Jing Wang

Bio: Jing Wang is an academic researcher. The author has contributed to research in topics: Crystallization of polymers & Molecularly imprinted polymer. The author has an hindex of 1, co-authored 1 publications receiving 39 citations.

Estimating the Relative Crystallinity of Biodegradable Polylactic Acid and Polyglycolide Polymer Composites by Machine Learning Methodologies

Abstract: Biodegradable polymers have recently found significant applications in pharmaceutics processing and drug release/delivery. Composites based on poly (L-lactic acid) (PLLA) have been suggested to enhance the crystallization rate and relative crystallinity of pure PLLA polymers. Despite the large amount of experimental research that has taken place to date, the theoretical aspects of relative crystallinity have not been comprehensively investigated. Therefore, this research uses machine learning methods to estimate the relative crystallinity of biodegradable PLLA/PGA (polyglycolide) composites. Six different artificial intelligent classes were employed to estimate the relative crystallinity of PLLA/PGA polymer composites as a function of crystallization time, temperature, and PGA content. Cumulatively, 1510 machine learning topologies, including 200 multilayer perceptron neural networks, 200 cascade feedforward neural networks (CFFNN), 160 recurrent neural networks, 800 adaptive neuro-fuzzy inference systems, and 150 least-squares support vector regressions, were developed, and their prediction accuracy compared. The modeling results show that a single hidden layer CFFNN with 9 neurons is the most accurate method for estimating 431 experimentally measured datasets. This model predicts an experimental database with an average absolute percentage difference of 8.84%, root mean squared errors of 4.67%, and correlation coefficient (R2) of 0.999008. The modeling results and relevancy studies show that relative crystallinity increases based on the PGA content and crystallization time. Furthermore, the effect of temperature on relative crystallinity is too complex to be easily explained.

Strategies of molecular imprinting-based solid-phase extraction prior to chromatographic analysis

Abstract: Molecular imprinting-based solid-phase extraction (MI-SPE) has been in the spotlight to improve the recognition selectivity and detection sensitivity. MI-SPE provides a powerful tool for chemo/bioanalysis in complex matrices and meanwhile, benefits from distinguished advantages such as easy operation, high throughput, low cost, high selectivity and durability. This review proposed the recent advances in molecular imprinting concerning novel preparation strategies of molecularly imprinted polymers (MIPs) and typical applications of MI-SPE. Preparation strategies are highlighted by dividing into ten sections mainly including dummy imprinting, multi-template imprinting, surface imprinting, water-compatible imprinting, restricted access material combining imprinting etc.; each section provides the descriptions about what restrictions led to the emergence of any strategy, strengths/weaknesses of every strategy and universal applications of upgraded MIPs in various SPE modes prior to chromatographic analysis. The potential of MIPs for implementation in routine laboratory activities and scale-up is expected, and finally remaining challenges and future perspectives are proposed.

Simple and selective detection of quercetin in extracts of plants and food samples by dispersive-micro-solid phase extraction based on core–shell magnetic molecularly imprinted polymers

Abstract: The objective of this study was to develop a simple, sensitive and selective procedure for the preconcentration and determination of quercetin residues in Apium graveolens, Brassica oleracea, Spinacia oleracea, watercress, onion, and apple matrices This novel method was developed on the basis of the dispersive-micro-solid phase extraction (D-μ-SPE) procedure based on a core–shell magnetic molecularly imprinted polymer (MMIP) in combination with high-performance liquid chromatography-ultraviolet (HPLC-UV) Variables affecting the quercetin extraction efficiency included pH, MIP dose, extraction contact time, elution organic solvent, and volume of organic solvent and were evaluated by the experimental central composite design (CCD) The obtained optimal parameters were as follows: pH (35), sorbent (12 mg), elution organic solvent and solvent volume (methanol, 02 mL), and elution time (220 min, without adding salt) The calibration curve was linear in the concentration range of 06–5500 μg L−1 with the lower limits of detection found in the range of 0113–0117 μg L−1, thereby revealing the high-sensitivity and -selectivity properties The combination of D-μ-SPE and HPLC-UV could provide a method for the recovery of the analyte in various matrices at 22 min contact time with good reusability and excellent recoveries at four concentration levels (50, 100, 500, and 1000 μg L−1), ranging between 9544 and 10689% (relative standard deviation <60%) Based on competitive sorption experiments, the synthesized MMIP displays higher selectivity toward quercetin compared to non-imprinted polymers (NIPs) and other sorbents

Molecularly Imprinted Materials for Selective Biological Recognition.

Abstract: Molecular imprinting is an approach of generating imprinting cavities in polymer structures that are compatible with the target molecules. The cavities have memory for shape and chemical recognition, similar to the recognition mechanism of antigen-antibody in organisms. Their structures are also called biomimetic receptors or synthetic receptors. Owing to the excellent selectivity and unique structural predictability of molecularly imprinted materials (MIMs), practical MIMs have become a rapidly evolving research area providing key factors for understanding separation, recognition, and regenerative properties toward biological small molecules to biomacromolecules, even cell and microorganism. In this review, the characteristics, morphologies, and applicability of currently popular carrier materials for molecular imprinting, especially the fundamental role of hydrogels, porous materials, hierarchical nanoparticles, and 2D materials in the separation and recognition of biological templates are discussed. Moreover, through a series of case studies, emphasis is given on introducing imprinting strategies for biological templates with different molecular scales. In particular, the differences and connections between small molecular imprinting (bulk imprinting, "dummy" template imprinting, etc.), large molecular imprinting (surface imprinting, interfacial imprinting, etc.), and cell imprinting strategies are demonstrated in detail. Finally, future research directions are provided.