[HTML][HTML] Machine learning toward advanced energy storage devices and systems

T Gao, W Lu - Iscience, 2021 - cell.com
Technology advancement demands energy storage devices (ESD) and systems (ESS) with
better performance, longer life, higher reliability, and smarter management strategy …

Machine learning techniques for prediction of capacitance and remaining useful life of supercapacitors: A comprehensive review

V Sawant, R Deshmukh, C Awati - Journal of Energy Chemistry, 2023 - Elsevier
Supercapacitors are appealing energy storage devices for their promising features like high
power density, outstanding cycling stability, and a quick charge–discharge cycle. The …

Optimization techniques for electrochemical devices for hydrogen production and energy storage applications

M Tawalbeh, A Farooq, R Martis… - International Journal of …, 2024 - Elsevier
With the rapidly evolving geo-political landscape and unceasing advancements in
technology, sustainable energy security is a very important topic. Research indicates that …

A multi-data-driven procedure towards a comprehensive understanding of the activated carbon electrodes performance (using for supercapacitor) employing ANN …

M Rahimi, MH Abbaspour-Fard, A Rohani - Renewable Energy, 2021 - Elsevier
Biomass resources are intensively used as economical and green-reserve precursor
preparation of sustainable carbon materials used in supercapacitors. The synthetic …

An emerging machine learning strategy for electrochemical sensor and supercapacitor using carbonized metal–organic framework

X Lu, P Liu, K Bisetty, Y Cai, X Duan, Y Wen… - Journal of …, 2022 - Elsevier
Abstract Machine learning (ML) plays an important role in the electrochemical application of
electrode materials. In this work, an emerging machine learning strategy for both …

Insights from machine learning techniques for predicting the efficiency of fullerene derivatives‐based ternary organic solar cells at ternary blend design

MH Lee - Advanced Energy Materials, 2019 - Wiley Online Library
Ternary organic solar cells (OSCs) have progressed significantly in recent years due to the
sufficient photon harvesting of the blend photoactive layer including three absorption …

Machine learning-assisted materials development and device management in batteries and supercapacitors: performance comparison and challenges

S Jha, M Yen, YS Salinas, E Palmer… - Journal of Materials …, 2023 - pubs.rsc.org
Machine learning (ML) has been the focus in recent studies aiming to improve battery and
supercapacitor technology. Its application in materials research has demonstrated promising …

[HTML][HTML] Artificial intelligence-navigated development of high-performance electrochemical energy storage systems through feature engineering of multiple descriptor …

H Adamu, SI Abba, PB Anyin, Y Sani, M Qamar - Energy Advances, 2023 - pubs.rsc.org
With the increased and rapid development of artificial intelligence-based algorithms coupled
with the non-stop creation of material databases, artificial intelligence (AI) has played a great …

Supercapacitor properties of partially oxidised-MXene quantum dots/graphene hybrids: Fabrication of flexible/wearable micro-supercapacitor devices

L Pradhan, B Mohanty, G Padhy, RK Trivedi… - Chemical Engineering …, 2024 - Elsevier
Recently, combining the synergistic properties of two-dimensional (2D) and zero-
dimensional (0D) materials has attracted significant attention for energy applications. Here …

Machine learning approach to understanding the 'synergistic'pseudocapacitive effects of heteroatom doped graphene

A Chenwittayakhachon, K Jitapunkul, B Nakpalad… - 2D …, 2023 - iopscience.iop.org
In recent years, graphene has been widely utilised as a supercapacitor electrode, and
doping heteroatom on graphene is reported to enhance the pseudocapacitance of the …