Results 281 to 290 of about 679,929 (398)

Quantitatively Predicting Angle‐Resolved Polarized Raman Intensity of Anisotropic Layered Materials

open access: yesAdvanced Materials, EarlyView.
This study develops comprehensive methodologies to predict angle‐resolved polarized Raman (ARPR) intensity profiles of anisotropic layered materials (ALMs), spanning from atomically‐thin layers to bulk limit. By considering birefringence, linear dichroism and multilayer interference, the complex refractive indexes and intrinsic Raman tensors are ...
Jia‐Liang Xie   +10 more
wiley   +1 more source

A near-threshold memristive computing-in-memory engine for edge intelligence. [PDF]

open access: yesNat Commun
Wang L   +14 more
europepmc   +1 more source

The Future of MXene Fibers

open access: yesAdvanced Materials, EarlyView.
This perspective explores the diverse applications of MXene fibers, including those often overlooked in fiber‐focused studies. It emphasizes the critical need to address challenges in synthesis, scalability, and long‐term stability to unlock their full potential in real‐world applications. Abstract Since the first report on MXene‐coated fibers in 2017,
Ken Aldren S. Usman   +6 more
wiley   +1 more source

Detachable and Reusable: Reinforced π‐Ion Film for Modular Synaptic Reservoir Computing

open access: yesAdvanced Materials, EarlyView.
This study presents a reinforced π‐ion film for organic electrochemical transistors (OECTs), addressing the rapid degradation of organic semiconductor layers. By introducing a mesh support and utilizing a scalable solvent exchange method, the π‐ion film enhances detachability and stability.
Gyu Won Woo   +8 more
wiley   +1 more source

Hardware Implementation of On‐Chip Hebbian Learning Through Integrated Neuromorphic Architecture

open access: yesAdvanced Materials, EarlyView.
This work presents a neuromorphic hardware platform that integrates presynaptic transistors, threshold switching neurons, and adaptive feedback synapses. The architecture enables on‐chip Hebbian learning through correlation‐based weight updates without external training circuits.
Seonkwon Kim   +6 more
wiley   +1 more source

Synaptic and neural behaviours in a standard silicon transistor. [PDF]

open access: yesNature
Pazos S   +8 more
europepmc   +1 more source

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