Study of the selective catalytic reduction of NOx on an efficient Fe/HBEA zeolite catalyst for heavy duty diesel engines

The present paper addresses the removal of NO_x from the exhaust of heavy duty vehicles using the SCR technique. The studies were conducted with a highly active H-BEA zeolite exhibiting a molar Si/Al ratio of 12.5 and a Fe load of 1.0 wt.% (1Fe/HBEA). The pronounced efficiency of 1Fe/HBEA is reflected by the apparent turnover frequency being superior to traditional V₂O₅/WO₃/TiO₂. The nature of the Fe sites was investigated with high resolution transmission electron microscopy (HRTEM), ⁵⁷Fe Mössbauer spectroscopy and powder X-ray diffraction (PXRD). In connection with previous examinations it is deduced that the iron sites represent octahedrally coordinated high spin Fe³⁺ cations. Furthermore, highly dispersed species, which are the most active sites, are supposed to be paramagnetic, while oligomeric and particulate structures indicate superparamagnetic behaviour.The practical evaluation of the 1Fe/HBEA catalyst was systematically carried out including laboratory studies of granulated powder and honeycomb samples as well as engine bench tests. For the latter studies a coated honeycomb prototype was employed showing very similar efficiency as referred to a commercial V₂O₅/WO₃/TiO₂ pattern.Furthermore, 1Fe/HBEA exhibits pronounced hydrothermal stability after aging at 550 °C which represents an elevated exhaust temperature of heavy duty vehicles. The aging caused no change in fast SCR, i.e. when a c(NO₂)/c(NO_x) ratio of 0.5 was used, and only minor decline in standard SCR. The slight aging effect is mainly referred to little decrease in BET surface area and NH₃ uptake, respectively. PXRD indicated maintenance of the BEA structure, whereas ²⁷Al nuclear magnetic resonance spectroscopy showed removal of some Al from the zeolite framework. Contrary, UV–vis spectroscopy evidenced no effect of hydrothermal aging on the composition of the Fe sites. Finally, the catalyst also maintained its efficiency after SO₂ aging at 300 °C. Diffuse reflectance infrared Fourier transform spectroscopic studies showed adsorption of molecular SO₂ on the zeolite substrate releasing already at about 400 °C.     

Cutting to the chase with warm-start contextual bandits

Knowledge and Information Systems - Multi-armed bandits achieve excellent long-term performance in practice and sublinear cumulative regret in theory. However, a real-world limitation of bandit...     

Carbon-Methanol Based Adsorption Heat Pumps: Identifying Accessible Parameter Space with Carbide-Derived Carbon Model Materials

In adsorption heat pumps, the properties of the porous adsorbent and the refrigerant determine the performance. Major parameters for this working pair are the total uptake of the adsorptive, its kinetics, and the heat transfer characteristics. In the technical application despite powdered adsorbents, thin consolidated layers of the adsorbent can be attractive and obtained by a binder-based approach but likely result in competing material properties. Thus, for a process optimization, the accessible parameter space and interdependencies have to be known and were deduced in this work for model porous carbons (carbide-derived carbons derived from TiC and ZrC) and methanol as well as the addition of different amounts of boron nitride, silver, and graphite as heat-conductive agents and the use of two binders.     

Calculating morphology development of polymer blends in extruders on the basis of results of boundary and finite element simulations using the sigma simulation software

Models have been developed for binary, incompatible polymer blends that can be used to estimate the morphology development that takes place in drops of the second component that are dispersely embedded in the matrix. The calculations are based on the results of flow simulations using the boundary element (BEM) and finite element (FEM) methods and, more particularly, on an analysis of the stresses that act on fluid particles over their trajectories as a function of the residence time. The models formulated are converted into algorithms, which can then be implemented in the SIGMA simulation software for designing and simulating the process behavior in tightly intermeshing co‐rotating twin‐screw extruders. In this way, it is possible to estimate the morphology development that takes place in incompatible polymer systems by describing the mean drop size and the drop size distribution as a function of the material properties, the geometry of the barrel and the screw, and the process parameters.     

Towards Keratan Sulfate – Chemoenzymatic Cascade Synthesis of Sulfated N‐Acetyllactosamine (LacNAc) Glycan Oligomers

We report on a novel chemoenzymatic cascade for the synthesis of sulfated N‐acetyllactosamine [(3Galβ1,4GlcNAcβ1,)_n, LacNAc] oligomer structures. Starting from a linker modified GlcNAc substrate di‐ and trisaccharides were first synthesized by sequential use of human β4‐galactosyltransferase‐1 (β4GalT‐1) and β3‐N‐acetylglucosaminyltransferase from Helicobacter pylori (β3GlcNAcT). Subsequent regioselective chemical sulfation rendered the C‐6 mono‐, di‐, and tri‐O‐sulfated products in good yields. Further enzymatic elongation by β4GalT‐1 and β3GlcNAcT in a sequential mode yielded 6‐O‐sulfated LacNAc oligomers up to hexasaccharide length with variable degrees of sulfation. These carbohydrate structures mimic the sulfation pattern found in keratan sulfate and are potential ligands for different classes of glycan binding proteins.

     

Development and Validation of a Novel 11-Gene Prognostic Model for Serous Ovarian Carcinomas Based on Lipid Metabolism Expression Profile

(1) Background: Biomarkers might play a significant role in predicting the clinical outcomes of patients with ovarian cancer. By analyzing lipid metabolism genes, future perspectives may be uncovered; (2) Methods: RNA-seq data for serous ovarian cancer were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The non-negative matrix factorization package in programming language R was used to classify molecular subtypes of lipid metabolism genes and the limma package in R was performed for functional enrichment analysis. Through lasso regression, we constructed a multi-gene prognosis model; (3) Results: Two molecular subtypes were obtained and an 11-gene signature was constructed (PI3, RGS, ADORA3, CH25H, CCDC80, PTGER3, MATK, KLRB1, CCL19, CXCL9 and CXCL10). Our prognostic model shows a good independent prognostic ability in ovarian cancer. In a nomogram, the predictive efficiency was notably superior to that of traditional clinical features. Related to known models in ovarian cancer with a comparable amount of genes, ours has the highest concordance index; (4) Conclusions: We propose an 11-gene signature prognosis prediction model based on lipid metabolism genes in serous ovarian cancer.