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Ultralow thermal conductance across the [FePt/h- BN/FePt] interface

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arXiv 2024年

作者： Xu, Chengchao Zhang, Enbo Yang, Bo-Yuan Varaprasad, B.S.D.C.S. Laughlin, David E. Zhu, Jian-Gang Data Storage Systems Center Carnegie Mellon University PittsburghPA15213 United States Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA15213 United States Department of Materials Science and Engineering Carnegie Mellon University PittsburghPA15213 United States

Heat transfer in nanocomposite materials has attracted great interest for various applications. Multilayer structures provide an important platform to study interfacial thermal transport and to engineer materials with ultralow thermal conductivity. Here we report on the fabrication and thermal characterization of [h-BN/L10-FePt]×N multilayers, where hexagonal boron nitride (h-BN) nanosheets (2.5 nm thick) and L10-FePt layers (6.5 nm thick) alternate periodically. Differential three-omega(3ω) measurements reveal an ultralow effective thermal conductivity of 0.60 ± 0.05 W m-1K-1across the multilayer films, and a low thermal boundary conductance (TBC) of 67.9 ± 6.6 MW m-2K-1for the [FePt/h-BN(2.5nm)/FePt] interface at room temperature. We attribute the ultralow thermal conductivity to the weak van der Waals bonding at h-BN/FePt interfaces, which dominates the thermal resistance of the multilayer structure. These findings provide insights into the thermal transport in 2D-material/metal multilayer nanostructures and suggest the [h-BN/FePt] superlattice as a promising material for nanoscale thermal barrier coating. Furthermore, the obtained TBC lays the foundation for analyzing heat transfer in FePt-(h-BN) nanogranular films, a promising magnetic recording media which can potentially provide high thermal gradient for heat-assisted magnetic recording (HAMR). This work advances the understanding of thermal transport in 2D-material/metal nanocomposites and demonstrates interface engineering as an effective approach to achieve materials with ultralow thermal conductivity. Copyright © 2024, The Authors. All rights reserved.

关键词： Nanocomposites

Kinetic Monte Carlo Simulations of Sodium Ion Transport in NaSICON Electrodes

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arXiv 2023年

作者： Wang, Ziliang Mishra, Tara P. Xie, Weihang Deng, Zeyu Gautam, Gopalakrishnan Sai Cheetham, Anthony K. Canepa, Pieremanuele Department of Materials Science and Engineering National University of Singapore 9 Engineering Drive 1 117575 Singapore Department of Materials Engineering Indian Institute of Science Karnataka Bengaluru560012 India Singapore-MIT Alliance for Research and Technology 1 CREATE Way 10-01 CREATE Tower Singapore138602 Singapore Materials Department and Materials Research Laboratory University of California Santa BarbaraCA93106 United States Department of Electrical & Computer Engineering University of Houston HoustonTX77204 United States

The development of high-performance sodium (Na) ion batteries requires improved electrode materials. The energy and power densities of Na superionic conductor (NaSICON) electrode materials are promising for large-scale energy storage applications. However, several practical issues limit the full utilization of the theoretical energy densities of NaSICON electrodes. A pressing challenge lies in the limited sodium extraction in low Na content NaSICONs, e.g., Na1VIVVIV(PO4)3 ↔ VVVIV(PO4)3 + 1e− + 1Na+. Hence, it is important to quantify the Na-ion mobility in a broad range of NaSICON electrodes. Using a kinetic Monte Carlo approach bearing the accuracy of first-principles calculations, we elucidate the variability of Na-ion transport vs. Na content in three important NaSICON electrodes, NaxTi2(PO4)3, NaxV2(PO4)3, and NaxCr2(PO4)3. Our study suggests that Na+ transport in NaSICON electrodes is almost entirely determined by the local electrostatic and chemical environment set by the transition metal and the polyanionic scaffold. The competition with the ordering-disordering phenomena of Na-vacancies also plays a role in influencing Na-transport. We identify the Na content providing the highest room-temperature diffusivities in these electrodes, i.e., Na2.7Ti2(PO4)3, Na2.9V2(PO4)3, and Na2.6Cr2(PO4)3. We link the variations in the Na+ kinetic properties by analyzing the competition of ligand field stabilization transition metal ions and their ionic radii. We interpret the limited Na-extraction at x = 1 observed experimentally by gaining insights into the local Na-vacancy interplay. We propose that targeted chemical substitutions of transition metals disrupting local charge arrangements will be critical to reducing the occurrence of strong Na+-vacancy orderings at low Na concentrations, thus, expanding the accessible capacities of these electrode materials. Copyright © 2023, The Authors. All rights reserved.

关键词： Metal ions

Prediction of Post-COVID-19 Pandemic Learning Mode Preferences Using Machine Learning

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Prediction of Post-COVID-19 Pandemic Learning Mode Preferenc...

International Conference on Computing and Networking Technology (ICCNT)

作者： Agus Pratondo Astri Novianty Budi Laksono Putro Siska Komala Sari Department of Multimedia Engineering School of Applied Sciences Telkom University Bandung Indonesia Department of Computer Engineering School of Electrical Engineering Telkom University Bandung Indonesia Department of Computer Science Education Indonesia University of Education Bandung Indonesia Diploma Program of Information System School of Applied System Telkom University Bandung Indonesia

The COVID-19 epidemic has had a huge impact on the educational landscape, prompting the adoption of online and remote learning as viable alternatives to conventional in-person instruction. In order to create effective educational methods as institutions prepare for the post-pandemic period, it is essential to understand students' preferences for various learning modes. With the aid of machine learning techniques, this study seeks to forecast preferences for learning styles in post-pandemic higher education. The study made use of a dataset compiled from a wide range of college students, which included information on the institution type (public or private), program type (bachelor's or diploma), academic discipline (science or humanities), gender, year of study, internet use, communication costs, comorbidity status, vaccination history, gadget and laptop ownership, and preferred learning mode (online, in-person, or both). For the aim of prediction, a Support Vector Machine (SVM) was used. Its kernel functions included linear, polynomial, radial basis function (RBF), and sigmoid. Performance criteria like accuracy, precision, recall, and F1 score were used to assess the models after the dataset was randomly partitioned into training and testing sets. The findings showed that for identifying the preferred mode of learning, SVM with the RBF kernel had the highest prediction accuracy (91.67%). Further proving the RBF kernel's efficacy, the confusion matrix analysis showed that high values in the diagonal represented accurate predictions for each of the three classes (both online and onsite). The results imply that machine learning approaches, in particular SVM with the RBF kernel, may accurately forecast students' preferences for learning modes in the post-pandemic situation. In a post-pandemic society, the findings provide insightful information that may be used to build adaptable and inclusive learning models and put them into practice.

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Quantitative Modeling of Point Defects in β-Ga2O3 Combining Hybrid Functional Energetics with Semiconductor and Processes Thermodynamics

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arXiv 2025年

作者： Arnab, Khandakar Aaditta Stephens, Megan Maxfield, Isaac Lee, Channyung Ertekin, Elif Frodason, Ymir K. Varley, Joel B. Scarpulla, Michael A. Department of Materials Science and Engineering University of Utah Salt Lake CityUT84112 United States Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Materials Research Laboratory University of Illinois at Urbana-Champaign UrbanaIL61801 United States Centre for Materials Science and Nanotechnology Physics University of Oslo Oslo Norway Lawrence Livermore National Laboratory LivermoreCA93106 United States Department of Electrical and Computer Engineering University of Utah Salt Lake CityUT84112 United States

β-gallium oxide (β-Ga2O3) is of high interest for power electronics because of its unique combination of melt growth, epitaxial growth, n-type dopability, ultrawide bandgap, and high critical field. Optimization of crystal growth processes to promote beneficial defects and suppress harmful ones requires accurate quantitative modelling of both native and impurity defects. Herein we quantitatively model defect concentrations as a function of bulk crystal growth conditions and demonstrate the necessity of including effects such as bandgap temperature dependence, chemical potentials from thermochemistry, and defect vibrational entropy in modelling based on defect formation energies computed by density functional theory (DFT) with hybrid functionals. Without these contributions, grossly-erroneous and misleading predictions arise, e.g. that n-type doping attempts would be fully compensated by Ga vacancies. Including these effects reproduces the experimental facts that melt-grown Sn-doped β-Ga2O3 crystals are conductive with small compensation while annealing the same crystals in O2 at intermediate temperatures renders them insulating. To accomplish this modeling, we developed a comprehensive modelling framework (KROGER) based on calculated defect formation energies and flexible thermodynamic conditions. These capabilities allow KROGER to capture full and partial defect equilibria amongst native defects and impurities occurring during specific semiconductor growth or fabrication processes. We use KROGER to model 873 charge-states of 259 defects involving 19 elements in conditions representing bulk crystal growth by edge-fed growth (EFG) and annealing in oxygen. Our methodology is transferrable to a wide range of materials beyond β-Ga2O3. The integration of thermodynamic and first-principles modelling of point defects provides insight into optimization of point defect populations in growth and processing. Copyright © 2025, The Authors. All rights reserved.

关键词： Point defects

Selective-Area Growth of Gan and Algan Nanowires on N-Polar Gan Templates with 4° Miscut by Plasma-Assisted Molecular Beam Epitaxy

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SSRN

SSRN 2022年

作者： Khan, Kamruzzaman Jian, Zhe Li, Jonathan Sun, Kai Ahmadi, Elaheh Department of Materials Science and Engineering University of Michigan Ann Arbor United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States Applied Physics Program University of Michigan Ann Arbor United States

In this study, selective area growth (SAG)s of AlGaN/GaN nanowires (NWs) on miscut N-polar GaN templates were studied and compared with that grown on Ga-polar templates using plasma-assisted molecular beam epitaxy (MBE). The SAG of N-polar AlGaN/GaN NWs demonstrated higher growth rate and more growth selectivity than that of Ga-polar AlGaN/GaN NWs. Additionally, lateral growth rate of N-polar NWs was significantly lower than Ga-polar NWs. Compared to the pyramidal shaped top surfaces of Ga-polar NWs, the N-polar GaN NWs had flat head top surfaces. The combination of higher growth selectivity, larger growth window, negligible lateral growth, and flat head, makes N-polar (Al,Ga)N NWs attractive for a variety of applications including UV LEDs and detectors as well as quantum sensing. © 2022, The Authors. All rights reserved.

关键词： Aluminum gallium nitride

A Novel Design of Capacitive Plasmonic Near Field Transducer

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arXiv 2024年

作者： Du, Tianxiang Laughlin, David E. Zhu, Jian-Gang Data Storage Systems Center Carnegie Mellon University PittsburghPA15213 United States Department of Materials Science and Engineering Carnegie Mellon University PittsburghPA15213 United States Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA15213 United States

A near field transducer (NFT) is a key photonics component in heat assisted magnetic recording (HAMR) for the localized heating of the magnetic medium. In this work, we present a novel NFT design through capacitive coupling. In our design, tapered metal bars separated by thin dielectric materials with gap distance G are used to create the plasmonic resonance and focus the electromagnetic field. The design is motivated by the intention to improve thermal stability, which can be achieved through segmentation using thermally stable dielectric material between the plasmonic metal bars. Using COMSOL Multiphysics software, the performance of this capacitive-coupled NFT is systematically modeled. It is shown that the electromagnetic field could gradually be focused through the tapering towards the air bearing surface (ABS). In addition, the focusing effect could be enhanced with a smaller NFT peg size at the resonant wavelength. The material selection for the NFT tip material will be discussed to further address the thermal stability of the device. In conclusion, this capacitive-coupled NFT with dielectric separation gaps and tapering yields an enhanced |E| field intensity at the tip with the potential for an enhanced material thermal stability. Such a design can also exhibit applications in other energy delivery systems as well as plasmonic waveguides and sensors. © 2024, CC BY.

关键词： Multiphysics

IoT–based tire pressure monitoring system for air and temperature pressure using MPX5500D and LM35 sensor

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IoT–based tire pressure monitoring system for air and tempe...

International Conference on Computing, engineering, and Design (ICCED)

作者： Agung Pangestu Iing Sodikin Muhammad Yusro Rum Sapundani Rosyid Ridlo Al Hakim Sinka Wilyanti Electrical Engineering Department Faculty of Engineering and Computer Science Jakarta Global University Depok Indonesia Department of Electronic Engineering Faculty of Engineering State University of Jakarta Jakarta Indonesia Electromedical Engineering Technology Faculty of Health Science University of Muhammadiyah Purwokerto Purwokerto Indonesia Graduate Program in Electrical Engineering Faculty of Engineering and Computer Science Jakarta Global University Depok Indonesia

ISBN: (纸本)9781665453905

Research has been carried out to monitor vehicle tires before they are used and can reduce damage, including overcoming vehicle fuel waste because air pressure is continuously monitored. This research aims to utilize the MPX5500DP sensor as an air pressure device, the LM35 sensor as a temperature reader, and a buzzer based on IoT to build a tire pressure monitoring system (TPMS). The MPX5500DP and LM35 sensor inputs to the Arduino Uno microcontroller are distributed by the NodeMCU, fitted with a Wi-Fi module. The Blynk application sends and displays the data on a smartphone using the IoT-based. Based on this research, data on the percentage of errors in monitoring air pressure and tire temperature on vehicles were obtained by comparing the data to the pressure gauge and thermometer: 1—the results of the average reading of the sensor error value. MPX5500DP air pressure against pressure gauge is 5.3%. 2—the average reading of the LM35 sensor error value on the temperature thermometer is 6.8%. With this research, the air pressure and temperature in the tires can be monitored in real-time via a smartphone using the IoT-based.

关键词： Temperature measurement Temperature distribution Thermometers Microcontrollers Tire pressure Real-time systems Pressure gauges

A Comparison of CdS and Zn(O,S) Buffer Layers in (Ag,Cu)(In,Ga)Se2 Solar Cells

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A Comparison of CdS and Zn(O,S) Buffer Layers in (Ag,Cu)(In,...

IEEE Conference Photovoltaic Specialists (PVSC)

作者： Michael F. Miller Ana Kanevce Marzieh Baan Rico Gutzler Darius Kuciauskas Theresa Magorian Friedlmeier Tyler J. Grassman Aaron R. Arehart Department of Electrical & Computer Engineering The Ohio State University Columbus OH USA Zentrum fuer Sonnenenergie-und Wasserstoff-Forschung (ZSW) Stuttgart Germany Department of Materials Science & Engineering The Ohio State University Columbus OH USA National Renewable Energy Laboratory Golden CO USA

ISBN: (数字)9781665464260

ISBN: (纸本)9781665475822

Cu(In,Ga)Se 2 -based solar cells typically use a $C$ dS buffer layer, even though its relatively low bandgap causes parasitic absorption. While alternatives to CdS have been explored in other studies, limited results have been shown for Ag-alloyed CIGS (ACIGS). In this study, ACIGS solar cells with both CdS and Zn(O,S) buffer layers were fabricated and compared for solar cell performance. The Zn(O,S) buffer slightly improved J sc through reduced absorption, although surface optimization is necessary. The Zn(O,S) ACIGS also had improved FF through reduced series resistance and ideality factor, which could be improved further through optimization. However, the Voc in the Zn(O,S) samples was reduced, likely due to increased bulk and front interface recombination. This study shows the promise of Zn(O,S) as a buffer layer in ACIGS solar cells and suggests pathways for further improvement.

关键词： Buffer layers Photovoltaic systems Absorption Photonic band gap Photovoltaic cells Surface resistance Loss measurement Capacitance measurement Optimization

Compact Micro-Stereolithographic (SLA) Printed, 3D Microelectrode Arrays (3D MEAS) with Monolithically Defined Positive and Negative Relief Features for in Vitro Cardiac Beat Sensing 35

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Compact Micro-Stereolithographic (SLA) Printed, 3D Microelec...

35th IEEE International Conference on Micro Electro Mechanical Systems Conference, MEMS 2022

作者： Didier, Charles M. Kundu, Avra Castro, Jorge Manrique Hart, Cacie Rajaraman, Swaminathan NanoScience Technology Center University of Central Florida OrlandoFL32816 United States Burnett School of Biomedical Sciences University of Central Florida OrlandoFL32816 United States College of Engineering and Computer Sciences University of Central Florida OrlandoFL32816 United States Department of Electrical and Computer Engineering University of Central Florida OrlandoFL32816 United States Department of Materials Science and Engineering University of Central Florida OrlandoFL32816 United States

ISBN: (纸本)9781665409117

We demonstrate a novel microfabrication and assembly strategy for the realization of 3D Microelectrode Arrays (3D MEAs) in compact form-factors. An optimized Micro-Stereolithographic (SLA) 3D printing process was utilized to ensure complete definition of both positive and negative relief features. electrical contacts (traces, pads, and electrodes) were established with thin-film metallization through a shadow mask and double-side processing, and the functional Insulation material and subsequent culturing area was defined utilizing a biolaminate layer. In this work, we present the results of this fabrication, impedance spectroscopy, root mean square (RMS) noise characterization, laser confocal analysis of the defined vias, along with optical and SEM imaging of the platform and electrophysiological spike data from a confluent HL-1 cardiac cell culture at 7 DIV (days in vitro). © 2022 IEEE.

关键词： Cell culture