Results 121 to 130 of about 6,930,474 (290)

Sustainable and Multifunctional Natural Macromolecular Polymers for Aqueous Zn Metal Batteries

Advanced Materials, EarlyView.
We comprehensively review the structure‐function relationships and regulatory mechanism of natural macromolecular polymers in stabilizing zinc anodes at the microscopic and mesoscopic scales. The interactions among polymer structures, optimization strategies, and regulatory mechanisms are discussed systematically summarizing recent related research ...
Yunuo Shi, Bo Jiang, Jingcheng Zhang, Xiaodong Shao, Peixun Xiong, Lutong Shan, Shengyang Huang, Mengfang Liang, Mengyao Chang, Fangyan Liu, Wenwu Li, Baoyu Xia, Wei Ji, Ho Seok Park   +13 more
wiley   +1 more source

Electrolyte Design for Fast‐Charging Lithium‐Based Batteries

Advanced Materials, EarlyView.
A decade of progress in fast‐charging electrolytes for lithium batteries is reviewed. Electrolyte design strategies spanning solvents, salts, additives, and advanced systems, such as localized high‐concentration electrolytes (LHCEs), are summarized. Advanced diagnostic tools for lithium plating and interphase chemistry are discussed, with perspectives ...
Chen Liu, Zehao Cui, Arumugam Manthiram
wiley   +1 more source

Memory Allocation in Resource-Constrained Reinforcement Learning

CoRR
RLDM ...
Massimiliano Tamborski, David Abel
openaire   +3 more sources

Polyphenol‐Inspired Materials for Agricultural Applications

Advanced Materials, EarlyView.
This review outlines the use of polyphenol‐inspired materials for sustainable agriculture, highlighting their molecular design, interfacial assembly, structure–property relationships, and prospects toward precision agriculture, climate resilience, ecosystem protection, and circular bioeconomy strategies.
Haofu Liu, Omid Mazaheri, Zhixing Lin, Tianzheng Wang, Jingqu Chen, Yuang Gu, Xia Liang, Deli Chen, Frank Caruso   +8 more
wiley   +1 more source

Scaling Reinforcement Learning Paradigms for Motor Control [PDF]

, 2003
Reinforcement learning offers a general framework to explain rewardrelated learning in artificial and biological motor control. However, current reinforcement learning methods rarely scale to high dimensional movement systems and mainly operate in ...
Vijayakumar, S.; id_orcid, Schaal, S., Peters, J.   +2 more
core  

Large Scale Constrained Clustering With Reinforcement Learning

CoRR
Given a network, allocating resources at clusters level, rather than at each node, enhances efficiency in resource allocation and usage. In this paper, we study the problem of finding fully connected disjoint clusters to minimize the intra-cluster distances and maximize the number of nodes assigned to the clusters, while also ensuring that no two nodes
Benedikt Schesch, Marco Caserta
openaire   +2 more sources

Integrating Risk-Averse and Constrained Reinforcement Learning for Robust Decision-Making in High-Stakes Scenarios

Mathematics
This paper considers a risk-averse Markov decision process (MDP) with non-risk constraints as a dynamic optimization framework to ensure robustness against unfavorable outcomes in high-stakes sequential decision-making situations such as disaster ...
Moiz Ahmad, Muhammad Babar Ramzan, Muhammad Omair, Muhammad Salman Habib   +3 more
doaj   +1 more source

Artificial Intelligence Meets Micro/Nanorobotics

Advanced Materials, EarlyView.
Artificial intelligence is transforming micro‐ and nanorobots from externally controlled, task‐specific machines into adaptive, autonomous systems. Machine learning, multimodal perception, digital twins, AI‐guided materials and geometry design enhance propulsion, localization, decision‐making, whichaccelerates clinical and environmental applications ...
Fatma M. Yurtsever, Minitha Cherukutty Ramakrishnan, Ian Kuula Ross, Ivan Zelinka, Hamed Shahsavan, Michal Otyepka, Martin Pumera   +6 more
wiley   +1 more source

Decoding Synergistic Pathways in Bimetallic MOFs for Advanced Oxidation Processes

Advanced Materials, EarlyView.
This review presents a unified framework linking metal pairing and framework design with electronic structure, redox cycling, oxidant activation, reactive‐species generation, and catalytic performance across photocatalytic and oxidant‐based BMOF‐AOPs. The resulting design principles guide the development of hydrolytically stable and efficient BMOFs for
Karim El‐Naggar, Huayang Zhang, Shaobin Wang   +2 more
wiley   +1 more source

Intelligent Task Offloading and Energy Management for Battery-Less 6G Industrial IoT Using Multi-Agent Deep Reinforcement Learning

Sulaimani Journal for Engineering Sciences
Battery-less Industrial Internet of Things (IIoT) devices that are energized by energy harvesting (EH) must both finish latency-critical tasks and avoid capacitor brownouts simultaneously, but prior multi-agent learning approaches only optimize average ...
Ghufran Farhan Marzoog , Ammar Awad Kazm , Mustafa Kamil Ati   +2 more
doaj   +1 more source