Computational Chemistry Made Easy

Simulating complex chemical systems

Bringing concepts from distributed computing and bioinformatics to the field of computational chemistry

life sciences and ehealth

Computational Chemistry Made Easy

Computational Chemistry Made Easy

Bringing concepts from distributed computing and bioinformatics to the field of computational chemistry

Studying chemistry has become easier and faster thanks to the development of a dedicated Python library to set up and run advanced calculations on parallel supercomputers. Whereas researchers in the past had to spend a large fraction of their time in making the appropriate inputs for modelling programs and then again in retrieving and processing the resulting data, many of these steps can now be run automatically. This makes it possible to study much larger sets of reactions in the computer to better identify trends in chemical reactivity or to calculate carrier cooling or hot-injection processes in semiconductor nanocrystals. The resulting software QMFlows is available as open source and will be used by company and academic researchers. The Noodles software that was initiated in this project finds also applicability in modelling areas outside chemistry in automating also other types of complex software.

eScience Coordinator Dr. Lars Ridder

Lars’ research interests cover (bio)chemical informatics and simulations. He is responsible as engineer and project coordinator for multiple projects in the life-sciences and chemistry domains.

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eScience Research Engineer Johan Hidding, MSc

Johan studied astrophysics at the University of Groningen

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