Vibrational identification for conformations of trans-1,2-bis (4-pyridyl) ethylene in gold molecular junctions

Photoexcited Plasmon-Driven Ultrafast Dynamics of the Adsorbate Probed by Femtosecond Time-Resolved Surface-Enhanced Time-Domain Raman Spectroscopy

Metal nanoparticles have high potential in light-harvesting applications by transferring absorbed photon energy to the adsorbates. However, photoexcited plasmon-driven ultrafast dynamics of the adsorbate on metal nanoparticles have not been clearly understood. We studied ultrafast plasmon-driven processes of trans-1,2-bis(4-pyridyl)ethylene (BPE) adsorbed on gold nanoparticle assemblies (GNAs) using time-resolved surface-enhanced impulsive stimulated Raman spectroscopy (TR-SE-ISRS). After photoexciting the localized surface plasmon resonance (LSPR) band of the GNAs, we measured femtosecond time-resolved surface-enhanced Raman spectra of the adsorbate, which exhibited transient bleach in the Raman signal and following biphasic recovery that proceeds on the time scale of a few tens of picoseconds. The TR-SE-ISRS data were analyzed with singular value decomposition, and the obtained species-associated Raman spectra indicated that photoexcitation of the LSPR band alters chemical interaction between BPE and the GNAs on an ultrafast time scale; initial steady-state BPE is recovered through a precursor state that has weaker interaction with the GNAs.

Selecting Surface-Enhanced Raman Spectroscopy Flavors for Multiplexed Imaging Applications: Beyond the Experiment

Multiplexing capabilities and sensitivity of surface-enhanced Raman spectroscopy (SERS) nanoparticles (NPs) are strongly dependent on the selected Raman reporter. These Raman-active molecules are responsible for giving each batch of SERS NPs its unique spectral fingerprint. Herein, we studied four types of SERS NPs, namely, AuNPs labeled with trans-1,2-bis(4-pyridyl)ethylene (BPE), 4,4'-bis(mercaptomethyl)biphenyl (BMMBP), 5-(4-pyridyl)-1,3,4-oxadiazole-2-thiol (PODT), and 5-(4-pyridyl)-1H-1,2,4-triazole-3-thiol (PTT), and demonstrated that the best level of theory could be chosen based on inner products of DFT-calculated and experimental Raman spectra. We also calculated the theoretical spectra of these Raman reporters bound to Au₂₀ clusters to interrogate how SERS enhancement would affect their spectral fingerprint. Importantly, we found a correlation between B3LYP-D3 calculated and experimental enhancement factors, which opens up an avenue toward predicting which Raman reporters could offer improved sensitivity. We observed 0.5 and 3 fM limits of detection for BMMBP- and PTT-labeled 60 nm AuNPs, respectively.

New advances in using Raman spectroscopy for the characterization of catalysts and catalytic reactions

Gaining insight into the mode of operation of heterogeneous catalysts is of great scientific and economic interest. Raman spectroscopy has proven its potential as a powerful vibrational spectroscopic technique for a fundamental and molecular-level characterization of catalysts and catalytic reactions. Raman spectra provide important insight into reaction mechanisms by revealing specific information on the catalysts' (defect) structure in the bulk and at the surface, as well as the presence of adsorbates and reaction intermediates. Modern Raman instrumentation based on single-stage spectrometers allows high throughput and versatility in design of in situ/operando cells to study working catalysts. This review highlights major advances in the use of Raman spectroscopy for the characterization of heterogeneous catalysts made during the past decade, including the development of new methods and potential directions of research for applying Raman spectroscopy to working catalysts. The main focus will be on gas-solid catalytic reactions, but (photo)catalytic reactions in the liquid phase will be touched on if it appears appropriate. The discussion begins with the main instrumentation now available for applying vibrational Raman spectroscopy to catalysis research, including in situ/operando cells for studying gas-solid catalytic processes. The focus then moves to the different types of information available from Raman spectra in the bulk and on the surface of solid catalysts, including adsorbates and surface depositions, as well as the use of theoretical calculations to facilitate band assignments and to describe (resonance) Raman effects. This is followed by a presentation of major developments in enhancing the Raman signal of heterogeneous catalysts by use of UV resonance Raman spectroscopy, surface-enhanced Raman spectroscopy (SERS), and shell-isolated nanoparticle surface-enhanced Raman spectroscopy (SHINERS). The application of time-resolved Raman studies to structural and kinetic characterization is then discussed. Finally, recent developments in spatially resolved Raman analysis of catalysts and catalytic processes are presented, including the use of coherent anti-Stokes Raman spectroscopy (CARS) and tip-enhanced Raman spectroscopy (TERS). The review concludes with an outlook on potential future developments and applications of Raman spectroscopy in heterogeneous catalysis.

Time-Domain Observation of Surface-Enhanced Coherent Raman Scattering with 105-106 Enhancement

Combining surface-enhanced Raman scattering (SERS) with the coherent nonlinear Raman technique is a promising route for achieving higher sensitivity and time-resolved SERS measurements, yet such attempts have just been started. Here, we report time-domain Raman measurements of trans-1,2-bis(4-pyridyl)ethylene (BPE) adsorbed on gold nanoparticle assemblies (GNAs), which were carried out with impulsive stimulated Raman spectroscopy using sub-8 fs pulses. We observe coherent nuclear wavepacket motion of BPE on GNAs with drastic enhancement through the surface plasmon resonance, which provides information on the Raman-active vibrations in the time domain. Through Fourier transform of the measured time-domain Raman data, we obtained SERS spectra of BPE on GNAs with enhancement factors as high as 10⁵-10⁶. The present study not only demonstrates applicability of time-domain nonlinear Raman techniques in SERS, i.e., surface-enhanced impulsive stimulated Raman spectroscopy (SE-ISRS), but also provides a technical basis for femtosecond time-resolved SE-ISRS experiments to track ultrafast dynamics of the adsorbates.

Machine Learning Protocol for Surface-Enhanced Raman Spectroscopy

Surface-enhanced Raman spectroscopy (SERS) is a powerful technique that can capture the electronic-vibrational "fingerprint" of molecules on surfaces. Ab initio prediction of Raman response is a long-standing challenge because of the diversified interfacial structures. Here we show that a cost-effective machine learning (ML) random forest method can predict SERS signals of a trans-1,2-bis (4-pyridyl) ethylene (BPE) molecule adsorbed on a gold substrate. Using geometric descriptors extracted from quantum chemistry simulations of thousands of ab initio molecular dynamics conformations, the ML protocol predicts vibrational frequencies and Raman intensities. The resulting spectra agree with density functional theory calculations and experiment. Predicted SERS responses of the molecule on different surfaces, or under external fields of electric fields and solvent environment, demonstrate the good transferability of the protocol.