Synthesis,characterization and magnetic properties of polythiophene/SrFe12-x(ZrZn)0.5xO19 nanocomposite as a microwave absorber

Ferrites are an important group of magnetic materials which are used as absorbers. The incorporation of ferrite and conducting polymer achieves great enhancement in microwave absorption properties. The nanocomposites of hexagonal ferrites embedded by conducting polymers such as polypyrrole, polyaniline and polythiophene (PTH) have been paid much attention. In the present study, strontium hexagonal ferrite doped by Zr and Zn with the final formula of SrFe_12-x(ZrZn)_0.5xO19 considering x = 0.9 and embedded by PTH was produced to achieve a nanocomposite with the highest microwave absorbing ability. In this study, after synthesis of SrFe₁₂O₁₉(ZrZn)_0.5xO19 and PTH, the nanocomposite was prepared by in situ polymerization. Wrapping the ferrite particles and PTH chains could form nanocomposite properly, and therefore acceptable interactions were observable between SrFe_12-x(ZrZn)_0.5xO19ferrite particles and PTH polymer chains in the composites. Assessing the X-ray diffraction (XRD) patterns of SrFe_12-x(ZrZn)_0.5xO19, PTH, and PTH/SrFe_12-x(ZrZn)_0.5xO19 nanocomposite indicated that the PTH characteristic peak shifts slightly and its peak intensity reduces, which may be attribute to the coating of PTH polymer chains onto SrFe_12-x(ZrZn)_0.5xO19 particles. We revealed also lower magnetic properties in the obtained nanocomposite. The morphological assessment also suggested that PTH could effectively coat the SrFe_12-x(ZrZn)_0.5xO19 particles. The synergistic effect of SrFe_12-x(ZrZn)_0.5xO19 particle plus PTH leads to microwave absorption percentage higher than 95% by PTH/SrFe_12-x(ZrZn)_0.5xO19 nanocomposite. Overall, nanocomposite creating by coupling interaction between SrFe_12-x(ZrZn)_0.5xO19 particles (x = 0.9) and PTH can effectively lead to achieve the highest rate of absorption of electromagnetic waves.     

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

Ohne Zusammenfassung     

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.     

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.     

Characterization and tests of planar Co3O4 model catalysts prepared by chemical vapor deposition

The chemical vapor deposition method was used to deposit thin films of cobalt oxide starting with cobalt (II) acetylacetonate and oxygen. The deposition process was investigated and the obtained films were identified as a cubic spinel-type polycrystalline Co₃O₄ with a crystallite size of 30–40 nm. The coating was carbon-free and the surface oxygen concentration was measured to be 66 at.% with AES analysis. Smooth and highly uniform thin films were deposited on planar stainless steel substrates and subjected to TPR and catalysis tests that show positive correlation. The apparent activation energy of Co₃O₄ reduction to CoO was measured to be (33±5) kJ/mol. The catalytic activity of Co₃O₄ was investigated toward the conversion of both propane and ethanol to carbon dioxide. Though the catalytic action was registered at the same temperature, the deactivation process was seen to be different. The catalytic conversion of ethanol induces a fast deactivation process, which was linked to its high ability to reduce Co₃O₄.