Results 241 to 250 of about 203,112 (311)

Predictable and Scalable Analog Matrix–Vector Multiplication in Memristor Crossbars via Closed‐Form Wire‐Resistance Compensation

open access: yesAdvanced Electronic Materials, EarlyView.
Wire resistance and sneak paths severely compromise the performance of large memristor crossbars. A predictive closed‐form distributed line‐resistance model, combined with a fourmatrix geometry‐averaging algorithm, eliminates these parasitic limitations.
Davide Rossetti   +5 more
wiley   +1 more source

A Pacific carbonate budgets approach reveals overall net positive production on O'ahu, Hawai'i. [PDF]

open access: yesPLoS One
Alagata CE   +5 more
europepmc   +1 more source

Impact of Rapid Thermal Annealing on the Structural and Piezoelectric Properties of AlN Thin Films

open access: yesAdvanced Electronic Materials, EarlyView.
Aluminum nitride (AlN) is a biocompatible piezoelectric material suitable for energy harvesting in MEMS resonators. Through rapid thermal annealing, a threshold for CMOS‐compatible processes is established. AlN improved its crystallinity and enhanced the piezoelectric coefficient by ∼160%. Devices show an improvement in the electromechanical properties
Laura Mazón‐Maldonado   +7 more
wiley   +1 more source

The WHO costing and budgeting tool for national action plans on antimicrobial resistance-a review and assessment of impact in Africa. [PDF]

open access: yesJAC Antimicrob Resist
Mazengiya YD   +6 more
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

open access: yesAdvanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen   +4 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

open access: yesAdvanced Energy Materials, EarlyView.
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

Home - About - Disclaimer - Privacy