activity
20072026
most citedBoltzTraP2, a program for interpolating band structures and calculating semi-classical transport coefficients

1.7k citations · 3.7k across the 65 of their papers we have counts for

collaborators
Showing 2017Show all

13 papers · 1 filter

cond-mat.mtrl-sci2017★ 41 cited

Phonon transport unveils the prevalent point defects in GaN

Ankita Katre, Jesús Carrete, Tao Wang +2

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…

cond-mat.mtrl-sci2017★ 1.7k cited

BoltzTraP2, a program for interpolating band structures and calculating semi-classical transport coefficients

Georg K. H. Madsen, Jesús Carrete, Matthieu J. Verstraete

BoltzTraP2 is a software package for calculating a smoothed Fourier expression of periodic functions and the Onsager transport coefficients for extended systems using the linearize…

cond-mat.mtrl-sci2017★ 54 cited

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

Marco Arrigoni, Jesús Carrete, Natalio Mingo +1

The standard theoretical understanding of the lattice thermal conductivity, , of semiconductor alloys assumes that mass disorder is the most important source of phonon sc…

cond-mat.mtrl-sci2017

The AFLOW Fleet for Materials Discovery

Cormac Toher, Corey Oses, David Hicks +48

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 d…

cond-mat.mtrl-sci2017

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

Eric Gossett, Cormac Toher, Corey Oses +8

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 p…

cond-mat.mtrl-sci2017

Predictive design and experimental realization of InAs/GaAs superlattices with tailored thermal conductivity

J. Carrete, B. Vermeersch, L. Thumfart +7

We demonstrate an ab-initio predictive approach to computing the thermal conductivity () of InAs/GaAs superlattices (SLs) of varying period, thickness, and composition. Our new…

cond-mat.mtrl-sci2017★ 14 cited

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

Annie Weathers, Jesus Carrete, John P. Degrave +6

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…

cond-mat.mtrl-sci2017

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

Fleur Legrain, Jesús Carrete, Ambroise van Roekeghem +2

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 o…

cond-mat.mtrl-sci2017★ 1 cited

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

Nakib Haider Protik, Ankita Katre, Lucas Lindsay +3

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…

physics.comp-ph2017★ 307 cited

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

Jesús Carrete, Bjorn Vermeersch, Ankita Katre +4

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…

cond-mat.mtrl-sci2017★ 98 cited

Exceptionally strong phonon scattering by B substitution in cubic SiC

Ankita Katre, Jesús Carrete, Bonny Dongre +2

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 measu…

cond-mat.mtrl-sci2017

Structural Complexity and Phonon Physics in 2D Arsenenes

Jesús Carrete, Luis J. Gallego, Natalio Mingo

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 t…

cond-mat.mtrl-sci2017★ 1 cited

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

Fleur Legrain, Jesús Carrete, Ambroise van Roekeghem +2

Computing vibrational free energies () and entropies () has posed a long standing challenge to the high-throughput ab initio investigation of finite temperature p…