Designing Structures that Maximize Spatially Averaged Surface-Enhanced Raman Spectra

TL;DR

This paper introduces a framework for designing nanopatterned surfaces that maximize the average SERS signal across randomly distributed molecules, significantly outperforming traditional designs.

Contribution

It develops a general inverse design method for SERS surfaces that accounts for spatial averaging and nonlinear damage, leading to novel, highly effective structures.

Findings

Optimized structures outperform coated spheres and bowtie structures by 4 times.

Including nonlinear damage effects increases performance gains to 20 times.

Designs improve hot-spot density and angular selectivity for enhanced SERS signals.

Abstract

We present a general framework for inverse design of nanopatterned surfaces that maximize spatially averaged surface-enhanced Raman (SERS) spectra from molecules distributed randomly throughout a material or fluid, building upon a recently proposed trace formulation for optimizing incoherent emission. This leads to radically different designs than optimizing SERS emission at a single known location, as we illustrate using several 2D design problems addressing effects of hot-spot density, angular selectivity, and nonlinear damage. We obtain optimized structures that perform about 4 times better than coating with optimized spheres or bowtie structures and about 20 times better when the nonlinear damage effects are included.