Surface imprinted polymers for oil denitrification with the combination of computational simulation and multi-template molecular imprinting

Engineering boron and nitrogen codoped carbon nanoarchitectures to tailor molecularly imprinted polymers for PFOS determination

Per- and polyfluoroalkyl substances (PFAS) have gained significant attention as emerging contaminants due to their persistence, abundance, and adverse health effects. Consequently, the urgent need for ubiquitous and effective sensors capable of detecting and quantifying PFAS in complex environmental samples has become a priority. In this study, we present the development of an ultrasensitive molecularly imprinted polymer (MIP) electrochemical sensor tailored by chemically vapour-deposited boron and nitrogen codoped diamond-rich carbon nanoarchitectures for the selective determination of perfluorooctanesulfonic acid (PFOS). This approach allows for a multiscale reduction of MIP heterogeneities, leading to improved selectivity and sensitivity in PFOS detection. Interestingly, the peculiar carbon nanostructures induce a specific distribution of binding sites in the MIPs that exhibit a strong affinity for PFOS. The designed sensors demonstrated a low limit of detection (1.2 μg L^-1) and exhibited satisfactory selectivity and stability. To gain further insights into the molecular interactions between diamond-rich carbon surfaces, electropolymerised MIP, and the PFOS analyte, a set of density functional theory (DFT) calculations was performed. Validation of the sensor's performance was carried out by successfully determining PFOS concentrations in real complex samples, such as tap water and treated wastewater, with average recovery rates consistent with UHPLC-MS/MS results. These findings demonstrate the potential of MIP-supported diamond-rich carbon nanoarchitectures for water pollution monitoring, specifically targeting emerging contaminants. The proposed sensor design holds promise for the development of in situ PFOS monitoring devices operating under relevant environmental concentrations and conditions.

The Use of Computational Methods for the Development of Molecularly Imprinted Polymers

Recent years have witnessed a dramatic increase in the use of theoretical and computational approaches in the study and development of molecular imprinting systems. These tools are being used to either improve understanding of the mechanisms underlying the function of molecular imprinting systems or for the design of new systems. Here, we present an overview of the literature describing the application of theoretical and computational techniques to the different stages of the molecular imprinting process (pre-polymerization mixture, polymerization process and ligand-molecularly imprinted polymer rebinding), along with an analysis of trends within and the current status of this aspect of the molecular imprinting field.

An Update on Molecularly Imprinted Polymer Design through a Computational Approach to Produce Molecular Recognition Material with Enhanced Analytical Performance

Molecularly imprinted polymer (MIP) computational design is expected to become a routine technique prior to synthesis to produce polymers with high affinity and selectivity towards target molecules. Furthermore, using these simulations reduces the cost of optimizing polymerization composition. There are several computational methods used in MIP fabrication and each requires a comprehensive study in order to select a process with results that are most similar to properties exhibited by polymers synthesized through laboratory experiments. Until now, no review has linked computational strategies with experimental results, which are needed to determine the method that is most appropriate for use in designing MIP with high molecular recognition. This review will present an update of the computational approaches started from 2016 until now on quantum mechanics, molecular mechanics and molecular dynamics that have been widely used. It will also discuss the linear correlation between computational results and the polymer performance tests through laboratory experiments to examine to what extent these methods can be relied upon to obtain polymers with high molecular recognition. Based on the literature search, density functional theory (DFT) with various hybrid functions and basis sets is most often used as a theoretical method to provide a shorter MIP manufacturing process as well as good analytical performance as recognition material.

Preparation of molecularly imprinted polymeric microspheres based on distillation-precipitation polymerization for an ultrasensitive electrochemical sensor

A highly sensitive electrochemical sensor based on a carbon paste electrode (CPE) modified with molecularly imprinted polymeric microspheres (MIPMSs) was developed for the determination of bisphenol A (BPA). For the first time BPA-imprinted MIPMSs were prepared via distillation precipitation polymerization, and then the polymeric microspheres were involved in producing the MIPMS-modified CPE (MIPMS/CPE). The polymers obtained were observed via a scanning electron microscope and its dynamic and static adsorption performances were investigated. Cyclic voltammetry and electrochemical impedance spectroscopy were performed to study the preparation process and electrochemical behavior of the modified carbon paste electrodes with [Fe(CN)₆]^3-/4- ions acting as electrical indicators. Compared with the bulk MIP packed sensor, the MIPMS/CPE exhibits a higher sensing response and better reproducibility. The detection linear range for BPA is 1 × 10^-11-1 × 10^-7 M with a detection limit of 2.8 × 10^-12 M (S/N = 3) under the optimal experimental conditions. Moreover, the MIPMS/CPE exhibited good selectivity and stability. The developed sensor can determine BPA in real samples including soil, milk and water rapidly and accurately after simple sample pretreatment.