InGaN/GaN/ZnO Thermoelectric Properties

The ability to harness waste heat and convert it into electricity via thermoelectric devices is a major breakthrough in green energy. Thermoelectric devices use the Seebeck effect to directly convert a temperature difference into a voltage output, or they can perform active cooling by running a current through the device. They have a wide range of applications, from portable refrigeration to power generation from an exhaust pipe or even body heat. However, the cost, scarcity, and inefficiency of current materials (i.e. Bi2Te3, SiGe) has limited the potential of thermoelectric power. With the discovery of better materials, it will be possible to use thermoelectric devices for more applications, increasing the use of renewable energy. The purpose of this study is to determine the thermoelectric properties indium gallium nitride grown on zinc oxide with a gallium nitride buffer layer (InGaN/GaN/ZnO), materials that are more cost effective and environmentally friendly, to determine their feasibility in thermoelectric devices. Several material properties were tested and reported, including the X-ray diffraction scan of the material structure, electrical properties such as conductivity and Seebeck coefficient, and the power factor, which determines the ability of the material to produce voltage. Based on this study, InGaN/GaN/ZnO has shown considerable potential as a material for thermoelectric generators due to its favorable power factor of up to 680∙10-4 W/mK2 at room temperature. In the future, this material should be further tested within thermoelectric devices, and p-type doping methods should be explored to enable the device level performance

Strain-stress study of AlxGa1−xN/AlN heterostructures on c-plane sapphire and related optical properties

This work presents a systematic study of stress and strain of AlxGa1−xN/AlN with composition ranging from GaN to AlN, grown on a c-plane sapphire by metal-organic chemical vapor deposition, using synchrotron radiation high-resolution X-ray diffraction and reciprocal space mapping. The c-plane of the AlxGa1−xN epitaxial layers exhibits compressive strain, while the a-plane exhibits tensile strain. The biaxial stress and strain are found to increase with increasing Al composition, although the lattice mismatch between the AlxGa1−xN and the buffer layer AlN gets smaller. A reduction in the lateral coherence lengths and an increase in the edge and screw dislocations are seen as the AlxGa1−xN composition is varied from GaN to AlN, exhibiting a clear dependence of the crystal properties of AlxGa1−xN on the Al content. The bandgap of the epitaxial layers is slightly lower than predicted value due to a larger tensile strain effect on the a-axis compared to the compressive strain on the c-axis. Raman characteristics of the AlxGa1−xN samples exhibit a shift in the phonon peaks with the Al composition. The effect of strain on the optical phonon energies of the epitaxial layers is also discussed

A Novel Shortest Paths Algorithm on Unweighted Graphs

The shortest paths problem is a common challenge in graph theory, with a broad range of potential applications. However, conventional serial algorithms often struggle to adapt to large-scale graphs. To address this issue, researchers have explored parallel computing as a solution. The state-of-the-art shortest paths algorithm is the Delta-stepping implementation method, which significantly improves the parallelism of Dijkstra's algorithm. We propose a novel shortest paths algorithm achieving higher parallelism and scalability, which requires $O(nm)$ and $O(S_{wcc} \cdot E_{wcc})$ times on the connected and unconnected graphs for APSP problems, respectively, where $S_{wcc}$ and $E_{wcc}$ denote the number of nodes and edges included in the largest weakly connected component in graph. To evaluate the effectiveness of our algorithm, we tested it using real network inputs from Stanford Network Analysis Platform and SuiteSparse Matrix Collection. Our algorithm outperformed the solution of BFS and Delta-stepping algorithm from Gunrock, achieving a speedup of 1,212.523$\times$ and 1,315.953$\times$, respectively

Single-Cell Transcriptome and Network Analyses Unveil Key Transcription Factors Regulating Mesophyll Cell Development in Maize

BACKGROUND: Maize mesophyll (M) cells play important roles in various biological processes such as photosynthesis II and secondary metabolism. Functional differentiation occurs during M-cell development, but the underlying mechanisms for regulating M-cell development are largely unknown. RESULTS: We conducted single-cell RNA sequencing (scRNA-seq) to profile transcripts in maize leaves. We then identified coregulated modules by analyzing the resulting pseudo-time-series data through gene regulatory network analyses. , , , and () families were highly expressed in the early stage, whereas () and families were highly expressed in the late stage of M-cell development. Construction of regulatory networks revealed that these transcript factor (TF) families, especially and , were the major players in the early and later stages of M-cell development, respectively. Integration of scRNA expression matrix with TF ChIP-seq and Hi-C further revealed regulatory interactions between these TFs and their targets. and were primarily expressed in the leaf bases and tips, respectively, and their targets were validated with protoplast-based ChIP-qPCR, with the binding sites of HSF1 being experimentally confirmed. CONCLUSIONS: Our study provides evidence that several TF families, with the involvement of epigenetic regulation, play vital roles in the regulation of M-cell development in maize