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Ageing of lithium-ion batteries results in irreversible reduction in performance. Intrinsic variability between cells, caused by manufacturing differences, occurs throughout life and increases with age. Researchers need to know the minimum…

Intensity noise cross-correlation of the polarization eigenstates of light emerging from an atomic vapor cell in the Hanle configuration allows one to perform high resolution spectroscopy with free- running semiconductor lasers. Such an…

Atomic Physics · Physics 2018-06-06 Ben Whitenack , Devan Tormey , Michael Crescimanno , Andrew C. Funk , Shannon OLeary

In this study we construct a data-driven model describing Lithium plating in a battery cell, which is a key process contributing to degradation of such cells. Starting from the fundamental Doyle-Fuller-Newman (DFN) model, we use asymptotic…

Chemical Physics · Physics 2024-08-28 Avesta Ahmadi , Kevin J. Sanders , Gillian R. Goward , Bartosz Protas

Electrical Impedance Tomography (EIT) is a noninvasive imaging technique that does not use ionizing radiation, with application both in environmental sciences and in health. Image reconstruction is performed by solving an inverse problem…

In the context of epilepsy monitoring, EEG artifacts are often mistaken for seizures due to their morphological similarity in both amplitude and frequency, making seizure detection systems susceptible to higher false alarm rates. In this…

Signal Processing · Electrical Eng. & Systems 2022-04-21 Thorir Mar Ingolfsson , Andrea Cossettini , Simone Benatti , Luca Benini

The strong non-linear optical response of atomic systems in electromagnetically induced transparency (EIT) states is considered as a means to detect the presence of small perturbations to steady states. For the 3-level system, expressions…

Atomic Physics · Physics 2023-09-06 Aneesh Ramaswamy , Svetlana A. Malinovskaya

Electroencephalography has been established as an effective method for detecting Parkinson's disease, typically diagnosed early.Current Parkinson's disease detection methods have shown significant success within individual datasets,…

Machine Learning · Computer Science 2025-08-21 Qian Zhang , Ruilin Zhang , Biaokai Zhu , Xun Han , Jun Xiao , Yifan Liu , Zhe Wang

Lithium-ion batteries (LIBs) are the leading technology used in consumer electronics, electric vehicles, and grid-level electrochemical energy storage applications. The ever-increasing use of LIBs has highlighted a gap in understanding of…

The generation of multiphase porous electrode microstructures with optimum morphological and transport properties is essential in the design of improved electrochemical energy storage devices, such as lithium-ion batteries. Electrode…

Computational Engineering, Finance, and Science · Computer Science 2025-08-05 Andrea Gayon-Lombardo , Ehecatl A. del Rio-Chanona , Catalina A. Pino-Munoz , Nigel P. Brandon

Degradation prediction for lithium-ion batteries using data-driven methods requires high-quality aging data. However, generating such data, whether in the laboratory or the field, is time- and resource-intensive. Here, we propose a method…

Systems and Control · Electrical Eng. & Systems 2025-03-19 Weihan Li , Harshvardhan Samsukha , Bruis van Vlijmen , Lisen Yan , Samuel Greenbank , Simona Onori , Venkat Viswanathan

Fast lithium transport across the solid-state electrolyte (SSE)/lithium metal anode interface is critical for high-performance all-solid-state batteries. Uncovering the complex lithium dynamics governed by diverse local environments in the…

Materials Science · Physics 2026-03-04 Qiye Guan , Yongqing Cai

Generative Adversarial Networks (GANs) have been used in many different applications to generate realistic synthetic data. We introduce a novel GAN with Autoencoder (GAN-AE) architecture to generate synthetic samples for variable length,…

Machine Learning · Computer Science 2022-10-10 Stephanie Ger , Yegna Subramanian Jambunath , Diego Klabjan

Fast charging has attracted increasing attention from the battery community for electrical vehicles (EVs) to alleviate range anxiety and reduce charging time for EVs. However, inappropriate charging strategies would cause severe degradation…

Systems and Control · Electrical Eng. & Systems 2023-04-11 Benben Jiang , Yixing Wang , Zhenghua Ma , Qiugang Lu

In situ scanning transmission electron microscopy (STEM) through liquids is a promising approach for exploring biological and materials processes. However, options for in situ chemical identification are limited: X-ray analysis is precluded…

Chemical Physics · Physics 2015-06-12 Megan E. Holtz , Yingchao Yu , Jie Gao , Héctor D. Abruña , David A. Muller

Transmission electron microscopy at very low energy is a promising way to avoid damaging delicate biological samples with the incident electrons, a known problem in conventional transmission electron microscopy. For imaging in the 0-30 eV…

Materials Science · Physics 2020-09-22 Peter S. Neu , Daniël Geelen , Aniket Thete , Rudolf M. Tromp , Sense Jan van der Molen

Measurements of many biological processes are characterized by an initial trend period followed by an equilibrium period. Scientists may wish to quantify features of the two periods, as well as the timing of the change point. Specifically,…

Applications · Statistics 2020-09-22 Wenyu Zhang , Maryclare Griffin , David S. Matteson

Electrical Impedance Tomography (EIT) is a non-invasive medical imaging method that reconstructs electrical conductivity mediums from boundary voltage-current measurements, but its severe ill-posedness renders direct operator learning with…

Numerical Analysis · Mathematics 2026-01-14 Amit Bhat , Ke Chen , Chunmei Wang

Non-circuit theory drift-diffusion numerical simulation of standard potentiostatic impedance spectroscopy (IS) is a well-known strategy for characterization of materials and electronic devices. It implies the time-dependent solutions from…

The physics-based Doyle-Fuller-Newman (DFN) model, widely adopted for its precise electrochemical modeling, stands out among various simulation models of lithium-ion batteries (LIBs). Although the DFN model is powerful in forward predictive…

Computational Engineering, Finance, and Science · Computer Science 2025-04-30 Weipeng Xu , Kaiqi Yang , Yuzhi Zhang , Shichao Sun , Sheng Mao , Tianju Xue

Modern laboratory techniques like ultrafast laser excitation and shock compression can bring matter into highly nonequilibrium states with complex structural transformation, metallization and dissociation dynamics. To understand and model…

Computational Physics · Physics 2022-05-24 Qiyu Zeng , Bo Chen , Xiaoxiang Yu , Shen Zhang , Dongdong Kang , Han Wang , Jiayu Dai
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