“Nanostructured Nickel-Rich Cathode Materials for High-Capacity and Fast-Charging Lithium-Ion Batteries” ABSTRACT: Fast-charging lithium-ion batteries are desired for use in personal electronics and electric vehicles, potentially allowing systems to charge devices in minutes rather than hours. Fast-charging can be achieved by nanostructuring battery materials, which decreases lithium-ion diffusion lengths and can suppress slow, rate-limiting phase transitions. This […]

Harnessing Conformational Dynamics to Engineer New Enzymes Understanding how new enzyme functions evolve, either on existing scaffolds, or completely de novo on previously non-catalytic scaffolds, is of great interest both from a fundamental biochemistry perspective, and from a biotechnological perspective. Several hypotheses have been put forward to rationalize enzyme evolution, one of which is that their […]

The NSF Center for Integrated Catalysis is delighted to announce that it will be hosting a monthly webinar series. The Fourth day of this series will be held on Tuesday, December 15th at 1:00 PM.  We are pleased to invite all students, postdocs, faculty, and staff.

“Tuning the Reactivity Landscape of Metalloenzymes: From Active Site Modifications to Long-range Dynamic Effects” Abstract: Metalloenzymes rely on transition metals within the protein scaffold to perform a wide variety of molecular transformations in biology. Synthetic models of metalloenzyme intermediates, inspired by the enzyme active site and its secondary coordination sphere, have provided systems for studying bond-forming/breaking […]

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, January 19th, 2021 at 1:00 PM.  We are pleased to invite all students, postdocs, faculty, and staff.

"Chemical and Biological Design Approaches to Controlling Protons, Electrons, and Substrates for Sustainable Catalysis"  Abstract: The reductive transformation of small molecules into value-added products represents an attractive way to store sustainable energy in chemical bonds. Achieving this efficiently and selectively requires the careful management of not only the substrate and intermediates, but also the proton and […]

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 of quantum mechanics. However, the high computational costs of these methods typically prevent rigorous predictions of macroscopic quantities at finite temperatures, such as chemical potential, […]