检索结果-内蒙古大学图书馆

Small Polaron-Induced Ultrafast Ferroelectric Restoration in BiFeO3

Physical Review X 2025年第2期15卷 021046-021046页

作者： Wenfan Chen Tian Wang Chun-Chieh Yu Yuancheng Jing Xiaosong Li Wei Xiong Materials Science and Engineering Program University of California San Diego La Jolla California 92093 USA Department of Chemistry University of Washington Seattle Washington 98195 USA Department of Chemistry University of California San Diego La Jolla California 92093 USA Department of Electrical and Computer Science Engineering University of California San Diego La Jolla California 92093 USA

In this report, we apply a suite of ultrafast spectroscopic techniques and advanced calculations to reveal the interplay between electronic and lattice degrees of freedom in ferroelectric BiFeO3. Using transient sum frequency generation spectroscopy, which is sensitive to electronic polarizations, we observe a transient electronic dipole reduction upon optical excitation which recovers at 0.5 and 10 ps timescale. The time-dependent density functional theory calculation reveals that both ligand-metal charge transfer and local excitation transition occurred upon photo excitation. To reveal the nature of electronic dipole restoration, we employ transient extreme ultraviolet (EUV) spectroscopy—an element-specific ultrafast technique that follows charge dynamics of Bi, Fe, and O altogether. The transient EUV dynamics observed both ultrafast free charge carrier relaxation to excitons, as well as polaron formation. However, a timescale comparison suggests that only the polaron formation is responsible for the 0.5 ps electronic dipole restoration, whereas the faster electronic relaxation does not contribute to the ferroelectric property changes. Multireference configuration interaction calculation further corroborates this result by showing both Fe and Bi atoms shift from the ground state equilibrium—leading to the polaron formation. Our result disentangles the multidegrees of freedom in ultrafast ferroelectric modulation and identifies the pivotal motion—a local polaron formation—for the fast ferroelectric recovery. It provides crucial insights on the specific lattice distortion that could modulate properties or phase transitions of condensed matter materials.

关键词： Light polarization

来源：评论

学校读者我要写书评

暂无评论

Imaging the evolution of lithium-solid electrolyte interface using operando scanning electron microscopy

引用

Nature Communications 2025年第1期16卷 1-11页

作者： Zhao, Lihong Feng, Min Wu, Chaoshan Guo, Liqun Chen, Zhaoyang Risal, Samprash Ai, Qing Lou, Jun Fan, Zheng Qi, Yue Yao, Yan Department of Electrical and Computer Engineering and Texas Center for Superconductivity at the University of Houston University of Houston Houston TX United States School of Engineering Brown University Providence RI United States Materials Science and Engineering Program University of Houston Houston TX United States Department of Materials Science and Nanoengineering and the Rice Advanced Materials Institute Rice University Houston TX United States Department of Engineering Technology University of Houston Houston TX United States

The quality of Li–solid electrolyte interface is crucial for the performance of solid-state lithium metal batteries, particularly at low stack pressure, but its dynamics during cell operation remain poorly understood due to a lack of reliable operando characterization techniques. Here, we report the evolution of Li–electrolyte interface with high spatial resolution using operando scanning electron microscopy under realistic operating conditions. By tracking the stripping process of both Li and Li-rich Li-Mg alloy anodes, we show that multiple voids coalesce into a single gap and eventually delaminate the interface in Li, whereas the voids split and collapse to partially recover interfacial contact in Li-Mg. Density functional theory calculations show that the stronger Mg-S interaction at the metal–electrolyte interface attracts Mg toward the interface and repels Li-vacancies into the bulk, resulting in a reduced number of voids. The pressure-dependent voltage profiles of Li and Li-Mg stripping suggest that loss of contact due to void formation, rather than Mg accumulation at the interface, is the origin of high overpotential that limits the utilization of metal anodes. Improved interfacial contact enables stable cycling of all-solid-state lithium full cell at low stack pressure (1 MPa) and moderate rate (2 mA cm⁻²) simultaneously. The real-time visualization of Li–electrolyte interface dynamics provides critical insights into the rational design of solid-state battery interfaces. © The Author(s) 2025.

关键词：

来源：评论

学校读者我要写书评

暂无评论

650 nm emitting InGaN red micro-LEDs with ITO n-electrodes

引用

Applied Physics Express 2025年第6期18卷 061001-061001页

作者： Cesur Altinkaya Rawan S. Jalmood Mohammed A. Najmi Daisuke Iida Kazuhiro Ohkawa Material Science and Engineering Program Physical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Electrical and Computer Engineering Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia

InGaN red micro-LEDs were fabricated with indium tin oxide (ITO) and metal n-electrode designs. Micro-LEDs with ITO electrodes achieved a peak on-wafer external quantum efficiency of 2.1% (at 1.25 A cm⁻²) and wall-plug efficiency of 1.7% (at 0.64 A cm⁻²), representing 1.6 times and 1.5 times improvements compared to metal-based electrodes. Improved performance was attributed to the transparency of ITO, enabling light extraction, while metal electrodes block emission. Both configurations achieved a low leakage current density (≤ 10^–7 A cm⁻²) and a high peak emission wavelength around 650 nm. These results represent a strong potential for low-power consumption required/area-limited AR/VR applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Advantages of two quantum programming platforms in quantum computing and quantum chemistry

引用

Journal of cheminformatics 2025年第1期17卷 77页

作者： Pei-Hua Wang Wei-Yeh Wu Che-Yu Lee Jia-Cheng Hong Yufeng Jane Tseng Undergraduate Program in Intelligent Computing and Big Data Chung Yuan Christian University No. 200 Zhongbei Road Taoyuan 320314 Taiwan. Quantum Information Center Chung Yuan Christian University No. 200 Zhongbei Road Taoyuan 320314 Taiwan. Department of Computer Science and Information Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. Department of Computer Science and Information Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yjtseng@csie.ntu.edu.tw. Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yjtseng@csie.ntu.edu.tw. Physics Division National Center for Theoretical Sciences No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yjtseng@csie.ntu.edu.tw. Center for Quantum Science and Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yjtseng@csie.ntu.edu.tw.

Quantum computing is at the forefront of technological advancement and has the potential to revolutionize various fields, including quantum chemistry. Choosing an appropriate quantum programming language becomes critical as quantum education and research increase. In this paper, we comprehensively compare two leading quantum programming languages, Qiskit and PennyLane, focusing on their suitability for teaching and research. We delve into their basic and advanced usage, examine their learning curves, and evaluate their capabilities in quantum computing experiments. We also demonstrate using a quantum programming language to build a half adder and a machine learning model. Our study reveals that each language has distinct advantages. While PennyLane excels in research applications due to its flexibility to adjust parameters in detail and access multiple sources of real quantum devices, Qiskit stands out in education because of its web-based graphical user interface and smaller code size. The codes and the dataset used in the studies are available at https://***/wangpeihua1231/quantum-programming-platform .

关键词： PennyLane Qiskit Quantum chemistry Quantum computing Quantum programming language

来源：评论

学校读者我要写书评

暂无评论

A review of the numerical methods for solving the binary Allen–Cahn equation

引用

Physica A: Statistical Mechanics and its Applications 2025年 670卷

作者： Lee, Hyun Geun Li, Yibao Yang, Junxiang Kwak, Soobin Hwang, Youngjin Ham, Seokjun Kim, Hyundong Jyoti Nam, Yunjae Kim, Junseok Department of Mathematics Dongguk University Seoul04620 Korea Republic of School of Mathematics and Statistics Xi'an Jiaotong University Xi'an710049 China School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology China Department of Mathematics Korea University Seoul02841 Korea Republic of Department of Mathematics and Physics Gangneung-Wonju National University Gangneung25457 Korea Republic of Smart infrastructure Gangneung-Wonju National University Gangneung25457 Korea Republic of The Institute of Basic Science Korea University Seoul02841 Korea Republic of Program in Actuarial Science and Financial Engineering Korea University Seoul02841 Korea Republic of

In this review, we present an overview of numerical methods to solve the binary Allen–Cahn (AC) equation, which is extensively used to model phase separation processes in materials science. It describes the time-dependent evolution of interfaces between two phases and accounts for both local reaction kinetics and diffusion effects. This equation plays a critical role in understanding the behavior of interfaces. The AC equation has various applications across fields such as materials science, physics, and biology, where it helps to analyze and predict phenomena such as phase transitions, grain boundary motion, and pattern formation in complex systems. Its importance lies in its ability to model the dynamics of interfaces and help the study of pattern formation and phase transitions in diverse environments. We discuss various computational methodologies developed for this important mathematical model and describe their strengths, limitations, and applications in diverse scientific domains. © 2025 Elsevier B.V.

关键词： Rate constants

来源：评论

学校读者我要写书评

暂无评论

Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using a Deep Learning Approach

Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using ...

引用

International Symposium on Applied science 2024, ISAS 2024

作者： Raza, Aquib Ching, Congo Tak Shing Liu, Peng-Ta Phan, Thien-Luan Tran, Ngoc-Luan Nguyen, Ha Anh T. Rameez, Mohammad Li, Hung-Chung Linh, Dao Nguyen Phuong Van Hieu, Nguyen Tran, Trung Nghia National Taiwan University Taipei City10673 Taiwan Research Center for Information Technology Academia Sinica Taipei City11529 Taiwan Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung402 Taiwan Department of Electrical Engineering National Chi Nan University Nantou County Taiwan Advanced Plant and Food Crop Biotechnology Center National Chung Hsing University Taichung402 Taiwan International Doctoral Program in Agriculture National Chung Hsing University Taichung402 Taiwan Fall Prevention Center Department of Physical Medicine & Rehabilitation Changhua Christian Hospital Changhua500 Taiwan Department of Physics and Electronic Engineering University of Science Vietnam National University - Ho Chi Minh City Ho Chi Minh City70000 Viet Nam Department of Computer Science University of York York HeslingtonYO10 5DD United Kingdom Undergraduate Program of Intellectual Creativity Engineering National Chung Hsing University Taichung402 Taiwan Ho Chi Minh City72409 Viet Nam HCMUT Vietnam National University Ho Chi Minh City Thu Duc Ho Chi Minh City71308 Viet Nam

This research introduces a deep learning framework that combines convolutional neural networks with autoencoders to improve the diagnostic accuracy of knee osteoarthritis. The study utilized a publicly available dataset from the Mendeley Data repository, where knee joint images were preprocessed using Contrast Limited Adaptive Histogram Equalization to enhance contrast and ensure consistent image sizing. Initially, an autoencoder was employed in an unsupervised manner to learn compressed representations of the data. These representations were then used to train a CNN to classify knee images into 'healthy' and 'osteoarthritic' categories. The model was trained using an 80:20 split for training and testing data, incorporating early stopping and data augmentation techniques to prevent overfitting and enhance generalization. Performance metrics such as accuracy, precision, recall, and the area under the Receiver Operating Characteristic curve (ROCAUC) were used to evaluate the model, resulting in a high test accuracy of 98.95%. The high precision and recall rates further confirmed the model's robustness in diagnosing KOA. To enhance interpretability, Gradient-weighted Class Activation Mapping (Grad-CAM) was applied to identify critical regions in the images that influenced the model's decisions. Additionally, t-Distributed Stochastic Neighbor Embedding (t-SNE) was used to visualize the high-dimensional encoded features in a two-dimensional space, providing deeper insights into how the model differentiates between classes. The promising results of this deep learning approach suggest its potential for broader applications in medical imaging diagnostics. By providing healthcare professionals with a tool that enhances diagnostic accuracy and operational efficiency, this framework lays the foundation for developing scalable, AI-driven diagnostic systems for various complex medical conditions. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Joints (anatomy)

来源：评论

学校读者我要写书评

暂无评论

Enhanced Performance and Data Privacy in Lung Nodule Classification via Federated Deep Learning Approach 24

Enhanced Performance and Data Privacy in Lung Nodule Classif...

引用

2024 7th International Conference on Healthcare Service Management, ICHSM 2024

作者： Nguyen, Duc-Khanh Li, Ai-Hsien Adam Lai, Yen-Jun Chiu, Yen-Ling Phan, Dinh-Van Chien, Ting-Ying Chan, Chien-Lung Department of Information Management Yuan Ze University Taoyuan Taiwan Department of Statistics and Informatics University of Economics The University of Danang Danang Viet Nam Division of Cardiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan ZDT Group- YZU Joint Research and Development Center for Big Data Taoyuan Taiwan Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400710162

This study explores the feasibility of deep learning for classifying nodule neoplasms, analyzing their performance on two openly available datasets, LUNGx SPIE, and LIDC-IDRI. These datasets offer valuable diversity in image quantity, quality, and malignancy annotation methodologies, posing a real-world challenge for effective model development. To handle the disparities in these diverse datasets, we aim to develop a robust classification model trained using federated learning. This decentralized approach allows model training across datasets without sharing patient data, preserving privacy and overcoming data fragmentation. Our experiments demonstrate that federated learning enables the development of a robust and superior deep learning model compared to individual models trained on limited data. This combination of deep learning, and federated learning holds immense promise for nodule neoplasm classification and can significantly improve patient care and outcomes. © 2024 Copyright held by the owner/author(s).

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Crack Catcher AI — Enabling Smart Fracture Mechanics Approach for Damage Control in Thin Silicon Wafers for 3D Semiconductor Integrated Devices/Packages

Crack Catcher AI — Enabling Smart Fracture Mechanics Approa...

引用

Annual International Symposium on Reliability Physics

作者： Gabriel Preston Greer Gonzolez Andrea S. Karnyoto Fitya S. Mozar Matthew M. Henry Mahmud Isnan Kuncahyo S. Nugroho Henry Candra Muhamad Doris Dianing N. N. Putri Tyas K Sari Bens Pardamean Endang Djuana Derrric Speaks Arief S. Budiman Oregon Renewable Energy Center (OREC) Oregon Institute of Technology (Oregon Tech) Klamath Falls OR USA Dept. of Manufacturing & Mechanical Eng. & Tech. (MMET) Oregon Institute of Technology Klamath Falls OR USA Bioinformatics & Data Science Research Center (BDSRC) Bina Nusantara University Jakarta Indonesia Computer Sci. Dept. BINUS Grad. Program - Master of Computer Sci. Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Center for Artificial Intelligence and Advanced Technology (CAPTIVATE) Universitas TRISAKTI Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Universitas TRISAKTI Jakarta Indonesia Industrial Eng. Dept. BINUS Grad. Program – Master of Industrial Eng. Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331504779

ISBN: (纸本)9798331504786

The importance of silicon cannot be undermined - in photovoltaics (PV) as well as in semiconductor industries. However, silicon is very brittle. Silicon cells/wafers crack easily during manufacturing assembly and/or during device operations. Crack Catcher AI uses novel smart fracture mechanics approach with Artificial Intelligence (AI) methodologies to predict and control crack/damage evolution in thin silicon cells/wafers. This is critical as semiconductor 3D integration technology calls for wafer-to-wafer bonding with utmost alignment accuracy and yield/reliability.

关键词： Semiconductor device measurement Three-dimensional displays Accuracy Semiconductor device reliability Silicon Artificial intelligence Bonding Stress Three-dimensional integrated circuits Stress measurement

来源：评论

学校读者我要写书评

暂无评论

Transfer Learning for Keypoint Detection in Low-Resolution Thermal TUG Test Images

arXiv

引用

arXiv 2025年

作者： Chen, Wei-Lun Hsieh, Chia-Yeh Kao, Yu-Hsiang Liu, Kai-Chun Peng, Sheng-Yu Tsao, Yu Research Center for Information Technology Innovation Academic Sinica Taiwan Graduate Institute of Electrical Engineering National Taiwan University Taiwan Bachelor’s Program in Medical Informatics and Innovative Applications Fu Jen Catholic University Taiwan Department of Electrical Engineering National Taiwan University Taiwan College of Information and Computer Sciences University of Massachusetts AmherstMA01003 United States Department of Electrical Engineering National Taiwan University of Science of Technology Taiwan

This study presents a novel approach to human keypoint detection in low-resolution thermal images using transfer learning techniques. We introduce the first application of the Timed Up and Go (TUG) test in thermal image computer vision, establishing a new paradigm for mobility assessment. Our method leverages a MobileNetV3-Small encoder and a ViTPose decoder, trained using a composite loss function that balances latent representation alignment and heatmap accuracy. The model was evaluated using the Object Keypoint Similarity (OKS) metric from the COCO Keypoint Detection Challenge. The proposed model achieves better performance with AP, AP50, and AP75 scores of 0.861, 0.942, and 0.887 respectively, outperforming traditional supervised learning approaches like Mask R-CNN and ViTPose-Base. Moreover, our model demonstrates superior computational efficiency in terms of parameter count and FLOPS. This research lays a solid foundation for future clinical applications of thermal imaging in mobility assessment and rehabilitation monitoring. Copyright © 2025, The Authors. All rights reserved.

关键词： Thermography (imaging)

来源：评论

学校读者我要写书评

暂无评论

Probabilistic genotype-phenotype maps reveal mutational robustness of RNA folding, spin glasses, and quantum circuits

引用

Physical Review Research 2025年第1期7卷 013118-013118页

作者： Anna Sappington Vaibhav Mohanty Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Harvard-MIT Program in Health Sciences and Technology Harvard Medical School Boston Massachusetts 02115 USA and Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Harvard/MIT MD-PhD Program Harvard Medical School Boston Massachusetts 02115 USA and Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Chemistry and Chemical Biology Harvard University Cambridge Massachusetts 02138 USA

Recent studies of genotype-phenotype maps have reported universally enhanced phenotypic robustness to genotype mutations, a feature essential to evolution. Virtually all of these studies make a simplifying assumption that each genotype—represented as a sequence—maps deterministically to a single phenotype, such as a discrete structure. Here we introduce probabilistic genotype-phenotype (PrGP) maps, where each genotype maps to a vector of phenotype probabilities, as a more realistic and universal language for investigating robustness in a variety of physical, biological, and computational systems. We study three model systems to show that PrGP maps offer a generalized framework which can handle uncertainty emerging from various physical sources: (1) thermal fluctuation in RNA folding, (2) external field disorder in the spin-glass ground state search problem, and (3) superposition and entanglement in quantum circuits, which are realized experimentally on IBM quantum computers. In all three cases, we observe a biphasic robustness scaling which is enhanced relative to random expectation for more frequent phenotypes and approaches random expectation for less frequent phenotypes. We derive an analytical theory for the behavior of PrGP robustness, and we demonstrate that the theory is highly predictive of empirical robustness.

关键词： Quantum computers

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：