Results 91 to 100 of about 315,597 (224)

Practical Lithium–Sulfur Batteries: An Integrated Design Roadmap from High‐Loading Cathodes to High‐Energy Pouch Cells

Advanced Science, EarlyView.
This review presents an integrated design roadmap for practical lithium–sulfur batteries, moving beyond isolated material breakthroughs to the synergistic combination of three interdependent frontiers: Scale‐Up, Electrolyte‐Cathode Synergy, and AI/ML Data‐Driven Design.
Shihzad Shakil, Fan Wang, Lejun Fu, Yuye Huang, Hanhui Lei, Jiarui Huang, Terence Xiaoteng Liu   +6 more
wiley   +1 more source

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

Advanced 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, Weipeng Wang, Xuan Cong, Shiyu Wang, Gao Li, Sen Gong, Lin Huang, Hongxin Zeng, Yaxin Zhang, Ziqiang Yang   +9 more
wiley   +1 more source

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials, EarlyView.
Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley   +1 more source

A Dual‐Memory Ferroelectric Transistor Emulating Synaptic Metaplasticity for High‐Speed Reservoir Computing

Advanced Electronic Materials, EarlyView.
A CMOS‐compatible ferroelectric transistor harnesses the interplay between stable gate polarization memory and volatile non‐quasi‐static channel charge dynamics to emulate how biological synapses regulate their own plasticity. This brain‐inspired dual‐memory mechanism, realized in a single device, enables a physical reservoir computer that solves ...
Yifan Wang, Muhammad Sakib Shahriar, Salma Soliman, Noah Vaillancourt, Lance Fernandes, Andrea Padovani, Asif Islam Khan, Md Sakib Hasan, Raisul Islam   +8 more
wiley   +1 more source

SPICE‐Compatible Compact Modeling of Cuprate‐Based Memristors Across a Wide Temperature Range

Advanced Electronic Materials, EarlyView.
A physics‐guided compact model for YBCO memristors is introduced, incorporating carrier trapping, field‐induced detrapping, and a differential balance equation to describe their switching dynamics. The model is compared with experiments and implemented in LTspice, allowing realistic circuit‐level simulations.
Thomas Günkel, Aleix Barrera, Lluís Balcells, Narcís Mestres, Enrique Miranda, Anna Palau, Jordi Suñé   +6 more
wiley   +1 more source

An In‐Line Machine Vision–Based Profilometry Tool for Non‐Destructive Thickness Assessment of Perovskite Films

Advanced Electronic Materials, EarlyView.
This work proposes a machine‐vision‐based tool for predicting the thickness of in‐line deposited perovskite films, enabling real‐time decision making to control deposition parameters. The workflow integrates perovskite deposition and annealing with uniformity analysis and minimodule fabrication.
Juan Pablo Velásquez, Juan José Patiño, Keony Jimenez, Santiago Mesa, Milton Perez, Ershad Parvazian, Edwin Alexander Ramírez, Rafael Betancur, Trystan Watson, Franklin Jaramillo   +9 more
wiley   +1 more source

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

Advanced 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, Isel Grau, Ricardo Grau‐Crespo, Said Hamad, Juan A. Anta   +4 more
wiley   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

Model‐based fault diagnosis and fault tolerant control in safety‐critical chemical reactors: An experimental study

AIChE Journal, EarlyView.
Abstract This study investigates a fault‐tolerant control (FTC) approach for continuous stirred‐tank reactors (CSTR), emphasizing the importance of timely interventions to ensure operational safety under fault conditions. A systematic methodology combining residual‐based fault estimation and Dynamic Safety Margin (DSM) monitoring is developed to guide ...
Pu Du, Ritu Ranjan, Benjamin Wilhite, Costas Kravaris   +3 more
wiley   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source