Research

The objective of the project is to evaluate the fatigue strength in the very high cycles regime for carburised and pseudo-carburised gear steel using fracture mechanics principles. Fatigue tests will be carried out using the ultrasonic fatigue testing technique at different load ratios. The fatigue strength (S-N curves) as well as the threshold stress intensity factor ranges for long cracks will be determined with tests up to ten billion load cycles.

A commercial building is being constructed in Engelhartszell that is as sustainable, resource-saving and circular as possible. To this end, research questions regarding the use of materials and the building's energy supply are being investigated. In a first step, the materials and technologies to be used are determined on the basis of a comprehensive literature review. In a second step, various HVAC concepts are developed in combination with a suitable heat distribution system. The next step is to model the building in a building simulation environment in order to simulate different variants of the wall structure and energy generation, but also to be able to map the effects on comfort and the indoor climate. In a final phase, the results are collected and summarized in a final report.

In recent years, molecular informatics has transformed from a niche discipline into a driving force of the research and development of functional small molecules such as drugs and agrochemicals. Advanced algorithms as well as powerful computer hardware are now opening unprecedented opportunities for the targeted design of safe and efficacious small molecules. However, the full potential of computational methods in the biosciences is by far not exploited yet. One of the main reasons for this situation is the fact that the most powerful technologies in molecular informatics, machine learning and simulations in particular, depend on the availability of substantial amounts of high-quality data for development and validation. Despite recently launched initiatives to boost collaborative research and learning, the vast majority of high-quality chemical, biological and structural data remain behind corporate firewalls, inaccessible for research by experts in academia. This initiative for the Christian Doppler Laboratory for Molecular Informatics in the Biosciences seeks to push the frontiers of machine learning and molecular dynamics simulations technologies for the prediction of small-molecule bioactivity by supporting three expert academic research groups of the University of Vienna and the University of Natural Resources and Life Sciences (BOKU) with big data on the chemical and biological properties of small molecules, and with significant capacities for experimental testing and method validation. The unique synergy that will be generated by this consortium stems from two important factors: First, the two industry partners of this consortium have strong interest in cheminformatics but their business areas are non-competing. Second, and from a scientific point highly important, these industry partners focus on distinct chemical spaces, opening a unique opportunity for academics to boost the capacity and applicability of in silico methods with uniquely diverse, high-quality data.