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Paul Erhart

Publications and source records attributed to Paul Erhart.

At least 55 records · Page 3Linked to original sources
arXiv2023

Accelerating Plasmonic Hydrogen Sensors for Inert Gas Environments by Transformer-Based Deep Learning

The ability to rapidly detect hydrogen gas upon occurrence of a leak is critical for the safe large-scale implementation of hydrogen (energy) technologies. However, to date, no technically viable sensor solution exists that meets the corresponding response time targets set by stakeholders at technically relevant conditions. Here, we demonstrate how a tailored Long Short-term Transformer Ensemble Model for Accelerated Sensing (LEMAS) accelerates the response of a state-of-the-art optical plasmonic hydrogen sensor by up to a factor of 40 in an oxygen-free inert gas environment, by accurately predicting its response value to a hydrogen concentration change before it is physically reached by the sensor hardware. Furthermore, it eliminates the pressure dependence of the response intrinsic to metal hydride-based sensors, while leveraging their ability to operate in oxygen-starved environments that are proposed to be used for inert gas encapsulation systems of hydrogen installations. Moreover LEMAS provides a measure for the uncertainty of the predictions that is pivotal for safety-critical sensor applications. Our results thus advertise the use of deep learning for the acceleration of sensor response, also beyond the realm of plasmonic hydrogen detection.

physics.comp-ph↗
arXiv2023

Phonon-bottleneck enhanced exciton emission in 2D perovskites

Layered halide perovskites exhibit remarkable optoelectronic properties and technological promise, driven by strongly bound excitons. The interplay of spin-orbit and exchange coupling creates a rich excitonic landscape, determining their optical signatures and exciton dynamics. Despite the dark excitonic ground state, surprisingly efficient emission from higher-energy bright states has puzzled the scientific community, sparking debates on relaxation mechanisms. Combining low-temperature magneto-optical measurements with sophisticated many-particle theory, we elucidate the origin of the bright exciton emission in perovskites by tracking the thermalization of dark and bright excitons under a magnetic field. We clearly attribute the unexpectedly high emission to a pronounced phonon-bottleneck effect, considerably slowing down the relaxation towards the energetically lowest dark states. We demonstrate that this bottleneck can be tuned by manipulating the bright-dark energy splitting and optical phonon energies, offering valuable insights and strategies for controlling exciton emission in layered perovskite materials that is crucial for optoelectronics applications.

cond-mat.mes-hall↗
arXiv2023

Tailoring hot-carrier distributions of plasmonic nanostructures through surface alloying

Alloyed metal nanoparticles are a promising platform for plasmonically enabled hot-carrier generation, which can be used to drive photochemical reactions. Although the non-plasmonic component in these systems has been investigated for its potential to enhance catalytic activity, its capacity to affect the photochemical process favorably has been underexplored by comparison. Here, we study the impact of surface alloy species and concentration on hot-carrier generation in Ag nanoparticles. By first-principles simulations, we photoexcite the localized surface plasmon, allow it to dephase, and calculate spatially and energetically resolved hot-carrier distributions. We show that the presence of non-noble species in the topmost surface layer drastically enhances hot-hole generation at the surface at the expense of hot-hole generation in the bulk, due to the additional d-type states that are introduced to the surface. The energy of the generated holes can be tuned by choice of the alloyant, with systematic trends across the d-band block. Already low surface alloy concentrations have a large impact, with a saturation of the enhancement effect typically close to 75% of a monolayer. Hot-electron generation at the surface is hindered slightly by alloying but here an judicious choice of the alloy composition allows one to strike a balance between hot electrons and holes. In this context, it is also important to consider that increasing the alloy concentration broadens the localized surface plasmon resonance, and thus decreases hot-carrier generation overall. Our work underscores the promise of utilizing multicomponent nanoparticles to achieve enhanced control over plasmonic catalysis, and provides guidelines for how hot-carrier distributions can be tailored by designing the electronic structure of the surface through alloying.

cond-mat.mes-hall↗
arXiv2023

Quantitative predictions of the thermal conductivity in transition metal dichalcogenides: The impact of point defects in MoS$_2$ and WS$_2$ monolayers

Transition metal dichalcogenides are investigated for various applications at the nanoscale thanks to their unique combination of properties and dimensionality. For many of the anticipated applications, heat conduction plays an important role. At the same time, these materials often contain relatively large amounts of point defects. Here, we provide a systematic analysis of the impact of intrinsic and selected extrinsic defects on the lattice thermal conductivity of MoS$_2$ and WS$_2$ monolayers. We combine Boltzmann transport theory and the Green's function-based T-matrix approach for the calculation of scattering rates. The force constants for the defect configurations are obtained from density functional theory calculations via a regression approach, which allows us to sample a rather large number of defects at a moderate computational cost and to systematically enforce both the translational and rotational acoustic sum rules. The calculated lattice thermal conductivity is in quantitative agreement with experimental data for heat transport and defect concentrations for both MoS$_2$ and WS$_2$. Crucially, this demonstrates that the strong deviation from a 1/T-temperature dependence of the lattice thermal conductivity observed experimentally, can be fully explained by the presence of point defects. We furthermore predict the scattering strengths of the intrinsic defects to decrease in the sequence $V_{Mo}\approx V_{2S}^=>V_{2S}^\perp>V_S>S_{ad}$ in both materials, while the scattering rates for the extrinsic (adatom) defects decrease with increasing mass such that Li$_{ad}$>Na$_{ad}$>K$_{ad}$. Compared to earlier work, we find that both intrinsic and extrinsic adatoms are relatively weak scatterers. We attribute this difference to the treatment of the translational and rotational acoustic sum rules, which if not enforced can lead to spurious contributions in the zero-frequency limit.

cond-mat.mtrl-sci↗
arXiv2023

Understanding correlations in BaZrO3:Structure and dynamics on the nano-scale

Barium zirconate BaZrO3 is one of few perovskites that is claimed to retain an average cubic structure down to 0K at ambient pressure, while being energetically very close to a tetragonal phase obtained by condensation of a soft phonon mode at the R-point. Previous studies suggest, however, that the local structure of BaZrO3 may change at low temperature forming nanodomains or a glass-like phase. Here, we investigate the global and local structure of BaZrO3 as a function of temperature and pressure via molecular dynamics simulations using a machine-learned potential with near density functional theory (DFT) accuracy. We show that the softening of the octahedral tilt mode at the R-point gives rise to weak diffuse superlattice reflections at low temperatures and ambient pressure, which are also observed experimentally. However, we do not observe any static nanodomains but rather soft dynamic fluctuations of the ZrO6 octahedra with a correlation length of 2 to 3nm over time-scales of about 1ps. This soft dynamic behaviour is the precursor of a phase transition and explains the emergence of weak superlattice peaks in measurements. On the other hand, when increasing the pressure at 300K we find a phase transition from the cubic to the tetragonal phase at around 16GPa, also in agreement with experimental studies.

cond-mat.mtrl-sci↗
arXiv2023

Revealing the free energy landscape of halide perovskites: Metastability and transition characters in CsPbBr$_3$ and MAPbI$_3$

Halide perovskites have emerged as a promising class of materials for photovoltaic applications. A challenge in these applications is how to prevent the crystal structure from degradation to photovoltaically inactive phases, which requires an understanding of the free energy landscape of these materials. Here, we uncover the free energy landscape of two prototypical halide perovskites, CsPbBr$_3$ and MAPbI$_3$ via atomic scale simulations using umbrella sampling and machine-learned potentials. For CsPbBr$_3$ we find very small free energy differences and barriers close to the transition temperatures for both the tetragonal-to-cubic and the orthorhombic-to-tetragonal transition. For MAPbI$_3$, however, the situation is more intricate. In particular the orthorhombic-to-tetragonal transition exhibits a large free energy barrier and there are several competing tetragonal phases. Using large-scale molecular dynamics simulations we explore the character of these transition and observe latent heat and a discrete change in structural parameters for the tetragonal-to-cubic phase transition in both CsPbBr$_3$ and MAPbI$_3$ indicating first-order transitions. We find that in MAPbI$_3$ the orthorhombic phase has an extended metastability range and furthermore identify a second metastable tetragonal phase. Finally, we compile a phase diagram for MAPbI$_3$ that includes potential metastable phases.

cond-mat.mtrl-sci↗
arXiv2023

Tuning the lattice thermal conductivity in van-der-Waals structures through rotational (dis)ordering

It has recently been demonstrated that MoS2 with irregular interlayer rotations can achieve an extreme anisotropy in the lattice thermal conductivity (LTC), which is for example of interest for applications in waste heat management in integrated circuits. Here, we show by atomic scale simulations based on machine-learned potentials that this principle extends to other two-dimensional materials including C and BN. In all three materials introducing rotational disorder drives the through-plane LTC to the glass limit, while the in-plane LTC remains almost unchanged compared to the ideal bulk materials. We demonstrate that the ultralow through-plane LTC is connected to the collapse of their transverse acoustic modes in the through-plane direction. Furthermore, we find that the twist angle in periodic moiré structures representing rotational order provides an efficient means for tuning the through-plane LTC that operates for all chemistries considered here. The minimal through-plane LTC is obtained for angles between 1 and 4 degree depending on the material, with the biggest effect in MoS2. The angular dependence is correlated with the degree of stacking disorder in the materials, which in turn is connected to the slip surface. This provides a simple descriptor for predicting the optimal conditions at which the LTC is expected to become minimal.

cond-mat.mtrl-sci↗
arXiv2023

Limits of the phonon quasi-particle picture at the cubic-to-tetragonal phase transition in halide perovskites

The soft modes associated with continuous-order phase transitions are associated with strong anharmonicity. This leads to the overdamped limit where the phonon quasi-particle picture can breakdown. However, this limit is commonly restricted to a narrow temperature range, making it difficult to observe its signature feature, namely the breakdown of the inverse relationship between the relaxation time and damping. Here we present a physically intuitive picture based on the relaxation times of the mode coordinate and its conjugate momentum, which at the instability approach infinity and the inverse damping factor, respectively. We demonstrate this behavior for the cubic-to-tetragonal phase transition of the inorganic halide perovskite CsPbBr$_3$ via molecular dynamics, and show that the overdamped region extends almost 200 K above the transition temperature. Further, we investigate how the dynamics of these soft phonon modes change when crossing the phase transition.

cond-mat.mtrl-sci↗
arXiv2023

Small-angle scattering tensor tomography algorithm for robust reconstruction of complex textures

The development of small-angle scattering tensor tomography has enabled the study of anisotropic nanostructures in a volume-resolved manner. It is of great value to have reconstruction methods that can handle many different nanostructural symmetries. For such a method to be employed by researchers from a wide range of backgrounds, it is crucial that its reliance on prior knowledge about the system is minimized, and that it is robust under various conditions. Here, we present a method employing band-limited spherical functions to enable the reconstruction of reciprocal space maps of a wide variety of nanostructures. This method has been thoroughly tested and compared to existing methods in its ability to retrieve known reciprocal space maps, as well as its robustness to changes in initial conditions, using both simulations and experimental data. The anchoring of this method in a framework of integral geometry and linear algebra highlights its possibilities and limitations.

cond-mat.mtrl-sci↗
arXiv2023

Quantifying Dynamic Tilting in Halide Perovskites: Chemical Trends and Local Correlations

Halide perovskites have emerged as one of the most interesting materials for optoelectronic applications due to their favorable properties, such as defect-tolerance and long charge carrier lifetimes, which are attributed to their dynamic softness. However, this softness has led to apparent disagreements between the local instantaneous and global average structures of these materials. In this work, we assess the local tilt angles of octahedra in the perovskite structure through large-scale molecular dynamics simulations using machine learned potentials based on density functional theory. We compare structural properties given by different density functionals, namely PBE, PBEsol, SCAN, and vdW-DF-cx, and establish trends across a family of CsMX3 with M=Sn or Pb and X=Cl, Br or I perovskites. Notably, we demonstrate a strong short-range ordering that persists even in the cubic phase of halide perovskites. This ordering is reminiscent of the tetragonal phase and bridges the disordered local structure and the global cubic arrangement. Our results provide a deeper understanding of the structural properties of halide perovskites and their local distortions, which is crucial for further understanding their optoelectronic properties.

cond-mat.mtrl-sci↗
arXiv2023

Phase transitions in inorganic halide perovskites from machine learning potentials

The atomic scale dynamics of halide perovskites have a direct impact not only on their thermal stability but their optoelectronic properties. Progress in machine learned potentials has only recently enabled modeling the finite temperature behavior of these material using fully atomistic methods with near first-principles accuracy. Here, we systematically analyze the impact of heating and cooling rate, simulation size, model uncertainty, and the role of the underlying exchange-correlation functional on the phase behavior of CsPbX3 with X=Cl, Br, and I, including both the perovskite and the delta-phases. We show that rates below approximately 30 K/ns and system sizes of at least a few ten thousand atoms are indicated to achieve convergence with regard to these parameters. By controlling these factors and constructing models that are specific for different exchange-correlation functionals we then show that the semi-local functionals considered in this work (SCAN, vdW-DF-cx, PBEsol, and PBE) systematically underestimate the transition temperatures separating the perovskite phases while overestimating the lattice parameters. Among the considered functionals the vdW-DF-cx functional yields the closest agreement with experiment, followed by SCAN, PBEsol, and PBE. Our work provides guidelines for the systematic analysis of dynamics and phase transitions in inorganic halide perovskites and similar systems. It also serves as a benchmark for the further development of machine-learned potentials as well as exchange-correlation functionals.

cond-mat.mtrl-sci↗
arXiv2022

Computational Design of Alloy Nanostructures for Optical Sensing of Hydrogen

Pd nanoalloys show great potential as hysteresis-free, reliable hydrogen sensors. Here, a multi-scale modeling approach is employed to determine optimal conditions for optical hydrogen sensing using the Pd-Au-H system. Changes in hydrogen pressure translate to changes in hydrogen content and eventually the optical spectrum. At the single particle level, the shift of the plasmon peak position with hydrogen concentration (i.e., the "optical" sensitivity) is approximately constant at 180 nm/c_H for nanodisk diameters >~ 100 nm. For smaller particles, the optical sensitivity is negative and increases with decreasing diameter, due to the emergence of a second peak originating from coupling between a localized surface plasmon and interband transitions. In addition to tracking peak position, the onset of extinction as well as extinction at fixed wavelengths is considered. We carefully compare the simulation results with experimental data and assess the potential sources for discrepancies. Invariably, the results suggest that there is an upper bound for the optical sensitivity that cannot be overcome by engineering composition and/or geometry. While the alloy composition has a limited impact on optical sensitivity, it can strongly affect H uptake and consequently the "thermodynamic" sensitivity and the detection limit. Here, it is shown how the latter can be improved by compositional engineering and even substantially enhanced via the formation of an ordered phase that can be synthesized at higher hydrogen partial pressures.

cond-mat.mtrl-sci↗
arXiv2022

GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations

We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in [Fan et al., Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package GPUMD. We increase the accuracy of NEP models both by improving the radial functions in the atomic-environment descriptor using a linear combination of Chebyshev basis functions and by extending the angular descriptor with some four-body and five-body contributions as in the atomic cluster expansion approach. We also detail our efficient implementation of the NEP approach in graphics processing units as well as our workflow for the construction of NEP models, and we demonstrate their application in large-scale atomistic simulations. By comparing to state-of-the-art MLPs, we show that the NEP approach not only achieves above-average accuracy but also is far more computationally efficient. These results demonstrate that the GPUMD package is a promising tool for solving challenging problems requiring highly accurate, large-scale atomistic simulations. To enable the construction of MLPs using a minimal training set, we propose an active-learning scheme based on the latent space of a pre-trained NEP model. Finally, we introduce three separate Python packages, GPYUMD, CALORINE, and PYNEP, which enable the integration of GPUMD into Python workflows.

physics.comp-ph↗
arXiv2022

Hot-carrier transfer across a nanoparticle-molecule junction: The importance of orbital hybridization and level alignment

While direct hot-carrier transfer can increase photo-catalytic activity, it is difficult to discern experimentally and competes with several other mechanisms. To shed light on these aspects, here, we model from first principles hot-carrier generation across the interface between plasmonic nanoparticles and a CO molecule. The hot-electron transfer probability depends non-monotonically on the nanoparticle-molecule distance and can be effective at long distances, well outside the region of chemisorption; hot-hole transfer on the other hand is limited to shorter distances. These observations can be explained by the energetic alignment between molecular and nanoparticle states as well as the excitation frequency. The hybridization of the molecular orbitals is the key predictor for hot-carrier transfer in these systems, emphasizing the need to include the effects of ground state hybridization for accurate predictions. Finally, we show a non-trivial dependence of the hot-carrier distribution on the excitation energy, which could be exploited when optimizing photo-catalytic systems.

cond-mat.mes-hall↗
arXiv2022

The moiré potential in twisted transition metal dichalcogenide bilayers

Moiré superlattices serve as a playground for emerging phenomena, such as localization of band states, superconductivity, and localization of excitons. These superlattices are large and are often modeled in the zero angle limit, which obscures the effect of finite twist angles. Here, by means of first-principles calculations we quantify the twist-angle dependence of the moiré potential in the MoS$_2$ homobilayer and identify the contributions from the constituent elements of the moiré potential. Furthermore, by considering the zero-angle limit configurations, we show that the moiré potential is rather homogeneous across the transition metal dichalcogenides (TMDs) and briefly discuss the separate effects of potential shifts and hybridization on the bilayer hybrid excitons. We find that the moiré potential in TMDs exhibits both an electrostatic component and a hybridization component, which are intertwined and have different relative strengths in different parts of the Brillouin zone. The electrostatic component of the moiré potential is a varying dipole field, which has a strong twist angle dependence. In some cases, the hybridization component can be interpreted as a tunneling rate but the interpretation is not generally applicable over the full Brillouin zone.

cond-mat.mtrl-sci↗
arXiv2022

High-throughput characterization of transition metal dichalcogenide alloys: Thermodynamic stability and electronic band alignment

Alloying offers a way to tune many of the properties of the transition metal dichalcogenide (TMD) monolayers. While these systems in many cases have been thoroughly investigated previously, the fundamental understanding of critical temperatures, phase diagrams and band edge alignment is still incomplete. Based on first principles calculations and alloy cluster expansions we compute the phase diagrams 72 TMD monolayer alloys and classify the mixing behavior. We show that ordered phases in general are absent at room temperature but that there exists some alloys, which have a stable Janus phase at room temperature. Furthermore, for a subset of these alloys, we quantify the band edge bowing and show that the band edge positions for the mixing alloys can be continuously tuned in the range set by the boundary phases.

cond-mat.mtrl-sci↗
arXiv2022

Exciton landscape in van der Waals heterostructures

van der Waals heterostructures consisting of vertically stacked transition-metal dichalcogenides (TMDs) exhibit a rich landscape of bright and dark intra- and interlayer excitons. In spite of a growing literature in this field of research, the type of excitons dominating optical spectra in different van der Waals heterostructures has not yet been well established. The spectral position of exciton states depends strongly on the strength of hybridization and energy renormalization due to the periodic moiré potential. Combining exciton density-matrix formalism and density-functional theory, we shed light on the exciton landscape in TMD homo- and heterobilayers at different stackings. This allows us to identify on a microscopic footing the energetically lowest-lying exciton state for each material and stacking. Furthermore, we disentangle the contribution of hybridization and layer polarization-induced alignment shifts of dark and bright excitons in photoluminescence spectra. By revealing the exciton landscape in van der Waals heterostructures, our work provides the basis for further studies of the optical, dynamical, and transport properties of this technologically promising class of nanomaterials.

cond-mat.mes-hall↗
arXiv2021

Quantitative predictions of thermodynamic hysteresis: Temperature-dependent character of the phase transition in Pd-H

The thermodynamics of phase transitions between phases that are size-mismatched but coherent differs from conventional stress-free thermodynamics. Most notably, in open systems such phase transitions are always associated with hysteresis. In spite of experimental evidence for the relevance of these effects in technologically important materials such as Pd hydride, a recipe for first-principles-based atomic-scale modeling of coherent, open systems has been lacking. Here, we develop a methodology for quantifying phase boundaries, hysteresis, and coherent interface free energies using density-functional theory, alloy cluster expansions, and Monte Carlo simulations in a constrained ensemble. We apply this approach to Pd--H and show that the phase transition changes character above approximately 400 K, occurring with an at all times spatially homogeneous hydrogen concentration, i.e., without coexistence between the two phases. Our results are consistent with experimental observations but reveal aspects of hydride formation in Pd nanoparticles that have not yet been accessible in experiment.

cond-mat.mtrl-sci↗