Gelatin is an attractive hydrogel material because of its excellent biocompatibility and non-cytotoxicity, but poor mechanical properties of gelatin-based hydrogels become a big obstacle that limits their wide-spread application.

Polydopamine (PDA)-coated magnetic multiwalled carbon nanotube (M-MWCNT) composites were synthesized in two facile preparation steps, and were used as adsorbents for magnetic solid-phase extraction (MSPE) coupled with high-performance liquid chromatography (HPLC) for simultaneous extraction, enrichment and determination of five kinds of typical chlorophenols (CPs) in water samples. The as-prepared magnetic composites showed excellent magnetic properties and high thermal stability. Various main parameters influencing the extraction efficiency of MSPE were systematically investigated. Under the optimized MSPE–HPLC conditions, a high enrichment factor (EF) was obtained in the range of 85–112 for 2-chlorophenol (2-CP), 4-chlorophenol (4-CP), 2,6-dichlorophenol (2,6-DCP), 2,4-dichlorophenol (2,4-DCP) and 2,4,6-trichlorophenol (2,4,6-TCP). Good linearity was obtained in the range of 2.0–200 μg L⁻¹ for 2-CP and 4-CP and 1.0–200 μg L⁻¹ for 2,6-DCP, 2,4-DCP and 2,4,6-TCP, with a correlation coefficient (R²) higher than 0.9964. The limits of detection (LODs) and the limits of quantification (LOQs) were in the range of 0.10–0.31 μg L⁻¹ and 0.35–1.03 μg L⁻¹, respectively. The intraday and interday precisions evaluated using relative standard deviation (RSD) values were in the range of 1.05–2.25% and 1.88–2.83%, respectively. The validated MSPE–HPLC method was also successfully applied to analyze five kinds of CPs in tap water, lake water, river water and seawater samples, and satisfactory recoveries were obtained in the range of 76.87–106.5% with RSDs of 1.64–6.78%.

Mechanically enhanced gelatin-based composite hydrogels were developed in the presence of functionalized cellulose nanocrystals (CNCs) employing microbial transglutaminase (mTG) as a binding agent. In this work, the surfaces of CNCs were grafted with (3-Aminopropyl) trimethoxysilane with a NH₂ functional group, and the success of CNCs’ modification was verified by FTIR spectroscopy and XPS. The higher degree of modification in CNCs resulted in more covalent cross-linking and dispersibility within the gelatin matrix; thus, the as-prepared hydrogels showed significantly improved mechanical properties and thermo-stability, as revealed by dynamic rheological analysis, uniaxial compression tests and SEM. The biocompatibility of the obtained hydrogels was evaluated by the MTT method, and it was found that the grafted CNCs had no obvious inhibitory effect on cell proliferation. Hence, the mechanically enhanced gelatin-based hydrogels might have great potential in biomedical applications.

Gelatin-based hydrogels with excellent mechanical properties and conductivities are desirable, but their fabrication is challenging. In this work, an innovative approach for the preparation of gelatin-based conductive hydrogels is presented that improves the mechanical and conductive properties of hydrogels by integrating Z–Gln–Gly into gelatin polymers via enzymatic crosslinking. In these hydrogels (Gel–TG–ZQG), dynamic π–π stacking interactions are created by the introduction of carbobenzoxy groups, which can increase the elasticity and toughness of the hydrogel and improve the conductivity sensitivity by forming effective electronic pathways. Moreover, the mechanical properties and conductivity of the obtained hydrogel can be controlled by tuning the molar ratio of Z–Gln–Gly to the primary amino groups in gelatin. The hydrogel with the optimal mechanical properties (Gel–TG–ZQG (0.25)) exhibits a high storage modulus, compressive strength, tensile strength, and elongation at break of 7.8 MPa at 10 °C, 0.15 MPa at 80% strain, 0.343 MPa, and 218.30%, respectively. The obtained Gel–TG–ZQG (0.25) strain sensor exhibits a short response/recovery time (260.37 ms/130.02 ms) and high sensitivity (0.138 kPa⁻¹) in small pressure ranges (0–2.3 kPa). The Gel–TG–ZQG (0.25) hydrogel-based sensors can detect full-range human activities, such as swallowing, fist clenching, knee bending and finger pressing, with high sensitivity and stability, yielding highly reproducible and repeatable sensor responses. Additionally, the Gel–TG–ZQG hydrogels are noncytotoxic. All the results demonstrate that the Gel–TG–ZQG hydrogel has potential as a biosensor for wearable devices and health-monitoring systems.

Amino-functionalized silica@resorcinol–formaldehyde nanocomposites (NH₂-SiO₂@RF) were synthesized for the removal of Cr(VI) from aqueous solutions using the sol–gel technique with two simple preparation steps, including the one-pot synthesis of SiO₂@RF using the Stöber method and (3-aminopropyl)triethoxysilane (APTES) modification. The morphology, particle size, functional group, and thermal stability of the obtained nanocomposites were systematically characterized, with the results indicating a uniform sphericity with a particle size of 200 nm and high thermal stability. The adsorption results demonstrated that the preferred pH value was 2, and the data were well fitted with the Langmuir and Temkin isotherm models and quasi-second-order kinetic equation, indicating a high adsorption capacity. The maximum Cr(VI) adsorption capacity from the nonlinear form of the Langmuir model was 272.6 mg·g⁻¹. The intra-particle diffusion model accurately described the adsorption of Cr(VI) onto NH₂-SiO₂@RF. The changes in Gibb’s free energy, enthalpy, and entropy revealed that Cr(VI) adsorption onto NH₂-SiO₂@RF was a spontaneous and endothermic process. Furthermore, high selectivity was demonstrated in the material for the removal of Cr(VI) from commonly coexisting ions. The obtained nanocomposites had good regeneration properties and maintained a removal rate above 85% in the fifth adsorption–desorption experiments. Moreover, under the optimized adsorption conditions, the obtained nanocomposites were preliminarily applied to tannery wastewater, demonstrating an excellent removal effect, which indicates their potential application value.