Chlorine gas and hydrogen chloride are highly reactive chemicals that pose a significant hazard to living organisms upon direct contact. Also, chlorine-containing gases are often by-products of industrial chemical synthesis and can be released into the air as a result of accidents. This can lead to great pollution of the environment. To remove toxic gases, various filter systems can be used. Filters based on carbon nanomaterials can be suitable for capturing gaseous chlorine-containing substances, preventing their spread into the air. In this work, the sorption activity of various carbon-based nanomaterials (graphene oxide, modified graphene oxide, reduced graphene oxide, multi-walled carbon nanotubes, carbon black) in relation to gaseous chlorine and hydrogen chloride was investigated for the first time. It has been shown that employed carbon nanomaterials have an excellent ability to remove chlorine and hydrogen chloride from the air, exceeding the performance of activated carbon. Modified graphene oxide with an increased surface area showed the highest sorption capacity of 73.1 mL HCl and 200.0 mL Cl₂ per gram of the sorbent, that is almost two and five times, respectively, higher than that of activated carbon. The results show that carbon nanomaterials could potentially be used for industrial filters and membrane fabrication.

A composite based on θ-Al₂O₃ microspheres coated with graphene oxide (GO) and reduced graphene oxide (RGO) was prepared and evaluated as a sorbent for the removal of synthetic dyes from aqueous solutions. GO was synthesized by a modified Hummers’ method and deposited onto alumina microspheres via ultrasound-assisted treatment under various conditions, followed by supercritical reduction to obtain the Al₂O₃_RGO composite. The structure, morphology, and composition of the materials were characterized by Raman spectroscopy, SEM, TGA/DSC, FTIR, and XRD, revealing the formation of mono- and few-layer GO/RGO coatings on the substrate surface. Adsorption tests for cationic methylene blue (MB) dye and anionic methyl orange (MO) dye demonstrated that the alumina substrate was inactive, whereas GO- and RGO-coated microspheres exhibited high adsorption efficiency for MB and partial uptake of MO from water solutions. In mixed-dye solutions, both Al₂O₃_GO and Al₂O₃_RGO composites showed selectivity toward MB, and the RGO-based composite demonstrated enhanced MB adsorption at low concentrations. The results highlight GO/RGO-coated θ-Al₂O₃ microspheres as convenient and selective composite sorbents for water purification processes.

The paper considers the kinetics of lead ions (Pb2+) sorption from model aqueous solutions using underoxidized and overoxidized graphene oxide samples obtained from synthetic and natural (taken as comparison material) graphite. It was experimentally found that the contaminant is sorbed in the first 5 min (for the underoxidized samples) and 30 min (for the overoxidized samples), achieving a sorption capacity of 105–138 mg g–1. Moreover, the capacity of the material increases with an increase in its oxidation state. The capacity of the synthetic material is slightly higher than that of the natural one. To study the removal mechanisms and determine the process parameters, the experimental data were fitted to kinetic (pseudo-first and pseudo-second order, as well as Elovich) and diffusion (internal diffusion – Morris-Weber and external diffusion – Boyd) models. It was found that the metal sorption is controlled by mixed diffusion of the sorbate into the bulk of the sorbent. It was also determined that this process is limited by the chemical interaction between the sorbent and the sorbate and depends on the sorbate concentration and the ambient temperature. Besides, the surface morphology of the samples was studied using scanning electron microscopy, and information on their elemental composition before and after the sorption was obtained using energy dispersive spectrometry, which confirmed the mechanism of the sorption processes occurring in the systems.

This work couples statistical synthesis optimization with AI-guided electrode-design to boost the electrochemical performance of additively manufactured rGO-Cobalt oxide supercapacitor electrodes. The optimal synthesis conditions found using a full-factorial design (DoE) of experiment (yielded a nanocomposite with well-dispersed Co3O4 and CoO domains embedded on a conductive rGO matrix to be further applied in inks. To decouple geometry-dependent effects from material contributions, 30 printed electrode architectures were systematically evaluated, producing specific capacitances of 59.7-96.2 F/g and establishing electrode topology as a first-order performance determinant. A machine learning model was subsequently trained to extract nonlinear structure-property relationships from geometric descriptors, including connectivity, curvature, and ion transport-path metrics and generated a computationally derived electrode pattern. This AI-optimised architecture achieved a specific capacitance of 104.8 F/g, measured by cyclic voltammetry, surpassing the tested pattern library by approximately 9% under identical experimental conditions. The optimised electrode further delivered 210.5 F/g at 0.5 A/g with a rate-capability retention of ~92%, corresponding to an estimated gravimetric energy density of ~7.3 Wh/kg. These findings demonstrate that coupling DoE-validated synthesis control with AI-generated electrode topology enables simultaneous improvement of capacitance, rate performance, and energy/power metrics without chemical reformulation, establishing a scalable and transferable digital-design framework for next-generation high-performance supercapacitor electrodes.

Anthropogenic contamination of water resources poses a critical global challenge for designing efficient adsorption-based water treatment processes. This work provides a systematic adsorption study of six graphene-based sorbents with different C/O ratios and surface chemistries for the removal of four representative cationic and anionic dyes and two broad-spectrum antibiotics (amoxicillin and norfloxacin) from aqueous solutions, including their mixtures in model wastewater. Overoxidized graphene oxide demonstrates high removal efficiencies for cationic dyes, with maximum sorption capacities of 155 mg/g for methylene blue and 175.5 mg/g for brilliant green. In contrast, under-oxidized graphene oxide shows even higher capacities for several dyes, reaching 369, 444 and 488 mg/g for methylene blue, brilliant green and Congo red, respectively. Thermally reduced graphene oxide combines partial reduction of carbon framework with residual oxygen functionalities and achieves sorption capacities of 153 mg/g for methylene blue and 209 mg/g for methyl orange. All graphene-based sorbents also effectively remove antibiotics, with maximum sorption capacities in the range of 322–487 mg/g. Adsorption kinetics and equilibrium are described using pseudo-second-order and nonlinear Langmuir and Sips models, enabling quantitative comparison of sorbent performance. The effectiveness of the graphene-based sorbents is further validated under near-real conditions in river water purification experiments, where dyes were present at extremely low concentrations (1 ppm). These results demonstrate that controlled oxidation and reduction of graphene oxide provide an effective route for tailoring sorbent selectivity and adsorption performance in wastewater treatment applications.