Gold Nanostar Spatial Distribution Impacts the Surface-Enhanced Raman Scattering Detection of Uranyl on Amidoximated Polymers

金纳米星空间分布影响酰胺肟化聚合物上铀酰的表面增强拉曼散射检测

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作者:Hoa T Phan, Claire Vinson, Amanda J Haes

Abstract

The plasmonic properties of carboxylated gold nanostars distributed on amidoximated polyacrylonitrile (AO PAN) electrospun polymer films scale with surface-enhanced Raman scattering (SERS) intensities for coordinated uranium(VI) oxide (uranyl) species. This two-step plasmonic sensor first isolates uranyl from solution using functionalized polymers; then carboxylated gold nanostars are subsequently deposited for SERS. Spatially resolved localized surface plasmon resonance (LSPR) and SERS facilitate correlated nanostar optical density and uranyl quantification. To reduce sampling bias, gold nanostars are deposited in an inverted drop-coating geometry and measurements are conducted inside resulting nanoparticle coffee rings that form on the polymer substrates. This approach naturally preserves the plasmonic properties of gold nanostars while reducing the deposition of nanoparticle aggregates in active sensing regions, thereby maximizing both the accuracy and the precision of SERS measurements. Several advances are made. First, second-derivative analysis of LSPR spectra facilitates the quantification of local nanostar density across large regions of the sensor substrate by reducing background variations caused by the polymeric and gold materials. Second, local nanostar densities ranging from 140 to 200 pM·cm are shown to result in uranyl signals that are independent of nanostar concentration. Third, the Gibbs free energy of uranyl adsorption to carboxylated nanostars is estimated at 8.4 ± 0.2 kcal/mol. Finally, a linear dynamic range from ∼0.3 to 3.4 μg U/mg polymer is demonstrated. Signals vary by 10% or less. As such, the uniformity of the plasmonic activity of distributed gold nanostars and the employment of spatially resolved spectroscopic measurements on the composite nanomaterial sensor interface facilitate the quantitative detection of uranyl while also reducing the dependence on user expertise and the selected sampling region. These important advances are critical for the development of a user-friendly SERS-based sensor for uranyl.

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