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2023 ASEE Annual Conference and Exposition - The Harbor of engineering: Education for 130 Years, ASEE 2023

作者： Harteveld, Casper Bennett, Victoria Zastavker, Yevgeniya V. El Shamy, Usama Tiwari, Binod De, Anirban Wirth, Xenia Wen, Kejun Saftner, David A. Ajmera, Beena Brandenberg, Scott Kennicutt, Alison Rose Congress, Surya Sarat Chandra Tessari, Anthony Omidvar, Mehdi Cabas, Ashly Northeastern University United States Rensselaer Polytechnic Institute United States Olin College of Engineering United States Southern Methodist University United States University of Michigan United States Manhattan College United States Jackson State University United States Northern Arizona University United States Iowa State University United States University of California Los Angeles United States York College of Pennsylvania United States

The aim of our project is to create a scalable and sustainable educational model of mixed reality gaming in civil engineering education that provides practical experiences, develops engineering judgment competency, and engages a diverse student audience. Specifically, we have been building a game-based learning module focused on experiencing the field testing technique cone-penetration testing (CPT). As part of the module, students start a virtual internship at a fictional engineering company. After being briefed through a lecture on CPT, they enter a 3D (game) environment where they conduct CPTs. Students analyze CPT data extracted from the environment and submit a report. To assess student experience of this module, we collected pre/post surveys, game data (including in-game assessments), and student/faculty interviews. In this paper, we report the findings of implementing this CPT module in the initial three years of the project (2016-2019) at five institutions. Overall, we find that students are engaged, especially women and students from historically marginalized communities, increase their knowledge and confidence in the subject matter, and find the module valuable to gain much-needed (field) experience. More recently, we find that the game-based learning intervention seems resilient and, in fact, a solid solution to the disturbances caused by the pandemic, with many students providing positive remarks about being able to experience hands-on learning, which is key to quality engineering education and difficult to achieve through online education. Opportunities for improvement exist regarding access to technology, as well as the instructional design. While we demonstrate the scalability of this approach across multiple institutions and classrooms, open questions remain on how to transform institutions to embed game-based learning not as an intervention but as a key part of the curriculum. © American Society for engineering Education, 2023.

关键词： Students

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Analysis of Students’ Concentration Levels for Online Learning Using Webcam Feeds

Analysis of Students’ Concentration Levels for Online Learn...

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IEEE International Conference on Big Data

作者： Linh Le Ying Xie Sumit Chakravarty Michael Hales John Johnson Tu N. Nguyen College of Computing and Software Engineering Kennesaw State University Marietta GA USA Southern Polytechnic College of Engineering and Engineering Technology Kennesaw State University Marietta GA USA WellStar College of Health and Human Services Kennesaw State University Marietta GA USA

ISBN: (纸本)9781665445993

Tracking the concentration of students during online learning offers great benefits. For examples, distracted students can be suggested to do a brief exercise to refresh their brains; or the teacher can be notified when too many students have difficulties on concentration so the class could take a short break. Traditionally, mental states like concentration levels can be analyzed using Electroencephalogram (EEG) or Functional Near-Infrared Spectroscopy (fNIRS). However, methods that utilize these data require specialized equipment which is not feasible to deploy on a large scale. On the other hand, recent breakthroughs in deep learning provide possibilities of scalable solutions to detect concentration levels using only webcam. Leveraging this advancement, we investigate the task of tracking students’ concentration levels during online learning using facial data coupled with deep learning based computer vision technologies. More specifically, we examine the performances of different representations of facial data integrated with various deep architectures to empirically determine a solution balanced between prediction accuracy and time efficiency that is suitable for real-time application. Our experimental study shows that the proposed solution achieves over 91% accuracy while keeping execution time low enough for real-time deployment.

关键词： Deep learning Webcams Neural networks Computer architecture Streaming media Big Data Real-time systems

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Ecology and risks of the global plastisphere as a newly expanding microbial habitat

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The Innovation 2024年第1期5卷 49-58页

作者： Changchao Li Michael RGillings Chao Zhang Qinglin Chen Dong Zhu Jie Wang Kankan Zhao Qicheng Xu Polly Hangmei Leung Xiangdong Li Jian Liu Ling Jin Department of Civil and Environmental Engineering The Hong Kong Polytechnic UniversityKowloonHong KongChina Environment Research Institute Shandong UniversityQingdao 266237China State Key Laboratory of Marine Pollution City University of Hong KongKowloon TongHong KongChina ARC Centre of Excellence in Synthetic Biology Faculty of Science and EngineeringMacquarie UniversitySydneyNSW 2109Australia Key Laboratory of Urban Environment and Health Ningbo Urban Environment Observation and Research StationInstitute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China Beijing Key Laboratory of Farmland Soil Pollution Prevention and Remediation College of Resources and Environmental SciencesChina Agricultural UniversityBeijing 100193China Institute of Soil and Water Resources and Environmental Science College of Environmental and Resource SciencesZhejiang UniversityHangzhou 310058China Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization Nanjing Agricultural UniversityNanjing 210095China Department of Health Technology and Informatics and Research Institute for Future Food The Hong Kong Polytechnic UniversityKowloonHong KongChina Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou) Guangzhou 511458China

Plastic offers a new niche for microorganisms,the *** everincreasing emission of plastic waste makes it critical to understand the microbial ecology of the plastisphere and associated ***,we present a global fingerprint of the plastisphere,analyzing samples collected from freshwater,seawater,and terrestrial *** plastisphere assembles a distinct microbial community that has a clearly higher heterogeneity and a more deterministically dominated assembly compared to natural *** coexistence patterns—loose and fragile networks with mostly specialist linkages among microorganisms that are rarely found in natural habitats—are seen in the *** microbiomes generally have a great potential to metabolize organic compounds,which could accelerate carbon *** involved in the nitrogen cycle are also altered in the plastisphere,especially in freshwater plastispheres,where a high abundance of denitrifiers may increase the release of nitrite(aquatic toxicant)and nitrous oxide(greenhouse gas).Enrichment of animal,plant,and human pathogens means that the plastisphere could become an increasingly mobile reservoir of harmful *** findings highlight that if the trajectory of plastic emissions is not reversed,the expanding plastisphere could pose critical planetary health challenges.

关键词： reservoir mostly habitat

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A novel vanadium complex VO(p-dmada)inhibits neuroinflammation induced by lipopolysaccharide

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Chinese Chemical Letters 2023年第10期34卷 209-214页

作者： Zhijun He Xiaoqian Li Huajie Zhang Xin Liu Shuangxue Han Anwar Abdurahman Liming Shen Xiubo Du Nan Li Xiaoda Yang Qiong Liu Shenzhen Key Laboratory of Marine Biotechnology and Ecology College of Life Sciences and OceanographyShenzhen UniversityShenzhen 518055China National R&D Center for Se-rich Agricultural Products Processing Hubei Engineering Research Center for Deep Processing of Green Se-rich Agricultural ProductsSchool of Modern Industry for Selenium Science and EngineeringWuhan Polytechnic UniversityWuhan 430023China Shenzhen Bay Laboratory Shenzhen 518055China State Key Laboratories of Natural and Biomimetic Drugs Department of Chemical BiologySchool of Pharmaceutical SciencesPeking University Health Science CenterBeijing 100191China Department of Pharmacy Shenzhen People’s Hospital(The Second Clinical Medical CollegeJinan UniversityThe First Affiliated HospitalSouthern University of Science and Technology)Shenzhen 518020China Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions Shenzhen 518055China

Uncontrolled microglial activation is decisively involved in the neuroinflammatory pathogenesis of brain diseases. Consequently, suppression of microglial overactivation appears to be a strategy for the prevention of nerve injury. In this paper, a novel vanadium complex, vanadyl N-(p-N,Ndimethylaminophenylcarbamoylmethyl)iminodiacetate(VO(p-dmada)), was synthesized from vanadyl sulfate and N,N-dimethyl-p-phenylenediamine, which was structurally characterized by Fourier transform infrared spectrum and ESI-MS analysis. The effect of VO(p-dmada) on neuroinflammation was investigated by using the models of lipopolysaccharide(LPS)-induced BV2 microglial cells and BALB/c *** data demonstrated that VO(p-dmada) significantly suppressed microglial activation by downregulating inflammatory mediators and associated proteins, and inactivating nuclear factor-κ B(NF-κ B) signaling pathway. VO(p-dmada) also upregulated peroxisome proliferator activated receptor gamma(PPARγ) by reducing transglutaminase 2 and heat shock protein 60 expression. Co-treatment with PPARγ antagonist GW9662 significantly impeded the inhibitory effect of VO(p-dmada) on LPS-induced *** cumulative findings demonstrated that VO(p-dmada) is a potential new drug for the treatment of neuroinflammation-related neurodegenerative diseases.

关键词： Vanadium Vanadyl N-(p-N,Ndimethylaminophenylcarbamoylmethyl)iminodiacetate (VO(p-dmada)) Neuroinflammation Microglia Proteomics Peroxisome proliferator activated receptor gamma(PPARγ)

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technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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DeepBHMR: Learning Bidirectional Hybrid Mixture Models for Generalized Rigid Point Set Registration

DeepBHMR: Learning Bidirectional Hybrid Mixture Models for G...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Zhe Min Zhengyan Zhang Ang Zhang Rui Song Yibin Li Max Q.-H. Meng School of Control Science and Engineering Shandong University China Wellcome/EPSRC Centre for Surgical and Interventional Sciences University College London UK Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Yuanhua Robotics Perception and AI Technologies Ltd Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we introduce a novel normal-assisted learning-based rigid registration approach, i.e., Deep Bi-directional Hybrid Mixture Registration (DeepBHMR). Our approach utilises helpful normal vectors explicitly in both correspondence and transformation stages and formulates the optimization objective of registration in a bi-directional way that considers noise in both point sets. DeepBHMR consists of three modules: (1) the correspondence network that estimates the correspondence probability relating points within one generalized point set (i.e., positional and normal vectors) with components of Hybrid Mixture Models (HMMs) representing the other generalized point set; (2) the posterior module that computes HMMs parameters; (3) the transformation module that computes the rotation matrix and the translation vector given the estimated generalized-point to hybrid-distribution correspondences and HMMs parameters. DeepBHMR has been validated on 291 human femur and 260 hip models, and extensive experimental results demonstrate that DeepBHMR outperforms the state-of-the-art registration methods (p-value < 0.01). In the circumstance of femur bones, the mean rotation and translation error values are around 1° (i.e., 1.01°) and less than 1 mm (i.e., 0.36mm), respectively. Furthermore, even under the large transformation (i.e., in the range of [0,180]° and [0, 100] mm), the mean RMSE values being 3.05 mm is still satisfactory. Additionally, the results demonstrate the DeepBHMR’s favorable generalizability from femur shapes to hip shapes. We have carefully validated the significant benefits of incorporating normal vectors and the bidirectional mechanism. DeepBHMR can successfully handle the challenging scenario of large transformation and partial registration. The codes are available at https://***/zzyrobot/***.

关键词： Translation Accuracy Shape Hidden Markov models Mixture models Bidirectional control Bones Vectors Optimization Hip

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OBHMR: Robust Partial-to-full Generalized Point Set Registration with Overlap-guided Bidirectional Hybrid Mixture Model

OBHMR: Robust Partial-to-full Generalized Point Set Registra...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Xinzhe Du Zhengyan Zhang Ang Zhang Rui Song Yibin Li Max Q.-H. Meng Zhe Min School of Control Science and Engineering Shandong University China Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Yuanhua Robotics Perception and AI Technologies Ltd Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Wellcome/EPSRC Centre for Interventional and Surgical Sciences University College London London UK

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we introduce a novel overlap-based bidirectional point set registration approach, i.e., Overlap-guided Bidirectional Hybrid Mixture Registration (OBHMR), which incorporates geometric information (i.e., normal vectors) in both the correspondence and transformation stages and formulates the optimization objective of registration in a bidirectional manner. More importantly, to address the issue of partial-to-full registration, OBHMR utilises the predicted point-wise overlap score using networks to formulate the overlap-guided Hybrid Mixture Model consisting of the Gaussian Mixture Model (GMM) and Fisher Mixture Model (FMM). OBHMR contains four components: (1) the overlap-guided correspondence network that estimates the correspondence probabilities and calculates the point-wise overlap score; (2) the learning posterior module that estimates the overlap-guided HMM parameters; (3) the transformation module that computes the rigid transformation by formulating the optimisation objective in a bidirectional registration way, given correspondences and overlap-guided HMM parameters. Experiments using 1457 human femur and 1301 human hip models demonstrate significant improvements in partial-to-full registration performance (p < 0.01) under different overlapping ratios, compared to state-of-the-art registration approaches. Furthermore, individual contributions of three modules (i.e., additional normal vectors, overlap score estimation module and the bidirectional mechanism) in OBHMR have been validated in ablation studies. The results demonstrate OBHMR’s capability of tackling the challenging partial-to-full registration problems in computer-assisted orthopedic surgery. The codes are available at https://***/Dxinz/DeepOBHMR.

关键词： Accuracy Orthopedic surgery Noise Hidden Markov models Estimation Mixture models Probability Vectors Optimization Intelligent robots

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Optical, Structural, and Synchrotron X-ray Absorption Studies for GaN Thin Films Grown on Si by Molecular Beam Epitaxy

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Materials 2024年第12期17卷 2921页

作者： Feng, Zhe Chuan Liu, Jiamin Xie, Deng Nafisa, Manika Tun Zhang, Chuanwei Wan, Lingyu Jiang, Beibei Lin, Hao-Hsiung Qiu, Zhi-Ren Lu, Weijie Klein, Benjamin Ferguson, Ian T. Liu, Shiyuan State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China Southern Polytechnic College of Engineering and Engineering Technology Kennesaw University MariettaGA30060 United States Science Exploring Lab Arbour Glenn Drive LawrencevilleGA30043 United States School of Electronic & Electrical Engineering and Physics Fujian University of Technology Fuzhou350118 China Center on Nano-Energy Research Laboratory of Optoelectronic Materials & Detection Technology Guangxi Key Laboratory for the Relativistic Astrophysics School of Physical Science & Technology Guangxi University Nanning530004 China Department of Electrical Engineering Graduate Institute of Photonics and Optoelectronics National Taiwan University Taipei10617 Taiwan State Key Laboratory of Optoelectronic Materials and Technologies School of Physics Sun Yat-sen University Guangzhou510275 China Hexagonal Scientific Lab LLC DaytonOH45459 United States

GaN on Si plays an important role in the integration and promotion of GaN-based wide-gap materials with Si-based integrated circuits (IC) technology. A series of GaN film materials were grown on Si (111) substrate using a unique plasma assistant molecular beam epitaxy (PA-MBE) technology and investigated using multiple characterization techniques of Nomarski microscopy (NM), high-resolution X-ray diffraction (HR-XRD), variable angular spectroscopic ellipsometry (VASE), Raman scattering, photoluminescence (PL), and synchrotron radiation (SR) near-edge X-ray absorption fine structure (NEXAFS) spectroscopy. NM confirmed crack-free wurtzite (w-) GaN thin films in a large range of 180–1500 nm. XRD identified the w- single crystalline structure for these GaN films with the orientation along the c-axis in the normal growth direction. An optimized 700 °C growth temperature, plus other corresponding parameters, was obtained for the PA-MBE growth of GaN on Si, exhibiting strong PL emission, narrow/strong Raman phonon modes, XRD w-GaN peaks, and high crystalline perfection. VASE studies identified this set of MBE-grown GaN/Si as having very low Urbach energy of about 18 meV. UV (325 nm)-excited Raman spectra of GaN/Si samples exhibited the GaN E2(low) and E2(high) phonon modes clearly without Raman features from the Si substrate, overcoming the difficulties from visible (532 nm) Raman measurements with strong Si Raman features overwhelming the GaN signals. The combined UV excitation Raman–PL spectra revealed multiple LO phonons spread over the GaN fundamental band edge emission PL band due to the outgoing resonance effect. Calculation of the UV Raman spectra determined the carrier concentrations with excellent values. Angular-dependent NEXAFS on Ga K-edge revealed the significant anisotropy of the conduction band of w-GaN and identified the NEXAFS resonances corresponding to different final states in the hexagonal GaN films on Si. Comparative GaN material properties are invest

关键词： Synchrotron radiation

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Using Deep Learning to Identify Multilingual Music Genres

Using Deep Learning to Identify Multilingual Music Genres

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IEEE Southeastcon

作者： Levi Ford Sylvia Bhattacharya Red Hayes Wesley Inman Polytechnic College of Engineering Kennesaw State University Southern

ISBN: (数字)9781728168616

ISBN: (纸本)9781728168623

Automatic genre classification is a widely explored topic nowadays. It is an important task as the quantity of music released is sky-rocket. A survey says that alone Spotify releases about ten thousand songs a month. At the same time, users developed a taste of listening to music of different languages. Hence, it is very crucial to maintain a data base that can automatically classify songs of any language based on their genres. This project attempts to utilize a deep learning convolutional neural network technique to identify the genre of a song from twelve different languages all over the world. This project utilized a data base of sixty songs and mainly classified them into three genres: metal, hip hop, and pop. Each song is trimmed to be exactly five seconds long, and each five second "slice" is converted into a spectrogram, a visual representation of a song's spectrum in the time domain. These spectrograms are divided into training and testing dataset. 75% of the data set is used for training and 25% is used for testing. A tensor flow deep learning convolutional neural network is used as an image classifier to automatically segregate the songs according to their genres. This deep learning model achieved a classification accuracy of 93.3% for all of the twelve languages considered in this database.

关键词： Deep learning Training Metals Predictive models Convolutional neural networks Spectrogram Testing

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Optical, surface, and structural studies of InN thin films grown on sapphire by molecular beam epitaxy

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Journal of Vacuum Science and technology A: Vacuum, Surfaces and Films 2023年第5期41卷

作者： Feng, Zhe Chuan Xie, Deng Nafisa, Manika Tun Lin, Hao-Hsiung Lu, Weijie Chen, Jin-Ming Yiin, Jeffrey Chen, Kuei-Hsien Chen, Li-Chyong Klein, Benjamin Ferguson, Ian T. Southern Polytechnic College of Engineering and Engineering Technology Kennesaw State University MariettaGA30060 United States School of Electronic and Electrical Engineering and Physics Fujian University of Technology Fujian350000 China Department of Electrical Engineering Graduate Institute of Photonics and Optoelectronics National Taiwan University Taipei10617 Taiwan Hexagonal Scientific Lab LLC DaytonOH45459 United States National Synchrotron Radiation Research Center Hsinchu30076 Taiwan Institute of Atomic and Molecular Sciences Academia Sinica Taipei10617 Taiwan National Taiwan University Center for Condensed Matter Sciences Taipei10617 Taiwan

A series of indium nitride (InN) thin films have been grown on sapphire substrates by molecular beam epitaxy (MBE) technology under different growth conditions of temperature and plasma power. Their structural, surface, and optical properties are studied by a variety of techniques of scanning electron microscopy, Hall effect, x-ray diffraction, photoluminescence (PL), Raman scattering, x-ray photoelectron spectroscopy (XPS), synchrotron radiation x-ray absorption near edge structure (XANES), and so on. The lower carrier concentration in InN can be obtained with a higher MBE growth temperature and a lower plasma power. As the plasma power increases, the PL peak energy is observed to shift toward the higher energy side and the Raman E2 (high) and A1 (LO) modes are shifted to the lower frequency. The residual compressive strain in epitaxial InN is relaxed. The lower plasma power and the higher growth temperature are preferred for the MBE growth of high-quality InN films. The influencing factors on the InN PL peak and band gap Eg have been revealed. It is evidenced that the InN PL peak and Eg can be shifted from high down to ∼0.65 eV with the carrier concentration down to low E19 cm−3 and the plasma power down to ∼80 W. Both the XPS and N K-edge XANES revealed the antisite defect of N on the In site, NIn. The XANES In L-edge measurements on the In L3-edge of InN films with various carrier concentrations has indicated the fourfold InN intermediate crystal structures. These obtained results are significant and useful to deepen the understanding and promote further investigation in InN and III-N materials. © 2023 Author(s).

关键词： Molecular beam epitaxy

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