Molecularly Detailed View of Strong Coupling in Supramolecular Plexcitonic Nanohybrids.

Plexcitons constitute a peculiar example of light-matter hybrids (polaritons) originating from the (strong) coupling of plasmonic modes and molecular excitations. Here we propose a fully quantum approach to model plexcitonic systems and test it against existing experiments on peculiar hybrids formed by Au nanoparticles and a well-known porphyrin derivative, involving the Q branch of the organic dye absorption spectrum. Our model extends simpler descriptions of polaritonic systems to account for the multilevel structure of the dyes, spatially varying interactions with a given plasmon mode, and the simultaneous occurrence of plasmon-molecule and intermolecular interactions. By keeping a molecularly detailed view, we were able to gain insights into the local structure and individual contributions to the resulting plexcitons. Our model can be applied to rationalize and predict energy funneling toward specific molecular sites within a plexcitonic assembly, which is highly valuable for designing and controlling chemical transformations in the new polaritonic landscapes.

Peeking into the Femtosecond Hot-Carrier Dynamics Reveals Unexpected Mechanisms in Plasmonic Photocatalysis.

Plasmonic-driven photocatalysis may lead to reaction selectivity that cannot be otherwise achieved. A fundamental role is played by hot carriers, i.e., electrons and holes generated upon plasmonic decay within the metal nanostructure interacting with molecular species. Understanding the elusive microscopic mechanism behind such selectivity is a key step in the rational design of hot-carrier reactions. To accomplish that, we present state-of-the-art multiscale simulations, going beyond density functional theory, of hot-carrier injections for the rate-determining step of a photocatalytic reaction. We focus on carbon dioxide reduction, for which it was experimentally shown that the presence of a rhodium nanocube under illumination leads to the selective production of methane against carbon monoxide. We show that selectivity is due to a (predominantly) direct hole injection from rhodium to the reaction intermediate CHO. Unexpectedly, such an injection does not promote the selective reaction path by favoring proper bond breaking but rather by promoting bonding of the proper molecular fragment to the surface.

Fast-forwarding molecular ground state preparation with optimal control on analog quantum simulators.

We show that optimal control of the electron dynamics is able to prepare molecular ground states, within chemical accuracy, with evolution times approaching the bounds imposed by quantum mechanics. We propose a specific parameterization of the molecular evolution only in terms of interaction already present in the molecular Hamiltonian. Thus, the proposed method solely utilizes quantum simulation routines, retaining their favorable scalings. Due to the intimate relationships between variational quantum algorithms and optimal control, we compare, when possible, our results with state-of-the-art methods in the literature. We found that the number of parameters needed to reach chemical accuracy and algorithmic scaling is in line with compact adaptive strategies to build variational Ansätze. The algorithm, which is also suitable for quantum simulators, is implemented by emulating a digital quantum processor (up to 16 qubits) and tested on different molecules and geometries spanning different degrees of electron correlation.

Time-dependent surface-enhanced Raman scattering: A theoretical approach.

A new procedure for computing the time-dependent Raman scattering of molecules in the proximity of plasmonic nanoparticles (NPs) is proposed, drawing inspiration from the pioneering Lee and Heller's theory. This strategy is based on a preliminary simulation of the molecular vibronic wavefunction in the presence of a plasmonic nanostructure and an incident light pulse. Subsequently, the Raman signal is evaluated through an inverse Fourier Transform of the coefficients' dynamics. Employing a multiscale approach, the system is treated by coupling the quantum mechanical description of the molecule with the polarizable continuum model for the NP. This method offers a unique advantage by providing insights into the time evolution of the plasmon-enhanced Raman signal, tracking the dynamics of the incident electric field. It not only provides for the total Raman signal at the process's conclusion but also gives transient information. Importantly, the flexibility of this approach allows for the simulation of various incident electric field profiles, enabling a closer alignment with experimental setups. This adaptability ensures that the method is relevant and applicable to diverse real-world scenarios.

Energy Transfer to Molecular Adsorbates by Transient Hot Electron Spillover.

Hot electron (HE) photocatalysis is one of the most intriguing fields of nanoscience, with a clear potential for technological impact. Despite much effort, the mechanisms of HE photocatalysis are not fully understood. Here we investigate a mechanism based on transient electron spillover on a molecule and subsequent energy release into vibrational modes. We use state-of-the-art real-time Time Dependent Density Functional Theory (rt-TDDFT), simulating the dynamics of a HE moving within linear chains of Ag or Au atoms, on which CO, N2, or H2O are adsorbed. We estimate the energy a HE can release into adsorbate vibrational modes and show that certain modes are selectively activated. The energy transfer strongly depends on the adsorbate, the metal, and the HE energy. Considering a cumulative effect from multiple HEs, we estimate this mechanism can transfer tenths of an eV to molecular vibrations and could play an important role in HE photocatalysis.

Effective Single-Mode Methodology for Strongly Coupled Multimode Molecular-Plasmon Nanosystems.

Strong coupling between molecules and quantized fields has emerged as an effective methodology to engineer molecular properties. New hybrid states are formed when molecules interact with quantized fields. Since the properties of these states can be modulated by fine-tuning the field features, an exciting and new side of chemistry can be explored. In particular, significant modifications of the molecular properties can be achieved in plasmonic nanocavities, where the field quantization volume is reduced to subnanometric volumes, thus leading to intriguing applications such as single-molecule imaging and high-resolution spectroscopy. In this work, we focus on phenomena where the simultaneous effects of multiple plasmonic modes are critical. We propose a theoretical methodology to account for many plasmonic modes simultaneously while retaining computational feasibility. Our approach is conceptually simple and allows us to accurately account for the multimode effects and rationalize the nature of the interaction between multiple plasmonic excitations and molecules.

Data-Driven Predetermination of Cu Oxidation State in Copper Nanoparticles: Application to the Synthesis by Laser Ablation in Liquid.

Copper-based nanocrystals are reference nanomaterials for integration into emerging green technologies, with laser ablation in liquid (LAL) being a remarkable technique for their synthesis. However, the achievement of a specific type of nanocrystal, among the whole library of nanomaterials available using LAL, has been until now an empirical endeavor based on changing synthesis parameters and characterizing the products. Here, we started from the bibliographic analysis of LAL synthesis of Cu-based nanocrystals to identify the relevant physical and chemical features for the predetermination of copper oxidation state. First, single features and their combinations were screened by linear regression analysis, also using a genetic algorithm, to find the best correlation with experimental output and identify the equation giving the best prediction of the LAL results. Then, machine learning (ML) models were exploited to unravel cross-correlations between features that are hidden in the linear regression analysis. Although the LAL-generated Cu nanocrystals may be present in a range of oxidation states, from metallic copper to cuprous oxide (Cu2O) and cupric oxide (CuO), in addition to the formation of other materials such as Cu2S and CuCN, ML was able to guide the experiments toward the maximization of the compounds in the greatest demand for integration in sustainable processes. This approach is of general applicability to other nanomaterials and can help understand the origin of the chemical pathways of nanocrystals generated by LAL, providing a rational guideline for the conscious predetermination of laser-synthesis parameters toward the desired compounds.

Enhancing Tungsten Oxide Gasochromism with Noble Metal Nanoparticles: The Importance of the Interface.

Crystalline tungsten trioxide (WO3 ) thin films covered by noble metal (gold and platinum) nanoparticles are synthesized via wet chemistry and used as optical sensors for gaseous hydrogen. Sensing performances are strongly influenced by the catalyst used, with platinum (Pt) resulting as best. Surprisingly, it is found that gold (Au) can provide remarkable sensing activity that tuned out to be strongly dependent on the nanoparticle size: devices sensitized with smaller nanoparticles display better H2 sensing performance. Computational insight based on density functional theory calculations suggested that this can be related to processes occurring specifically at the Au nanoparticle-WO3 interface (whose extent is in fact dependent on the nanoparticle size), where the hydrogen dissociative adsorption turns out to be possible. While both experiments and calculations single out Pt as better than Au for sensing, the present work reveals how an exquisitely nanoscopic effect can yield unexpected sensing performance for Au on WO3 , and how these performances can be tuned by controlling the nanoscale features of the system.

Unraveling the electronic origin of a special feature in the triplet-minus-singlet spectra of carotenoids in natural photosystems.

The influence of carotenoid triplet states on the Qy electronic transitions of chlorophylls has been observed in experiments on light-harvesting complexes over the past three decades, but the interpretation of the resulting spectral feature in the triplet minus singlet (T-S) absorption spectra of photosystems is still debated, as the physical-chemical explanation of this feature has been elusive. Here, we resolve this debate, by explaining the T-S spectra of pigment complexes over the Qy-band spectral region through a comparative study of chlorophyll-carotenoid model dyads and larger pigment complexes from the main light harvesting complex of higher plants (LHCII). This goal is achieved by combining state-of-the-art time-dependent density functional theory with analysis of the relationship between electronic properties and nuclear structure, and by comparison to the experiment. We find that the special signature in the T-S spectra of both model and natural photosystems is determined by singlet-like triplet excitations that can be described as effective singlet excitations on chlorophylls influenced by a stable electronic triplet on the carotenoid. The comparison with earlier experiments on different light-harvesting complexes confirms our theoretical interpretation of the T-S spectra in the Qy spectral region. Our results indicate an important role for the chlorophyll-carotenoid electronic coupling, which is also responsible for the fast triplet-triplet energy transfer, suggesting a fast trapping of the triplet into the relaxed carotenoid structure. The gained understanding of the interplay between the electronic and nuclear structures is potentially informative for future studies of the mechanism of photoprotection by carotenoids.

Exploring AuRh Nanoalloys: A Computational Perspective on the Formation and Physical Properties.

We studied the formation of AuRh nanoalloys (between 20-150 atoms) in the gas phase by means of Molecular Dynamics (MD) calculations, exploring three possible formation processes: one-by-one growth, coalescence, and nanodroplets annealing. As a general trend, we recover a predominance of Rh@Au core-shell ordering over other chemical configurations. We identify new structural motifs with enhanced thermal stabilities. The physical features of those selected systems were studied at the Density Functional Theory (DFT) level, revealing profound correlations between the nanoalloys morphology and properties. Surprisingly, the arrangement of the inner Rh core seems to play a dominant role on nanoclusters' physical features like the HOMO-LUMO gap and magnetic moment. Strong charge separations are recovered within the nanoalloys suggesting the existence of charge-transfer transitions.

Inverse design of molecule-metal nanoparticle systems interacting with light for desired photophysical properties.

Molecules close to a metal nanoparticle (NP) have significantly different photophysical properties from those of the isolated one. In order to harness the potential of the molecule-NP system, appropriate design guidelines are required. Here, we propose an inverse design method of the optimal molecule-NP systems and incident electric field for desired photophysical properties. It is based on a gradient-based optimization search within the time-dependent quantum chemical description for the molecule and the continuum model for the metal NP. We designed the optimal molecule, relative molecule-NP spatial conformation, and incident electric field of a molecule-NP system to maximize the population transfer to the target electronic state of the molecule. The design results were presented and discussed. The present method is promising as the basis for designing molecule-NP systems and incident fields and accelerates discoveries of efficient molecular plasmonics systems.

Time Resolved Raman Scattering of Molecules: A Quantum Mechanics Approach with Stochastic Schroedinger Equation.

Raman scattering is a very powerful tool employed to characterize molecular systems. Here we propose a novel theoretical strategy to calculate the Raman cross-section in time domain, by computing the cumulative Raman signal emitted during the molecular evolution in time. Our model is based on a numerical propagation of the vibronic wave function under the effect of a light pulse of arbitrary shape. This approach can therefore tackle a variety of experimental setups. Both resonance and nonresonance Raman scattering can be retrieved, and also the time-dependent fluorescence emission is computed. The model has been applied to porphyrin considering both resonance and nonresonance conditions and varying the incident field duration. Moreover the effect of the vibrational relaxation, which should be taken into account when its time scale is similar to that of the Raman emission, has been included through the stochastic Schroedinger equation approach.

Strong Coupling between Localized Surface Plasmons and Molecules by Coupled Cluster Theory.

Plasmonic nanocavities enable the confinement of molecules and electromagnetic fields within nanometric volumes. As a consequence, the molecules experience a remarkably strong interaction with the electromagnetic field to such an extent that the quantum states of the system become hybrids between light and matter: polaritons. Here, we present a nonperturbative method to simulate the emerging properties of such polaritons: it combines a high-level quantum chemical description of the molecule with a quantized description of the localized surface plasmons in the nanocavity. We apply the method to molecules of realistic complexity in a typical plasmonic nanocavity, featuring also a subnanometric asperity (picocavity). Our results disclose the effects of the mutual polarization and correlation of plasmons and molecular excitations, disregarded so far. They also quantify to what extent the molecular charge density can be manipulated by nanocavities and stand as benchmarks to guide the development of methods for molecular polaritonics.

Role of Ionic Strength in the Formation of Stable Supramolecular Nanoparticle-Protein Conjugates for Biosensing.

Monolayer-protected gold nanoparticles (AuNPs) exhibit distinct physical and chemical properties depending on the nature of the ligand chemistry. A commonly employed NP monolayer comprises hydrophobic molecules linked to a shell of PEG and terminated with functional end group, which can be charged or neutral. Different layers of the ligand shell can also interact in different manners with proteins, expanding the range of possible applications of these inorganic nanoparticles. AuNP-fluorescent Green Fluorescent Protein (GFP) conjugates are gaining increasing attention in sensing applications. Experimentally, their stability is observed to be maintained at low ionic strength conditions, but not at physiologically relevant conditions of higher ionic strength, limiting their applications in the field of biosensors. While a significant amount of fundamental work has been done to quantify electrostatic interactions of colloidal nanoparticle at the nanoscale, a theoretical description of the ion distribution around AuNPs still remains relatively unexplored. We perform extensive atomistic simulations of two oppositely charged monolayer-protected AuNPs interacting with fluorescent supercharged GFPs co-engineered to have complementary charges. These simulations were run at different ionic strengths to disclose the role of the ionic environment on AuNP-GFP binding. The results highlight the capability of both AuNPs to intercalate ions and water molecules within the gold-sulfur inner shell and the different tendency of ligands to bend inward allowing the protein to bind not only with the terminal ligands but also the hydrophobic alkyl chains. Different binding stability is observed in the two investigated cases as a function of the ligand chemistry.

Atomistic Simulations of Functionalized Nano-Materials for Biosensors Applications.

Nanoscale biosensors, a highly promising technique in clinical analysis, can provide sensitive yet label-free detection of biomolecules. The spatial and chemical specificity of the surface coverage, the proper immobilization of the bioreceptor as well as the underlying interfacial phenomena are crucial elements for optimizing the performance of a biosensor. Due to experimental limitations at the microscopic level, integrated cross-disciplinary approaches that combine in silico design with experimental measurements have the potential to present a powerful new paradigm that tackles the issue of developing novel biosensors. In some cases, computational studies can be seen as alternative approaches to assess the microscopic working mechanisms of biosensors. Nonetheless, the complex architecture of a biosensor, associated with the collective contribution from "substrate-receptor-analyte" conjugate in a solvent, often requires extensive atomistic simulations and systems of prohibitive size which need to be addressed. In silico studies of functionalized surfaces also require ad hoc force field parameterization, as existing force fields for biomolecules are usually unable to correctly describe the biomolecule/surface interface. Thus, the computational studies in this field are limited to date. In this review, we aim to introduce fundamental principles that govern the absorption of biomolecules onto functionalized nanomaterials and to report state-of-the-art computational strategies to rationally design nanoscale biosensors. A detailed account of available in silico strategies used to drive and/or optimize the synthesis of functionalized nanomaterials for biosensing will be presented. The insights will not only stimulate the field to rationally design functionalized nanomaterials with improved biosensing performance but also foster research on the required functionalization to improve biomolecule-surface complex formation as a whole.

Atomistic simulations of gold surface functionalization for nanoscale biosensors applications.

A wide class of biosensors can be built via functionalization of gold surface with proper bio conjugation element capable of interacting with the analyte in solution, and the detection can be performed either optically, mechanically or electrically. Any change in physico-chemical environment or any slight variation in mass localization near the surface of the sensor can cause differences in nature of the transduction mechanism. The optimization of such sensors may require multiple experiments to determine suitable experimental conditions for the immobilization and detection of the analyte. Here, we employ molecular modeling techniques to assist the optimization of a gold-surface biosensor. The gold surface of a quartz-crystal-microbalance sensor is functionalized using polymeric chains of poly(ethylene glycol) (PEG) of 2 KDa molecular weight, which is an inert long chain amphiphilic molecule, supporting biotin molecules (bPEG) as the ligand molecules for streptavidin analyte. The PEG linkers are immobilized onto the gold surface through sulphur chemistry. Four gold surfaces with different PEG linker density and different biotinylation ratio between bPEG and PEG, are investigated by means of state-of-the art atomistic simulations and compared with available experimental data. Results suggest that the amount of biotin molecules accessible for the binding with the protein increases upon increasing the linkers density. At the high density a 1:1 ratio of bPEG/PEG can further improve the accessibility of the biotin ligand due to a strong repulsion between linker chains and different degree of hydrophobicity between bPEG and PEG linkers. The study provides a computaional protocol to model sensors at the level of single molecular interactions, and for optimizing the physical properties of surface conjugated ligand which is crucial to enhance output of the sensor.

Proline isomerization effects in the amyloidogenic protein ß2-microglobulin.

The protein ß2-microglobulin (ß2-m) can aggregate in insoluble amyloid fibrils, which deposit in the skeletal muscle system of patients undergoing long-term haemodialysis. The molecular mechanisms of such amyloidogenesis are still not fully understood. A potential, although debated, triggering factor is the cis to trans isomerization of a specific proline (Pro32) in ß2-m. Here we investigate this process in the native protein and in the aggregation-prone mutant D76N by means of molecular dynamics and the enhanced sampling method metadynamics. Our simulations, including the estimation of the free energy difference between the cis and trans isomers, are in good agreement with in vitro experiments and highlight the importance of the hydrogen bond and hydrophobic interaction network around the critical Pro32 in stabilizing and de-stabilizing the two isomers.

LayerPCM: An implicit scheme for dielectric screening from layered substrates.

We present LayerPCM, an extension of the polarizable-continuum model coupled to real-time time-dependent density-functional theory, for an efficient and accurate description of the electrostatic interactions between molecules and multilayered dielectric substrates on which they are physisorbed. The former are modeled quantum-mechanically, while the latter are treated as polarizable continua characterized by their dielectric constants. The proposed approach is purposely designed to simulate complex hybrid heterostructures with nano-engineered substrates including a stack of anisotropic layers. LayerPCM is suitable for describing the polarization-induced renormalization of frontier energy levels of the adsorbates in the static regime. Moreover, it can be reliably applied to simulating laser-induced ultrafast dynamics of molecules through the inclusion of electric fields generated by Fresnel-reflection at the substrate. Depending on the complexity of the underlying layer structure, such reflected fields can assume non-trivial shapes and profoundly affect the dynamics of the photo-excited charge carriers in the molecule. In particular, the interaction with the substrate can give rise to strong delayed fields, which lead to interference effects resembling those of multi-pulse-based spectroscopy. The robustness of the implementation and the above-mentioned features are demonstrated with a number of examples, ranging from intuitive models to realistic systems.

Role of metal-nanostructure features on tip-enhanced photoluminescence of single molecules.

Tip-enhanced photoluminescence (TEPL) experiments have recently reached the ability to investigate single molecules exploiting resolution at the submolecular level. Localized surface plasmon resonances of metallic nanostructures have the capability of enhancing an impinging electromagnetic radiation in the proximity of their surface, with evident consequences both on absorption and emission of molecules placed in the same region. We propose a theoretical analysis of these phenomena in order to interpret TEPL experiments on single molecules, including a quantum mechanical description of the target molecule equilibrated with the presence of two nanostructures representative of the nanocavity usually employed in STMs. The approach has been applied to the zinc phthalocyanine molecule, previously considered in recent TEPL experiments [Yang et al., Nat. Photonics 14, 693-699 (2020)]. This work has the aim of providing a comprehensive theoretical understanding of the experimental results, particularly focusing on the investigation of the tip features that majorly influence the excitation and fluorescence processes of the molecule, such as the geometry, the dielectric function, and the tip-molecule distance.

Molecular Dynamics Simulations of a Catalytic Multivalent Peptide-Nanoparticle Complex.

Molecular modeling of a supramolecular catalytic system is conducted resulting from the assembling between a small peptide and the surface of cationic self-assembled monolayers on gold nanoparticles, through a multiscale iterative approach including atomistic force field development, flexible docking with Brownian Dynamics and µs-long Molecular Dynamics simulations. Self-assembly is a prerequisite for the catalysis, since the catalytic peptides do not display any activity in the absence of the gold nanocluster. Atomistic simulations reveal details of the association dynamics as regulated by defined conformational changes of the peptide due to peptide length and sequence. Our results show the importance of a rational design of the peptide to enhance the catalytic activity of peptide-nanoparticle conjugates and present a viable computational approach toward the design of enzyme mimics having a complex structure-function relationship, for technological and nanomedical applications.