Simulated Raman correlation spectroscopy for quantifying nucleic acid-silver composites

Surface-enhanced Raman spectroscopy and density functional theory study of thymine-1-acetic acid interaction with silver nanoparticles

Thymine-1-acetic acid (TAA) is a modified nucleobase often used to add thymine functionality to materials. This study reports the Raman band assignments for TAA by comparing its experimental and density functional theory (DFT) simulated Raman spectra. Further comparison of experimental surface-enhanced Raman spectroscopy (SERS) of TAA on silver nanoparticles (Ag NPs) with simulated spectra of various complexes of xAg+ (x = 1, 2, or 3) and TAA reveals its likely adsorption orientation on the Ag NPs. This is one of the few studies that has achieved reasonably accurate simulation of SERS by employing multiple unconnected Ag+ ions, which could represent a compromise between a single atom or ion on one hand and a computationally expensive cluster on the other.

Silver oxide model surface improves computational simulation of surface-enhanced Raman spectroscopy on silver nanoparticles

Surface-enhanced Raman spectroscopy (SERS) coupled with density functional theory (DFT) computations can characterise the adsorption orientation of a molecule on a nanoparticle surface. When using DFT to simulate SERS on a silver surface, one typically employs an atom (Ag), ion (Ag+), or cluster (Agx or Agx+) as the model surface. Here, by examining the nucleobase 2,6-diaminopurine (2,6-DAP) and then generalising our strategy to three other molecules, we show that employing silver oxide (Ag2O) as the model surface can quantitatively improve the accuracy of simulated SERS.

Machine learning for composition analysis of ssDNA using chemical enhancement in SERS

Surface-enhanced Raman spectroscopy (SERS) is an attractive method for bio-chemical sensing due to its potential for single molecule sensitivity and the prospect of DNA composition analysis. In this manuscript we leverage metal specific chemical enhancement effect to detect differences in SERS spectra of 200-base length single-stranded DNA (ssDNA) molecules adsorbed on gold or silver nanorod substrates, and then develop and train a linear regression as well as neural network models to predict the composition of ssDNA. Our results indicate that employing substrates of different metals that host a given adsorbed molecule leads to distinct SERS spectra, allowing to probe metal-molecule interactions under distinct chemical enhancement regimes. Leveraging this difference and combining spectra from different metals as an input for PCA (Principal Component Analysis) and NN (Neural Network) models, allows to significantly lower the detection errors compared to manual feature-choosing analysis as well as compared to the case where data from single metal is used. Furthermore, we show that NN model provides superior performance in the presence of complex noise and data dispersion factors that affect SERS signals collected from metal substrates fabricated on different days.

Energetics and Vibrational Signatures of Nucleobase Argyrophilic Interactions

This study investigates the interactions of both purine (adenine and guanine) and pyrimidine (cytosine, thymine, and uracil) nucleobases with a pair of silver atoms (Ag2). Full geometry optimizations were performed on several structures of each nucleobase/Ag2 complex and the corresponding isolated monomers using the M06-2X density functional with a correlation consistent triple-ζ basis set augmented with diffuse functions on all atoms and a relativistic pseudopotential on Ag (aug-cc-pVTZ for H, C, N, and O and aug-cc-pVTZ-PP for Ag; denoted aVTZ). Harmonic vibrational frequency computations indicate that each optimized structure corresponds to a minimum on the M06-2X/aVTZ potential energy surface. Relative electronic energies for interactions between Ag2 and each nucleobase were compared to elucidate energetic differences between isomers. Further analysis of the changes in vibrational frequencies, infrared intensities, and Raman scattering activities reveals how different Ag2 binding sites might be differentiated spectroscopically. These results provide molecular-level insight into the interactions between nucleobases and silver, which may lead to better understanding and interpretation of surface-enhanced Raman spectroscopy experiments on nucleobases and related systems.