Morphology-Driven optimization of Double Nanohole-based Plasmonic Optical Tweezers
Abstract
Plasmonic Optical Tweezers based on Double Nanohole (DNH) structures are an emerging tool for trapping and interrogating single proteins under physiologically relevant conditions without the need for labeling or tethering. Nevertheless, their current performance is hindered by low signal-to-noise ratios for small proteins, fabrication variability, and photothermal instabilities, in part due to the required high laser power. To address these limitations, we present a comprehensive optimization of DNH parameters using parametric simulations and morphological characterization of experimentally fabricated DNHs. This approach ensures that the optimized geometries are experimentally realizable and compatible with established fabrication processes. We evaluate critical structural features, including gap width, gap length, cusp curvature, wedged tapers, adhesion layer and gold layer thicknesses, and the inclusion of pillars inside the nanoholes. By tailoring these variables, we aim to maximize the transmission variation upon trapping single nanoparticles or proteins and the local electric-field enhancement, thereby maximizing the optical force, while minimizing the required optical power. Two optimized DNH designs are proposed and simulated using a heuristic approach and a differential evolution algorithm. Both substantially outperform the reference structure and deliver 6.5- and 22-fold increases in sensitivity and 2.4- and 1.4-fold improvement in electric-field enhancement, respectively. These refinements provide a framework for developing efficient nanostructures to study single-protein dynamics with Plasmonic Optical Tweezers.
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BibTeX
@misc{molet2026morphologydriven,
title = {{Morphology-Driven optimization of Double Nanohole-based Plasmonic Optical Tweezers}},
author = {Pau Molet and Edona Karakaçi and Maria Sanz Paz and Mariano Barella and Michael Mayer},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2605.20259},
eprint = {2605.20259},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2605.20259},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - Morphology-Driven optimization of Double Nanohole-based Plasmonic Optical Tweezers
AU - Pau Molet
AU - Edona Karakaçi
AU - Maria Sanz Paz
AU - Mariano Barella
AU - Michael Mayer
PY - 2026
DA - 2026/08/31
PB - arXiv
DO - 10.48550/arxiv.2605.20259
UR - https://arxiv.org/abs/2605.20259
AB - Plasmonic Optical Tweezers based on Double Nanohole (DNH) structures are an emerging tool for trapping and interrogating single proteins under physiologically relevant conditions without the need for labeling or tethering. Nevertheless, their current performance is hindered by low signal-to-noise ratios for small proteins, fabrication variability, and photothermal instabilities, in part due to the required high laser power. To address these limitations, we present a comprehensive optimization of DNH parameters using parametric simulations and morphological characterization of experimentally fabricated DNHs. This approach ensures that the optimized geometries are experimentally realizable and compatible with established fabrication processes. We evaluate critical structural features, including gap width, gap length, cusp curvature, wedged tapers, adhesion layer and gold layer thicknesses, and the inclusion of pillars inside the nanoholes. By tailoring these variables, we aim to maximize the transmission variation upon trapping single nanoparticles or proteins and the local electric-field enhancement, thereby maximizing the optical force, while minimizing the required optical power. Two optimized DNH designs are proposed and simulated using a heuristic approach and a differential evolution algorithm. Both substantially outperform the reference structure and deliver 6.5- and 22-fold increases in sensitivity and 2.4- and 1.4-fold improvement in electric-field enhancement, respectively. These refinements provide a framework for developing efficient nanostructures to study single-protein dynamics with Plasmonic Optical Tweezers.
ER -