Manufacturing Hierarchical Multifunctional Architectures

Nanoscale elements, such as nanoparticles, serve as ‘metamolecule’ building blocks where periodicity, geometry, gap spacings, and dielectric environment provide many degrees of freedom for tuning light matter interactions. While top down methods such as holography and electron beam lithography provide periodic patterns over large area there are trade-offs between ultrahigh signal enhancement that result from nanogaps with sub-2 nm spacing and reproducibility or complexity of fabrication. Conventional lithographic techniques have further challenges in producing large-area assemblies on soft substrates. Understanding how to integrate plasmonic surfaces into device architectures with reproducible performance using low-cost and scalable manufacturing methods is addressed using chemical assembly of gold nanoparticles on deblock copolymer substrates. Electrokinetic driving forces for initiating chemical reactions between molecular ligands on nanoparticle surfaces. The length of the resultant molecular linker controls the gap distance between nanoparticles. For example the nanogap distance is 0.9 nm (16 carbon atoms across) when the linker is an anhydride bond between two lipoic acid molecules. Microfluidic channels have been fabricated with embedded electrical and optical architectures to produce large area arrays of devices which benefit from near field enhancements with controlled molecular scale gap spacings and surface chemistry. These compact electro-optical micro fluidic devices are used in numerous applications. By changing the molecular linker for sensors, we are able to tune interactions with analytes of interest for improving precision in detection. The resultant reproducible signals acquired with short integration times enable rapid acquisition of large data sets needed for analysis with machine learning algorithms. We can acquire 10,000 spectra in under an hour. This represents a transformative improvement in label free sensing. Large, high quality datasets are at the heart of the machine learning revolution. The fabricated sensors fabricated have demonstrated ability for quantifying molecular concentration down to 10 fM, detection of bacterial biofilms, locate environmental contaminants, and determine effective antibiotic treatment for infection.