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.

Quantum-mechanical effects in photoluminescence from thin crystalline gold films

Luminescence constitutes a unique source of insight into hot carrier processes in metals, including those in plasmonic nanostructures used for sensing and energy applications. However, being weak in nature, metal luminescence remains poorly understood, its microscopic origin strongly debated, and its potential for unraveling nanoscale carrier dynamics largely unexploited. Here, we reveal quantum-mechanical effects in the luminescence emanating from thin monocrystalline gold flakes. Specifically, we present experimental evidence, supported by first-principles simulations, to demonstrate its photoluminescence origin (i.e., radiative emission from electron/hole recombination) when exciting in the interband regime. Our model allows us to identify changes to the measured gold luminescence due to quantum-mechanical effects as the gold film thickness is reduced. Excitingly, such effects are observable in the luminescence signal from flakes up to 40 nm in thickness, associated with the out-of-plane discreteness of the electronic band structure near the Fermi level. We qualitatively reproduce the observations with first-principles modeling, thus establishing a unified description of luminescence in gold monocrystalline flakes and enabling its widespread application as a probe of carrier dynamics and light-matter interactions in this material. Our study paves the way for future explorations of hot carriers and charge-transfer dynamics in a multitude of material systems.

Nanomolding of Two-Dimensional Materials

Lateral confinement of layered, two-dimensional (2D) materials has uniquely enabled the exploration of several topological phenomena in electron transport due to the well-defined nanoscale cross-sections and perimeters. At present, research on laterally confined 2D materials is constrained by the lack of synthesis methods that can reliably and controllably produce nanostructures with narrow widths and high aspect ratios. We demonstrate the use of thermomechanical nanomolding (TMNM) to fabricate nanowires of six layered materials (Te, In2Se3, Bi2Te3, Bi2Se3, GaSe, and Sb2Te3) with widths of 40 nm and aspect ratios above 100. During molding, the van der Waals (vdW) layers rotate by 90° from the horizontal direction in the bulk feedstock to the vertical direction in the molded nanowire, such that the layers are aligned along the nanowire length. We find that interfacial diffusion and surface energy minimization drive nanowire formation during TMNM, often resulting in single-crystalline nanowires with consistent crystallographic orientation.

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.

How spin relaxes and dephases in bulk halide perovskites

Spintronics in halide perovskites has drawn significant attention in recent years, due to their highly tunable spin-orbit fields and intriguing interplay with lattice symmetry. Here, we perform first-principles calculations to determine the spin relaxation time (T1) and ensemble spin dephasing time ([Formula: see text]) in a prototype halide perovskite, CsPbBr3. To accurately capture spin dephasing in external magnetic fields we determine the Landé g-factor from first principles and take it into account in our calculations. These allow us to predict intrinsic spin lifetimes as an upper bound for experiments, identify the dominant spin relaxation pathways, and evaluate the dependence on temperature, external fields, carrier density, and impurities. We find that the Fröhlich interaction that dominates carrier relaxation contributes negligibly to spin relaxation, consistent with the spin-conserving nature of this interaction. Our theoretical approach may lead to new strategies to optimize spin and carrier transport properties.

Transport and Interfacial Injection of d-Band Hot Holes Control Plasmonic Chemistry

Harnessing nonequilibrium hot carriers from plasmonic metal nanostructures constitutes a vibrant research field with the potential to control photochemical reactions, particularly for solar fuel generation. However, a comprehensive understanding of the interplay of plasmonic hot-carrier-driven processes in metal/semiconducting heterostructures has remained elusive. In this work, we reveal the complex interdependence among plasmon excitation, hot-carrier generation, transport, and interfacial collection in plasmonic photocatalytic devices, uniquely determining the charge injection efficiency at the solid/liquid interface. Measuring the internal quantum efficiency of ultrathin (14-33 nm) single-crystalline plasmonic gold (Au) nanoantenna arrays on titanium dioxide substrates, we find that the performance of the device is limited by hot hole collection at the metal/electrolyte interface. Our solid- and liquid-state experimental approach, combined with ab initio simulations, demonstrates more efficient collection of high-energy d-band holes traveling in the [111] orientation, enhancing oxidation reactions on {111} surfaces. These findings establish new guidelines for optimizing plasmonic photocatalytic systems and optoelectronic devices.

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.

Design of Polymer Nanodielectrics for Capacitive Energy Storage

Polymer nanodielectrics present a particularly challenging materials design problem for capacitive energy storage applications like polymer film capacitors. High permittivity and breakdown strength are needed to achieve high energy density and loss must be low. Strategies that increase permittivity tend to decrease the breakdown strength and increase loss. We hypothesize that a parameter space exists for fillers of modest aspect ratio functionalized with charge-trapping molecules that results in an increase in permittivity and breakdown strength simultaneously, while limiting increases in loss. In this work, we explore this parameter space, using physics-based, multiscale 3D dielectric property simulations, mixed-variable machine learning and Bayesian optimization to identify the compositions and morphologies which lead to the optimization of these competing properties. We employ first principle-based calculations for interface trap densities which are further used in breakdown strength calculations. For permittivity and loss calculations, we use continuum scale modelling and finite difference solution of Poisson's equation for steady-state currents. We propose a design framework for optimizing multiple properties by tuning design variables including the microstructure and interface properties. Finally, we employ mixed-variable global sensitivity analysis to understand the complex interplay between four continuous microstructural and two categorical interface choices to extract further physical knowledge on the design of nanodielectrics.

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.

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 solvent 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 charges of maximum capacitance (CMC) and 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.

Topological Metal MoP Nanowire for Interconnect

The increasing resistance of copper (Cu) interconnects for decreasing dimensions is a major challenge in continued downscaling of integrated circuits beyond the 7 nm technology node as it leads to unacceptable signal delays and power consumption in computing. The resistivity of Cu increases due to electron scattering at surfaces and grain boundaries at the nanoscale. Topological semimetals, owing to their topologically protected surface states and suppressed electron backscattering, are promising candidates to potentially replace current Cu interconnects. Here, we report the unprecedented resistivity scaling of topological metal molybdenum phosphide (MoP) nanowires, and it is shown that the resistivity values are superior to those of nanoscale Cu interconnects <500 nm² cross-section areas. The cohesive energy of MoP suggests better stability against electromigration, enabling a barrier-free design . MoP nanowires are more resistant to surface oxidation than the 20 nm thick Cu. The thermal conductivity of MoP is comparable to those of Ru and Co. Most importantly, it is demonstrated that the dimensional scaling of MoP, in terms of line resistance versus total cross-sectional area, is competitive to those of effective Cu with barrier/liner and barrier-less Ru, suggesting MoP is an attractive alternative for the scaling challenge of Cu interconnects.

Dielectric Properties of Polymer Nanocomposite Interphases Using Electrostatic Force Microscopy and Machine Learning

Knowing the dielectric properties of the interfacial region in polymer nanocomposites is critical to predicting and controlling dielectric properties. They are, however, difficult to characterize due to their nanoscale dimensions. Electrostatic force microscopy (EFM) provides a pathway to local dielectric property measurements, but extracting local dielectric permittivity in complex interphase geometries from EFM measurements remains a challenge. This paper demonstrates a combined EFM and machine learning (ML) approach to measuring interfacial permittivity in 50 nm silica particles in a PMMA matrix. We show that ML models trained to finite-element simulations of the electric field profile between the EFM tip and nanocomposite surface can accurately determine the interface permittivity of functionalized nanoparticles. It was found that for the particles with a polyaniline brush layer, the interfacial region was detectable (extrinsic interface). For bare silica particles, the intrinsic interface was detectable only in terms of having a slightly higher or lower permittivity. This approach fully accounts for the complex interplay of filler, matrix, and interface permittivity on the force gradients measured in EFM that are missed by previous semianalytic approaches, providing a pathway to quantify and design nanoscale interface dielectric properties in nanodielectric materials.

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.

Behavior of Linear and Nonlinear Dimensionality Reduction for Collective Variable Identification of Small Molecule Solution-Phase Reactions

Identifying collective variables (CVs) for chemical reactions is essential to reduce the 3N-dimensional energy landscape into lower dimensional basins and barriers of interest. However, in condensed phase processes, the nonmeaningful motions of bulk solvent often overpower the ability of dimensionality reduction methods to identify correlated motions that underpin collective variables. Yet solvent can play important indirect or direct roles in reactivity, and much can be lost through treatments that remove or dampen solvent motion. This has been amply demonstrated within principal component analysis (PCA), although less is known about the behavior of nonlinear dimensionality reduction methods, e.g., uniform manifold approximation and projection (UMAP), that have become recently utilized. The latter presents an interesting alternative to linear methods though often at the expense of interpretability. This work presents distance-attenuated projection methods of atomic coordinates that facilitate the application of both PCA and UMAP to identify collective variables in the presence of explicit solvent and further the specific identity of solvent molecules that participate in chemical reactions. The performance of both methods is examined in detail for two reactions where the explicit solvent plays very different roles within the collective variables. When applied to raw molecular dynamics data in solution, both PCA and UMAP representations are dominated by bulk solvent motions. On the other hand, when applied to data preprocessed by our attenuated projection methods, both PCA and UMAP identify the appropriate collective variables (though varying sensitivity is observed due to the presence of explicit solvent that results from the projection method). Importantly, this approach allows identification of specific solvent molecules that are relevant to the CVs and their importance.

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 E_z 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.

Resolving the Geometry/Charge Puzzle of the c(2 × 2)-Cl Cu(100) Electrode

Potential-induced changes in charge and surface structure are significant drivers of the reactivity of electrochemical interfaces but are frequently difficult to decouple from the effects of surface solvation. Here, we consider the Cu(100) surface with a c(2 × 2)-Cl adlayer, a model surface with multiple geometry measurements under both ultrahigh vacuum and electrochemical conditions. Under aqueous electrochemical conditions, the measured Cu-Cl interplanar separation (dCu-Cl) increases by at least 0.3 Å relative to that under ultrahigh vacuum conditions. This large geometry change is unexpected for a hydrophobic surface, and it requires invoking a negative charge on the Cl-covered surface which is much greater than expected from the work function and our capacitance measurements. To resolve this inconsistency we employ ab initio calculations and find that the Cu-Cl separation increases with charging at a rate of 0.7 Å/e- per Cl atom. The larger Cu-Cl bond distance increases the surface dipole and, therefore, the work function of the interface, contributing to the negative charge under fixed potential electrochemical conditions. Interactions with water are not needed to explain either the large charge or large Cu-Cl interplanar spacing of this surface under electrochemical conditions.

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.

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.

Coupled Electromagnetic and Reaction Kinetics Simulation of Super-Resolution Interference Lithography

Inspired by the ability of super-resolved fluorescence microscopy to circumvent the diffraction barrier, two-color super-resolution interference lithography exploits nonequilibrium kinetics in materials to achieve large-area nanopatterning while using visible light. Periodic patterns with super-resolved features down to tens of nanometers have been demonstrated in thin films and monolayers. Extending these advances to the bulk nanopatterning of thick films requires a quantitative understanding of the time-dependent interactions of optical dynamics, including absorption, diffraction, and intensity modulation at two wavelengths, with the photoactivated and inhibited reaction kinetics. Here, we develop an efficient electromagnetic (EM) perturbation theory approach that facilitates for the first time fully coupled simulations of EM and chemical kinetics in two-color interference lithography. Applied to a spirothiopyran-functionalized photoresist system, these simulations show that diffraction and absorption effects are negligible (<0.1%) for depths up to 10 μm, and that tuning exposure time and intensities can lead to concentration contrast up to 80%. We investigate multiple exposure strategies to reduce the pitch of the line pattern including sequential exposures with different times to achieve uniform lines and multiplexed exposures with equal periods. This capability to rapidly and accurately predict the coupled optical and chemical dynamics facilitates the computational design of high-precision patterns in two-color interference lithography.

Spin-phonon relaxation from a universal ab initio density-matrix approach

Designing new quantum materials with long-lived electron spin states urgently requires a general theoretical formalism and computational technique to reliably predict intrinsic spin relaxation times. We present a new, accurate and universal first-principles methodology based on Lindbladian dynamics of density matrices to calculate spin-phonon relaxation time of solids with arbitrary spin mixing and crystal symmetry. This method describes contributions of Elliott-Yafet and D'yakonov-Perel' mechanisms to spin relaxation for systems with and without inversion symmetry on an equal footing. We show that intrinsic spin and momentum relaxation times both decrease with increasing temperature; however, for the D'yakonov-Perel' mechanism, spin relaxation time varies inversely with extrinsic scattering time. We predict large anisotropy of spin lifetime in transition metal dichalcogenides. The excellent agreement with experiments for a broad range of materials underscores the predictive capability of our method for properties critical to quantum information science.

Hot-Hole versus Hot-Electron Transport at Cu/GaN Heterojunction Interfaces

Among all plasmonic metals, copper (Cu) has the greatest potential for realizing optoelectronic and photochemical hot-carrier devices, thanks to its CMOS compatibility and outstanding catalytic properties. Yet, relative to gold (Au) or silver (Ag), Cu has rarely been studied and the fundamental properties of its photoexcited hot carriers are not well understood. Here, we demonstrate that Cu nanoantennas on p-type gallium nitride (p-GaN) enable hot-hole-driven photodetection across the visible spectrum. Importantly, we combine experimental measurements of the internal quantum efficiency (IQE) with ab initio theoretical modeling to clarify the competing roles of hot-carrier energy and mean-free path on the performance of hot-hole devices above and below the interband threshold of the metal. We also examine Cu-based plasmonic photodetectors on corresponding n-type GaN substrates that operate via the collection of hot electrons. By comparing hot hole and hot electron photodetectors that employ the same metal/semiconductor interface (Cu/GaN), we further elucidate the relative advantages and limitations of these complementary plasmonic systems. In particular, we find that harnessing hot holes with p-type semiconductors is a promising strategy for plasmon-driven photodetection across the visible and ultraviolet regimes. Given the technological relevance of Cu and the fundamental insights provided by our combined experimental and theoretical approach, we anticipate that our studies will have a broad impact on the design of hot-carrier optoelectronic devices and plasmon-driven photocatalytic systems.

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.

A chiral switchable photovoltaic ferroelectric 1D perovskite

Spin and valley degrees of freedom in materials without inversion symmetry promise previously unknown device functionalities, such as spin-valleytronics. Control of material symmetry with electric fields (ferroelectricity), while breaking additional symmetries, including mirror symmetry, could yield phenomena where chirality, spin, valley, and crystal potential are strongly coupled. Here we report the synthesis of a halide perovskite semiconductor that is simultaneously photoferroelectricity switchable and chiral. Spectroscopic and structural analysis, and first-principles calculations, determine the material to be a previously unknown low-dimensional hybrid perovskite (R)-(-)-1-cyclohexylethylammonium/(S)-(+)-1 cyclohexylethylammonium) PbI₃. Optical and electrical measurements characterize its semiconducting, ferroelectric, switchable pyroelectricity and switchable photoferroelectric properties. Temperature dependent structural, dielectric and transport measurements reveal a ferroelectric-paraelectric phase transition. Circular dichroism spectroscopy confirms its chirality. The development of a material with such a combination of these properties will facilitate the exploration of phenomena such as electric field and chiral enantiomer-dependent Rashba-Dresselhaus splitting and circular photogalvanic effects.

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.

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.

Cellular Automata with Synthetic Image A Secure Image Communication with Transform Domain

    Image encryption has attained a great attention due to the necessity to safeguard confidential images. Digital documents, site images, battlefield photographs, etc. need a secure approach for sharing in an open channel. Hardware – software co-design is a better option for exploiting unique features to cipher the confidential images. Cellular automata (CA) and synthetic image influenced transform domain approach for image encryption is proposed in this paper. The digital image is initially divided into four subsections by applying integer wavelet transform. Confusion is accomplished on low – low section of the transformed image using CA rules 90 and 150. The first level of diffusion with consecutive XORing operation of image pixels is initiated by CA rule 42. A synthetic random key image is developed by extracting true random bits generated by Cyclone V field programmable gate array 5CSEMA5F31C6. This random image plays an important role in second level of diffusion. The proposed confusion and two level diffusion assisted image encryption approach has been validated through the entropy, correlation, histogram, number of pixels change rate, unified average change intensity, contrast and encryption quality analyses.

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.

Increased rise time of electron temperature during adiabatic plasmon focusing

Decay of plasmons to hot carriers has recently attracted considerable interest for fundamental studies and applications in quantum plasmonics. Although plasmon-assisted hot carriers in metals have already enabled remarkable physical and chemical phenomena, much remains to be understood to engineer devices. Here, we present an analysis of the spatio-temporal dynamics of hot electrons in an emblematic plasmonic device, the adiabatic nanofocusing surface-plasmon taper. With femtosecond-resolution measurements, we confirm the extraordinary capability of plasmonic tapers to generate hot carriers by slowing down plasmons at the taper apex. The measurements also evidence a substantial increase of the “lifetime” of the electron gas temperature at the apex. This interesting effect is interpreted as resulting from an intricate heat flow at the apex. The ability to harness the “lifetime” of hot-carrier gases with nanoscale circuits may provide a multitude of applications, such as hot-spot management, nonequilibrium hot-carrier generation, sensing, and photovoltaics.

Knowledge of the electron-gas dynamics in nanometric hot spots is of importance for hot-carrier technologies. Here Lozan et al. present a theoretical and experimental analysis of the spatio-temporal dynamics of hot electrons in a nano-focusing surface-plasmon polariton taper.

JDFTx: software for joint density-functional theory

Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate predictions of new classes of materials and properties, and for connecting to nano- and mesoscale properties using coarse-grained theories. JDFTx is a fully-featured open-source electronic DFT software designed specifically to facilitate rapid development of new theories, models and algorithms. Using an algebraic formulation as an abstraction layer, compact C++11 code automatically performs well on diverse hardware including GPUs (Graphics Processing Units). This code hosts the development of joint density-functional theory (JDFT) that combines electronic DFT with classical DFT and continuum models of liquids for first-principles calculations of solvated and electrochemical systems. In addition, the modular nature of the code makes it easy to extend and interface with, facilitating the development of multi-scale toolkits that connect to ab initio calculations, e.g. photo-excited carrier dynamics combining electron and phonon calculations with electromagnetic simulations.

Electrochemical Capacitance of CO-Terminated Pt(111) Dominated by the CO-Solvent Gap

The distribution of electric fields within the electrochemical double layer depends on both the electrode and electrolyte in complex ways. These fields strongly influence chemical dynamics in the electrode-electrolyte interface but cannot be measured directly with submolecular resolution. We report experimental capacitance measurements for aqueous interfaces of CO-terminated Pt(111). By comparing these measurements with first-principles density functional theory (DFT) calculations, we infer microscopic field distributions and decompose contributions to the inverse capacitance from various spatial regions of the interface. We find that the CO is strongly electronically coupled to the Pt and that most of the interfacial potential difference appears across the gap between the terminating O and water and not across the CO molecule, as previously hypothesized. This "gap capacitance" resulting from hydrophobic termination lowers the overall capacitance of the aqueous Pt-CO interface and makes it less sensitive to electrolyte concentration compared to the bare metal.

Plasmonic tunnel junctions for single-molecule redox chemistry

Nanoparticles attached just above a flat metallic surface can trap optical fields in the nanoscale gap. This enables local spectroscopy of a few molecules within each coupled plasmonic hotspot, with near thousand-fold enhancement of the incident fields. As a result of non-radiative relaxation pathways, the plasmons in such sub-nanometre cavities generate hot charge carriers, which can catalyse chemical reactions or induce redox processes in molecules located within the plasmonic hotspots. Here, surface-enhanced Raman spectroscopy allows us to track these hot-electron-induced chemical reduction processes in a series of different aromatic molecules. We demonstrate that by increasing the tunnelling barrier height and the dephasing strength, a transition from coherent to hopping electron transport occurs, enabling observation of redox processes in real time at the single-molecule level.

Electroless Formation of Hybrid Lithium Anodes for Fast Interfacial Ion Transport

Rechargeable batteries based on metallic anodes are of interest for fundamental and application-focused studies of chemical and physical kinetics of liquids at solid interfaces. Approaches that allow facile creation of uniform coatings on these metals to prevent physical contact with liquid electrolytes, while enabling fast ion transport, are essential to address chemical instability of the anodes. Here, we report a simple electroless ion-exchange chemistry for creating coatings of indium on lithium. By means of joint density functional theory and interfacial characterization experiments, we show that In coatings stabilize Li by multiple processes, including exceptionally fast surface diffusion of lithium ions and high chemical resistance to liquid electrolytes. Indium coatings also undergo reversible alloying reactions with lithium ions, facilitating design of high-capacity hybrid In-Li anodes that use both alloying and plating approaches for charge storage. By means of direct visualization, we further show that the coatings enable remarkably compact and uniform electrodeposition. The resultant In-Li anodes are shown to exhibit minimal capacity fade in extended galvanostatic cycling when paired with commercial-grade cathodes.

Plasmonic hot electron transport drives nano-localized chemistry

Nanoscale localization of electromagnetic fields near metallic nanostructures underpins the fundamentals and applications of plasmonics. The unavoidable energy loss from plasmon decay, initially seen as a detriment, has now expanded the scope of plasmonic applications to exploit the generated hot carriers. However, quantitative understanding of the spatial localization of these hot carriers, akin to electromagnetic near-field maps, has been elusive. Here we spatially map hot-electron-driven reduction chemistry with 15 nm resolution as a function of time and electromagnetic field polarization for different plasmonic nanostructures. We combine experiments employing a six-electron photo-recycling process that modify the terminal group of a self-assembled monolayer on plasmonic silver nanoantennas, with theoretical predictions from first-principles calculations of non-equilibrium hot-carrier transport in these systems. The resulting localization of reactive regions, determined by hot-carrier transport from high-field regions, paves the way for improving efficiency in hot-carrier extraction science and nanoscale regio-selective surface chemistry.

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.

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.

Energy level alignment at semiconductor–water interfaces from atomistic and continuum solvation models

Efficient electronic energy level alignment at solid–liquid interfaces with continuum solvation models.

Partial oxidation of step-bound water leads to anomalous pH effects on metal electrode step-edges

The design of better heterogeneous catalysts for applications such as fuel cells and electrolyzers requires a mechanistic understanding of electrocatalytic reactions and the dependence of their activity on operating conditions such as pH. A satisfactory explanation for the unexpected pH dependence of electrochemical properties of platinum surfaces has so far remained elusive, with previous explanations resorting to complex co-adsorption of multiple species and resulting in limited predictive power. This knowledge gap suggests that the fundamental properties of these catalysts are not yet understood, limiting systematic improvement. Here, we analyze the change in charge and free energies upon adsorption using density-functional theory (DFT) to establish that water adsorbs on platinum step edges across a wide voltage range, including the double-layer region, with a loss of approximately 0.2 electrons upon adsorption. We show how this as-yet unreported change in net surface charge due to this water explains the anomalous pH variations of the hydrogen underpotential deposition (Hupd) and the potentials of zero total charge (PZTC) observed in published experimental data. This partial oxidation of water is not limited to platinum metal step edges, and we report the charge of the water on metal step edges of commonly used catalytic metals, including copper, silver, iridium, and palladium, illustrating that this partial oxidation of water broadly influences the reactivity of metal electrodes.

Nonradiative Plasmon Decay and Hot Carrier Dynamics: Effects of Phonons, Surfaces, and Geometry

The behavior of metals across a broad frequency range from microwave to ultraviolet frequencies is of interest in plasmonics, nanophotonics, and metamaterials. Depending on the frequency, losses of collective excitations in metals can be predominantly classical resistive effects or Landau damping. In this context, we present first-principles calculations that capture all of the significant microscopic mechanisms underlying surface plasmon decay and predict the initial excited carrier distributions so generated. Specifically, we include ab initio predictions of phonon-assisted optical excitations in metals, which are critical to bridging the frequency range between resistive losses at low frequencies and direct interband transitions at high frequencies. In the commonly used plasmonic materials, gold, silver, copper, and aluminum, we find that resistive losses compete with phonon-assisted carrier generation below the interband threshold, but hot carrier generation via direct transitions dominates above threshold. Finally, we predict energy-dependent lifetimes and mean free paths of hot carriers, accounting for electron-electron and electron-phonon scattering, to provide insight toward transport of plasmonically generated carriers at the nanoscale.

Mechanistic Explanation of the pH Dependence and Onset Potentials for Hydrocarbon Products from Electrochemical Reduction of CO on Cu (111)

Energy and environmental concerns demand development of more efficient and selective electrodes for electrochemical reduction of CO2 to form fuels and chemicals. Since Cu is the only pure metal exhibiting reduction to form hydrocarbon chemicals, we focus here on the Cu (111) electrode. We present a methodology for density functional theory calculations to obtain accurate onset electrochemical potentials with explicit constant electrochemical potential and pH effects using implicit solvation. We predict the atomistic mechanisms underlying electrochemical reduction of CO, finding that (1) at acidic pH, the C1 pathway proceeds through COH to CHOH to form CH4 while C2 (C3) pathways are kinetically blocked; (2) at neutral pH, the C1 and C2 (C3) pathways share the COH common intermediate, where the branch to C-C coupling is realized by a novel CO-COH pathway; and (3) at high pH, early C-C coupling through adsorbed CO dimerization dominates, suppressing the C1 pathways by kinetics, thereby boosting selectivity for multi-carbon products.

The charge-asymmetric nonlocally determined local-electric (CANDLE) solvation model

Many important applications of electronic structure methods involve molecules or solid surfaces in a solvent medium. Since explicit treatment of the solvent in such methods is usually not practical, calculations often employ continuum solvation models to approximate the effect of the solvent. Previous solvation models either involve a parametrization based on atomic radii, which limits the class of applicable solutes, or based on solute electron density, which is more general but less accurate, especially for charged systems. We develop an accurate and general solvation model that includes a cavity that is a nonlocal functional of both solute electron density and potential, local dielectric response on this nonlocally determined cavity, and nonlocal approximations to the cavity-formation and dispersion energies. The dependence of the cavity on the solute potential enables an explicit treatment of the solvent charge asymmetry. With four parameters per solvent, this "CANDLE" model simultaneously reproduces solvation energies of large datasets of neutral molecules, cations, and anions with a mean absolute error of 1.8 kcal/mol in water and 3.0 kcal/mol in acetonitrile.