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  1. Antimony selenide (Sb2Se3) has excellent directional optical and electronic behaviors due to its quasi-1D nanoribbons structure. The photovoltaic performance of Sb2Se3 solar cells largely depends on the orientation of the nanoribbons. It is desired to grow these Sb2Se3 ribbons normal to the substrate to enhance photoexcited carrier transport. Therefore, it is necessary to develop a strategy for the vertical growth of Sb2Se3 nanoribbons to achieve high-efficiency solar cells. Since antimony sulfide (Sb2S3) and Sb2Se3 are from the same space group (Pbnm) and have the same crystal structure, herein an ultrathin layer (≈20 nm) of Sb2S3 has been used to assistmore »the vertical growth of Sb2Se3 nanoribbons to improve the overall efficiency of Sb2Se3 solar cell. The Sb2S3 thin layer deposited by the hydrothermal process helps the Sb2Se3 ribbons grow normal to the substrate and increases the efficiency from 5.65% to 7.44% through the improvement of all solar cell parameters. This work is expected to open a new direction to tailor the Sb2Se3 grain growth and further develop the Sb2Se3 solar cell in the future.« less
    Free, publicly-accessible full text available May 12, 2023
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  6. As large-scale scientific simulations and big data analyses become more popular, it is increasingly more expensive to store huge amounts of raw simulation results to perform post-analysis. To minimize the expensive data I/O, “in-situ” analysis is a promising approach, where data analysis applications analyze the simulation generated data on the fly without storing it first. However, it is challenging to organize, transform, and transport data at scales between two semantically different ecosystems due to the distinct software and hardware difference. To tackle these challenges, we design and implement the X-Composer framework. X-Composer connects cross-ecosystem applications to form an “in-situ” scientificmore »workflow, and provides a unified approach and recipe for supporting such hybrid in-situ workflows on distributed heterogeneous resources. X-Composer reorganizes simulation data as continuous data streams and feeds them seamlessly into the Cloud-based stream processing services to minimize I/O overheads. For evaluation, we use X-Composer to set up and execute a cross-ecosystem workflow, which consists of a parallel Computational Fluid Dynamics simulation running on HPC, and a distributed Dynamic Mode Decomposition analysis application running on Cloud. Our experimental results show that X-Composer can seamlessly couple HPC and Big Data jobs in their own native environments, achieve good scalability, and provide high-fidelity analytics for ongoing simulations in real-time.« less
    Free, publicly-accessible full text available July 5, 2022