NSF requires disclosure of AI tool usage in proposal preparation. Ensure you disclose the use of FindGrants' AI drafting in your application.
NSF
Non-Technical Summary: Self-assembly refers to the spontaneous emergence of well-defined structures from an initial disordered state. Common examples include the formation of soap films, the folding of proteins and nucleic acids, as well as the formation of crystals. Self-assembly is a powerful bottom-up approach to materials synthesis. While capable of generating intricate structures, equilibrium self-assembly suffers from limitations. It requires microscopic constituents that exhibit riotous dynamics driven by thermal noise. To overcome these limitations, this project will develop a paradigm of active assembly for generating materials from building blocks that exhibit no thermal motion. Non-thermal Velcro-like bundles of filaments are placed in an active fluid. Spontaneous flows generated by active fluid endow passive bundles with enhanced dynamics. These bundles move chaotically, stick to each other, generating permanent connections, and assembling three-dimensional elastic networks, whose structure and mechanical properties cannot be realized with conventional self-assembly methods. The proposed research provides a powerful platform for generating new materials with unique properties. From a societal perspective, the proposed project will provide rigorous interdisciplinary training to graduate students. The project will also provide invaluable research opportunities and extensive mentoring to undergraduate students from UCSB and throughout the California State educational system. Finally, the project pursues extensive outreach activities targeting the general public and K-12 education, enhancing the public awareness of materials research. Technical Abstract: Self-assembly is a versatile paradigm for engineering materials with intricate structures and targeted mechanical properties. Well-understood equilibrium statistical mechanics provides a quantitative relationship between the interactions of the microscopic building blocks and the ensuing macroscopic properties of the target assemblage. Notwithstanding its considerable successes, equilibrium self-assembly suffers from limitations. Self-assembly demands an equilibrium environment wherein all intermediate states exhibit thermal motion. To ensure that the process reaches the target state, one has to balance the strength and specificity of the attractive interactions against the characteristic thermal energy. This project aims to extend the capabilities of equilibrium self-assembly by establishing the foundations of active assembly. Chaotic flows generated by an active fluid endow passive molecular building blocks with enhanced stochastic dynamics and excess energy that are not accessible in equilibrium. This overcomes energetic barriers that trap the equilibrium system and allows for the exploration of a much larger landscape of accessible states. In active assembly, the building blocks move throughout the sample, encounter each other, and bind together to give rise to soft materials with unique structures, shapes, mechanics, and dynamics. When compared to equilibrium self-assembly, active assembly extends the manifold of accessible structures, overcomes kinetic trapping associated with equilibrium, and enables the assembly of mesoscale building blocks that do not exhibit thermal motion in the absence of activity. In the first aim, actin filaments and their crosslinkers are placed into a microtubule-based active fluid. Being advected by the active flows, actin filaments efficiently explore the accessible phase space and assemble into elastic networks whose architectures are not accessible using conventional protocols. State-of-the-art microscopy and quantitative image analysis elucidate the kinetic pathways of network assembly in real-time with near-molecular detail. In the second aim, the rheological properties of the assembled elastic network are correlated to the microscopic network structure. These unique features will enable a study of the non-thermal transition from floppy networks lacking a finite shear modulus to networks with a finite rigidity. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Up to $329K
2028-08-31
Detailed requirements not yet analyzed
Have the NOFO? Paste it below for AI-powered requirement analysis.
One-time $749 fee · Includes AI drafting + templates + PDF export
Category I: CloudBank 2: Accelerating Science and Engineering Research in the Commercial Cloud
NSF — up to $24M
Category I: Nexus: A Confluence of High-Performance AI and Scientific Computing with Seamless Scaling from Local to National Resources
NSF — up to $24.0M
Research Infrastructure: Mid-scale RI-1 (MI:IP): Dual-Doppler 3D Mobile Ka-band Rapid-Scanning Volume Imaging Radar for Earth System Science
NSF — up to $20.0M
A Scientific Ocean Drilling Coordinating Office for the US Community
NSF — up to $17.6M
Category I: AMA27: Sustainable Cyber-infrastructure for Expanding Participation
NSF — up to $13.8M
Graduate Research Fellowship Program (GRFP)
NSF — up to $9.0M