Results 181 to 190 of about 6,919 (250)

Memristors Based on Ferroelectric Cu‐Deficient Copper Indium Thiophosphate for Multilevel Storage and Neuromorphic Computing

open access: yesSmall, EarlyView.
Different from CIPS with threshold switching behaviors, Cu‐deficient CIPS* shows stable non‐volatile digital and analog RS. Owing to the formation of metallic IPS at the LRS, CIPS* memristors demonstrate high ON/OFF ratio and endurance stability, which can be utilized to implement multilevel storage.
Mengdie Li   +6 more
wiley   +1 more source

Opportunities for 2D‐Material‐Based Multifunctional Devices and Systems in Bioinspired Neural Networks

open access: yesSmall, EarlyView.
Bio‐inspired computing offers a route to highly energy‐efficient artificial intelligence. The unique physical properties of two‐dimensional (2D) materials can further enhance such computing approaches. This perspective highlights recent developments in 2D materials‐based neuromorphic devices and discusses future opportunities for integrating such novel
Jin Feng Leong   +9 more
wiley   +1 more source

Exploiting Device Deformability for Fluid and Particle Manipulation

open access: yesSmall, EarlyView.
Deformable devices enable fluid and particle manipulation modes that are inaccessible to rigid platforms. This review examines soft materials and architectures that translate controlled deformation into microscale fluid operations such as pumping, valving, mixing, and particle handling.
Zhiyang Hong   +4 more
wiley   +1 more source

Tailoring Model‐Based Systems Engineering for Sub‐100 g PlanarSats: A Power‐First View Stack

open access: yesSystems Engineering, EarlyView.
ABSTRACT This paper addresses how to apply model‐based systems engineering (MBSE) to ultrasmall planar satellites under severe power and resource constraints. PlanarSats are sub‐100‐gram spacecraft built as single printed‐circuit boards where the same surface must host both electronics and solar cells, so power generation, geometry, and component ...
Mehmet Şevket Uludaǧ   +1 more
wiley   +1 more source

Reinforcement Learning With Timed Constraints for Robotics Motion Planning

open access: yesArtificial Intelligence for Engineering, EarlyView.
This work presents a unified automata‐based reinforcement learning framework that enforces MITL time‐bounded task specifications in both MDPs and POMDPs. Results from grid‐world and office scenarios show robust policy learning under stochastic dynamics and partial observability.
Zhaoan Wang   +3 more
wiley   +1 more source

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