CMD30 FisMat2023 - Submission - View

Abstract title: Ab-initio study of Surface-Enhanced Raman Specroscopy of optimized cyanobiphenyl-4-thiol Self-Assembled Monolayers on Au(111)
Submitting author: Bruno Candelas
Affiliation: CFM-MPC (Centro mixto CSIC-UPV/EHU)
Affiliation Address: Manuel de Lardizabal 5, 20018, Donostia, Spain
Country: Spain
Other authors and affiliations: Nerea Zabala (CFM-MPC, Centro mixto CSIC-UPV/EHU; Department of Electricity and Electronics, FCT-ZTF, UPV/EHU), Joakim Löfgren (Department of Applied Physics, Aalto University), Patrick Rinke (Department of Applied Physics, Aalto University), Tuomas Rossi (Department of Applied Physics, Aalto University), Javier Aizpurua (CFM-MPC, Centro mixto CSIC-UPV/EHU).
Abstract
Self-assembled monolayers (SAMs) play a central role in modern surface chemistry and nanotechnology, due to their many applications in fields such as nanoelectronics, sensing, and catalysis. One of the most established techniques for studying these interfaces is Surface-Enhanced Raman Spectroscopy (SERS), with recent works demonstrating its potential for imaging or even revealing single-atom dynamics [1,2]. SAMs often feature tightly-packed arrangements of molecules, such as the (2x2) hexagonal configurations observed in experimental preparations of 1,1’-biphenyl-4-thiol SAMs on Au(111) [3]. It is also well known that there are important contributions to the SERS signal enhancement arising from the chemical interactions between adsorbate and surface [4]. However, most of the theoretical descriptions of SERS for SAM configurations do not fully consider the interactions between molecules together with the chemical enhancement mechanisms. The aim of this work is to study the Raman Spectrum of cyanobiphenyl-4-thiol SAMs with an ab-initio approach that includes these effects, in order to evaluate their importance. We determine the adsorption configuration with the Bayesian Optimization Structure Search (BOSS) code [5], which uses a ‘building block’ approach and Density Functional Theory (DFT) sampling data to construct and minimize N-dimensional energy landscapes. The DFT calculations are performed with the GPAW package [6], and the Raman spectra are obtained within the Placzek approximation using the finite-difference scheme implemented in the ASE package [7,8]. References[1] R. Zhang, Y. Zhang, Z. Dong, et al., Nature 498, 82-86 (2013).[2] J. Griffiths et al., Nat Comm 12, 6759 (2021).[3] D. G. Matei, H. Muzik, A. Gölzhäuser, and A. Turchanin, Langmuir 28, 13905-13911 (2012).[4] L. Jensen, C. M. Aikens, and G. C. Schatz, Chem. Soc. Rev. 37, 1061-1073 (2008).[5] M. Todorović, M. U. Gutmann, J. Corander, and P. Rinke, npj Comput Matter 5, 35 (2019).[6] J. Enkovaara et al., J. Phys: Condens. Matter 22, 253202 (2010).[7] A. H. Larsen et al., J. Phys: Condens. Matter 29 273002 (2017).[8] M. Walter and M. Moseler, J. Chem. Theory Comput. 16, 576-586 (2020).