Journal ArticleDOI
Effects of A/B-Site Co-Doping on Microstructure and Dielectric Thermal Stability of AgNbO3 Ceramics
TLDR
In this paper, the microstructure, dielectric properties, and impedance spectra of the AgNbO3 samples co-doped with Bi3+, Zn2+, and Ti4+ were systematically characterized.Abstract:
AgNbO3-based lead-free ceramics are a promising candidate material for capacitors, where thermal stability is a key property for applications in severe and complex environments. This study investigated the fabrication of Ag1-3xBixNb1-3/5x(Zn1/2Ti1/2)xO3\n (ABNZT-x) (x = 0, 0.005, 0.01, 0.02, or 0.04) via a solid-state reaction under oxygen flow. The microstructure, dielectric properties, and impedance spectra of the AgNbO3 samples co-doped with Bi3+, Zn2+, and Ti4+ were systematically\n characterized. All samples exhibited an orthorhombic phase structure, where the average grain size decreased with increasing co-doping level, the grain growth kinetics was studied by phase-field simulation. The phase transition temperatures became lower and the maximum permittivity values\n decreased. These findings demonstrated that enhanced dielectric thermal stability had been achieved. The grain conduction effect was observed during the impedance spectroscopy analysis, where the calculated activation energy decreased with increasing co-doping level. This ABNZT-x ceramic\n system exhibited stable dielectric properties, and shows promise for use as a functional material in electronic devices.read more
Citations
More filters
Journal ArticleDOI
State of health estimation of lithium-ion battery based on improved ant lion optimization and support vector regression
TL;DR: Zhang et al. as discussed by the authors proposed a SOH estimation method based on improved ant lion optimization algorithm and support vector regression (IALO-SVR), which can achieve accurate estimation of SOH with high estimation accuracy and robustness, and the estimation error is stable within 2%.
Journal ArticleDOI
Electrochemical Impedance Spectroscopy Based on the State of Health Estimation for Lithium-Ion Batteries
TL;DR: The improved model (IPSO-CNN-BiLSTM) proposes a convolution neural network (CNN) to process EIS data which can not only extract the key points but also simplifies the complexity of manual feature extraction.
Journal ArticleDOI
Aging state prediction for supercapacitors based on heuristic kalman filter optimization extreme learning machine
TL;DR: In this paper , the authors proposed an optimized forecasting model-an extreme learning machine (ELM) model coupled with the heuristic Kalman filter (HKF) algorithm to forecast the capacity of supercapacitors.
Journal ArticleDOI
Temperature prediction of lithium‐ion batteries based on electrochemical impedance spectrum: A review
TL;DR: In this paper , the main methods of using Electrochemical impedance spectroscopy (EIS) to predict the temperature of lithium-ion batteries have been summarized, including the methods based on the impedance, phase shift, and intercept frequency.
Journal ArticleDOI
Strong robustness and high accuracy in predicting remaining useful life of supercapacitors
TL;DR: In this article , a temporal convolutional network is used to predict the remaining useful life of supercapacitors so as to ensure the reliability of the whole super-capacitor bank.