Graphene, being a two-dimensional monolayer of carbon, exhibits an exceptionally increased surface-to-volume ratio due to its atomic thinness and high aspect ratio, making it a material of considerable interest in advanced technology applications. Recent developments have leveraged their unique surface characteristics, such as nanoscale ripples and grooves, to enhance energy storage, sensing, catalysis, and environmental remediation performance. Its extensive surface area enables rapid ion adsorption and desorption, significantly improving energy and power densities in supercapacitors and lithium-ion batteries while enhancing stability over prolonged cycles. In sensing, the high surface-to-volume ratio supports the immobilization of biomolecules and nanoparticles, improving sensitivity in detecting gases, biomarkers, and pollutants, thereby advancing diagnostic and environmental monitoring applications. Its expansive surface area and unique electronic properties contribute to high catalytic efficiencies, enabling sustainable chemical processes, such as hydrogen production, water treatment, and pollutant degradation. Unlike many review articles that primarily explore the functionalization of graphene, this study mainly emphasizes the evaluation of methodologies aimed at augmenting graphene’s surface area. This review systematically evaluates recent advancements in the optimization of graphene surface characteristics, with a primary focus on their role in enhancing energy storage systems while also addressing emerging applications in healthcare and environmental sustainability.

The structural components of an automotive chassis, including critical elements like the frame and cross-members, must possess high strength to distribute and support the vehicle's load during operation effectively. In chassis manufacturing, slot welding has proven to be an effective method for improving support and durability under cyclical loading conditions. However, the absence of standardized guidelines for slot-filling during chassis welding poses a significant challenge, particularly concerning the fatigue life of components in the automotive industry. In this study, three different slot geometries were employed and welded by adjusting robotic programming to achieve complete filling (CF) or partial filling (PF) of the slots to improve fatigue life. A hot rolled 590 MPa steel sheet used for automotive applications with a cold metal transfer (CMT) technique was adopted to weld the samples. Digital image correlation (DIC) was conducted to identify stress concentration and the crack propagation path during the tensile loading of the sample. The fatigue crack initiation showed a location similar to the highest stress concentration area, as revealed by DIC. Additionally, an infrared camera was utilized during welding to monitor temperature variations, providing insights into the thermal aspects of each welding condition. The study revealed that higher effective weld width (W_eff) in the PF sample enhanced the tensile fatigue life by reducing stress concentration. However, the cross-tensile fatigue properties of the CF sample exhibited a longer fatigue life due to a larger weld size and associated weld width.