Results 51 to 60 of about 1,643 (192)

MXenes as a Versatile Platform for High‐Energy‐Density Asymmetric Supercapacitors

Carbon Energy, EarlyView.
MXenes with high conductivity and tunable surface chemistry are reviewed as advanced electrodes for asymmetric supercapacitors. MAX‐phase synthesis, surface and interlayer engineering, defect modulation, and composite designs are discussed, highlighting enhanced ion transport, pseudocapacitance, energy density, cycling stability, and sustainable routes
Seul‐Yi Lee, Jagadis Gautam, Shrikant Vaiju Sadavar, Soo‐Jin Park   +3 more
wiley   +1 more source

Perovskite Photodetectors at the Intelligence Frontier: From Tunable Materials to Adaptive Optoelectronic Systems

Carbon Energy, EarlyView.
This comprehensive review presents a progressive roadmap for perovskite vision detectors. Centered on perovskite‐based artificial perception, the graphic illustrates a systematic evolution: starting with fundamental material engineering and device architectures, advancing toward complex functional strategies such as flexible neuromorphic imaging ...
Chenglong Li, Wei Qu, Deepak Kumar, Naini Jain, Nur Wardina Syahirah binti Mohamad Fadil, Nur Najiha binti Ahmad Rasid, Emannuel Kymakis, Maria Vasilopoulou, Chunxiong Bao, Feng Gao, Peng Gao, Sanjeev Kumar Sharma, Mohammad Khaja Nazeeruddin, Abd. Rashid bin Mohd Yusoff, Haotong Wei   +14 more
wiley   +1 more source

Harnessing machine learning and optimization for informed chemical engineering decisions: A styrene reactor analysis

The Canadian Journal of Chemical Engineering, EarlyView.
This study shows that integrating multiple machine learning models with optimization and decision‐making improves chemical process design, and that a consensus‐based strategy across models provides more robust and reliable operating recommendations than any single model, especially under limited or noisy data conditions.
Farough Agin, Clémence Fauteux‐Lefebvre, Jules Thibault   +2 more
wiley   +1 more source

Quantitative Detection of Entotic Cell‐In‐Cell Structures Using Deformable Segmentation and Deep Learning

Cytometry Part A, EarlyView.
ABSTRACT Cell‐in‐cell (CIC) structures are among the most intriguing cellular phenomena occasionally observed in human cancer specimens. Once regarded as incidental findings, accumulating evidence has linked specific CIC subtypes, particularly entosis, to tumor progression and patient prognosis.
Maria V. Leyba‐Mesa, Mikołaj Biegański, Elijah Ray, Izabela Młynarczuk‐Bialy, Buket D. Barkana   +4 more
wiley   +1 more source

Incorporating sampling bias into ENM/SDM permutation tests: new methods and a case study on neotropical ants

Ecography, EarlyView.
Spatial sampling bias in occurrence data can generate spurious environmental associations in models of species distributions and ecological niches, and can also undermine inferences based on permutation tests made using these models. Geographic randomization tests are often used to generate distributions of expected behavior under the null hypothesis ...
Dan L. Warren, Alexandre Cassadei‐Ferreira, Evan P. Economo, Russell Dinnage, Jamie M. Kass   +4 more
wiley   +1 more source

Next‐Generation Carbon‐Based Anodes for Alkali Metal‐Ion Batteries: Recent Progress on Biphenylene and Emerging Materials

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Recent advances in carbon‐based anodes for alkali metal‐ion batteries are critically reviewed, with emphasis on biphenylene and other emerging carbon allotropes. Biphenylene exhibits exceptional theoretical electrochemical properties beyond conventional graphite, highlighting its strong potential as a next‐generation anode material once scalable ...
Adewale Hammed Pasanaje, Nirpendra Singh
wiley   +1 more source

A Rapid Post‐Disaster Restoration Method for Networked Microgrids Based on Adaptive Quantum Particle Swarm Optimization

Energy Science &Engineering, EarlyView.
To enhance the power restoration speed of networked microgrids (NMGs) after extreme natural disasters and reduce the power outage of the system, this paper proposes a rapid post‐disaster restoration method for NMGs based co‐optimization of fault repair and load restoration.
Yunfan Zhang, Qiang Li, Jun Zhang, Chaohuang Xu   +3 more
wiley   +1 more source

Monolithic Framework to Simulate Fluid‐Structure Interaction Problems Using Geometric Volume‐of‐Fluid Method

International Journal for Numerical Methods in Fluids, EarlyView.
A three‐dimensional fluid‐structure interaction (FSI) framework is developed using the geometric volume‐of‐fluid (VOF) interface capturing method and applied to assess largescale turbulent FSI interactions. The monolithic FSI framework is extensively validated, and despite the discontinuities across the interface, the FSI framework delivers stable and ...
Soham Prajapati, Ali Fakhreddine, Krishnan Mahesh   +2 more
wiley   +1 more source

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source

Multifactorial Screening for Fine‐Scale Selection of CCS Industrial Clusters and Hubs in Brazil

Greenhouse Gases: Science and Technology, EarlyView.
ABSTRACT As Brazil moves toward implementing its decarbonization commitments, carbon capture and storage (CCS) hubs are emerging as a key pathway for large‐scale CO2 abatement in hard‐to‐abate sectors. This paper presents a multifactorial, data‐driven framework to screen and prioritize potential CCS industrial clusters and hubs across Brazilian regions,
Gustavo P. Oliveira, Beatriz R. Almeida, Thiago R. C. Justino, Carlos A. S. Santos, Alex A. Santos, Fabiana Philipi   +5 more
wiley   +1 more source