Results 151 to 160 of about 148,724 (314)

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Advancing Lithium–Oxygen Batteries: Pioneering Cathode Catalyst Innovation and Artificial Intelligence‐Driven Design Paradigms

Advanced Materials, EarlyView.
This review summarizes the principles and challenges of nonaqueous lithium‐oxygen batteries and recent advances in cathode catalysts, including carbon‐based materials, metals, oxides, sulfides, nitrides, carbides, and redox mediators. It highlights emerging design strategies and artificial intelligence‐driven approaches, emphasizing data‐assisted ...
Yuqing Yao, Chongyang Hao, Karol Viviana Mejia‐Centeno, Malik Dilshad Khan, Shang Wang, Longqiu Li, Yanhong Tian, Andreu Cabot, Qing Sun   +8 more
wiley   +1 more source

Sum-rate optimization methods and analysis for reconfigurable intelligent surface aided communication system

Digital Communications and Networks
When deploying Reconfigurable Intelligent Surface (RIS) to improve System Sum-Rate (SSR), the timeliness and accuracy of SSR optimization methods are difficult to achieve simultaneously through a single algorithm.
Jinfeng Li, Xiaorong Zhu
doaj   +1 more source

Checking LTL Properties of Recursive Markov Chains

, 2005
We present algorithms for the qualitative and quantitative model checking of Linear Temporal Logic (LTL) properties for Recursive Markov Chains (RMCs). Recursive Markov Chains are a natural abstract model of procedural probabilistic programs and related ...
M. Yannakakis, Yannakakis, Mihalis, Etessami, Kousha; id_orcid, K. Etessami   +3 more
core   +1 more source

Methods and algorithms of swarm intelligence for the problems of nonlinear regression analysis and optimization of complex processes, objects, and systems: review and modification of methods and algorithms

System Research in Energy
The development of high-speed methods and algorithms for global multidimensional optimization and their modifications in various fields of science, technology, and economics is an urgent problem that involves reducing computing costs, accelerating, and effectively searching for solutions to such problems.
Vladyslav Khaidurov, Vadym Tatenko, Mykyta Lytovchenko, Tamara Tsiupii, Tetiana Zhovnovach   +4 more
openaire   +2 more sources

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Evolutionary algorithms in artificial intelligence: a comparative study through applications [PDF]

, 1994
For many years research in artificial intelligence followed a symbolic paradigm which required a level of knowledge described in terms of rules. More recently subsymbolic approaches have been adopted as a suitable means for studying many problems.
Nettleton, David John, Nettleton, D.J
core  

Machine Learning Accelerated Computational Design of Bio‐Inspired Catalysts in the Nitrogen Reduction Reaction

Advanced Materials, EarlyView.
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano, Zihan You, Haoran Chen, Qifan Zhong, Rong‐Zhen Liao, Shaoqi Zhan   +5 more
wiley   +1 more source

Deep Learning Inverse Design of Phase‐Change Reconfigurable Terahertz Metadevices for Multidimensional Secure Communication

Advanced Materials, EarlyView.
A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong, Xieyu Chen, Aarthy Nagarajan, Yi Yang, Zhihao Wang, Rui Yu, Chuang Zheng, Chunmei Ouyang, Xueqian Zhang, Tun Cao, Ranjan Singh, Zhen Tian   +11 more
wiley   +1 more source

A Survey of Interlayer Interaction Models for Graphene and Other 2D Materials

Advanced Materials Interfaces, EarlyView.
Van der Waals interactions arising from electronic polarization at atomically close interfaces generate corrugated interlayer energy landscapes that govern normal and tangential tractions. This review presents an overview of quantum, atomistic, analytical, and continuum modeling approaches, highlighting their roles across length scales in capturing ...
Gourav Yadav, Shakti S. Gupta, Roger A. Sauer   +2 more
wiley   +1 more source