Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2026/r/gumushane/13721
  Enhanced cationic dye adsorption using Stenotrophomonas indicatrix -modified MnFe2O4: performance evaluation and adsorption mechanism

  Ozdes, Duygu; Dede, Alper; Turfan, Fatma Asya; Seker, Serdal

  In this study, MnFe2O4 magnetic nanoparticles were modified with the Stenotrophomonas indicatrix bacteria for the first time in the literature to develop an effective and novel bio-adsorbent for the remediation of toxic cationic dyes, specifically Rhodamine 6G (R6G) and Methylene Blue (MB), from contaminated aqueous media. MnFe2O4 and bacteria-loaded MnFe2O4 were thoroughly characterized using FTIR, XRD, and SEM-EDX analyses. XRD results confirmed that the cubic spinel structure of MnFe2O4 was preserved after bacterial modification, while FTIR spectra evidenced the successful incorporation of biological functional groups, including –NH, –OH, amide, and phosphate moieties, onto the nanoparticle surface. Adsorption performance of the dyes was evaluated in terms of parameters including aqueous solution pH, equilibrium time, bacteria-loaded MnFe2O4 dosage, and initial R6G and MB concentration. After investigating the effect of salt on adsorption efficiency, the applicability of the proposed adsorbent was assessed using real water samples. According to the experimental results, the optimum pH and equilibrium period for the uptake of both dyes were determined to be 8.0 and 60 min, respectively. Kinetic analyses showed that the pseudo-second order kinetic model exhibited a superior fit in representing the adsorption rates of both dyes, while isotherm studies indicated that both Langmuir and Freundlich isotherm models fit the experimental data well. While the adsorption capacities of pure MnFe2O4 for MB and R6G were 19.5 mg g− 1 and 15.3 mg g− 1, respectively, these values reached 67.6 mg g− 1 and 59.5 mg g− 1 for the bacteria-loaded MnFe2O4. The obtained data revealed that bacterial modification significantly increased the adsorption capacity of MnFe2O4, suggesting that the developed bio-adsorbent stands out as an effective and promising candidate for the remediation of dye-contaminated effluents.

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• MakaleYayıncıda açık erişim2026/r/gumushane/13551
  Boric acid-activated carbon derived from Scots pine sawdust for phenol removal: adsorption mechanism, linear and nonlinear kinetic and isotherm modeling, and artificial neural network prediction

  Ozdes, Duygu; Turfan, Fatma Asya; Seker, Serdal; Kavgaci, Gonca; Onal, Yunus

  In this study, a sustainable activated carbon was successfully prepared from Scots pine sawdust via boric acid activation (H3BO3-AC-SPS) and evaluated for phenol adsorption from aqueous solutions. The physicochemical characteristics of the adsorbent were investigated using FTIR, SEM-EDX, XRD, and BET analyses, while the effects of solution pH, contact time, adsorbent dosage, initial phenol concentration, temperature, ionic strength, and reusability without regeneration on the adsorption performance were systematically examined. H3BO3-AC-SPS exhibited excellent adsorption performance over a wide pH range (5–8), showed good tolerance to coexisting inorganic ions and organic contaminants, and retained appreciable adsorption efficiency over five consecutive adsorption cycles without regeneration. Phenol uptake increased with temperature, and NaOH enabled partial desorption of phenol. The adsorption kinetics and equilibrium data were analyzed using both linear and nonlinear regression approaches and comparatively evaluated based on the coefficient of determination (R2), sum of squared errors (SSE), and root mean square error (RMSE). The pseudo-second order kinetic model and the Langmuir isotherm exhibited the best predictive performance, with the Langmuir model estimating a maximum adsorption capacity of 65.4 mg g−1. The adsorption mechanism may involve π–π interactions, hydrogen bonding, pore filling, and hydrophobic interactions. In addition, an artificial neural network (ANN) model accurately predicted the adsorption behavior, yielding a high correlation coefficient (R = 0.9789). The applicability of H3BO3-AC-SPS was further demonstrated in stream water and mining wastewater. These findings demonstrate that boric acid activation is an effective strategy for converting Scots pine sawdust into a high-performance adsorbent and that integrating linear and nonlinear adsorption modeling with statistical error analysis provides a reliable framework for interpreting adsorption behavior. This journal is

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