Machine learning driven synthesis of nickel phosphate for advanced hybrid supercapacitors

Chetankumar D. Chavare

doi:10.1016/j.est.2026.124029

Machine learning driven synthesis of nickel phosphate for advanced hybrid supercapacitors

2026-08-08

0

OA

AI

C

Chetankumar D. Chavare

P

Prafullata C. Chavare

S

Sampada V. Chavan

C

Chinmayee Padwal

X

Xijue Wang

H

Harishchandra R. Kulkarni *

D

Deepak P. Dubal *

G

Gaurav M. Lohar *

DOI：10.1016/j.est.2026.124029

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Abstract

En 中文

• Machine learning identified key factors governing NP performance. • Synthesis, device, and testing parameters were systematically analyzed. • NP was synthesized hydrothermally under varied conditions. • NP-4 exhibited a capacity of 59.1 mAh g−1 at 3 A g−1 in 1 M KOH. • NP-4//AC achieved 16.6 Wh kg−1 and 88.7% retention after 10,000 cycles.

Keywords:

Machine learning

Predicted capacitance

Nickel phosphate

Hydrothermal method

Hybrid supercapacitor

Machine learning driven synthesis of nickel phosphate for advanced hybrid supercapacitors

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