Performance of TF-VLS Grown InP Photovoltaic Cells

A grand challenge of photovoltaics (PV) is to find materials offering a promising combination of low costs and high efficiencies. While III-V material-based PV cells have set many world records, often their cost is much greater than other commercial cells. To help address this gap, thin-film vapor-liquid-solid (TF-VLS) grown Indium Phosphide (InP) PV cells have recently been developed, which both eliminate a key source of high costs and offer a direct bandgap of 1.34eV with potential to approach maximum theoretical efficiencies. However, the unanticipated phenomenon of open circuit voltage (Voc) degradation has prevented TF-VLS grown InP PV cells from achieving their theoretical efficiencies, which appears to be caused by effective bandgap narrowing in certain portions of the cells. To address this issue, we have developed a 3D model for these PV cells in Xyce, a SPICE-like free circuit modeling software. Our model quantifies lateral variation of TF-VLS grown cells observed in photoluminescence (PL) images with two sets of unit cell parameters. It turns out that the PL intensity correlates to PV cells of different bandgaps (Eg). Based on user-defined cutoffs, we are able to categorize the expected bandgap and reduced bandgap cells. With the addition of an appropriate shunt resistance, it is possible to explain most of current-voltage relationship with this model. Finally, we are building a web-enabled tool to allow users to upload their own heterogeneous PV cell data into our model, using a graphical user interface on nanoHUB.org, an open-access science gateway for cloud-based simulation tools and resources for research and education in nanoscale science and technology

Improved constructions of permutation and multi-permutation codes correcting a burst of stable deletions

Permutation codes and multi-permutation codes have been widely considered due to their various applications, especially in flash memory. In this paper, we consider permutation codes and multi-permutation codes against a burst of stable deletions. In particular, we propose a construction of permutation codes correcting a burst stable deletion of length $s$, with redundancy $\log n+ 2\log \log n+O(1)$. Compared to the previous known results, our improvement relies on a different strategy to retrieve the missing symbol on the first row of the array representation of a permutation. We also generalize our constructions for multi-permutations and the variable length burst model. Furthermore, we propose a linear-time encoder with optimal redundancy for single stable deletion correcting permutation codes.Comment: Accepted for publication in IEEE Trans. Inf. Theor

Research on Optimization of Management System of Small and Medium-sized Enterprises Based on Key Performance Indicators

Performance management is an important part of enterprise human resource management, which helps enterprise managers to review the past period of enterprise operation and development, dynamically and continuously monitor the realization of the organization’s expected goals, and realize dynamic two-way communication, communication and evaluation among all levels and departments of the enterprise. Based on the KPI (Key Performance Indicators), this paper further optimizes the management system of small and medium-sized enterprises. In fact, performance appraisal is only an important part of performance management, and it is a local link and means in the management process. At present, the company’s performance management, by comparison, pays more attention to the results and ignores the management process. In an enterprise, the performance of employees is embodied in the quantity, quality, time, cost, etc. The establishment of KPI can provide an objective and fair judgment basis for the enterprise’s value evaluation and value distribution system, and can accurately measure whether and how much employees have contributed to the value creation of the enterprise

Monotone methods for a discrete boundary problem

AbstractThis paper is motivated by recent interests in space discrete Nagumo equations and is concerned with the existence of solutions of a nonlinear discrete boundary value problem. Monotone methods are used to derive the existence theorems. These methods, as is well known, provide constructive schemes for calculating the solutions

Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!

Large Language Models (LLMs) have made remarkable strides in various tasks. Whether LLMs are competitive few-shot solvers for information extraction (IE) tasks, however, remains an open problem. In this work, we aim to provide a thorough answer to this question. Through extensive experiments on nine datasets across four IE tasks, we demonstrate that current advanced LLMs consistently exhibit inferior performance, higher latency, and increased budget requirements compared to fine-tuned SLMs under most settings. Therefore, we conclude that LLMs are not effective few-shot information extractors in general. Nonetheless, we illustrate that with appropriate prompting strategies, LLMs can effectively complement SLMs and tackle challenging samples that SLMs struggle with. And moreover, we propose an adaptive filter-then-rerank paradigm to combine the strengths of LLMs and SLMs. In this paradigm, SLMs serve as filters and LLMs serve as rerankers. By prompting LLMs to rerank a small portion of difficult samples identified by SLMs, our preliminary system consistently achieves promising improvements (2.4% F1-gain on average) on various IE tasks, with an acceptable time and cost investment.Comment: Accepted by EMNLP 2023 Finding