Stefano Curtarolo - MIT Massacchusetts Institute of Technology Cambridge MA USA

Stefano Curtarolo
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Name
Stefano Curtarolo
Affiliation
MIT Massacchusetts Institute of Technology Cambridge MA USA
City
Cambridge
Country
United States

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Pub Categories

 
Physics - Materials Science (46)
 
Physics - Superconductivity (3)
 
Physics - Mesoscopic Systems and Quantum Hall Effect (2)
 
Physics - Strongly Correlated Electrons (2)
 
Physics - Computational Physics (2)
 
Physics - Other (1)
 
Physics - Soft Condensed Matter (1)
 
Physics - Data Analysis; Statistics and Probability (1)
 
Mathematics - Combinatorics (1)
 
Computer Science - Digital Libraries (1)
 
Mathematics - Group Theory (1)

Publications Authored By Stefano Curtarolo

We discuss the application of the Agapito Curtarolo and Buongiorno Nardelli (ACBN0) pseudo-hybrid Hubbard density functional to several transition metal oxides. ACBN0 is a fast, accurate and parameter-free alternative to traditional DFT+$U$ and hybrid exact exchange methods. In ACBN0, the Hubbard energy of DFT+$U$ is calculated via the direct evaluation of the local Coulomb and exchange integrals in which the screening of the bare Coulomb potential is accounted for by a renormalization of the density matrix. Read More

The fundamental principles underlying the arrangement of the elements into solid compounds with an enormous variety of crystal structures are still largely unknown. This study presents a general overview of the structure types appearing in an important subset of the solid compounds, i.e. Read More

Computing vibrational free energies ($F_{vib}$) and entropies ($S_{vib}$) has posed a long standing challenge to the high-throughput ab initio investigation of finite temperature properties of solids. Here we use machine-learning techniques to efficiently predict $F_{vib}$ and $S_{vib}$ of crystalline compounds in the Inorganic Crystal Structure Database. By employing descriptors based simply on the chemical formula and using a training set of only 300 compounds, mean absolute errors of less than 0. Read More

Automated computational materials science frameworks rapidly generate large quantities of materials data useful for accelerated materials design. We have extended the data oriented AFLOW-repository API (Application-Program-Interface, as described in Comput. Mater. Read More

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. Read More

One of the most accurate approaches for calculating lattice thermal conductivity, $\kappa_l$, 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. Read More

The evaluation of phase stabilities of unstable elemental phases is a long-standing problem in the computational assessment of phase diagrams. Here we tackle this problem by explicitly calculating phase diagrams of intermetallic systems where its effect should be most conspicuous, binary systems of titanium with bcc transition metals (Mo, Nb, Ta and V). Two types of phase diagrams are constructed: one based on the lattice stabilities extracted from empirical data, and the other using the lattice stabilities computed from first principles. Read More

The calculations of electronic transport coefficients and optical properties require a very dense interpolation of the electronic band structure in reciprocal space that is computationally expensive and may have issues with band crossing and degeneracies. Capitalizing on a recently developed pseudo-atomic orbital projection technique, we exploit the exact tight-binding representation of the first principles electronic structure for the purposes of (1) providing an efficient strategy to explore the full band structure $E_n({\bf k})$, (2) computing the momentum operator differentiating directly the Hamiltonian, and (3) calculating the imaginary part of the dielectric function. This enables us to determine the Boltzmann transport coefficients and the optical properties within the independent particle approximation. Read More

Historically, materials discovery has been driven by a laborious trial-and-error process. The growth of materials databases and emerging informatics approaches finally offer the opportunity to transform this practice into data- and knowledge-driven rational design. By using data from the AFLOW repository for high-throughput ab-initio calculations, we have generated Quantitative Materials Structure-Property Relationship (QMSPR) models to predict eight critical electronic and thermomechanical materials properties, such as the metal/insulator classification, band gap energy, bulk and shear moduli, Debye temperature, and heat capacity. Read More

An easily available resource of common crystal structures is essential for researchers, teachers, and students. For many years this was provided by the U.S. Read More

Using finite-temperature phonon calculations and machine-learning methods, we calculate the mechanical stability of about 400 semiconducting oxides and fluorides with cubic perovskite structures at 0 K, 300 K and 1000 K. We find 92 mechanically stable compounds at high temperatures -- including 36 not mentioned in the literature so far -- for which we calculate the thermal conductivity. We demonstrate that the thermal conductivity is generally smaller in fluorides than in oxides, largely due to a lower ionic charge, and describe simple structural descriptors that are correlated with its magnitude. Read More

Metallic glasses have attracted considerable interest in recent years due to their unique combination of superb properties and processability. Predicting bulk metallic glass formers from known parameters remains a challenge and the search for new systems is still performed by trial and error. It has been speculated that some sort of "confusion" during crystallization of the crystalline phases competing with glass formation could play a key role. Read More

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, Gr\"uneisen 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. Read More

In 2006, a novel cobalt-based superalloy was discovered [1] with mechanical properties better than some conventional nickel-based superalloys. As with conventional superalloys, its high performance arises from the precipitate-hardening effect of a coherent L1$_2$ phase, which is in two-phase equilibrium with the fcc matrix. Inspired by this unexpected discovery of an L1$_2$ ternary phase, we performed a first-principles search through 2224 ternary metallic systems for analogous precipitate-hardening phases of the form $X_{3}$[$A_{0. Read More

Magneli phase Ti5O9 ceramics with 200-nm grain-size were fabricated by hot-pressing nanopowders of titanium and anatase TiO2 at 1223 K. The thermoelectric properties of these ceramics were investigated from room temperature to 1076 K. We show that the experimental variation of the electrical conductivity with temperature follows a small-polaron model and that the Seebeck coefficient can be explained by a temperature-dependent Heikes-Chaikin-Beni model. Read More

Despite two decades of studies, the formation of metallic glasses, very promising systems for industrial applications, still remains mostly unexplained. This lack of knowledge hinders the search for new systems, still performed with combinatorial trial and error. In the past, it was speculated that some sort of "confusion" during crystallization could play a key role during their formation. Read More

We present a scheme to controllably improve the accuracy of tight-binding Hamiltonian matrices derived by projecting the solutions of plane-wave ab initio calculations on atomic orbital basis sets. By systematically increasing the completeness of the basis set of atomic orbitals, we are able to optimize the quality of the band structure interpolation over wide energy ranges including unoccupied states. This methodology is applied to the case of interlayer and image states, which appear several eV above the Fermi level in materials with large interstitial regions or surfaces such as graphite and graphene. Read More

Predicting material properties of disordered systems remains a long-standing and formidable challenge in rational materials design. To address this issue, we introduce an automated software framework capable of modeling partial occupation within disordered materials using a high-throughput (HT) first principles approach. At the heart of the approach is the construction of supercells containing a virtually equivalent stoichiometry to the disordered material. Read More

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. Read More

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. Read More

We study the physical properties of Zn$X$ ($X$=O, S, Se, Te) and Cd$X$ ($X$=O, S, Se, Te) in the zinc-blende, rock-salt, and wurtzite structures using the recently developed fully $ab$ $initio$ pseudo-hybrid Hubbard density functional ACBN0. We find that both the electronic and vibrational properties of these wide-band gap semiconductors are systematically improved over the PBE values and reproduce closely the experimental measurements. Similar accuracy is found for the structural parameters, especially the bulk modulus. Read More

Although the P\'olya enumeration theorem has been used extensively for decades, an optimized, purely numerical algorithm for calculating its coefficients is not readily available. We present such an algorithm for finding the number of unique colorings of a finite set under the action of a finite group. Read More

As the proliferation of high-throughput approaches in materials science is increasing the wealth of data in the field, the gap between accumulated-information and derived-knowledge widens. We address the issue of scientific discovery in materials databases by introducing novel analytical approaches based on structural and electronic materials fingerprints. The framework is employed to (i) query large databases of materials using similarity concepts, (ii) map the connectivity of the materials space (i. Read More

Nanostructuring has spurred a revival in the field of direct thermoelectric energy conversion. Nanograined materials can now be synthesized with higher figures of merit (ZT) than the bulk counterparts. This leads to increased conversion efficiencies. Read More

Topological insulators are a class of materials with insulating bulk but protected conducting surfaces due to the combination of spin-orbit interactions and time-reversal symmetry. The surface states are topologically non-trivial and robust against non-magnetic backscattering, leading to interesting physics and potential quantum computing applications1, 2. Recently there has been a fast growing interest in samarium hexboride (SmB6), a Kondo insulator predicted to be the first example of a correlated topological insulator3, 4. Read More

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. Read More

In this theoretical study, we investigate the origins of the very low thermal conductivity of tin selenide (SnSe) using ab-initio calculations. We obtained high-temperature lattice thermal conductivity values that are close to those of amorphous compounds. We also found a strong anisotropy between the three crystallographic axes: one of the in-plane directions conducts heat much more easily than the other. Read More

The accurate prediction of the electronic properties of materials at a low computational expense is a necessary conditions for the development of effective high-throughput quantum-mechanics (HTQM) frameworks for accelerated materials discovery. HTQM infrastructures rely on the predictive capability of Density Functional Theory (DFT), the method of choice for the first principles study of materials properties. However, DFT suffers of approximations that result in a somewhat inaccurate description of the electronic band structure of semiconductors and insulators. Read More

The continued advancement of science depends on shared and reproducible data. In the field of computational materials science and rational materials design this entails the construction of large open databases of materials properties. To this end, an Application Program Interface (API) following REST principles is introduced for the AFLOWLIB. Read More

Using density functional theory calculations, many researchers have predicted that various tungsten-nitride compounds WN$_x$ ($x$ > 1) will be "ultra-compressible" or "superhard", $i.e.$ as hard as or harder than diamond. Read More

The lattice thermal conductivity ({\kappa}{\omega}) is a key property for many potential applications of compounds. Discovery of materials with very low or high {\kappa}{\omega} remains an experimental challenge due to high costs and time-consuming synthesis procedures. High-throughput computational pre-screening is a valuable approach for significantly reducing the set of candidate compounds. Read More

We present the structural, electronic and superconducting properties of Li2B2 under pressure within the framework of the density functional theory. The structural parameters, electronic band structure, phonon frequency of the E2g phonon mode and superconducting critical temperature Tc were calculated for pressures up to 20 GPa. We predicted that the superconducting critical temperature of Li2B2 is about 11 K and this decreases as pressure increases. Read More

We present a straightforward, noniterative projection scheme that can represent the electronic ground state of a periodic system on a finite atomic-orbital-like basis, up to a predictable number of electronic states and with controllable accuracy. By co-filtering the projections of plane-wave Bloch states with high-kinetic-energy components, the richness of the finite space and thus the number of exactly-reproduced bands can be selectively increased at a negligible computational cost, an essential requirement for the design of efficient algorithms for electronic structure simulations of realistic material systems and massive high-throughput investigations. Read More

Recent advances in computational materials science present novel opportunities for structure discovery and optimization, including uncovering of unsuspected compounds and metastable structures, electronic structure, surface, and nano-particle properties. The practical realization of these opportunities requires systematic generation and classification of the relevant computational data by high-throughput methods. In this paper we present Aflow (Automatic Flow), a software framework for high-throughput calculation of crystal structure properties of alloys, intermetallics and inorganic compounds. Read More

Technetium, element 43, is the only radioactive transition metal. It occurs naturally on earth in only trace amounts. Experimental investigation of its possible compounds is thus inherently difficult and limited. Read More

We report a comprehensive study of the binary systems of the platinum group metals with the transition metals, using high-throughput first-principles calculations. These computations predict stability of new compounds in 38 binary systems where no compounds have been reported in the literature experimentally, and a few dozen of as yet unreported compounds in additional systems. Our calculations also identify stable structures at compound compositions that have been previously reported without detailed structural data and indicate that some experimentally reported compounds may actually be unstable at low temperatures. Read More

Both IrV and RhV crystallize in the alpha-IrV structure, with a transition to the higher symmetry L1_0 structure at high temperature, or with the addition of excess Ir or Rh. Here we present evidence that this transition is driven by the lowering of the electronic density of states at the Fermi level of the alpha-IrV structure. The transition has long been thought to be second order, with a simple doubling of the L1_0 unit cell due to an unstable phonon at the R point (0 1/2 1/2). Read More

The article is devoted to the discussion of the high-throughput approach to band structures calculations. We present scientific and computational challenges as well as solutions relying on the developed framework (Automatic Flow, AFLOW/ACONVASP). The key factors of the method are the standardization and the robustness of the procedures. Read More

The ability to predict the existence and crystal type of ordered structures of materials from their components is a major challenge of current materials research. Empirical methods use experimental data to construct structure maps and make predictions based on clustering of simple physical parameters. Their usefulness depends on the availability of reliable data over the entire parameter space. Read More

Despite the increasing importance of hafnium in numerous technological applications, experimental and computational data on its binary alloys is sparse. In particular, data is scant on those binary systems believed to be phase separating. We performed a comprehensive study of 44 hafnium binary systems with alkali metals, alkaline earths, transition metals and metals, using high-throughput first principles calculations. Read More

The origin of nonproportionality in scintillator materials has been a long standing problem for more than four decades. In this manuscript, we show that, with the help of first principle modeling, the parameterization of the nonproportionality for several systems, with respect to their band structure curvature suggests a correlation between carrier effective mass and energy response. We attribute this correlation to the case where free electrons and holes are the major energy carriers. Read More

FePt nanoparticles are known to exhibit reduced L1$_0$ order with decreasing particle size. The reduction in order reduces the magnetic anisotropy and the thermal stability of the direction of magnetization of the particle. The phenomenon is addressed by investigating the thermodynamic driving forces for surface segregation using a local (inhomogeneous) cluster expansion fitted to ab initio data which accurately represents interatomic interactions in both the bulk and surface regions. Read More

By devising a novel framework, we present a comprehensive theoretical study of solubilities of alkali (Li, Na, K, Rb, Cs) and alkaline earth (Be, Ca, Sr, Ba) metals in the he boron-rich Mg-B system. The study is based on first-principle calculations of solutes formation energies in MgB$_2$, MgB$_4$, MgB$_7$ alloys and subsequent statistical-thermodynamical evaluation of solubilities. The advantage of the approach consists in considering all the known phase boundaries in the ternary phase diagram. Read More

We present an approach to calculate the atomic bulk solubility in binary alloys based on the statistical-thermodynamic theory of dilute lattice gas. The model considers all the appropriate ground states of the alloy and results in a simple Arrhenius-type temperature dependence determined by a {\it "low-solubility formation enthalpy"}. This quantity, directly obtainable from first-principle calculations, is defined as the composition derivative of the compound formation enthalpy with respect to nearby ground states. Read More

Lubricants can affect quasicrystalline coatings surfaces by modifying commensurability of the interfaces. We report results of the first computer simulation studies of physically adsorbed hydrocarbons on a quasicrystalline surface: methane, propane, and benzene on decagonal Al-Ni-Co. The grand canonical Monte Carlo method is employed, using novel Embedded Atom Method potentials generated from it ab initio calculations, and standard hydrocarbon interactions. Read More

Density functional theory calculations have been used to identify stable layered Li-$M$-B crystal structure phases derived from a recently proposed binary metal-sandwich (MS) lithium monoboride superconductor. We show that the MS lithium monoboride gains in stability when alloyed with electron-rich metal diborides; the resulting ordered Li$_{2(1-x)}M_x$B$_2$ ternary phases may form under normal synthesis conditions in a wide concentration range of $x$ for a number of group-III-V metals $M$. In an effort to pre-select compounds with the strongest electron-phonon coupling we examine the softening of the in-plane boron phonon mode at $\Gamma$ in a large class of metal borides. Read More

We explore the role of Mo in Fe:Mo nanocatalyst thermodynamics for low-temperature chemical vapor deposition growth of single walled carbon nanotubes (SWCNTs). By using the size-pressure approximation and ab initio modeling, we prove that for both Fe-rich (~80% Fe or more) and Mo-rich (~50% Mo or more) Fe:Mo clusters, the presence of carbon in the cluster causes nucleation of Mo2C. This enhances the activity of the particle since it releases Fe, which is initially bound in a stable Fe:Mo phase, so that it can catalyze SWCNT growth. Read More

Using electronic structure calculation we study the superconducting properties of the theoretically-devised superconductor MS1-LiB (LiB). We calculate the electron-phonon coupling ($\lambda=0.62$) and the phonon frequency logarithmic average ($<\omega >_{log}=54. Read More

The thermal behavior of free and alumina-supported iron-carbon nanoparticles is investigated via molecular dynamics simulations, in which the effect of the substrate is treated with a simple Morse potential fitted to ab initio data. We observe that the presence of the substrate raises the melting temperature of medium and large $Fe_{1-x}C_x$ nanoparticles ($x$ = 0-0.16, $N$ = 80-1000, non- magic numbers) by 40-60 K; it also plays an important role in defining the ground state of smaller Fe nanoparticles ($N$ = 50-80). Read More

The grand canonical Monte Carlo method is employed to study the adsorption of Xe on a quasicrystalline Al-Ni-Co surface. The calculation uses a semiempirical gas-surface interaction, based on conventional combining rules and the usual Lennard-Jones Xe-Xe interaction. The resulting adsorption isotherms and calculated structures are consistent with the results of LEED experimental data. Read More