arXiv subjects

Natalio Mingo

Publications and source records attributed to Natalio Mingo.

At least 37 records · Page 2Linked to original sources

arXiv2017

Phonon transport unveils the prevalent point defects in GaN

Determining the types and concentrations of vacancies present in intentionally doped GaN is a notoriously difficult and long-debated problem. Here we use an unconventional approach, based on thermal transport modeling, to determine the prevalence of vacancies in previous measurements. This allows us to provide conclusive evidence of the recent hypothesis that gallium vacancies in ammonothermally grown samples can be complexed with hydrogen. Our calculations for O-doped and Mg-O co-doped samples yield a consistent picture interlinking dopant and vacancy concentration, carrier density, and thermal conductivity, in excellent agreement with experimental measurements. These results also highlight the predictive power of ab initio phonon transport modeling, and its value for understanding and quantifying defects in semiconductors.

cond-mat.mtrl-sci↗

arXiv2017

First-principles quantitative prediction of the lattice thermal conductivity in random semiconductor alloys: the role of force-constant disorder

The standard theoretical understanding of the lattice thermal conductivity, $κ_{\ell}$, of semiconductor alloys assumes that mass disorder is the most important source of phonon scattering. In contrast, we show that the hitherto neglected contribution of force-constant (IFC) disorder is essential to accurately predict the $κ_{\ell}$ of those polar compounds characterized by a complex atomic-scale structure. We have developed an \emph{ab initio} method based on special quasirandom structures and Green's functions, and including the role of IFC disorder, and applied it in order to calculate the $κ_{\ell}$ of $\mathrm{In_{1-x}Ga_xAs}$ and $\mathrm{Si_{1-x}Ge_x}$ alloys. We show that, while for $\mathrm{Si_{1-x}Ge_x}$, phonon-alloy scattering is dominated by mass disorder, for $\mathrm{In_{1-x}Ga_xAs}$, the inclusion of IFC disorder is fundamental to accurately reproduce the experimentally observed $κ_{\ell}$. As the presence of a complex atomic-scale structure is common to most III-V and II-VI random semiconductor alloys, we expect our method to be suitable for a wide class of materials.

cond-mat.mtrl-sci↗

arXiv2017

The AFLOW Fleet for Materials Discovery

The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational materials design automates high-throughput first principles calculations, and provides tools for data verification and dissemination for a broad community of users. AFLOW incorporates different computational modules to robustly determine thermodynamic stability, electronic band structures, vibrational dispersions, thermo-mechanical properties and more. The AFLOW data repository is publicly accessible online at aflow.org, with more than 1.7 million materials entries and a panoply of queryable computed properties. Tools to programmatically search and process the data, as well as to perform online machine learning predictions, are also available.

cond-mat.mtrl-sci↗

arXiv2017

AFLOW-ML: A RESTful API for machine-learning predictions of materials properties

Machine learning approaches, enabled by the emergence of comprehensive databases of materials properties, are becoming a fruitful direction for materials analysis. As a result, a plethora of models have been constructed and trained on existing data to predict properties of new systems. These powerful methods allow researchers to target studies only at interesting materials $\unicode{x2014}$ neglecting the non-synthesizable systems and those without the desired properties $\unicode{x2014}$ thus reducing the amount of resources spent on expensive computations and/or time-consuming experimental synthesis. However, using these predictive models is not always straightforward. Often, they require a panoply of technical expertise, creating barriers for general users. AFLOW-ML (AFLOW $\underline{\mathrm{M}}$achine $\underline{\mathrm{L}}$earning) overcomes the problem by streamlining the use of the machine learning methods developed within the AFLOW consortium. The framework provides an open RESTful API to directly access the continuously updated algorithms, which can be transparently integrated into any workflow to retrieve predictions of electronic, thermal and mechanical properties. These types of interconnected cloud-based applications are envisioned to be capable of further accelerating the adoption of machine learning methods into materials development.

cond-mat.mtrl-sci↗

arXiv2017

Glass-Like Thermal Conductivity in Nanostructures of a Complex Anisotropic Crystal

Size effects on vibrational modes in complex crystals remain largely unexplored, despite their importance in a variety of electronic and energy conversion technologies. Enabled by advances in a four-probe thermal transport measurement method, we report the observation of glass-like thermal conductivity in ~20 nm thick single crystalline ribbons of higher manganese silicide, a complex, anisotropic crystal with a ~10 nm scale lattice constant along the incommensurate c axis. The boundary scattering effect is strong for many vibrational modes because of a strong anisotropy in their group velocities or diffusive nature, while confinement effects are pronounced for acoustic modes with long wavelengths along the c axis. Furthermore, the transport of the non-propagating, diffusive modes is suppressed in the nanostructures by the increased incommensurability between the two substructures as a result of the unusual composition of the nanostructure samples. These unique effects point to diverse, new approaches to suppressing the lattice thermal conductivity in complex materials.

cond-mat.mtrl-sci↗

arXiv2017

Quasiballistic heat removal from small sources studied from first principles

Heat sources whose characteristic dimension $R$ is comparable to phonon mean free paths display thermal resistances that exceed conventional diffusive predictions. This has direct implications to (opto)electronics thermal management and phonon spectroscopy. Theoretical analyses have so far limited themselves to particular experimental configurations. Here, we build upon the multidimensional Boltzmann transport equation (BTE) to derive universal expressions for the apparent conductivity suppression $S(R) = κ_{\text{eff}}(R)/κ_{\text{bulk}}$ experienced by radially symmetric 2D and 3D sources. In striking analogy to cross-plane heat conduction in thin films, a distinct quasiballistic regime emerges between ballistic ($κ_{\text{eff}} \sim R$) and diffusive ($κ_{\text{eff}} \simeq κ_{\text{bulk}}$) asymptotes that displays a logarithmic dependence $κ_{\text{eff}} \sim \ln(R)$ in single crystals and fractional power dependence $κ_{\text{eff}} \sim R^{2-α}$ in alloys (with $α$ the Lévy superdiffusion exponent). Analytical solutions and Monte Carlo simulations for spherical and circular heat sources in Si, GaAs, Si$_{0.99}$Ge$_{0.01}$ and Si$_{0.82}$Ge$_{0.18}$, all carried out from first principles, confirm the predicted generic tendencies. Contrary to the thin film case, common approximations like kinetic theory estimates $κ_{\text{eff}} \simeq \sum S_ω^{\text{grey}} \, κ_ω$ and modified Fourier temperature curves perform relatively poorly. Up to threefold deviations from the BTE solutions for sub-100$\,$nm sources underline the need for rigorous treatment of multidimensional nondiffusive transport.

cond-mat.mes-hall↗

arXiv2017

Materials Screening for the Discovery of New Half-Heuslers: Machine Learning versus Ab Initio Methods

Machine learning (ML) is increasingly becoming a helpful tool in the search for novel functional compounds. Here we use classification via random forests to predict the stability of half-Heusler (HH) compounds, using only experimentally reported compounds as a training set. Cross-validation yields an excellent agreement between the fraction of compounds classified as stable and the actual fraction of truly stable compounds in the ICSD. The ML model is then employed to screen 71,178 different 1:1:1 compositions, yielding 481 likely stable candidates. The predicted stability of HH compounds from three previous high throughput ab initio studies is critically analyzed from the perspective of the alternative ML approach. The incomplete consistency among the three separate ab initio studies and between them and the ML predictions suggests that additional factors beyond those considered by ab initio phase stability calculations might be determinant to the stability of the compounds. Such factors can include configurational entropies and quasiharmonic contributions.

cond-mat.mtrl-sci↗

arXiv2017

Phonon thermal transport in 2H, 4H and 6H silicon carbide from first principles

Silicon carbide (SiC) is a wide band gap semiconductor with a variety of industrial applications. Among its many useful properties is its high thermal conductivity, which makes it advantageous for thermal management applications. In this paper we present \textit{ab initio} calculations of the in-plane and cross-plane thermal conductivities, $κ_{\text{in}}$ and $κ_{\text{out}}$, of three common hexagonal polytypes of SiC: 2H, 4H and 6H. The phonon Boltzmann transport equation is solved iteratively using as input interatomic force constants determined from density functional theory. Both $κ_{\text{in}}$ and $κ_{\text{out}}$ decrease with increasing $n$ in $n$H SiC because of additional low-lying optic phonon branches. These optic branches are characterized by low phonon group velocities, and they increase the phase space for phonon-phonon scattering of acoustic modes. Also, for all $n$, $κ_{\text{in}}$ is found to be larger than $κ_{\text{out}}$ in the temperature range considered. At electron concentrations present in experimental samples, scattering of phonons by electrons is shown to be negligible except well below room temperature where it can lead to a significant reduction of the lattice thermal conductivity. This work highlights the power of \textit{ab initio} approaches in giving quantitative, predictive descriptions of thermal transport in materials. It helps explain the qualitative disagreement that exists among different sets of measured thermal conductivity data and provides information of the relative quality of samples from which measured data was obtained.

cond-mat.mtrl-sci↗

arXiv2017

almaBTE: a solver of the space-time dependent Boltzmann transport equation for phonons in structured materials

almaBTE is a software package that solves the space- and time-dependent Boltzmann transport equation for phonons, using only ab-initio calculated quantities as inputs. The program can predictively tackle phonon transport in bulk crystals and alloys, thin films, superlattices, and multiscale structures with size features in the nm-$μ$m range. Among many other quantities, the program can output thermal conductances and effective thermal conductivities, space-resolved average temperature profiles, and heat-current distributions resolved in frequency and space. Its first-principles character makes almaBTE especially well suited to investigate novel materials and structures. This article gives an overview of the program structure and presents illustrative examples for some of its uses.

physics.comp-ph↗

arXiv2017

Exceptionally strong phonon scattering by B substitution in cubic SiC

We use ab-initio calculations to predict the thermal conductivity of cubic SiC with different types of defects. An excellent quantitative agreement with previous experimental measurements is found. The results unveil that B$_\mathrm{C}$ substitution has a much stronger effect than any of the other defect types in 3C-SiC, including vacancies. This finding contradicts the prediction of the classical mass-difference model of impurity scattering, according to which the effects of B$_\mathrm{C}$ and N$_\mathrm{C}$ would be similar and much smaller than that of the C vacancy. The strikingly different behavior of the B$_\mathrm{C}$ defect arises from a unique pattern of resonant phonon scattering caused by the broken structural symmetry around the B impurity.

cond-mat.mtrl-sci↗

arXiv2017

Structural Complexity and Phonon Physics in 2D Arsenenes

In the quest for stable 2D arsenic phases, four different structures have been recently claimed to be stable. We show that, due to phonon contributions, the relative stability of those structures differs from previous reports and depends crucially on temperature. We also show that one of those four phases is in fact mechanically unstable. Furthermore, our results challenge the common assumption of an inverse correlation between structural complexity and thermal conductivity. Instead, a richer picture emerges from our results, showing how harmonic interactions, anharmonicity and symmetries all play a role in modulating thermal conduction in arsenenes. More generally, our conclusions highlight how vibrational properties are an essential element to be carefully taken into account in theoretical searches for new 2D materials.

cond-mat.mtrl-sci↗

arXiv2017

How the Chemical Composition Alone Can Predict Vibrational Free Energies and Entropies of Solids

Computing vibrational free energies ($F_{vib}$) and entropies ($S_{vib}$) has posed a long standing challenge to the high-throughput ab initio investigation of finite temperature properties of solids. Here we use machine-learning techniques to efficiently predict $F_{vib}$ and $S_{vib}$ of crystalline compounds in the Inorganic Crystal Structure Database. By employing descriptors based simply on the chemical formula and using a training set of only 300 compounds, mean absolute errors of less than 0.04 meV/K/atom (15 meV/atom) are achieved for $S_{vib}$ ($F_{vib}$), whose values are distributed within a range of 0.9 meV/K/atom (300 meV/atom.) In addition, for training sets containing fewer than 2,000 compounds the chemical formula alone is shown to perform as well as, if not better than, four other more complex descriptors previously used in the literature. The accuracy and simplicity of the approach mean that it can be advantageously used for the fast screening of phase diagrams or chemical reactions at finite temperatures.

cond-mat.mtrl-sci↗

arXiv2016

Unraveling the dominant phonon scattering mechanism in thermoelectric compound ZrNiSn

Determining defect types and concentrations remains a big challenge of semiconductor materials science. By using ab-initio thermal conductivity calculations we reveal that Ni/vacancy antisites, and not the previously claimed Sn/Zr antisites, are the dominant defects affecting thermal transport in half-Heusler compound ZrNiSn. Our calculations correctly predict the thermal conductivity dependence with temperature and concentration, in quantitative agreement with published experimental results. Furthermore, we find a characteristic proportionality between phonon-antisite scattering rates and the sixth power of phonon frequency, for which we provide an analytic derivation. These results suggest that thermal conductivity measurements in combination with ab-initio calculations can be used to quantitatively assess defect types and concentrations in semiconductors.

cond-mat.mtrl-sci↗

arXiv2016

Anomalous thermal conductivity and suppression of negative thermal expansion in ScF3

The empty perovskite ScF3 exhibits negative thermal expansion up to 1100 K. We demonstrate that ab-initio calculations of temperature-dependent effective phonon spectra allow to quantitatively describe the behavior of this compound and the suppression of negative thermal expansion. Based on this result, we predict an anomalous temperature dependence of the thermal conductivity and interpret it as a general feature of the perovskite class. Finally, we comment on the fact that the suppression of negative thermal expansion at such a high temperature is beyond the reach of the quasi-harmonic approximation and we discuss this suppression based on the temperature-dependence of the mode Grüneisen parameters.

cond-mat.mtrl-sci↗

arXiv2016

High throughput thermal conductivity of high temperature solid phases: The case of oxide and fluoride perovskites

Using finite-temperature phonon calculations and machine-learning methods, we calculate the mechanical stability of about 400 semiconducting oxides and fluorides with cubic perovskite structures at 0 K, 300 K and 1000 K. We find 92 mechanically stable compounds at high temperatures -- including 36 not mentioned in the literature so far -- for which we calculate the thermal conductivity. We demonstrate that the thermal conductivity is generally smaller in fluorides than in oxides, largely due to a lower ionic charge, and describe simple structural descriptors that are correlated with its magnitude. Furthermore, we show that the thermal conductivities of most cubic perovskites decrease more slowly than the usual $T^{-1}$ behavior. Within this set, we also screen for materials exhibiting negative thermal expansion. Finally, we describe a strategy to accelerate the discovery of mechanically stable compounds at high temperatures.

cond-mat.mtrl-sci↗

arXiv2016

Cross-plane heat conduction in thin films with ab-initio phonon dispersions and scattering rates

We present a first-principles study of the cross-plane thermal conductivity $κ_{\perp}$ in a wide variety of semiconductor thin films. We introduce a simple suppression model that matches variance-reduced Monte Carlo simulations with ab-initio phonon dispersions and scattering rates within $\leq 5\%$ even for anisotropic compounds. This, in turn, enables accurate $κ_{\perp}$ reconstruction from tabulated cumulative conductivity curves $κ_Σ(Λ_{\perp})$. We furthermore reveal, and explain, a distinct quasiballistic regime characterised by a fractional thickness dependence $κ_{\perp} \sim L^{2-α}$ in alloys (where $α$ is the Lévy exponent) and logarithmic dependence $κ_{\perp} \sim \ln(L)$ in single crystals. These observations culminate in the formulation of two compact parametric forms for $κ_{\perp}(L)$ that can fit the first-principles curves across the entire ballistic-diffusive range within a few percent for all investigated compounds.

cond-mat.mes-hall↗

arXiv2016

Physically founded phonon dispersions of few-layer materials, and the case of borophene

An increasing number of theoretical calculations on few-layer materials have been reporting a non-zero sound velocity for all three acoustic phonon modes. In contrast with these reports, here we show that the lowest phonon dispersion branch of atomistically described few-layer materials should be quadratic, and this can have dramatic consequencies on calculated properties, such as the thermal conductivity. By reformulating the interatomic force constants (IFC) in terms of internal coordinates, we find that a delicate balance between the IFCs is responsible for this quadraticity. This balance is hard to obtain in ab-initio calculations even if all the symmetries are numerically enforced a posteriori, but it arises naturally in our approach. We demonstrate the phenomenon in the case of borophene, where a very subtle correction to the ab-initio IFCs yields the physically correct quadratic dispersion, while leaving the rest of the spectrum virtually unmodified. Such quadraticity nevertheless has a major effect on the computed lattice thermal conductivity, which in the case of borophene changes by more than a factor 2, and reverses its anisotropy, when the subtle IFC correction is put in place.

cond-mat.mtrl-sci↗

arXiv2014

Superdiffusive heat conduction in semiconductor alloys -- I. Theoretical foundations

Semiconductor alloys exhibit a strong dependence of effective thermal conductivity on measurement frequency. So far this quasi-ballistic behaviour has only been interpreted phenomenologically, providing limited insight into the underlying thermal transport dynamics. Here, we show that quasi-ballistic heat conduction in semiconductor alloys is governed by Lévy superdiffusion. By solving the Boltzmann transport equation (BTE) with ab initio phonon dispersions and scattering rates, we reveal a transport regime with fractal space dimension $1 < α< 2$ and superlinear time evolution of mean square energy displacement $σ^2(t) \sim t^β (1 < β< 2)$. The characteristic exponents are directly interconnected with the order $n$ of the dominant phonon scattering mechanism $τ\sim ω^{-n} (n>3)$ and cumulative conductivity spectra $κ_Σ(τ;Λ)\sim (τ;Λ)^γ$ resolved for relaxation times or mean free paths through simple relations $α= 3-β= 1 + 3/n = 2 - γ$. The quasi-ballistic transport inside alloys is no longer governed by Brownian motion, but instead dominated by Lévy dynamics. This has important implications for the interpretation of thermoreflectance (TR) measurements with modified Fourier theory. Experimental $α$ values for InGaAs and SiGe, determined through TR analysis with a novel Lévy heat formalism, match ab initio BTE predictions within a few percent. Our findings lead to a deeper and more accurate quantitative understanding of the physics of nanoscale heat flow experiments.

cond-mat.mtrl-sci↗