arXiv subjects

Ravishankar Sundararaman

Publications and source records attributed to Ravishankar Sundararaman.

At least 19 recordsLinked to original sources

arXiv2026

Revealing Wavelength- and Size-Dependent CO2 Reduction Selectivity via Operando Scanning Photo-Electrochemical Microscopy

Controlling product selectivity in plasmonic catalysis, particularly in CO2 reduction (CO2R), remains a central unsolved challenge with direct implications for light-driven fuel and chemical synthesis. Here, we deploy quantitative operando scanning photoelectrochemical microscopy (photo-SECM) to provide a direct demonstration that tuning photon energy switches CO2R selectivity through an electronically driven pathway. On plasmonic Au/p-GaN photocathodes, interband excitation (460-560 nm) drives selective CO production while intraband excitation (640-800 nm) favors H2 evolution. By maintaining constant absorbed power across wavelengths and confirming linear power dependence, we isolate the role of hot-carrier energy from photonic and photothermal contributions. Density functional theory calculations reveal that higher-energy interband excitation progressively increases the overlap between hot-electron-accessible states and the CO-producing intermediate, selectively promoting CO over formate, in excellent agreement with experiment. We further show that selectivity is geometrically gated by hot-carrier transport: sub-100 nm nanostructures sustain CO2R activity, while ~300 nm nanodisks suffer transport losses that suppress it, consistent with ab initio hot-carrier transport calculations. Together, these results establish photon energy, carrier transport, and nanostructure geometry as coupled design parameters for plasmonic CO2R selectivity, resolve a longstanding debate on the origin of plasmon-driven selectivity effects, and position photo-SECM as a broadly applicable operando platform for photo(electro)catalysis.

physics.chem-ph↗

arXiv2026

Chirality-Induced Spin Selectivity: Nonlinear Spin Response from Electron-Phonon Scattering

Chirality-induced spin selectivity (CISS) generates spin-polarized currents in nonmagnetic materials from structural chirality alone, yet its microscopic origin remains debated. Using a first-principles spatiotemporal density-matrix dynamics approach including electron-phonon scatterings with self-consistent spin-orbit coupling (SOC), we elucidate the interplay of SOC, structural chirality, and spin-dependent electron-phonon interactions in driving the generation and transport of spin and orbital angular momentum. In particular we quantitatively distinguish CISS from the collinear Edelstein effect (CEE) in trigonal selenium, a prototypical chiral solid. CEE yields a spatially uniform spin polarization scaling linearly with applied field ($S_z \propto E$). In contrast, explicit spin-dependent electron-phonon scattering produces a nonlinear response ($S_z \propto E^2$) and a length-dependent spin accumulation -- the hallmark experimental signature of CISS. We identify intervalley scattering mediated by chiral phonon angular momentum as the microscopic origin of this nonlinearity.

cond-mat.mtrl-sci↗

arXiv2026

Systematic Fine-Tuning of MACE Interatomic Potentials for Catalysis

Once trained, machine-learned interatomic potentials (MLIPs) provide a fast and accurate way to study catalytic reaction pathways, but their performance strongly depends on the training set. Here, we compare nine MLIPs trained with different data sets and strategies, including from-scratch (FS) training and fine-tuning (FT) of large foundation models. The models are evaluated on reaction energies, $E_{r}$, and reaction energy barriers, $E_{a}$, for 141 reactions, including CO$_2$ reduction to C$_2$ and C$_3$ products, propane dehydrogenation, hydrogen intercalation on Pd, and out-of-distribution oxygen evolution reaction (OER) on metal oxides. FS models trained with 5%--10% perturbed high-energy configurations from molecular dynamics or contour exploration reduce the error by more than twofold compared with models trained only on relaxation trajectories. In contrast, FT MLIPs are less sensitive to sampling and transfer well to out-of-distribution reactions. An MLIP fine-tuned on metallic catalysts achieves a 0.30 eV MAE for OER on iridium oxide polymorphs, outperforming out-of-the-box MACE-MH-1 by 0.08 eV and the best FS model by 0.14 eV. A model fine-tuned to O and OH adsorption on metal oxides gives a 0.19 eV reaction-barrier MAE for out-of-distribution CO$_2$RR on Cu, comparable to an FS model trained on in-distribution C--C bond-breaking reactions. Finally, a large MLIP fine-tuned on 49,860 configurations gives the best overall performance across metallic and metal-oxide catalysts and was used to screen a large left-out set of bimetallic alloys, achieving a 0.15 eV MAE for $E_{r}$, even for adsorbates on unseen Miller-index surfaces such as (532). This work identifies the training configurations needed for accurate FS and FT MLIPs for catalytic reaction modeling.

physics.chem-ph↗

arXiv2026

Development of machine-learned interatomic potentials to predict structure, transport, and reactivity in platinum-based fuel cells

Machine-learned interatomic potentials (MLIPs) have rapidly progressed in accuracy, speed, and data efficiency in recent years. However, training robust MLIPs in multicomponent systems still remains a challenge. In this work, we train a MLIP to describe hydrated Nafion ionomers and platinum catalysts, which are important components of fuel cells, by constructing a diverse training set to describe the bulk polymer and interfacial catalyst-polymer interactions well. We find that active learning improves the initial dataset little in terms of reducing uncertainty and error, pointing towards a need for more effective methods to efficiently explore the relevant interactions in complex, multicomponent systems. We use our trained MLIP to study the properties of the platinum-Nafion system, including polymer structure, proton mobility in a bulk Nafion polymer and near a platinum-Nafion interface, and reactions near and far from the interface, finding excellent results for structure and reactions contained within our training set. Transport seems well described, with both vehicular transport and Grotthuss hopping captured, although converged calculations of diffusivities were not computed because they require calculations of tens of nanoseconds that are challenging with current state-of-the-art MLIPs. The combined insights that this model provides can be leveraged to optimize fuel cell performance, and the approach can be applied to other chemical processes and devices where structure, transport, and reactivity all contribute to overall observed performance.

physics.chem-ph↗

arXiv2026

Photogalvanic currents from first-principles real-time density-matrix dynamics

The photogalvanic effect is the generation of a second-order direct current by illumination of a non-centrosymmetric material. In this work, we develop a first-principles real-time density matrix (FPDMD) formalism enabling the calculations of the photogalvanic current in all time regimes: transient and steady. Unlike past \textit{ab-initio} studies which focused only on the photo-excitation process, our first-principles theory framework encodes all quantum scatterings (intra/interband relaxation and electron-hole recombination) mediated by bosons (photons and phonons), and is thus predictive of photogalvanic currents in realistic materials. In particular, for the linear photogalvanic effect, we find electron scatterings mediated by phonons contribute significantly to the shift current for prototypical piezoelectrics like BaTiO$_3$. For the circular photogalvanic effect, we develop a self-consistent theory of a steady injection current that incorporates realistic scattering mediated by phonons. Our formulation developed for photogalvanic current elucidates its connection with fundamental quantum-geometric quantities such as the Berry curvature and the quantum metric. A phonon-based explanation is proposed for the bipolar transient photogalvanic current observed by the THz emission spectroscopy.

cond-mat.mtrl-sci↗

arXiv2025

Alkali Intercalation of Moire Heterostructures for Low-Loss Plasmonics

Two-dimensional metals generically support gapless plasmons with wavelengths well below the wavelength of free-space radiation at the same frequency. Typically, however, this substantial confinement of electromagnetic energy is associated with commensurately high losses, and mitigating such losses may only be achieved through judicious band structure engineering near the Fermi level. In a clean system, an isolated, moderately flat, band at the Fermi level with sufficiently high carrier density can support a plasmon that is immune to propagation losses up to some order in the electron-phonon interaction. However, proposed materials that satisfy these criteria have been ferromagnetic, structurally unstable, or otherwise difficult to fabricate. Here, we propose a class of band structure engineered materials that evade these typical pitfalls -- Moire heterostructures of hexagonal boron nitride intercalated with alkali atoms. We find that only sodium atoms engender a sufficiently isolated band with plasmons lossless at first order in the electron-phonon interaction. We calculate higher order electron-phonon losses and find that at frequencies of about $1$eV the electron-phonon decay mechanism is negligible -- leading to a contribution to the decay rate of about 10^7 Hz in a small frequency range. We next calculate losses from the electron-electron interaction and find that this is the dominant process -- leading plasmons to decay to lower frequency plasmons at a rate of around 10^14 Hz.

cond-mat.mtrl-sci↗

arXiv2025

Spatio-temporal spin transport from first principles

We introduce a computational framework for first-principles density matrix transport within the Wigner function formalism to predict transport of quantum-mechanical degrees of freedom such as spin over long time and length scales. This framework facilitates simulation of spin dynamics and transport from first principles, while accounting for electron-phonon scattering at device length scales. We demonstrate this framework to elucidate the impact of various spin-orbit field profiles, such as Rashba and persistent spin helix, on coherent spin transport in several materials. Using graphene under an electric field as an example to illustrate the impact of electron-phonon scattering on incoherent transport, we show how the transport changes with the strength of scattering. We identify three distinct regimes of incoherent spin transport corresponding to the free induction decay, Dyakonov-Perel and Elliott-Yafet regimes of spin relaxation. In particular, we show that the spin diffusion length is insensitive to the strength of scattering within the Dyakonov-Perel regime.

cond-mat.mes-hall↗

arXiv2025

Nanomolding single-crystalline CoIn3 and RhIn3 nanowires

Intermetallic compounds containing transition metals and group III-V metals tend to possess strong correlations and high catalytic activities, both of which can be enhanced via reduced dimensionality. Nanostructuring is an effective approach to explore this possibility, yet the synthesis of nanostructured intermetallics is challenging due to vast differences in melting points and vapor pressures of the constituent elements. In this work, we demonstrate that this challenge can be overcome with thermomechanical nanomolding (TMNM), exemplified by the synthesis of intermetallic CoIn3 and RhIn3 nanowires. We show that TMNM successfully extrudes single-crystalline nanowires of these compounds down to the 20 nm diameter range, and the nanowires remain metallic with resistivity values higher than calculated bulk resistivity. We discuss possible effects of surface roughness scattering, vacancy-induced scattering, and surface oxidation, on the measured resistivities of the nanowires. For CoIn3 nanowires, the measured resistivity values are the first reported values for this compound.

cond-mat.mtrl-sci↗

arXiv2025

Surface-dominant transport in Weyl semimetal NbAs nanowires for next-generation interconnects

Ongoing demands for smaller and more energy efficient electronic devices necessitate alternative interconnect materials with lower electrical resistivity at reduced dimensions. Despite the emergence of many promising candidates, synthesizing high quality nanostructures remains a major bottleneck in evaluating their performance. Here, we report the successful synthesis of Weyl semimetal NbAs nanowires via thermomechanical nanomolding, achieving single crystallinity and controlled diameters as small as 40 nm. Our NbAs nanowires exhibit a remarkably low room-temperature resistivity of 9.7 +/- 1.6 microOhm-cm, which is three to four times lower than their bulk counterpart. Theoretical calculations corroborate the experimental observations, attributing this exceptional resistivity reduction to surface dominant conduction with long carrier lifetime at finite temperatures. Further characterization of NbAs nanowires and bulk single crystals reveals high breakdown current density, robust stability, and superior thermal conductivity. Collectively, these properties highlight the strong potential of NbAs nanowires as next-generation interconnects, which can surpass the limitations of current copper-based interconnects. Technologically, our findings present a practical application of topological materials, while scientifically showcasing the fundamental properties uniquely accessible in nanoscale platforms.

cond-mat.mes-hall↗

arXiv2025

Magnetic-field dependence of spin-phonon relaxation and dephasing due to g-factor fluctuations from first principles

The electron spin decay lifetime in materials can be characterized by relaxation (T1) and irreversible (T2) and reversible (T2*) decoherence processes. Their interplay leads to a complex dependence of spin relaxation times on the direction and magnitude of magnetic fields, relevant for spintronics and quantum information applications. Here, we use real-time first-principles density matrix dynamics simulations to directly simulate Hahn echo measurements, disentangle dephasing from decoherence, and predict T1, T2 and T2* spin lifetimes. We show that g-factor fluctuations lead to non-trivial magnetic field dependence of each of these lifetimes in inversion-symmetric crystals of CsPbBr3 and silicon, even when only intrinsic spin-phonon scattering is present. Most importantly, fluctuations in the off-diagonal components of the g-tensor lead to a strong magnetic field dependence of even the T1 lifetime in silicon. Our calculations elucidate the detailed role of anisotropic g-factors in determining the spin dynamics even in simple, low spin-orbit coupling materials such as silicon.

cond-mat.mtrl-sci↗

arXiv2024

Bridging electronic and classical density-functional theory using universal machine-learned functional approximations

The accuracy of density-functional theory (DFT) is determined by the quality of the approximate functionals, such as exchange-correlation in electronic DFT and the excess functional in the classical DFT formalism of fluids. The exact functional is highly nonlocal for both electrons and fluids, yet most approximate functionals are semi-local or nonlocal in a limited weighted-density form. Machine-learned (ML) nonlocal density-functional approximations are promising in both electronic and classical DFT, but have so far employed disparate approaches with limited generality. Here, we formulate a universal approximation framework and training protocol for nonlocal ML functionals, combining features of equivariant convolutional neural networks and the weighted-density approximation. We prototype this approach for several 1D and quasi-1D problems and demonstrate that a functional with exactly the same hyperparameters achieves excellent accuracy for the hard-rod fluid, the inhomogeneous Ising model, the exact exchange functional for electrons, the electron kinetic energy functional for orbital-free DFT, as well as for liquid water with 1D inhomogeneities. These results lay the foundation for a universal ML approach to exact 3D functionals spanning electronic and classical DFT.

physics.chem-ph↗

arXiv2024

Spin Dynamics in Hybrid Halide Perovskites -- Effect of Dynamical and Permanent Symmetry Breaking

The hybrid organic-inorganic halide perovskite (HOIP), for example MAPbBr3, exhibits extended spin lifetime and apparent spin lifetime anisotropy in experiments. The underlying mechanisms of these phenomena remain illusive. By utilizing our first-principles densitymatrix dynamics approach with quantum scatterings including electron-phonon and electronelectron interactions and self-consistent spinorbit coupling, we present temperature- and magnetic field-dependent spin lifetimes in hybrid perovskites, in agreement with experimental observations. For centrosymmetric hybrid perovskite MAPbBr3, the experimentally observed spin lifetime anisotropy is mainly attributed to the dynamical Rashba effect arising from the interaction between organic and inorganic components and the rotation of the organic cation. For noncentrosymmetric perovskite, such as MPSnBr3, we found persistent spin helix texture at the conduction band minimum, which significantly enhances the spin lifetime anisotropy. Our study provides theoretical insight to spin dynamics in HOIP and strategies for controlling and optimizing spin transport.

cond-mat.mtrl-sci↗

arXiv2024

Distinguishing Inner and Outer-Sphere Hot Electron Transfer in Au/p-GaN Photocathodes

Exploring nonequilibrium hot carriers from plasmonic metal nanostructures is a dynamic field in optoelectronics, driving photochemical reactions such as solar fuel generation. The hot carrier injection mechanism and the reaction rate are highly impacted by the metal/molecule interaction. However, determining the primary type of the reaction and thus the injection mechanism of the hot carriers has remained elusive. In this work, we reveal an electron injection mechanism deviating from a purely outersphere process for the reduction of ferricyanide redox molecule in a gold/p-type gallium nitride (Au/p- GaN) photocathode system. Combining our experimental approach with ab initio simulations, we discover that the efficient inner-sphere transfer of low-energy electrons leads to a continuous enhancement in the photocathode device performance in the interband regime. These findings provide important mechanistic insights, showing our methodology as a powerful tool for analyzing and engineering hot-carrier-driven processes in plasmonic photocatalytic systems and optoelectronic devices.

physics.chem-ph↗

arXiv2024

BEAST DB: Grand-Canonical Database of Electrocatalyst Properties

We present BEAST DB, an open-source database comprised of ab initio electrochemical data computed using grand-canonical density functional theory in implicit solvent at consistent calculation parameters. The database contains over 20,000 surface calculations and covers a broad set of heterogeneous catalyst materials and electrochemical reactions. Calculations were performed at self-consistent fixed potential as well as constant charge to facilitate comparisons to the computational hydrogen electrode. This article presents common use cases of the database to rationalize trends in catalyst activity, screen catalyst material spaces, understand elementary mechanistic steps, analyze electronic structure, and train machine learning models to predict higher fidelity properties. Users can interact graphically with the database by querying for individual calculations to gain granular understanding of reaction steps or by querying for an entire reaction pathway on a given material using an interactive reaction pathway tool. BEAST DB will be periodically updated, with planned future updates to include advanced electronic structure data, surface speciation studies, and greater reaction coverage.

cond-mat.mtrl-sci↗

arXiv2024

Static Subspace Approximation for Random Phase Approximation Correlation Energies: Implementation and Performance

Developing theoretical understanding of complex reactions and processes at interfaces requires using methods that go beyond semilocal density functional theory to accurately describe the interactions between solvent, reactants and substrates. Methods based on many-body perturbation theory, such as the random phase approximation (RPA), have previously been limited due to their computational complexity. However, this is now a surmountable barrier due to the advances in computational power available, in particular through modern GPU-based supercomputers. In this work, we describe the implementation of RPA calculations within BerkeleyGW and show its favorable computational performance on large complex systems relevant for catalysis and electrochemistry applications. Our implementation builds off of the static subspace approximation which, by employing a compressed representation of the frequency dependent polarizability, enables the evaluation of the RPA correlation energy with significant acceleration and systematically controllable accuracy. We find that the computational cost of calculating the RPA correlation energy scales only linearly with system size for systems containing up to 50 thousand bands, and is expected to scale quadratically thereafter. We also show excellent strong scaling results across several supercomputers, demonstrating the performance and portability of this implementation.

cond-mat.mtrl-sci↗

arXiv2024

Surface-dominated conductance scaling in Weyl semimetal NbAs

Protected surface states arising from non-trivial bandstructure topology in semimetals can potentially enable new device functionalities in compute, memory, interconnect, sensing, and communication. This necessitates a fundamental understanding of surface-state transport in nanoscale topological semimetals. Here, we investigate quantum transport in a prototypical topological semimetal NbAs to evaluate the potential of this class of materials for beyond-Cu interconnects in highly-scaled integrated circuits. Using density functional theory (DFT) coupled with non-equilibrium Green's function (NEGF) calculations, we show that the resistance-area RA product in NbAs films decreases with decreasing thickness at the nanometer scale, in contrast to a nearly constant RA product in ideal Cu films. This anomalous scaling originates from the disproportionately large number of surface conduction states which dominate the ballistic conductance by up to 70% in NbAs thin films. We also show that this favorable RA scaling persists even in the presence of surface defects, in contrast to RA sharply increasing with reducing thickness for films of conventional metals, such as Cu, in the presence of surface defects. These results underscore the promise of topological semimetals like NbAs as future back-end-of-line (BEOL) interconnect metals.

cond-mat.mes-hall↗

arXiv2024

Challenges and Opportunities in Searching for Rashba-Dresselhaus Materials for Efficient Spin-Charge Interconversion at Room Temperature

Spintronic logic devices require efficient spin-charge interconversion: converting charge current to spin current and spin current to charge current. In spin-orbit materials that are regarded as the most promising candidate for spintronic logic devices, one mechanism that is responsible for spin-charge interconversion is Edelstein and inverse Edelstein effects based on spin-momentum locking in materials with Rashba-type spin-orbit coupling. Over last decade, there has been rapid progresses for increasing interconversion efficiencies due to the Edelstein effect in a few Rashba-Dresselhaus materials and topological insulators, making Rashba spin-momentum locking a promising technological solution for spin-orbit logic devices. However, despite the rapid progress that leads to high spin-charge interconversion efficiency at cryogenic temperatures, the room-temperature efficiency needed for technological applications is still low. This paper presents our understanding on the challenges and opportunities in searching for Rashba-Dresselhaus materials for efficient spin-charge interconversion at room temperature by focusing on materials properties such as Rashba coefficients, momentum relaxation times, spin-momentum locking relations and electrical conductivities.

cond-mat.mtrl-sci↗

arXiv2023

Improving the reliability of machine learned potentials for modeling inhomogenous 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 at such interfaces. Classical molecular dynamics simulations have been applied extensively to simulate the response of inhomogeneous fluids directly, and as inputs to classical density functional theory, but are limited by the accuracy of the underlying empirical force fields. Here, we deploy neural network potentials (NNPs) trained to ab initio simulations to accurately predict the inhomogeneous response of two widely different fluids: liquid water and molten NaCl. Although NNPs can be readily trained to model complex bulk systems across a range of state points, in order to appropriately model a fluid's response at an interface, inhomogeneous configurations must be included in the training data. We establish protocols based on molecular dynamics simulations in external atomic potentials in order to sufficiently sample the correct configurations of inhomogeneous fluids. We show that NNPs trained to inhomogeneous fluid configurations can predict several properties such as the density response, surface tension and size-dependent cavitation free energies in water and molten NaCl corresponding to ab initio interactions more accurately than empirical force fields. This work therefore provides a first demonstration and framework for extracting the response of inhomogeneous fluids from first principles for classical density-functional treatment of fluids free from empirical potentials.

cond-mat.mtrl-sci↗