Results 111 to 120 of about 21,720 (266)
In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar +9 more
wiley +1 more source
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
On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification
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 +4 more
wiley +1 more source
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj +4 more
wiley +1 more source
Array‐Level Characterization of Cryogenic RRAM
This paper reports the first array‐level comprehensive electrical characterization of a 1024‐device HfO2‐based RRAM array from 300, 77 to 4 K, covering forming, set/reset switching, endurance, retention, relaxation, and read disturb. The results manifest the high performance of RRAM array at cryogenic temperatures and huge application potential for ...
Yuyao Lu +7 more
wiley +1 more source
Compact circuits based on contact‐controlled transistors are well‐suited to unsupervised thermal management, sensitive temperature measurement, or temperature‐stable current references. Demonstrated on flexible microcrystalline silicon and supported by simulation, the approach does not require supply voltage regulation, remains manufacturable across ...
Eva Bestelink +6 more
wiley +1 more source
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
Study on Power Line Coupler for Auxiliary Power to Overhead Line
Gunbok Lee +4 more
openaire +1 more source
Integration of a physical solar cell model into Bayesian optimization is performed using the Knowledge Gradient acquisition function to balance exploration and exploitation. Experimental validation on the PTQ10:BTP‐eC9 material system and statistical validation on an OPV benchmark function show that the model‐based approach outperforms conventional ...
Leonard Christen, Thomas Kirchartz
wiley +1 more source
Abstract Electrification of distillation offers a promising route to reducing scope‐1 emissions from one of the chemical industry's most energy‐intensive unit operations. However, conventional adiabatic columns are dynamically inflexible: Long, energy‐intensive start‐ups make shutdown and restart impractical under variable electricity prices and ...
Samuel Mercer, Michael Baldea
wiley +1 more source

