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Research project (§ 26 & § 27)
Duration : 2022-01-01 - 2024-12-31

This project includes the participation in IEA Bioenergy Task33 - Thermal Gasification of Biomass for the triennium 2022 - 2024, the inter- and national networking and the dissemination of information within Austria. The aim of IEA Bioenergy Task33 is to support and promote the thermal gasification of biomass and waste. The activities of Task 33 are coordination of the research activities of the individual member countries to identify non-technical barriers and, if possible, to remove them. The exchange of experience and the joint activities in this task are very valuable for Austria, as currently some new gasification projects are being implemented, where the experiences from the projects in other countries can be incorporated in this way.
Research project (§ 26 & § 27)
Duration : 2020-08-01 - 2023-07-31

Metal containing biomolecules are surprisingly common and essential for a spectrum of biological activities and physiological functions including i.a. respiration or photosynthesis. About one third of all the proteins include a metal-site, those metalloproteins typically coordinate metals by amino acid residues or organic co-factors. Metalloproteins have been investigated extensively towards understanding of their structure, function and, in particular, metal-ligand interactions which are relevant for drug design of metalloenzyme inhibitors and metallodrugs. Modelling and simulation of metalloproteins is challenging in various respects. Molecular dynamics (MD) simulations together with classical force fields do not suffice to describe the behaviour of metals and coordinated atoms. A quantum mechanical (QM) description of the systems is required to capture electronic effects. However, the efficiency of those methods is rather poor in the context of QM/MM hybrid approaches that are necessary to study large and complex biomolecules. To accelerate such hybrid systems, machine learning approaches seem to be promising. With the advances of deep learning algorithms, QM potential energy surfaces can be reproduced. Novel approaches in computational chemistry utilize neural networks (NNs) for the quantum description. With this project we propose a hybrid NN/MM-MD workflow, which we will implement in the GROMOS simulation package and apply the developed methodology to metal-sites of increasing complexity. Thus, we hope to improve the description of metal-ligand interactions in classical simulations with a specific focus on metalloproteins. The project opens the way for numerous applications and will allow for the evaluation of free-energy differences at a QM/MM level of theory, without the methodological challenges and computational costs. We expect that successful completion of the work will have considerable impact in the field of molecular simulations of metalloproteins.
Research project (§ 26 & § 27)
Duration : 2021-12-01 - 2022-11-30

Monitoring the vibration properties of ultrasonic fatigue specimens during testing is a promising application of acoustic damage evaluation methods: As the longitudinal soundwave travelling through the specimen is disturbed and reflected on newly formed interfaces and discontunities (i.e. cracks), harmonic overtones of the nominal vibration signal at 20 kHz are generated. By monitoring the harmonic content of specimen vibration and comparing the current state over the course of a fatigue test to the virgin specimen, the progress of fatigue damage can be monitored in-situ in real time. The technique does not require the additional transducers typically employed in nonlinear acoustic analysis or direct optical observation of fatigue crack size in the specimens for fatigue crack growth analysis. Rather, the technique uses the available signal of specimen movement during high frequency resonance vibration. The project objective is the development of fatigue testing DAQ software to work in conjunction with prevously developed ultrasonic fatige testing equipment. This shall enable the in-situ realtime monitoring of fatigue damage in different metallic materials (e.g. cast steel, cast aluminium alloys) subjected to ultrasonic cycling. Suitable models shall be explored and further developed to asses the fatigue damage based on resonance frequency and harmonic overtone content, to detect - changes in vibration properties due strain localisations and/or initial short cracks at natural and artificially initiated stress concentrations - correlate the resonating properties (second or higher order harmonics, resonance frequency changes) with crack lengths in long cracks. - Additionally, the portion of crack initiation and the transition from initiation to propagation should be evaluated for very high-cycle fatigue failure.

Supervised Theses and Dissertations