Heinz Maier-Leibnitz Prize goes to Pascal Fri

picture: Pascal Friederich receives the Heinz Maier-Leibnitz Prize, a very powerful recognition of early-career researchers in Germany.
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Credit: Amadeus Bramsiepe, KIT

Pascal Friederich, Tenure-track Professor at Karlsruhe Institute of Technology (KIT), is awarded the Heinz Maier-Leibnitz Prize of the German Research Foundation (DFG). The prize within the quantity of EUR 20,000 is a very powerful recognition of early-career researchers in Germany. Pascal Friederich’s interdisciplinary work concentrates on the usage of synthetic intelligence for the simulation of supplies, digital supplies design, and autonomous experimental platforms for automated supplies recognition. 

 

“Requirements to be met by new, extremely performing supplies – could it’s for environment friendly vitality storage programs or for purposes in medication – are additional growing. At the identical time, improvement instances have to be shortened. Tenure-track Professor Pascal Friederich takes on this problem and completely combines machine studying strategies with supplies sciences,” says the President of KIT, Professor Holger Hanselka. “The Leibnitz Prize is a superb recognition of his excellent work. We are proud and really joyful!”

 

DFG awards the Heinz Maier-Leibnitz Prize to early-career researchers in recognition of their excellent achievements. The prize within the quantity of EUR 20,000 is meant to help the researchers in furthering their scientific careers. In 2022, the Leibnitz Prize is awarded to ten researchers. It is known as after physicist Professor Heinz Maier-Leibnitz, DFG President from 1974 to 1979.

 

Increasing Demand for High-performance Materials

Pascal Friederich is Tenure-track Professor at KIT’s Institute of Theoretical Informatics (ITI) and related group chief on the Institute of Nanotechnology (INT). He heads the analysis group AiMat (Artificial Intelligence for Materials Sciences) for data-based prognosis of supplies properties, computer-based supplies design, use of machine studying strategies to simulate supplies on the atomic scale, and direct mixture of synthetic intelligence strategies with laboratory experiments. In view of the growing demand for extremely performing supplies and the massive vary of purposes, these matters are gaining significance.

 

After he acquired his bachelor’s and grasp’s levels in physics at KIT, Pascal Friederich, throughout the framework of his doctorate at KIT, developed a brand new methodology to compute supplies properties of natural semiconductors. This will allow the design of novel natural semiconductors. He performed analysis at Georgia Institute of Technology / USA and as a Marie Curie Fellow at Harvard University / USA and the University of Toronto / Canada, the place he labored on the event of machine studying strategies for numerous disciplines. Friederich is writer of quite a few publications in famend scientific journals. (or)

 

About Pascal Friederich’s Research:

 

Einsatz Künstlicher Intelligenz bei der Entwicklung metall-organischer Gerüstverbindungen (use of synthetic intelligence for the event of metal-organic frameworks, KIT News relating to a publication in Angewandte Chemie): https://www.kit.edu/kit/30310.php  (in German)

 

Machine Learning for Faster and More Accurate Simulations of Materials (KIT Press Release relating to a publication in Nature Materials): https://www.kit.edu/kit/english/pi_2021_049_machine-learning-speeds-up-simulations-in-material-science.php

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https://www.eurekalert.org/news-releases/945839

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