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Asta, Mark

Publications and source records attributed to Asta, Mark.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Dipolar cations confer defect tolerance in wide-bandgap metal halide perovskites

Efficient wide-bandgap perovskite solar cells (PSCs) enable high-efficiency tandem photovoltaics when combined with crystalline silicon and other low-bandgap absorbers. However, wide-bandgap PSCs today exhibit performance far inferior to that of sub-1.6-eV bandgap PSCs due to their tendency to form a high density of deep traps. Here, we show that healing the deep traps in wide-bandgap perovskites—in effect, increasing the defect tolerance via cation engineering—enables further performance improvements in PSCs. We achieve a stabilized power conversion efficiency of 20.7% for 1.65-eV bandgap PSCs by incorporating dipolar cations, with a high open-circuit voltage of 1.22 V and a fill factor exceeding 80%. We also obtain a stabilized efficiency of 19.1% for 1.74-eV bandgap PSCs with a high open-circuit voltage of 1.25 V. From density functional theory calculations, we find that the presence and reorientation of the dipolar cation in mixed cation–halide perovskites heals the defects that introduce deep trap states.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Matminer: An open source toolkit for materials data mining

As materials data sets grow in size and scope, the role of data mining and statistical learning methods to analyze these materials data sets and build predictive models is becoming more important. This manuscript introduces matminer, an open-source, Python-based software platform to facilitate data-driven methods of analyzing and predicting materials properties. Matminer provides modules for retrieving large data sets from external databases such as the Materials Project, Citrination, Materials Data Facility, and Materials Platform for Data Science. It also provides implementations for an extensive library of feature extraction routines developed by the materials community, with 47 featurization classes that can generate thousands of individual descriptors and combine them into mathematical functions. Finally, matminer provides a visualization module for producing interactive, shareable plots. These functions are designed in a way that integrates closely with machine learning and data analysis packages already developed and in use by the Python data science community. We explain the structure and logic of matminer, provide a description of its various modules, and showcase several examples of how matminer can be used to collect data, reproduce data mining studies reported in the literature, and test new methodologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Spatial correlation of elastic heterogeneity tunes the deformation behavior of metallic glasses

Metallic glasses (MGs) possess remarkably high strength but often display only minimal tensile ductility due to the formation of catastrophic shear bands. Purposely enhancing the inherent heterogeneity to promote distributed flow offers new possibilities in improving the ductility of monolithic MGs. Here, we report the effect of the spatial heterogeneity of elasticity, resulting from the inherently inhomogeneous amorphous structures, on the deformation behavior of MGs, specifically focusing on the ductility using multiscale modeling methods. A highly heterogeneous, Gaussian-type shear modulus distribution at the nanoscale is revealed by atomistic simulations in Cu 64 Zr 36 MGs, in which the soft population of the distribution exhibits a marked propensity to undergo the inelastic shear transformation. By employing a mesoscale shear transformation zone dynamics model, we find that the organization of such nanometer-scale shear transformation events into shear-band patterns is dependent on the spatial heterogeneity of the local shear moduli. A critical spatial correlation length of elastic heterogeneity is identified for the simulated MGs to achieve the best tensile ductility, which is associated with a transition of shear-band formation mechanisms, from stress-dictated nucleation and growth to structure-dictated strain percolation, as well as a saturation of elastically soft sites participating in the plastic flow. This discovery is important for the fundamental understanding of the role of spatial heterogeneity in influencing the deformation behavior of MGs. We believe that this can facilitate the design and development of new ductile monolithic MGs by a process of tuning the inherent heterogeneity to achieve enhanced ductility in these high-strength metallic alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Phase transformation pathways of ultrafast-laser-irradiated Ln 2 O 3 ( Ln = Er – Lu )

Ultrafast laser irradiation causes intense electronic excitations in materials, leading to transient high temperatures and pressures. Here, we show that ultrafast laser irradiation drives an irreversible cubic-to-monoclinic phase transformation in Ln 2 O 3 ( Ln = Er – Lu ) , and explore the mechanism by which the phase transformation occurs. A combination of grazing incidence x-ray diffraction and transmission electron microscopy are used to determine the magnitude and depth-dependence of the phase transformation, respectively. Although all compositions undergo the same transformation, their transformation mechanisms differ. The transformation is pressure-driven for Ln = Tm – Lu , consistent with the material's phase behavior under equilibrium conditions. However, the transformation is thermally driven for Ln = Er , revealing that the nonequilibrium conditions of ultrafast laser irradiation can lead to novel transformation pathways. Ab initio molecular-dynamics simulations are used to examine the atomic-scale effects of electronic excitation, showing the production of oxygen Frenkel pairs and the migration of interstitial oxygen to tetrahedrally coordinated constitutional vacancy sites, the first step in a defect-driven phase transformation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Capillary fluctuations of surface steps: An atomistic simulation study for the model Cu(111) system

Molecular dynamics (MD) simulations are employed to investigate the capillary fluctuations of steps on the surface of a model metal system. The fluctuation spectrum, characterized by the wave number ($k$) dependence of the mean squared capillary-wave amplitudes and associated relaxation times, is calculated for $\langle 110 \rangle$ and $\langle 112 \rangle$ steps on the { 111 } surface of elemental copper near the melting temperature of the classical potential model considered. Step stiffnesses are derived from the MD results, yielding values from the largest system sizes of ( 37 ± 1 ) meV / Å for the different line orientations, implying that the stiffness is isotropic within the statistical precision of the calculations. The fluctuation lifetimes are found to vary by approximately four orders of magnitude over the range of wave numbers investigated, displaying a $k$ dependence consistent with kinetics governed by step-edge mediated diffusion. The values for step stiffness derived from these simulations are compared to step free energies for the same system and temperature obtained in a recent MD-based thermodynamic-integration (TI) study [Freitas, Frolov, and Asta, Phys. Rev. B 95, 155444 (2017)]. Results from the capillary-fluctuation analysis and TI calculations yield statistically significant differences that are discussed within the framework of statistical-mechanical theories for configurational contributions to step free energies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Three-State Ferroelastic Switching and Large Electromechanical Responses in PbTiO 3 Thin Films

Leveraging competition between energetically degenerate states to achieve large field-driven responses is a hallmark of functional materials, but routes to such competition are limited. Here, a new route to such effects involving domain-structure competition is demonstrated, which arises from straininduced spontaneous partitioning of PbTiO 3 thin films into nearly energetically degenerate, hierarchical domain architectures of coexisting c/a and a 1 /a 2 domain structures. Using band-excitation piezoresponse force microscopy, this study manipulates and acoustically detects a facile interconversion of different ferroelastic variants via a two-step, three-state ferroelastic switching process (out-of-plane polarized c+ → in-plane polarized a → out-of-plane polarized c- state), which is concomitant with large nonvolatile electromechanical strains (≈1.25%) and tunability of the local piezoresponse and elastic modulus (>23%). It is further demonstrated that deterministic, nonvolatile writing/erasure of large-area patterns of this electromechanical response is possible, thus showing a new pathway to improved function and properties.

36 MATERIALS SCIENCE↗
DOE OSTI2017

On the question of fractal packing structure in metallic glasses

Significance Our work clearly demonstrates a lack of fractal structure in metallic glasses, considering the packing of all atoms or solute-centered clusters. This finding clarifies the long-standing debate over the packing structure of metallic glasses from the perspective of fractal models; it is thus of significance for the community of researchers working with amorphous solids. Moreover, our percolation analysis of metallic glasses, revealing their cluster structure and percolation threshold, provides an important and powerful theoretical framework to describe the properties of amorphous alloys, such as the glass transition and mechanical deformation.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Orientation-dependent properties of epitaxially strained perovskite oxide thin films: Insights from first-principles calculations

The structural properties, energetics, and polarizations of perovskite-based thin-film oxide systems are computed as a function of biaxial strain state and epitaxial orientation, employing an automated computational workflow based on density functional theory. In this work, a total of 14 compositions are considered, of the form ABO 3 , with A = Ba, K, Na, Pb, and Sr and B = Hf, Sn, Ti, Zr, Nb, Ta, and V site cations chosen to yield tolerance factors with values ranging between 0.95 and 1.1. Three biaxial strain states corresponding to epitaxial growth of (100)-, (110)-, and (111)-oriented films are considered, with misfit strains ranging between -4% to 4%. Results are presented for the series of perovskite-derived phases, and their corresponding symmetries, which are energetically favorable as a function of misfit strain, along with their corresponding equilibrium atomic positions, lattice parameters, and electric polarizations. The results demonstrate robust trends of in-plane polarization enhancement under tensile strain for all epitaxial orientations, and out-of-plane polarization enhancementwith compression for the (100)- and (110)-oriented films. Strains corresponding to the (111)-growth orientation lead to a wider variety of out-of-plane polarization behavior, with BaTiO 3 showing anomalous diminishing polarization with compression. Epitaxial orientation is shown to have a strong effect on the nature of strain-induced phase transitions, with (100)-oriented systems tending to have smooth, second-order transitions and (110)- and (111)-oriented systems more commonly exhibiting first-order transitions. The significance of this effect for device applications is discussed, and a number of systems are identified as potentially interesting for ferroelectric thin-film applications based on energetic stability and polarization behavior. Analysis of polarization behavior across different orientations reveals distinct groups into which compositions can be organized, some of which have polarization dependencies on misfit strain that have not been reported previously.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Tunable and low-loss correlated plasmons in Mott-like insulating oxides

Plasmonics has attracted tremendous interests for its ability to confine light into subwavelength dimensions, creating novel devices with unprecedented functionalities. New plasmonic materials are actively being searched, especially those with tunable plasmons and low loss in the visible–ultraviolet range. Such plasmons commonly occur in metals, but many metals have high plasmonic loss in the optical range, a main issue in current plasmonic research. Here, we discover an anomalous form of tunable correlated plasmons in a Mott-like insulating oxide from the Sr 1-x Nb 1-y O 3+δ family. These correlated plasmons have multiple plasmon frequencies and low loss in the visible–ultraviolet range. Supported by theoretical calculations, these plasmons arise from the nanometre-spaced confinement of extra oxygen planes that enhances the unscreened Coulomb interactions among charges. The correlated plasmons are tunable: they diminish as extra oxygen plane density or film thickness decreases. Our results open a path for plasmonics research in previously untapped insulating and strongly-correlated materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Universal structural parameter to quantitatively predict metallic glass properties

Quantitatively correlating the amorphous structure in metallic glasses (MGs) with their physical properties has been a long-sought goal. Here we introduce flexibility volume' as a universal indicator, to bridge the structural state the MG is in with its properties, on both atomic and macroscopic levels. The flexibility volume combines static atomic volume with dynamics information via atomic vibrations that probe local configurational space and interaction between neighbouring atoms. We demonstrate that flexibility volume is a physically appropriate parameter that can quantitatively predict the shear modulus, which is at the heart of many key properties of MGs. Moreover, the new parameter correlates strongly with atomic packing topology, and also with the activation energy for thermally activated relaxation and the propensity for stress-driven shear transformations. These correlations are expected to be robust across a very wide range of MG compositions, processing conditions and length scales.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Chemical ordering in substituted fluorite oxides: a computational investigation of Ho 2 Zr 2 O 7 and RE 2 Th 2 O 7 (RE=Ho, Y, Gd, Nd, La)

Fluorite-structured oxides find widespread use for applications spanning nuclear energy and waste containment, energy conversion, and sensing. In such applications the host tetravalent cation is often partially substituted by trivalent cations, with an associated formation of charge-compensating oxygen vacancies. The stability and properties of such materials are known to be influenced strongly by chemical ordering of the cations and vacancies, and the nature of such ordering and associated energetics are thus of considerable interest. Here we employ density-functional theory (DFT) calculations to study the structure and energetics of cation and oxygen-vacancy ordering in Ho 2 Zr 2 O 7 . In a recent neutron total scattering study, solid solutions in this system were reported to feature local chemical ordering based on the fluorite-derivative weberite structure. The calculations show a preferred chemical ordering qualitatively consistent with these findings, and yield values for the ordering energy of 9.5 kJ/mol-cation. Similar DFT calculations are applied to additional RE 2 Th 2 O 7 '' fluorite compounds, spanning a range of values for the ratio of the tetravalent and trivalent (RE) cation radii. Finally, the results demonstrate that weberite-type order becomes destabilized with increasing values of this size ratio, consistent with an increasing energetic preference for the tetravalent cations to have higher oxygen coordination.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Predicting defect behavior in B2 intermetallics by merging ab initio modeling and machine learning

We present a combination of machine learning and high throughput calculations to predict the points defects behavior in binary intermetallic (A-B) compounds, using as an example systems with the cubic B2 crystal structure (with equiatomic AB stoichiometry). To the best of our knowledge, this work is the first application of machine learning-models for point defect properties. High throughput first principles density functional calculations have been employed to compute intrinsic point defect energies in 100 B2 intermetallic compounds. The systems are classified into two groups: (i) those for which the intrinsic defects are antisites for both A and B rich compositions, and (ii) those for which vacancies are the dominant defect for either or both composition ranges. The data was analyzed by machine learning-techniques using decision tree, and full and reduced multiple additive regression tree (MART) models. Among these three schemes, a reduced MART (r-MART) model using six descriptors (formation energy, minimum and difference of electron densities at the Wigner-Seitz cell boundary, atomic radius difference, maximal atomic number and maximal electronegativity) presents the highest fit (98 %) and predictive (75 %) accuracy. This model is used to predict the defect behavior of other B2 compounds, and it is found that 45 % of the compounds considered feature vacancies as dominant defects for either A or B rich compositions (or both). The ability to predict dominant defect types is important for the modeling of thermodynamic and kinetic properties of intermetallic compounds, and the present results illustrate how this information can be derived using modern tools combining high throughput calculations and data analytics.

97 MATHEMATICS AND COMPUTING↗