Machine Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis
Year: 2021
Type: preprint
Abstract: Modern polymer science is plagued by the curse of multidimensionality; the large chemical space imposed by including combinations of monomers into a statistical copolymer overwhelms polymer synthesis and characterization technology and limits the ability to systematically study structure–property relationships. To tackle this challenge in the context of 19F MRI agents, we pursued a computer-guided materials discovery approach that combines synergistic innovations in automated flow synthesis and machine learning (ML) method development. A software controlled, continuous polymer synthesis platform was developed to enable iterative experimental–computational cycles that resulted in the synthesis of 397 unique copolymer compositions within a six-variable compositional space. The non-intuitive design criteria identified by ML, which was accomplished by exploring less than 0.9% of overall compositional space, upended conventional wisdom in the design of 19F MRI agents and lead to the identification of >10 copolymer compositions that outperformed state-of-the-art materials.
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: gold
Awards: G1425170006, G1554045874, Computation for the Endless Frontier, MRI: Acquisition of a 600 MHz Spectrometer with Cryogenic Probe, D3SC: CDS&E: Collaborative Research: Development and application of accurate, transferable and extensible deep neural network potentials for molecules and reactions, G2392772430, MRI: Upgrade of a 600 MHz Spectrometer for high-sensitivity Nuclear Magnetic Resonance (NMR), G3551130803, G3981648682, G4108146759, G413696558, G4972501803, G6554368712, XSEDE: eXtreme Science and Engineering Discovery Environment, G6985996734, G7579982596, G7613920406, D3SC: CDS&E: Collaborative Research: Development and application of accurate, transferable and extensible deep neural network potentials for molecules and reactions
OpenAlex ID: W3186613554