"Synergistic effect" is prevalent in natural metalloenzymes in activating small molecules, and the success has inspired the development of artificial catalysts capable of unprecedented organic transformations. In this work, we found that the attractive π-π interaction between organic additives (as electron-donors) and the perfluorinated arenes (as electron acceptors) is effective in gold hydride catalyzed activation of C-F bonds, specifically hydrodefluorination (HDF) of perfluoroarenes catalyzed by the Sadighi's gold hydrides [(NHC)AuH] (NHC = N-heterocyclic carbene). Although a weak interaction between [(NHC)AuH] and perfluoroarenes was observed from (1)H NMR and UV-vis spectroscopies, low reactivity of [(NHC)AuH] toward HDF was found. In contrast, in the presence of p-N,N-dimethylaminopyridine (DMAP), the HDF of perfluoroarenes with silanes can be efficiently catalyzed by [(NHC)AuH], resulting in mainly the para-hydrodefluorinated products with up to 90% yield and 9 turnovers. The yield of the reaction increases with the more electron-withdrawing groups and degree of fluorination on the arenes, and the HDF reaction also tolerates different function groups (such as formyl, alkynyl, ketone, ester, and carboxylate groups), without reduction or hydrogenation of these function groups. To reveal the role of DMAP in the reactions, the possible π-π interaction between DMAP and perfluoroarenes was suggested by UV-vis spectral titrations, (1)H NMR spectroscopic studies, and DFT calculations. Moreover, (1)H and (19)F-NMR studies show that this π-π interaction promotes hydrogen transfer from [(NHC)AuH] to pyridyl N atom, resulting in C-F bond cleavage. The interpretation of π-π interaction assisted C-F activation is supported by the reduced activation barriers in the presence of DMAP (31.6 kcal/mol) than that in the absence of DMAP (40.8 kcal/mol) for this reaction. An analysis of the charge distribution and transition state geometries indicate that this HDF process is controlled by the π-π interaction between DMAP and perfluoroarenes, accompanied with the changes of partial atomic charges.

We report the first example of gold catalyzing CF bond activation for perfluoroarenes in the presence of silanes. Tricoordinated gold(I) complexes supported by Xantphos‐type ligands, such as Xantphos and tBuXantphos ligands, exhibit efficacy in the hydrodefluorination (HDF) of various types of perfluoroarenes. For [tBuXantphosAu(AuCl2)], the highest turnover number is up to 1000 in the HDF of pentafluoronitrobenzene with diphenylsilane. An examination of functional group tolerance shows the orthogonality of this gold(I) catalytic protocol to ketone, ester, carboxylate, alkynyl, alkenyl and amide groups, suggesting its potential application in chemoselective CF activations. Mechanistic studies show that the equilibrium between tetracoordinated [L2Au]+ and [LAu]+ is important for the reactivity of gold catalysts, which is dependent on the sterically bulky group of Xantphos‐type ligands. Furthermore, computational studies for the possible reaction pathways suggest that direct oxidative addition of CF bonds by gold(I) cation might be the key step during these catalytic reactions.

The objective of this study was to identify the areas that are most susceptible to landslide occurrence, and to find the key factors associated with landslides along Jinsha River and its tributaries close to Derong and Deqin County. Thirteen influencing factors, including (a) lithology, (b) slope angle, (c) slope aspect, (d) TWI, (e) curvature, (f) SPI, (g) STI, (h) topographic relief, (i) rainfall, (j) vegetation, (k) NDVI, (l) distance-to-river, (m) and distance-to-fault, were selected as the landslide conditioning factors in landslide susceptibility mapping. These factors were mainly obtained from the field survey, digital elevation model (DEM), and Landsat 4–5 imagery using ArcGIS software. A total of 40 landslides were identified in the study area from field survey and aerial photos’ interpretation. First, the frequency ratio (FR) method was used to clarify the relationship between the landslide occurrence and the influencing factors. Then, the principal component analysis (PCA) was used to eliminate multiple collinearities between the 13 influencing factors and to reduce the dimension of the influencing factors. Subsequently, the factors that were reselected using the PCA were introduced into the logistic regression analysis to produce the landslide susceptibility map. Finally, the receiver operating characteristic (ROC) curve was used to evaluate the accuracy of the logistic regression analysis model. The landslide susceptibility map was divided into the following five classes: very low, low, moderate, high, and very high. The results showed that the ratios of the areas of the five susceptibility classes were 23.14%, 22.49%, 18.00%, 19.08%, and 17.28%, respectively. And the prediction accuracy of the model was 83.4%. The results were also compared with the FR method (79.9%) and the AHP method (76.9%), which meant that the susceptibility model was reasonable. Finally, the key factors of the landslide occurrence were determined based on the above results. Consequently, this study could serve as an effective guide for further land use planning and for the implementation of development.

Molecular dynamics (MD) simulations using a reactive force field (ReaxFF) method for a Green River oil shale model demonstrate that the thermal decomposition of the oil shale molecule is initiated with the cleavage of the oxygen bridge (C–O bond), and the first product is formaldehyde (CH2O). The simulation results show that the C–O bond is weaker than the other bonds, agreeing with its smaller bond dissociation energy (BDE). The ring-opening position of the aliphatic ring is usually determined by the stability of free radicals formed in this process. For aromatic hydrocarbons, the long-chain substituents are found to be easier to leave and the cleavage of C–C bonds leads to a series of chain reactions and the formation of small fragments, such as ethylene and propylene. The bond cleavages are almost in accordance with the minimum bonding energy rule. NVT simulations show that the pyrolysis process progresses in two stages: the decomposition of kerogen into heavy (C40+) species and then the generation of light compounds. Recombinations and rearrangements of different fragments are also observed via MD simulations. The main hydrocarbon fragments of C10–C20 are regarded as the component or precursor of diesel oil. The formation pathways of typical aromatic components are analyzed by tracking the motion trajectories of relevant structures. The intermediates and products in MD simulations are found to be similar to the gas chromatography–mass spectrometry (GC–MS) results from previous experiments.

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