检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Li, Kejia Khamdang, Chadawan Wang, Mengen Department of Electrical and Computer Engineering State University of New York at Binghamton BinghamtonNY13902 United States Materials Science and Engineering Program State University of New York at Binghamton BinghamtonNY13902 United States

CsSnI3 is widely studied as an environmentally friendly Pb-free perovskite material for optoelectronic device applications. To further improve material and device performance, it is important to understand the surface structures of CsSnI3. We generate surface structures with various stoichiometries, perform density functional theory calculations to create phase diagrams of the CsSnI3 (001), (110), and (100) surfaces, and determine the most stable surfaces under a wide range of Cs, Sn, and I chemical potentials. Under I-rich conditions, surfaces with Cs vacancies are stable, which lead to partially occupied surface states above the valence band maximum. Under I-poor conditions, we find the stoichiometric (100) surface to be stable under a wide region of the phase diagram, which does not have any surface states and can contribute to long charge carrier lifetimes. Consequently, the I-poor (Sn-rich) conditions will be more beneficial to improve the device performance. © 2024, CC BY-NC-SA.

关键词： Tin compounds

来源：评论

学校读者我要写书评

暂无评论

Energy Efficient Stochastic Signal Manipulation in Superparamagnetic Tunnel Junctions via Voltage-Controlled Exchange Coupling

arXiv

引用

arXiv 2024年

作者： Jia, Qi Benally, Onri J. Zink, Brandon Zhang, Delin Lv, Yang Liang, Shuang Lyu, Deyuan Chen, Yu-Chia Yang, Yifei Huang, Yu Han Wang, Jian-Ping Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States Department of Chemical Engineering and Materials Science University of Minnesota MinneapolisMN55455 United States Department of Materials Science and Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

Superparamagnetic tunnel junctions (sMTJs) are emerging as promising components for stochastic units in neuromorphic computing, owing to their tunable random switching behavior. Conventional MTJ control methods, such as spin-transfer torque (STT) and spin-orbit torque (SOT), often require substantial power. Here, we introduce the voltage-controlled exchange coupling (VCEC) mechanism, enabling switching between antiparallel and parallel states in sMTJs with an ultralow power consumption of only 40 nW, approximately two orders of magnitude lower than conventional STT-based sMTJs. This mechanism yields a sigmoid-shaped output response, making it ideally suited for neuromorphic computing applications. Furthermore, we validate the feasibility of integrating VCEC with the SOT current control, offering an additional dimension for magnetic state manipulation. This work marks the first practical demonstration of VCEC effect in sMTJs, highlighting its potential as a low-power control solution for probabilistic bits in advanced computing systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Generation and manipulation of skyrmions and other topological spin structures with rare metals

引用

Rare Metals 2022年第7期41卷 2200-2216页

作者： Chu Ye Lin-Lin Li Yun Shu Qian-Rui Li Jing Xia Zhi-Peng Hou Yan Zhou Xiao-Xi Liu Yun-You Yang Guo-Ping Zhao College of Physics and Electronic Engineering Sichuan Normal UniversityChengdu 610068China Center for Magnetism and Spintronics Sichuan Normal UniversityChengdu 610068China Guangdong Provincial Key Laboratory of Optical Information Materials and Technology Guangzhou 510006China Institute for Advanced Materials South China Normal UniversitySouth China Academy of Advanced OptoeletronicsGuangzhou 510006China School of Science and Engineering The Chinese University of Hong KongShenzhen 518172China Department of Electrical and Computer Engineering Shinshu UniversityNagano 380-8553Japan

Skyrmions are nano-scale quasi-particles with topological protection,which have potential applications in next-generation spintronics-based information *** papers have been published to review various aspects of skyrmions,including physics,materials and ***,no review paper has focused on rare metals which play important roles in nucleating and manipulating skyrmions and other topological *** this paper,various roles of rare metals have been classified and summarized,which can tune Curie temperature(TC),Dzyaloshinskii-Moriya interaction(DMI),magnetocrystalline anisotropy,Ruderman-Kittel-Kasuya-Yosida(RKKY)interaction and four-spin interaction so as to trigger the generation of skyrmions and other topological spin *** materials covered include typical B20 crystals,various layered systems with interfacial DMI,frustrated materials,antiferromagnets,ferrimagnets,twodimensional(2D)materials,*** addition,the rare-earth(RE)permanent magnets can provide an energy barrier and enrich the dynamic behaviors of skyrmions,which has also been reviewed.

关键词： Magnetic skyrmions Rare metals Generation and manipulation

来源：评论

学校读者我要写书评

暂无评论

Thermo-optic Properties in PECVD Silicon Rich Silicon Carbide

Thermo-optic Properties in PECVD Silicon Rich Silicon Carbid...

引用

Novel Optical materials and Applications, NOMA 2022

作者： Chang, Li-Yang Sunny Pappert, Steve Yu, Paul K.L. Materials Science and Engineering Program University of California 9500 Gilman Drive La Jolla San DiegoCA92093 United States Department of Electrical and Computer Engineering University of California 9500 Gilman Drive La Jolla San DiegoCA92093 United States

We study the thermo-optic coefficient of silicon carbide with different silicon content. We demonstrate a clear trend between the silicon content and the thermo-optic coefficient which measured as high as 1.88×10... 详细信息

ISBN: (纸本)9781557528209

关键词： Silicon carbide

来源：评论

学校读者我要写书评

暂无评论

Defect formation in CsSnI3 from Density Functional Theory and Machine Learning

arXiv

引用

arXiv 2024年

作者： Khamdang, Chadawan Wang, Mengen Department of Electrical and Computer Engineering State University of New York at Binghamton BinghamtonNY13902 United States Materials Science and Engineering Program State University of New York at Binghamton BinghamtonNY13902 United States

Sn-based perovskites as low-toxicity materials are actively studied for optoelectronic applications. However, their performance is limited by p-type self-doping, which can be suppressed by substitutional doping on the cation sites. In this study, we combine density functional theory (DFT) calculations with machine learning (ML) to develop a predictive model and identify the key descriptors affecting formation energy and charge transition levels of the substitutional dopants in CsSnI3. Our DFT calculations create a dataset of formation energies and charge transition levels and show that Y, Sc, Al, Zr, Nb, Ba, and Sr are effective dopants that pin the Fermi level higher in the band gap, suppressing the p-type self-doping. We explore ML algorithms and propose training a random forest regression model to predict the defect formation properties. This work shows the predictive capability of combining DFT with machine learning and provides insights into the important features that determine the defect formation energetics. © 2024, CC BY-NC-SA.

关键词： Perovskite

来源：评论

学校读者我要写书评

暂无评论

Genetic Algorithm-Based Feature Selection for Accurate Breast Cancer Classification

Genetic Algorithm-Based Feature Selection for Accurate Breas...

引用

2023 International Conference on IT and Industrial Technologies, ICIT 2023

作者： Shabbir, Attia Ali, Raja Hashim Shabbir, Muhammad Zeeshan Abideen, Zain Ul Khan, Talha Ali Ijaz, Ali Zeeshan Ali, Nisar Imad, Muhammad Bakar, Muhammad Abu Gik Institute of Engg. Sciences & Technology Faculty of Computer Science & Engineering Topi Pakistan University of Europe for Applied Sciences Dept. of Technology & Software Engineering Berlin Germany Department of Electrical Engineering Lahore Pakistan BCMaterials Basque Center for Materials Applications & Nanostructure Basque Country Leioa Spain University of Regina Faculty of Electronic Systems Engineering Regina Canada

ISBN: (纸本)9798350315974

Breast cancer is a significant global healthcare challenge, particularly in developing and underdeveloped countries, with profound physical, emotional, and psychological consequences, including mortality. Timely diagnosis and accurate treatment are crucial in addressing this issue. We propose the utilization of a feature selection technique to identify the most relevant features from among all features for breast cancer diagnosis, and show that Genetic Algorithms are impressive for this task. The study compares the results of GA with no selection and an alternative method, Principle Component Analysis (PCA). Three machine learning models, all based on supervised learning with data split into training and test data, are employed for binary classification using the selected feature subset. The evaluation metrics employed encompass accuracy, precision, recall, and F1-score. Among the selected models, Random Forest demonstrates the most favorable outcomes, achieving an accuracy score of 0.96, precision score of 0.96, recall value of 0.98, and an F1-score of 0.97. These results underscore the effectiveness of GA in feature selection for breast cancer diagnosis. Consequently, the integration of Genetic Algorithms (GA) with Random Forest showcases the superior performance among the evaluated models. © 2023 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Writable and Erasable Second Harmonic Generation from Crystal-Derived All-Glass Optical Fibers

Writable and Erasable Second Harmonic Generation from Crysta...

引用

2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Pietros, Alexander R. Rebeszko, Kacper Hawkins, Thomas Cavillon, Maxime Ballato, John Dragic, Peter D. Laboratory The Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign 208 N Wright St UrbanaIL61801 United States The Department of Materials Science and Engineering Clemson University 91 Technology Drive AndersonSC29625 United States Université Pans-Saclay CNRS Orsay91400 France

All glass optical fibers drawn from crystalline precursors via the molten core method demonstrate instantaneous and greatly enhanced second harmonic generation. Results when pumping in the NIR at relatively low powers... 详细信息

ISBN: (纸本)9781957171258

关键词： Harmonic generation

来源：评论

学校读者我要写书评

暂无评论

ConvNeXt Model for Breast Cancer Image Classification

ConvNeXt Model for Breast Cancer Image Classification

引用

International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Devin Setiawan Andrea Stevens Karnyoto Indo Intan Bens Pardamean Department of Electrical Engineering and Computer Science University of Kansas Lawrence United States Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Informatics Engineering Universitas Dipa Makassar Makassar Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331539603

ISBN: (纸本)9798331539610

Breast cancer is an occurrence of cancer that attacks breast tissue and is the most common cancer among women worldwide, affecting one in eight women. In this modern world, breast cancer image classification simplifies the process of analyzing, providing objective and accurate results. By leveraging machine learning algorithms and computer vision techniques, we developed breast cancer detection. The dataset is histopathology dataset from BreakHis and UNHAS Hospital. We chose the ConvNeXt-Tiny model then modified the classifier head as the proposed method. Before the dataset is processed by the model, we augment the images by applying random horizontal and vertical flips, adjustments to brightness, contrast, saturation, and hue using color jitter. The augmentation process simulates real-world variance and enhances the model's ability to generalize to unseen data. Our proposed model gained better performance (accuracy, F1-Score) results compared two other techniques to VGG16 and SVM. According to our experiments, the F1-Score for the ConvNeXt-Tiny model with classifier head modification is higher at 0.9516, than the gain for VGG16 at 0.9292, and the gain for the SVM at 0.83.

关键词： Support vector machines Accuracy Head Computational modeling Transfer learning Breast cancer Magnetic heads Data models Reliability Image classification

来源：评论

学校读者我要写书评

暂无评论

Computational search for materials having a giant anomalous Hall effect in the pyrochlore and spinel crystal structures

arXiv

引用

arXiv 2025年

作者： Sullivan, Sean Lee, Seungjun Szymanski, Nathan J. Merchant, Amil Cubuk, Ekin Dogus Low, Tony Bartel, Christopher J. Department of Chemical Engineering and Materials Science University of Minnesota MinneapolisMN55455 United States Department of Electrical Engineering and Computer Engineering University of Minnesota MinneapolisMN55455 United States Google DeepMind United Kingdom

Ferromagnetic pyrochlore and spinel materials with topological flat bands are of interest for their potential to exhibit a giant anomalous Hall effect (AHE). In this work, we present computational predictions of stability and electronic structure for 448 compositions within the pyrochlore (A2B2O7) and spinel (AB2O4) frameworks. Of these, 92 are predicted to be thermodynamically stable or close (2Ir2O7 exhibits an exceptionally high AHA of 0.728 when its Fermi level is optimized. These findings provide a roadmap for the targeted synthesis of new pyrochlore and spinel compounds with enhanced AHE properties. They also broaden the compositional design space for these structures and support the discovery of high-performance materials for next-generation spintronic applications. Copyright © 2025, The Authors. All rights reserved.

关键词： Crystal atomic structure

来源：评论

学校读者我要写书评

暂无评论

NCU-IISR/AS-GIS: Using BERTScore and Snippet Score to Improve the Performance of Pretrained Language Model in BioASQ 10b Phase B

NCU-IISR/AS-GIS: Using BERTScore and Snippet Score to Improv...

引用

2022 Conference and Labs of the Evaluation Forum, CLEF 2022

作者： Ting, Hao-Hsuan Zhang, Yu Han, Jen-Chieh Tsai, Richard Tzong-Han Interdisciplinary Program of Electrical Engineering and Computer Science National Central University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan IoX Center National Taiwan University Taiwan Research Center for Humanities and Social Sciences Academia Sinica Taiwan

This paper presents our system for the BioASQ10b Phase B task. For ideal answers, we used the fine-tuned BioBERT model on the MNLI dataset to construct sentence embeddings and combined it with BERTScore to select sentences from the provided Snippets as answers. For the exact answers, we also used the BioBERT model and used the snippet scores generated from the ideal answer selection model to predict the exact answers for factoid and list questions. The exact answers of our fifth test batch ranked second place. In addition, the ideal answers we submitted achieved first place in the ROUGE score in all test batches from batch second to fifth. © 2022 Copyright for this paper by its authors.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：