Advanced Graphene–Mxene Supported MOF-Derived Hybrid Nanomaterials for High-Performance Energy Storage, Supercapacitors, and Hydrogen Evolution Technology

作者
Kalsoom Hayat,Ambar Riaz,Aimen Amjad,Zubair Aziz,Muhammad Naeem Khalid,Muhammad Suleman Ahmad,Iqra Rizwan,Junaid Abbas,Mujahid Abbas,Khizra Waheed
出处
期刊:Scholars academic journal of biosciences [Scholars Academic and Scientific Publishers]
卷期号:14 (05): 371-393
标识
DOI:10.36347/sajb.2026.v14i05.001
摘要

Energy demand is rising across modern systems. Efficient storage and conversion are now critical challenges. This study introduces a novel design based on advanced Graphene–MXene Supported MOF-Derived Hybrid Nanomaterials. The approach integrates conductive graphene layers with MXene sheets and MOF-derived porous structures. Each component plays a precise role. Graphene improves electrical conductivity. MXene enhances surface reactivity. MOF templates create a stable porous network. The combined structure forms a continuous pathway for charge transfer. This design reduces resistance and improves ion diffusion. As a result, electrochemical performance is significantly enhanced. The material shows high capacitance and long cycle stability in supercapacitors. It also demonstrates strong catalytic activity in hydrogen evolution reactions. Structural uniformity ensures consistent performance. Surface functionalization further optimizes active sites. The synthesis process is controlled and scalable. This maintains material integrity and reproducibility. The study connects material design with practical application. Each stage supports the overall performance goal. The integration strategy avoids structural mismatch. It also minimizes energy loss during operation. Results indicate improved energy density and faster charge–discharge rates. Hydrogen production efficiency is also increased. The system remains stable under repeated use. This work provides a unified platform for energy storage and conversion. It highlights the importance of hybrid architecture. The findings open new directions for multifunctional nanomaterials. Future optimization can further enhance performance and scalability.

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