Evaluation Of Catalytic Hydrogenation Of Coal And Biomass Based On Chemometrics

Three kinds of coal:Ningdong lignite（ND）,Ekuang sub-bituminous coal（EK）,Shanxi bituminous coal（SX）and three kinds of biomass:rice stalk（DG）,rice husk（DK）and wheat stalk（MG）are selected as research samples.All the research samples were sequentially thermal dissolved with n-hexane and methanol solvent at 300°C to obtain thermal dissolution samples（TDs）,the TDs were subjected to catalytic hydrotreation conversion with Ni/HZSM-5catalyst to obtain catalytic hydrogenation products（CATAs）.Fourier transform infrared spectroscopy（FTIR）and orbitrap mass spectrometry（Orbitrap MS）were applied to detect 12TDs and 12 CATAs.Four chemometrics methods:principal component analysis（PCA）,hierarchical clustering analysis（HCA）,artificial neural network（ANN）,random forest（RF）algorithm were used to explore the similarities and differences between different samples,evaluate the influence of catalysts on the molecular composition and structural characteristics of organic matter in coal and biomass.The functional group information of 24 samples were obtained using FTIR analysis.The main absorption peaks were distributed in six similar regions,corresponding to functional groups:-OH,aliphatic C-H,C=O or C=C,-CH₂ or-CH₃,C-O-C and aromatic C-H.PCA,HCA,ANN and RF were used to analyze the FTIR data of 24 samples.The 24 samples were divided into four classes:TD-coal,CATA-coal,TD-biomass and CATA-biomass,PCA method showed they were distinguished successfully,and aromatics CH,C-O-C,aliphatic-CH₂ and-CH₃ and aromatics C=O or C=C are the main characteristic variables for separating samples.HCA analysis found that 24 samples were cluster to four classes according to the similarities and differences of samples in functional groups,TDs contain more aromatic C-H,C=C or C=O,-CH₂ or-CH₃ and C-O-C,CATAs contain more aliphatic C-H and-OH,indicated that catalyst destroyed the aromatic structure and C-O bonds in TDs of coal and biomass.Samples were divided into training set and test set for ANN and RF analysis.The results showed that samples in the training set were successfully divided into four classes,TD-coal,CATA-coal,TD-biomass and CATA-biomass.The main characteristic variables were identified as aliphatic C-H,-OH and C-O-C,and the classification accuracy of the two models were about 50%.For Orbitrap MS,spectral-stitching and in-source collision activated dissociation were applied to obtain more detailed molecular composition information about coal and biomass samples.For spectral-stitching mode,the measured compounds of 24 samples were divided into CH,O,N and S classes.PCA method showed that 24 samples were separated successfully,and TDs contain more O₃,O₄,O₅,O₆ and N₄ classes compounds,CATAs contain more CH,O₁,N₁and N₂ classes compounds,revealed the hydrogenation and deheteroatom effect of catalyst.HCA analysis showed that 24 samples were cluster to five classes according to the characteristic of O class compounds and four classes according to the characteristic of N class compounds,revealed the diversity between TDs and CATAs.ANN and RF methods also successfully classified the samples,and identified the characteristic variables.The classification accuracy of two models were about 50%.For in-source collision activated dissociation mode,the main compounds attribute to CH,O,N,and ON classes.With the collision energy from 0 to 100 e V,compounds for all molecular structure convert into aromatic nucleus structure.The results of PCA and HCA ananlysis showed that TDs and CATAs were distinguished according to the difference and similarity of O class and N class compounds,the samples mainly contained O₁,O₂ and N₁ classes compounds at 100 e V,and the catalyst removed the heteroatoms on the aromatic nucleus.The combination of various chemometrics methods and data acquisition modes provides a reliable basis for studying the molecular composition of coal and biomass and the hydroconversion of catalysts.There are 41 figures,20 tables and 107 references in this thesis.