Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)

Saal, James E.; Kirklin, Scott; Aykol, Muratahan; Meredig, Bryce; Wolverton, Christopher

doi:10.1007/s11837-013-0755-4

Cited by 1,913 publications

(1,482 citation statements)

References 92 publications

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“…Because of the well-known tendency of DFT calculations to underestimate the band-gap, the value with U=0 underestimates the band-gap with respect to the experimental. This value is similar to other previous results in the literature [23,24]. However, including an effective Hubbard U=3 eV in the Hamiltonian, the bangap is closer to the experimental.…”

Section: Structure and Electronic Propertiessupporting

confidence: 91%

“…These structures ( Figure 1) are built up from infinite weakly linked ribbons (SbX 2 ) n of trigonal SbX 3 with Sb-X bonds of 2.605, 2.795 Å (X =Se), and 2.829, 2.953, 2.955 Å (X =Te) [21]. The SbSeI experimental band-gap reported in the literature is 1.66 eV [22] and the theoretical band-gaps are between 1.29-1.40 eV (1.29 eV [9], 1.37 eV [23], 1.40 eV [24]). For SbTeI the theoretical band-gaps are 0.86 eV [24] and 2.07 eV [25].…”

Section: Structure and Electronic Propertiesmentioning

confidence: 99%

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Optical properties of Sb(Se,Te)I and photovoltaic applications

Tablero

2016

Journal of Alloys and Compounds

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SbXI (X=Se, Te) are ferroelectric semiconductors that allow a variety of applications including optoelectronic and photovoltaic applications. An analysis of the optical properties is carried out starting from first-principles density-functional theory with orbital-dependent one-electron potentials. To go into the contributions to the optical properties more deeply, the absorption coefficients have been split into inter-and intraspecies contributions and into atomic angular momentum contributions. The optical results are used to evaluate the efficiencies when this material is used to absorb sunlight at several sunlight concentrations and the usual radiative and the ferroelectric photovoltaic mechanisms. The results indicate their applicability in photovoltaic devices as absorbent of the solar spectrum with high conversion efficiency.

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Section: Structure and Electronic Propertiessupporting

confidence: 91%

Section: Structure and Electronic Propertiesmentioning

confidence: 99%

Optical properties of Sb(Se,Te)I and photovoltaic applications

Tablero

2016

Journal of Alloys and Compounds

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“…The assumption of an absolute error bar is also consistent with observed distributions of cohesive energies (see Figure 1(b)) and formation energies. 22,23 . When assessing a large and diverse set of materials, the errors may then be considered to assume a Gaussian distribution, and only the elimination of systematic deviations makes it possible to treat all materials on equal footing.…”

Section: Ansatzmentioning

confidence: 99%

Is the error on first-principles volume predictions absolute or relative?

Lejaeghere

Vanduyfhuys

Verstraelen

et al. 2016

Computational Materials Science

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Many benchmarks of density-functional theory with respect to experiment suggest the error on predicted equilibrium volumes to scale with the volume. Relative volume errors are therefore often used as a decisive argument to select one exchange-correlation functional over another. We show that the error on the volume (after correcting for systematic deviations) is only approximately relative. A simple analytic model, validated by rigorous Monte Carlo simulations, reveals that a more accurate error estimate can be derived from the inverse of the bulk modulus. This insight is not only instrumental for the selection or design of suitable functionals. It also calls for a new attitude towards computational errors: to report computational errors on electronic-structure calculations, identify systematic deviations and distinguish between relative and absolute effects.

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“…On one hand, databases of materials have been created containing structural information of both experimental and theoretical compounds from highthroughput calculations, which are the basis for data-mining techniques in materials discovery projects. [1][2][3][4][5][6][7] On the other hand, ab initio structure predictions [8][9][10][11][12][13][14][15] can produce a huge number of new structures that have either not yet been found experimentally or are metastable. [16][17][18][19][20][21] In both cases, it is essential to quantify similarities and dissimilarities between structures in the data sets, requiring a configurational distance that satisfies the properties of a metric.…”

Section: Introductionmentioning

confidence: 99%

A fingerprint based metric for measuring similarities of crystalline structures

Zhu

Amsler

Fuhrer

et al. 2016

The Journal of Chemical Physics

130

124

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Measuring similarities/dissimilarities between atomic structures is important for the exploration of potential energy landscapes. However, the cell vectors together with the coordinates of the atoms, which are generally used to describe periodic systems, are quantities not directly suitable as fingerprints to distinguish structures. Based on a characterization of the local environment of all atoms in a cell, we introduce crystal fingerprints that can be calculated easily and define configurational distances between crystalline structures that satisfy the mathematical properties of a metric. This distance between two configurations is a measure of their similarity/dissimilarity and it allows in particular to distinguish structures. The new method can be a useful tool within various energy landscape exploration schemes, such as minima hopping, random search, swarm intelligence algorithms, and high-throughput screenings. C 2016 AIP Publishing LLC. [http://dx

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Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)

Cited by 1,913 publications

References 92 publications

Optical properties of Sb(Se,Te)I and photovoltaic applications

Optical properties of Sb(Se,Te)I and photovoltaic applications

Is the error on first-principles volume predictions absolute or relative?

A fingerprint based metric for measuring similarities of crystalline structures

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