Results 151 to 160 of about 98,895 (273)

Aqueous Zinc‐Based Batteries: Active Materials, Device Design, and Future Perspectives

Advanced Energy Materials, EarlyView.
This review conducts a comprehensive analysis of aqueous zinc‐based batteries (AZBs) based on their intrinsic mechanisms, including redox reactions, ion intercalation reactions, alloying reactions, electrochemical double‐layer reactions, and mixed mechanisms, systematically discussing recent advancements in each type of AZBs.
Yan Ran, Fang Dong, Shuhui Sun, Yong Lei
wiley   +1 more source

Toward Complete CO2 Electroconversion: Status, Challenges, and Perspectives

Advanced Energy Materials, EarlyView.
Electrocatalytic CO2 reduction and CO2 batteries face challenges in achieving complete CO2 conversion with high conversion rates and Faradaic efficiency simultaneously. Existing systems compromise one for the other with incomplete CO2 conversion and inefficiencies, hindering practical applications. This perspective highlights state‐of‐the‐art progress,
Changfan Xu, Ping Hong, Yulian Dong, Marc Robert, Guosheng Shao, Yong Lei   +5 more
wiley   +1 more source

From Materials to Systems: Challenges and Solutions for Fast‐Charge/Discharge Na‐Ion Batteries

Advanced Energy Materials, EarlyView.
This review systematically analyzes the key characteristics limiting the fast‐charge/discharge capability of Na‐ion batteries (SIBs) from a multi‐scale perspective encompassing electrode materials, the electrode‐electrolyte interface, and the system. Furthermore, it presents practical solution strategies for the fundamental issues arising at each scale,
Bonyoung Ku, Sangbin Park, Sunha Hwang, Sunghyun Lim, Won‐Sub Yoon, Jongsoon Kim   +5 more
wiley   +1 more source

Multi modal hierarchical reinforcement learning framework for dynamic sports sponsorship optimization. [PDF]

Sci Rep
Yu Q.
europepmc   +1 more source

Safety of Sodium‐Ion Batteries: Evaluation and Perspective from Component Materials to Cells, Modules, and Packs

Advanced Energy Materials, EarlyView.
This review provides a bottom‐up evaluation of sodium‐ion battery safety, linking material degradation mechanisms, cell engineering parameters, and module/pack assembly. It emphasizes that understanding intrinsic material stability and establishing coordinated engineering control across hierarchical levels are vital for preventing degradation coupling ...
Won‐Gwang Lim, Seoa Kim, Erik A. Wu, Darren H. S. Tan, Shawn Peng, Xiaolin Li   +5 more
wiley   +1 more source

A Federated Hierarchical DQN-Based Distributed Intelligent Anti-Jamming Method for UAVs. [PDF]

Sensors (Basel)
Ni D, Ma S, Du J, Wu Y, Zhou C, Xiao H.
europepmc   +1 more source

Citizen Engagement for Social and Technological Innovation in Sustainable Energy Systems

Advanced Energy and Sustainability Research, EarlyView.
This study underscores the potential of citizen participation in the energy transition by providing insights to foster citizen‐driven innovation. An analysis of energy communities, one of the most dynamic innovations in the energy sector, reveals that these models can be citizen‐led initiatives regarding their operational and organizational structure ...
Ana Belén Cristóbal, Cristina Sanz‐Cuadrado, Kiane Alves e Silva, Luis Narvarte   +3 more
wiley   +1 more source

Adaptive airspace allocation model for urban drone logistics using multi-objective optimization under uncertainty. [PDF]

Sci Rep
Zhu Y, Sun X, Hou T.
europepmc   +1 more source

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

Advanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod, Ajay Vikram Singh, Preeti Bhardwaj, Tulika Rai, Sweta Vijay Nakhale, Amruta Shelar, Rajendra Patil, Peter Laux, Andreas Luch, Christopher J. Osgood, Michael W. Stacey   +10 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source