arXiv subjects

Jose J. Plata

Publications and source records attributed to Jose J. Plata.

11 recordsLinked to original sources

arXiv2026

Off-stoichiometric variable doping for exceptional power factors in L2$_1$ Fe$_2$VAlM$_x$ (M=Ti, W) epitaxial thin films

We show that the addition of Ti or W to stoichiometric L2$_1$ Fe$_2$VAl thin films by sputter codeposition produces off stoichiometric thin film alloys with superior thermoelectric properties than their stoichiometric counterparts. Ti incorporation induces p-type semiconducting behavior, while W incorporation shifts the material toward n-type, hereby enabling simultaneous tuning of both carrier types within a single parent (Fe$_2$VAl) material system, making it highly desirable for thermoelectric devices. The introduction of both Ti and W partly substitutes V in the stoichiometric compound. The partial substitution of V in the stoichiometric alloy allows fine-tuning the band structure of the system and transport properties. With this approach we obtain exceptional maximum power factor values for p and n-type films of 1300 $μ$W/m$\cdot$K$^2$ and 2100 $μ$W/m$\cdot$K$^2$ ,respectively, yielding maximum figures of merit zT of 0.07 and 0.14, respectively.

cond-mat.mtrl-sci↗

arXiv2025

High-Entropy Skutterudites as Thermoelectrics: Potential Synthesizability, Enhanced Stability and Band Convergence via the Cocktail Effect

High entropy materials offer a promising avenue for thermoelectric materials discovery, design, and optimization. However, the large chemical spaces that need to be explored hamper their development. In this work, a large family of high-entropy skutterudites is explored as promising thermoelectric materials. Their potential synthesizability is screened and rationalized using the disordered enthalpy-entropy descriptor through high-throughput density functional theory calculations. In the case of high-entropy skutterudites, the thermodynamic density of states and the entropy gain parameter appear to be key factors for their stabilization. Electronic band structure analyses not only show a reduction in the band gap, which enhances carrier concentration and electrical conductivity, but also a band convergence phenomenon for some specific compositions, which is related to the "cocktail effect". Analyzing atom-projected band structures shows how band convergence is due to the simultaneous presence of Fe, Ni, and Co in the compound. The presence of Rh or Ir, while not contributing to this band convergence effect, can be directly linked to an increase in system's entropy, which enhances the thermodynamic stability of these materials. Transport properties are computed for the most promising compositions, and their dynamical, mechanical, and thermal stability are addressed. Our results demonstrates that these types of compounds open new avenues, not only to enhance thermoelectric efficiency but also to reduce costs by utilizing more abundant elements and also improving their durability.

cond-mat.mtrl-sci↗

arXiv2023

Theoretical investigation of the lattice thermal conductivities of II-IV-V2 pnictide semiconductors

Ternary pnictides semiconductors with II-IV-V2 stoichiometry hold potential as cost effective thermoelectric materials with suitable electronic transport properties, but their lattice thermal conductivities ($κ$) are typically too high. Gaining insight into their vibrational properties is therefore crucial to finding strategies to reduce $κ$ and achieve improved thermoelectric performance. We present a theoretical exploration of the lattice thermal conductivities for a set of pnictide semiconductors with ABX2 composition (A = Zn, Cd; B = Si, Ge, Sn; and X = P, As), using machine-learning based regression algorithms to extract force constants from a reduced number of density functional theory simulations, and then solving the Boltzmann transport equation for phonons. Our results align well available experimental data, decreasing the mean absolute error by ~3 Wm-1K-1 with respect to the best previous set of theoretical predictions. Zn-based ternary pnictides have, on average, more than double the thermal conductivity of the Cd-based compounds. Anisotropic behaviour increases with the mass difference between A and B cations, but while the nature of the anion does not affect the structural anisotropy, the thermal conductivity anisotropy is typically higher for arsenides than for phosphides. We identify compounds, like CdGeAs2, for which nanostructuring to an affordable range of particle sizes could lead to values low enough for thermoelectric applications.

cond-mat.mtrl-sci↗

arXiv2020

High-throughput screening of the thermoelastic properties of ultra-high temperature ceramics

Ultra-high temperature ceramics, UHTCs, are a group of materials with high technological interest because their use in extreme environments. However, their characterization at high temperatures represents the main obstacle for their fast development. Obstacles are found from a experimental point of view, where only few laboratories around the world have the resources to test these materials under extreme conditions, and also from a theoretical point of view, where actual methods are extremely expensive. Here, a new theoretical high-throughput framework for the prediction of the thermoelastic properties of materials is introduced. This approach can be systematically applied to any kind of crystalline material, drastically reducing the computational cost of previous methodologies. Elastic constants for UHTCs have been calculated at a wide range of temperatures with excellent agreement with experimentally reported values. Moreover, other mechanical properties such a bulk modulus, shear modulus or Poisson ration have been also explored. Other frameworks with similar computational cost have been used only for predicting isotropic or averaged properties, however this new approach opens the door to the calculation of anisotropic properties at a very low computational cost.

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

Combining the AFLOW GIBBS and Elastic Libraries for efficiently and robustly screening thermo-mechanical properties of solids

Thorough characterization of the thermo-mechanical properties of materials requires difficult and time-consuming experiments. This severely limits the availability of data and it is one of the main obstacles for the development of effective accelerated materials design strategies. The rapid screening of new potential systems requires highly integrated, sophisticated and robust computational approaches. We tackled the challenge by surveying more than 3,000 crystalline solids within the AFLOW framework with the newly developed "Automatic Elasticity Library" combined with the previously implemented GIBBS method. The first extracts the mechanical properties from automatic self-consistent stress-strain calculations, while the latter employs those mechanical properties to evaluate the thermodynamics within the Debye model. The new thermo-elastic library is benchmarked against a set of 74 experimentally characterized systems to pinpoint a robust computational methodology for the evaluation of bulk and shear moduli, Poisson ratios, Debye temperatures, Grüneisen parameters, and thermal conductivities of a wide variety of materials. The effect of different choices of equations of state is examined and the optimum combination of properties for the Leibfried-Schlömann prediction of thermal conductivity is identified, leading to improved agreement with experimental results than the GIBBS-only approach.

cond-mat.mtrl-sci↗

arXiv2016

Predicting the lattice thermal conductivity of solids by solving the Boltzmann transport equation: AFLOW - AAPL an automated, accurate and effcient framework

One of the most accurate approaches for calculating lattice thermal conductivity, $κ_l$, is solving the Boltzmann transport equation starting from third-order anharmonic force constants. In addition to the underlying approximations of ab-initio parameterization, two main challenges are associated with this path. High computational costs and lack of automation in the frameworks using this methodology affect the discovery rate of novel materials with ad-hoc properties. Here, we present the Automatic-Anharmonic-Phonon-Library, AAPL. It efficiently computes interatomic force constants by making effective use of crystal symmetry analysis, it solves the Boltzmann transport equation to obtain $κ_l$, and allows a fully integrated operation with minimum user intervention, a rational addition to the current high-throughput accelerated materials development framework AFLOW. We show an "experiment versus theory" study of the approach, we compare accuracy and speed with respect to other available packages, and for materials characterized by strong electron localization and correlation, we demonstrate that it is possible to improve accuracy without increasing computational requirements by combining AAPL with the pseudo-hybrid functional ACBN0.

cond-mat.mtrl-sci↗

arXiv2016

High-Throughput Prediction of Finite-Temperature Properties using the Quasi-Harmonic Approximation

In order to calculate thermal properties in automatic fashion, the Quasi-Harmonic Approximation (QHA) has been combined with the Automatic Phonon Library (APL) and implemented within the AFLOW framework for high-throughput computational materials science. As a benchmark test to address the accuracy of the method and implementation, the specific heats, thermal expansion coefficients, Grüneisen parameters and bulk moduli have been calculated for 130 compounds. It is found that QHA-APL can reliably predict such values for several different classes of solids with root mean square relative deviation smaller than 28% with respect to experimental values. The automation, robustness, accuracy and precision of QHA-APL enable the computation of large material data sets, the implementation of repositories containing thermal properties, and finally can serve the community for data mining and machine learning studies.

cond-mat.mtrl-sci↗

arXiv2015

First principles thermodynamical modeling of the binodal and spinodal curves in lead chalcogenides

High-throughput ab-initio calculations, cluster expansion techniques and thermodynamic modeling have been synergistically combined to characterize the binodal and the spinodal decompositions features in the pseudo-binary lead chalcogenides PbSe-PbTe, PbS-PbTe, and PbS-PbSe. While our results agree with the available experimental data, our consolute temperatures substantially improve with respect to previous computational modeling. The computed phase diagrams corroborate that the formation of spinodal nanostructures causes low thermal conductivities in these alloys. The presented approach, making a rational use of online quantum repositories, can be extended to study thermodynamical and kinetic properties of materials of technological interest.

cond-mat.mtrl-sci↗

arXiv2015

The AFLOW Standard for High-Throughput Materials Science Calculations

The Automatic-Flow ( AFLOW ) standard for the high-throughput construction of materials science electronic structure databases is described. Electronic structure calculations of solid state materials depend on a large number of parameters which must be understood by researchers, and must be reported by originators to ensure reproducibility and enable collaborative database expansion. We therefore describe standard parameter values for k-point grid density, basis set plane wave kinetic energy cut-off, exchange-correlation functionals, pseudopotentials, DFT+U parameters, and convergence criteria used in AFLOW calculations.

cond-mat.mtrl-sci↗

arXiv2014

High-Throughput Computational Screening of thermal conductivity, Debye temperature and Grüneisen parameter using a quasi-harmonic Debye Model

The quasi-harmonic Debye approximation has been implemented within the AFLOW and Materials Project frameworks for high-throughput computational science (Automatic Gibbs Library, AGL), in order to calculate thermal properties such as the Debye temperature and the thermal conductivity of materials. We demonstrate that the AGL method, which is significantly cheaper computationally compared to the fully ab initio approach, can reliably predict the ordinal ranking of the thermal conductivity for several different classes of semiconductor materials. We also find that for the set of 182 materials investigated in this work the Debye temperature, calculated with the AGL, is often a better predictor of the ordinal ranking of the experimental thermal conductivities than the calculated thermal conductivity. The Debye temperature is thus a potential descriptor for high-throughput screening of the thermal properties of materials.

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