Prediction of Flooding in Packed Liquid-Liquid and High-Pressure Extraction Columns Using a Gaussian Process

Reliable prediction of flooding conditions is needed for sizing and operating packed extraction columns. Due to the complex interplay of physicochemical properties, operational parameters and the packing-specific properties, it is challenging to develop accurate semi-empirical or rigorous models with a high validity range. State of the art models may therefore fail to predict flooding accurately. To overcome this problem, a data-driven model based on Gaussian processes is developed to predict flooding for packed liquid-liquid and high-pressure extraction columns. The optimized Gaussian process for the liquid-liquid extraction column results in an average absolute relative error (AARE) of 15.23 %, whereas the algorithm for the high-pressure extraction column results in an AARE of 13.68 %. Both algorithms can predict flooding curves for different packing geometries and chemical systems precisely.     

Investigation of the action of flame retardants in cellulose. I. Investigation of the flame retardant action of 2,2′-oxybis(5,5-dimethyl-1,3,2-dioxaphosphorinane-2,2′-disulfide) in cellulose

Pyrolysis experiments were performed in high vacuum and under reduced air pressure (100 Pa). The volatile products of pure cellulose and cellulose containing various amounts of flame retardant 2,2′-oxybis (5,5-dimethyl-1,3,2-dioxaphosphorinane-2,2′-disulfide), i.e., Sandoflam 5060 of Sandoz AG, were studied by means of gas chromatography in combination with mass spectroscopy. The volatile products were characterized with infrared spectroscopy. The studied revealed that the incorporation of the flame retardant enhanced the water release and shifted the onset of this reaction to lower temperature. On the basis of these findings an explanation for the mechanism of flame retardancy in generated cellulose fibers modified with this particular flame retardant is attempted. From experiments with different residual air pressure the influence of oxygen on the primary processes of the pyrolytic degradation of cellulose is being discussed.     

Is there a direct relationship between oral astringency and human salivary protein binding?

For decades, it is believed that astringency is due to the polyphenol-induced complexation of proline-rich salivary proteins in the oral cavity. In order to compare for the first time the human sensory threshold concentrations and the salivary protein binding activity of a series of astringent stimuli, human saliva protein was incubated for 5 min at 37 °C in the presence of astringent food-derived compounds and, after micro-centrifugation, the amount of the target molecules in the supernatant was quantitatively determined by HPLC-UV/Vis. Significant protein binding was observed for (−)-epigallocatechin-3-gallate, (−)-gallocatechin-3-gallate, (+)-gallocatechin, and (−)-catechin-3-gallate, all of which containing at least one galloyl moiety in the molecule and exhibiting rather high sensory thresholds of more than 200 μmol/L. In comparison, (+)-catechin and procyanidin B2, both lacking in any galloyl function, showed only comparatively low binding activity and, most interestingly, quercetin-3-O-α-l-rhamnopyranosyl-(1 → 6)-β-d-glucopyranoside and 3-carboxymethyl-indole-1-N-β-d-glucopyranoside did not show any protein binding at all, although the later N- and O-glycosides exhibited extraordinarily low sensory threshold concentrations of less than 0.001 and 0.0003 μmol/L, respectively. The data give some first evidence that the quantity of the non-bound, “free” astringent stimulus in the saliva liquid might be more closely related to the sensory perception of astringency than the amount complexed or precipitated by proteins. It is therefore questionable as to whether oral perception of astringency is related to the complexation and/or precipitation of salivary proteins.     

Influence of Reaction Parameters on the Hydrogenolysis of Hydroxymatairesinol Over Carbon Nanofibre Supported Palladium Catalysts

The density functional theory (DFT/B3LYP) calculations were applied to investigate the interaction of a Pt₆ particle with the ZSM-5 zeolite framework. The electronic structure of the metal particle is strongly affected by the interaction with basic framework oxygens and acid sites of the zeolite support. Adsorption on basic sites (E_ads = 6 kcal/mol) favors the formation of the electron enriched metal cluster. Interaction of the platinum cluster with the acid site characterized by stabilization energy of 47 kcal/mol results in oxidation of the metal particle and suppression of Brønsted acidity of the support. The hypothesis is put forward that the oxidized platinum particle can function as an active site for the alkane isomerisation on platinum supported high silica zeolites.     

Slip Control System for a Deep-Sea Mining Machine

Tracked vehicles capable of locomotion in the deep sea are used for manganese nodule mining. This requires specific technical solutions in various respects. Locomotion in the soft sea bed is one of them. For the Crawler to safely maneuver, an automatic drive mode with slip control of the driving tracks is essential. Based on experimental studies at IKS, University of Siegen, slip control for the NIOT-IKS mining machine has been developed and implemented. The experimental setup for the development of the slip control along with the logic of the automatic driving mode is described. The system is critically discussed and the test results and future work are briefly outlined. Note to Practitioners-The work is carried out as part of the polymetallic nodule mining program of the Government of India. The technique of slip control is a specific requirement for a tracked vehicle used in the deep sea. Slip is common in many vehicles-tracked and otherwise. Examples are steam engines in the early days and ordinary cars while negotiating slush or snow/ice and dozers working in soft soil. While these are manually controlled by drivers who have firsthand knowledge of the environmental conditions, in the case of a mining machine in deep sea, it has to be completely automatic and, hence, is challenging. The knowledge generated in this work could be effectively used by practitioners in other related areas of automobile engineering for updating their expertise. Also, similar techniques may be used for maneuvering vehicles sent to other planets     

Pruning Algorithms for Rule Learning

Pre-pruning and Post-pruning are two standard techniques for handling noise in decision tree learning. Pre-pruning deals with noise during learning, while post-pruning addresses this problem after an overfitting theory has been learned. We first review several adaptations of pre- and post-pruning techniques for separate-and-conquer rule learning algorithms and discuss some fundamental problems. The primary goal of this paper is to show how to solve these problems with two new algorithms that combine and integrate pre- and post-pruning.