STTR Phase I: Entropy-Driven Assembly of Gradient Lamellar Nanocomposites for Scalable Photonic Coatings

Award ID: 2538045

The broader/commercial impact of this Small Business Technology Transfer Phase I project will be to explore a faster, lower-cost way to fabricate advanced optical coatings for next-generation photonic, electronic, and sensing devices. Today, many high-performance optical coatings require expensive vacuum equipment, high temperatures, long deposition times, and multiple processing steps. This project will investigate whether solution-based, single-step fabrication can produce wavelength-selective protective coatings in minutes, offering a potential alternative to complex, multi-step coating methods. If successful, this approach could reduce manufacturing cost and energy use while enabling coatings on flexible, curved, and lightweight devices. These coatings may combine optical filtering with moisture protection in a single film, simplifying device designs and improving product lifetimes. Project success would support domestic manufacturing in photonic materials, strengthen U.S. leadership in flexible electronics, and develop future skilled workers in materials science, advanced manufacturing, and data-driven research. The intellectual merit of this project is based on the high-risk translation of entropy-driven, self-assembling nanocomposite films into wavelength-selective Bragg and gradient optical coatings. The central technical question is whether scalable, solution-based self-assembly can control nanoscale structure well enough to produce visible-wavelength reflective films that combine spectral selectivity, low haze, mechanical durability, and barrier performance. This project will study how formulation chemistry, nanoparticle loading, polymer organization, coating conditions, and solvent evaporation affect film structure and optical performance. The work will target reflection across the visible spectrum, from approximately 400 to 700 nanometers, while evaluating film uniformity and stability on flexible and non-traditional substrates. Films will be characterized for reflectance, transmittance, haze, angular response, adhesion, mechanical durability, and moisture resistance. Structural analysis using advanced scattering methods and electron microscopy will evaluate nanoscale ordering, layer uniformity, and defect formation. Predictive machine learning models will then support the selection and refinement of promising formulations by linking processing conditions, film structure, and measured performance. Successful completion will determine whether single-step self-assembly can provide a feasible path toward manufacturable optical coatings while advancing the understanding of how processing controls nanoscale order, optical response, and film durability. 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.

NSF Program Director: Benaiah Schrag