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Language Switching for Inexperienced Foreign Language Speakers

Language Switching for Inexperienced Foreign Language Speakers
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Optical Charge Trap Memory Based on Graphene/ZnO Heterostructures for Long‐Term Retention and Adaptive Learning

Advanced Electronic Materials, EarlyView.
A biocompatible graphene/ZnO optical charge trap memory (CTM) is reported with over 54 h retention, enabled by interfacial photodoping. Using transient absorption spectroscopy and electrical analysis, charge transfer quenching is elucidated and reveal that a large energy barrier at the interface is responsible for long‐term memory retention.
Seungmin Shin, Junhyung Kim, Hyungdoh Lee, Yixuan Dou, Jacob T. Heiden, Seung Eun Lee, Jinwoo Song, Lina Quan, Giulia Tagliabue, Min Seok Jang, Himchan Cho   +10 more
wiley   +1 more source

Life‐Cycle Assessment of Printed Electronic Components ‐ Case Study for Organic Electrochemical Transistors

Advanced Electronic Materials, EarlyView.
This tutorial introduces a practical framework for implementing early‐stage Life‐Cycle Assessment (LCA) in flexible and printed electronics. Using organic electrochemical transistors (OECTs) as a case study, the modular Process‐of‐Record and open‐access inventory provides a rich resource adaptable to a plethora of technologies in printed electronics ...
Laura Teuerle, Tommy Meier, Klara Hänisch, Finn Jaekel, Yeohoon Yoon, Andreas Wendel, Hans Kleemann   +6 more
wiley   +1 more source

Conformal Reconfigurable Intelligent Surfaces: A Cylindrical Geometry Perspective

Advanced Electronic Materials, EarlyView.
Cylindrical reconfigurable intelligent surfaces are explored for low‐complexity beam steering using one‐bit meta‐atoms. A multi‐level modeling approach, including optimization‐based synthesis, demonstrates that even minimal hardware can support directive scattering.
Filippo Pepe, Ivan Iudice, Giuseppe Castaldi, Marco Di Renzo, Vincenzo Galdi   +4 more
wiley   +1 more source

Electrode‐Engineered Dual‐Mode Multifunctional Lead‐Free Perovskite Optoelectronic Memristors for Neuromorphic Computing

Advanced Electronic Materials, EarlyView.
A lead‐free perovskite memristive solar cell structure that call emulate both synaptic and neuronal functions controlled by light and electric fields depending on top electrode type. ABSTRACT Memristive devices based on halide perovskites hold strong promise to provide energy‐efficient systems for the Internet of Things (IoT); however, lead (Pb ...
Michalis Loizos, Konstantinos Rogdakis, Konstantinos Chatzimanolis, Katerina Anagnostou, Emmanuel Kymakis   +4 more
wiley   +1 more source

Twisted MoS2 Bilayers as Functional Elements in Memtransistors: Hysteresis, Optical Signatures, and Photocurrent Kinetics

Advanced Electronic Materials, EarlyView.
ABSTRACT Layered 2D materials are considered as promising for memristive applications due to their ultimate vertical scalability compared to conventional semiconductor films and pronounced hysteresis properties. Bias‐resolved Raman and Photoluminescence mapping is used to quantify strain from phonon shifts and carrier density from the exciton‐trion ...
Vladislav Kurtash, Ilya Eliseyev, Valery Davydov, Heiko O. Jacobs, Jörg Pezoldt   +4 more
wiley   +1 more source

Low‐Power Control Of Resistance Switching Transitions in First‐Order Memristors

Advanced Electronic Materials, EarlyView.
Joule losses are a serious concern in modern integrated circuit design. In this regard, minimizing the energy necessary for programming memristors should be handled with care. This manuscript presents an optimal control framework, allowing to derive energy‐efficient programming voltage protocols for resistance switching devices. Following this approach,
Valeriy A. Slipko, Alon Ascoli, Fernando Corinto, Yuriy V. Pershin   +3 more
wiley   +1 more source

Enhanced High Dimensionality and the Information Processing Capacity in Interfered Spin Wave‐Based Reservoir Computing, Achieved With Eight Detectors

Advanced Electronic Materials, EarlyView.
Physical reservoir computing (PRC) based on spin wave interference has demonstrated high computational performance, yet room for improvement remains. In this study, we fabricated this concept PRC with eight detectors and evaluated the impact of the number of detectors using a chaotic time series prediction task.
Sota Hikasa, Wataru Namiki, Daiki Nishioka, Maki Nishimura, Ryo Iguchi, Kazuya Terabe, Takashi Tsuchiya   +6 more
wiley   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification

Advanced Electronic Materials, EarlyView.
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels, Duna Wattad, Ronny Ronen, David Saad, Shahar Kvatinsky   +4 more
wiley   +1 more source