Graphene Materials for Sustainable Energy Applications: A Contemporary Perspective
ABSTRACT Graphene has garnered significant attention as a promising material with great potential for contributing to sustainable energy initiatives, such as RE100 (100% renewable energy initiative) and CF100 (100% carbon‐free initiative). This review aims to explore the potential of graphene for advancing renewable energy applications by highlighting
Niraj Kumar +3 more
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Experimental Study on OC PEMFC Performance Improvement and MEA Parameter Optimization Under Water Shortage Conditions. [PDF]
Wang J +5 more
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This study employs a simple solid‐phase alkali‐oxygen oxidation (SAO) method to extract inherent components (humic acids) from coal. We successfully extracted yellow, brown, and black humic acids by adjusting the amount of alkali. Among them, brown humic acid extraction created abundant ultra‐micropores and closed pores, greatly enhancing sodium ...
Ruizhen Song +8 more
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Study on the influence of working environment on the insulation of fuel cell. [PDF]
Pu J +6 more
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Herein, we mainly summarize the characteristics of the main types of carbon dots (CDs), analyze the strategies for improving advanced batteries' performance via incorporating CDs, comprehensively summarize recent applications of CDs in the main components (electrode, electrolyte, and separator) of advanced batteries, and propose the technical ...
Chuang Jiang +5 more
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An efficient approach for mathematical modeling and parameter estimation of PEM fuel based on Young's double-slit experiment algorithm. [PDF]
Alqadi BS +7 more
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Sulfophenylated centimeter-sized graphene membrane in a direct methanol fuel cell. [PDF]
Zhang W +24 more
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AI-driven multi-objective optimization of FCHEV sizing and energy management considering degradation and vehicle dynamics under realistic machine learning-based traffic conditions. [PDF]
Montazeri-Gh M, Mostashiri A.
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Machine learning in next-generation AEM fuel cells: a systematic review. [PDF]
Ponnada S.
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Optimizing hybrid energy systems for locomotives based on improved grey lag goose algorithm. [PDF]
Gou X, Li J, Yazdani B.
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