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arXiv 2020年

作者： Lawrence, Nick Shen, Mingren Yin, Ruiqi Feng, Cloris Morgan, Dane Department of Materials Science and Engineering University of Wisconsin-Madison MadisonWI53706 United States Department of Industrial & Systems Engineering University of Wisconsin-Madison MadisonWI53706 United States Department of Computer Science University of Wisconsin-Madison MadisonWI53706 United States Department of Electrical & Computer Engineering University of Wisconsin-Madison MadisonWI53706 United States

The use of accurate scanning transmission electron microscopy (STEM) image simulation methods require large computation times that can make their use infeasible for the simulation of many images. Other simulation methods based on linear imaging models, such as the convolution method, are much faster but are too inaccurate to be used in application. In this paper, we explore deep learning models that attempt to translate a STEM image produced by the convolution method to a prediction of the high accuracy multislice image. We then compare our results to those of regression methods. We find that using the deep learning model Generative Adversarial Network (GAN) provides us with the best results and performs at a similar accuracy level to previous regression models on the same dataset. Codes and data for this project can be found in this GitHub repository, https://***/uw-cmg/GAN-STEM-Conv2MultiSlice. © 2020, CC BY.

关键词： Generative adversarial networks

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A Circuit for Evaluating GaN HEMT Dynamic Rds(on) at Cryogenic Temperatures

A Circuit for Evaluating GaN HEMT Dynamic Rds(on) at Cryogen...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Charley Shi Suzanne Lo Duleepa J. Thrimawithana Francesca Adams Aaron Wadsworth Matthew G.S. Pearce Rachel A. Oliver David J. Wallis Rodney A. Badcock Department of Electrical Computer and Software Engineering The University of Auckland New Zealand Department of Materials Science and Metallurgy University of Cambridge United Kingdom Department of Engineering Cardiff University United Kingdom Robinson Research Institute Victoria University of Wellington New Zealand

ISBN: (数字)9798350351156

ISBN: (纸本)9798350351163

GaN HEMTs are promising power switching devices for cryogenic power converters in superconducting motor drives and space applications. However, GaN HEMTs experience dynamic on-resistance R ds(on) which is not well understood at cryogenic temperatures (CT). This paper presents a circuit for evaluating the dynamic R ds(on) of GaN HEMTs at CT by using on-the-fly measurements to capture off-state trapping transients. The evaluation circuit utilises a measurement circuit with a blocking switch to accurately measure the V ds. Due to the much lower R ds(on) at CT than room temperature (RT), an amplifier was implemented to amplify the output of the measurement circuit, for which the performance is validated using a coaxial shunt resistor. Results demonstrate that the circuit can successfully measure the dynamic R ds(on) 2 μs after the device turns on at both RT and 77 K.

关键词： Current measurement Cryogenics Switches HEMTs Clamps MODFETs Transient analysis Voltage control Stress Switching circuits

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Picosecond response of metal-semiconductor-metal ultraviolet phootodiodes

Picosecond response of metal-semiconductor-metal ultraviolet...

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Conference on Lasers and Electro-Optics, CLEO

作者： Li, Jianliang Donaldson, W.R. Hsiang, T.Y. University of Rochester Material Science Program Laboratory for Laser Energetics 250 East River Road Rochester NY 14623 United States Laboratory for Laser Energetics University of Rochester 250 East River Road Rochester NY 14623-1299 United States Department of Electrical and Computer Engineering University of Rochester Rochester NY 14627 United States

We studied the ultrafast response in metal-semiconductor-metal ultraviolet photodiodes fabricated on GaN. The best performance of a device with 1-μmn finger width and spacing showed a 3.5-ps response. The pulse width... 详细信息

关键词： Photodiodes

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Cost-effective search for lower-error region in material parameter space using multifidelity Gaussian process modeling

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Physical Review materials 2020年第8期4卷 083802-083802页

作者： Shion Takeno Yuhki Tsukada Hitoshi Fukuoka Toshiyuki Koyama Motoki Shiga Masayuki Karasuyama Department of Computer Science Graduate School of Engineering Nagoya Institute of Technology Gokiso-cho Showa-ku Nagoya 466-8555 Japan Center for Advanced Intelligence Project RIKEN 1-4-1 Nihonbashi Chuo-ku Tokyo 103-0027 Japan Department of Materials Design Innovation Engineering Graduate School of Engineering Nagoya University Furo-cho Chikusa-ku Nagoya 464-8603 Japan JST PRESTO 4-1-8 Honcho Kawaguchi Saitama 332-0012 Japan Department of Electrical Electronic and Computer Engineering Faculty of Engineering Gifu University 1-1 Yanagido Gifu 501-1193 Japan Center for Materials Research by Information Integration National Institute for Materials Science 1-2-1 Sengen Tsukuba Ibaraki 305-0047 Japan

Information regarding precipitate shapes is critical for estimating material parameters. Hence, we considered estimating a region of material parameter space in which a computational model produces precipitates having shapes similar to those observed in the experimental images. This region, called the lower-error region (LER), reflects intrinsic information of the material contained in the precipitate shapes. However, the computational cost of LER estimation can be high because the accurate computation of the model is required many times to better explore parameters. To overcome this difficulty, we used a Gaussian-process-based multifidelity modeling, in which training data can be sampled from multiple computations with different accuracy levels (fidelity). Lower-fidelity samples may have lower accuracy, but the computational cost is lower than that for higher-fidelity samples. Our proposed sampling procedure iteratively determines the most cost-effective pair of a point and a fidelity level for enhancing the accuracy of LER estimation. We demonstrated the efficiency of our method through estimation of the interface energy and lattice mismatch between MgZn2 and α−Mg phases in an Mg-based alloy. The results showed that the sampling cost required to obtain accurate LER estimation could be drastically reduced.

关键词： Coarse graining Machine learning

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Analysis of the dynamics and topology dependencies of small perturbations in electric transmission grids

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Physical Review E 2020年第1期101卷 012313-012313页

作者： Luiscarlos A. Torres-Sánchez Giuseppe T. Freitas de Abreu Stefan Kettemann Department of Energy Division Decon International GmbH 61352 Bad Homburg Germany Department of Computer Science and Electrical Engineering Jacobs University Bremen 28759 Bremen Germany Department of Physics and Earth Science Jacobs University Bremen 28759 Bremen Germany Division of Advanced Materials Science Pohang University of Science and Technology Pohang 790-784 South Korea

We study the phase dynamics in power grids in response to small disturbances and how this depends on the grid topology. To this end, we consider the swing equations in linear order in phase disturbances and solve the resulting linear wave equation, deriving the eigenmodes of the weighted graph Laplacian. A linear response expression for the deviation of frequency is given in terms of these eigenvalues and eigenvectors, which it is argued to be the basis for future power system stabilizers and other control measures in power systems. As an example, we present results for random networks based on the Watts-Strogatz model, where we observe a transition to localized eigenstates as the randomness in the degree distribution grows. Moreover, it is found that localization leads to faster decay rates. Thereby, disturbances are found to remain localized on a few nodes where they decay faster. Finally, we also consider the German transmission grid topology, where the eigenstate of the lowest eigenfrequency, the Fiedler vector, is found to be extended, with large intensities at the northwestern and southern boundaries.

关键词： Coupled oscillators Network structure Topological tools

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Load Manipulation by a Triangular Formation of Quadrotors

Load Manipulation by a Triangular Formation of Quadrotors

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Valentim Ernandes Neto Alexandre Santos Brandão Mário Sarcinelli-Filho Graduate Program on Electrical Engineering Federal University of Espírito Santo Vitória ES Brazil Núcleo de Especialização em Robótica Department of Electrical Engineering and Graduate Program on Computer Science Federal University of Viçosa Viçosa MG Brazil

ISBN: (数字)9781728142784

ISBN: (纸本)9781728142791

This work discusses a trajectory tracking task accomplished by a group of three Bebop 2 quadrotors working cooperatively to transport a load. Such unmanned aerial vehicles (UAVs) are considered as a triangular formation, and the load, a triangle-shaped structure, is attached to them through massless flexible cables. The reason to use three quadrotors is the gain in terms of the payload capability and the stability of the load, since it is attached to three vehicles, staying vertically aligned with the center of mass of the triangle correspondent to the formation. A formation controller, actually a kinematic controller applied to a virtual massless robot correspondent to the center of mass of the triangle, is adopted, which generates reference velocities for the three UAVs, whose movement generates the movement and reshaping of the triangular formation. Then, individual dynamic compensators are adopted for each UAV, whose input is the reference velocity delivered by the formation controller. Finally, experimental results are discussed, which validate the proposal.

关键词： Vehicle dynamics Aerodynamics Atmospheric modeling Aircraft Robot kinematics Mathematical model

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Fully Epitaxial, Reconfigurable Ferroelectric ScAlN/AlGaN/GaN HEMTs

Fully Epitaxial, Reconfigurable Ferroelectric ScAlN/AlGaN/Ga...

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Device Research Conference

作者： Ding Wang Ping Wang Minming He Jiangnan Liu Shubham Mondal Mingtao Hu Danhao Wang Yuanpeng Wu Tao Ma Zetian Mi Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA Michigan Center for Materials Characterization (MC) University of Michigan Ann Arbor MI USA

Reconfigurable devices and circuits have long been sought for their flexibility, cost reduction, energy efficiency, scalability, and versatility. One good example of a reconfigurable device is a ferroelectric transistor, where the carrier concentration in the channel can be programmed due to the gradual switching properties of ferroelectrics. There have been ongoing efforts to further introduce ferroelectrics into high electron mobility transistors, which could enable enhanced-mode operation, dynamic V th tuning, and reconfigurable radio-frequency/microwave applications. 1, 2 Recent studies have demonstrated that by alloying IIIB element, e.g., Sc, with conventional III-nitride semiconductors, the polarity switching barrier of III-nitride materials could be greatly reduced, resulting in a new class of ferroelectric materials with giant polarization, including ScAlN and ScGaN. 3–5 The giant polarization provides ample design space for ferroelectric charge coupling in the channel, potentially supporting broader threshold voltage tuning window, which is tantalizing for memory and reconfigurable RF/microwave applications. 6, 7 Herein, we report the first experimental demonstration of ferroelectric switching in ultrathin (5 nm) ScAlN, as well as the realization of fully epitaxial ScAlN/AlGaN/GaN based ferroelectric high electron mobility transistors (FeHEMTs).

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Extraordinary thermal conductivity of graphene: Possibility of thermal management applications

Extraordinary thermal conductivity of graphene: Possibility ...

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Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITHERM)

作者： S. Ghosh S. Subrina V. Goyal D.L. Nika E.P. Pokatilov A.A. Balandina Intel Corporation Hillsboro Oregon U.S.A. Department of Electrical Engineering and Materials Science and Engineering Program University of California - Riverside Riverside CA U.S.A. University of California Riverside Riverside CA US

ISBN: (纸本)9781424453429;9781424453436

We review the results of our investigation of the thermal conductivity of the suspended single-layer graphene. Using an original non-contact optical technique we discovered experimentally that the thermal conductivity of suspended graphene flakes with low coupling to the substrate is extremely high and can exceeds that of bulk graphite and carbon nanotubes. The high values of the thermal conductivity of graphene and their dependence on the graphene flake size were explained within the framework of Klemens theory. Superior thermal properties of graphene benefit all proposed graphene device applications and may lead to new high-heat flux thermal management solutions for advanced electronics.

关键词： Thermal conductivity Thermal management Thermal management of electronics Phonons Optical scattering Temperature Conducting materials Brillouin scattering Conductivity measurement Ultraviolet sources

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Linking Molecular Origin of Melt Fragility Index with Topological Phases of Network Glasses

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SSRN 2024年

作者： Gogi, Vamshi Kiran Mandal, Avik Welton, Aaron Mohanty, Chandi Bhosle, Siddhesh Chakraborty, Shibalik Gunasekera, Kapila Chakravarty, Soumendu Almutairi, Badriah Boolchand, Punit Department of Electrical Engineering and Computer Science University of Cincinnati CincinnatiOH45221-0030 United States Department of Mechanical and Materials Engineering University of Cincinnati CincinnatiOH United States Department of Physics University of Cincinnati CincinnatiOH United States

Network glasses are composed of three topological phases: flexible, intermediate, and stressed-rigid. Intermediate Phase (IP) glasses form compact, rigid, and stress-free networks with no Open Degrees of Freedom (ODF). IP melts are observed to be super-strong with the lowest fragility index, m = 15 due to the absence of ODF in the parent glass. This feature is general and observed in multiple selenide, sulfide, and modified oxide glasses can be traced to Isostatically Rigid Local Structures (ISRLSs) formed in the IP. On the other hand, the flexible and stressed-rigid phase glasses form non-compacted and stressed networks with increasing residual pressure as the count of ODF increases. Their melts are found to be fragile and display fragility indices m > 20 as the count of the ODF in the glass increases and the count of ISRLSs dissipates. © 2024, The Authors. All rights reserved.

关键词： Glass

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An Improved Network Segmentation Performance in Lesion Segmentation based on Mask R-CNN

An Improved Network Segmentation Performance in Lesion Segme...

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International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： T. Thivya C. Kalaivanan N. Juliet Vengadapathiraj M G. Mary Valantina V. Mohanavel Department of Information Technology Velammal Engineering College Chennai Department of Electrical and Electronics Engineering Sona College of Technology Salem Department of Master of Computer Application S.A Engineering College Chennai Department of Electronics and Communication Engineering Rajalakshmi Instittue of Technology Chennai Department of Computer Science and Engineering Saveetha School of Engineering SIMATS Chennai Centre for Materials Engineering and Regenerative Medicine Bharath Institute of Higher Education and Research Chennai Tamil Nadu India Department of Mechanical Engineering Chandigarh University Mohali Punjab India

ISBN: (纸本)9781665482721

Computational intelligence has grown increasingly common in the analysis of healthcare data in recent years. The deep learning algorithms, in instance, have such a number of fruitful implications in the analysis of medical images. This research study has presented a double awareness deep convolution network-based system for end-to-end healthcare lesion classification. Several fully supervised and poorly supervised extracted features are included in this framework. The issue of the high cost of pixel-level labels with lesions in the medical pictures is alleviated by the weakly supervised segmentation module's use of bounding-box labels of lesion regions, which allows for correct lesion segmentation to be accomplished. In addition to this, a dual attention mechanism has been included for the purpose of improving the network's capacity for visual feature learning. The dual attention mechanism, which consists of both channel and spatial attention, may assist in drawing the network's attention to the extraction of features from significant locations. It is possible for it to considerably minimize the gaps between ground-truth labels and pseudo labels, in comparison to the current standard approach of weakly supervised segmentation using pseudo labels. Final results show that our proposed approach beat the competitors on to an oral disease collection, while our approach was extended to incorporate dermatological disease categorization in the ultimate analysis.

关键词： Representation learning Deep learning Visualization Costs Medical services Feature extraction Lesions

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