Results 201 to 210 of about 1,026,038 (317)

Organic Thin‐Film Transistors for Neuromorphic Computing

open access: yesAdvanced Electronic Materials, EarlyView.
Organic thin‐film transistors (OTFTs) are reviewed for neuromorphic computing applications, highlighting their power‐efficient, and biological time‐scale operation. This article surveys OFET and OECT devices, compares them with memristors and CMOS, analyzes how fabrication parameters shape spike‐based metrics, proposes standardized characterization ...
Luke McCarthy   +2 more
wiley   +1 more source

Photoresponse Properties of Ambipolar Transport in WSe2 Field‐Effect Transistors

open access: yesAdvanced Electronic Materials, EarlyView.
This study explores the photoresponse of WSe2 ambipolar field‐effect transistors, which exhibit unipolar, saturation, and ambipolar transport regions. Light illumination induces a shift of critical voltage with enhanced photocurrent generation driven by the photogating effect without the material degradation seen in avalanche photodetectors. This study
Jongeun Yoo   +11 more
wiley   +1 more source

Aging and Electrical Stability of DNTT Honey‐Gated OFETs

open access: yesAdvanced Electronic Materials, EarlyView.
DNTT honey‐gated organic transistors were fabricated and evaluated to assess short‐ and long‐term stability under electrical stress and aging. Short‐term transfer measurements (five days, 40 sweeps/day) showed minimal parameter shift, while extended measurements revealed gradual degradation over weeks.
Douglas H. Vieira   +8 more
wiley   +1 more source

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

open access: yesAdvanced 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   +6 more
wiley   +1 more source

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

open access: yesAdvanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez   +10 more
wiley   +1 more source

Home - About - Disclaimer - Privacy