Article Dans Une Revue Journal of Engineering Research and Reports Année : 2025

AI-Driven Integration of Nanotechnology and Green Nanotechnology for Sustainable Energy and Environmental Remediation

Résumé

This research critically examines the synergistic integration of nanotechnology and green nanotechnology as a disruptive framework for addressing dual imperatives of sustainable environmental remediation and next-generation clean energy systems. By exploiting the physicochemical uniqueness of nanomaterials- such as quantum confinement, surface plasmon resonance, enhanced electron mobility, and high surface-to-volume ratios- this study elucidates the multifaceted mechanisms by which engineered nanomaterials (ENMs) facilitate the adsorption, catalysis, degradation, and real-time sensing of diverse pollutants across air, water, and soil matrices. Importantly, these processes are governed by the foundational principles of green chemistry and sustainable engineering, prioritizing biogenic synthesis, non-toxic precursors, low-energy fabrication, and end-of-life biodegradability to mitigate ecological and health risks. The study further explores how nanostructured components- including perovskite nanocrystals, quantum dots, plasmonic nanoparticles, and nanocomposites- redefine the performance boundaries of photovoltaic cells, fuel cells, thermoelectric generators, and electrochemical storage devices. The convergence of nanogenerators (TENGs, PENGs), nano-enabled supercapacitors, and AI-optimized hybrid energy modules is shown to enable continuous, resilient, and decentralized electricity generation, particularly in climate-vulnerable and off-grid regions. A novel AI-augmented architecture incorporating nano-sensors, edge computing, and digital twins is proposed to facilitate predictive diagnostics, adaptive control, and lifecycle optimization of these intelligent energy ecosystems. Moreover, a comprehensive cradle-to-grave life cycle sustainability assessment (LCSA) evaluates carbon intensity, energy return on investment (EROI), nanotoxicological profiles, recyclability, and circularity potential. This ensures that technological advancement aligns with planetary boundaries and long-term ecological integrity. The research underscores the ethical imperative of responsible innovation, advocating for regulatory convergence, precautionary design, and stakeholder-inclusive deployment strategies. By fusing material science, environmental engineering, artificial intelligence, and sustainability science, this study presents a cutting-edge, multidisciplinary roadmap for leveraging nanotechnology and green nanotechnology as accelerators of global ecological restoration and clean energy transition.

Fichier non déposé

Dates et versions

hal-05159243 , version 1 (12-07-2025)

Identifiants

  • HAL Id : hal-05159243 , version 1

Citer

F. A. Samiul Islam, M. A. Naimul Islam. AI-Driven Integration of Nanotechnology and Green Nanotechnology for Sustainable Energy and Environmental Remediation. Journal of Engineering Research and Reports, 2025, 27 (7), pp.260-311. ⟨hal-05159243⟩
24 Consultations
0 Téléchargements

Partager

  • More