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Atomic Layer Deposition Josephson Junctions for Cryogenic Circuit Applications

Superconducting-insulating-superconducting (SIS) trilayers have been produced for Josephson Junction fabrication by thermal atomic layer deposition (ALD) processes. The trilayers are composed of alternating layers of Ti0.4N0.6/Al2O3/ Ti0.4N0.6, deposited at 450°C, in a thermal ALD reactor on Al2O3-coated silicon. The conformal nature of the ALD process provides excellent step coverage of superconducting and insulating films. The film thickness of a single ALD cycle being one mono-layer, allows us to precisely control the tunnel-barrier insulator thickness by counting the number of ALD cycles during the insulator deposition step. Tunnel-junctions with critical current 500 A/cm2 are reported. Fabrication of Josephson Junctions and progress toward development of a single-element ALD Superconducting Quantum Interference Device (SQUID) will be discussed

Atomic Layer Definition↗

Degradation & Performance Studies of ALD-Stabilized Nano-Composite SOFC Cathodes

This work showed, definitively, for the first time, that zirconia Atomic Layer Deposited (ALD) overcoats improve the stability of Solid Oxide Fuel Cell (SOFC) cathodes by chemically gettering interfacial Sr that has segregated out of lanthanum strontium cobalt iron oxide (LSCF). The optimum ALD ZrO 2 overcoat thickness was found to be ≥5 nm and <10 nm. Gadolinium doped ceria (GDC) pre-infiltration was also shown, for the first time, to improve SOFC cathode stability through the chemical getting of Sr at the LSCF-backbone and LSCF-gas interfaces. Due to the fact that it can be performed easily in air on large-area electrodes, GDC pre-infiltration is likely more commercially viable than ALD ZrO 2 overcoating as an interfacial Sr gettering technique. Combining ZrO 2 overcoating with GDC pre-infiltration was not successful because the GDC nano-particles gettered the ZrO 2 overcoat instead of the interfacial Sr.

30 DIRECT ENERGY CONVERSION↗

Machine learning enabled quantification of the hydrogen bonds inside the polyelectrolyte brush layer probed using all-atom molecular dynamics simulations

The configuration of densely grafted charged polyelectrolyte (PE) brushes is strongly dictated by the properties and behavior of the counterions that screen the PE brush charges and the solvent molecules (typically water) that solvate the brush molecules and these screening counterions. Only recently, efforts have been made to study the PE brushes atomistically, thereby shedding light on the properties of brush-supported ions and water molecules. However, even for such efforts, there are limitations associated with using a generic definition to estimate certain properties of water and ions inside the brush layer. For example, water–water hydrogen bonds (HBs) will behave differently for locations outside and inside the brush layer, given the fact that the densely closely grafted PE brush molecules create a soft nanoconfinement where the water connectivity becomes highly disrupted: therefore, using the same definition to quantify the HBs inside and outside the brush layer will be unwise. In this paper, we address this limitation by employing an unsupervised machine learning (ML) approach to predict the water–water hydrogen bonding inside a cationic PE brush layer modeled using all-atom molecular dynamics (MD) simulations. Here, the ML method, which relies on a clustering approach and uses the equilibrium coordinates of the water molecules (obtained from the all-atom MD simulations) as the input, is capable of identifying the structural modification of water–water HBs (revealed through appropriate clustering of the data) inside the PE brush layer induced soft nanoconfinement. Such capabilities would not have been possible by using a generic definition of the HBs. Our calculations lead to four key findings: (1) the clusters formed inside and outside the brush layer are structurally similar; (2) the margin of the cluster is shorter inside the PE brush layer confirming the possible disruption of the HBs inside the PE brush layer; (3) the average “hydrogen–acceptor-oxygen–donor-oxygen” angle that defines the HB is reduced for the HBs formed inside the brush layer; (4) the use of the generic definition (definition usable for characterizing the HBs in brush-free bulk) leads to an overprediction of the number of HBs formed inside the PE brush layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrogen Bonding Inside Anionic Polymeric Brush Layer: Machine Learning-Driven Exploration of the Relative Roles of the Polymer Steric Effect, Charging, and Type of Screening Counterions

This paper employs a combination of all-atom molecular dynamics (MD) simulations and unsupervised machine learning (ML) for studying the water-water hydrogen bonds (HBs) inside the anionic poly-acrylic acid (PAA) brushes modeled using all-atom MD simulations. PAA brush layer with different charge fraction (f), namely f=0, f=0.25, and f=1, is considered. Water-water interactions, both inside and outside the brush layer, are represented through distinct clusters of tupules of variables representing distances associated with the interacting water molecules. While clusters representing the HBs are present for water inside and outside the brushes, several clusters representing the long-range water-water interactions are missing for the water molecules inside the highly charged (f=1) PAA brushes. More importantly, inside highly charged brushes, the edge of the clusters representing the water-water HBs is progressively shortened, as compared to that in the bulk. Both these results stem from the presence of the PAA brushes imparting the steric effect and the charge effect, or the effect associated with enhanced interactions of water molecules with PE charges and counterions, thereby disrupting the water connectivity. This water-charged-species interaction also increases the water-water HB angle, i.e., makes the water-water HBs less stable inside the highly charged PAA brush layer. The narrowing of the clusters representing the HBs and the alteration of the angle characterizing the HBs confirm that the conditions defining the water-water HBs change inside the PAA brush layer as a function of the charges on the PAA brush layer. Furthermore, we show that the use of the generic definition of HBs, as compared to using our simulation-motivated modified definition of water-water HBs, overpredict the number of water-water HBs inside the PAA brush layer. Finally, we employ this all-atom-MD-ML framework to quantify the effect of other types of screening counterions (Li + , Ca 2+ , and Y 3+ ions) in determining the water-water interactions and water-water HB properties inside the PAA brush layer. Furthermore, the findings of the present study, confirming the weakening of water-water HBs inside the PAA brush layer, points to the possibility that the water molecules will be more available for hydrating the brush layer and counterions, thereby leading to a more pronounced wetting of the PAA brush layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystal structures and formation mechanisms of boron-rich tungsten borides

Boron-rich tungsten borides tend to adopt mechanically unfavorable layered structures but experimentally exhibit excellent mechanical properties rivalling traditional superhard solids. Unravelling the contraindicated structure-property relationship, however, has been impeded by their structural ambiguities because of the difficulty in probing boron and atomic deficiency of these borides. Here, we study crystal structures of boron-rich tungsten borides WB 3+x and WB 2+x by neutron diffraction based on high-quality samples prepared by a high-pressure method, leading to definitive structural resolutions for both borides with unique compositions of WB 5.14 and WB 2.34 . Combined with theoretical calculations, their structural stability is revealed to be closely related to atomic deficiency, which is governed by the valence-band filling with an optimal valence-electron concentration of ~10 per cell. The presence of interstitial boron trimers at the vacant W : 2b sites in WB 5.14 alters the crystal symmetry, making the Wyckoff 2d site more favorably occupied by W, rather than the 2c site, as previously misassigned. Here, the staggered planar boron layers and wrinkled boron bonding in WB 2.34 are identified to be crucial for stabilizing its structure. These findings unveil the longstanding structural mysteries of boron-rich tungsten borides and offer powerful insights for rational design of borides by defect chemistry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Contribution of the Sub-Surface to Electrocatalytic Activity in Atomically Precise La 0.7 Sr 0.3 MnO 3 Heterostructures

Electrocatalytic reactions are known to take place at the catalyst/electrolyte interface. Whereas recent studies of size-dependent activity in nanoparticles and thickness-dependent activity of thin films imply that the sub-surface layers of a catalyst can contribute to the catalytic activity as well, most of these studies consider actual modification of the surfaces. Here, in this study, the role of catalytically active sub-surface layers was investigated by employing atomic-scale thickness control of the La 0.7 Sr 0.3 MnO 3 (LSMO) films and heterostructures, without altering the catalyst/electrolyte interface. The activity toward the oxygen evolution reaction (OER) shows a non-monotonic thickness dependence in the LSMO films and a continuous screening effect in LSMO/SrRuO 3 heterostructures. The observation leads to the definition of an “electrochemically-relevant depth” on the order of 10 unit cells. This study on the electrocatalytic activity of epitaxial heterostructures provides new insight in designing efficient electrocatalytic nanomaterials and core-shell architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomistic Method Applied to Computational Modeling of Surface Alloys

The formation of surface alloys is a growing research field that, in terms of the surface structure of multicomponent systems, defines the frontier both for experimental and theoretical techniques. Because of the impact that the formation of surface alloys has on surface properties, researchers need reliable methods to predict new surface alloys and to help interpret unknown structures. The structure of surface alloys and when, and even if, they form are largely unpredictable from the known properties of the participating elements. No unified theory or model to date can infer surface alloy structures from the constituents properties or their bulk alloy characteristics. In spite of these severe limitations, a growing catalogue of such systems has been developed during the last decade, and only recently are global theories being advanced to fully understand the phenomenon. None of the methods used in other areas of surface science can properly model even the already known cases. Aware of these limitations, the Computational Materials Group at the NASA Glenn Research Center at Lewis Field has developed a useful, computationally economical, and physically sound methodology to enable the systematic study of surface alloy formation in metals. This tool has been tested successfully on several known systems for which hard experimental evidence exists and has been used to predict ternary surface alloy formation (results to be published: Garces, J.E.; Bozzolo, G.; and Mosca, H.: Atomistic Modeling of Pd/Cu(100) Surface Alloy Formation. Surf. Sci., 2000 (in press); Mosca, H.; Garces J.E.; and Bozzolo, G.: Surface Ternary Alloys of (Cu,Au)/Ni(110). (Accepted for publication in Surf. Sci., 2000.); and Garces, J.E.; Bozzolo, G.; Mosca, H.; and Abel, P.: A New Approach for Atomistic Modeling of Pd/Cu(110) Surface Alloy Formation. (Submitted to Appl. Surf. Sci.)). Ternary alloy formation is a field yet to be fully explored experimentally. The computational tool, which is based on the BFS (Bozzolo, Ferrante, and Smith) method for the calculation of the energetics, consists of a small number of simple PCbased computer codes that deal with the different aspects of surface alloy formation. Two analysis modes are available within this package. The first mode provides an atom-by-atom description of real and virtual stages 1. during the process of surface alloying, based on the construction of catalogues of configurations where each configuration describes one possible atomic distribution. BFS analysis of this catalogue provides information on accessible states, possible ordering patterns, and details of island formation or film growth. More importantly, it provides insight into the evolution of the system. Software developed by the Computational Materials Group allows for the study of an arbitrary number of elements forming surface alloys, including an arbitrary number of surface atomic layers. The second mode involves large-scale temperature-dependent computer 2. simulations that use the BFS method for the energetics and provide information on the dynamic processes during surface alloying. These simulations require the implementation of Monte-Carlo-based codes with high efficiency within current workstation environments. This methodology capitalizes on the advantages of the BFS method: there are no restrictions on the number or type of elements or on the type of crystallographic structure considered. This removes any restrictions in the definition of the configuration catalogues used in the analytical calculations, thus allowing for the study of arbitrary ordering patterns, ultimately leading to the actual surface alloy structure. Moreover, the Monte Carlo numerical technique used for the large-scale simulations allows for a detailed visualization of the simulated process, the main advantage of this type of analysis being the ability to understand the underlying features that drive these processes. Because of the simplicity of the BFS method for e energetics used in these calculations, a detailed atom-by-atom analysis can be performed at any point in the simulation, providing necessary insight on the details of the process. The main objective of this research program is to develop a tool to guide experimenters in understanding and interpreting often unexpected results in alloy formation experiments. By reducing the computational effort without losing physical accuracy, we expect that powerful simulation tools will be developed in the immediate future, which will allow material scientists to easily visualize and analyze processes at a level not achievable experimentally.

Bozzolo, Guillermo H.↗

High-Level Data Races

Data races are a common problem in concurrent and multi-threaded programming. They are hard to detect without proper tool support. Despite the successful application of these tools, experience shows that the notion of data race is not powerful enough to capture certain types of inconsistencies occurring in practice. In this paper we investigate data races on a higher abstraction layer. This enables us to detect inconsistent uses of shared variables, even if no classical race condition occurs. For example, a data structure representing a coordinate pair may have to be treated atomically. By lifting the meaning of a data race to a higher level, such problems can now be covered. The paper defines the concepts view and view consistency to give a notation for this novel kind of property. It describes what kinds of errors can be detected with this new definition, and where its limitations are. It also gives a formal guideline for using data structures in a multi-threading environment.

Artho, Cyrille↗

Emergent quasi-two-dimensional metallic state derived from the Mott-insulator framework

Recent quasi-two-dimensional (quasi-2D) systems with judicious exploitation of the atomic monolayer or few-layer architecture exhibit unprecedented physical properties that challenge the conventional wisdom on condensed matter physics. Here we show that the infinite layer SrCuO 2 (SCO), a topical cuprate Mott insulator in bulk form, can manifest an unexpected metallic state in the quasi-2D limit when SCO is grown on TiO 2 -terminated SrTiO 3 (STO) substrates. The sheet resistance does not conform to Landau's Fermi liquid paradigm. Hard x-ray core-level photoemission spectra demonstrate a definitive Fermi level that resembles the hole doped metal. Soft x-ray absorption spectroscopy also reveals features analogous to those of a hole doped Mott insulator. Based on these results, we conclude that the hole doping does not occur at the interfaces between SCO and STO; instead, it comes from the transient layers between the chain-type and the planar-type structures within the SCO slab. In conclusion, the present work reveals a metallic state in the infinite layer SCO and invites further examination to elucidate the spatial extent of this state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A non-linearly stable implicit finite element algorithm for hypersonic aerodynamics

A generalized curvilinear coordinate Taylor weak statement implicit finite element algorithm is developed for the two-dimensional and axisymmetric compressible Navier-Stokes equations for ideal and reacting gases. For accurate hypersonic simulation, air is modeled as a mixture of five perfect gases, i.e., molecular and atomic oxygen and nitrogen as well as nitric oxide. The associated pressure is then determined via Newton solution of the classical chemical equilibrium equation system. The directional semidiscretization is achieved using an optimal metric data Galerkin finite element weak statement, on a developed 'companion conservation law system', permitting classical test and trial space definitions. Utilizing an implicit Runge-Kutta scheme, the terminal algorithm is then nonlinearly stable, and second-order accurate in space and time on arbitrary curvilinear coordinates. Subsequently, a matrix tensor product factorization procedure permits an efficient numerical linear algebra handling for large Courant numbers. For ideal- and real-gas hypersonic flows, the algorithm generates essentially nonoscillatory numerical solutions in the presence of strong detached shocks and boundary layer-inviscid flow interactions.

Iannelli, G. S.↗

Physi-sorption of H 2 on pure and boron-doped graphene monolayers: A dispersion-corrected DFT study

Carbon based materials are of interest as potential candidates for H 2 storage. Earlier work has been inconclusive on the effect of boron doping on the energy of H 2 binding. However, earlier work has been inconclusive on the definitive effect of boron doping on the energy of H 2 binding, i.e. isosteric heats of adsorption (Qst). In this work, we completed a systematic DFT study to evaluate this effect, and found that doping graphene with boron provides only minor enhancement in H 2 binding. More importantly, the presence of the electron deficient boron into a graphene ring introduces a defect, such as terminal hydrogen or distortion from planarity, which creates hydrogen adsorption sites with slightly increased Qst. The increase is from ~ 5 kJ/mol H 2 for the pure carbon matrix to ~6 - 7 kJ/mol for the boron doped system. The more strongly bond H 2 is located near the defect and shows little direct interaction with the boron. Most significant enhancement is found in systems where H 2 is confined between layers at a distance of about 7Å. In this case, the H 2 binding nearly doubles, to ~10 kJ/mol for both pure, undistorted graphene, and the 2% boron doped system, containing tetrahedral C atom distortion. Interestingly, at higher doping levels of boron, we found that the Qst decreases compared to the all carbon materials. These finding suggest that interplanar nanoconfinement may be more effective way to enhance H 2 binding than boron doping.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A data-driven peridynamic continuum model for upscaling molecular dynamics

Nonlocal models, including peridynamics, often use integral operators that embed lengthscales in their definition. However, the integrands in these operators are difficult to define from the data that are typically available for a given physical system, such as laboratory mechanical property tests. In contrast, molecular dynamics (MD) does not require these integrands, but it suffers from computational limitations in the length and time scales it can address. To combine the strengths of both methods and to obtain a coarse-grained, homogenized continuum model that efficiently and accurately captures materials’ behavior, we propose a learning framework to extract, from MD data, an optimal Linear Peridynamic Solid (LPS) model as a surrogate for MD displacements. To maximize the accuracy of the learnt model we allow the peridynamic influence function to be partially negative, while preserving the well-posedness of the resulting model. To achieve this, we provide sufficient well-posedness conditions for discretized LPS models with sign-changing influence functions and develop a constrained optimization algorithm that minimizes the equation residual while enforcing such solvability conditions. This framework guarantees that the resulting model is mathematically well-posed, physically consistent, and that it generalizes well to settings that are different from the ones used during training. We illustrate the efficacy of the proposed approach with several numerical tests for single layer graphene. Our two-dimensional tests show the robustness of the proposed algorithm on validation data sets that include thermal noise, different domain shapes and external loadings, and discretizations substantially different from the ones used for training.

homogenization↗

Real- and momentum-space description of the excitons in bulk and monolayer chromium tri-halides

Excitons with large binding energies ~2–3 eV in CrX 3 have been characterized as being localized (Frenkel) excitons that emerge from the atomic d – d transitions between the Cr-3d-t 2g and e g orbitals. The argument has gathered strength in recent years as the excitons in recently made monolayers are found at almost the same energies as the bulk. The Laporte rule, which restricts such parity forbidden atomic transitions, can relax if a symmetry-breaking mechanism is present. While what can be classified as a purely Frenkel exciton is a matter of definition, we show using an advanced first principles parameter-free approach that these excitons in CrX 3 , in both its bulk and monolayer variants, have band origin and it is the dp hybridization between Cr and X that primarily acts as the symmetry-breaking mechanism that relaxes the Laporte rule. We show that the character of these excitons is mostly determined by the Cr-d orbital manifold, nevertheless, the fractions of the spectral weight shared with the ligand halogen states increases as the dp hybridization enhances. The hybridization enhances as the halogen atom becomes heavier, bringing the X-p states closer to the Cr-d states in the sequence Cl → Br → I, with an attendant increase in exciton intensity and a decrease in binding energy. By applying a range of different kinds of perturbations that qualitatively mimics the effects originating from the missing vertex in self-energy, we show that moderate changes to the two-particle Hamiltonian that essentially modifies the Cr-d-X-p hybridization, can alter both the intensities and positions of the exciton peaks. A detailed analysis of several deep-lying excitons, with and without strain, elucidates the fact that the exciton is most Frenkel-like in CrCl 3 and CrBr 3 and acquires mixed Frenkel–Wannier character in CrI 3 , making the excitons in CrI 3 most susceptible to environmental screening and spin–orbit coupling.

36 MATERIALS SCIENCE↗

Oxide– and Silicate–Water Interfaces and Their Roles in Technology and the Environment

Interfacial reactions drive all elemental cycling on Earth and play pivotal roles in human activities such as agriculture, water purification, energy production and storage, environmental contaminant remediation, and nuclear waste repository management. The onset of the 21st century marked the beginning of a more detailed understanding of mineral aqueous interfaces enabled by advances in techniques that use tunable high-flux focused ultrafast laser and X-ray sources to provide near-atomic measurement resolution, as well as by nanofabrication approaches that enable transmission electron microscopy in a liquid cell. This leap into atomic- and nanometer-scale measurements has uncovered scale-dependent phenomena whose reaction thermodynamics, kinetics, and pathways deviate from previous observations made on larger systems. A second key advance is new experimental evidence for what scientists hypothesized but could not test previously, namely, interfacial chemical reactions are frequently driven by “anomalies” or “non-idealities” such as defects, nanoconfinement, and other nontypical chemical structures. Third, progress in computational chemistry has yielded new insights that allow a move beyond simple schematics, leading to a molecular model of these complex interfaces. In combination with surface-sensitive measurements, we have gained knowledge of the interfacial structure and dynamics, including the underlying solid surface and the immediately adjacent water and aqueous ions, enabling a better definition of what constitutes the oxide– and silicate–water interfaces. This critical review discusses how science progresses from understanding ideal solid–water interfaces to more realistic systems, focusing on accomplishments in the last 20 years and identifying challenges and future opportunities for the community to address. Further, we anticipate that the next 20 years will focus on understanding and predicting dynamic transient and reactive structures over greater spatial and temporal ranges as well as systems of greater structural and chemical complexity. Closer collaborations of theoretical and experimental experts across disciplines will continue to be critical to achieving this great aspiration.

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