
Projects
Hessian scientists of various disciplines are using High Performance Computers for their research.
Hessian scientists of various disciplines are using High Performance Computers for their research.
Displaying 1 - 30 of 67
Non-covalent interactions (NCIs) not only govern the structure biomacromolecules such as proteins and DNA, but often ...
Biomass-derived fuels are promising candidates to replace traditional fossil-based fuels for mobility and propulsion but ...
Azides are omnipresent in organic and inorganic chemical synthesis. They are readily introduced into molecules and allow ...
The computational resources of the Lichtenberg HPC were used in this project to train physics informed machine learning ...
The project seeks to create a comprehensive model linking nanoscale phenomena to larger-scale behaviors to better ...
The objective of this ongoing project is the continuous development and advancement of effective simulation methods for ...
While hydrogen is promising for energy storage or mobility applications, the platinum catalysts often needed to convert ...
With street traffic being a major contributor to carbon dioxide emission and global warming, alternatives to the ...
The previous investigation of SnN clusters with N = 6−40 showed that below a clusters size of about 30 atoms, a prolate ...
Combined with quantum chemical calculations, Mössbauer spectroscopy is a powerful tool to elucidate the structure of ...
Mössbauer spectroscopy is a powerful tool for investigating iron in molecular and especially amorphous systems. Combined ...
Variational inference with Gaussian mixture models (GMMs) can be used to learn highly tractable approximations of ...
During development and adult homeostasis, cells in our bodies need to constantly integrate internal and external ...
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...
Artificial intelligence is currently developing faster than ever and introduces many different possibilities. Our client ...
Many problems in machine learning involve inference from intractable distributions. For example, when learning latent ...
In order to facilitate rapid prototyping and testing in the advanced motorsport industry, we consider the problem of ...
Vibroacoustic vehicle behavior specifies among others the quality of vehicles and contributes to customer satisfaction ...
Metal nitrene compounds are highly reactive species with a unique electronic structure. Such compounds are promising ...
In the framework of the Collaborative Research Center (CRC 1487), iron is studied as a substitute for rare-earth metals ...
The Pd-catalyzed asymmetric allylic alkylation of cyclobutenes is known to proceed in a deracemizing, de-epimerizing and ...
The project aims to develop a bridging model that connects the nanoscale to the upscaled levels for understanding the ...
Recent work has shown that deep neural networks are able to predict human similarity judgments with high accuracy (e.g ...
For transition metal doped clusters, the transition metal and the host element play a fundamental role in the physical ...
Detailed multi-scale modelling provides in-depth insights into the complex phenomena of catalytic systems that typically ...
In the framework of the Collaborative Research Center (CRC 1487), iron is studied as a substitute for rare-earth metals ...
The project focuses on an iron catalysed method to prepare unprecedented chemical synthons, developed in the group of Dr ...
Neural networks are usually trained with a static architecture. However, the fields of growing and pruning, or ...
During development and adult homeostasis, cells in our bodies need to constantly integrate internal and external ...
The increase in complex cyber-attacks illustrates the vulnerability of society and information infrastructure. In ...