Article
Energy & Fuels
Seung Hoon Lee, Gyu Hyun Lee, Hae-Seok Lee, Donghwan Kim, Yoonmook Kang
Summary: The study demonstrates that CIS solar cells prepared via three-stage MOCVD show high energy conversion efficiency without the need for a buffer layer. By applying a Cu-deficient layer, a buried pn junction can be created, indicating that the fabrication of fully-MOCVD-processed CIS photovoltaic devices is feasible.
Article
Nanoscience & Nanotechnology
Tuomas Haggren, Vidur Raj, Anne Haggren, Nikita Gagrani, Chennupati Jagadish, Hoe Tan
Summary: This report demonstrates the construction of a hole-selective III-V semiconductor solar cell on i-GaAs using copper iodide (CuI) and optimization of the GaAs surface passivation and oxygen content of CuI, leading to high open-circuit voltage and solar conversion efficiency.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Review
Energy & Fuels
Jiaying Chen, Youtian Mo, Chaoying Guo, Jiansen Guo, Bingshe Xu, Xi Deng, Quan Xue, Guoqiang Li
Summary: The combination of III-V compound semiconductor materials and organic semiconductor materials is a potential pathway to solve the problems of conventional doped p-n junction solar cells. This review presents the recent progress of organic-inorganic hybrid solar cells based on polymers and III-V semiconductors, including materials, devices, growth processes, patterning and etching processes, advanced device structure designs, and optimization pathways for efficiency enhancement. The future development of such hybrid cells is also discussed.
Article
Chemistry, Multidisciplinary
Sahil Sharma, Carlos A. Favela, Bo Yu, Eduard Galstyan, Sicong Sun, Tanguy Terlier, Venkat Selvamanickam
Summary: This study presents a method for the heteroepitaxial growth of independent semiconductor films on commercial GaAs wafers by depositing fluoride layers and subsequently growing GaAs using MOCVD. The triple fluoride layers enable the liftoff of free-standing semiconductor films, which can be further transferred to desired substrates. The findings have significant implications in the development of high-performance, flexible, and large-area electronics.
ADVANCED MATERIALS INTERFACES
(2022)
Article
Energy & Fuels
Jiaping Wang, Peng Zhao, Ying Hu, Zhenhua Lin, Jie Su, Jincheng Zhang, Jingjing Chang, Yue Hao
Summary: The study focuses on optimizing all-inorganic perovskite/gallium arsenide tandem solar cells for potential space applications, achieving high power conversion efficiencies through adjustments in material thickness and doping concentrations. By achieving current matching, a significantly high efficiency is achieved in the 2-T configuration.
Article
Energy & Fuels
Malek Rwaimi, Christopher G. Bailey, Peter J. Shaw, Thomas M. Mercier, Chirenjeevi Krishnan, Tasmiat Rahman, Pavlos G. Lagoudakis, Ray-Hua Horng, Stuart A. Boden, Martin D. B. Charlton
Summary: This study successfully utilized perovskite quantum dots deposited on the window layer of GaAs thin-film solar cells to improve the external quantum efficiency across its entire absorption range. Luminescent downshifting and improved surface passivation of the window layer contributed to the enhancement of the internal quantum efficiency, leading to a doubling of EQE in the ultraviolet region of the solar spectrum.
SOLAR ENERGY MATERIALS AND SOLAR CELLS
(2022)
Article
Chemistry, Physical
Nikola Papez, Rashid Dallaev, Pavel Kaspar, Dinara Sobola, Pavel Skarvada, Stefan Talu, Shikhgasan Ramazanov, Alois Nebojsa
Summary: This work focuses on the degradation of GaAs solar cells under continuous laser irradiation. The solar cells were exposed to intense light for two months, leading to changes in electrical characteristics and structural composition. Analysis using various techniques such as Raman spectroscopy and X-ray photoelectron spectroscopy confirmed displacement of titanium and aluminum atoms, as well as slight redistribution of oxygen bonds in the anti-corrosion coating.
Review
Chemistry, Physical
Nikola Pap, Rashid Dallaev, Stefan Talu, Jaroslav Kagtyl
Summary: GaAs-based solar cells, despite achieving the highest efficiency, are not widely used but are suitable for specific applications due to their durability. This review provides a summary of past, present, and future uses, as well as advancements in development and performance.
Article
Materials Science, Multidisciplinary
Ameer Abdullah, Fawad Tariq, Mandar A. Kulkarni, Hamza Thaalbi, Jun-Seok Ha, June Key Lee, Sang-Wan Ryu
Summary: In this article, the use of reproducible GaN nanowires (GNWs) with metal oxide overlayers and an efficient co-catalyst is demonstrated for high-performance photoelectrochemical (PEC) water splitting. The facile growth of GNWs using MOCVD method increases the active area for the water splitting reaction and facilitates charge transport. The passivation of surface defects and the visible absorption range of the co-catalyst greatly enhance the photocurrent density and achieve a high solar to hydrogen conversion efficiency of 6.4%.
MATERIALS TODAY PHYSICS
(2023)
Article
Materials Science, Multidisciplinary
Xiaoye Wang, Xiaoguang Yang, Wenna Du, Tao Yang
Summary: In this study, the effects of multiple growth parameters on self-catalyzed growth of InAs/GaSb axial heterostructured nanowires on Si substrate by MOCVD were investigated. It was found that the growth temperature and switching time have significant influences on the nanowire growth.
Article
Chemistry, Physical
Zaki N. Zahran, Yugo Miseki, Eman A. Mohamed, Yuta Tsubonouchi, Kikuo Makita, Takeyoshi Sugaya, Kazuhiro Sayama, Masayuki Yagi
Summary: A customized double-junction GaAs / GaAs photovoltaic (PV) device was matched with an efficient electrolyzer to achieve a perfect performance match. Under solar irradiation, the efficient and stable solar water splitting with high solar-to-hydrogen efficiency was demonstrated. This study highlights the importance of the perfect matching between the PV device and the electrolyzer, as well as the development of efficient electrolyzers, for improving the solar-to-hydrogen efficiency and stability.
ACS APPLIED ENERGY MATERIALS
(2022)
Article
Energy & Fuels
Steaphan M. Wallace, Wipakorn Jevasuwan, Naoki Fukata
Summary: Schottky junction photovoltaic devices were successfully assembled using nanowire shaped graphene sheets grown on-site onto nano-imprint lithography silicon nanowires, simplifying the fabrication process and improving power conversion efficiency. However, high recombination losses likely limited device performance in this simple system.
Article
Computer Science, Information Systems
Ahid S. Hajo, Sascha Preu, Leonid Kochkurov, Thomas Kusserow, Oktay Yilmazoglu
Summary: This study investigates fully integrated THz detectors using silver NWs as bridge contacts on highly doped GaAs and InGaAs layers, achieving improved performance at zero bias with a maximum cut-off frequency of 2.6 THz. Initial THz measurements suggest a responsivity of 0.81 A/W and low NEP value of 7 pW/root Hz at 1 THz.
Article
Materials Science, Multidisciplinary
Fawad Tariq, Ameer Abdullah, Mandar A. Kulkarni, Hamza Thaalbi, Indrajit Bagal, Soon Hyung Kang, Jun-Seok Ha, Sang-Wan Ryu
Summary: Nanostructured GaN semiconductors have the potential to enhance the efficiency of photoelectrochemical cells, but their stability and solar-to-hydrogen conversion efficiency need improvement. This study explores the use of passivation layers, cocatalysts, and textured platforms to address these issues. The results show that GaN nanowires on silicon substrate exhibit higher photocurrent density and conversion efficiency compared to other substrates.
MATERIALS TODAY PHYSICS
(2023)
Article
Engineering, Electrical & Electronic
Qiangjian Sun, Junhua Long, Xuefei Li, Pan Dai, Yi Zhang, Jingjing Xuan, Xia Wang, Zhitao Chen, Xiaoxu Wu, Shulong Lu
Summary: This study investigates the diffusion effect of copper in flexible solar cells under high temperature annealing and finds that the excess copper diffusion into the active region leads to the degradation of the cell's performance.
IEEE ELECTRON DEVICE LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Sumit K. Mandal, Gokul Krishnan, Chaitali Chakrabarti, Jae-Sun Seo, Yu Cao, Umit Y. Ogras
IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS
(2020)
Article
Computer Science, Hardware & Architecture
Gokul Krishnan, Sumit K. Mandal, Chaitali Chakrabarti, Jae-sun Seo, Umit Y. Ogras, Yu Cao
IEEE DESIGN & TEST
(2020)
Article
Chemistry, Physical
Xin Shen, Maoqing Yao, Ke Sun, Tianshuo Zhao, Yulian He, Chun-Yung Chi, Chongwu Zhou, Paul Daniel Dapkus, Nathan S. Lewis, Shu Hu
Summary: The use of GaAs nanowire arrays as photoanodes in solar-driven water oxidation demonstrates long-term stability and efficiency, highlighting the benefits of discretized absorbers on insulating substrates. This approach offers a promising strategy to transform unstable absorbers into defect-tolerant, corrosion-resistant photoanodes.
ACS ENERGY LETTERS
(2021)
Article
Chemistry, Physical
Fang Liu, Xingxing Chen, Haoming Liu, Jie Zhao, Meiqi Xi, Hongshan Xiao, Tongkang Lu, Yu Cao, Yan Li, Lianmao Peng, Xuelei Liang
Summary: A closed-loop recycling strategy is proposed in this study, which enables the production of high-purity and structurally stable s-SWCNTs while significantly reducing material costs and increasing total yield.
Article
Computer Science, Hardware & Architecture
Rakshith Saligram, Wriddhi Chakraborty, Ningyuan Cao, Yu Cao, Suman Datta, Arijit Raychowdhury
Summary: This article analyzes the importance of cryogenic CMOS in building scalable quantum computers and its benefits for high-performance computing, focusing on the power and performance trade-offs in the cryogenic operation of digital logic. Experimental measurements and simulation studies show significant performance improvements and energy-delay product enhancement in cryogenic operation compared to room temperature.
IEEE JOURNAL ON EXPLORATORY SOLID-STATE COMPUTATIONAL DEVICES AND CIRCUITS
(2021)
Article
Computer Science, Hardware & Architecture
Gokul Krishnan, Sumit K. Mandal, Chaitali Chakrabarti, Jae-Sun Seo, Umit Y. Ogras, Yu Cao
Summary: With the widespread use of Deep Neural Networks, machine learning algorithms have evolved in two directions: one for better accuracy and the other for energy efficiency. This research focuses on efficient on-chip communication for DNN accelerators and proposes a method to determine the optimal interconnect choice. Experimental results show that NoC-tree is suitable for compact DNNs, while NoC-mesh is necessary for DNNs with high connection density.
ACM JOURNAL ON EMERGING TECHNOLOGIES IN COMPUTING SYSTEMS
(2022)
Article
Chemistry, Physical
Fang Liu, Xingxing Chen, Meiqi Xi, Nan Wei, Lan Bai, Lianmao Peng, Yu Cao, Xuelei Liang
Summary: This paper comparatively studied the chiral selectivity of two polymers in wrapping carbon nanotubes, and found that they have different selectivity for raw materials with different diameters. The research results provide important information for improving the method of polymer wrapping and extracting single-chirality s-SWCNTs.
Article
Engineering, Electrical & Electronic
Sumit K. Mandal, Gokul Krishnan, A. Alper Goksoy, Gopikrishnan Ravindran Nair, Yu Cao, Umit Y. Ogras
Summary: Graph convolutional networks (GCNs) have remarkable learning capabilities when processing graph-structured data. This paper presents a communication-aware in-memory computing architecture (COIN) for GCN hardware acceleration to optimize performance and energy efficiency. Experimental evaluations show a 105x improvement in energy consumption compared to state-of-the-art GCN accelerators.
IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS
(2022)
Article
Computer Science, Hardware & Architecture
Zhenhua Zhu, Hanbo Sun, Tongxin Xie, Yu Zhu, Guohao Dai, Lixue Xia, Dimin Niu, Xiaoming Chen, Xiaobo Sharon Hu, Yu Cao, Yuan Xie, Huazhong Yang, Yu Wang
Summary: This work proposes an efficient modeling tool, MNSIM 2.0, for PIM architectures, which includes hardware-level modeling structure, algorithm-level simulation, and scheduling-level description. Validation using fabricated PIM macros shows that MNSIM 2.0 performs well in terms of modeling error rate and has influentials in PIM design space explorations, device parameter analysis, and architecture design insights.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Abhishek Moitra, Abhiroop Bhattacharjee, Runcong Kuang, Gokul Krishnan, Yu Cao, Priyadarshini Panda
Summary: Spiking neural networks (SNNs) are a research domain focused on energy-efficient machine intelligence using temporal spike data and bio-plausible activation functions. The authors propose SpikeSim, a tool for realistic evaluation of IMC-mapped SNNs, and find that topological modifications can significantly reduce area and energy-delay-product of the neuronal module. The study also concludes that lower number of time-steps lead to higher throughput and energy-efficiency for SNNs compared to 4-bit ANNs.
IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Ziyao Yang, Amol D. Gaidhane, Kassandra Anderson, Glenn Workman, Yu Cao
Summary: Compact models for CMOS transistors often require manual parameter extraction, which is time-consuming and requires expertise. This paper proposes a graph-based compact model (GCM) approach using machine learning to automate the parameter extraction process. The GCM integrates physical equations and neural networks to accurately predict device behavior. Experimental results show that the GCM achieves high accuracy in parameter extraction for a specific technology and passes benchmark tests.
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Jingbo Sun, Li Yang, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar, Deliang Fan, Yu Cao
Summary: This paper proposes a novel self-supervised approach for unsupervised detection of out of distribution (OOD) data. The method evaluates the Mahalanobis distance of gradients to identify OOD data. Experimental results show that the proposed approach outperforms other methods in terms of the area under the receiver operating characteristic (AUROC) on various datasets. Furthermore, the detector is capable of accurately handling OOD data in continual learning.
CONTINUAL SEMI-SUPERVISED LEARNING, CSSL 2021
(2022)
Article
Computer Science, Artificial Intelligence
Li Yang, Zhezhi He, Yu Cao, Deliang Fan
Summary: Deep neural network (DNN) model compression is an important optimization method for hardware acceleration, but the compressed model usually lacks the ability to adjust computing complexity in real-time. To address this challenge, researchers constructed a dynamic DNN with runtime adaptation of computing structures. They proposed a progressive subnetwork searching framework to obtain multiple high-quality subnets for the dynamic DNN.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Review
Engineering, Electrical & Electronic
P. Daniel Dapkus, Chun Yung Chi, Sang Jun Choi, Hyung Joon Chu, Mitchell Dreiske, Rijuan Li, Yenting Lin, Yoshitake Nakajima, Dawei Ren, Ryan Stevenson, Maoqing Yao, Ting Wei Yeh, Hanmin Zhao
Summary: Selective area epitaxial growth of III-V materials and devices by metalorganic chemical vapor deposition is reviewed, with a special focus on its applications in photonic integration, heterogeneous integration of materials relevant to photonic integration, and nanostructure integration. The pioneering work led by Professor James J. Coleman demonstrates the value of selective growth in various applications.
PROGRESS IN QUANTUM ELECTRONICS
(2021)
Proceedings Paper
Computer Science, Hardware & Architecture
Shreyas K. Venkataramanaiah, Han-Sok Suh, Shihui Yin, Eriko Nurvitadhi, Aravind Dasu, Yu Cao, Jae-Sun Seo
2020 IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER AIDED-DESIGN (ICCAD)
(2020)
