Removal of organics from water in an aeration basin : A mathematical model

A mathematical model was developed to describe the removal of volatile organic compounds from drinking water in aeration basins. The model was used to simulate removal under a range of expected treatment conditions using the Continuous Systems Modeling Program. Results indicated that temperature and air-to-water ratio are the major factors influencing the removal of chloroform from water in an aeration basin. Bubble diameter was a lesser factor while liquid residence time had the smallest effect of the variables examined.     

Cold water detergency studies using radiolabeled soils

The effects of single and multiple washing and of resoiling-rewashing of cotton and synthetic fabrics have been studied in Tergotometer tests at various levels of temperature, detergent concentration and water hardness. The soiling mixture consisted of a seven component sebum tagged with tritium and carbon-14; in some tests gammaray emitting Kaolinite clay was also used. Linear primary alcohol ethoxylate (LAEO) and linear alkylbenzene sulfonate (LAS) were used for surfactant type comparisons. In single wash tests in both hot and cold water, LAEO was generally more effective than LAS in removing sebum. This was particularly noticeable at low product concentration where insufficient sodium tripolyphosphate was present to sequester the water hardness. A 1/1 blend of the two surfactants approached LAEO in performance. The nonpolar sebum fraction was more readily removed from Dacron or nylon in cold water; otherwise, detergency was generally better at high temperatures. In rewash tests, using labeled lube oil, cholesterol and clay, a progressive increase in soil removal was found during five wash cycles. The nonpolar lube oil component was the most difficult to remove from permanent press Dacron-cotton (PP), but was more readily removed from cotton. The more polar cholesterol and especially the clay were more easily removed from PP. LAEO gave better detergency both hot and cold than LAS, especially in hard water. On cotton swatches resoiled with sebum after each wash the residual sebum content was still increasing after five cycles. With PP in soft water, a steady state was reached after three to five cycles. Soil buildup was greater as hardness increased and as wash temperature and active matter concentration decreased, and was generally greater on cotton than on PP. LAEO allowed appreciably less soil buildup than did LAS especially at low concentration in hard water, indicating a reduced requirement for sodium tripolyphosphate. Presented before the AOCS Meeting, New Orleans, April 1970.     

Formal Verification Successes at Motorola

Formal tools are either too labor intensive or are completely impractical for industrial-size problems. This paper describes two formal verification tools used within Motorola, Versys2 and CBV, that challenge this assertion. The two tools are being used in current design verification flows and have shown that it is possible to seamlessly integrate formal tools into existing design flows.     

Possible acception criteria for structure functions

This paper deals with the verification of thermal transient evaluation implementations. This subject is relevant because e.g. the upcoming standard will describe the thermal transient measurement as a standard method to estimate the junction-to-case thermal resistance [1], [2], thus anybody can create their own implementation of the evaluation method. We have to have a method to verify these implementations. For this reason we examined the result of the NID (Network Identification by Deconvolution) method from different aspects. For these examinations we defined a multilayer structure as a reference structure and we analytically expressed the unit-step response and the cumulative structure function of this structure. Using the unit-step response as an input data set for the implementation in question we got an approximation of the structure function. Analysing this and the reference RC network we could define a practical maximum tolerance for the deviation between the analytical and the calculated functions.     

Evaporated Te on CdTe: A vacuum-compatible approach to making back contact to CdTe solar cell devices

A commonly used process for forming low-resistance contacts to thin-film p-type CdTe involves the formation of a Te layer by etching the CdTe film in a concentrated mixture of nitric and phosphoric acids. The authors compare evaporated Te back contacts with ‘control’ back contacts formed by the usual etching process, and demonstrate that evaporating Te onto a CdTe thin film is a viable process for forming a low-resistance contact. The best efficiency achieved for a CdTe solar cell made with an evaporated Te back contact is 12.1%, whereas the efficiency of the device made with the control back contact was 11.9%. The evaporation process offers numerous advantages over acid etching, most notably vacuum compatibility amenable to large-scale production of CdTe solar cell modules.     

rGO Sheets/ZnFe2O4 Nanocomposities as an Efficient Electro Catalyst Material for I3−/I− Reaction for High Performance DSSCs

In this paper, Reduced Graphene Oxide (rGO)/ZnFe₂O₄ (rZnF) nanocomposite is synthesized by a simple hydrothermal method and employed as a counter electrode (CE) material for tri-iodide redox reactions in Dye sensitized solar cells (DSSC) to replace the traditional high cost platinum (Pt) CE. X-ray diffraction analysis and High resolution Transmission electron microscopy, clearly indicated the formation of rZnF nanocomposite and also amorphous rGO sheets were smoothly distributed on the surface of ZnFe₂O₄ (ZnF) nanostructure. The rZnF-50 CE shows excellent electro catalytic activity toward I₃^? reduction, which has simultaneously been confirmed by cyclic voltammetry, electrochemical impedance spectroscopy and Tafel polarization measurements. A DSSC developed by rZnF-50 CE (η?=?8.71%) obtained quite higher than the Pt (η?=?8.53%) based CE under the same condition. The superior performances of rZnF-50 CE due to addition of graphene in to Spinel (ZnF) nanostructure results in creation of highly active electrochemical sites, fast electron transport linkage between CE and electrolyte. Thus it’s a promising low cost CE material for DSSCs.

     

Toxicity to Daphnia magna and Vibrio fischeri of Kraft bleach plant effluents treated by catalytic wet-air oxidation

Two Kraft-pulp bleaching effluents from a sequence of treatments which include chlorine dioxide and caustic soda were treated by catalytic wet-air oxidation (CWAO) at T=463 K in trickle-bed and batch-recycle reactors packed with either TiO2 extrudates or Ru(3 wt%)/TiO2 catalyst. Chemical analyses (TOC removal, color, HPLC) and bioassays (48-h and 30-min acute toxicity tests using Daphnia magna and Vibrio fischeri, respectively) were used to get information about the toxicity impact of the starting effluents and of the treated solutions. Under the operating conditions, complex organic compounds are mostly oxidized into carbon dioxide and water, along with short-chain carboxylic acids. Bioassays were found as a complement to chemical analyses for ensuring the toxicological impact on the ecosystem. In spite of a large decrease of TOC, the solutions of end products were all more toxic to Daphnia magna than the starting effluents by factors ranging from 2 to 33. This observation is attributed to the synergistic effects of acetic acid and salts present in the solutions. On the other hand, toxicity reduction with respect to Vibrio fischeri was achieved: detoxification factors greater than unity were measured for end-product solutions treated in the presence of the Ru(3 wt%)/TiO2 catalyst, suggesting the absence of cumulative effect for this bacteria, or a lower sensitivity to the organic acids and salts. Bleach plant effluents treated by the CWAO process over the Ru/TiO2 catalyst were completely biodegradable.     

A data mining approach to process optimization without an explicit quality function

In process optimization, the setting of the process variables is usually determined by estimating a function that relates the quality to the process variables and then optimizing this estimated function. However, it is difficult to build an accurate function from process data in industrial settings because the process variables are correlated, outliers are included in the data, and the form of the functional relation between the quality and process variables may be unknown. A solution derived from an inaccurate function is normally far from being optimal. To overcome this problem, we use a data mining approach. First, a partial least squares model is used to reduce the dimensionality of the process and quality variables. Then the process settings that yield the best output are identified by sequentially partitioning the reduced process variable space using a rule induction method. The proposed method finds an optimal setting from historical data without constructing an explicit quality function. The proposed method is illustrated with two examples obtained from steel making processes. We also show, through simulation, that the proposed method gives more stable results than estimating an explicit function even when the form of the function is known in advance.