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• Functional groups are effective variables of machine learning for FTIR spectra. • OH is a key factor discriminating the samples because of deoxidation reactions. • Pre-integration of initial samples increases the classification effects of PCA. Three biomass (rice straw, rice husk and wheat straw) and three coal samples (lignite, subbituminous coal and bituminous coal) were extracted via a thermal dissolution (TD) process, and the TD extracts were treated by catalytic hydrogenation to obtain reaction products. To reveal the similarity in molecular information among the samples and elucidate their chemical reactivity, four machine learning algorithms were applied to analyze the Fourier transform infrared spectra of both TD extracts and catalytic hydrogenation products. Functional groups were used as variables and the difference in peak area can be treated as the basis for sample classification. Aromatic C H, C O C, aliphatic CH 2 or CH 3 and aromatic C O or C C bonds were the main characteristic variables in principal component analysis algorithm to classify biomass- and coal-derivated samples. These samples were also grouped into four clusters by hierarchical clustering analysis algorithm according to the similarity and difference in the distribution of functional groups. For artificial neural network algorithm, aliphatic C H and OH bonds are the most important variables to classify these samples into four groups, and aromatic C H, OH, and C O C groups are the main variables contributed to the classification trees in random forest algorithm. Machine learning algorithms will provide methodological guidance for the data mining of the spectra of complex organic systems. [ABSTRACT FROM AUTHOR]

Directly converting lignite into arenes as commodity chemicals and drop-in fuels is a highly desirable target for researchers. However, this is severely limited by the presence of stable inter unit C-O linkages in lignite. Herein, a highly active catalyst, Co-MoS 2 , has been designed and prepared to be used for the selective catalytic cleavage of inter unit C-O bridged bonds (BBs) in the conversion of Naomaohu (NMH), a lignite, to yield arenes. Both catalytic hydrogenation conversion (CHC) and thermal dissolution (a non-catalytic process, named NCHC) of NMH were conducted using n-hexane as the solvent. The soluble fractions from the first stage of NCHC (SF NCHC-1) and CHC (SF CHC-1), as well as the second stage of NCHC (SF NCHC-2) and CHC (SF CHC-2) were obtained using the same solvent. After the first-stage catalytic treatment, the relative contents of arenes and alkanes in SF CHC-1 increased by 16.7 % and 9.3 %, respectively, compared to those in SF NCHC-1 , and the relative content of oxygen-containing compounds (OCCs), such as alcohols, phenols, esters, ketones, acids, and furans, decreased by 13.2 %. For the second-stage conversion, the relative contents of arenes and alkanes in SF CHC-2 were 53.5 % and 15.5 % higher than those in SF NCHC-2 , and the relative contents of OCCs was only 6.6 % in SF CHC-2. The catalytic mechanisms of cleavage of C-O BBs and deoxygenation were proposed based on the CHC of model compounds and density functional theory (DFT) calculation. The adsorption of OCCs and the activation of released hydrogen radical (H·) by Co-MoS 2 , followed by H· addition to the carbon atom connected to oxygen in C-O BBs and oxygen-containing functional groups, are crucial for the cleavage of C-O BBs and formation of deoxygenated compounds, particularly arenes. • Co@MoS 2 selectively cleave C-O bridged bonds in lignite. • Co@MoS 2 is effective for hydrodeoxygenation and generation of arenes. • C ar -O cleavage mechanism was revealed by catalytic model compounds and DFT calculation. [ABSTRACT FROM AUTHOR]

[Display omitted] • Mesoporosity and hydrophobicity improve the reusability of the catalysts. • The balance of metal/acidic sites is critical for maximizing PCA yields. • Changes in metal/acid ratio had a greater effect on PCA yield in PP-ol than in ODB. • Partial hydrogenation of ODB is a necessary step before C-O bond cleavage. MY zeolites with mesopores were prepared by hydrothermal method using functionalized SiO 2 (F-SiO 2) as a silica source, and hydrophobic bifunctional Ru/MY- O catalysts were obtained by deposition precipitation method and silylation treatment. This work aims at obtaining polycyclic alkane (PCA) based high-density hydrocarbon fuels (HDHFs). We focused on the catalytic hydroconversion (CHC) of 2-phenoxy-1-phenylethanol (PP-ol) and oxydibenzene (ODB), two typical lignin-related model compounds (LRMCs), over Ru/MY- O. The effects of different reaction conditions and catalysts on the product distribution in PP-ol and ODB were investigated. The partial hydrogenation of ODB was found to be a necessary step before achieving C-O ether bond cleavage and C-C bond coupling. The balance of metal/acidic sites is critical for maximizing PCA yields. Changes in the metal/acid ratio had a greater effect on PCA yield in PP-ol than in ODB. Poor stability of cycloalkyl cations and partial hydrogenation of ODB hinder the generation of C-C coupling products. The incorporation of mesopores and hydrophobic treatment were found to weaken the negative effects of C-C bond coupling products and water on the catalyst. The conversion of Ru 3 /MY- O was improved by nearly 10% compared to Ru 3 /Y in the fifth cycle reaction. This work provided a theoretical basis for the generation of HDHFs from lignin. [ABSTRACT FROM AUTHOR]

[Display omitted] • Spectral stitching improves the detection ability towards minor and trace species. • Comprehensive molecular information and transfer behavior of O and N atoms are revealed. • Similarity and difference of samples are visually exhibited in PCA and HCA plots. The combination of mass spectrometry (MS) data and chemometrics methods is conducive to obtaining more comprehensive molecular information and evaluating the transfer behavior of O and N atoms during the conversion of biomass and coal. In this work, 12 thermal dissolution (TD) extracts of coal/biomass samples and the catalytic hydrogenation products of TD extracts were analyzed by Orbitrap MS using spectral stitching and in-source collision-activated dissociation (ISCAD) methods. Spectral stitching improves the detection ability towards minor and trace species, enhancing the number of identified compounds by two times. Meanwhile, ISCAD provides more comprehensive molecular structure information, which can illustrate the transfer patterns of heteroatoms and deepen the understanding of the structural characteristics of aromatic rings during the conversion of biomass and coal. Two chemometrics methods, principal component analysis (PCA) and hierarchical cluster analysis (HCA), were introduced to dig out the detailed similarities and differences between O-containing and N-containing compounds in coal and biomass. HCA method not only recognized the category of O-containing and N-containing compounds in each sample, but also showed the removal behavior of O and N atoms in biomass and coal. Thus, the combination of MS methods and chemometrics method is expected to provide methodological support to elucidate the molecular structure and conversion pathways for complex coal and biomass. [ABSTRACT FROM AUTHOR]