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<p>The escalating discharge of heavy metals, synthetic dyes, pharmaceuticals, and per- and polyfluoroalkyl substances (PFAS) into aquatic systems poses a critical challenge to conventional wastewater treatment technologies, particularly under complex multi-contaminant conditions. Graphene quantum dots (GQDs), characterized by quantum confinement effects, abundant edge sites, and tunable surface chemistry, have emerged as next-generation carbon nanomaterials for advanced water remediation. Notably, while the chemical synthesis of GQDs usually involves a hazardous precursor and sustainability issues, most of the reviews are focused on either a single pollutant or generic properties of the materials. In this review, a rigorous and integrative analysis of green and defect-engineered GQDs defined strictly as sub-10&#xa0;nm graphene fragments distinct from bulk GO or rGO derivatives for multi-pollutant wastewater treatment is presented. A critical evaluation of green synthetic routes emphasizing the role of precursor chemistry on size distributions, defect states, heteroatom doping and surface chemistries is explained, along with the correlation of the role of defect states (vacancies, edge distortions) and heteroatom dopants (N, S, P) on band structure, charge carrier kinetics, reactive oxygen species generation, and adsorption specificity to the removal mechanisms of metals, dyes, pharmaceuticals, and PFAS in simulated and real wastewater environments. Engineering deployment through immobilization in membranes, hydrogels, magnetic composites and flow-through systems is evaluated alongside regeneration, stability, and leaching control. Environmental safety, life-cycle implications and regulatory considerations are integrated to deliver a sustainability-centered perspective. This review establishes a mechanistic and translational framework for designing scalable, green, defect-optimized GQD platforms for next-generation wastewater remediation.</p> Graphical abstract <p></p>

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Green and defect-engineered graphene quantum dots for multi-pollutant water remediation

  • 期刊论文

  • 发表日期：

    2026年7月20日

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  • Harshita Jain,
  • Sithara Soman,
  • Sakshi Thakur,
  • Victor Ezebuiro,
  • Kamaldeen Olayinka Suleiman,
  • Onche Emmanuel,
  • Lovepreet Singh

摘要

The escalating discharge of heavy metals, synthetic dyes, pharmaceuticals, and per- and polyfluoroalkyl substances (PFAS) into aquatic systems poses a critical challenge to conventional wastewater treatment technologies, particularly under complex multi-contaminant conditions. Graphene quantum dots (GQDs), characterized by quantum confinement effects, abundant edge sites, and tunable surface chemistry, have emerged as next-generation carbon nanomaterials for advanced water remediation. Notably, while the chemical synthesis of GQDs usually involves a hazardous precursor and sustainability issues, most of the reviews are focused on either a single pollutant or generic properties of the materials. In this review, a rigorous and integrative analysis of green and defect-engineered GQDs defined strictly as sub-10 nm graphene fragments distinct from bulk GO or rGO derivatives for multi-pollutant wastewater treatment is presented. A critical evaluation of green synthetic routes emphasizing the role of precursor chemistry on size distributions, defect states, heteroatom doping and surface chemistries is explained, along with the correlation of the role of defect states (vacancies, edge distortions) and heteroatom dopants (N, S, P) on band structure, charge carrier kinetics, reactive oxygen species generation, and adsorption specificity to the removal mechanisms of metals, dyes, pharmaceuticals, and PFAS in simulated and real wastewater environments. Engineering deployment through immobilization in membranes, hydrogels, magnetic composites and flow-through systems is evaluated alongside regeneration, stability, and leaching control. Environmental safety, life-cycle implications and regulatory considerations are integrated to deliver a sustainability-centered perspective. This review establishes a mechanistic and translational framework for designing scalable, green, defect-optimized GQD platforms for next-generation wastewater remediation.

Graphical abstract