arXiv subjects

Natalio Mingo

Publications and source records attributed to Natalio Mingo.

At least 19 recordsLinked to original sources

arXiv2024

Can silica nanoparticles improve lithium transport in polymer electrolytes?

The question of if silica nanoparticles can enhance the ionic conductivity of a polymer electrolyte above its crystallization temperature has remained unclear for the two decades following the first experiments on these systems. We use Molecular Dynamics simulations to decipher the atomic scale mechanisms affecting the properties of LiTFSI-poly(ethylene oxide) electrolytes upon the addition of silica nanoparticles. At any ionic concentration, adding nanoparticles significantly decreases the conductivity. Most of this reduction can be simply accounted for by the diffusion equation, resulting from the fact that the space occupied by the nanoparticles is made inactive and unable to sustain ionic diffusion. We identify two distinct regimes, above and below a concentration threshold, corresponding to very different ionic distributions and coordination features of the various species. The lack of conductivity enhancement observed in the simulations supports the conclusions of some recent measurements, and disagrees with the earliest experimental reports on hybrid silica/polyethylene-oxide electrolytes.

cond-mat.soft↗

arXiv2024

Modelling structure and ionic diffusion in a class of ionic liquid crystal-based solid electrolytes

Next-generation high-efficiency Li-ion batteries require an electrolyte that is both safe and thermally stable. A possible choice for high performance all-solid-state Li-ion batteries is a liquid crystal, which possesses properties in-between crystalline solids and isotropic liquids. By employing molecular dynamics simulations together with various experimental techniques, we have designed and analyzed a novel liquid crystal electrolyte composed of rigid naphthalene-based moieties as mesogenic units, grafted to flexible alkyl chains of different lengths. We have synthesized novel highly ordered lamellar phase liquid crystal electrolytes at 99% purity and have evaluated the effect of alkyl chain length variation on ionic conduction. We find that the conductivity of the liquid crystal electrolytes is directly dependent on the extent of the nanochannels formed by molecule self-organization, which itself depends non-monotonously on the size of the alkyl chains. In addition, we show that the ion pair interaction between the anionic center of the liquid crystal molecules and the Li+ ions plays a crucial role in the overall conductivity. Based on our results, we suggest that further improvement of the ionic conductivity performance is possible, making this novel family of liquid crystal electrolytes a promising option for the design of entirely solid-state Li+ ion batteries.

cond-mat.mtrl-sci↗

arXiv2024

Two-step growth mechanism of the solid electrolyte interphase in argyrodyte/Li-metal contacts

The structure and growth of the Solid Electrolyte Interphase (SEI) region between an electrolyte and an electrode is one of the most fundamental, yet less-well understood phenomena in solid-state batteries. We present a parameter-free atomistic simulation of the SEI growth for one of the currently promising solid electrolytes (Li$_6$PS$_5$Cl), based on \textit{ab initio} trained machine learning (ML) interatomic potentials, for over 30,000 atoms during 10 ns, well-beyond the capabilities of conventional MD. This unveils a two-step growth mechanism: Li-argyrodite chemical reaction leading to the formation of an amorphous phase, followed by a kinetically slower crystallization of the reaction products into a 5Li$_2$SLi$_3$PLiCl solid solution. The simulation results support the recent, experimentally founded hypothesis of an indirect pathway of electrolyte reduction. These findings shed light on the intricate processes governing SEI evolution, providing a valuable foundation for the design and optimization of next-generation solid-state batteries.

cond-mat.mtrl-sci↗

arXiv2022

Finite temperature dielectric properties of KTaO$_3$ from first principles and machine learning: Phonon spectra, Barrett law, strain engineering and electrostriction

Despite important breakthroughs in the last decade, the calculation of temperature dependent properties of solids still remains a challenging task, especially in the vicinity of structural phase transitions. We show that the combination of machine-learning interatomic potentials with quantum self-consistent ab initio lattice dynamics allows to calculate efficiently the temperature dependence of dielectric properties of the quantum paraelectric perovskite KTaO$_3$, with a precision beyond what could be reasonably achieved using plain density functional theory. We first follow the strong anharmonic softening of the polar mode in this incipient ferroelectric material, and the resulting divergence of the dielectric constant that eventually saturates due to the interplay between temperature and quantum fluctuations. Further, we predict the stability range of the quantum paraelectric state under the application of epitaxial strain at 0 K and 300 K. Finally, we calculate the temperature dependence of electrostrictive tensors for this material and show that giant electrostriction in KTaO$_3$ is to be expected also at room temperature under the condition of strain engineering.

cond-mat.mtrl-sci↗

arXiv2022

Site independent strong phonon-vacancy scattering in high temperature ceramics ZrB$_2$ and HfB$_2$

Similar effects of metal and boron vacancies on phonon scattering and lattice thermal conductivity ($κ_l$) of ZrB$_2$ and HfB$_2$ are reported. These defects challenge the conventional understanding that associates larger impacts to bigger defects. We find the underlying reason to be a strong local perturbation caused by the boron vacancy that substantially changes the interatomic force constants. In contrast, a long ranged but weaker perturbation is seen in the case metal vacancies. We show that these behaviours originate from a mixed metallic and covalent bonding nature in the metal diborides. The thermal transport calculations are performed in a complete \textit{ab initio} framework based on Boltzmann transport equation and density functional theory. Phonon-vacancy scattering is calculated using \textit{ab initio} Green's function approach. Effects of natural isotopes and grain boundaries on $κ_l$ are also systematically investigated, however we find an influential role of vacancies to explain large variations seen in the experiments. We further report a two-order of magnitude difference between the amorphous and pure-crystal limits. Our results outline significant material design aspects for these multi-functional high temperature ceramics.

cond-mat.mtrl-sci↗

arXiv2021

Free energy of (CoxMn1-x)3O4 mixed phases from machine-learning-enhanced ab initio calculations

(CoxMn1-x)3O4 is a promising candidate material for solar thermochemical energy storage. A high-temperature model for this system would provide a valuable tool for evaluating its potential. However, predicting phase diagrams of complex systems with ab initio calculations is challenging due to the varied sources affecting the free energy, and with the prohibitive amount of configurations needed in the configurational entropy calculation. In this work, we compare three different machine learning (ML) approaches for sampling the configuration space of (CoxMn1-x)3O4, including a simpler ML approach, which would be suitable for application in high-throughput studies. We use experimental data for a feature of the phase diagram to assess the accuracy of model predictions. We find that with some methods, data pre-treatment is needed to obtain accurate predictions due to inherently composition-imbalanced training data for a mixed phase. We highlight that the important entropy contributions depend on the physical regimes of the system under investigation and that energy predictions with ML models are more challenging at compositions where there are energetically competing ground state crystal structures. Similar methods to those outlined here can be used to screen other candidate materials for thermochemical energy storage

cond-mat.mtrl-sci↗

arXiv2021

Quantum Self-Consistent Ab-Initio Lattice Dynamics

The Quantum Self-Consistent Ab-Initio Lattice Dynamics package (QSCAILD) is a python library that computes temperature-dependent effective 2nd and 3rd order interatomic force constants in crystals, including anharmonic effects. QSCAILD's approach is based on the quantum statistics of a harmonic model. The program requires the forces acting on displaced atoms of a solid as an input, which can be obtained from an external code based on density functional theory, or any other calculator. This article describes QSCAILD's implementation, clarifies its connections to other methods, and illustrates its use in the case of the SrTiO3 cubic perovskite structure.

cond-mat.mtrl-sci↗

arXiv2020

High-throughput study of the static dielectric constant at high temperatures in oxide and fluoride cubic perovskites

Using finite-temperature phonon calculations and the Lyddane-Sachs-Teller relations, we calculate ab initio the static dielectric constants of 78 semiconducting oxides and fluorides with cubic perovskite structures at 1000 K. We first compare our method with experimental measurements, and we find that it succeeds in describing the temperature dependence and the relative ordering of the static dielectric constant $ε_{DC}$ in the series of oxides BaTiO$_{3}$, SrTiO$_{3}$, KTaO$_{3}$. We show that the effects of anharmonicity on the ion-clamped dielectric constant, on Born charges, and on phonon lifetimes, can be neglected in the framework of our high-throughput study. Based on the high-temperature phonon spectra, we find that the dispersion of $ε_{DC}$ is one order of magnitude larger amongst oxides than fluorides at 1000 K. We display the correlograms of the dielectric constants with simple structural descriptors, and we point out that $ε_{DC}$ is actually well correlated with the infinite-frequency dielectric constant $ε_{\infty}$, even in those materials with phase transitions in which $ε_{DC}$ is strongly temperature-dependent.

cond-mat.mtrl-sci↗

arXiv2020

How do defects limit the ultrahigh thermal conductivity of BAs? A first principles study

The promise enabled by BAs high thermal conductivity in power electronics cannot be assessed without taking into account the reduction incurred when doping the material. Using first principles calculations, we determine the thermal conductivity reduction induced by different group IV impurities in BAs as a function of concentration and charge state. We unveil a general trend, where neutral impurities scatter phonons more strongly than the charged ones. $\text{C}_{\text{B}}$ and $\text{Ge}_{\text{As}}$ impurities show by far the weakest phonon scattering and retain BAs $κ$ values of over $\sim$ 1000 $\text{W}\cdot\text{K}^{-1}\cdot\text{m}^{-1}$ even up to high densities making them ideal n-type and p-type dopants. Furthermore, going beyond the doping compensation threshold associated to Fermi level pinning triggers observable changes in the thermal conductivity. This informs design considerations on the doping of BAs, and it also suggests a direct way to determine the onset of compensation doping in experimental samples.

cond-mat.mtrl-sci↗

arXiv2020

Growth, charge and thermal transport of flowered graphene

We report on the structural and transport properties of the smallest dislocation loop in graphene, known as a flower defect. First, by means of advanced experimental imaging techniques, we deduce how flower defects are formed during recrystallization of chemical vapor deposited graphene. We propose that the flower defects arise from a bulge type mechanism in which the flower domains are the grains left over by dynamic recrystallisation. Next, in order to evaluate the use of such defects as possible building blocks for all-graphene electronics, we combine multiscale modeling tools to investigate the structure and the electron and phonon transport properties of large monolayer graphene samples with a random distribution of flower defects. For large enough flower densities, we find that electron transport is strongly suppressed while, surprisingly, hole transport remains almost unaffected. These results suggest possible applications of flowered graphene for electron energy filtering. For the same defect densities, phonon transport is reduced by orders of magnitude as elastic scattering by defects becomes dominant. Heat transport by flexural phonons, key in graphene, is largely suppressed even for very low concentrations.

cond-mat.mtrl-sci↗

arXiv2019

Thermal conductivity of crystalline AlN and the influence of atomic-scale defects

Aluminum nitride (AlN) plays a key role in modern power electronics and deep-ultraviolet photonics, where an understanding of its thermal properties is essential. Here we measure the thermal conductivity of crystalline AlN by the 3$ω$ method, finding it ranges from 674 ${\pm}$ 56 W/m/K at 100 K to 186 ${\pm}$ 7 W/m/K at 400 K, with a value of 237 ${\pm}$ 6 W/m/K at room temperature. We compare these data with analytical models and first principles calculations, taking into account atomic-scale defects (O, Si, C impurities, and Al vacancies). We find Al vacancies play the greatest role in reducing thermal conductivity because of the largest mass-difference scattering. Modeling also reveals that 10% of heat conduction is contributed by phonons with long mean free paths, over ~7 $μ$m at room temperature, and 50% by phonons with MFPs over ~0.3 $μ$m. Consequently, the effective thermal conductivity of AlN is strongly reduced in sub-micron thin films or devices due to phonon-boundary scattering.

cond-mat.mtrl-sci↗

arXiv2019

Combined treatment of phonon scattering by electrons and point defects explains the thermal conductivity reduction in highly-doped Si

The mechanisms causing the reduction in lattice thermal conductivity in highly P- and B-doped Si are looked into in detail. Scattering rates of phonons by point defects, as well as by electrons, are calculated from first principles. Lattice thermal conductivities are calculated considering these scattering mechanisms both individually and together. It is found that at low carrier concentrations and temperatures phonon scattering by electrons is dominant and can reproduce the experimental thermal conductivity reduction. However, at higher doping concentrations the scattering rates of phonons by point defects dominate the ones by electrons except for the lowest phonon frequencies. Consequently, phonon scattering by point defects contributes substantially to the thermal conductivity reduction in Si at defect concentrations above $10^{19}$ cm$^{-3}$ even at room temperature. Only when, phonon scattering by both point defects and electrons are taken into account, excellent agreement is obtained with the experimental values at all temperatures.

cond-mat.mtrl-sci↗

arXiv2019

Anharmonic Thermodynamics of Vacancies Using a Neural Network Potential

Lattice anharmonicity is thought to strongly affect vacancy concentrations in metals at high temperatures. It is however non-trivial to account for this effect directly using density functional theory (DFT). Here we develop a deep neural network potential for aluminum that overcomes the limitations inherent to DFT, and we use it to obtain accurate anharmonic vacancy formation free energies as a function of temperature. While confirming the important role of anharmonicity at high temperatures, the calculation unveils a markedly nonlinear behavior of the vacancy formation entropy and shows that the vacancy formation free energy only violates Arrhenius law at temperatures above 600 K, in contrast with previous DFT calculations.

cond-mat.mtrl-sci↗

arXiv2019

Effect of local chemistry and structure on thermal transport in doped GaAs

Using a first-principles approach, we analyze the impact of \textit{DX} centers formed by S, Se, and Te dopant atoms on the thermal conductivity of GaAs. Our results are in good agreement with experiments and unveil the physics behind the drastically different effect of each kind of defect. We establish a causal chain linking the electronic structure of the dopants to the thermal conductivity of the bulk solid, a macroscopic transport coefficient. Specifically, the presence of lone pairs leads to the formation of structurally asymmetric \textit{DX} centers that cause resonant scattering of incident phonons. The effect of such resonances is magnified when they affect the part of the spectrum most relevant for thermal transport. We show that these resonances are associated with localized vibrational modes in the perturbed phonon spectrum. Finally, we illustrate the connection between flat adjacent minima in the energy landscape and resonant phonon scattering through detailed analyses of the energy landscape of the defective structures.

cond-mat.mtrl-sci↗

arXiv2019

Thermal resistance of GaN/AlN graded interfaces

Compositionally graded interfaces in power electronic devices eliminate dislocations, but they can also decrease thermal conduction, leading to overheating. We quantify the thermal resistances of GaN/AlN graded interfaces of varying thickness using ab initio Green's functions, and compare them with the abrupt interface case. A non-trivial power dependence of the thermal resistance versus interface thickness emerges from the interplay of alloy and mismatch scattering mechanisms. We show that the overall behavior of such graded interfaces is very similar to that of a thin-film of an effective alloy in the length scales relevant to real interfaces.

cond-mat.mtrl-sci↗

arXiv2018

Magnetic Order and Lattice Instabilities in Ni$_{2}$Mn$_{1+x}$Sn$_{1-x}$ Heusler based Magnetic Shape-Memory Alloys

The magnetic correlations in the austenite phase and the consequent martensitic transition in inverse magnetocaloric alloys, Ni$_{2}$Mn$_{1+x}$Sn$_{1-x}$, have been a matter of debate for decades. We conclusively establish using {\it ab initio} phonon calculations that the spin alignment of excess Mn at the Sn site (Mn$_{Sn}$) with the existing Mn in the unit cell in the high temperature cubic phase of Ni-Mn-Sn alloy is ferromagnetic (FM), and not ferrimagnetic (FI), resolving a long lasting controversy. Using first principles density functional perturbation theory (DFPT), we observe an instability of the TA$_{2}$ mode along the $Γ$-M direction in the FM phase, very similar to that observed in the prototypical ferromagnetic shape memory alloy (FSMA) Ni$_{2}$MnGa. This specific instability is not observed in the FI phase. Further finite temperature first principles lattice dynamics calculations reveal that at 300 K the FM phase becomes mechanically stable, while the FI phase continue to remain unstable providing credence to the fact that the high-temperature phase has FM order. These results will be primordial to understand the magneto-structural properties of this class of compounds.

cond-mat.str-el↗

arXiv2018

Ab initio lattice thermal conductivity of bulk and thin-film $α$-Al$\mathrm{_2}$O$\mathrm{_3}$

The thermal conductivities ($κ$) of bulk and thin-film $α$-Al$_2$O$_3$ are calculated from first principles using both the local density approximation (LDA), and the generalized gradient approximation (GGA) to exchange and correlation. The room temperature single crystal LDA value $\sim39~$W/m$~$K agrees well with the experimental values $\sim35-39~$W/m$~$K, whereas the GGA values are much smaller $\sim$26$~$W/m$~$K. Throughout the temperature range, LDA is found to slightly overestimate $κ$ whereas GGA strongly underestimates it. We calculate the $κ$ of crystalline $α$-Al$\mathrm{_2}$O$\mathrm{_3}$ thin films and observe a maximum of 79$\%$ reduction for $10~$nm thickness.

cond-mat.mtrl-sci↗

arXiv2018

Vibrational properties of metastable polymorph structures by machine learning

Despite vibrational properties being critical for the ab initio prediction of the finite temperature stability and transport properties of solids, their inclusion in ab initio materials repositories has been hindered by expensive computational requirements. Here we tackle the challenge, by showing that a good estimation of force constants and vibrational properties can be quickly achieved from the knowledge of atomic equilibrium positions using machine learning. A random-forest algorithm trained on only 121 metastable structures of KZnF$_3$ reaches a maximum absolute error of 0.17 eV/$\textrmÅ^2$ for the interatomic force constants, and it is much less expensive than training the complete force field for such compound. The predicted force constants are then used to estimate phonon spectral features, heat capacities, vibrational entropies, and vibrational free energies, which compare well with the ab initio ones. The approach can be used for the rapid estimation of stability at finite temperatures.

cond-mat.mtrl-sci↗