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Results for “Structural order parameter”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Magnetic transition behavior in epitaxial Fe 47 Rh 47 Pd 6 films

The properties of Fe–Rh–Pd epitaxial thin films grown on MgO(001) were studied as a function of growth temperature. Films grown above 400°C exhibit a first-order antiferromagnetic to ferromagnetic magnetic phase transition with a transition temperature that decreases as the growth temperature is increased. The chemical order parameter computed from the ratio of intensities of the (001) and (002) diffraction peaks is nearly independent of the growth temperature, while the lattice constants change slightly. A comparison of our structural, magnetic, and electrical transport results with first-principle-based calculations as well as literature results indicates that the transition temperature of Fe–Rh-based alloy films depends sensitively on the lattice parameters and is of electronic origin. The transition temperature and its width can be tuned over a wide range by controlling the crystal structure via growth conditions or postdeposition annealing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Structural stability, elemental ordering, and transport properties of layered ScTaN 2

Ternary transition metal (TM) nitrides have gained significant attention in thin film research due to their promising properties for a broad range of applications. Particularly, some of the ternary TM nitrides have been predicted to adopt layered structures that make them interesting for thermoelectric conversion and quantum materials applications. Unfortunately, synthesis of TM ternary nitride films by physical vapor deposition often favors disordered 3D structures rather than the predicted 2D-like layered structure. In this study, we investigate the structural interplay in the Sc-Ta-N ternary system using a combinatorial approach. Combinatorial libraries S⁢c 𝑥 ⁢T⁢a 1−𝑥 ⁢N are synthesized following a two-step method: First, deposit film precursors by cosputtering and then process the resulting 3D-structured samples with rapid thermal annealing. Synchrotron grazing-incidence wide-angle x-ray scattering on films annealed at 1200 ⁢°⁢C for 20 min leads to the nucleation of ScTaN 2 layered structure (𝑃⁢6 3 /𝑚⁢𝑚⁢𝑐) near stoichiometry. We find that the layered structure can accommodate large off-stoichiometry in the Ta-rich region (𝑥 < 0.5), facilitated by the alloying with quasi-isostructural Ta 5 ⁢N 6 compound that exists on a composition tie line at 𝑥 = 0. While focusing on ScTaN 2 , we estimate the long-range order parameter in near-stoichiometric films to be 0.86, corresponding to a fraction of Sc/Ta antisites of 7%. Transport measurements on ScTaN 2 reveal a nearly temperature-independent high carrier density (10 21 c⁢m −3 ), suggesting a heavily doped semiconductor or semimetallic character, consistent with a small positive Seebeck coefficient of +19 µV/K. The carrier mobility at 2 K is relatively small (9.5c⁢m 2 V −1 s −1 ) and the residual-resistivity ratio is minor, suggesting that electrical conduction is dominated by defects or disorder. Measured magnetoresistance suggests possible weak antilocalization at 2 K. This paper highlights the interplay between ScTaN 2 and Ta 5 ⁢N 6 crystal structures in stabilizing layered materials, emphasizes the importance of cation order/disorder for potential tunable alloys, and suggests that ScTaN 2 is a promising platform for exploring electronic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Magnetic structure, excitations and short-range order in honeycomb Na 2 Ni 2 TeO 6

Na 2 Ni 2 TeO 6 has a layered hexagonal structure with a honeycomb lattice constituted by Ni 2+ and a chiral charge distribution of Na + that resides between the Ni layers. In the present work, the antiferromagnetic transition temperature of Na 2 Ni 2 TeO 6 is confirmed at TN˜ 27 K, and further, it is found to be robust up to 8 T magnetic field and 1.2 GPa external pressure; and, without any frequency-dependence. Slight deviations from nominal Na-content (up to 5%) does not seem to influence the magnetic transition temperature, TN. Isothermal magnetization curves remain almost linear up to 13 T. Our analysis of neutron diffraction data shows that the magnetic structure of Na 2 Ni 2 TeO 6 is faithfully described by a model consisting of two phases described by the commensurate wave vectors vec kc, (0.5 0 0) and (0.5 0 0.5), with an additional short-range order component incorporated in to the latter phase. Consequently, a zig-zag long-range ordered magnetic phase of Ni 2+ results in the compound, mixed with a short-range ordered phase, which is supported by our specific heat data. Theoretical computations based on density functional theory (DFT) predict predominantly in-plane magnetic exchange interactions that conform to a J1-J2-J3 model with a strong J3 term. The computationally predicted parameters lead to a reliable estimate for TN and the experimentally observed zig-zag magnetic structure. A spin wave excitation in Na 2 Ni 2 TeO 6 at E ˜ 5 meV at T = 5 K is mapped out through inelastic neutron scattering experiments, which is reproduced by linear spin wave theory calculations using the J values from our computations. Our specific heat data and inelastic neutron scattering data strongly indicate the presence of short-range spin correlations, at T > TN, stemming from incipient antiferromagnetic clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High-Pressure Investigation of 2,4,6-Trinitro-3-bromoanisole (TNBA): Structural Determination and Piezochromism

Understanding phase transitions in energetic materials is crucial for developing predictive models of detonation. 2,4,6-Trinitro-3-bromoanisole (TNBA), an energetic material, was studied in its single-crystal form up to pressures of 45 GPa in a diamond anvil cell. The material was characterized by using X-ray, Raman, and optical transmission measurements. From single-crystal X-ray diffraction, the ambient structure of TNBA was determined which crystallizes in the P2 1 /c space group having four molecular units per unit cell. The X-ray data up to 9.2 GPa were fitted to a third-order Birch–Murnaghan equation of state by using the parameters K o = 13.2(2.4) GPa and K p = 5.1(1.4). Between 6.8 and 7.3 GPa, a phase transition was inferred in TNBA from concurrent fading of X-ray diffraction, disappearance of Raman peaks, increase in sample fluorescence, and discontinuous color change. The new phase was consistent with an amorphous state of at least partially intact molecules judging from the presence of higher-order Raman modes and irreversibility of the Raman spectra upon release. Piezochromism was observed with the translucent yellow TNBA gradually darkening and becoming opaque black at ~25 GPa. This correlated to the absorption edge gradually shifting to the red in the visible spectrum. Signs of two possible additional structural transitions were detected in the 32.4–41.0 GPa range as suggested by a jump in the absorption edge, the irreversible changes in the absorption spectrum upon release to ambient pressure, and by the lack of Raman modes in recovered samples. Here, the crystal and electronic structures of TNBA were also investigated up to 10 GPa by using DFT calculations and crystal structure prediction (CSP) simulations. In agreement with the experimentally observed transition at 7 GPa, the simulations at 10 GPa found a bevy of polymorphs lower in enthalpy and higher in density than P2 1 /c. The lowest calculated enthalpy structure was determined to be P2 1 2 1 2 1 , being in a different space group than the ambient experimental result.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Nearest neighbour distributions: New statistical measures for cosmological clustering

ABSTRACT The use of summary statistics beyond the two-point correlation function to analyse the non-Gaussian clustering on small scales, and thereby, increasing the sensitivity to the underlying cosmological parameters, is an active field of research in cosmology. In this paper, we explore a set of new summary statistics – the k-Nearest Neighbour Cumulative Distribution Functions (kNN-CDF). This is the empirical cumulative distribution function of distances from a set of volume-filling, Poisson distributed random points to the k-nearest data points, and is sensitive to all connected N-point correlations in the data. The kNN-CDF can be used to measure counts in cell, void probability distributions, and higher N-point correlation functions, all using the same formalism exploiting fast searches with spatial tree data structures. We demonstrate how it can be computed efficiently from various data sets – both discrete points, and the generalization for continuous fields. We use data from a large suite of N-body simulations to explore the sensitivity of this new statistic to various cosmological parameters, compared to the two-point correlation function, while using the same range of scales. We demonstrate that the use of kNN-CDF improves the constraints on the cosmological parameters by more than a factor of 2 when applied to the clustering of dark matter in the range of scales between 10 and $40\, h^{-1}\, {\rm Mpc}$. We also show that relative improvement is even greater when applied on the same scales to the clustering of haloes in the simulations at a fixed number density, both in real space, as well as in redshift space. Since the kNN-CDF are sensitive to all higher order connected correlation functions in the data, the gains over traditional two-point analyses are expected to grow as progressively smaller scales are included in the analysis of cosmological data, provided the higher order correlation functions are sensitive to cosmology on the scales of interest.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

How Cooperatively Folding Are Homopolymer Molecular Knots?

Detailed thermodynamic analysis of complex systems with multiple stable configurational states allows for insight into the cooperativity of each individual transition. In this work, we derive a heat capacity decomposition comprising contributions from each individual configurational state, which together sum to a baseline heat capacity, and contributions from each state-to-state transition. We apply this analysis framework to a series of replica exchange molecular dynamics simulations of linear and 1-1 coarse-grained homo-oligomer models, which fold into stable, configurationally well-defined molecular knots, in order to better understand the parameters leading to stable and cooperative folding of these knots. We find that a stiff harmonic backbone bending angle potential is key to achieving knots with specific 3D structures. Tuning the backbone equilibrium angle in small increments yields a variety of knot topologies. Populations of different knotted states as a function of temperature can also be manipulated by tuning the backbone torsion stiffness or by adding side-chain beads. We find that sharp total heat capacity peaks for the homo-oligomer knots are largely due to a coil-to-globule transition rather than a cooperative knotting step. Furthermore, in some cases, the cooperativity of globule-to-knot and coil-to-globule transitions is comparable, suggesting that highly cooperative folding to knotted structures can be achieved by refining the model parameters or adding sequence specificity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Long‐Term Observations of Turbulence Vertical Velocity Spectra in a Convective Mixed Layer: Dependence on Land‐Surface Forcing in the U.S. Southern Great Plains

Doppler lidar vertical velocity retrievals were analyzed for the scale and structure of mixed-layer turbulence over a 7-year period, on fair-weather warm season days (442 cases) in the U.S. Southern Great Plains. Based on the hypothesized influence of land-surface forcing and updraft size on convective boundary layer clouds, a spectral analysis was performed to quantify effects of surface forcing (surface buoyancy flux, friction velocity, and evaporative fraction) on turbulence scale. Significant (order-of-magnitude) variations in spectral density were found in the energy-production subrange and mesoscale regimes. Integral scale decreased with increasing buoyancy flux (and Monin-Obukhov stability parameter), while spectral density in the energy-production subrange increased, implying a transition to buoyancy-driven cellular structures with narrower updrafts. The influence of stability parameter was limited to the neutral to convective transition, and could not explain the wide variation in spectral density in the mesoscale regime. However, high friction velocity (u* > 0.5 m s –1 ) was associated with larger integral scale (updraft width), and a greater portion of spectral density in the mesoscale regime. Lidar profiles and radar reflectivity for individual cases revealed evidence of roll and wave-like structures contributing to mesoscale variability on high friction velocity days, suggesting shear instabilities on days with wetter land surface conditions and smaller buoyancy flux. The role of friction velocity emphasizes the multivariate nature of surface influences on turbulence, and implies that variance-based turbulence closures may not be adequate for capturing effects of surface forcing on updraft size.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Influence of growth temperature of KTiOAsO{sub 4} single crystals on their physicochemical parameters and formation of domain structures

A potassium titanyl arsenate (KTiOAsO{sub 4}, KTA) crystal 50 × 80 × 60 mm in size has been grown by upgraded Czochralski method from flux (TGGS) with a decrease in temperature from 900 to 770 °C during pulling. It is shown that the spectroscopic properties of the parts of KTA crystals grown at 900 and 770 °C are close, whereas the electrical conductivity of the low-temperature (770 °C) KTA part turned out to be an order of magnitude lower than that of the high-temperature part. Visualisation of the domain structure by second-harmonic generation microscopy revealed a more efficient domain intergrowth (throughout the sample) in the low-temperature KTA, which is important for forming a regular domain structure (RDS) in a KTA-based nonlinear optical element. It is established that the quantum efficiency of parametric generation of light in the RDS formed in low-temperature KTA is several times higher than in the case of high-temperature KTA. The results obtained are important for optimising RDS parameters. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal Processing

Neuromorphic computing inspired by mammalian intelligence aims to emulate the nonlinear dynamics of biological neurons and synapses to achieve fast, low-energy, and highly efficient information processing. Brain-inspired computing relies on the design and discovery of materials exhibiting nonlinear current–voltage profiles, frequently underpinned by electronic state transitions, to achieve spiking neurons and dynamically tunable synapses. A signature challenge in the design of artificial neurons is controlling the steepness of first-order transitions in active elements, as abrupt transitions are at risk of driving unstable voltage and temperature oscillations, which result in catastrophic device failure. A critical knowledge gap is the lack of structure–function correlations mapping the composition and atomistic structure of crystalline solids to nonlinear dynamical response characteristics. Here, we address the key question of how modification of atomistic structure correlates with alteration of neuron-like functionality. Constructing oscillator circuits from millimeter-scale single crystals enables high-resolution atomic structure solutions, which we use to demonstrate that the selective positioning of Pb cations modifies charge ordering along a one-dimensional CuxV2O5 framework even at low insertion stoichiometries, thereby providing an atom-precise design parameter for damping first-order transitions. We use temperature-variant X-ray diffraction and X-ray spectroscopy to elucidate the suppression of Cu-ion shuttling based on the precise positioning of Pb ions in seven-coordinated tunnel interstitial sites as the mechanistic basis for transition broadening, thus bridging a critical gap between statistical mechanics and quantum chemical descriptions of phase transitions. Such mechanistic understanding thus paves the way to site-selective modification strategies for modulating the sharpness of first-order transitions, with an exemplary demonstration here in tuning neuronal signal processing.

Crystal structure↗
DOE OSTI2025

High-Entropy Alloys for Accelerator Beam Window Applications

Development of novel high-entropy alloys (HEAs) is currently underway for potential use as beam windows in future multi-megawatt target systems at Fermilab. HEAs encompass a new class of materials with a vast design space allowing for material properties to be tailored for particular applications and to potentially offer improved resistance to beam-induced radiation damage and thermal shock effects. The alloy systems being studied consist of several compositions of AlCoCrMnTiV with 4 6 component elements. These alloys are all predicted by CALPHAD simulation to have a single-phase BCC crystal structure and low density, with some compositions displaying ordered, nanoscale precipitates. This presentation will briefly discuss alloy design and synthesis before giving a detailed description of the characterization studies of these HEAs in both the pristine state and post-irradiation by low-energy heavy ions to high damage levels. Electron microscopy techniques to quantify elemental homogeneity and composition, determine grain size, shape, and orientation, and quantify lattice parameters, defect structures and precipitate phases are all being used to study alloy microstructures. Mechanical properties of the alloys at the microscale will be reported. The evolution of these properties as a function of radiation damage will also be described. Bulk thermal characteristics of these HEAs have been tested to measure specific heat capacity and coefficient of thermal expansion as a function of temperature. To determine bulk tensile properties a miniature tensile testing apparatus is under development; it s commissioning will be covered briefly. The talk will conclude with our plans for alloy down-selection.

Burleigh, A. [Fermilab]↗
DOE OSTI2025

LeaPP: Learning Pathways to Polymorphs through Machine Learning Analysis of Atomic Trajectories

Understanding the mechanisms underlying crystal nucleation and growth is crucial for many technological applications. Due to the short length and time scales involved, crystal nucleation is often studied using molecular simulations. Most existing approaches to extract the nucleation mechanism from simulations focus on the analysis of static snapshots of the configurations, potentially overlooking subtle local fluctuations and the history of the particles involved in the formation of solid nuclei. Here, in this work, we propose a novel methodology called LeaPP that categorizes nucleation trajectories based on the temporal information of their constituent particles. We leverage the time evolution of the local environment of the crystallizing particles to encapsulate the relationship between the structure and dynamics and distinguish between different evolving particle paths. Identification of the distinct particle paths further enables characterizing the nucleation trajectories into different pathways. Collectively, LeaPP provides a more nuanced understanding of nucleation through an unsupervised approach with lesser dependence on traditional order parameters. Furthermore, the pathways identified by LeaPP are predictive of the resulting polymorph. We demonstrate LeaPP on three different systems─Lennard-Jones-like particles, Ni 3 Al, and water on surfaces. The general methodology underlying LeaPP─considering the time evolution of the building blocks─applies to a wide range of self-assembly problems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Supramolecular bending and twisting in the hierarchical self-assembly of monodisperse mesogenic oligomers

Understanding how different forms of supramolecular curvature arise during assembly is crucial to designing and tuning the microstructure of hierarchically self-assembled materials. Here, we show that in crystalline phases of mesogenic oligomers, the oligomer length is a critical parameter that determines the type of curvature (Gaussian or cylindrical) exhibited by the self-assembled structures. We use iterative exponential growth to synthesize monodisperse mesogenic oligomers ranging from dimer to octamer. By analyzing their phase behavior and microstructure, we elucidate how length-dependent thermodynamic and kinetic effects tune their hierarchical degree of ordering. The oligomers’ length-dependent crystalline order drives the formation of scrolled sheets in shorter oligomers and twisted ribbons in longer oligomers. These studies highlight how oligomer length interplays with mesogen geometry and crystalline packing to drive self-assembly, introducing oligomer length as a powerful design parameter toward tailored applications of mesogenic systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Green Needle Coke Production from Pyrolysis Biocrude toward Bio-based Anode Material Manufacture: Biochar Fines Addition Effect as “Physical Template” on the Crystalline Order

Here, a new method for producing green needle coke (GNC) is developed by replacing the “heavy fraction” of petroleum pitch delayed coking with fast pyrolysis biocrude. A series of alternative biocrude distillation, carbonization, and calcination conditions were investigated to determine the influence of these processing parameters onto the crystalline structure of the resulting graphitized material. For the first time, the addition of biochar fines was found to serve as a “physical template” to increase the graphitic nature of the final product. During the initial biocrude carbonization (350–450 °C), volatile compounds are released, and aromatics in pyrolysis biocrude experience condensation, resulting in GNC solids with carbon contents above 95 wt % and some early lamellar structure. In the second stage of the thermal process (25–1500 °C), there are additional thermal decomposition reactions with an increase in the aromatic nature of the graphitized solid. It was found that systematic addition of biochar fines induces a nucleating effect during the GNC development. Thermogravimetric analysis suggests that biochar fines promote polycondensation reactions by modifying the biopitch structure and molecular weight, while elemental analysis (CHN) shows a reduction in both H/C and O/C ratios which are consistent with the increase in aromaticity and removal of oxygenated compounds as thermal treatment evolves. The effects of different bio-based pitch materials (after distillation) and GNC intermediates were evaluated by pyrolysis-gas chromatography mass spectrometry and Fourier transform infrared, displaying slight changes on product yields and quality. X-ray diffraction patterns taken after graphitization evidence an increase in the graphitic order with the addition of biochar fines. Transmittance electron microscopy depicts an improvement on graphitic morphology as biochar fine content increases. The use of biochar fines showed a significant increase in graphitic ordering at addition levels above 0.01 wt %. These results show that thermally treated biocrude/biochar fine systems can produce graphitic structures (hard carbon-like) that might be suitable for the manufacture of sodium-ion batteries.

09 BIOMASS FUELS↗
DOE OSTI2022

Probabilistic inversion of circular phase spectra: application to two-station phase-velocity dispersion estimation in western Canada

SUMMARY Periodic directional and temporal measurements are common in seismology, and necessitate specific statistical analyses that are appropriate for circular quantities. In this work, we explore the use of a von Mises distribution as a representation of errors on circular seismological observations. Specifically, we automate the estimation of surface-wave phase-velocity dispersion for the teleseismic two-station method, which generally suffers from a 2π phase ambiguity. The use of Bayesian inverse techniques, which aim to rigorously quantify model parameter uncertainty, have become widespread throughout seismology over the last decade. Here, we apply Bayesian inversion to measurements of surface-wave phase spectra in order to estimate 1-D, path-averaged Earth structure between station pairs. The dispersion curve and associated uncertainties are additional results of the inversion, which can then be used as input for subsequent analyses (e.g. tomography). We demonstrate this technique through application to surface-wave recordings from long-running seismic stations throughout western Canada. Our results for over 10 000 station pairs reveal first-order tectonic features consistent with previous studies, which provides confidence in our approach as well as an initial step towards resolving a full 3-D seismic velocity model for the region. This work also presents a foundation for the inversion of surface-wave phase spectra to estimate 3-D Earth structure directly. Finally, the ideas presented in this work are not limited to the inversion of surface-wave phase spectra, but can also be considered for Bayesian geophysical inversion of any circular quantities.

Gosselin, Jeremy M. (ORCID:0000000203754102)↗
DOE OSTI2021

Observation of Forward Neutron Multiplicity Dependence of Dimuon Acoplanarity in Ultraperipheral Pb-Pb Collisions at $\sqrt{s_{NN}}$ = 5.02 TeV

The first measurement of the dependence of $γγ → μ^+μ^–$ production on the multiplicity of neutrons emitted very close to the beam direction in ultraperipheral heavy ion collisions is reported. Data for lead-lead interactions at $\sqrt{s_{NN}}$ = 5.02 TeV, with an integrated luminosity of approximately 1.5 nb –1 , are collected using the CMS detector at the LHC. The azimuthal correlations between the two muons in the invariant mass region 8 < $m_{μμ}$ < 60 GeV are extracted for events including 0, 1, or at least 2 neutrons detected in the forward pseudorapidity range |η| > 8.3. The back-to-back correlation structure from leading-order photon-photon scattering is found to be significantly broader for events with a larger number of emitted neutrons from each nucleus, corresponding to interactions with a smaller impact parameter. This observation provides a data-driven demonstration that the average transverse momentum of photons emitted from relativistic heavy ions has an impact parameter dependence. These results provide new constraints on models of photon-induced interactions in ultraperipheral collisions. They also provide a baseline to search for possible final-state effects on lepton pairs caused by traversing a quark-gluon plasma produced in hadronic heavy ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Sensitivity of cellular automata grain structure predictions for high solidification rates

Understanding as-solidified grain structure development during constrained (G 0) alloy solidification conditions is a necessary component of understanding the larger process-microstructure relationships during additive manufacturing (AM) processing. This study applies a cellular automata (CA) model, for static solidification velocities and thermal gradients on the order of those expected in AM melt pools, to investigate grain shape development across ranges of input parameters governing temperature field evolution, nucleation, and growth. Variation in nucleated grain shape from columnar to equiaxed as a function of thermal gradient and nucleation density is modeled with CA and verified against the established transition model of Hunt and Gaumann. Furthermore, while thermal conditions and nucleation density are shown to have the largest roles on microstructure development, the sensitivity of grain structure was very unevenly distributed across parameter space. In particular, it was found that microstructure is very sensitive to mean nucleation undercooling and the interfacial response function in process space regimes near grain structure transitions, but entirely controlled by a combination of thermal gradient, solidification velocity, and nucleation density away from such transitions. The understanding of grain shape sensitivity obtained through CA modeling, particularly at large thermal gradient and nucleation density, will be necessary for accurate microstructure prediction during the extreme processing conditions and large input parameter uncertainty common to AM.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Anisotropic superconductivity of niobium based on its response to nonmagnetic disorder

Niobium is one of the most studied superconductors, both theoretically and experimentally. It is tremendously important for applications, and it has the highest superconducting transition temperature, T c = 9.32 K, of all pure metals. In addition to power applications in alloys, pure niobium is used for sensitive magnetosensing, radio-frequency cavities, and, more recently, as circuit metallization layers in superconducting qubits. A detailed understanding of its electronic and superconducting structure, especially its normal and superconducting state anisotropies, is crucial for mitigating the loss of quantum coherence in such devices. Recently, a microscopic theory of the anisotropic properties of niobium with the disorder was put forward. To verify theoretical predictions, we studied the effect of disorder produced by 3.5 MeV proton irradiation of thin Nb films grown by the same team and using the same protocols as those used in transmon qubits. By measuring the superconducting transition temperature and upper critical fields, we show a clear suppression of T c by potential (nonmagnetic) scattering, which is directly related to the anisotropic order parameter. Here, we obtain a very close quantitative agreement between the theory and the experiment.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗