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Correlation of K-points and cut-off with a, c) crystal system and b, d) number of unique elements in a simulation cell. The error bars indicate the standard deviation.
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In this work, we developed an automatic convergence procedure for k-points and plane wave cut-off in density functional (DFT) calculations and applied it to more than 30,000 materials. The computational framework for automatic convergence can take a user-defined input as a convergence criterion. For k-points, we converged energy per cell (EPC) to 0...
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... the Pearson coefficient relating k-point length to average slope at the band crossings is among the highest PC we found, and higher than any other PC related to k-points (PC=0.617), implying a relatively strong correlation. Now, we investigate the effect of crystal systems and the number of atoms per unit cell on the cut- off and k-points. In Fig. 4, we plot the average number of converged k-points and cut-off for each crystal system and the number of species in each simulation cell. As shown in Fig. 4a and 4c, cubic and hexagonal materials require higher k-points, but lower cut-off than any other system, while triclinic materials require fewer k-points but higher cutoff. ...
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... to k-points (PC=0.617), implying a relatively strong correlation. Now, we investigate the effect of crystal systems and the number of atoms per unit cell on the cut- off and k-points. In Fig. 4, we plot the average number of converged k-points and cut-off for each crystal system and the number of species in each simulation cell. As shown in Fig. 4a and 4c, cubic and hexagonal materials require higher k-points, but lower cut-off than any other system, while triclinic materials require fewer k-points but higher cutoff. Interestingly, we observe that as the number of species in a system increases, the k-points decreases while the cut-off value increases, as shown in Fig. 4 b, d. To ...
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... cell. As shown in Fig. 4a and 4c, cubic and hexagonal materials require higher k-points, but lower cut-off than any other system, while triclinic materials require fewer k-points but higher cutoff. Interestingly, we observe that as the number of species in a system increases, the k-points decreases while the cut-off value increases, as shown in Fig. 4 b, d. To investigate the effect of chemical species, for each element of the periodic table we averaged the converged k-point length of all the materials in the database containing that particular ...
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... the Pearson coefficient relating k-point length to average slope at the band crossings is among the highest PC we found, and higher than any other PC related to k-points (PC=0.617), implying a relatively strong correlation. Now, we investigate the effect of crystal systems and the number of atoms per unit cell on the cut- off and k-points. In Fig. 4, we plot the average number of converged k-points and cut-off for each crystal system and the number of species in each simulation cell. As shown in Fig. 4a and 4c, cubic and hexagonal materials require higher k-points, but lower cut-off than any other system, while triclinic materials require fewer k-points but higher cutoff. ...
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... to k-points (PC=0.617), implying a relatively strong correlation. Now, we investigate the effect of crystal systems and the number of atoms per unit cell on the cut- off and k-points. In Fig. 4, we plot the average number of converged k-points and cut-off for each crystal system and the number of species in each simulation cell. As shown in Fig. 4a and 4c, cubic and hexagonal materials require higher k-points, but lower cut-off than any other system, while triclinic materials require fewer k-points but higher cutoff. Interestingly, we observe that as the number of species in a system increases, the k-points decreases while the cut-off value increases, as shown in Fig. 4 b, d. To ...
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... cell. As shown in Fig. 4a and 4c, cubic and hexagonal materials require higher k-points, but lower cut-off than any other system, while triclinic materials require fewer k-points but higher cutoff. Interestingly, we observe that as the number of species in a system increases, the k-points decreases while the cut-off value increases, as shown in Fig. 4 b, d. To investigate the effect of chemical species, for each element of the periodic table we averaged the converged k-point length of all the materials in the database containing that particular ...
Citations
... For Lu, a Topsakal-Wentzcovitch [60] pseudopotential was used. Due to the highthroughput nature of this study, which is primarily focused on screening potential high-pressure hydride candidates, we used preconverged k-points from the JARVIS database [61], a 2 × 2 × 2 q-point grid and a kinetic energy cutoff of 610 eV (45 Ry). It was demonstrated in [36] and [37] that these lower q-point grids can still be effective for material screening purposes. ...
... It was demonstrated in [36] and [37] that these lower q-point grids can still be effective for material screening purposes. For structures not already in the JARVIS dataset (materials added from the literature), we used the automated k-point convergence scheme in JARVIS [61]. ...
The observation of superconductivity in hydride-based materials under ultrahigh pressures (for example, H3S and LaH10) has fueled the interest in a more data-driven approach to discovering new high-pressure hydride superconductors. In this work, we performed density functional theory (DFT) calculations to predict the critical temperature ( Tc ) of over 900 hydride materials under a pressure range of (0–500) GPa, where we found 122 dynamically stable structures with a Tc above MgB2 (39 K). To accelerate screening, we trained a graph neural network (GNN) model to predict Tc and demonstrated that a universal machine learned force-field can be used to relax hydride structures under arbitrary pressures, with significantly reduced cost. By combining DFT and GNNs, we can establish a more complete map of hydrides under pressure.
... While there are more than 400 approximate exchange-correlation functionals proposed in DFT literature 103 110 , in the leaderboard. We use converged k-points and cut-offs as available in the JARVIS-DFT database 111 . We have used the Vienna Ab initio Simulation Package (VASP) 81,82 , ABINIT [112][113][114] , GPAW 79 and Quantum Espresso (QE) 115 as DFT software packages, but other packages can be easily added as well. ...
Lack of rigorous reproducibility and validation are significant hurdles for scientific development across many fields. Materials science, in particular, encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC), and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboard/
... Charge convergence was achieved after a total number of 40 iterations, resulting in an accuracy of 10 −5 Ry. A huge mesh of 1900-K points is selected [57]. We utilized the semi classical Boltzmann transport theory to compute the thermoelectric characteristics in detail [58]. ...
Halide perovskites are significant due to their versatility and high performance in optoelectronics and green technologies. This paper thoroughly investigates the structural, elastic, optoelectronic and transport characteristics of RbInX3 (X = I, Br, Cl) perovskites using density functional theory (DFT) embedded in Wein2K. Modified Becke Johnson as an exchange correlation potential is used to evaluate the physical characteristics. Structural stability is achieved with the tolerance factor and octahedral tilting along with the optimization curves. A metallic character is detected in RbInI3. However, the replacement of I with Br and Cl atoms results in an indirect band gap of 0.9 eV and 1.95 eV at (L-X) symmetry points, respectively. The elastic constants are utilized to determine the elastic parameters that ensure the structural stability of perovskites. Cauchy pressure and Poisson’s ratio indicate the ductile nature of all studied phases. The thermal behavior is evaluated through the computation of Debye temperature. Furthermore, an insight into the material’s interaction with electromagnetic radiation is accessed through the optical parameters. A high absorption at 1.49 eV for RbInI3, 1.65 for RbInBr3 and 2.57 for RbInCl3 show their potential for light emitting devices. The semi-classical Boltzmann theory is employed to compute thermoelectric properties, which show RbInI3, RbInBr3 and RbInCl3 possess high electrical conductivities of 3.068 ×1019 S m–1, 1.88 ×1019 S m–1 and 1.76 ×1019 S m–1 at 1200 K, respectively. The ZT value for RbInBr3 is 0.74 and RbInCl3 is 0.73, while RbInI3 exhibit the lowest ZT of 0.04 at 1200 K. The examined characteristics indicate that RbInBr3 and RbInCl3 possess promising potential for renewable energy applications.
... Before the calculation of the lattice constant, we ensured the convergence parameters until the error on the calculated total energy reached the criteria of 0.001 ev/atom [34]. We used the VCA method to study the lattice constant of Ti 42 Hf 21 Nb 21 V 16 RHEA, which was calculated to be 3.318 Å, with an error of less than 1% compared to the experimental result of as-cast sample (given in Section 3.2). ...
Refractory high-entropy alloys (RHEA), particularly those with a body-centered cubic lattice structure, are garnering increased interest due to their potential industrial applications. However, their strength-ductility trade-off at room temperature presents a challenge that requires resolution. In this study, we fabricated a ductile Ti42Hf21Nb21V16 RHEA for additive manufacturing using a directed energy deposition (DED) technique, with a focused laser serving as the energy source. The additively manufactured RHEA demonstrated an exceptional strength-ductility synergy, boasting a gigapascal yield strength and a substantial tensile strain until failure (∼22.5%). Compared to its as-cast state, the tensile yield strength increased by 32%, and ductility improved slightly by 2%, suggesting a potential solution to the enduring strength-ductility trade-off dilemma. The enhanced yield strength can be attributed to solidification-enabled interstitial atoms resulting from the low-content nitrogen and oxygen atmosphere applied, while the high ductility is linked to the modified dislocation motion mechanism facilitated by the decomposition of the body-centered cubic matrix. This finding opens up possibilities for in-situ tailoring of microstructure and compositions to achieve superior mechanical performance in alloys through additive manufacturing processes.
... CdTe and ZnTe both crystallize in a zinc blend structure and belong to the cubic F43m space group (216). Prior to the formation of ZnTe:Cu, DFT calculations were performed on ZnTe to obtain band diagrams and cell specifications similar to the experimental values [18]. The single-unit cell ZnTe structure has been upgraded to a supercell structure due to the limitations in the variety of doping concentrations utilizing a single cell structure. ...
Cadmium telluride (CdTe) solar cells have attracted a lot of interest in recent years, attributed to their low cost and eco-friendly fabrication technique. However, the back contact is still the key issue for further improvement in device performance due to the work function difference between p-CdTe and metal contacts. In this study, the interatomic characteristics of zinc telluride (ZnTe) and Cu-doped ZnTe (ZnTe:Cu) as a back surface field (BSF) in CdTe structure is investigated using first-principles density functional theory (DFT) to overcome the Schottky barrier in CdTe solar cells. The incorporation of different doping levels of copper (Cu) in ZnTe on an atomic scale, where Zn 1−x Te:Cu x (x = 0, 2, 4, 6, 8, and 10) as the potential back surface field layers is investigated. The effect of doping concentration on electrical characteristics such as bandgap structure and density of states (DOS) were examined via ab initio with the Hubbard U (DFT + U) correction. The results showed an interesting gradual decrease in the bandgap energy of ZnTe from 2.24 eV to 2.10 eV, 1.98 eV, 1.92 eV, 1.88 eV, and 1.87 eV for the incremented value of Cu content of 3.13%, 6.25%, 9.38%, 12.50%, and 15.63%, respectively. Accordingly, it has been found that controlling of the effective copper doping, i.e., concentration, is crucial for developing efficient back contact junctions for high-efficiency CdTe thin-film solar cells.
... The geometries were optimized on the basis of the convergence of analytical gradients and nuclear displacements [21]. The diagonalization was performed using a grid of k points according to the Monkhorst-Pack method [22]. The shrinking factor was set to 8 (50 independent k points in the Brillouin zone). ...
This study offers important insights into the impact of incorporating cobalt on a range of characteristics of ZnO nanoparticles. Undoped ZnO and doped Zn1−xCoxO (x = 0.01 and 0.05) were effectively elaborated by the co-precipitation method. It establishes for the first time a full description of physical properties from experimental and theoretical points of view for Co-doped ZnO nanoparticles. The theoretical results studied by means of the Density Functional Theory are correlated with the experimental findings obtained using various techniques. Besides, the structural analysis revealed the formation of the hexagonal wurtzite structure of all the powdered samples with the appearance of the secondary phase ZnCo2O4 for the Zn0.95Co0.05O composition. An increasing trend of the average crystallite size from 26.49 to 53.93 nm was obtained under Co doping effect. Concerning the optical characterization, the band gap energy was found to decline with increasing Co doping concentration. Furthermore, the dielectric analysis was performed at different temperatures in the range frequency 40–10⁷ Hz. An enhancement of the dielectric constant was observed with the addition of Co into ZnO host matrix. Overall, this novel contribution improves the performances of such structures that make them potential candidates for dielectric applications.
... In the optimization process, the optimized NSW = 999 was selected, that is, the number of steps in the nucleus was 999, and the subsequent self-consistent motion in the nucleus remained immobile in the nucleus, that is, NSW = 0. The calculation of each system was carried out after the convergence test, in which the parameters of the truncated energy and the Brillouin zone position point (K point) were set in accordance with the different calculation systems, and the Monkhorst-Pack method was adopted for the selection of K points [25][26][27] . The plane wave truncation energy was first optimized for the value of the equal difference series 200, 250, 300, 350, 400, 450, 500, 550, and 600 eV because the structural optimization part and the energy calculation part have different requirements for accuracy. ...
With the rapid development of industry, heavy metal pollution has seriously damaged the health of soil, and heavy metals spread through the food chain, posing a threat to human health. The firm existence of heavy metals in soil under earthy conditions is a center trouble faced by soil dense metal pollution solidification and correction technology. However, the existing investigation results are mostly controlled to soil passivation experiments using various materials. Macroscopically, heavy metal passivation materials have been selected, but the intrinsic mechanisms of different compound functional groups in soil passivation have been ignored. With the common heavy metal ion Pb ²⁺ as an example, the stability of the combination of heavy metal ions and common ion groups in soil was analyzed in this study by using quantum chemical calculation as the theoretical guidance. The results show that SO 4 ²⁻ and PO 4 ³⁻ , as functional groups of passivating agents, are used to control lead pollution and have been verified to have good effects. When the pollution is particularly serious and not easy to passivation and precipitation, Fe ³⁺ can be considered to enhance the passivation effect.
... The electronic properties like band structure and density of states (DOS) [27] are important to characterize the energy levels in solids, especially semiconductors, which can be integral in comprehending the physical properties of solids. The plane-wave energy cut-off [28] was set to a 400.0 eV for energy and electronic property calculations, with the Brillouin zone integration [29] performed over an ultrafine 6 Â 2 Â 2 grids, implementing the Monkhorst-Pack Method. To reduce the number of base planes in the convergence calculations, an ultra-soft pseudopotential was employed to understand the interactions between the electrons and the ions. ...
Inorganic lead halide perovskites have appeared as favorable and novel materials for their effective use in photovoltaics. The synthesis route of such materials via the simple wet chemistry technique renders these inorganic halide perovskites the ideal property for light-harvesting materials. Despite these novel properties, the inherently unstable nature under increased heat and ambient moisture conditions is still a conjecture that needs to be addressed. This work shows the wet chemistry method as a synthesis route of the novel RbPbCl3 perovskite using four different solvents for photovoltaic applications. Interestingly, the synthesized perovskite was stable in only one solvent with a band gap of 2.6 eV, whereas the material degraded in the other three. The DFT calculations performed post-geometric optimization revealed well-defined electronic bandgap and optical properties, nearly imitating the experimental data of our synthesized perovskite. The copious properties such as electronic, optical, and formation energy revealed that the perovskite possesses huge charge screening ability, a low recombination rate of electron-hole pairs, board absorption spectrum, and high stability. Henceforth, establishes its suitability for photovoltaic devices. The close fit of the experimental results with our theoretical trend demonstrates the importance of developing a computational strategy to screen for new perovskite materials for photovoltaic cells.
... We used the converged k-point and cutoff from the JARVIS-DFT dataset based on total energy convergence. 40 We used an energy convergence of 10 −6 eV during the self-consistent cycle. Currently, we have 530 entries for the vacancies and the dataset is still growing. ...
The presence of point defects, such as vacancies, plays an important role in materials design. Here, we explore the extrapolative power of a graph neural network (GNN) to predict vacancy formation energies. We show that a model trained only on perfect materials can also be used to predict vacancy formation energies (Evac) of defect structures without the need for additional training data. Such GNN-based predictions are considerably faster than density functional theory (DFT) calculations and show potential as a quick pre-screening tool for defect systems. To test this strategy, we developed a DFT dataset of 530 Evac consisting of 3D elemental solids, alloys, oxides, semiconductors, and 2D monolayer materials. We analyzed and discussed the applicability of such direct and fast predictions. We applied the model to predict 192 494 Evac for 55 723 materials in the JARVIS-DFT database. Our work demonstrates how a GNN-model performs on unseen data.
... The electronic wave function was unfolded using plane waves, and a 450 eV truncation energy was chosen. Utilizing a 1 × 1 × 1 k-point mesh that is centered in each primitive lattice vector of the reciprocal space, integration in the Brillouin zone was carried out for geometric optimization using the Monkhorst-Pack method [42]. With the convergence scale and energy convergence quasi for each atomic minimum force set to −0.01 eV Å −1 and 4 × 10 −5 eV. ...
Even in their bulk forms, complex alloys like high-entropy alloys (HEAs) exhibit favorable activity and stability as electrocatalysts for the oxygen evolution reaction (OER). However, the underlying reasons are not yet fully understood. In a family of Mo-doped CrFeCoNi-based HEAs, we have identified three crucial factors that govern their performance: (i) Homogeneous solid solution phase of HEAs helps to maintain high-valence states of metals; (ii) Surface reconstruction results in a hybrid material comprising amorphous domains and percolated crystalline structures; (iii) Diversity of active intermediate species (M-O, M-OOH, and, notably, the abundance of superoxide μ-OO), which display stronger adsorption capacity on the reconstructed surface. These results are revealing due to their resemblance to findings in other families of electrocatalysts for OER, as well as their unique features specific to HEAs. In line with these factors, a CrFeCoNiMo0.2 bulk integrated electrode displays a low overpotential of 215 mV, rapid kinetics, and long-term stability of over 90 days. Bulk HEAs hold great potential for industrial applications.
