Nonlinear regression for treating adsorption isotherm data to characterize new sorbents: Advantages over linearization demonstrated with simulated and experimental data

Continuous-flow phosphate removal using Cry-Ca-COS Monolith: Insights from dynamic adsorption modeling

This study rigorously evaluates the adsorption performance of the Cry-Ca-COS monolith for phosphate removal in a column operation mode. Characterization of the material both before and after exhaustion in a continuous flow system (column form) showed no difference compared to results from a batch system (tablet form). The XPS results indicated that the adsorption mechanism of phosphate on the Cry-Ca-COS column involved surface microprecipitation and ligand exchange (inner-sphere complexation). A systematic examination of key parameters revealed that higher column height, lower flow rate, and higher initial phosphate concentration favor increased phosphate adsorption in continuous mode. The application of the developed system to a real wastewater sample resulted in a satisfactory removal efficiency of 99.16 %, along with a concurrent reduction in total suspended solids (TSS) by 63.07 %. The adsorption data were analyzed using five dynamic adsorption models-Adam-Bohart, Wolborska, Thomas, Yoon-Nelson, and Yan-employing both linear and non-linear approaches. The non-linear models demonstrated a better fit with the experimental data, as indicated by higher correlation coefficients (R² = 0.9994 in the Yoon-Nelson model). An analysis of comprehensive errors was also conducted to assess the adequacy and precision of the model equations.

Frontal affinity chromatography to investigate the interaction of benzophenone with humic acid supported on microbore monolithic columns

The principles of frontal affinity chromatography were used to determine the sorption constants and sorption capacities of benzophenone on immobilized humic acid. Poly(glycidyl-co-ethylene dimethacrylate) monoliths were constructed inside microbore capillaries (12 cm long × 1.016 mm internal diameter) and further aminated with ethylenediamine. The free amine groups coordinated Cu(II), which served as an intermediate ligand to immobilize about 27.2-28.7 mg of humic acid per gram of polymer skeleton (or 93 ± 4 μg per cm of column). The reversible nature of the interactions with Cu(II) allowed to leach and reload humic acid, thus suggesting that a single Cu(II) modified column may be further explored to immobilize humic acids from different sources using the concept of exchangeable chemistries on a stable monolithic platform. Frontal affinity chromatograms were obtained by injecting 1000 μL of benzophenone solutions of various concentrations (1.11-112 μmol L-1) at 25 °C and pH 7.00 ± 0.1. The concentration-dependent elution volume enabled the construction of sorption isotherms that were fitted to Langmuir and Freundlich equations and the linearized Scatchard plot. The binding of benzophenone to the humic substance was ruled by two classes of interaction sites withK L = (1.2 ± 0.2) × 106 and (6.7 ± 0.8) × 103 L mol-1 and a maximum sorption capacity of 19.2 ± 1.2 μmol g-1. The results correspond to an average of duplicate injections in three columns, thus demonstrating the acceptable reproducibility and stability of the proposed methodology.

Groundnut-shell derived oxygen enriched mesoporous carbon adsorbent for removal of thiophenic sulfur compounds

In this work, groundnut shell-derived mesoporous carbons, synthesized by one-step carbonization at different temperatures in presence of potassium hydroxide, were used for desulfurization studies involving dibenzothiophene, benzothiophene and thiophene. The pore formation and corresponding surface area of synthesized mesoporous carbon was governed by carbonization temperature as it increased from 600 to 900 °C. The carbon synthesized at carbonization temperature of 800 °C, that is GN-800, showed highest surface area (1192 m2/g) and pore volume (0.58 cm3/g) amongst the all synthesized mesoporous carbons. For all the thiophenic sulfur compounds, the prepared mesoporous carbons exhibited improved adsorptive desulfurization performance as the adsorption temperature increased from 25 to 70 °C. The oxygen enriched adsorbents showed higher oxygen content and improved removal for all the thiophenic sulfur compounds. The oxygen enriched adsorbent, obtained by treatment with nitric acid (V) and carbonized at 800 °C, showed highest adsorptive desulfurization performance for all sulfur compounds. At 70 °C the removal for thiophene, benzothiophene and dibenzothiophene was 97.7, 93.8 and 90.2%, while the corresponding adsorption capacities were 58.7, 56.3 and 54.6 mg/g, respectively. For mesoporous carbonized carbons, the π-π interaction also contributed to adsorptive forces in addition to Van der Waals forces. For the oxygen enriched samples, additional acid-base interactions also contributed to adsorptive forces. The experimental data was best fitted to pseudo-second order kinetics model and Langmuir isotherm model. The adsorbent showed a slight drop in the removal percentage after five adsorption-regeneration cycles. The oxygen enriched groundnut shell derived mesoporous carbon was observed to have the potential to function as an excellent desulfurization adsorbent for producing clean fuel.

Adsorption isotherms, kinetics, and thermodynamics of Au(III) on chitosan/palm kernel fatty acid distillate/magnetite nanocomposites

This study examined the adsorption isotherms, kinetics, and thermodynamics of Au(III) onto chitosan/palm kernel fatty acid distillate/magnetite nanocomposites (CPMNs) to enhance the understanding of adsorption behavior and mechanisms. Adsorption experiments were conducted across various initial Au(III) concentrations, contact times, and temperatures. The experimental data were analyzed using nonlinear isotherm and kinetic models, and thermodynamic parameters were evaluated. The results revealed that the Langmuir model best fits the adsorption equilibrium data, showing a maximum monolayer adsorption capacity of 1.102-1.163 mmol/g (217-229 mg/g). The pseudo-first-order model best describes the kinetic data, suggesting first-order kinetics and a physisorption-dominated process. Thermodynamic analysis indicated that the adsorption is spontaneous, endothermic, entropy-driven, and highly favorable, primarily governed by physisorption. This study provides significant insights into the adsorption mechanisms of CPMNs for Au(III), contributing to advancing cost-effective and eco-friendly adsorbents for industrial use, such as wastewater treatment and metal recovery in mining, metallurgy, and electronic waste recycling industries.

Modelling of a new form of nitrogen doped activated carbon for adsorption of various dyes and hexavalent chromium ions

This study reports a new form of nitrogen-doped activated carbon (AC5-600) produced from a blend of sawdust (SD) and fish waste (FW) treated with urea and ZnCl2 for the adsorption of toxic metals and dyes. The adsorbent was also explored in the treatment of acid brown 14 (AB14) and acid orange 7 (AO7) dye molecules and hexavalent chromium (Cr6+) ions. The pH controls the sorption of individual contaminants, with an observed superlative % of individual contaminants removed at pH 1.5. Removal at pH was credited to the electrostatic interaction (EI) between the anion dyes and Cr6+ species at this pH and the protonated sites accessible on the AC5-600 adsorbent surface. Based on the error values obtained from the non-linear modelling (NLM) of the kinetic and isotherm models, the Elovich (ELM-AB14 and Cr6+), pseudo-first- (PFOM-AB14) and second-order models (PSOM-AB14, AO7 and Cr6+) and the Freundlich (FRHM) model were found to ideally define the sorption of the various contaminants. The determined maximum sorption capacity (Qm) based on the NLM was 1114, 1929 and 318 mg.g-1 for AB14 dye, AO7 dye and Cr6+ ions, respectively. Based on the computational adsorption calculations, the sorption energies for the AO7 and AB14 dyes were -4.492 and -8.090 eV and 2.563, 1.789, 1.226 and 1.928 eV for Cr2, CrO3, CrO4, and CrO4H species. AB14 and AO7 dyes and Cr6+ ions adsorption to synthesised AC5-600 was predicted employing the response surface methodology (RSM) and artificial neural network (ANN) models. The ANN model was more effective in predicting AB14 and AO7 dyes and Cr6+ ions adsorption than the RSM, and it was highly applicable in the sorption process.

Smart Crowding on pH-Induced Elasticity of Weakly Anionic poly(N-Isopropylacrylamide)-Based Semi-Interpenetrating Polymer Networks via Integration of Methacrylic Acid and Linear Polyacrylamide Chains

Weakly anionic semi-interpenetrating polymer networks (semi-IPNs), comprised of copolymer poly(N-isopropylacrylamide-co-methacrylic acid) P(NIPA-MA) and linear poly(acrylamide) (LPA) chains as macromolecular crowding agent, are designed to evaluate pH-induced swelling and elasticity. Uniaxial compression testing after swelling in various pH-conditions is used to analyze the compressive elasticity as a function of swelling pH and LPA-content. The swelling of P(NIPA-MA)/LPA semi-IPNs is strongly pH-dependent due to MA units incorporated into the copolymer network which already exhibits temperature-sensitivity by presence of PNIPA counterpart. Since the behavior of semi-IPNs is a combination of PMA, LPA, and PNIPA moieties, the sensitivity of swelling to external pH can be modified with increasing swelling temperature. At high pH conditions, LPA-doped semi-IPNs show elasticity representing soft and loosely cross-linked structure. Elastic modulus is higher in acidic pH condition due to the less swelling tendency, while in basic pH, the modulus decreases significantly in coordination with swelling. Oscillatory swelling reveals how fast semi-IPNs can respond to environmental pH change (2.1-10.7). By describing adsorption potential of semi-IPNs for cationic methylene blue uptake by pseudo-first-order and Freundlich model, the designed poly(NIPA-MA)/LPA semi-IPNs emerge as promising smart materials in applications requiring rapid response to changes in temperature and pH via diffusional properties.

Metal-organic-framework and walnut shell biochar composites for lead and hexavalent chromium removal from aqueous environments

Extensive research in recent years has explored the realm of porous carbon composites for various applications, including electrochemistry, structural materials, environmental remediation, and more. In particular, the fabrication of porous carbon composites using a metal-organic framework (MOF) and biochar (BC) for aqueous remediation is a fairly new avenue of research. In this study, a MOF-BC composite was synthesized with unmodified and chemically modified BCs using solvothermal synthesis. The composites were used as adsorbents to remediate heavy metals, such as lead (II) and chromium (VI), from aqueous environments. It was verified that the MOF was homogeneously deposited onto the BC's surface using various material characterization techniques. Lead and chromium adsorption studies revealed a high adsorption capacity with greater than 99% removal for lead and ∼65% for chromium, respectively. Impressively, for lead, the highest observed experimental adsorption capacity of the MOF-chemically modified BC composite was 535 mg/g, compared to 240 mg/g for pristine BC. Meanwhile, the adsorption capacity of the same MOF-BC composite for chromium ions was low at 18 mg/g, compared to 80 mg/g for the chemically modified BC. The MOF-BC had a rapid adsorption rate, achieving equilibrium at only 150 min of reaction time for lead ions. MOF-BCs have higher adsorption for cationic lead through physisorption and ion-exchange mechanisms, whereas, for anionic chromium, removal is dominated only by physisorption mechanisms. The outcomes and methodological developments attained in this study offer a novel and compelling approach for synthesizing MOF-BC composites for aqueous remediation applications.

Evaluating the Suitability of Linear and Nonlinear Regression Approaches for the Langmuir Adsorption Model as Applied toward Biomass-Based Adsorbents: Testing Residuals and Assessing Model Validity

Regression analysis is a powerful tool in adsorption studies. Researchers often favor linear regression for its simplicity when fitting isotherm models, such as the Langmuir equation. Validating regression assumptions is crucial to ensure that the model accurately represents the data and allows appropriate inferences. This study provides a detailed examination of assumption checking in the context of adsorption studies while simultaneously evaluating the robustness of linear regression methods for fitting the Langmuir equation to isotherm data from 2,4-dichlorophenol (DCP) adsorption onto various biomass-based adsorbents and activated carbon. Different linearized Langmuir equations (Hanes-Woolf, Lineweaver-Burk, Eadie-Hofstee, and Scatchard) were compared to nonlinear regression, and each method was validated by rigorous residual checking. This included visual plots of residuals as well as statistical tests, including the Durbin-Watson test for autocorrelation (independence), the Shapiro-Wilk test for normality, and the White test for homoscedasticity. Key findings indicate that the Hanes-Woolf (type 1) and Lineweaver-Burk (type 2) linearizations were the best for most biomass adsorbents studied and that Eadie-Hofstee (type 3) and Scatchard (type 4) were generally invalid due to the negative parameters or assumption violations. For activated carbon, all linearization methods were unsuitable due to independence violations. In the case of nonlinear regression, there were no major assumption violations for all of the adsorbents. Symbolic regression identified the Langmuir equation only for activated carbon (AC). This study revealed shortcomings in relying solely on linearized Langmuir models. A proposed workflow recommends using nonlinear or weighted nonlinear regression, starting with Hanes-Woolf or Lineweaver-Burk linearization results as initial values for parameter estimation. If assumptions remain violated with nonlinear techniques, novel methods such as symbolic regression should be employed. This advanced regression technique can improve adsorption models' accuracy and predictive behavior without the stringent need for assumption checking. Symbolic regression can also aid in understanding mechanisms of novel adsorbents.

Metal sequestration by Microcystis extracellular polymers: a promising path to greener water treatment

The problem of heavy metal pollution in water bodies poses a significant threat to both the environment and human health, as these toxic substances can persist in aquatic ecosystems and accumulate in the food chain. This study investigates the promising potential of using Microcystis aeruginosa extracellular polymeric substances (EPS) as an environmentally friendly, highly efficient solution for capturing copper (Cu2+) and nickel (Ni2+) ions in water treatment, emphasizing their exceptional ability to promote green technology in heavy metal sequestration. We quantified saccharides, proteins, and amino acids in M. aeruginosa biomass and isolated EPS, highlighting their metal-chelating capabilities. Saccharide content was 36.5 mg g-1 in biomass and 21.4 mg g-1 in EPS, emphasizing their metal-binding ability. Proteins and amino acids were also prevalent, particularly in EPS. Scanning electron microscopy (SEM) revealed intricate 3D EPS structures, with pronounced porosity and branching configurations enhancing metal sorption. Elemental composition via energy dispersive X-ray analysis (EDAX) identified essential elements in both biomass and EPS. Fourier transform infrared (FTIR) spectroscopy unveiled molecular changes after metal treatment, indicating various binding mechanisms, including oxygen atom coordination, π-electron interactions, and electrostatic forces. Kinetic studies showed EPS expedited and enhanced Cu2+ and Ni2+ sorption compared to biomass. Thermodynamic analysis confirmed exothermic, spontaneous sorption. Equilibrium biosorption studies displayed strong binding and competitive interactions in binary metal systems. Importantly, EPS exhibited impressive maximum sorption capacities of 44.81 mg g-1 for Ni2+ and 37.06 mg g-1 for Cu2+. These findings underscore the potential of Microcystis EPS as a highly efficient sorbent for heavy metal removal in water treatment, with significant implications for environmental remediation and sustainable water purification.

Preparation and study of straw porous biochar with aromatic ring structure for adsorption performance and mechanism toward TNT red water

2,4,6-Trinitrotoluene (TNT) production processes generate a substantial amount of toxic wastewater. Therefore, it is crucial to identify efficient and sustainable methods for treating this wastewater. This paper explores the application of sustainable biomass-derived carbon produced from rice straw for the adsorption of 2,4,6-trinitrotoluene (TNT) red water. The rice straw-derived biochar (SBC) materials were synthesized by two-step reactions through hydrothermal carbonization and chemical activation with KOH. Characterization of the fabricated biochar was conducted using various techniques. Here, the chemical oxygen demand (COD) was used as an evaluation index for adsorption efficiency. The adsorption kinetics showed a good fit with the pseudo-second-order model, and the adsorption equilibrium was achieved in 30 min. The biochar's high surface area (1319 m2/g) and large pore volume (1.058 cm3/g) gave it a large adsorption capacity. The Langmuir model exhibited better correlation for equilibrium data analysis, with a maximum adsorption capacity of 173.9 mg/g at 298 K. The SBC was found to have a high removal effect over a wide pH range (from 1 to 13) and showed remarkable stability after undergoing five desorption-adsorption cycles using ethanol and acetone as eluent. The results provide a simple and low-cost method for the efficient treatment of TNT red water.