Machine learning assisted chemical characterization to investigate the temperature-dependent...

Reduced graphene oxide-wrapped ZnS–SnS 2 heterojunction bimetallic hollow cubic boxes as high-magnification and long lifespan supercapacitor anode materials

X Li, G Feng, L Zhou, T Zhao, F Jiang, H Li, Y Liu, Q Yu… - Nanoscale, 2024 - pubs.rsc.org
Metal sulfides have attracted extensive attention due to their excellent electrochemical
performance. However, issues such as poor conductivity and severe volume expansion …
Mentés Hivatkozás Idézetek száma: 2 Kapcsolódó cikkek Mind a(z) 3 változat

Machine learning framework for selective and sensitive metal ion sensing with nitrogen-doped graphene quantum dots heterostructure

R Das, A Paria, PK Giri - Carbon, 2025 - Elsevier
This study introduces a machine learning (ML) framework to optimize photodetector
performance for sensor applications. Using the data from the fabricated photodetector with …
Mentés Hivatkozás Idézetek száma: 2 Kapcsolódó cikkek Mind a(z) 2 változat
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[HTML][HTML] Machine learning-assisted prediction, screen, and interpretation of porous carbon materials for high-performance supercapacitors

H Liu, Z Cui, Z Qiao, X An, Y Wang - Journal of Materials …, 2024 - oaepublish.com
Porous carbon materials (PCMs) are preferred as electrode materials for supercapacitor
energy storage applications due to their superior characteristics. However, the optimal …
Mentés Hivatkozás Idézetek száma: 1 Kapcsolódó cikkek Tárolt változat