(611a) Design of Nanostructured Materials from Sequence Controlled Biopolymers
AIChE Annual Meeting
2023
2023 AIChE Annual Meeting
Materials Engineering and Sciences Division
Polymer thermodynamics, Self-Assembly, and Polymer-Molecule Interactions
Sunday, November 5, 2023 - 3:30pm to 4:00pm
Biological polymers offer an as-yet unparalleled level of sequence control in polymer design, enabling them to achieve a wide variety of properties in natural systems. This sequence control inspires chemists to harness the potential of these polymers for a wide variety of applications in new polymer design, particularly in biomaterials and nanomaterials. However, the design space for sequence-controlled polymers is massive, even with the comparatively limited chemical diversity of monomers in natural polymers such as proteins. Therefore, new paradigms for exploring and designing in this extremely high-dimensional space are required to effectively navigate through it and accelerate the pace of material discovery.
To provide a formalism for sequence-controlled polymer modelling, we have developed a variation of the classical self-consistent field theory formalism that allows field theoretic simulation of sequence-defined polymer self-assembly for arbitrary polymer sequences. By representing the polymer sequence as continuously differentiable interaction function, we can model a wide variety of different monomer interactions in a simplified form, and the efficacy of the model is validated on relatively simple sequence-defined polymers such as tapered block copolymers. The model provides an intellectual formalism for analysing the relevant length scales for self-assembly using Fourier transforms of the sequence functions providing key insight into how different Fourier components affect nanostructure formation.
Using elastin-like proteins as model biopolymers, we have also explored different methods for the parameterization of these sequence functions and experimental routes for generating the necessary thermodynamic data. When properly parameterized, the simulation approach has potential for use in inverse design algorithms that can help to discover novel nanomaterial structures based on these biopolymers.
To provide a formalism for sequence-controlled polymer modelling, we have developed a variation of the classical self-consistent field theory formalism that allows field theoretic simulation of sequence-defined polymer self-assembly for arbitrary polymer sequences. By representing the polymer sequence as continuously differentiable interaction function, we can model a wide variety of different monomer interactions in a simplified form, and the efficacy of the model is validated on relatively simple sequence-defined polymers such as tapered block copolymers. The model provides an intellectual formalism for analysing the relevant length scales for self-assembly using Fourier transforms of the sequence functions providing key insight into how different Fourier components affect nanostructure formation.
Using elastin-like proteins as model biopolymers, we have also explored different methods for the parameterization of these sequence functions and experimental routes for generating the necessary thermodynamic data. When properly parameterized, the simulation approach has potential for use in inverse design algorithms that can help to discover novel nanomaterial structures based on these biopolymers.