Results 161 to 170 of about 204,649 (283)

Multifunctional Structural Electrolyte with Glass Fiber‐Reinforced Polyvinyl Alcohol/Epoxy Matrix with Optimized Lithium Salt and Nanofiller

Advanced Energy and Sustainability Research, EarlyView.
This study presents a novel structural electrolyte reinforced with glass fiber and a polyvinyl alcohol/epoxy matrix incorporating optimized lithium salt and ceramic nanofiller. Its multifunctionality—mechanical, electrochemical, and thermomechanical—is evaluated using various characterization techniques.
Maryam Niazi, Diana Paiva, Federico Danzi, Tânia Lopes, Adélio Mendes, Pedro P. Camanho   +5 more
wiley   +1 more source

Development of Efficient In-Situ Cleaning Methods for Stained Textile Relics. [PDF]

Gels
Wei Y, Guo J, Su Z, Yu K, Ling X, Zhang Z, Liu K, Pan W.   +7 more
europepmc   +1 more source

Strategies for Paired Electrolysis with Enhanced Efficiency

Advanced Energy and Sustainability Research, EarlyView.
This review summarizes the fundamentals, challenges, and strategies for paired electrolysis, with examples in the chlor‐alkali, hydrogen production, CO2 reduction, and ammonia synthesis industries. Future directions include the development of advanced membranes, computational studies, process integration, scale‐up, and techno‐economic analysis.
Yuanyuan Yao, Xin Yang, Yuqi Pan, Leo Lai, Liuyue Cao, Li Wei, Yuan Chen   +6 more
wiley   +1 more source

Reverse Osmosis Membrane Cleaning Optimization from Textile Dyeing Wastewater Reuse Applications. [PDF]

Membranes (Basel)
Wang Z, Ouyang R, Zhang G, Wei C, Ji S, Li Q, Tao C, Rong H.   +7 more
europepmc   +1 more source

Triboelectric Tactile Transducers for Neuromorphic Sensing and Synaptic Emulation: Materials, Architectures, and Interfaces

Advanced Energy and Sustainability Research, EarlyView.
Triboelectric nanogenerators are vital for sustainable energy in future technologies such as wearables, implants, AI, ML, sensors and medical systems. This review highlights improved TENG neuromorphic devices with higher energy output, better stability, reduced power demands, scalable designs and lower costs.
Ruthran Rameshkumar, Arunkumar Chandrasekhar, Poongundran Selvaprabhu   +2 more
wiley   +1 more source

Deep learning-empowered triboelectric acoustic textile for voice perception and intuitive generative AI-voice access on clothing. [PDF]

Sci Adv
Shao B, Wu TC, Yan ZX, Ko TY, Peng WC, Jhan DJ, Chang YH, Fong JW, Lu MH, Yang WC, Chen JY, Lu MY, Sun B, Liu HJ, Liu R, Lai YC.   +15 more
europepmc   +1 more source

Wine Tourism as a Catalyst for Sustainable Performance: The Mediating Role of Corporate Legitimacy and Green Innovation

Agribusiness, EarlyView.
ABSTRACT This study aims to explore the influence of Wine Tourism (WT) on the Sustainable Performance (SP) of wineries in Spain. It particularly investigates how Corporate Social Legitimacy (CSL) and Green Innovation (GI) may act as intermediary factors in this relationship.
Javier Martínez‐Falcó, Eduardo Sánchez‐García, Bartolomé Marco‐Lajara, Luis A. Millán‐Tudela   +3 more
wiley   +1 more source

Datasets of textile fibre persistence and the influence of physical activity for forensic interpretation and statistical analysis. [PDF]

Data Brief
Lau V, Roux C, Spindler X.
europepmc   +1 more source

Sustainability Strategies in the Cocoa‐Chocolate Value Chain: An Analysis Using Stakeholder Theory, Global Value Chain Theory, and Resource Dependence Theory

Agribusiness, EarlyView.
ABSTRACT The cocoa‐chocolate value chain faces significant environmental and social challenges, driving firms to adopt sustainability strategies ranging from individual practices to third‐party certifications. This study investigates the factors associated with these strategies by analyzing 304 cocoa‐chocolate companies using firm‐level data from the ...
Stella Marschner, Luigi Orsi, Alessandro Olper, Stefanella Stranieri   +3 more
wiley   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source