Adsorption of mercaptopropionic acid onto Au(1 1 1): Part II. Effect on copper electrodeposition

Copper deposition in the presence of an organic additive (3-mercaptopropionic acid, MPA) was studied by cyclic voltammetry and in situ scanning tunneling microscopy (STM) and the results are compared to those for additive-free solutions. It is shown that underpotential deposition (upd) of copper onto a fully MPA-covered electrode produces a defect-rich substrate, but the defects are blocked by the dense organic film for bulk deposition, resulting in a low number of nuclei. A grain-refining effect of MPA, however, was found, when Cu deposition was initiated shortly after addition of MPA to the solution, i.e., for a low-coverage MPA adlayer.     

Charakterisierung und Störstoffanalyse von rückgewonnenen Stoffströmen aus Wärmedämmverbundsystemen

Due to the growing energy requirements, the proportion of external thermal insulation composite systems (ETICS) installed has increased significantly during the past 50 years. Due to the longevity of these systems, ETICS waste is currently accumulating. Owing to the complex construction as well as a multitude of differently installed materials and substances of the past generations, there are many uncertainties and problems with the clean and low-pollutant processing of such systems. In the frame of this work, the ETICS were processed and sorted before being screened for ingredients or pollutants as well as for the purity of the recovered material fractions.     

Comparing Efficiency per Volume of Uniflow Cyclones and Standard Cyclones

A competitive alternative to the standard reverse flow cyclone for gas-solids separation is the uniflow cyclone. Gas and particles passing through it in only one direction, allowing a cost-effective usage in space limited applications. Comprehensive studies of uniflow cyclones have strongly improved their understanding and led to approved design criteria and calculation methods. Here it is shown that uniflow cyclones can achieve higher efficiencies per volume with a low pressure drop than standard cyclones.     

Aramid pulp treated with imidazolium ionic liquids as a filler in rigid polyurethane bio-foams

This article reports an aramid pulp (AP) treated with two ionic liquids (IL), namely 1-n-butyl-3-methylimidazolium chloride (C₄.Cl) and 1-carboxymethyl-3-methylimidazolium chloride (HO₂C), and its use as a filler in reinforced rigid polyurethane foams (RPUF). The RPUF were incorporated with the treated AP at three weight fractions (c.a. 0.1, 0.5, and 1.0 wt%) and were produced by the free rising method. The results showed that the studied IL promoted a better interaction between the AP and the RPUF system, which increased the overall reactivity, imparting a higher cell anisotropy. This also yielded a positive effect in mechanical properties and thermal stability of the RPUF. Compared to the neat RPUF, outstanding increases of approximately 50 and 20% were achieved in compressive modulus and strength, respectively. In all, the use of IL promoted increased compatibility between matrix and reinforcement, especially that HO₂C IL.     

Optimizing the ring-rolling operation with process control

To minimize costs in the manufacture of ring-shaped products, the ring-rolling process must be controlled efficiently. Toward this end, a recently developed control system allows nearly unattended operation of ring-rolling machines. The control system determines optimum preform geometry, thereby minimizing scrap; it also continuously monitors the process to adjust for deviations from set conditions. Various operations can be controlled, and process efficiency and quality are greatly improved.     

Selecting linear algebra kernel composition using response time prediction

Numerical linear algebra libraries provide many kernels that can be composed to perform complex computations. For a given computation, there is typically a large number of functionally equivalent kernel compositions. Some of these compositions achieve better response times than others for particular data and when executed on a particular computer architecture. Previous research provides methods to enumerate (a subset of) these kernel compositions. In this work, we study the problem of determining the composition that yields the lowest response time. Our approach is based on a response time prediction for each candidate combination. While this prediction could in principle be obtained using analytical and/or empirical performance models, developing accurate such models is known to be challenging. Instead, we define a feature space that captures salient properties of kernel combinations and predict response time using supervised machine learning. We experiment with a standard set of machine learning algorithms and identify an effective algorithm for our kernel composition selection problem. Using this algorithm, our approach widely outperforms the strategy that would consist in always using the simplest kernel composition and is often close to the fastest kernel compositions among those evaluated. We quantify the potential benefit of our approach if it were to be implemented as part of an interactive computational tool. We find that although the potential benefit is substantial, a limiting factor is the kernel composition enumeration overhead. Copyright © 2014 John Wiley & Sons, Ltd.     

Molecular interaction networks in the analyses of sequence variation and proteomics data

Protein–protein interaction networks are typically generated in standard cell lines or model organisms as it is prohibitively difficult to record large interaction datasets from specific tissues or disease models at a reasonable pace. Although the interaction data are of high confidence, they thus do not reflect in vivo relationships as such. A wealth of physiologically relevant protein information, obtained under different conditions and from different systems, is available including information on genetic variation, protein levels, and PTMs. However, these data are difficult to assess comprehensively because the relationships between the entities remain elusive from the measurements. Here, we exemplarily highlight recent studies that gained deeper insight from genetic variation, protein, and PTM measurements using interaction information pointing toward the importance and potential of interaction networks for the interpretation of sequencing and proteomics data.     

Fiber optic sensing technology for detecting gas hydrate formation and decomposition

A fiber optic-based distributed sensing system (DSS) has been integrated with a large volume (72 l) pressure vessel providing high spatial resolution, time-resolved, 3D measurement of hybrid temperature-strain (TS) values within experimental sediment-gas hydrate systems. Areas of gas hydrate formation (exothermic) and decomposition (endothermic) can be characterized through this proxy by time series analysis of discrete data points collected along the length of optical fibers placed within a sediment system. Data are visualized as an animation of TS values along the length of each fiber over time. Experiments conducted in the Seafloor Process Simulator at Oak Ridge National Laboratory clearly indicate hydrate formation and dissociation events at expected pressure-temperature conditions given the thermodynamics of the CH(4)-H(2)O system. The high spatial resolution achieved with fiber optic technology makes the DSS a useful tool for visualizing time-resolved formation and dissociation of gas hydrates in large-scale sediment experiments.     

Zeolite based trace humidity sensor for high temperature applications in hydrogen atmosphere

We present a humidity sensor based on H-ZSM-5 type zeolite that is suitable to detect traces of humidity (10–110 ppm_V) under harsh conditions, e.g. reducing atmosphere (H₂) and high temperature (up to 600 °C). By means of complex impedance spectroscopy (IS) we show that the zeolite sensor responds linearly towards minimal changes in humidity. Therefore this result indicates that the zeolite sensor is capable to detect traces of humidity in processes where high temperatures in a hydrogen environment are required.