Heinz Maier-Leibnitz Prize for Pascal Friederich
Pascal Friederich, tenure-track professor at the Institute for Theoretical Informatics, receives a Heinz Maier-Leibnitz Prize from the German Research Foundation (DFG). The prize is considered the most important award for young scientists in Germany. In his interdisciplinary work, Pascal Friederich focuses on the use of artificial intelligence in material simulation, virtual material design, and autonomous experimental platforms for automatic material recognition.
"The requirements for new, high-performance materials - whether for efficient energy storage or for applications in medicine - continue to increase, while at the same time development times must become shorter and shorter. Tenure-track professor Pascal Friederich meets this challenge by perfectly combining machine learning methods with materials science," says KIT President Professor Holger Hanselka. "The Leibnitz Prize is a great recognition of his great work. We are proud and very happy with him!"
The DFG awards the Heinz Maier-Leibnitz Prize to researchers at an early stage of their careers for outstanding achievements. The prize is endowed with 20,000 euros and is intended to support the honorees in pursuing their scientific careers. In 2022, a total of ten researchers will receive the Leibnitz Prize. The prize is named after the physicist Professor Heinz Maier-Leibnitz, DFG President from 1974 to 1979.
Increasing demand for high-performance materials
Pascal Friederich is a tenure-track professor at the Institute for Theoretical Informatics (ITI) of KIT as well as an associated group leader at the Institute for Nanotechnology (INT) and heads the AiMat (Artificial Intelligence for Materials Sciences) research group. She is primarily concerned with data-based prediction of material properties, computer-aided material design, the use of machine learning for material simulation at the atomic scale, and the direct connection of artificial intelligence methods with experiments in the laboratory. These topics are steadily gaining in importance given the increasing demand for high-performance materials and the variety of potential applications.
After completing his bachelor's and master's degree in physics at KIT, Pascal Friederich developed a new method for calculating the material properties of organic semiconductors as part of his doctorate, also at KIT, which points the way to the design of novel organic semiconductors. During research stays at the Georgia Institute of Technology/USA and as Marie Curie Fellow at Harvard University/USA and at the University of Toronto/Canada, he worked on the development of machine learning methods for different disciplines. He is the author of numerous publications in renowned scientific journals.
About Pascal Friederich's research:
Application of Artificial Intelligence in the Development of Metal-Organic Framework Compounds (KIT News for a publication in the journal Angewandte Chemie):https://www.kit.edu/kit/30310.php
Application of machine learning for faster and more accurate material simulations (KIT press release on a publication in the journal Nature Materials): https://www.kit.edu/kit/pi_2021_049_maschinelles-lernen-beschleunigt-materialsimulationen.php