RAPID AND FACILE SYNTHESIS OF ACYL AZIDES FROM ACYL HALIDES USING A POLYMER-SUPPORTED AZIDE ION UNDER HETEROGENEOUS CONDITIONS

In this article a rapid and facile method for synthesis of acyl azide is described. The cross-linked poly（N-methyl-4- vinylpyridinium） azide ion, [Pa-VP]N3 is prepared and used as an efficient polymeric reagent for synthesis of acyl azides from acyl halides at room temperature under heterogeneous conditions. Various benzoyl halides, with electron-withdrawing groups as well as electron-donating groups, were transformed into the corresponding benzoyl azides in high to excellent yields in short reaction times. The acyl azide products were characterized by FT-IR, and some of them were also characterized by IH- and/or 13C-NMR spectroscopy, and physical properties were compared to literature values of known compounds. The spent polymeric reagents can be regenerated and reused for several times without losing their activity. Relative to the reported methods, the present method has the advantages of operational simplicity, mild reaction conditions, fast reaction rates, simple reaction work-up and lower hazardous and potentially explosive nature. Also the present method is the first procedure for the synthesis of acyl azides from acyl halides by using a polymer-supported azide ion under heterogeneous conditions.

Landslide susceptibility prediction using slope unit-based machine learning models considering the heterogeneity of conditioning factors

To perform landslide susceptibility prediction(LSP),it is important to select appropriate mapping unit and landslide-related conditioning factors.The efficient and automatic multi-scale segmentation(MSS)method proposed by the authors promotes the application of slope units.However,LSP modeling based on these slope units has not been performed.Moreover,the heterogeneity of conditioning factors in slope units is neglected,leading to incomplete input variables of LSP modeling.In this study,the slope units extracted by the MSS method are used to construct LSP modeling,and the heterogeneity of conditioning factors is represented by the internal variations of conditioning factors within slope unit using the descriptive statistics features of mean,standard deviation and range.Thus,slope units-based machine learning models considering internal variations of conditioning factors(variant slope-machine learning)are proposed.The Chongyi County is selected as the case study and is divided into 53,055 slope units.Fifteen original slope unit-based conditioning factors are expanded to 38 slope unit-based conditioning factors through considering their internal variations.Random forest(RF)and multi-layer perceptron(MLP)machine learning models are used to construct variant Slope-RF and Slope-MLP models.Meanwhile,the Slope-RF and Slope-MLP models without considering the internal variations of conditioning factors,and conventional grid units-based machine learning(Grid-RF and MLP)models are built for comparisons through the LSP performance assessments.Results show that the variant Slopemachine learning models have higher LSP performances than Slope-machine learning models;LSP results of variant Slope-machine learning models have stronger directivity and practical application than Grid-machine learning models.It is concluded that slope units extracted by MSS method can be appropriate for LSP modeling,and the heterogeneity of conditioning factors within slope units can more comprehensively reflect the relationships between conditioning factors and landslides.The research results have important reference significance for land use and landslide prevention.

Matching Boundary Conditions for a Heterogeneous Atomic Chain

We propose accurate boundary treatments for a heterogeneous atomic chain, in terms of matching boundary conditions （MBCs）. The main challenge lies in reproducing the physical reflection across the boundary to a correct amount. With reflection coefficients we demonstrate that the accuracy is improved when more atoms are used under the boundary condition. The inclusion of an atom in the embedded sublattice B may considerably enhance the performance. Numerical testing illustrates the effectiveness of the proposed MBCs.

Regioselective tetrahydropyranylation of alcohols catalyzed by Fe(HSO_4)_3

Alcohols are selectively and efficiently protected as their tetrahydropranyl ethers in the presence of a catalytic amount of Fe（HSO4）3 in good to high yields. All reactions are performed under mild and completely heterogeneous reaction conditions.

Silica sulfuric acid:A versatile reagent for oxathioacetalyzation of carbonyl compounds and deprotection of 1,3-oxathiolanes

Oxathioacetalyzation of carbonyl compounds with 2-mercaptoethanol and deprotection of the obtained 1,3-oxathiolanes is easily performed in the presence of silica sulfuric acid （SSA）. All reactions were performed under mild and completely heterogeneous reaction conditions in good to high yields.

A mild and efficient method for the methoxymethylation and acetylation of alcohols promoted by benzyltriphenylphosphonium tribromide

A mild and efficient method for the conversion of alcohols to their corresponding methoxymethyl ethers and acetates using benzyltriphenylphosphonium tribromide （BTPTB） as catalyst is described. All reactions were performed under completely heterogeneous reaction conditions in good to high yields.

Nanocrystalline TiO_2 as an efficient and reusable catalyst for the chemoselective trimethylsilylation of primary and secondary alcohols and phenols

Nanocrystalline TiO_2 was used as an efficient and recyclable catalyst for the chemoselective trimethylsilylation of primary and less hindered secondary alcohols and phenols with hexamethyldisilazane（HMDS）.All reactions were performed under mild and completely heterogeneous conditions in good to excellent yields.

An efficient method for synthesis of acylals from aldehydes using multi-walled carbon nanotubes functionalized with phosphonic acid(MWCNTs-C-PO_3H_2)

MWCNTs-C-PO3H2has been used as an efficient,heterogeneous and reusable nanocatalyst for synthesis of acylals from aldehydes under solvent-free conditions at room temperature.A wide range of aldehydes was studied and corresponding products were obtained in good to excellent yields in short reaction times.Nanocatalyst can be easily recovered by centrifuge and reused for subsequent reactions for at least five times without deterioration in catalytic activity.The major advantages of the present method are high yields,short reaction time,recyclable catalyst and solvent-free reaction conditions at room temperature.