Interaction effect of process parameters and <scp>Pd‐electrocatalyst</scp> in formic acid <scp>electro‐oxidation</scp> for fuel cell applications: Implementing supervised machine learning algorithms-Reference-Cited by-同舟云学术

Interaction effect of process parameters and Pd‐electrocatalyst in formic acid electro‐oxidation for fuel cell applications: Implementing supervised machine learning algorithms

Published:2022-01-02 Issue:15 Volume:46 Page:21583-21597
ISSN:0363-907X
Container-title:International Journal of Energy Research
language:en
Short-container-title:Intl J of Energy Research

Author:

Hossain SK Safdar¹,Ali Syed Sadiq¹,Rushd Sayeed¹,Ayodele Bamidele Victor²^ORCID,Cheng Chin Kui³

Affiliation:

1. Department of Chemical Engineering College of Engineering, King Faisal University Al‐Ahsa Saudi Arabia

2. Institute of Energy Policy and Research, Universiti Tenaga Nasional Kajang Malaysia

3. Department of Chemical Engineering Centre for Catalysis and Separation (CeCaS), College of Engineering, Khalifa University of Science and Technology Abu Dhabi UAE

Publisher

Hindawi Limited

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/er.7602

Reference50 articles.

1. Electrochemical hydrogen storage: Opportunities for fuel storage, batteries, fuel cells, and supercapacitors

2. Critical challenges in the system development of direct alcohol fuel cells as portable power supplies: An overview

3. Overview of porous media/metal foam application in fuel cells and solar power systems

4. Recent advances in formic acid electro-oxidation: from the fundamental mechanism to electrocatalysts

5. Recent progress in electrocatalysts and electrodes for portable fuel cells

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-driven strategy for evaluating the response of eco-friendly concrete at elevated temperatures for fire resistance construction;Results in Engineering;2023-12

2. Biochar production from valorization of agricultural Wastes: Data-Driven modelling using Machine learning algorithms;Fuel;2023-11

3. Friction and Wear Behavior of Al-Graphene Nanocomposite Synthesized by Powder Metallurgy and Hot Extrusion;Journal of Materials Engineering and Performance;2023-09-25

4. Study of Friction and Wear Behavior of Graphene-Reinforced AA7075 Nanocomposites by Machine Learning;Journal of Nanomaterials;2023-02-15

5. Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations;Applied Sciences;2022-12-15