KLE Institute of Technology

High-performing sensors are critical tools for the trace-level detection of hazardous chemicals, ensuring public health and environmental safety. In the present study, we report an electrochemical sensor based on synergistic properties of multiwall carbon nanotubes (MWCNTs) and titanium dioxide (TiO2) nanoparticles for sensitive and selective detection of fungicide carbendazim (CRZ). The morphological and elemental composition of the MWCNTs/TiO2 nano-composite was determined using scanning electron microscopy (SEM), energy-dispersive Xray spectroscopy (EDX), X-ray diffraction (XRD), and atomic force microscopy (AFM). In addition, the electrochemical studies were executed using electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and square wave voltammetry (SWV) techniques. The hybrid composite electrode effectively enhanced the electrochemical performance in the detection of CRZ, with a lower limit of detection of 3.49 nM within the linear range 0.1-10.0 & micro;M. Under optimized conditions, such as pH and accumulation time, spiked samples of soil and water were analyzed demonstrating high accuracy and good recovery. The fabricated electrode proposed had the least interference from the excipients, proving its practical applicability. The electrode was cost-effective ($0.12 USD/electrode) and time saving (require 30 min fabrication time), simple and easily renewable making it unique from other proposed sensors. The stability and wide range of pertinency of the fabricated electrode suggested it as a promising sensor platform for detecting CRZ.

Concrete produced using ash from biomedical waste is a sustainable construction solution that can help reduce the environmental impact associated with cement production. The study develops a database of Biomedical Waste Ash (BMWA) concrete from literature sources and applies advanced Machine Learning (ML) techniques to predict the mechanical properties of the mixes. Four ML models (Random Forest (RF), Self-Attention and Intersample Attention Transformer (SAINT), TabNet, and an Ensemble model) were subjected to performance evaluation, hyperparameter optimization, and ten-fold cross-validation. RF and TabNet achieved the highest predictive performance, with an R² of 0.82 across strength parameters, while SAINT demonstrated stable generalization but reduced accuracy for certain strength parameters. The ensemble model showed poorer performance than each model, which emphasizes the capability of robust standalone models in specific and limited databases. The external validation showed good agreement between them and hence supports the reliability of our models. Sustainability Index (SI) incorporates cement substitution, durability improvement, and retained strength to evaluate the overall performance of the BMWA concrete at 15% BMWA. The study proposes an integrated data-driven framework that combines advanced ML methods, interpretability analysis, external validation, and sustainability indexing to optimize BMWA concrete and indicate its dual role in reducing the environmental footprint of the cement industry and utilizing biomedical waste in building materials, thus supporting the principles of the circular economy and the global sustainability goals.

Perfluorochemicals are synthetic compounds used in many applications; however, their slow degradation classifies them as emerging micropollutants that persist in the environment. Long-term exposure to perfluorononanoic acid (PFNA) and perfluorooctanesulfonic acid (PFOS) via soil, water, and food can cause human health problems. In this research, SnO2 nanoparticles were synthesized hydrothermally to study the electrocatalytic detection of PFNA and PFOS. The tin oxide (SnO2) nanoparticles were characterized by scanning electron microscopy and X-ray diffraction, which showed a tetragonal rutile structure with an average crystallite size of 68.5 nm and particle sizes ranging from 53 to 225 nm. Electrochemical properties of SnO2-coated carbon paste electrodes (SnO2/CPE) were used in cyclic voltammetry and square wave voltammetry to investigate the sensing properties of the materials developed. Due to their higher electroactive surface area and faster charge transfer rates, SnO2/CPE exhibits higher sensitivity with detection limits of 15.9 nM (0.0159 μM; 7380 ppm) for PFNA and 30.7 nM (0.0307 μM; 15,350 ppt) for PFOS, respectively. The ECSA of SnO2/CPE was 0.068 cm2 vs 0.042 cm2 in the nascent CPE, representing a 1.6-fold increase in the active sites. The sensor demonstrated sensitivities of 58.11 μA μM-1·cm-2 (PFNA) and 25.03 μA μM-1·cm-2 (PFOS), respectively while the recoveries of PFAAs in spiked soil and water samples ranged between 87.0 and 95.46 %, and 87.5-94.7 %, respectively with RSD of 2.0-3.5 %. The study outlines the capabilities of SnO2 nanoparticles to produce low-cost, high-efficiency sensors to detect pollutants, suggesting the potential future environmental monitoring applications.

The studies reported a novel method for synthesizing hafnium-doped tungsten oxide as a sensing platform for clinically crucial serolytic agent, ambroxol. A carbon matrix decorated with synthesized nanostructures exhibited a synergistic effect, displaying high conductivity and a large surface area, which significantly enhanced the oxidative peak current compared to the bare carbon matrix. The analytical performance was evaluated electrochemically employing techniques such as cyclic voltammetry, electrochemical impedance spectroscopy, and square wave voltammetry. Under a wide linear range, the key highlight was low detection limit of 2.55 nM. The fabricated electrode was highly selective, reproducible, and suitable for long-term usage with good stability. Reasonable recovery rates from pharmaceutical and urine samples showed the accuracy and reliability of the sensor for real-world sample analysis. The proposed work is promising in quantifying ambroxol at trace levels, representing a cost-effective and a direct method for clinical analysis and pharmaceutical quantification.

The full text of this preprint has been withdrawn by the authors while they make corrections to the work. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.