DECHEMA

About: DECHEMA is a nonprofit organization based out in Frankfurt am Main, Germany. It is known for research contribution in the topics: Corrosion & Oxide. The organization has 756 authors who have published 1307 publications receiving 25693 citations.

Influence of surface inhomogeneities of boron doped CVD-diamond electrodes on reversible charge transfer reactions

Abstract: The electrochemical behaviour of reversible charge transfer reactions on boron doped diamond (BDD) was studied by cyclic voltammetry and electrochemical impedance spectroscopy using rotating disc electrodes under defined convection. Diamond films of 5 μm thickness with doping levels of 200, 3000 and 6000 ppm were prepared by hot filament chemical vapour deposition on niobium substrate. The electrochemical measurements were carried out on BDD electrodes in deaerated 0.5 M Na2SO4 + 5 mM K3[Fe(CN)6]/K4[Fe(CN)6] solution at rotation frequencies 0 < frot < 4000 rpm. Comparative measurements were carried out on an active Pt electrode. The BDD electrodes exhibit distinct irreversibilities indicated by a larger peak potential difference in the cyclic voltammograms, lower diffusion limiting current densities and an additional impedance element at high frequencies. Mechanical polishing with carbon fleece and SiC paper strongly affects the irreversible behaviour of the BDD electrodes. The experimental results are explained by a partial blocking of the diamond surface with reversible charge transfer at active sites. The impedance spectra are analysed quantitatively using a transport impedance model for reversible reactions on partially blocked electrode surfaces.

Reactive plasma immersion ion implantation for surface passivation

Abstract: Plasma immersion ion implantation (PIII) using halogen or oxygen plasmas has been employed for the surface passivation of advanced alloys with a view to their applications for high-temperature oxidation protection and in medicine. Special devices have been designed to ensure efficient plasma generation and reduce sample contamination arising from the interaction of the aggressive plasmas with the chamber components under bias. The paper addresses two main applications of PIII, namely oxidation protection of gamma-titanium aluminides (γ-TiAl), and modification of the surface properties of shape-memory superelastic nickel–titanium (NiTi) alloys. TiAl intermetallics are of great interest for advanced automobile, aerospace and power generation applications due to their low specific weight and high strength. However, excessive oxidation occurring in these materials at temperatures above 700 °C has hindered their widespread use. Samples of technical γ-TiAl alloys have been treated by both beamline implantation of Cl or F, and PIII of Cl using an Ar/Cl gaseous blend or alternative precursor gases. High-temperature oxidation behavior has been examined under conditions of either isothermal or thermocyclic oxidation at 900 °C. Optimized implantation processing produces marked improvement in the oxidation behavior of the γ-TiAl samples. On the basis of these results, a commercially viable process for enhancing the high-temperature oxidation resistance of γ-TiAl alloys using PIII of halogens is being developed. NiTi alloys are promising materials for use in biomedicine, provided that the release of Ni ions into the body environment can be sufficiently reduced. Oxygen PIII at substrate temperatures below 250 °C results in the formation of a transparent rutile TiO2 surface layer with a Ni content down to below 1 at.%. This layer in turn serves as a barrier to the corrosion and out-diffusion of Ni ions. Biocompatibility tests show superior in vitro blood compatibility in comparison with untreated NiTi samples.

SysBioMed report: Advancing systems biology for medical applications

Abstract: The following report selects and summarises some of the conclusions and recommendations generated throughout a series of workshops and discussions that have lead to the publication of the Science Policy Briefing (SPB) Nr. 35, published by the European Science Foundation. (Large parts of the present text are directly based on the ESF SPB. Detailed recommendations with regard to specific application areas are not given here but can be found in the SPB. Issues related to mathematical modelling, including training and the need for an infrastructure supporting modelling are discussed in greater detail in the present text.)The numerous reports and publications about the advances within the rapidly growing field of systems biology have led to a plethora of alternative definitions for key concepts. Here, with ‘mathematical modelling’ the authors refer to the modelling and simulation of subcellular, cellular and macro-scale phenomena, using primarily methods from dynamical systems theory. The aim of such models is encoding and testing hypotheses about mechanisms underlying the functioning of cells. Typical examples are models for molecular networks, where the behaviour of cells is expressed in terms of quantitative changes in the levels of transcripts and gene products. Bioinformatics provides essential complementary tools, including procedures for pattern recognition, machine learning, statistical modelling (testing for differences, searching for associations and correlations) and secondary data extracted from databases.Dynamical systems theory is the natural language to investigate complex biological systems demonstrating nonlinear spatio-temporal behaviour. However, the generation of experimental data suitable to parameterise, calibrate and validate such models is often time consuming and expensive or not even possible with the technology available today. In our report, we use the term ‘computational model’ when mathematical models are complemented with information generated from bioinformatics resources. Hence, ‘the model’ is, in reality, an integrated collection of data and models from various (possibly heterogeneous) sources. The present report focuses on a selection of topics, which were identified as appropriate case studies for medical systems biology, and adopts a particular perspective which the authors consider important. We strongly believe that mathematical modelling represents a natural language with which to integrate data at various levels and, in doing so, to provide insight into complex diseases: 1. Modelling necessitates the statement of explicit hypotheses, a process which often enhances comprehension of the biological system and can uncover critical points where understanding is lacking. 2. Simulations can reveal hidden patterns and/or counter-intuitive mechanisms in complex systems. 3. Theoretical thinking and mathematical modelling constitute powerful tools to integrate and make sense of the biological and clinical information being generated and, more importantly, to generate new hypotheses that can then be tested in the laboratory.Medical Systems Biology projects carried out recently across Europe have revealed a need for action: 4. While the need for mathematical modelling and interdisciplinary collaborations is becoming widely recognised in the biological sciences, with substantial implications for the training and research funding mechanisms within this area, the medical sciences have yet to follow this lead. 5. To achieve major breakthroughs in Medical Systems Biology, existing academic funding schemes for large-scale projects need to be reconsidered. 6. The hesitant stance of the pharmaceutical industry towards major investment in systems biology research has to be addressed. 7. Leading medical journals should be encouraged to promote mathematical modelling.