Search

First-principles calculations for electrochemistry require accurate treatment of both electronic structure and solvation. The perturbative GW approximation starting from density functional theory (DFT) calculations accurately models materials systems with varying dimensionality. Continuum solvation models enable efficient treatment of solvation effects in DFT calculations, but their applications with beyond-DFT electronic structure methods such as GW have been limited. Here, we introduce the frequency-dependent liquid polarizability from a nonlocal continuum solvation model in the screened Coulomb interaction of full-frequency GW calculations with a solvated DFT starting point. We show that the liquid screening contributions substantially reduce the HOMO-LUMO gap of molecules by 3 - 5 eV, while solvent effects on the DFT starting point negligibly impact the GW gap. The resulting framework facilitates the simultaneous electronic and solvation accuracy needed for first-principles electrochemistry.

We used machine learning (ML) to accurately predict eigenvalues of the hybrid HSE06 functional using eigenvalues computed by the less computationally expensive PBE and associated electronic features based on the k-point resolved atomic band char- acter. The ML model was trained using eigenvalues from only one k-point for each of the 168 compounds in the training set. The HSE06 eigenvalues across all k-points were then predicted for a separate set of 169 compounds with a mean absolute error (MAE) of 0.13 eV, representing a significant improvement over the error of PBE-computed eigenvalues relative to HSE06 (0.96 eV). These accurately predicted eigenvalues result in remarkably accurate predictions for the band structures, projected density of states and band gaps, even though the model was not explicitly trained on these other prop- erties. Finally, we demonstrate that our ML model has a similar accuracy for both ternary and quaternary compounds well outside the initial training set and on systems with 112 and 160 atoms, demonstrating its potential to rapidly predict HSE06-quality electronic structures of complex materials that are practically unfeasible for HSE06.

The electrochemical nitrogen reduction reaction (NRR) is a promising route to enable carbon-free ammonia production. However, it is limited by the poor activity and selectivity of current catalysts. The rational design of superior NRR electrocatalysts requires a detailed mechanistic understanding of current material limitations to inform how these can be overcome. The current understanding of how scaling limits NRR on metal catalysts is predicated on a simplified reaction pathway that only considers proton-coupled electron transfer (PCET) steps. Here, we apply grand canonical density functional theory to investigate a more comprehensive NRR mechanism that includes both electrochemical and chemical steps on 23 metal surfaces in solvent under an applied potential. We applied Φmax, a grand canonical adaptation of the Gmax descriptor, to evaluate trends in catalyst activity. This approach produces a Φmax “volcano” diagram for NRR activity scaling on metals that qualitatively differs from the scaling relations identified when only PCET steps are considered. NH3* desorption was found to limit NRR activity for materials at the top of the volcano and truncates the volcano’s peak at increasingly reducing potentials. These revised scaling relations may inform the rational design of superior NRR electrocatalysts. This approach is transferable to study additional materials and reaction chemistries where both electrochemical and chemical steps are modeled under an applied potential.

Identifying collective variables (CVs) for chemical reactions is essential to reduce the 3

Metal nanostructures capture light efficiently due to plasmonic enhancement and generate energetic electrons and holes that can be used to drive chemical reactions or transferred across metal–semiconductor interfaces for solar cells and photodetectors. The overall efficiency of plasmonic hot-carrier devices depends on the generated energy distribution, on its evolution with transport through the metal, and, most critically, on the transport across the metal surface or interface. Here, we review the mechanistic considerations, strategies, and challenges for efficient hot-carrier extraction, highlighting the need for new materials to transport carriers with minimal energy loss and for interfaces designed to transfer them with high probability.

Increasing resistivity of metal wires with reducing nanoscale dimensions is a major performance bottleneck of semiconductor computing technologies. We show that metals with suitably anisotropic Fermi velocity distributions can strongly suppress electron scattering by surfaces and outperform isotropic conductors such as copper in nanoscale wires. We derive a corresponding descriptor for the resistivity scaling of anisotropic conductors, screen thousands of metals using first-principles calculations of this descriptor and identify the most promising materials for nanoscale interconnects. Previously-proposed layered conductors such as MAX phases and delafossites show promise in thin films, but not in narrow wires due to increased scattering from side walls. We find that certain intermetallics (notably CoSn) and borides (such as YCo$_3$B$_2$) with one-dimensionally anisotropic Fermi velocities are most promising for narrow wires. Combined with first-principles electron-phonon scattering predictions, we show that the proposed materials exhibit 2-3x lower resistivity than copper at 5 nm wire dimensions., Comment: 11 pages, 5 figures, 1 table; SI within source archive

Interactions of charge carriers with lattice vibrations, or phonons, play a critical role in unconventional electronic transport of metals and semimetals. Recent observations of phonon-mediated collective electron flow in bulk semimetals, termed electron hydrodynamics, present new opportunities in the search for strong electron-electron interactions in high carrier density materials. Here we present the general transport signatures of such a second-order scattering mechanism, along with analytical limits at the Eliashberg level of theory. We study electronic transport, using $ab$ $initio$ calculations, in finite-size channels of semimetallic ZrSiS and TaAs$_2$ with and without topological band crossings, respectively. The order of magnitude separation between momentum-relaxing and momentum-conserving scattering length-scales across a wide temperature range make both of them promising candidates for further experimental observation of electron hydrodynamics. More generally, our calculations show that the hydrodynamic transport regime can be realized in a much broader class of anisotropic metals and does not, to first order, rely on the topological nature of the bands. Finally, we discuss general design principles guiding future search for hydrodynamic candidates, based on the analytical formulation and our $ab$ $initio$ predictions. We find that systems with strong electron-phonon interactions, reduced electronic phase space, and suppressed phonon-phonon scattering at temperatures of interest are likely to feature hydrodynamic electron transport. We predict that layered and/or anisotropic semimetals composed of half-filled $d$-shells and light group V/VI elements with lower crystal symmetry are ideal candidates to observe hydrodynamic phenomena in future., Comment: 10 pages, 5 figures

Realizing the potential of plasmonic hot carrier harvesting for energy conversion and photodetection requires new materials that resolve the bottleneck of extracting carriers prior to energy relaxation within the metal. Using first-principles calculations of optical response and carrier transport properties, we show that directional conductors with Fermi velocities restricted predominantly to one or two directions present significant advantages for efficient hot carrier harvesting. We show that the optical response of film-like conductors, PtCoO$_2$ and Cr$_2$AlC, resemble that of 2D metals, while that of wire-like conductors, CoSn and YCo$_3$B$_2$, resemble that of 1D metals, which can lead to high mode confinement and efficient light collection in small dimensions, while still working with 3D materials with high carrier densities. Carrier lifetimes and transport distances in these materials, especially in PtCoO$_2$ and CoSn, are competitive with noble metals. Most importantly, we predict that carrier injection efficiency from all of these materials into semiconductors can exceed 10% due to the small component of carrier velocity parallel to the metal surface, substantially improving upon the typical less than 0.1% injection efficiency from noble metals into semiconductors., 9 pages, 8 figures, SI within source archive

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. (c) 2018 The Authors. Published by Elsevier Ltd.

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.

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.

The resistivity size effect in the ordered intermetallic CuTi compound is quantified using in situ and ex situ thin film resistivity ρ measurements at 295 and 77 K, and density functional theory Fermi surface and electron–phonon scattering calculations. Epitaxial CuTi(001) layers with thickness d = 5.8–149 nm are deposited on MgO(001) at 350 °C and exhibit ρ vs d data that are well described by the classical Fuchs and Sondheimer model, indicating a room-temperature effective electron mean free path λ = 12.5 ± 0.6 nm, a bulk resistivity ρo = 19.5 ± 0.3 μΩ cm, and a temperature-independent product ρo λ = 24.7 × 10−16 Ω m2. First-principles calculations indicate a strongly anisotropic Fermi surface with electron velocities ranging from 0.7 × 105 to 6.6 × 105 m/s, electron–phonon scattering lengths of 0.8–8.5 nm (with an average of 4.6 nm), and a resulting ρo = 20.6 ± 0.2 μΩ cm in the (001) plane, in excellent agreement (7% deviation) with the measurements. However, the measured ρo λ is almost 2.4 times larger than predicted, indicating a break-down of the classical transport models. Air exposure causes a 6%–30% resistivity increase, suggesting a transition from partially specular ( p = 0.5) to completely diffuse surface scattering due to surface oxidation as detected by x-ray photoelectron spectroscopy. Polycrystalline CuTi layers deposited on SiO2/Si substrates exhibit a 001 texture, a grain width that increases with d, and a 74%–163% larger resistivity than the epitaxial layers due to electron scattering at grain boundaries. The overall results suggest that CuTi is a promising candidate for highly scaled interconnects in integrated circuits only if it facilitates liner-free metallization.

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 (PME) 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 \emph{ab initio} MD (AIMD). Here, we combine large ensembles of long-time-scale classical MD simulations with charge response from electronic density functional theory (DFT) 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 -3.7 $\mu$C/cm$^2$ and -3.3 $\mu$C/cm$^2$, regardless of details in the electronic response. Simulated heating of the same interfaces reveals that the entropy peaks at a charge of maximum entropy (CME) of $-6.4 \pm 0.7~\mu$C/cm$^2$, 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., Comment: Combines main text, SI and erratum corrections from published version; 12 pages and 9 figures total

The increasing resistance of 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 of the interconnects at the nanoscale. Topological semimetals, owing to their topologically protected surface states and suppressed electron backscattering, are promising material candidates to potentially replace current Cu interconnects as low-resistance interconnects. Here, we report the attractive resistivity scaling of topological metal MoP nanowires and show that the resistivity values are comparable to those of Cu interconnects below 500 nm$^2$ cross-section areas. More importantly, we demonstrate that the dimensional scaling of MoP nanowires, in terms of line resistance versus total cross-sectional area, is superior to those of effective Cu and barrier-less Ru interconnects, suggesting MoP is an attractive solution to the current scaling challenge of Cu interconnects., Comment: 4 figures

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 ($\tau_s$) of solids with arbitrary spin mixing and crystal symmetry. This method describes contributions of Elliott-Yafet (EY) and D'yakonov-Perel' (DP) 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 DP 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., Comment: 12 pages, 7 figures

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.

Ab initio design of polymer nanocomposite materials for high breakdown strength requires prediction of localized trap states at the polymer–filler interface. Systematic first-principles calculations of realistic interfaces can be challenging, particularly for amorphous polymers and fillers that necessitate the calculation of ensembles of large unit cells with hundreds of atoms. We present a computational approach for automatically generating reasonable structures for amorphous polymer–filler interfaces, combining classical molecular dynamics and Monte Carlo simulations. We identify trap states by analyzing the localization of electronic eigenstates calculated using density functional theory on ensembles of interface structures, clearly distinguishing shallow trap states from delocalized band-edge states. Applying this approach to silica–polyethylene interfaces as an initial example, we find under-coordination and distorted coordination structures at amorphous silica surfaces contribute a combination of deep and shallow traps at these interfaces, whereas polyethylene does not generate localized interfacial states.

Spin relaxation and decoherence is at the heart of spintronics and spin-based quantum information science. Currently, theoretical approaches that can accurately predict spin relaxation of general solids including necessary scattering pathways and capable for ns to ms simulation time are urgently needed. We present a first-principles real-time density-matrix approach based on Lindblad dynamics to simulate ultrafast spin dynamics for general solid-state systems. Through the complete first-principles descriptions of pump, probe and scattering processes including electron-phonon, electron-impurity and electron-electron scatterings with self-consistent electronic spin-orbit couplings, our method can directly simulate the ultrafast pump-probe measurements for coupled spin and electron dynamics over ns at any temperatures and doping levels. We first apply this method to a prototypical system GaAs and obtain excellent agreement with experiments. We find that the relative contributions of different scattering mechanisms and phonon modes differ considerably between spin and carrier relaxation processes. In sharp contrast to previous work based on model Hamiltonians, we point out that the electron-electron scattering is negligible at room temperature but becomes dominant at low temperatures for spin relaxation in n-type GaAs. We further examine ultrafast dynamics in novel spin-valleytronic materials - monolayer and bilayer WSe2 with realistic defects. We find that spin relaxation is highly sensitive to local symmetry and chemical bonds around defects. Our work provides a predictive computational platform for spin dynamics in solids, which has unprecedented potentials for designing new materials ideal for spintronics and quantum information technology., Comment: 10 pages, 8 figures

Through First-Principles real-time Density-Matrix (FPDM) dynamics simulations, we investigate spin relaxation due to electron-phonon and electron-impurity scatterings with spin-orbit coupling in two-dimensional Dirac materials - silicene and germanene, at finite temperatures and under external fields. We discussed the applicability of conventional descriptions of spin relaxation mechanisms by Elliott-Yafet (EY) and D'yakonov-Perel' (DP) compared to our FPDM method, which is determined by a complex interplay of intrinsic spin-orbit coupling, external fields, and electron-phonon coupling strength, beyond crystal symmetry. For example, the electric field dependence of spin relaxation time is close to DP mechanism for silicene at room temperature, but rather similar to EY mechanism for germanene. Due to its stronger spin-orbit coupling strength and buckled structure in sharp contrast to graphene, germanene has a giant spin lifetime anisotropy and spin valley locking effect under nonzero Ez and relatively low temperature. More importantly, germanene has extremely long spin lifetime (~100 ns at 50 K) and ultrahigh carrier mobility, which makes it advantageous for spin-valleytronic applications., 9 pages, 4 figures

Identifying collective variables for chemical reactions is essential to reduce the 3$N$ dimensional energy landscape into lower dimensional basins and barriers of interest. However in condensed phase processes, the non-meaningful 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, although less is known about the behavior of nonlinear dimensionality reduction methods, e.g., UMAP, that have become more popular recently. 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 solution, 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. The first reaction consists of the dynamic exchange of a cation about a polyhydroxy anion that is facilitated by waters of solvation, while the second reaction consists of a nucleophilic attack of water upon ethylene to initiate cis/trans isomerization. When applied to raw data, 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 in solution.

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.

Polymer Nanodielectrics are class of materials with intriguing combinations of properties. Predicting and designing the properties, however, is complex due to the number of parameters controlling the properties. This makes it difficult to compare results across groups, validate models, and develop a design methodology. This presentation will share a recent approach to developing a data driven design methodology grounded in physics-based models and experimental calibration. We combine finite element modeling of dielectric constant and loss functions with a Monte Carlo multi-scale simulation of carrier hopping to predict break down strength. Filler dispersion, filler geometry, isotropy and interface properties are explicitly taken into to account to compute objective functions for ideal nanodielectric insulators. Further, we have used machine learning to develop an EFM technique for directly measuring the dielectric constant of the nanoscale interfacial region as critical input to our models. Ultimately, we calculate the Pareto frontier with respect to nanocomposite constitute properties and geometry to optimize properties. The finite element approach can be used to forward predict properties based on the properties of the interfacial region and filler dispersion, or as an inverse tool to calculate interface properties or develop optimized filler morphologies. The breakdown strength model critically depends on the energy distribution of trap states that inhibit space charge motion. We have developed an ab initio approach to determine the trap states at amorphous interfaces, and have used that to do a systematic analyses of trap distributions in composites with functionalized particle interfaces. The models all use 3D particle distributions based on 2D imaging (TEM) of the composites and publicly available tools for binarization and characterization of filler morphology. Finally, we use a design of experiment approach (Latin Hybercube Design) to sample the complete experimental design space, and using calibrated models and morphologies, create a data set spanning the full set of parameters. We use the data from the DOE to train a Gaussian Process metamodel and a genetic algorithm to determine which designs fulfill the design parameters. The talk will present several case studies as examples. The data for this work was accessed from a new data resource, MaterialsMine, using FAIR (Findable, Accessible, Interoperable, and Reusable) principles. MaterialsMine is an open source data repository, and resource. It includes unique visualization tools as well as modeling and characterization resources.

The Dirac point and linear band structure in Graphene bestow it with remarkable electronic and optical properties, a subject of intense ongoing research. Explanations of high electronic mobility in graphene, often invoke the masslessness of electrons based on the effective relativistic Dirac-equation behavior, which are inaccessible to most undergraduate students and are not intuitive for non-physics researchers unfamiliar with relativity. Here, we show how to use only basic concepts from semiconductor theory and the linear band structure of graphene to explain its unusual effective mass and mobility, and compare them with conventional metals and semiconductors. We discuss the more intuitive concept of transverse effective mass that emerges naturally from these basic derivations, which approaches zero in the limit of undoped graphene at low temperature and is responsible for its extremely high mobility., Comment: 5 pages, 3 figures

We have calculated the time constants of the electron dynamics in traps in a metal–insulator–metal (MIM) plasmonic structure. Because of electron relaxation in metal, the surface plasmon polaritons decays into hot electrons near the surface of the metal, which facilitates the trap of electrons in the interfacial layer of the dielectric. We have calculated the capture and emission times separately as the electron does not follow the same mechanisms with the capture process when it is emitted from a trap at the metal/oxide interface. We have developed a quasi-two-dimensional treatment that has been modified from a previously used semiconductor/oxide junction by using Bardeen’s function to calculate the capture time. Various parameters including trap’s distance from the interface, temperature, voltage bias, and spectral nature of the hot electrons’ energy distribution influence the interaction between a plasmonic hot electron and a neutral near-interface trap in the capture process. On the one hand, the emission time is independent of the capture time, and it is determined by the tunneling time to the metal depending on the temperature and the energy difference between the trap energy levels (ground and excited states). We have showed that a wide range of capture times from seconds to picoseconds is possible for an interfacial trap at the room temperature due to the spectral energy distribution of hot electrons and dependence of the capture process on the losses in metals. On the other hand, the temperature plays the dominant role in the emission time. For the trap with 250 meV energy difference between its levels, the emission time is in the range of picosecond at room temperature. Therefore, the MIM plasmonic device can respond to a wide range of ac voltage frequencies including the ultra-fast domain. These interesting findings are useful to understand the ac response of the MIM plasmonic devices with applications in integrated photonics and ultra-fast optoelectronics.

Although often ignored in first-principles studies of material behavior, electronic free energy can have a profound effect in systems with a high-temperature threshold for kinetics and a high Fermi-level density of states (DOS). ${\mathrm{Nb}}_{3}\mathrm{Sn}$ and many other members of the technologically important A15 class of superconductors meet these criteria. This is no coincidence: both electronic free energy and superconducting transition temperature ${T}_{\text{c}}$ are closely linked to the electronic density of states at the Fermi level. Antisite defects are known to have an adverse effect on ${T}_{\text{c}}$ in these materials because they disrupt the high Fermi-level density of states. We observe that this also locally reduces electronic free energy, giving rise to large temperature-dependent terms in antisite defect formation and interaction free energies. This work explores the effect of electronic free energy on antisite defect behavior in the case of ${\mathrm{Nb}}_{3}\mathrm{Sn}$. Using ab initio techniques, we perform a comprehensive study of antisite defects in ${\mathrm{Nb}}_{3}\mathrm{Sn}$, and find that their effect on the Fermi-level DOS plays a key role determining their thermodynamic behavior, their interactions, and their effect on superconductivity. Based on our findings, we calculate the A15 region of the Nb-Sn phase diagram and show that the phase boundaries depend critically the electronic free energy of antisite defects. In particular, we show that extended defects such as grain boundaries alter the local phase diagram by suppressing electronic free-energy effects, explaining experimental measurements of grain boundary antisite defect segregation. Finally, we quantify the effect of antisite defects on superconductivity with the first ab initio study of ${T}_{\text{c}}$ in ${\mathrm{Nb}}_{3}\mathrm{Sn}$ as a function of composition, focusing on tin-rich compositions observed in segregation regions around grain boundaries. As tin-rich compositions are not observed in bulk, their properties cannot be directly measured experimentally; our calculations therefore enable quantitative Ginzburg-Landau simulations of grain boundary superconductivity in ${\mathrm{Nb}}_{3}\mathrm{Sn}$. We discuss the implications of these results for developing new growth processes to improve the properties of ${\mathrm{Nb}}_{3}\mathrm{Sn}$ thin films.

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 A 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 A/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.

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

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.

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

A switchable photoactive ferroelectric chiral one-dimensional perovskite is predicted and created., 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.