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1.
In recent years, nanobubble technologies have drawn great attention due to their wide applications in many fields of science and technology. From previous studies, a kind of honeycomb structure for high efficiency nanobubble generation has been proposed. In this paper, the numerical simulations of bubbly flow in the honeycomb structure were performed by using a computational fluid dynamics–population balance model (CFD-PBM) coupled model. The numerical model was based on the Eulerian multiphase model and the population balance model (PBM) was used to calculate the bubble size distribution. The bubble size distributions in the honeycomb structure under different work conditions were predicted. Two different drag force models (Schiller-Naumann model and Tomiyama model) and two different aggregation models (Luo model and turbulent aggregation model) were investigated. Both two drag models gave similar prediction of bubble number density distribution at the outlet. The results obtained from Luo model had better reflection of the trend of number density distribution. The turbulence dissipation rate ε can be used to evaluate the nanobubble generating ability. The water tank was not included in the CFD model in this work. The bubbles in the water tank should be studied in the future.  相似文献   
2.
Journal of Radioanalytical and Nuclear Chemistry - The extraction chromatography experiments for Am(III) and Cm(III) recovery from genuine HLLW were carried out in order to demonstrate modified 2...  相似文献   
3.
Various types of α-arylpropionic acid esters were effectively obtained by the coupling reaction of aryl Grignard reagents and α-bromopropionic acid esters in the presence of nickel catalysts. α-Arylpropionitriles, precursors of α-arylpropionic acids, were also synthesized by the reaction of α-methanesulfonyloxypropionitrile and arylcopper reagents prepared from equimolar amount of arylmagnesium halides and copper(I) bromide.  相似文献   
4.
We give an explicit formula for the first non-trivial boundary map of the Akin–Buchsbaum–Weyman resolution (Schur functors and Schur complexes, Adv. Math 1982;44:207-278). The role of the Laplace expansion formula is emphasized.  相似文献   
5.
Principal component analysis (PCA) and other multivariate analysis methods have been used increasingly to analyse and understand depth‐profiles in XPS, AES and SIMS. For large images or three‐dimensional (3D) imaging depth‐profiles, PCA has been difficult to apply until now simply because of the size of the matrices of data involved. In a recent paper, we described two algorithms, random vector 1 (RV1) and random vector 2 (RV2), that improve the speed of PCA and allow datasets of unlimited size, respectively. In this paper, we now apply the RV2 algorithm to perform PCA on full 3D time‐of‐flight SIMS data for the first time without subsampling. The dataset we process in this way is a 128 × 128 pixel depth‐profile of 120 layers, each voxel having a 70 439 value mass spectrum associated with it. This forms over a terabyte of data when uncompressed and took 27 h to process using the RV2 algorithm using a conventional windows desktop personal computer (PC). While full PCA (e.g. using RV2) is to be preferred for final reports or publications, a much more rapid method is needed during analysis sessions to inform decisions on the next analytical step. We have therefore implemented the RV1 algorithm on a PC having a graphical processor unit (GPU) card containing 2880 individual processor cores. This increases the speed of calculation by a factor of around 4.1 compared with what is possible using a fast commercially available desktop PC having central processing units alone, and full PCA is performed in less than 7 s. The size of the dataset that can be processed in this way is limited by the size of the memory on the GPU card. This is typically sufficient for two‐dimensional images but not 3D depth‐profiles without sampling. We have therefore examined efficient sampling schemes that allow a good approximate solution to the PCA problem for large 3D datasets. We find that low‐discrepancy series such as Sobol series sampling gives more rapid convergence than random sampling, and we recommend such methods for routine use. Using the GPU and low‐discrepancy series together, we anticipate that any time‐of‐flight SIMS dataset, of whatever size, can be efficiently and accurately processed into PCA components in a maximum of around 10 s using a commercial PC with a widely available GPU card, although the longer RV2 approach is still to be preferred for the presentation of final results, such as in published papers. Copyright © 2016 The Authors Surface and Interface Analysis Published by John Wiley & Sons Ltd  相似文献   
6.
7.
Principal component analysis (PCA) and other multivariate analysis methods have been used increasingly to analyse and understand depth profiles in X‐ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES) and secondary ion mass spectrometry (SIMS). These methods have proved equally useful in fundamental studies as in applied work where speed of interpretation is very valuable. Until now these methods have been difficult to apply to very large datasets such as spectra associated with 2D images or 3D depth‐profiles. Existing algorithms for computing PCA matrices have been either too slow or demanded more memory than is available on desktop PCs. This often forces analysts to ‘bin’ spectra on much more coarse a grid than they would like, perhaps even to unity mass bins even though much higher resolution is available, or select only part of an image for PCA analysis, even though PCA of the full data would be preferred. We apply the new ‘random vectors’ method of singular value decomposition proposed by Halko and co‐authors to time‐of‐flight (ToF)SIMS data for the first time. This increases the speed of calculation by a factor of several hundred, making PCA of these datasets practical on desktop PCs for the first time. For large images or 3D depth profiles we have implemented a version of this algorithm which minimises memory needs, so that even datasets too large to store in memory can be processed into PCA results on an ordinary PC with a few gigabytes of memory in a few hours. We present results from ToFSIMS imaging of a citrate crystal and a basalt rock sample, the largest of which is 134GB in file size corresponding to 67 111 mass values at each of 512 × 512 pixels. This was processed into 100 PCA components in six hours on a conventional Windows desktop PC. © 2015 The Authors. Surface and Interface Analysis published by John Wiley & Sons Ltd.  相似文献   
8.
We found that three isomers of mono-Ru substituted Keggin-type germanotungstate with a dmso ligand, [GeW11O39RuII(dmso)]6?, could be formed by a reaction of α-Keggin-type mono-lacunary germanotungstate, [α-GeW11O39]8?, with Ru(dmso)4Cl2. The main isomer is an α-isomer, and the others are β2-isomer and β3-isomer, which were confirmed by 1H NMR, cyclic voltammetry, IR, and single crystal X-ray structure analysis.  相似文献   
9.
Using a modified method developed from Vonk's method, detailed values of crystallinity and crystal disorder were obtained by wide angle X-ray diffraction (WAXD). In Vonk's method, the crystallinity (w) is determined by extrapolation of the WAXD experimental curve back to zero scattering angle, while the distortion factor (k) is determined by the inclination of the experimental curve at zero scattering angle. In our new method, both w and k are determined at the same time by using the least squares method. In order to show the efficiency of our method, the new fitting procedure was applied to the experimental values of polyethylene and polyethylene terephthalate as measured by Vonk, and the values of w and k determined by our new method were compared with those found by Vonk's method. The new fitting method has the advantage that it uses the whole experimental curve. Moreover, our modified Vonk's method enables us to discuss crystal distortions as arising from first-kind (thermal) disorder and second-kind (paracrystalline) disorder.  相似文献   
10.
The cathepsin B inhibitor surugamide B ( 2 ), along with structurally related derivatives (A and C–E), has previously been isolated from the marine actinomycete Streptomyces sp. JAMM992. The biosynthetic genes are unexpectedly part of a cluster of four non‐ribosomal peptide synthetase (NRPS) genes, two of which are responsible for the biosynthesis of the additional linear decapeptide surugamide F. However, the thioesterase domain required for the later stage of the biosynthesis of the cyclic peptides surugamides A–E is not present in any module architecture of the surugamide NRPSs. Herein, we report the first total synthesis of surugamide B ( 2 ) through the macrocyclization at the biomimetic position, which not only alleviated the Cα epimerization in the macrolactamization process, but also efficiently provided 2 in 34 % yield for 18 steps. Furthermore, both the chemical and enzymatic studies with the biosynthetic precursor mimics revealed that the stand‐alone enzyme SurE, which belongs to the penicillin‐binding protein family, is responsible for macrocyclization of the tethered octapeptidyl intermediate.  相似文献   
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