive representations. By contrast, further TPDN experiments show that the representations of four models trained to encode naturally-occurring sentences can be largely approximated with a bag of words, with only marginal improvements from more sophisticated structures. We conclude that TPDNs provide a powerful method for interpreting vector representations, and that standard RNNs can induce compositional sequence representations that are remarkably well approximated by TPRs; at the same time, existing training tasks for sentence representation learning may not be sufficient for inducing robust structural representations.Comment: Accepted to ICLR 201

Phase field modelling of surfactants in multi-phase flow

A diffuse interface model for surfactants in multi-phase flow with three or more fluids is derived. A system of Cahn-Hilliard equations is coupled with a Navier-Stokes system and an advection-diffusion equation for the surfactant ensuring thermodynamic consistency. By an asymptotic analysis the model can be related to a moving boundary problem in the sharp interface limit, which is derived from first principles. Results from numerical simulations support the theoretical findings. The main novelties are centred around the conditions in the triple junctions where three fluids meet. Specifically the case of local chemical equilibrium with respect to the surfactant is considered, which allows for interfacial surfactant flow through the triple junctions

Ion-Cyclotron Double Resonance

A charged particle in a uniform moving magnetic field H describes a circular orbit in a plance perpendicular to H with an angular frequency or "cyclotron frequency" omagae. When an alternating electric field E(t) is applied normal to H at omegae, the ions absorb energy from the alternating electric field, and are accelerated to larger velocities and orbital radii. [1] The absorption of energy from E(t) at the cyclotron resonance frequency can be conveniently detected using a marginal oscillator detector. When the ions accelerated by E(t) collide with other particles, they lose some of their excess energy. A mixture of ions and neutral molecules in the presence of H and E(t) then reaches a steady-state condition in which the energy gained by the ions from E(t) between collisions is lost to the neutral molecules in collisions

Riverology: Promoting Stewardship of Rivers Through Youth Participation in Science and Art

This project focuses on mentoring children to help reduce marine debris in their local river by implementing one of ten lessons from an inquiry-based Riverology curriculum to empower youth voice, increase geo-literacy, and spatial thinking. Eighteen participants aged seven and eight, piloted Riverology Lesson 2: What Do I Know or Imagine about the Elizabeth River? that includes six steps: inquire, visualize, draw, share, act, and reflect. The children were asked to make drawings before and after viewing an Elizabeth River Story Map presentation (Dunbar, 2021a). The drawings were then compared to see if the participants included marine debris, stewardship solutions, and a mental map of the river with branches. This study addresses four questions 1.) Why should we teach youth about rivers? 2.) How can creating art and stories serve as a communication tool for students to share their ideas? 3.) How can visualization activities be utilized to connect youth to their local rivers? 4.) What barriers do students face on their journey to act and participate in the public sphere? Scholars, such as Jürgen Habermas (1974), Sibel Ozsoy and Berat Ahi (2014), Tom Cockburn (2019), Lynda Barry (2019), and Millie Kerr (2016) have advocated for a citizen democracy fueled by youth participation in the arts. Some of these efforts have been applied to environmental conservation, but no such inquiry-based effort has been undertaken to address the stewardship of the Elizabeth River in Virginia. The scale of the marine debris issue sometimes creates the impression that local actions are futile, but research shows people using their own expertise and knowledge as stewards is a driver for change (N. Bennett, et al., 2017). To foster river stewards these young participants completed Riverology Lesson 2 and although none of their pre- drawings included marine debris or stewardship actions, 83% of the post- drawings did. In addition, only 11% drew a mental map of the river in their pre- drawings, but 44% did after viewing maps and images. An unexpected finding showed none of the drawings included people and this may relate to youth empowerment issues, the inquiry question wording, or COVID-19 isolation

Fluctuations and Correlations in Lattice Models for Predator-Prey Interaction

Including spatial structure and stochastic noise invalidates the classical Lotka-Volterra picture of stable regular population cycles emerging in models for predator-prey interactions. Growth-limiting terms for the prey induce a continuous extinction threshold for the predator population whose critical properties are in the directed percolation universality class. Here, we discuss the robustness of this scenario by considering an ecologically inspired stochastic lattice predator-prey model variant where the predation process includes next-nearest-neighbor interactions. We find that the corresponding stochastic model reproduces the above scenario in dimensions 1< d \leq 4, in contrast with mean-field theory which predicts a first-order phase transition. However, the mean-field features are recovered upon allowing for nearest-neighbor particle exchange processes, provided these are sufficiently fast.Comment: 5 pages, 4 figures, 2-column revtex4 format. Emphasis on the lattice predator-prey model with next-nearest-neighbor interaction (Rapid Communication in PRE

Lung Paraquat Content and Effects on the Lung Glutathione Antioxidant System, Nadph, and Polyamines Resulting From Intravenous Coinfusion of Paraquat and Putrescine to Rats

Paraquat was administered to male, Sprague-Dawley rats via continous infusion, at dosage rates of 250 (LoPQ) or 500 (HiPQ) nmoles/hr for seven days. The purpose was to characterize the effects of prolonged, low blood levels of the herbicide on selected lung biochemical parameters. The efficacy of putrescine as an inhibitor of pulmonary paraquat accumulation, in vivo, was assessed in these animals by I.V. coinfusion of 2500 or 5000 nmoles putrescine/hr. Dose-dependent levels of both paraquat and putrescine were achieved by 18 hours and were maintained throughout the exposure period. Terminal lung paraquat content was also dose-dependent and up to 18-fold greater than corresponding blood levels, indicative of pulmonary accumulation of the herbicide. Despite relatively high putrescine dosage rates, resulting blood levels of this diamine were low and did not significantly alter terminal lung paraquat content. No evidence of paraquat toxicity was seen in LoPQ animals while frank toxicity was observed in the HiPQ animals beginning between the fourth and fifth day. Qualitative histopathological examination of the lungs revealed changes typical of paraquat toxicity (e.g., interstitial edema, increase in type II cells) resulting from HiPQ. Significant increases were found in levels of lung glutathione and activities of the GSH peroxidase system enzymes, glucose-6-phosphate dehydrogenase and GSSG reductase. These changes were probably the result of paraquat-induced oxidant stress and increased NADPH requirements. Elevations in lung putrescine, spermidine, and ornithine decarboxylase activity were detected in HiPQ animals only, and reflected the observed lung damage and/or resulting proliferative state of the tissue rather than a direct response to paraquat. As in the case of pulmonary oxygen toxicity, the increased levels of lung polyamines may serve to mediate a reparative response to paraquat-induced lung damage. The results demonstrate only a narrow difference between a paraquat dose which produces no apparent lung damage but stimulates components of the GSH peroxidase antioxidant system and one which causes characteristic, paraquat-induced lung damage. The experimental model employed here represents a useful means to study subtle, paraquat-induced biochemical and morphological alterations in lung by avoiding paraquat doses which rapidly produce lung damage or are directly toxic to extrapulmonary tissues