Results 241 to 250 of about 57,740 (314)

Advanced Ceramics in Aerospace and Defense: The Interrelationship between Traditional and Additive Manufacturing Approaches

Advanced Materials Technologies, EarlyView.
Additive manufacturing revolutionizes production by enabling on‐demand, customized, and sustainable manufacturing with streamlined supply chains. While metal and polymer AM are well‐established, advanced ceramic AM is rapidly emerging, overcoming traditional material challenges.
Kateryna Oleksandrivna Shvydyuk, Senentxu Lanceros‐Mendez, Abílio Pereira Silva   +2 more
wiley   +1 more source

Deep Reinforcement Learning of Mobile Robot Navigation in Dynamic Environment: A Review. [PDF]

Sensors (Basel)
Zhu Y, Wan Hasan WZ, Harun Ramli HR, Norsahperi NMH, Mohd Kassim MS, Yao Y.   +5 more
europepmc   +1 more source

An Exploration Strategy Improves the Diversity of de novo Ligands Using Deep Reinforcement Learning – A Case for the Adenosine A2A Receptor

, 2018
Xuhan Liu, Kai Ye, Herman van Vlijmen, Adriaan P. IJzerman, Gerard J. P. van Westen   +4 more
openalex   +1 more source

Diamond 2D/3D Printing Technology: Bringing Scintillating Performance to Functional Materials and Their Applications

Advanced Materials Technologies, EarlyView.
This review highlights advances in printing with nano‐ and microparticulate diamond for applications such as sensors, thermal management, machining tools, and biointerfaces. By covering screen, inkjet, microcontact, and 3D printing techniques, it outlines how diamond particles can be integrated into composite materials and functional devices, while ...
Simona Baluchová, Josephus G. Buijnsters   +1 more
wiley   +1 more source

Rotary 4D Printing of Programmable Metamaterials on Sustainable 4D Mandrel

Advanced Materials Technologies, EarlyView.
The paper introduces open, rotary 4D printing of programmable tubular metamaterials. It presents an open, non‐planar path‐to‐G‐code pipeline and shape‐changing rotary mandrel that enable support‐free fabrication and multi‐stimuli actuation. Experiments and FEA validate the mentioned features and stress redistribution.
Hesam Soleimanzadeh, Mahdi Bodaghi, Marzieh Jamalabadi, Bernard Rolfe, Ali Zolfagharian   +4 more
wiley   +1 more source

Applications of QSPR and Machine Learning in Molecular Photonics

Advanced Optical Materials, EarlyView.
Quantitative structureproperty relationships (QSPR) and machine learning (ML) are transforming photochemistry by enabling pre‐synthetic screening of photoactive molecules. This review outlines advances in data‐driven discovery of optical materials and functional dyes, identifies effective descriptors and models for photophysical processes, and provides
Andrey A. Buglak, Platon P. Chebotaev, Mikhail A. Filatov   +2 more
wiley   +1 more source

Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning. [PDF]

Sci Rep
Liu Q, Ma Y.
europepmc   +1 more source

Cloaking and Antennas: From Theoretical Paradigms to Next‐Generation Intelligent Systems

Advanced Optical Materials, EarlyView.
The inception of electromagnetic cloaking sparked an immediate question: Can antennas be made invisible? Two decades later, this review charts the intertwined progress of major cloaking strategies (from transformation optics to scattering cancellation), metasurface technology, and their application to antennas, revealing how AI‐enabled devices are ...
Helen Guo, Xun Li
wiley   +1 more source

Analysis of Deep Reinforcement Learning Algorithms for Task Offloading and Resource Allocation in Fog Computing Environments. [PDF]

Sensors (Basel)
Ali EM, Abawajy J, Lemma F, Baho SA.
europepmc   +1 more source

Multiobject Tracking in Videos Based on LSTM and Deep Reinforcement Learning

, 2018
Mingxin Jiang, Chao Deng, Zhigeng Pan, Lanfang Wang, Xing Sun   +4 more
openalex   +1 more source