(MURI-20)UNRAVELING THE MECHANISMS OF ICE NUCLEATION AND ANTI-ICING THROUGH AN INTEGRATED MULTISCALE APPROACH
Abstract
Many organisms that thrive at cold temperatures have evolved biomolecules to control ice formation. The commonality of these molecules is their ability to bind ice, although their functions can be quite distinct: they can be antifreeze or ice nucleating. Proteins excel at both functions. However, they are expensive to produce in large quantities for applications that allow them to prevent and control ice formation on large surfaces. Understanding how proteins bind to ice and determine what characteristics make them good antifreeze or ice nucleating agents is key to designing new molecules that excel at preventing ice growth and recrystallization, controlling ice nucleation, and facilitating de-icing, which is the focus of this MURI project. This MURI integrates multi-scale multi-resolution computer simulations and theory with state-of-the-art experimental techniques probing properties at different length and time scales, biochemical synthesis, and machine learning to elucidate the fundamental mechanisms and interactions that control ice recognition, formation and adhesion. The main aims are: 1) To elucidate the diversity of chemical motifs that bind strongly to ice, and identify signatures in the structure and dynamics of hydration of ice-binding molecules that can predict their strength of ice-binding; 2) To develop a multi-scale multi-resolution modeling approach that identifies and accounts for all steps in the reaction network responsible for antifreeze and ice recrystallization inhibition activities, and design and synthesize new ice binding materials with improved antifreeze activity; 3) To elucidate how biological and organic molecules and crystals nucleate ice, use that knowledge to identify and design materials that nucleate ice without supercooling, and develop a biomimetic approach to ice nucleation; and 4) To develop new experimental and simulation techniques to probe buried ice interfaces, and to characterize the properties of the premelted layer.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 12, 2021
- Source ID
- FA95502010351
Entities
People
- Francesco Paesani
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of California, San Diego