Improving the reliability of machine learned potentials for modeling inhomogeneous liquids.

The atomic-scale response of inhomogeneous fluids at interfaces and surrounding solute particles plays a critical role in governing chemical, electrochemical, and biological processes. Classical molecular dynamics simulations have been applied extensively to simulate the response of fluids to inhomogeneities directly, but are limited by the accuracy of the underlying interatomic potentials. Here, we use neural network potentials (NNPs) trained to ab initio simulations to accurately predict the inhomogeneous responses of two distinct fluids: liquid water and molten NaCl. Although NNPs can be readily trained to model complex bulk systems across a range of state points, we show that to appropriately model a fluid's response at an interface, relevant inhomogeneous configurations must be included in the training data. In order to sufficiently sample appropriate configurations of such inhomogeneous fluids, we develop protocols based on molecular dynamics simulations in the presence of external potentials. We demonstrate that NNPs trained on inhomogeneous fluid configurations can more accurately predict several key properties of fluids-including the density response, surface tension and size-dependent cavitation free energies-for liquid water and molten NaCl, compared to both empirical interatomic potentials and NNPs that are not trained on such inhomogeneous configurations. This work therefore provides a first demonstration and framework to extract the response of inhomogeneous fluids from first principles for classical density-functional treatment of fluids free from empirical potentials.

Fully Ab Initio Approach to Inelastic Atom-Surface Scattering.

We introduce a fully ab initio theory for inelastic scattering of any atom from any surface exciting single phonons, and apply the theory to helium scattering from Nb(100). The key aspect making our approach general is a direct first-principles evaluation of the scattering atom-electron vertex. By correcting misleading results from current state-of-the-art theories, this fully ab initio approach will be critical in guiding and interpreting experiments that adopt next-generation, nondestructive atomic beam scattering.

Improving the Accuracy of Atomistic Simulations of the Electrochemical Interface.

Atomistic simulation of the electrochemical double layer is an ambitious undertaking, requiring quantum mechanical description of electrons, phase space sampling of liquid electrolytes, and equilibration of electrolytes over nanosecond time scales. All models of electrochemistry make different trade-offs in the approximation of electrons and atomic configurations, from the extremes of classical molecular dynamics of a complete interface with point-charge atoms to correlated electronic structure methods of a single electrode configuration with no dynamics or electrolyte. Here, we review the spectrum of simulation techniques suitable for electrochemistry, focusing on the key approximations and accuracy considerations for each technique. We discuss promising approaches, such as enhanced sampling techniques for atomic configurations and computationally efficient beyond density functional theory (DFT) electronic methods, that will push electrochemical simulations beyond the present frontier.

Solvent effects determine the sign of the charges of maximum entropy and capacitance at silver electrodes.

Fully harnessing electrochemical interfaces for reactions requires a detailed understanding of solvent effects in the electrochemical double layer. Predicting the significant impact of solvents on entropic and electronic properties of electrochemical interfaces has remained an open challenge of computational electrochemistry. Using molecular dynamics simulations of silver-water and silver-acetonitrile interfaces, we show that switching the solvent changes the signs for both the charge of maximum capacitance (CMC) and charge of maximum entropy (CME). Contrasting the capacitance and CME behavior of these two interfaces, we demonstrate that the preferred orientation of the solvent molecule and the corresponding charge density determine the sign of the CMC and CME and, hence, the qualitatively different charge asymmetry of the electrochemical interface.

First-principles molten salt phase diagrams through thermodynamic integration.

Precise prediction of phase diagrams in molecular dynamics simulations is challenging due to the simultaneous need for long time and large length scales and accurate interatomic potentials. We show that thermodynamic integration from low-cost force fields to neural network potentials trained using density-functional theory (DFT) enables rapid first-principles prediction of the solid-liquid phase boundary in the model salt NaCl. We use this technique to compare the accuracy of several DFT exchange-correlation functionals for predicting the NaCl phase boundary and find that the inclusion of dispersion interactions is critical to obtain good agreement with experiment. Importantly, our approach introduces a method to predict solid-liquid phase boundaries for any material at an ab initio level of accuracy, with the majority of the computational cost at the level of classical potentials.

Simulating dielectric spectra: A demonstration of the direct electric field method and a new model for the nonlinear dielectric response.

We demonstrate a method to compute the dielectric spectra of fluids in molecular dynamics (MD) by directly applying electric fields to the simulation. We obtain spectra from MD simulations with low magnitude electric fields (≈0.01 V/Å) in agreement with spectra from the fluctuation-dissipation method for water and acetonitrile. We examine this method's trade-off between noise at low field magnitudes and the nonlinearity of the response at higher field magnitudes. We then apply the Booth equation to describe the nonlinear response of both fluids at low frequency (0.1 GHz) and high field magnitude (up to 0.5 V/Å). We develop a model of the frequency-dependent nonlinear response by combining the Booth description of the static nonlinear dielectric response of fluids with the frequency-dependent linear dielectric response of the Debye model. We find good agreement between our model and the MD simulations of the nonlinear dielectric response for both acetonitrile and water.

Interfacial water asymmetry at ideal electrochemical interfaces.

Controlling electrochemical reactivity requires a detailed understanding of the charging behavior and thermodynamics of the electrochemical interface. Experiments can independently probe the overall charge response of the electrochemical double layer by capacitance measurements and the thermodynamics of the inner layer with potential of maximum entropy measurements. Relating these properties by computational modeling of the electrochemical interface has so far been challenging due to the low accuracy of classical molecular dynamics (MD) for capacitance and the limited time and length scales of ab initio MD. Here, we combine large ensembles of long-time-scale classical MD simulations with charge response from electronic density functional theory to predict the potential-dependent capacitance of a family of ideal aqueous electrochemical interfaces with different peak capacitances. We show that while the potential of maximum capacitance varies, this entire family exhibits an electrode charge of maximum capacitance (CMC) between -2.9 and -2.2 µC/cm2, regardless of the details in the electronic response. Simulated heating of the same interfaces reveals that the entropy peaks at a charge of maximum entropy (CME) of -5.1 ± 0.6 µC/cm2, in agreement with experimental findings for metallic electrodes. The CME and CMC both indicate asymmetric response of interfacial water that is stronger for negatively charged electrodes, while the difference between CME and CMC illustrates the richness in behavior of even the ideal electrochemical interface.

Giant Spin Lifetime Anisotropy and Spin-Valley Locking in Silicene and Germanene from First-Principles Density-Matrix Dynamics.

Through first-principles real-time density-matrix (FPDM) dynamics simulations, we investigated spin relaxation due to electron-phonon and electron-impurity scatterings with spin-orbit coupling (SOC) in two-dimensional Dirac materials silicene and germanene at finite temperatures. We discussed the applicability of conventional descriptions of spin relaxation mechanisms by Elliott-Yafet (EY) and D'yakonov-Perel' (DP) compared to the FPDM method, which is determined by a complex interplay of intrinsic SOC, external fields, and scattering strength. For example, the electric field dependence of the spin lifetime by FPDM is close to the DP mechanism for silicene at room temperature but similar to the EY mechanism for germanene. Because of its stronger SOC strength and buckled structure in contrast to graphene, germanene has a giant spin lifetime anisotropy and spin-valley locking effect under nonzero Ez and low temperatures. More importantly, germanene has a long spin lifetime (∼100 ns at 50 K) and an ultrahigh carrier mobility, making it advantageous for spin-valleytronic applications.

Ultrafast hot-hole injection modifies hot-electron dynamics in Au/p-GaN heterostructures.

A fundamental understanding of hot-carrier dynamics in photo-excited metal nanostructures is needed to unlock their potential for photodetection and photocatalysis. Despite numerous studies on the ultrafast dynamics of hot electrons, so far, the temporal evolution of hot holes in metal-semiconductor heterostructures remains unknown. Here, we report ultrafast (t < 200 fs) hot-hole injection from Au nanoparticles into the valence band of p-type GaN. The removal of hot holes from below the Au Fermi level is observed to substantially alter the thermalization dynamics of hot electrons, reducing the peak electronic temperature and the electron-phonon coupling time of the Au nanoparticles. First-principles calculations reveal that hot-hole injection modifies the relaxation dynamics of hot electrons in Au nanoparticles by modulating the electronic structure of the metal on timescales commensurate with electron-electron scattering. These results advance our understanding of hot-hole dynamics in metal-semiconductor heterostructures and offer additional strategies for manipulating the dynamics of hot carriers on ultrafast timescales.

Quantifying Uncertainties in Solvation Procedures for Modeling Aqueous Phase Reaction Mechanisms.

Computational quantum chemistry provides fundamental chemical and physical insights into solvated reaction mechanisms across many areas of chemistry, especially in homogeneous and heterogeneous renewable energy catalysis. Such reactions may depend on explicit interactions with ions and solvent molecules that are nontrivial to characterize. Rigorously modeling explicit solvent effects with molecular dynamics usually brings steep computational costs while the performance of continuum solvent models such as polarizable continuum model (PCM), charge-asymmetric nonlocally determined local-electric (CANDLE), conductor-like screening model for real solvents (COSMO-RS), and effective screening medium method with the reference interaction site model (ESM-RISM) are less well understood for reaction mechanisms. Here, we revisit a fundamental aqueous hydride transfer reaction-carbon dioxide (CO2) reduction by sodium borohydride (NaBH4)-as a test case to evaluate how different solvent models perform in aqueous phase charge migrations that would be relevant to renewable energy catalysis mechanisms. For this system, quantum mechanics/molecular mechanics (QM/MM) molecular dynamics simulations almost exactly reproduced energy profiles from QM simulations, and the Na+ counterion in the QM/MM simulations plays an insignificant role over ensemble averaged trajectories that describe the reaction pathway. However, solvent models used on static calculations gave much more variability in data depending on whether the system was modeled using explicit solvent shells and/or the counterion. We pinpoint this variability due to unphysical descriptions of charge-separated states in the gas phase (i.e., self-interaction errors), and we show that using more accurate hybrid functionals and/or explicit solvent shells lessens these errors. This work closes with recommended procedures for treating solvation in future computational efforts in studying renewable energy catalysis mechanisms.

The electrochemical interface in first-principles calculations.

First-principles predictions play an important role in understanding chemistry at the electrochemical interface. Electronic structure calculations are straightforward for vacuum interfaces, but do not easily account for the interfacial fields and solvation that fundamentally change the nature of electrochemical reactions. Prevalent techniques for first-principles prediction of electrochemical processes range from expensive explicit solvation using ab initio molecular dynamics, through a hierarchy of continuum solvation techniques, to neglecting solvation and interfacial field effects entirely. Currently, no single approach reliably captures all relevant effects of the electrochemical double layer in first-principles calculations. This review systematically lays out the relation between all major approaches to first-principles electrochemistry, including the key approximations and their consequences for accuracy and computational cost. Focusing on ab initio methods for thermodynamic properties of aqueous interfaces, we first outline general considerations for modeling electrochemical interfaces, including solvent and electrolyte dynamics and electrification. We then present the specifics of various explicit and implicit models of the solvent and electrolyte. Finally, we discuss the compromise between computational efficiency and accuracy, and identify key outstanding challenges and future opportunities in the wide range of techniques for first-principles electrochemistry.

Ultrafast Electron Dynamics in Single Aluminum Nanostructures.

Aluminum nanostructures are a promising alternative material to noble metal nanostructures for several photonic and catalytic applications, but their ultrafast electron dynamics remain elusive. Here, we combine single-particle transient extinction spectroscopy and parameter-free first-principles calculations to investigate the non-equilibrium carrier dynamics in aluminum nanostructures. Unlike gold nanostructures, we find the sub-picosecond optical response of lithographically fabricated aluminum nanodisks to be more sensitive to the lattice temperature than the electron temperature. We assign the rise in the transient transmission to electron-phonon coupling with a pump-power-independent lifetime of 500 ± 100 fs and theoretically confirm this strong electron-phonon coupling behavior. We also measure electron-phonon lifetimes in chemically synthesized aluminum nanocrystals and find them to be even longer (1.0 ± 0.1 ps) than for the nanodisks. We also observe a rise and decay in the transient transmissions with amplitudes that scale with the surface-to-volume ratio of the aluminum nanodisks, implying a possible hot carrier trapping and detrapping at the native oxide shell-metal core interface.

Quantification of functional crosslinker reaction kinetics via super-resolution microscopy of swollen microgels.

Super resolution microscopy (SRM) brings the advantages of optical microscopy to the imaging of nanostructured soft matter, and in colloidal microgels, promises to quantify variations of crosslink densities at unprecedented length scales. However, the distribution of all crosslinks does not coincide with that of dye-tagged crosslinks, and density quantification in SRM is not guaranteed due to over/under-counting dye molecules. Here we demonstrate that SRM images of microgels encode reaction rate constants of functional cross linkers, which hold the key to correlating these distributions. Combined with evolution of microgel particle radii, the functional cross linker distributions predict consumption versus time with high fidelity. Using a Bayesian regression approach, we extract reaction rate constants for homo and cross propagation of the functional crosslinker, which should be widely useful for predicting spatial variations in crosslink density of gels.

Dynamics and Spin-Valley Locking Effects in Monolayer Transition Metal Dichalcogenides.

Transition metal dichalcogenides have been the primary materials of interest in the field of valleytronics for their potential in information storage, yet the limiting factor has been achieving long valley decoherence times. We explore the dynamics of four monolayer TMDCs (MoS2, MoSe2, WS2, WSe2) using ab initio calculations to describe electron-electron and electron-phonon interactions. By comparing calculations which both omit and include relativistic effects, we isolate the impact of spin-resolved spin-orbit coupling on transport properties. In our work, we find that spin-orbit coupling increases carrier lifetimes at the valence band edge by an order of magnitude due to spin-valley locking, with a proportional increase in the hole mobility at room temperature. At temperatures of 50 K, we find intervalley scattering times on the order of 100 ps, with a maximum value of ∼140 ps in WSe2. Finally, we calculate excited-carrier generation profiles which indicate that direct transitions dominate across optical energies, even for WSe2 which has an indirect band gap. Our results highlight the intriguing interplay between spin and valley degrees of freedom critical for valleytronic applications. Further, our work points toward interesting quantum properties on-demand in transition metal dichalcogenides that could be leveraged via driving spin, valley, and phonon degrees of freedom.

Improving accuracy of electrochemical capacitance and solvation energetics in first-principles calculations.

Reliable first-principles calculations of electrochemical processes require accurate prediction of the interfacial capacitance, a challenge for current computationally efficient continuum solvation methodologies. We develop a model for the double layer of a metallic electrode that reproduces the features of the experimental capacitance of Ag(100) in a non-adsorbing, aqueous electrolyte, including a broad hump in the capacitance near the potential of zero charge and a dip in the capacitance under conditions of low ionic strength. Using this model, we identify the necessary characteristics of a solvation model suitable for first-principles electrochemistry of metal surfaces in non-adsorbing, aqueous electrolytes: dielectric and ionic nonlinearity, and a dielectric-only region at the interface. The dielectric nonlinearity, caused by the saturation of dipole rotational response in water, creates the capacitance hump, while ionic nonlinearity, caused by the compactness of the diffuse layer, generates the capacitance dip seen at low ionic strength. We show that none of the previously developed solvation models simultaneously meet all these criteria. We design the nonlinear electrochemical soft-sphere solvation model which both captures the capacitance features observed experimentally and serves as a general-purpose continuum solvation model.

Absence of diffuse double layer effect on the vibrational properties and oxidation of chemisorbed carbon monoxide on a Pt(111) electrode.

In this work we investigate the effects of the diffuse double layer thickness on the electrochemical Stark tuning and oxidation of carbon monoxide at Pt(111) surfaces in perchloric acid solution. The diffuse double layer thickness was modified by changing the concentration (ionic strength) of the supporting electrolyte. The Stark tuning slope of the adsorbed CO was evaluated with Fourier Transformed Infrared Spectroscopy, and the CO oxidation was monitored with cyclic voltammetry. The results show that both electrochemical Stark tuning and oxidation are independent of the HClO4 concentration of the supporting electrolyte, revealing the absence of diffuse layer effects on the aqueous Pt(111)/CO system. By comparison to previously reported theoretical calculations, we attribute this insensitivity to the special double layer structure of Pt(111)/CO, in which the potential drop occurs primarily between the terminating oxygen of the adsorbed CO adlayer and first water layer of the electrolyte, making the properties of adsorbed CO nearly independent of the ionic strength of the electrolyte.

Experimental and Ab Initio Ultrafast Carrier Dynamics in Plasmonic Nanoparticles.

Ultrafast pump-probe measurements of plasmonic nanostructures probe the nonequilibrium behavior of excited carriers, which involves several competing effects obscured in typical empirical analyses. Here we present pump-probe measurements of plasmonic nanoparticles along with a complete theoretical description based on first-principles calculations of carrier dynamics and optical response, free of any fitting parameters. We account for detailed electronic-structure effects in the density of states, excited carrier distributions, electron-phonon coupling, and dielectric functions that allow us to avoid effective electron temperature approximations. Using this calculation method, we obtain excellent quantitative agreement with spectral and temporal features in transient-absorption measurements. In both our experiments and calculations, we identify the two major contributions of the initial response with distinct signatures: short-lived highly nonthermal excited carriers and longer-lived thermalizing carriers.

Evaluating continuum solvation models for the electrode-electrolyte interface: Challenges and strategies for improvement.

Ab initio modeling of electrochemical systems is becoming a key tool for understanding and predicting electrochemical behavior. Development and careful benchmarking of computational electrochemical methods are essential to ensure their accuracy. Here, using charging curves for an electrode in the presence of an inert aqueous electrolyte, we demonstrate that most continuum models, which are parameterized and benchmarked for molecules, anions, and cations in solution, undersolvate metal surfaces, and underestimate the surface charge as a function of applied potential. We examine features of the electrolyte and interface that are captured by these models and identify improvements necessary for realistic electrochemical calculations of metal surfaces. Finally, we reparameterize popular solvation models using the surface charge of Ag(100) as a function of voltage to find improved accuracy for metal surfaces without significant change in utility for molecular and ionic solvation.

First-principles electrostatic potentials for reliable alignment at interfaces and defects.

The alignment of electrostatic potential between different atomic configurations is necessary for first-principles calculations of band offsets across interfaces and formation energies of charged defects. However, strong oscillations of this potential at the atomic scale make alignment challenging, especially when atomic geometries change considerably from bulk to the vicinity of defects and interfaces. We introduce a method to suppress these strong oscillations by eliminating the deep wells in the potential at each atom. We demonstrate that this method considerably improves the system-size convergence of a wide range of first-principles predictions that depend on the alignment of electrostatic potentials, including band offsets at solid-liquid interfaces, and formation energies of charged vacancies in solids and at solid surfaces in vacuum. Finally, we use this method in conjunction with continuum solvation theories to investigate energetics of charged vacancies at solid-liquid interfaces. We find that for the example of an NaCl (001) surface in water, solvation reduces the formation energy of charged vacancies by 0.5 eV: calculation of this important effect was previously impractical due to the computational cost in molecular-dynamics methods.