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ACS Electrochemistry 2025年第4期1卷 552-559页

作者： Kaden Wheeler Joseph Gott Brian Roehrich Julia Chung Kajal Kajal Jaroslaw Syzdek Joao Hespanha Lior Sepunaru Department of Chemistry and Biochemistry University of California at Santa Barbara Santa Barbara California 93106 United States Interdepartmental Program in Biomolecular Science and Engineering University of California at Santa Barbara Santa Barbara California 93106 United States Bio-Logic USA LLC 9050 Executive Park Dr. Ste. 110C Knoxville Tennessee 37923 United States Electrical and Computer Engineering Department University of California at Santa Barbara Santa Barbara California 93106 United States

Measurement of small currents is often impeded by a suboptimal signal-to-noise ratio, largely due to background noise. This background noise significantly constrains the range of catalysts accessible for interrogation via micro- and nanoscale electrochemistry. In response, this work reveals how background noise scales in the presence of induced Faradaic reactions. We measured noise under a series of electrochemical conditions and discovered that the induced noise from a Faradaic reaction scales directly with current. Complementary electrochemical impedance spectroscopy measurements demonstrated that diffusional resistance dictates the noise of Faradaic reactions, independent of the electrochemical mechanism. The noise source is thermal in origin and propagates in a predictable trend, which is inversely proportional to the equivalent diffusional resistance of the analyte. The universality of the observed phenomenon allows for better deconvolution of measured charge from background noise, thus assisting in achieving higher resolution and measurement precision, which is a key in micro- and nanoscale electrochemical measurements.

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Unbiased Parameter Estimation for Bayesian Inverse Problems

arXiv

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arXiv 2025年

作者： Chada, Neil K. Jasra, Ajay Maama, Mohamed Tempone, Raul Department of Mathematics City University of Hong Kong China School of Data Science The Chinese University of Hong Kong Shenzhen CN Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this paper we consider the estimation of unknown parameters in Bayesian inverse problems. In most cases of practical interest, there are several barriers to performing such estimation, This includes a numerical approximation of a solution of a differential equation and, even if exact solutions are available, an analytical intractability of the marginal likelihood and its associated gradient, which is used for parameter estimation. The focus of this article is to deliver unbiased estimates of the unknown parameters, that is, stochastic estimators that, in expectation, are equal to the maximizer of the marginal likelihood, and possess no numerical approximation error. Based upon the ideas of [4] we develop a new approach for unbiased parameter estimation for Bayesian inverse problems. We prove unbiasedness and establish numerically that the associated estimation procedure is faster than the current state-of-the-art methodology for this problem. We demonstrate the performance of our methodology on a range of problems which include a PDE and ODE. Copyright © 2025, The Authors. All rights reserved.

关键词： Markov processes

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Correction: Materials laboratories of the future for alloys, amorphous, and composite materials (MRS Bulletin, (2025), 50, 2, (190-207), 10.1557/s43577-024-00846-y)

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MRS Bulletin 2025年 1-2页

作者： Banerjee, Sarbajit Meng, Y. Shirley Minor, Andrew M. Zhang, Minghao Zaluzec, Nestor J. Chan, Maria K.Y. Seidler, Gerald McComb, David W. Agar, Joshua Mukherjee, Partha P. Melot, Brent Chapman, Karena Guiton, Beth S. Klie, Robert F. McCue, Ian D. Voyles, Paul M. Robertson, Ian Li, Ling Chi, Miaofang Destino, Joel F. Devaraj, Arun Marquis, Emmanuelle A. Segre, Carlo U. Liu, Huinan H. Yang, Judith C. Momeni, Kasra Misra, Amit Abdolrahim, Niaz Medvedeva, Julia E. Cai, Wenjun Sehirlioglu, Alp Dizbay-Onat, Melike Mehta, Apurva Graham-Brady, Lori Maruyama, Benji Rajan, Krishna Warner, Jamie H. Taheri, Mitra L. Kalinin, Sergei V. Reeja-Jayan, B. Schwarz, Udo D. Simon, Sindee L. Brown, Craig M. Department of Chemistry and Department of Materials Science & Engineering Texas A & M University College Station United States Pritzker School of Molecular Engineering The University of Chicago Chicago United States Department of Materials Science & Engineering University of California Berkeley Berkeley United States National Center for Electron Microscopy Molecular Foundry Lawrence Berkeley National Laboratory Berkeley United States Center for Nanoscale Materials Argonne National Laboratory Lemont United States Department of Physics University of Washington Seattle United States Department of Materials Science & Engineering The Ohio State University Columbus United States Department of Mechanical Engineering and Mechanics Drexel University Philadelphia United States School of Mechanical Engineering Purdue University West Lafayette United States Department of Chemistry University of Southern California Los Angeles United States Department of Chemistry Stony Brook University The State University of New York Stony Brook United States Department of Chemistry University of Kentucky Lexington United States Department of Physics University of Illinois at Chicago Chicago United States Department of Materials Science & Engineering Northwestern University Evanston Bangladesh Department of Materials Science & Engineering University of Wisconsin–Madison Madison United States Department of Materials Science and Engineering University of Pennsylvania Philadelphia United States Department of Mechanical Engineering and Materials Science Duke University Durham United States Department of Chemistry Creighton University Omaha United States Physical and Computational Sciences Directorate Pacific Northwest National Laboratory Richland United States Department of Materials Science & Engineering University of Michigan–Ann Arbor Ann Arbor United States Department of Physics Illinois Institute of Technology Chicago United States Department of Bioengineering and the Mater

This article was updated to correct Minghao Zhang’s affiliation from "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA" to "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA;Argonne National Laboratory, Lemont, USA." Argonne National Laboratory was left off the original publication. © The Author(s) 2025.

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

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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.

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FAULT TOLERANCE ANALYSIS OF THE CLASS OF REARRANGEABLE INTERCONNECTION NETWORKS

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 1989年第1期7卷 148-164页

作者： PAKZAD, S Computer Engineering Program Department of Electrical Engineering The Pennsylvania State University University Park Pennsylvania 16802 USA

The issue of the fault tolerance of interconnection networks has received considerable attention since the last decade. The theoretical framework developed by J. P. Shen and J. P. Hays ( IEEE Trans. Comput. C-33 , 3 (Mar. 1984), 241–248) and extended by S. Pakzad and S. Lakshmivarahan ( Internat. J. Comput. Syst. Sci. Engrg. 3 , 2 (April 1988), 91–99) can be used as a guideline to analyze the fault tolerance behavior of the interconnection networks in a multicomputer environment. This paper analyzes the fault tolerance characteristics of a range of rearrangeable β-networks based on the concepts and the framework developed by S. Pakzad and S. Lakshmivarahan (cited earlier). These rearrangeable β-networks include the Benes network, the Waksman network, the Joel network, and the serial network. In addition, this paper presents a comparative analysis of the aforementioned networks according to their hardware cost, performance, and degree of fault tolerance.

关键词： computer Systems, Digital

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Sources of contrast in confocal reflectance imaging

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APPLIED OPTICS 1996年第19期35卷 3441-3446页

作者： Dunn, AK Smithpeter, C Welch, AJ RichardsKortum, R []The authors are with the Department of Electrical and Computer Engineering Biomedical Engineering Program University of Texas at Austin Austin Texas 78712

The relationship between optical properties and image contrast in confocal imaging is investigated. A Monte Carlo simulation has been developed to analyze the effects of changes in scattering, index of refraction, and absorption in a three-layer medium. Contrast was calculated from the computed signal-to-background ratios for changes in tissue optical properties. Results show that the largest source of contrast is changes in refractive index. (C) 1996 Optical Society of America

关键词： .Monte Carlo optical properties pinhole detector relative contributions signal-to-background source of contrast signal contrast

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MICROcomputer REALIZATIONS OF LYNN FAST DIGITAL-FILTERING DESIGNS

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MEDICAL & BIOLOGICAL engineering & COMPUTING 1980年第5期18卷 638-642页

作者： MALIK, NR Electrical & Computer Engineering Program University of Iowa Iowa City Iowa USA

The feasibility of real-time digital filtering using dedicated state-of-the-art microcomputers of 8-bit wordlength is demonstrated. Implementations of Lynn's integer filter structures by means of wrap-around queue data structures are shown to operate at sampling rates of over 8 kHz. An initial condition constraint unique to this filter class which must be satisfied to prevent inadvertent overflows or oscillations in microcomputers is discussed. The fast-filtering techniques are applied to the problem of calculating the average absolute value of a fast signal in real time.

关键词： Digital filters Microcomputers Online computing Signal processing

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Scaling Up Synthetic Cell Production Using Robotics and Machine Learning Toward Therapeutic Applications

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Advanced Biology 2025年第5期9卷 e2400671页

作者： Sharf-Pauker, Noga Galil, Ido Kfir, Omer Chen, Gal Menachem, Rotem Shklover, Jeny Schroeder, Avi Ackerman, Shanny The Louis Family Laboratory for Targeted Drug Delivery and Personalized Medicine Technologies Department of Chemical Engineering Technion – Israel Institute of Technology Haifa32000 Israel The Norman Seiden Multidisciplinary Program for Nanoscience and Nanotechnology Technion – Israel Institute of Technology Haifa32000 Israel Faculty of Computer Science Technion – Israel Institute of Technology Haifa32000 Israel The Interdisciplinary Program for Biotechnology Technion – Israel Institute of Technology Haifa32000 Israel Cell Biology and Cancer Science Rappaport Faculty of Medicine Technion – Israel Institute of Technology Haifa32000 Israel

Synthetic cells (SCs), developed through bottom-up synthetic biology, hold great potential for biomedical applications, with the promise of replacing malfunctioning natural cells and treating diseases with spatiotemporal control. Currently, most SC synthesis and characterization processes are manual, limiting scalability and efficiency. In this study, an automated method is developed for large-scale production of protein-producing SCs for therapeutic applications. The optimized process, compatible with a robotic liquid handling system (LiHa), reduces production time by half. Additionally, incorporation of an automated tissue dissociator-based emulsification increases batch size 30-fold while preserving SC characteristics. To assess SC quality and protein synthesis, artificial intelligence (AI)-based image analysis is employed, allowing for automated, accurate and high-throughput SC characterization. Large-scale luciferase-expressing SCs from a single homogeneous batch are administered to mice, allowing for real-time monitoring of protein expression and reducing experimental variability. By troubleshooting several central steps in SC synthesis, it is demonstrated that automation and computerized quality control can significantly improve the process of SC synthesis for preclinical and clinical applications. © 2025 The Author(s). Advanced Biology published by Wiley-VCH GmbH.

关键词： AI artificial Intelligence automation machine learning robotics synthetic biology synthetic cells

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

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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.

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Impact of Quantum Well Thickness on Efficiency Loss in InGaN/GaN LEDs: Challenges for Thin-Well Designs

arXiv

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arXiv 2025年

作者： Li, Xuefeng Pant, Nick Rahman, Sheikh Ifatur Armitage, Rob Rajan, Siddharth Kioupakis, Emmanouil Feezell, Daniel University of New Mexico AlbuquerqueNM87106 United States Department of Materials Science & Engineering University of Michigan Ann ArborMI48109 United States Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Electrical and Computer Engineering The Ohio State University ColumbusOH43210 United States Lumileds LLC San JoseCA95131 United States Department of Materials Science and Engineering The Ohio State University ColumbusOH43210 United States

We investigate the impact of quantum well (QW) thickness on efficiency loss in c-plane InGaN/GaN LEDs using a small-signal electroluminescence (SSEL) technique. Multiple mechanisms related to efficiency loss are independently examined, including injection efficiency, carrier density vs. current density relationship, phase space filling (PSF), quantum confined stark effect (QCSE), and Coulomb enhancement. An optimal QW thickness of around 2.7 nm in these InGaN/GaN LEDs was determined for quantum wells having constant In composition. Despite better control of deep-level defects and lower carrier density at a given current density, LEDs with thin QWs still suffer from an imbalance of enhancement effects on the radiative and intrinsic Auger-Meitner recombination coefficients. The imbalance of enhancement effects results in a decline in internal quantum efficiency (IQE) and radiative efficiency with decreasing QW thickness at low current density in LEDs with QW thicknesses below 2.7 nm. We also investigate how LED modulation bandwidth varies with quantum well thickness, identifying the key trends and their implications for device performance. Copyright © 2025, The Authors. All rights reserved.

关键词： Semiconductor quantum wells

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