Predicting material properties with the help of machine learning A central goal of computational physics and chemistry is to predict material properties using first-principles methods based on the fundamental laws […]
Molecules in quantum motion In order to fully understand the nature of chemical reactions and molecular properties, we need to simulate both the electronic and vibrational motion quantum mechanically. However, […]
“ Exploring Metalloenzymes for Therapeutics and Sustainable Catalysis” Abstract: Metalloenzymes are at the heart of numerous biological processes ranging from respiration and photosynthesis to natural product biosynthesis. Research in the […]
Abstract: Primary and secondary mutations in anaplastic lymphoma kinase (ALK) are oncogenic. Insights into ALK acquired resistance were used to define a drug design strategy that led to the discovery […]
"Switches, sensors, and new shapes: from design of new functions to cellular consequences of allostery"
“Multidisciplinary (mission directed) research in nanotechnology at the University of Sydney”
"Structural Evidence for Dynamic Nitrogenase Metalloclusters" Abstract: Nitrogenase catalyzes dinitrogen reduction to ammonia and is the only enzyme capable of supplying the world with a reduced form of ‘N’ that […]
Abstract: SARS-CoV2, the causative agent of the COVID-19 pandemic, is an RNA virus that has efficient human to human transmission and carries significant morbidity and mortality for vulnerable patient populations. […]
"Metabolic control of post-translational modifications"
First-Principles Materials Prediction: From Sustainability to the Quantum Information Age Theory-guided materials design is vital to the advancement of sustainability and quantum information science. First-principles theory entirely based on quantum […]
The NSF Center for Integrated Catalysis is delighted to announce that it will be hosting a monthly webinar series. The next webinar of this series will be held on Tuesday, […]
