Recent Advances in Real-Time Time-Dependent Density Functional Theory Simulations of Plasmonic Nanostructures and Plasmonic Photocatalysis

Computational Discovery of Design Principles for Plasmon-Driven Bond Activation on Alloy Antenna Reactors

Plasmonic "antenna reactor" alloys, consisting of a plasmonic material doped with a catalytically active metal, show great promise for efficient photocatalysis. However, while simple, intuitive, and approximate design principles such as the Sabatier principle have been developed for thermal and electrocatalysis, similar design principles for plasmonic catalysts remain elusive. Here, we develop these simple design principles by using real-time, time-dependent density functional theory to study small molecule activation (CH4, CO2, H2O, and N2) on a number of Cu-based antenna reactors and elucidate trends. We first show that this technique gives results consistent with experimental plasmonic catalysis studies. We then identify promising, previously untested antenna reactors for these molecules. Next, we find that, for a given molecule, bond activation correlates with the size of the charge oscillations between the nanoparticle and molecule as quantified by the standard deviation over the propagation time. Furthermore, the orbital overlap between the dopant and molecule also roughly correlates with the bond activation. For CH4, N2, and H2O, a greater overlap leads to higher activation. For CO2, the trend is reversed because a greater overlap leads to higher chemical activation upon adsorption, which inhibits photoactivation. Hence, the orbital overlap can be used as a computationally efficient and intuitively simple predictor of photoactivation for the initial screening of plasmonic catalysts.

Simulation of 24,000 Electron Dynamics: Real-Time Time-Dependent Density Functional Theory (TDDFT) with the Real-Space Multigrids (RMG)

We present the theory, implementation, and benchmarking of a real-time time-dependent density functional theory (RT-TDDFT) module within the RMG code, designed to simulate the electronic response of molecular systems to external perturbations. Our method offers insights into nonequilibrium dynamics and excited states across a diverse range of systems, from small organic molecules to large metallic nanoparticles. Benchmarking results demonstrate excellent agreement with established TDDFT implementations and showcase the superior stability of our time integration algorithm, enabling long-term simulations with minimal energy drift. The scalability and efficiency of RMG on massively parallel architectures allow for simulations of complex systems, such as plasmonic nanoparticles with thousands of atoms. Future extensions, including nuclear and spin dynamics, will broaden the applicability of this RT-TDDFT implementation, providing a powerful toolset for studies of photoactive materials, nanoscale devices, and other systems where real-time electronic dynamics is essential.

Plasmon Dynamics in Nanoclusters: Dephasing Revealed by Excited States Evaluation

The photocatalytic efficiency of materials such as graphene and noble metal nanoclusters depends on their plasmon lifetimes. Plasmon dephasing and decay in these materials is thought to occur on ultrafast time scales, ranging from a few femtoseconds to hundreds of femtoseconds and longer. Here we focus on understanding the dephasing and decay pathways of excited states in small lithium and silver clusters and in plasmonic states of the π-conjugated molecule anthracene, providing insights that are crucial for interpreting optical properties and photophysics. To do this, we study the time dependence of the electronic density matrix of these molecules using a new approach that expresses the density matrix in terms of TDDFT eigenstates (ESs) of the TDDFT Hamiltonian. This approach, which involves combining linear response time-dependent density functional theory (LR-TDDFT) and real-time time-dependent density functional theory (RT-TDDFT), leads to an analysis of the electron dynamics in terms of ESs, rather than individual molecular orbital (MO) transitions as has typically been done. This circumvents the complexities and subjective biases that traditional MO-based analysis provides. We find in an analysis of the induced dipole moment in these molecules that what had previously been considered to be energy relaxation is actually dephasing associated with the eigenstates that are stationary after the excitation pulse is turned off. We conclude that the ES-basis analysis has significant potential to advance understanding of the electron dynamics of plasmonic nanomaterials, aiding their optimization for photocatalytic and technological applications.

Machine-Learning Electron Dynamics with Moment Propagation Theory: Application to Optical Absorption Spectrum Computation Using Real-Time TDDFT

We present an application of our new theoretical formulation of quantum dynamics, moment propagation theory (MPT) (Boyer et al., J. Chem. Phys. 160, 064113 (2024)), for employing machine-learning techniques to simulate the quantum dynamics of electrons. In particular, we use real-time time-dependent density functional theory (RT-TDDFT) simulation in the gauge of the maximally localized Wannier functions (MLWFs) for training the MPT equation of motion. Spatially localized time-dependent MLWFs provide a concise representation that is particularly convenient for the MPT expressed in terms of increasing orders of moments. The equation of motion for these moments can be integrated in time, while the analytical expressions are quite involved. In this work, machine-learning techniques were used to train the second-order time derivatives of the moments using first-principles data from the RT-TDDFT simulation, and this MPT enabled us to perform electron dynamics efficiently. The application to computing optical absorption spectrum for various systems was demonstrated as a proof-of-principles example of this approach. In addition to isolated molecules (water, benzene, and ethene), condensed matter systems (liquid water and crystalline silicon) were studied, and we also explored how the principle of the nearsightedness of electrons can be employed in this context.

Strong-field effects in the photo-induced dissociation of the hydrogen molecule on a silver nanoshell

Plasmonic catalysis is a rapidly growing field of research, both from experimental and computational perspectives. Experimental observations demonstrate an enhanced dissociation rate for molecules in the presence of plasmonic nanoparticles under low-intensity visible light. The hot-carrier transfer from the nanoparticle to the molecule is often claimed as the mechanism for dissociation. However, the charge transfer time scale is on the order of a few femtoseconds and cannot be resolved experimentally. In this situation, ab initio non-adiabatic calculations can provide a solution. Such simulations, however, have their own limitations related to the computational cost. To accelerate plasmonic catalysis simulations, many researchers resort to applying high-intensity external fields to nanoparticle-molecule systems. Here, we show why such an approach can be problematic and emphasize the importance of considering strong-field effects when interpreting the results of time-dependent density functional theory simulations of plasmonic catalysis. By studying the hydrogen molecule dissociation on the surface of a silver nanoshell and analyzing the electron transfer at different field frequencies and high intensities, we demonstrate that the molecule dissociates due to multiphoton absorption and subsequent ionization.

Noise reduction of stochastic density functional theory for metals

Density Functional Theory (DFT) has become a cornerstone in the modeling of metals. However, accurately simulating metals, particularly under extreme conditions, presents two significant challenges. First, simulating complex metallic systems at low electron temperatures is difficult due to their highly delocalized density matrix. Second, modeling metallic warm-dense materials at very high electron temperatures is challenging because it requires the computation of a large number of partially occupied orbitals. This study demonstrates that both challenges can be effectively addressed using the latest advances in linear-scaling stochastic DFT methodologies. Despite the inherent introduction of noise into all computed properties by stochastic DFT, this research evaluates the efficacy of various noise reduction techniques under different thermal conditions. Our observations indicate that the effectiveness of noise reduction strategies varies significantly with the electron temperature. Furthermore, we provide evidence that the computational cost of stochastic DFT methods scales linearly with system size for metal systems, regardless of the electron temperature regime.

Bond Selective Photochemistry at Metal Nanoparticle Surfaces: CO Desorption from Pt and Pd

The use of visible photon fluxes to influence catalytic reactions on metal nanoparticle surfaces has attracted attention based on observations of reaction mechanisms and selectivity not observed under equilibrium heating. These observations suggest that photon fluxes can selectively impact the rates of certain elementary steps, creating nonequilibrium energy distributions among various reaction pathways. However, quantitative studies validating these hypotheses on metal nanoparticle surfaces are lacking. We examine the influence of continuous wave visible photon fluxes on the CO desorption rates from 1 to 2 nm diameter Pt and Pd nanoparticle surfaces supported on γ-Al2O3. Temperature-programmed desorption measurements quantified via diffuse reflectance infrared Fourier transform spectroscopy demonstrate that visible photon fluxes significantly enhanced the rate of CO desorption from Pt nanoparticles in a wavelength-dependent manner. 440 nm photons most efficiently promoted CO desorption from Pt nanoparticle surfaces, aligning with the excitation energy for the interfacial electronic transition within the Pt-CO bond. Conversely, visible photon fluxes had no measurable influence on CO desorption rates from Pd nanoparticle surfaces after accounting for photon-induced heating. Density functional theory calculations demonstrate that the Pt-CO bond exhibits a narrower LUMO resonance, stronger coupling between the photoexcitation and forces induced on the metal-C bond, and vibrational energy dissipation that more effectively couples to desorption as compared to Pd-CO. These results demonstrate the specificity photons provide in facilitating chemical reactions on metal nanoparticle surfaces and substantiate the idea that photon fluxes can steer processes and outcomes of catalytic reactions in ways not achievable by equilibrium heating.

Effects of Nanowire Doping on Plasmon-Enhanced N2 Dissociation

Doping a transition metal element into plasmonic systems can tune the optical properties of the system, which will potentially facilitate the plasmon-enhanced catalytic process. In this study, we applied the linear-response time-dependent density functional theory (LR-TDDFT) method with real-time electron dynamics and mean-field Ehrenfest dynamics methods to computationally investigate the effects of doping silver nanowires on plasmon-enhanced N2 dissociation. We calculated the absorption spectra for different doped systems, applied an external electric field to the system, and performed mean-field Ehrenfest dynamics to examine how plasmonic excitation will affect the N2 activation or dissociation. In addition, we also studied how the transition metal dopant affects the system's electronic structure and potential energy surface.

Plasmon-induced hot carrier distribution in a composite nanosystem: role of the adsorption site

The generation of hot carriers (HCs) through the excitation of localized surface plasmon resonance (LSPR) in metal nanostructures is a fascinating phenomenon that fuels both fundamental and applied research. However, gaining insights into HCs at a microscopic level has posed a complex challenge, limiting our ability to create efficient nanoantennas that utilize these energized carriers. In this investigation, we employ real-time time-dependent density functional theory (rt-TDDFT) calculations to examine the creation and distribution of HCs within a model composite system consisting of a silver (Ag) nanodisk and a carbon monoxide (CO) molecule. We find that the creation and distribution of HCs are notably affected by the CO adsorption site. Particularly, when the CO molecule adsorbs onto the hollow site of the Ag nanodisk, it exhibits the highest potential among various composite systems in terms of structural stability, enhanced orbital hybridization, and HC generation and transfer. Utilizing a Gaussian laser pulse adjusted to match the LSPR frequency, we observe a marked buildup of hot electrons and hot holes on the C and O atoms. Conversely, the region encompassing the C-O bond exhibits a depletion of hot electrons and hot holes. We believe that these findings could have significant implications in the field of HC photocatalysis.