Electrochemical sensing of benzodiazepines: Tracing the evolution of carbonaceous nano-hybrid materials from 3D to 0D, their integration into smart technologies for real-time monitoring

• Indispensable resource for researchers aiming to drive innovation in this field. • Progression from 3D to 0D carbon-based materials in sensing of Benzodiazepines. • Benefits of electrochemical techniques: sensitivity, reproducibility, cost-effectiveness. • Future research: rapid diagnostic devices, smart electronics. • AI and machine learning to enhance drug detection accuracy and efficiency. The misuse of benzodiazepines, often implicated in drug-facilitated crimes, presents a significant global concern, profoundly affecting public health and safety. In response to the growing need for rapid, sensitive, and on-site detection methods, this review aims to critically evaluate the current landscape of electrochemical sensing of benzodiazepines. The main objective is to consolidate fragmented research findings on a singular platform and trace the progression of carbonaceous nanohybrid materials from early 3D frameworks to modern 0D structures into a cohesive overview that highlights emerging trends and innovations. We also aim to evaluate how this transformation has enhanced sensor performance. Unlike previous reviews that predominantly focus on conventional gold-standard techniques such as chromatographic and spectroscopic methods, this work focuses exclusively on electrochemical sensing as a promising, portable, and real-time alternative. This evolutionary approach has led to considerable improvements in sensitivity, selectivity, and portability, making these systems increasingly suitable for field-deployable applications. By highlighting key advances especially in graphene oxide (GO), carbon nanotubes (CNTs), fullerenes, quantum dots (QDs) and their metal-oxide-supported nanocomposites, this review underscores how nanostructure dimensionality directly influences electrochemical response. Furthermore, it explores the integration of these advanced materials into smart sensing platforms including those with AI-enabled features, positioning them as next-generation solutions. This work not only maps current advancements but also identifies future research directions bridging the gap between laboratory research and deployable forensic tools.