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The study aims to blend carbon quantum dots (CQDs) with chitosan and polyvinyl alcohol to produce micro fibrous membranes. To create electrospun carbon quantum dots nanofibers (ECQNF) that can absorb rhodamine B dye (RB) found in wastewater. A variety of methodologies were utilized to investigate the ECQNF, including scanning electron microscopy (SEM) for surface morphology, Fourier transform infrared spectroscopy (FTIR) to identify functional groups, X-ray photoelectron spectroscopy (XPS) for elemental analysis, X-ray diffraction (XRD), and N2 adsorption/desorption isotherms for structural analysis. Batch adsorption experiments varied parameters like contact time, initial RB concentrations, and adsorbent dosages. The membrane achieved a maximum adsorption of 522 mg/g at 600 ppm and 298 K. Thermodynamic evaluation indicated the process is endothermic. Several isothermal models analyzed the adsorption of RB onto the electrospun adsorbent, with the Langmuir model best fitting the data. The pseudo-second-order model effectively described the kinetics. The Dubinin-Radushkevich model indicated an adsorption energy of 32.6 kJ/mol, suggesting chemisorption. Positive entropy and enthalpy values, along with a more negative Gibbs free energy, confirm the process is endothermic and spontaneous. The increase in adsorption capability with rising temperature is evident. The ECQNF can be reused up to six times, maintaining efficiency and chemical structure. The XRD analyses demonstrate consistent results before and after each reuse cycle. It's crucial to investigate the interaction mechanisms between the adsorbent and adsorbate, including hydrogen bonding, n-π stacking, electrostatic interactions, and pore filling. Using the Box-Behnken design, the adsorption outcomes were optimized, highlighting the effectiveness of ECQNF in enhancing pollutant removal from wastewater., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 Elsevier B.V. All rights reserved.)