Results 161 to 170 of about 71,313 (246)
Artificial intelligence-augmented smart grid architecture for cyber intrusion detection and mitigation in electric vehicle charging infrastructure. [PDF]
Sharma A, Rani S, Shabaz M.
europepmc +1 more source
All Organic Fully Integrated Neuromorphic Crossbar Array
In this work, the first fully integrated crossbar array of electrochemical random‐access memory (ECRAM) that is composed entirely of organic materials is represented. This array can perform inference and in situ parallel training and is capable of classifying linearly separable 2D and 3D classification tasks with high accuracy.
Setareh Kazemzadeh +2 more
wiley +1 more source
A Self-Powered Double U-Finger MME Resonator Capable of Wirelessly Capturing Abnormal Message in Smart Grid Networks. [PDF]
Zheng X +10 more
europepmc +1 more source
While perovskite solar cells have been widely studied, including their stability, perovskite indoor photovoltaics (IPVs) have only recently emerged. Nevertheless, more studies are appearing in the literature. The systematic stability study of IPVs is crucial, particularly given the inconsistencies in reported methodologies and results, which call for ...
Ivy Mawusi Asuo +7 more
wiley +1 more source
An online learning method for assessing smart grid stability under dynamic perturbations. [PDF]
Alaerjan A, Jabeur R.
europepmc +1 more source
Degradation Pathways of Silicon‐Based Anodes in Lithium‐Ion Batteries
Silicon‐based anodes undergo degradation through five primary pathways: (1) mechanical and structural deterioration of the active material, (2) loss of electrode integrity and electrical contact, (3) mechanical instability of the solid electrolyte interphase (SEI), characterized by repetitive fracture and deformation, (4) chemical instability of the ...
Yoon Jeong Choi +3 more
wiley +1 more source
Revolutionizing smart grid security: a holistic cyber defence strategy. [PDF]
Nemade B +4 more
europepmc +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Advancements, challenges, and future prospects of smart grid technology in India. [PDF]
Talhar Belge A +4 more
europepmc +1 more source
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source

