Results 131 to 140 of about 289,279 (277)

Corn Leaf Disease Classification Optimization Using Resnet50 Architecture Utilizing Bayesian Optimization

open access: yesJournal of Electrical Engineering and Computer
This research aims to optimize the classification of diseases on corn leaves using Convolutional Neural Network (CNN) architecture, ResNet50, combined with hyperparameter optimization techniques using Bayesian Optimization.
Yahya Auliya Abdillah, Kusrini Kusrini
doaj   +1 more source

A smart headband for multimodal physiological monitoring in human exercises

open access: yesAdvanced Science, EarlyView.
A novel smart headband incorporating a thermal‐sensation‐based electronic skin is presented for continuous and accurate multimodal physiological monitoring, including pulse waveforms, total metabolic energy expenditure, heart rate, and forehead temperature, across both static and dynamic daily activities.
Shiqiang Liu   +7 more
wiley   +1 more source

Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges

open access: yesAdvanced Science, EarlyView.
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang   +6 more
wiley   +1 more source

Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems

open access: yesAdvanced Electronic Materials, EarlyView.
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang   +9 more
wiley   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

open access: yesAdvanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho   +6 more
wiley   +1 more source

Integrating Automated Electrochemistry and High‐Throughput Characterization with Machine Learning to Explore Si─Ge─Sn Thin‐Film Lithium Battery Anodes

open access: yesAdvanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin   +7 more
wiley   +1 more source

Quantifying Evolving Defect Parameters in Metal Halide Perovskites via the Measurement and Modeling of Power‐Dependent Transient Photoluminescence

open access: yesAdvanced Energy Materials, EarlyView.
ABSTRACT Dynamic photoinduced defect states in metal halide perovskites (MHPs) critically govern the non‐equilibrium photophysics, metastability, and long‐term performance of optoelectronic devices, such as solar cells. This metastability is evident in steady‐state photoluminescence experiments, where the amplitudes increase or decrease depending on ...
Maxim Simmonds   +6 more
wiley   +1 more source

Roadmap for High‐Throughput Ceramic Materials Synthesis and Discovery for Batteries

open access: yesAdvanced Energy Materials, EarlyView.
This work examines ceramic synthesis through the lens of high‐throughput synthesis and optimization, identifying opportunities for faster, adaptable routes. It emphasizes flexible liquid precursor–to–solid film methods over slower solid‐state approaches and highlights computer‐aided decision making to optimize both material properties and device ...
Jesse J. Hinricher   +10 more
wiley   +1 more source

Inversion of the Impedance Response Towards Physical Parameter Extraction Using Interpretable Machine Learning

open access: yesAdvanced Energy Materials, EarlyView.
ABSTRACT Interpreting the impedance response of perovskite solar cells (PSCs) is challenging due to the complex coupling of ionic and electronic motion. While drift‐diffusion (DD) modelling is a reliable method, its mathematical complexity makes directly extracting physical parameters from experimental data infeasible.
Mahmoud Nabil   +4 more
wiley   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

open access: yesAdvanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan   +12 more
wiley   +1 more source

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