Interview mit Hans-Christian Boos zum Thema „Unternehmertum in der IT-Branche“

Ohne Zusammenfassung     

High quality gate dielectrics formed by rapid thermal chemical vapor deposition of silane and nitrous oxide

In the present study, we have performed electrical characterization of oxides deposited via rapid thermal chemical vapor deposition using SiH₄ and N₂O. We have investigated the effect of temperature, pressure, and SiH₄ to N₂O ratio on the electrical and material properties of as-deposited films. We have found that as-deposited oxides deposited at low temperatures, low pressures, and with a low silane to nitrous oxide ratio of ～0.5% give good material and electrical properties. The as-deposited films are stoichiometric in nature and have high deposition rates. As-deposited films had very low D_it values, high breakdown fields, and excellent subthreshold swing. The leakage currents and metal oxide semiconductor field effect transistor current drive, although lower than thermal oxides, were found to be quite acceptable. We have also investigated the thickness dependence of the films and found that as the film thickness is reduced below 50Å, the reliability improves for all oxides including the silicon-rich deposited oxides.     

Thermolysis of poly(diaryl diazosulfide)s

Poly(diaryl diazosulfide)s and model diaryl diazosulfides of the general structure aryl-N?N? S-aryl' are tested for their thermostability. Thermolysis in solution is followed by means of UV spectroscopy. At the beginning of the decay most model diazosulfides follow first-order kinetics, but show an acceleration of the decay rate in the further course of the thermolysis. In contrast to the models the decomposition of the corresponding polymers cannot be described by first-order kinetics, except one example ( P 1 ). Thermogravimetry studies show weight losses of 8–12% in the range between 80 and 150°C depending on the structure of the models and polymeric diazosulfides. These values correspond with the content of azo function in these compounds, therefore it is assumed that nitrogen is split off under these reaction conditions.     

Structure-Activity Relationships of Benzamides and Isoindolines Designed as SARS-CoV Protease Inhibitors Effective against SARS-CoV-2

Inhibition of coronavirus (CoV)-encoded papain-like cysteine proteases (PL^pro) represents an attractive strategy to treat infections by these important human pathogens. Herein we report on structure-activity relationships (SAR) of the noncovalent active-site directed inhibitor (R)-5-amino-2-methyl-N-(1-(naphthalen-1-yl)ethyl) benzamide ( 2 b ), which is known to bind into the S3 and S4 pockets of the SARS-CoV PL^pro. Moreover, we report the discovery of isoindolines as a new class of potent PL^pro inhibitors. The studies also provide a deeper understanding of the binding modes of this inhibitor class. Importantly, the inhibitors were also confirmed to inhibit SARS-CoV-2 replication in cell culture suggesting that, due to the high structural similarities of the target proteases, inhibitors identified against SARS-CoV PL^pro are valuable starting points for the development of new pan-coronaviral inhibitors.     

The Inflammatory Profile of Obesity and the Role on Pulmonary Bacterial and Viral Infections

Obesity is a globally increasing health problem, entailing diverse comorbidities such as infectious diseases. An obese weight status has marked effects on lung function that can be attributed to mechanical dysfunctions. Moreover, the alterations of adipocyte-derived signal mediators strongly influence the regulation of inflammation, resulting in chronic low-grade inflammation. Our review summarizes the known effects regarding pulmonary bacterial and viral infections. For this, we discuss model systems that allow mechanistic investigation of the interplay between obesity and lung infections. Overall, obesity gives rise to a higher susceptibility to infectious pathogens, but the pathogenetic process is not clearly defined. Whereas, viral infections often show a more severe course in obese patients, the same patients seem to have a survival benefit during bacterial infections. In particular, we summarize the main mechanical impairments in the pulmonary tract caused by obesity. Moreover, we outline the main secretory changes within the expanded adipose tissue mass, resulting in chronic low-grade inflammation. Finally, we connect these altered host factors to the influence of obesity on the development of lung infection by summarizing observations from clinical and experimental data.     

Regional mass flux balancing for controlling gentle soil remediation operations

Extraction of heavy metals by accumulating plants is a method which is currently in development for the "gentle" remediation of contaminated agricultural soils (phytoremediation, see [2]). Areal contaminant mass flux balances are basic criteria for the design of such remediations and their control. A framework for the integration of contaminant balances relating the field scale of remediation with the regional scale of soil monitoring networks is provided by the recently developed method PROTERRA [3]. The objective of the study presented in this paper was to test the suitability of PROTERRA for planning and monitoring gentle soil remediations. For this purpose we applied the PROTERRA method to the contaminated agricultural land in and around Dornach, Switzerland, to assess copper flux balances.The calculations showed that atmospheric deposition and the application of pesticides and manure are important pathways for the inputs of copper. The copper export with a special maize cultivar accumulating heavy metals would be about three times higher than the average metal export with crops. A moderate increase of sewage sludge application would lead to a substantial increase of the copper input. Decisions to remediate the soil should take the uncertainty of mass flux balances both on field scale as well as on regional scale into account. Therefore, an important need of further development of the PROTERRA method is the integration of uncertainty analysis on both scales.     

Predicting roadheader performance by using artificial neural network

With growing use of roadheaders in the world and its significant role in the successful accomplishment of a tunneling project, it is a necessity to accurately predict performance of this machine in different ground conditions. On the other hand, the existence of some shortcomings in the prediction models has made it necessary to perform more research on the development of the new models. This paper makes an attempt to model the rate of roadheader performance based on the geotechnical and geological site conditions. For achieving the aim, an artificial neural network (ANN), a powerful tool for modeling and recognizing the sophisticated structures involved in data, is employed to model the relationship between the roadheader performance and the parameters influencing the tunneling operations with a high correlation. The database used in modeling is compiled from laboratory studies conducted at Azad University at Science and Research Branch, Tehran, Iran. A model with architecture 4-10-1 trained by back-propagation algorithm is found to be optimum. A multiple variable regression (MVR) analysis is also applied to compare performance of the neural network. The results demonstrate that predictive capability of the ANN model is better than that of the MVR model. It is concluded that roadheader performance could be accurately predicted as a function of unconfined compressive strength, Brazilian tensile strength, rock quality designation, and alpha angle R ² = 0.987. Sensitivity analysis reveals that the most effective parameter on roadheader performance is the unconfined compressive strength.