Meiting Shi

Bio: Meiting Shi is an academic researcher from Zhengzhou University. The author has contributed to research in topics: Hemicellulose & Hydrolysis. The author has an hindex of 3, co-authored 3 publications receiving 175 citations.

Raman spectroscopy combined with machine learning algorithms for rapid detection Primary Sjögren's syndrome associated with interstitial lung disease.

Abstract: BACKGROUND Interstitial lung disease (ILD) is a major complication of Primary Sjögren's syndrome (pSS) patients.It is one of the main factors leading to the death of patients. The aimed of this study is to evaluate the value of serum Raman spectroscopy combined with machine learning algorithms in the discriminatory diagnosis of patients with Primary Sjögren's syndrome associated with interstitial lung disease (pSS-ILD). METHODS Raman spectroscopy was performed on the serum of 30 patients with pSS, 28 patients with pSS-ILD and 30 healthy controls (HC). First, the data were pre-processed using baseline correction, smoothing, outlier removal and normalization operations. Then principal component analysis (PCA) is used to reduce the dimension of data. Finally, support vector machine(SVM), k nearest neighbor (KNN) and random forest (RF) models are established for classification. RESULTS In this study, SVM, KNN and RF were used as classification models, where SVM chooses polynomial kernel function (poly). The average accuracy, sensitivity, and precision of the three models were obtained after dimensionality reduction. The Accuracy of SVM (poly) was 5.71% higher than KNN and 6.67% higher than RF; Sensitivity was 5.79% higher than KNN and 8.56% higher than RF; Precision was 6.19% higher than KNN and 7.45% higher than RF. It can be seen that the SVM (poly) had better discriminative effect. In summary, SVM (poly) had a fine classification effect, and the average accuracy, sensitivity and precision of this model reached 89.52%, 91.27% and 89.52%, respectively, with an AUC value of 0.921. CONCLUSIONS This study demonstrates that serum RS combined with machine learning algorithms is a valuable tool for diagnosing patients with pSS-ILD. It has promising applications.

Potential and challenges of zeolite chemistry in the catalytic conversion of biomass

Abstract: Increasing demand for sustainable chemicals and fuels has pushed academia and industry to search for alternative feedstocks replacing crude oil in traditional refineries. As a result, an immense academic attention has focused on the valorisation of biomass (components) and derived intermediates to generate valuable platform chemicals and fuels. Zeolite catalysis plays a distinct role in many of these biomass conversion routes. This contribution emphasizes the progress and potential in zeolite catalysed biomass conversions and relates these to concepts established in existing petrochemical processes. The application of zeolites, equipped with a variety of active sites, in Bronsted acid, Lewis acid, or multifunctional catalysed reactions is discussed and generalised to provide a comprehensive overview. In addition, the feedstock shift from crude oil to biomass involves new challenges in developing fields, like mesoporosity and pore interconnectivity of zeolites and stability of zeolites in liquid phase. Finally, the future challenges and perspectives of zeolites in the processing of biomass conversion are discussed.

A critical review on hemicellulose pyrolysis

Abstract: Fast pyrolysis is a promising thermochemical technology that breaks down renewable and abundant lignocellulosic biomass into a primary liquid product (bio-oil) in seconds. The bio-oil can then be potentially catalytically upgraded into transportation fuels and multiple commodity chemicals. Hemicellulose is one of the three major components of lignocellulosic biomass and is characterized as a group of cell wall polysaccharides that are neither cellulose nor pectin. The composition and structural features of hemicellulose (mixture of different heterogeneous polysaccharides) and different specific hemicellulose polysaccharides are reviewed. Particular focus is then given to reviewing the status of hemicellulose pyrolysis in terms of experimental investigations, reaction mechanisms, and kinetic modeling. For each aspect, recent results, challenges, and future prospects are addressed.

Synthesis, characterisation, and catalytic evaluation of hierarchical faujasite zeolites: milestones, challenges, and future directions

Abstract: Faujasite (X, Y, and USY) zeolites represent one of the most widely-applied and abundant catalysts and sorbents in the chemical industry. In the last 5 years substantial progress was made in the synthesis, characterisation, and catalytic exploitation of hierarchically-structured variants of these zeolites. Hererin, we provide an overview of these contributions, highlighting the main advancements regarding the evaluation of the nature and functionality of introduced secondary porosity. The novelty, efficiency, versatility, and sustainability of the reported bottom-up and (predominately) top-down strategies are discussed. The crucial role of the relative stability of faujasites in aqueous media is highlighted. The interplay between the physico-chemical properties of the hierarchical zeolites and their use in petrochemical and biomass-related catalytic processes is assessed.

Hierarchically Structured Zeolites: From Design to Application.

Abstract: Hierarchical zeolites combine the intrinsic catalytic properties of microporous zeolites and the enhanced access and transport of the additional meso- and/or macroporous system. These materials are the most desirable catalysts and sorbents for industry and become a highly evolving field of important current interests. In addition to the enhanced mass transfer leading to high activity, selectivity, and cycle time, another essential merit of the hierarchical structure in zeolite materials is that it can significantly improve the utilization effectiveness of zeolite materials resulting in the minimum energy, time, and raw materials consumption. Substantial progress has been made in the synthesis, characterization, and application of hierarchical zeolites. Herein, we provide an overview of recent achievements in the field, highlighting the significant progress in the past decade on the development of novel and remarkable strategies to create an additional pore system in zeolites. The most innovative synthesis approaches are reviewed according to the principle, versatility, effectiveness, and degree of reality while establishing a firm link between the preparation route and the resultant hierarchical pore quality in zeolites. Zeolites with different hierarchically porous structures, i.e., micro-mesoporous structure, micro-macroporous structure, and micro-meso-macroporous structure, are then analyzed in detail with concrete examples to illustrate their benefits and their fabrications. The significantly improved performances in catalytic, environmental, and biological applications resulting from enhanced mass transport properties are discussed through a series of representative cases. In the concluding part, we envision the emergence of "material-properties-by-quantitative and real rational design" based on the "generalized Murray's Law" that enables the predictable and controlled productions of bioinspired hierarchically structured zeolites. This Review is expected to attract important interests from catalysis, separation, environment, advanced materials, and chemical engineering fields as well as biomedicine for artificial organ and drug delivery systems.