Results 131 to 140 of about 135,414 (287)

Enhanced Stability in Zero‐Excess Li‐Metal Batteries via Prelithiated Carbon Nanofiber Interlayers

Advanced Science, EarlyView.
Carbon nanofibers carbonized at 700°C show Li metal deposition predominantly on the side facing the Cu current collector. During delithiation, Li agglomerates remain as inactive lithium on the fiber surface. This behavior can be changed by a modified n‐Buli prelithiation without a washing step, suppressing dead Li formation and therefore enabling ...
Sandro Schöner, Marius Ast, Vera Michaela Barysch, Rebecca Erkes, Jule Meier‐Merziger, Pengfei Cao, Joachim Mayer, Josef Granwehr, Fabian Jeschull, Hermann Tempel, Shicheng Yu, Rüdiger‐A. Eichel   +11 more
wiley   +1 more source

Neural decoding using a parallel sequential Monte Carlo method on point processes with ensemble effect. [PDF]

Biomed Res Int, 2014
Xu K, Wang Y, Wang F, Liao Y, Zhang Q, Li H, Zheng X.   +6 more
europepmc   +1 more source

A Data‐Driven Inverse Design Methodology for Magnetic Soft Millirobots Navigating in Confined Spaces

Advanced Science, EarlyView.
A data‐efficient inverse design framework automates the optimization of magnetic soft millirobots for confined‐space navigation. Integrating a physics‐based Cosserat rod model with Bayesian optimization efficiently identifies high‐performance geometries.
Ziyu Ren, Hong Wang, Chak Wang Tse, Yi Zheng, Xi Chen, Wenqi Hu   +5 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

Composite reliability assessment of systems with grid‐edge renewable resources via quasi‐sequential Monte Carlo and cross‐entropy techniques

IET Generation, Transmission & Distribution
The still growing share of intermittent renewable sources in the electric energy matrix is a factor that greatly increases the complexity of modelling electrical power systems. Although its exploitation is conditioned to the geographic location where the
Bruno A. S. Manso, Armando M. Leite da Silva, André Milhorance, Fernando A. Assis   +3 more
doaj   +1 more source

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification

Advanced Electronic Materials, EarlyView.
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels, Duna Wattad, Ronny Ronen, David Saad, Shahar Kvatinsky   +4 more
wiley   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Comparative Insights and Overlooked Factors of Interphase Chemistry in Alkali Metal‐Ion Batteries

Advanced Energy Materials, EarlyView.
This review presents a comparative analysis of Li‐, Na‐, and K‐ion batteries, focusing on the critical role of electrode–electrolyte interphases. It especially highlights overlooked aspects such as SEI/CEI misconceptions, binder effects, and self‐discharge relevance, emphasizing the limitations of current understanding and offering strategies for ...
Changhee Lee, Zachary T. Gossage, Shinichi Kumakura, Shinichi Komaba   +3 more
wiley   +1 more source

Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries

Advanced Energy Materials, EarlyView.
This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu, Huaping Zhao, Lizhuang Chen, Weidong Shi, Guosheng Shao, Yong Lei   +5 more
wiley   +1 more source