Samir G. Patel

Electrocatalytic polyethylene terephthalate (PET) upcycling coupled with green hydrogen production offers an energy‐efficient route for plastic waste valorization. Herein, Nb‐incorporated NiCoS electrocatalysts are synthesized on nickel foam via a one‐step chemical bath deposition route for PET electro‐upcycling. Nb incorporation modulates the electronic structure and morphology of NiCoS, producing defect‐rich vertically interconnected nanosheets with abundant electrochemically dynamic Ni ³⁺ /Co ³⁺ active sites. The optimized electronic structure promotes reconstruction into active NiOOH/CoOOH species, resulting in enhanced performance toward the hydrogen evolution reaction (HER), oxygen evolution reaction (OER), ethylene glycol oxidation reaction (EGOR), and PET hydrolysate oxidation reaction (POR). Nb‐NiCoS requires 1.32 and 1.34 V vs RHE to achieve 100 mA cm ⁻² for EGOR and POR, respectively, significantly lower than OER (1.52 V vs RHE). Mechanistic analysis reveals an indirect oxy‐hydroxide‐mediated oxidation pathway, enabling selective conversion of PET‐derived EG into formic acid with a Faradaic efficiency of 93.3% (with ~100% selectivity) and a production rate of 1.16 mmol h ⁻¹ cm ⁻² at 100 mA cm ⁻² . Coupling PET electro‐upcycling with hydrogen production reduces the energy consumption to 3.52 kWh Nm ⁻³ from 4.49 kWh Nm ⁻³ for conventional water electrolysis, enabling energy saving of 21.3%, highlighting a scalable strategy for simultaneous plastic waste valorization and hydrogen production.

Background: Tofacitinib (TFC) is a Janus kinase inhibitor approved by the FDA, for the treatment of autoimmune disorders. Objective: The research aimed to develop, validate, and apply a simple, rugged, and environmentally sustainable reversed-phase (RP)-HPLC method for the quantitative estimation of TFC in in-house developed mesoporous silica nanoparticles (MCM-41 and MCM-48), intended for formulation-related analytical applications, while systematically evaluating environmental and analytical sustainability. Method: The chromatographic separation was achieved on an Inertsil® C18 column using an isocratic mobile phase of Milli-Q water–acetonitrile (65 + 35, v/v) at a flow rate of 1 mL/min, with photodiode array (PDA) detection at 287 nm and a total run time of 15 min. The validated approach was applied to formulation-based analytical studies. Environmental and analytical sustainability was evaluated using the Analytical GREEnness (AGREE) and the Red-Green-Blue-12 (RGB-12) whiteness model. Results: The method exhibited excellent specificity without interference from formulation excipients and showed linearity over 1–24 µg/mL (r² = 0.9987). High accuracy (98–102%), precision 0.06–1.31% RSD, and sensitivity ( 0.28 µg/mL LOD and 0.848 µg/mL LOQ) in compliance with International Conference on Harmonisation (ICH) guidelines, enabled reliable estimation of TFC. The method demonstrated good ruggedness (0.012–1.33% RSD), indicating reliability under small deliberate changes. High AGREE and RGB-12 whiteness (0.79 and 87.0) values confirmed the enhanced sustainability and practical feasibility. Conclusion: The developed RP-HPLC method integrates reliable analytical performance with green and white chemistry principles, rendering it suitable for routine QC and formulation-oriented research involving mesoporous silica-based drug delivery systems. Highlights: A novel sustainable RP-HPLC method was developed and validated for the analysis of TFC-loaded MCM-41 and MCM-48 MSNs. The method demonstrated excellent performance in accordance with ICH Q2 (R2) guidelines. It was successfully applied for drug content determination and in vitro diffusion studies. Sustainability assessment using AGREE and RGB-12 models confirmed favorable greenness and whiteness, with reduced analysis time and resource consumption compared to reported methods.

Electrocatalytic upcycling of polyethylene terephthalate (PET) plastics into value-added chemicals provides a sustainable route to simultaneously mitigate plastic pollution and enable energy-efficient chemical synthesis.

Polyethylene terephthalate (PET) is one of the most widely used plastics, whose extensive consumption and limited recyclability have led to severe environmental challenges. Electrocatalytic upcycling of PET has emerged as a promising strategy that not only mitigates plastic waste but also enables the concurrent generation of value-added chemicals and hydrogen (H₂). Herein, cerium-incorporated nickel cobalt sulfide (Ce-NiCoS) catalysts was prepared via one-step chemical bath deposition and utilized for electro-oxidation of real PET-waste derived ethylene glycol (EG) and cathodic hydrogen evolution at industrial-scale current densities. With optimized electronic structure and hierarchical morphology, Ce-NiCoS catalysts demonstrated EG oxidation reaction (EGOR) at 1.30 V vs RHE (reversible hydrogen electrode) at a current density of 100 mA cm^-2, which is lowered by 230 mV, compared to the oxygen evolution reaction. In-situ Raman spectroscopy and electrochemical impedance spectroscopy further confirms the accelerated electro-oxidation of catalysts surface and formation of metal oxyhydroxides sites, which are highly active for the chemical oxidation of EG into formate. Quantitative analysis suggests that the Ce-NiCoS catalysts exhibit a Faradaic efficiency of 99% for H₂-production and 96.5% for EG to FA conversion. Because of thermodynamically favorable EGOR kinetics, PET hydrolysate electrolysis generates 1 N m³ of H₂ utilizing the electrical energy of 4.39 kWh Nm^-3 which is 13% less than the electric input required for fresh water electrolysis (5.05 kWh Nm^-3) and demonstrates the exceptional stability for catalytic performance at industrial scale current density for 60 h. Overall, this integrated approach thus presents a sustainable paradigm for addressing plastic pollution while contributing to carbon-neutral hydrogen production and advancing green chemical technologies.

Microplastic reformation in conjunction with the electrochemical hydrogen evolution has merits for producing value-added chemicals and mitigating environmental pollution.

Simultaneous green H ₂ production and PET plastic upcycling.

Berberine hydrochloride (BHC), a key isoquinoline alkaloid from the Berberis genus, is gaining prominence for its diverse pharmacological properties. The goal was to devise rapid and sensitive spectrofluorophotometric methods (Analytical and Bioanalytical) for precise BHC estimation in varied matrices, addressing crucial needs in pharmaceutical and biomedical research.Utilizing a luminescence spectrometer (Perkin Elmer, UK), BHC was detected with 1M Methanolic H2SO4, at excitation and emission wavelength of 350 nm, and 530 nm respectively. BHC extraction from spiked human plasma employed a protein precipitation method with acetonitrile. Validation studies, following ICH Q2 (R1) guidelines, demonstrated the efficacy of both methods. Linear responses were observed in the 200-800 ng/mL BHC concentration range, with precision (% RSD <5%) meeting acceptable limits. Recovery studies (90%-110%) affirmed reliability and reproducibility. The developed spectrofluorophotometric methods for BHC estimation offer simplicity, linearity, sensitivity, precision, and accuracy. Their robustness, confirmed through validation and comparison with existing methods, positions them as valuable tools for BHC quantification in pharmaceutical and biomedical research. These methods present a promising advancement in analytical approaches for researchers in the field.

Background Achieving optimal tacrolimus dosing is vital for effectively balancing therapeutic efficacy and safety, as CYP3A5 genetic variants and inter-patient variability emphasize the need for precision strategies. Aim This study aimed to optimize tacrolimus dosage prediction for renal transplant recipients by incorporating genetic polymorphisms, specifically profiling CYP3A5 genetic variants, within the DoseOptimal framework to enhance interpretability and accuracy of dosing decisions. Method The dataset comprised clinical, demographic, and CYP3A5 genetic variants information from 1045 stable tacrolimus-treated patients. The DoseOptimal framework was developed by integrating the strengths of the most effective algorithms from fifteen machine learning models. SHapley Additive exPlanations (SHAP) and decision tree insights were incorporated to enhance the framework’s interpretability. The framework’s performance was assessed using mean absolute error (MAE) and the coefficient of determination (R² score). The F-statistic and p value were calculated to validate the framework’s statistical significance. Results The DoseOptimal framework demonstrated robust performance with an R² score of 0.884 in the training set and 0.830 in the testing set. The MAE was 0.40 mg/day (95% CI 0.38–0.43) in the training set and 0.41 mg/day (95% CI 0.38–0.45) in the testing set. The framework predicted the ideal tacrolimus dosage in 87.6% (n = 275) of the test cohort, with 3.2% (n = 10) underestimation and 9.2% (n = 29) overestimation. The framework’s statistical significance was confirmed with an F-statistic of 266.095 and a p value < 0.001. Conclusion The framework provides precision medicine-based dosing solutions tailored to individual genetic profiles, minimizing dosing errors and enhancing patient outcomes.