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Ferroelectric transistors based on shear-transformation-mediated rhombohedral-stacked molybdenum disulfide

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Nature Electronics 2024年第1期7卷 29-38页

作者： Yang, Tilo H. Liang, Bor-Wei Hu, Hsiang-Chi Chen, Fu-Xiang Ho, Sheng-Zhu Chang, Wen-Hao Yang, Liu Lo, Han-Chieh Kuo, Tzu-Hao Chen, Jyun-Hong Lin, Po-Yen Simbulan, Kristan Bryan Luo, Zhao-Feng Chang, Alice Chinghsuan Kuo, Yi-Hao Ku, Yu-Seng Chen, Yi-Cheng Huang, You-Jia Chang, Yu-Chen Chiang, Yu-Fan Lu, Ting-Hua Lee, Min-Hung Li, Kai-Shin Wu, Menghao Chen, Yi-Chun Lin, Chun-Liang Lan, Yann-Wen Department of Physics National Taiwan Normal University Taipei Taiwan Taiwan Semiconductor Research Institute National Applied Research Laboratories Hsinchu Taiwan Department of Electrophysics National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Physics National Cheng Kung University Tainan Taiwan School of Physics Huazhong University of Science and Technology Wuhan China Institute of Cellular and Organismic Biology Academia Sinica Taipei Taiwan Department of Mathematics and Physics University of Santo Tomas Manila Philippines Program for Semiconductor Devices Materials and Hetero-integration Graduate School of Advanced Technology National Taiwan University Taipei Taiwan Hsinchu Taiwan Department of Physics National Taiwan University Taipei Taiwan Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States

To develop low-power, non-volatile computing-in-memory device using ferroelectric transistor technologies, ferroelectric channel materials with scaled thicknesses are required. Two-dimensional semiconductors, such as molybdenum disulfide (MoS2), equipped with sliding ferroelectricity could provide an answer. However, achieving switchable electric polarization in epitaxial MoS2 remains challenging due to the absence of mobile domain boundaries. Here we show that polarity-switchable epitaxial rhombohedral-stacked (3R) MoS2 can be used as a ferroelectric channel in ferroelectric memory transistors. We show that a shear transformation can spontaneously occur in 3R MoS2 epilayers, producing heterostructures with stable ferroelectric domains embedded in a highly dislocated and unstable non-ferroelectric matrix. This diffusionless phase transformation process produces mobile screw dislocations that enable collective polarity control of 3R MoS2 via an electric field. Polarization–electric-field measurements reveal a switching field of 0.036 V nm−1 for shear-transformed 3R MoS2. Our sliding ferroelectric transistors are non-volatile memory units with thicknesses of only two atomic layers and exhibit an average memory window of 7 V with an applied voltage of 10 V, retention times greater than 104 seconds and endurance greater than 104 cycles. © 2023, The Author(s), under exclusive licence to Springer Nature Limited.

关键词： Molybdenum disulfide

Analyzing Diversity in Healthcare LLM Research: A Scientometric Perspective

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arXiv 2024年

作者： Restrepo, David Wu, Chenwei Vásquez-Venegas, Constanza Matos, João Gallifant, Jack Celi, Leo Anthony Bitterman, Danielle S. Nakayama, Luis Filipe Laboratory for Computational Physiology Massachusetts Institute of Technology CambridgeMA United States Departamento de Telematica Universidad del Cauca Cauca Popayán Colombia Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI United States Scientific Image Analysis Lab Faculty of Medicine Universidad de Chile RM Santiago Chile Department of Computer Science Faculty of Engineering Universidad de Concepción Biobio Concepción Chile Department of Biostatistics Harvard TH Chan School of Public Health BostonMA United States Department of Medicine Beth Israel Deaconess Medical Center BostonMA United States Artificial Intelligence in Medicine Program Mass General Brigham Harvard Medical School BostonMA United States Department of Ophthalmology São Paulo Federal University São Paulo São Paulo Brazil

The deployment of large language models (LLMs) in healthcare has demonstrated substantial potential for enhancing clinical decision-making, administrative efficiency, and patient outcomes. However, the underrepresentation of diverse groups in the development and application of these models can perpetuate biases, leading to inequitable healthcare delivery. This paper presents a comprehensive scientometric analysis of LLM research for healthcare, including data from January 1, 2021, to July 1, 2024. By analyzing metadata from PubMed and Dimensions, including author affiliations, countries, and funding sources, we assess the diversity of contributors to LLM research. Our findings highlight significant gender and geographic disparities, with a predominance of male authors and contributions primarily from high-income countries (HICs). We introduce a novel journal diversity index based on Gini diversity to measure the inclusiveness of scientific publications. Our results underscore the necessity for greater representation in order to ensure the equitable application of LLMs in healthcare. We propose actionable strategies to enhance diversity and inclusivity in artificial intelligence research, with the ultimate goal of fostering a more inclusive and equitable future in healthcare innovation. © 2024, CC BY.

关键词： Decision making

Caco-2 Cell-Derived Biomimetic Electrochemical Biosensor for Cholera Toxin Detection

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SSRN

SSRN 2022年

作者： Kim, Yonghwan Lee, Dongtak Seo, Youngjun Jung, Hyo Gi Jang, Jae Won Park, Dongsung Kim, Insu Lee, Gyudo Hwang, Kyo Seon Kim, Seung-Hyun Lee, Sang Won Lee, Jeong Hoon Yoon, Dae Sung School of Biomedical Engineering Korea University Seoul02841 Korea Republic of Interdisciplinary Program in Precision Public Health Korea University Seoul02841 Korea Republic of Department of Clinical Pharmacology and Therapeutics College of Medicine Kyung Hee University Seoul02447 Korea Republic of Department of Biotechnology and Bioinformatics Korea University Sejong30019 Korea Republic of Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Korea University Sejong30019 Korea Republic of School of Engineering Brown University ProvidenceRI02912 United States Department of Electrical Engineering and Computer Science University of California IrvineCA92697 United States Department of Electrical Engineering Kwangwoon University Seoul01897 Korea Republic of Astrion Inc Seoul02841 Korea Republic of

Cholera is a highly contagious and lethal waterborne disease induced by an infection with Vibrio cholerae (V. cholerae) secreting cholera toxin (CTx). Cholera toxin subunit B (CTxB) from the CTx specifically binds with monosialo-tetra-hexosyl-ganglioside (GM1) found on the exterior cell membrane of an enterocyte. Owing to the pathological process of CTx, a biomimetic electrochemical biosensor (CCB) was developed by applying GM1-expressing Caco-2 cell membrane (CCM) on the electrode surface of the biosensor for CTx detection. Briefly, the electrode surface was functionalized with CCM using the vesicle fusion method. The specific binding between GM1 and CTxB on the electrode surface was verified using confocal laser scanning microscopy and atomic force microscopy. The CTxB detection performances of the CCB, including sensitivity, selectivity, and long-term stability, were determined using electrochemical impedance spectroscopy (EIS). Based on the results, the CCB had an excellent limit of detection of ~11.46 nM and a detection range spanning 100 ng/mL - 1 mg/mL. Further, the CCB had high selectivity for the CTxB compared to different interfering molecules, which are abundant constituents of intestinal fluid and fecal matter in the human body. The long-term stability of the CCBs was also verified for 3 weeks using EIS. Overall, the CCB was found to have an excellent potential for application to point-of-care and cost-effective testing for CTxB detection in developing countries. © 2022, The Authors. All rights reserved.

关键词： Electrochemical impedance spectroscopy

Loss tangent fluctuations due to two-level systems in superconducting microwave resonators

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arXiv 2024年

作者： Vallières, André Russell, Megan E. You, Xinyuan Garcia-Wetten, David A. Goronzy, Dominic P. Walker, Mitchell J. Bedzyk, Michael J. Hersam, Mark C. Romanenko, Alexander Lu, Yao Grassellino, Anna Koch, Jens McRae, Corey Rae H. Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Fermi National Accelerator Laboratory BataviaIL60510 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Chemistry Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States Center for Applied Physics and Superconducting Technologies Northwestern University EvanstonIL60208 United States Electrical Computing and Energy Engineering Department University of Colorado BoulderCO80309 United States Department of Physics University of Colorado BoulderCO80309 United States National Institute of Standards and Technology BoulderCO80305 United States

Superconducting microwave resonators are critical to quantum computing and sensing technologies. Additionally, they are common proxies for superconducting qubits when determining the effects of performance-limiting loss mechanisms such as from two-level systems (TLS). The extraction of these loss mechanisms is often performed by measuring the internal quality factor Qi as a function of power or temperature. In this work, we investigate large temporal fluctuations of Qi at low powers over periods of 12 to 16 hours (relative standard deviation σQi/Qi = 13%). These fluctuations are ubiquitous across multiple resonators, chips and cooldowns. We are able to attribute these fluctuations to variations in the TLS loss tangent due to two main indicators. First, measured fluctuations decrease as power and temperature increase. Second, for interleaved measurements, we observe correlations between low- and medium-power Qi fluctuations and an absence of correlations with high-power fluctuations. Agreement with the TLS loss tangent mean is obtained by performing measurements over a time span of a few hours. We hypothesize that, in addition to decoherence due to coupling to individual near-resonant TLS, superconducting qubits are affected by these observed TLS loss tangent fluctuations. © 2024, CC BY.

关键词： Qubits

Linearity assessment between lower limb joint angles and angular accelerations at standard maximum vertical jumps with long-short and no countermovement

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Gait & Posture 2023年 106卷 S174-S175页

作者： Rodrigues, Carlos Correia, Miguel Abrantes, João Benedetti, Marco Nadal, Jurandir Faculty of Engineering- University of Porto Biomedical Engineering Program Porto Portugal INESC TEC - Institute for Systems and Computer Engineering- Technology and Science C-BER - Centre for Biomedical Engineering Research Porto Portugal Faculty of Engineering- University of Porto Department of Electrical and Computer Engineering Porto Portugal CICANT - Centre for Research in Applied Communication- Culture and New Technologies MovLab - Laboratory of Technologies for Interactions and Interfaces Lisbon Portugal Federal University of Pernambuco Department of Electronic and Systems Recife Brazil Federal University of Rio de Janeiro Biomedical Engineering Program Rio de Janeiro Brazil

IntroductionStandard maximum vertical jump (MVJ) has been applied to assess lower limb long countermovement (CM) on countermovement jump (CMJ) and short CM on drop jump (DJ) for comparison to squat jump (SJ) without CM [1,2]. Research questionNevertheless, the ability for lower limb joint accelerations depending on lower limb joint angles at long, short and no CM remains an open issue [3,4], in particular linearity assessment of these relations at long, short and no CM in association with MVJ whole-body impulsion. MethodsFor this reason, we applied piecewise linear detection of segmented subphases on lower limb joint angles ( θ)-angular acceleration ( α) diagrams for the hip (H), knee (K) and ankle (A) during impulse phases on CMJ, DJ and SJ. Selected sample corresponds to best MVJ trials based on higher flight-time of 3 CMJ, DJ and SJ repetitions for six healthy untrained subjects with ages (21.5±1.4) years, (76.7±9.3)kg mass and (1.79±0.06)m height. Adhesive reflective markers were applied at lower limb and torso, with sagittal hip, knee, and ankle θ, α obtained by inverse kinematics. H,K,A ( θ, α) diagrams were plotted and impulsion subphases segmented at selected instants of ∂ a/∂ q phase reversal with linear fit by the least-squares method, Fig. 1. Fig. 1. Hip, knee, ankle joint ( θ, α) diagrams at CMJ, DJ, SJ with segmented subphases time span(Δt), |∂α/∂θ| slope magnitudes and R² linear fit regression. ResultsSJ presented larger number of ( θ, α) subphases than DJ, both larger than CMJ with higher |∂ α/∂ θ| variation at DJ and SJ than CMJ, pointing to higher complexity of neuromuscular control and contributing to explain reduced SJ, DJ performance without CM (0.33±0.05)m and with short CM (0.27±0.03)m in relation to CMJ with long CM (0.36±0.04)m for untrained selected subjects, Fig. 1. Thus, despite the larger total time span Δt at CMJ (0.76±0.10)s in relation to SJ (0.36±0.08)s and DJ (0.23±0.05)s, CMJ presented lower number of subphases with longer time span

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Automating the Practice of Science – Opportunities, Challenges, and Implications

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arXiv 2024年

作者： Musslick, Sebastian Bartlett, Laura K. Chandramouli, Suyog H. Dubova, Marina Gobet, Fernand Griffiths, Thomas L. Hullman, Jessica King, Ross D. Nathan Kutz, J. Lucas, Christopher G. Mahesh, Suhas Pestilli, Franco Sloman, Sabina J. Holmes, William R. Institute of Cognitive Science Osnabrück University Osnabrück49090 Germany Department of Cognitive Linguistic & Psychological Sciences Brown University ProvidenceRI02912 United States Centre for Philosophy of Natural and Social Science London School of Economics Lakatos Building Houghton Street LondonWC2A 2AE United Kingdom AaltoFI-00076 Finland Department of Computing Science University of Alberta 8900 114 St NW EdmontonABT6G 2S4 Canada Cognitive Science Program Indiana University 1101 E 10th St BloomingtonIN47405 United States School of Psychology University of Roehampton LondonSW15 4JD United Kingdom Departments of Psychology and Computer Science Princeton University PrincetonNJ United States Department of Computer Science Northwestern University IL United States Department of Chemical Engineering and Biotechnology University of Cambridge CambridgeCB3 0AS United Kingdom Department of Computer Science and Engineering Chalmers University of Technology Gothenburg412 96 Sweden Department of Applied Mathematics and Electrical and Computer Engineering University of Washington Seattle98195 United States School of Informatics University of Edinburgh 10 Crichton St. EH8 9AB United Kingdom Department of Materials Science and Engineering University of Toronto Canada Department of Psychology Department of Neuroscience The University of Texas AustinTX United States Department of Computer Science University of Manchester M13 9PL United Kingdom

Automation transformed various aspects of our human civilization, revolutionizing industries and streamlining processes. In the domain of scientific inquiry, automated approaches emerged as powerful tools, holding promise for accelerating discovery, enhancing reproducibility, and overcoming the traditional impediments to scientific progress. This article evaluates the scope of automation within scientific practice and assesses recent approaches. Furthermore, it discusses different perspectives to the following questions: Where do the greatest opportunities lie for automation in scientific practice?;What are the current bottlenecks of automating scientific practice?;and What are significant ethical and practical consequences of automating scientific practice? By discussing the motivations behind automated science, analyzing the hurdles encountered, and examining its implications, this article invites researchers, policymakers, and stakeholders to navigate the rapidly evolving frontier of automated scientific practice. © 2024, CC BY.

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Three-dimensional C-scan-based generation adversarial network with synthetic input to improve optical coherence tomography angiography

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Journal of Biomedical Optics 2025年第5期30卷 056006页

作者： Xu, Jingjiang Feng, Zhongwu Qiu, Haixia Tang, Peijun Gao, Kai Huang, Yanping Lan, Gongpu Qin, Jia An, Lin Jia, Gangyong Wu, Qing Foshan University Guangdong-Hong Kong-Macao Intelligent Micro-Nano Optoelectronic Technology Joint Laboratory Foshan China Guangdong Weiren Meditech Co. Ltd Innovation and Entrepreneurship Teams Project of Guangdong Pearl River Talents Program Foshan China Foshan University School of Mechatronic Engineering and Automation Foshan China Chinese PLA General Hospital The First Medical Centre Department of Laser Medicine Beijing China South China Normal University College of Biophotonics Guangzhou China Sun Yat-sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science State Key Laboratory of Ophthalmology Guangdong Provincial Clinical Research Center for Ocular Diseases Zhongshan Ophthalmic Center Guangzhou China Hangzhou Dianzi University School of Computer Science Hangzhou China

Significance: Optical coherence tomography angiography (OCTA) usually suffers from the inherent random fluctuations of noise and speckles in the imaging system. Previous deep learning methods have mainly focused on improving the quality of B-scan blood flow images or en face projection images. We propose a deep learning method to reconstruct high-quality 3D vasculature, which fully utilizes the volumetric OCTA data and the topological features of the vascular network. Aim: We propose a deep learning method called the three-dimensional C-scanbased generation adversarial network (3DCS-GAN) to improve vascular visualization for volumetric OCTA data. Approach: To train the network, we superimposed the single-shot en face OCTA images on avascular noisy C-scan images to synthesize the input data and used the multiple averaged en face OCTA images as the reference labels. The deep learning algorithm is based on Pix2Pix architecture and consists of a generator model and a discriminator model. A perceptual loss function was utilized by combining content loss and adversarial loss. The proposed algorithm is applied to the C-scan images depth-by-depth to suppress the background noise and enhance vascular visualization in the 3D OCTA data. Results: The proposed method has improved the contrast-to-noise ratio of crosssectional OCTA images by ∼2 times. It greatly enhances the visualization of blood vessels in the deep layer and offers much clearer blood vessel topology in the 3D volume-rendering of OCTA. 3DCS-GAN has exhibited superior image enhancement compared with alternative methods. It has been used to enhance the OCTA images of port wine stain disease for clinical investigation. Conclusions: It demonstrates that the proposed 3DCS-GAN can greatly improve vascular visualization in the deep layer, provide better image quality than the multiple averaged OCTA images, and achieve superior image enhancement for volumetric OCTA data. © 2025 SPIE. All rights reserved.

关键词： Image enhancement

Autoencoders as Weight Initialization of Deep Classification Networks for Cancer versus Cancer Studies

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arXiv 2020年

作者： Ferreira, Mafalda Falcão Camacho, Rui Teixeira, Luís F. Doctoral Program in Informatics Engineering Faculty of Engineering University of Porto INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal Department of Informatics Engineering Faculty of Engineering University of Porto Porto - Portugal

Cancer is still one of the most devastating diseases of our time. One way of automatically classifying tumor samples is by analyzing its derived molecular information (i.e., its genes expression signatures). In this work, we aim to distinguish three different types of cancer: thyroid, skin, and stomach. For that, we compare the performance of a Denoising Autoencoder (DAE) used as weight initialization of a deep neural network. Although we address a different domain problem in this work, we have adopted the same methodology of Ferreira et al.. In our experiments, we assess two different approaches when training the classification model: (a) fixing the weights, after pre-training the DAE, and (b) allowing fine-tuning of the entire classification network. Additionally, we apply two different strategies for embedding the DAE into the classification network: (1) by only importing the encoding layers, and (2) by inserting the complete autoencoder. Our best result was the combination of unsupervised feature learning through a DAE, followed by its full import into the classification network, and subsequent fine-tuning through supervised training, achieving an F1 score of 98.04% ± 1.09 when identifying cancerous thyroid samples. Copyright © 2020, The Authors. All rights reserved.

关键词： Classification (of information)

Van der Waals device integration beyond the limits of van der Waals forces via adhesive matrix transfer

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arXiv 2023年

作者： Satterthwaite, Peter F. Zhu, Weikun Jastrzebska-Perfect, Patricia Tang, Melbourne Gao, Hongze Kitadai, Hikari Lu, Ang-Yu Tan, Qishuo Tang, Shin-Yi Chueh, Yu-Lun Kuo, Chia-Nung Lue, Chin Shan Kong, Jing Ling, Xi Niroui, Farnaz Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Chemical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Chemistry Boston University BostonMA02215 United States Department of Materials Science and Engineering National Tsing Hua University Hsinchu30013 Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei11492 Taiwan College of Semiconductor Research National Tsing Hua University Hsinchu30013 Taiwan Department of Physics National Cheng Kung University Tainan70101 Taiwan Taiwan Consortium of Emergent Crystalline Materials National Science and Technology Council Taipei10601 Taiwan Program on Key Materials Academy of Innovative Semiconductor and Sustainable Manufacturing National Cheng Kung University Tainan70101 Taiwan Division of Materials Science and Engineering Boston University BostonMA02215 United States The Photonics Center Boston University BostonMA02215 United States

Pristine van der Waals (vdW) interfaces between two-dimensional (2D) and other materials are core to emerging optical and electronic devices. Their direct fabrication is, however, challenged as the vdW forces are weak and cannot be tuned to accommodate integration of arbitrary layers without solvents, sacrificial-layers or high-temperatures, steps that can introduce damage. To address these limitations, we introduce a single-step 2D material-to-device integration approach in which forces promoting transfer are decoupled from the vdW forces at the interface of interest. We use this adhesive matrix transfer to demonstrate conventionally-forbidden direct integration of diverse 2D materials (MoS2, WSe2, PtS2, GaS) with dielectrics (SiO2, Al2O3), and scalable, aligned heterostructure formation, both foundational to device development. We then demonstrate a single-step integration of monolayer-MoS2 into arrays of transistors. With no exposure to polymers or solvents, clean interfaces and pristine surfaces are preserved, which can be further engineered to demonstrate both n- and p-type behavior. Beyond serving as a platform to probe the intrinsic properties of sensitive nanomaterials without the influence of processing steps, our technique allows efficient formation of unconventional device form-factors, with an example of flexible transistors demonstrated. Copyright © 2023, The Authors. All rights reserved.

关键词： Van der Waals forces