Solventless solid‐phase extraction using Zn ion‐imprinted polymer detected by colorimetric method

Machine Learning-Assisted Carbon Quantum Dot-Enhanced Fluorescent Probe for the Detection of Zn2+ in Sweat

Zinc, an indispensable trace element for human body, plays a vital role in numerous physiological processes. While current methods for detecting Zn2+ exhibit high sensitivity and specificity, they typically rely on complex instrumentation and entail laborious sample preparations. This study synthesized highly selective fluorescent carbon quantum dots (CQDs) with microcrystalline cellulose extracted from biological waste as the raw material. The synthesized CQDs, leveraging their superior aggregation-induced emission (AIE) properties, enabled the detection of trace levels of Zn2+ in sweat and maintained stable fluorescence performance even in the presence of other chemical species. Furthermore, a machine learning-powered detection framework was developed, synergizing spectral feature clustering with a lightweight MobileViT architecture. This intelligent system boosted Zn2+ identification accuracy to 82.4% through automated analysis of 650 fluorescence profiles, while enabling real-time quantification. The machine learning-optimized workflow achieved exceptional performance (LOD: 0.17 μM) even in multi-interferent sweat matrices. This machine learning-enhanced CQD-based biosensing method establishes a transformative approach for next-generation trace element monitorin.

Influence of Synthesis Parameters and Polymerization Methods on the Selective and Adsorptive Performance of Bio-Inspired Ion Imprinted Polymers

Ion-imprinted polymers (IIPs) have been widely used in different fields of Analytical Sciences due to their intrinsic selective properties. However, the success of chemical imprinting in terms of selectivity, as well as the stability, specific surface area, and absence of swelling effect depends on fully understanding the preparation process. Therefore, the proposal of this review is to describe the influence of relevant parameters on the production processes of ion-imprinted polymers, including the nature (organic, inorganic, or hybrid materials), structure, properties of the salt (source of the metal ion), ligand, crosslinking agent, porogenic solvent, and initiator. Additionally, different polymerization methods are discussed, the classification of IIPs as well as the applications of these adsorbent materials in the last years (2017–2022).