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NASA NTRS1990

Integrated Aerodynamic and Control System Design of Oblique Wing Aircraft

An efficient high speed aircraft design must achieve a high lift to drag ratio at transonic and supersonic speeds. In 1952 Dr. R. T. Jones proved that for any flight Mach number minimum drag at a fixed lift is achieved by an elliptic wing planform with an appropriate oblique sweep angle. Since then, wind tunnel tests and numerical flow models have confirmed that the compressibility drag of oblique wing aircraft is lower than similar symmetrical sweep designs. At oblique sweep angles above thirty degrees the highly asymmetric planform gives rise to aerodynamic and inertia couplings which affect stability and degrade the aircraft's handling qualities. In the case of the NASA-Rockwell Oblique Wing Research Aircraft, attempts to improve the handling qualities by implementing a stability augmentation system have produced unsatisfactory results because of an inherent lack of controllability in the proposed design. The present work focuses on improving the handling qualities of oblique wing aircraft by including aerodynamic configuration parameters as variables in the control system synthesis to provide additional degrees of freedom with which to further decouple the aircraft's response. Handling qualities are measured using a quadratic cost function identical to that considered in optimal control problems, but the controller architecture is not restricted to full state feedback. An optimization procedure is used to simultaneously solve for the aircraft configuration and control gains which maximize a handling qualities measure, while meeting imposed constraints on trim. In some designs wing flexibility is also modeled and reduced order controllers are implemented. Oblique wing aircraft synthesized by this integrated design method show significant improvement in handling qualities when compared to the originally proposed closed loop aircraft. The integrated design synthesis method is then extended to show how handling qualities may be traded for other types of mission performance (drag, weight, etc.). Examples are presented which show how performance can be maximized while maintaining a desired level of handling quality.

Morris, Stephen James↗

DOE OSTI2023

Controlling Mass Transport in Direct Carbon Dioxide Zero-Gap Electrolyzers via Cell Compression

The development of high-performance CO 2 electrolyzers is crucial for accelerating the sustainable production of fuels and chemicals integrated with renewable energy sources. Here, we introduce a methodology to actively control mass transport inside a realistic zero-gap membrane electrode assembly of a CO 2 electrolyzer by varying the gasket thickness, which consequently changes the cell compression. This allows control over the thickness and porosity of the gas diffusion electrodes, influencing the overall electrolyzer performance, as demonstrated using Ag-deposited electrodes. At low operating voltages (<2.9 V), both high- and low-compression electrolyzers exhibit similar faradaic efficiencies and partial current densities for CO formation. However, at high voltages, the low-compression electrolyzer with high electrode porosity demonstrates superior CO selectivity and activity with suppressed H 2 formation. These experimental results are validated by the computational membrane electrode assembly (MEA) model developed by using the measured in situ electrode thicknesses and electrode porosities. Additionally, liquid electrolyte saturation at the catalyst layer is found to play a dominant role in determining the mass transport, resulting in a decreased electrolyzer performance with low electrode porosity. Finally, the systematic investigation in this study improves the understanding of the transport dynamics in MEA-based devices and provides insights into optimizing device design parameters for industry-relevant CO 2 electrolysis.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2026

DESI DR2 Baryon Acoustic Oscillations from the Lyman Alpha Forest Multipoles

We present an alternative measurement of the Baryon Acoustic Oscillation (BAO) using the Legendre multipole representation of the Ly$α$ forest correlation functions from the second data release (DR2) of the Dark Energy Spectroscopic Instrument survey. Compressing the auto- and cross-correlation functions into Legendre multipoles yields a positive-definite covariance matrix without any smoothing -- unlike the baseline DR2 analysis -- thanks to a significantly reduced data vector size. We introduce the statistical corrections required to debias the finite-sample covariance matrix estimate and demonstrate that monopole and quadrupole terms for both auto- and cross-correlations can be used even when the correlation functions are distorted by continuum errors and contaminated by metals. This formalism has slightly diminished the constraining power of the BAO scale, while considerably weakening constraints on nuisance parameters. We measure the isotropic BAO scale with $0.93\%$ precision at $z_\mathrm{eff}=2.35$, the Hubble parameter $H(z_\mathrm{eff})=(239.5\pm3.4)~(147.09~\mathrm{Mpc}/r_d) ~\mathrm{km~s}^{-1}~\text{Mpc}^{-1}$, and the transverse comoving distance $D_M(z_\mathrm{eff})=(5.80 \pm 0.10)~(r_d/147.09~\mathrm{Mpc})$~Gpc for a given value of the sound horizon ($r_d$). Our BAO results are entirely consistent with the baseline DR2 analysis.

Karaçaylı, Naim Göksel [Chicago U., KICP; Ohio Sta↗

NASA NTRS1977

Data-handling considerations for advanced high-resolution multispectral scanners

Several scanner design parameters that greatly affect data rates were varied to determine overall effect on data rates. Bit rates were calculated for scanners with 10-, 15-, 20-, and 30-meter instantaneous fields of view; with 5, 7, and 10 channels; and with swath widths of 46.3, 92.6, 138.9, and 185.2 kilometers (25, 50, 75, and 100 nautical miles). The data were analyzed to determine whether they could be (1) recorded onboard the spacecraft with currently available equipment, (2) recorded onboard with the equipment proposed for the 1980-90 period, (3) transmitted to earth with current or proposed equipment; and (4) compressed and decompressed without significant degradation of classification accuracy. The effect of classifying 10-meter scanner data on the existing and the development pattern-recognition systems was examined.

Whitley, S. L.↗

NASA NTRS1991

Hydrogen no-vent fill testing in a 34 liter (1.2 cubic foot) tank

Experimental results of no-vent fill testing with liquid hydrogen in a 34 liter stainless steel tank are presented. More than 40 tests were performed with various liquid inlet temperatures, inlet flowrates, initial tank wall temperatures, and liquid injection techniques. Maximum pressure within the receiver tank was limited to 0.207 MPa (30 psia), and fill levels equal to or exceeding 90 percent by volume were achieved in 40 percent of the tests. Three liquid injection techniques were employed; top spray, upward pipe discharge, and bottom diffuser. Effects of each of the various parameters on the tank pressure history and final fill level are evaluated. The final fill level is found to be indirectly proportional to the initial wall and inlet liquid temperatures and directly proportional to the inlet liquid flowrate. Furthermore, the top spray is the most efficient no-vent fill method of the three configurations examined. The success of this injection method is primarily due to condensation of the ullage vapor onto the incoming liquid droplets. Ullage condensation counteracts the tank pressure rise resulting from energy exchange between the fluid and the warmer tank walls and from ullage compression.

Moran, Matthew E.↗

DOE OSTI2020

MULTI-DIMENSIONAL MODELING OF THE CFR ENGINE FOR THE INVESTIGATION OF SI NATURAL GAS COMBUSTION AND CONTROLLED END-GAS AUTOIGNITION

Engine knock and misfire are barriers to pathways leading to high-efficiency Spark-Ignited (SI) Natural Gas engines. The general tendency to knock is highly dependent on engine operating conditions and the fuel reactivity. The problem is further complicated by low emission limits and the wide range of chemical reactivity in pipeline quality natural gas. Depending on the region and the source of the natural gas, its reactivity, described by its methane number (analogous to the octane number for liquid SI fuels) can span from 65 - 95. In order to realize diesel-like efficiencies, SI natural gas engines must be designed to operate at high BMEP near knock limits over a wide range of fuel reactivity. This requires a deep understanding regarding the combustion-engine interactions pertaining to flame propagation and end-gas autoignition (EGAI). However, EGAI, if controlled, provides an opportunity to increase SI natural gas engine efficiency by increasing combustion rate and the total burned fuel, mitigating the effects of the slow flame speeds of natural gas fuels which generally reduce BMEP and increase unburned hydrocarbon emissions. For this reason, in order to study EGAI phenomenon, the present work highlights multi-dimensional computational fluid dynamics (CFD) models of the Cooperative Fuel Research (CFR) engine. The CFR engine models are used to investigate fuel-engine interactions that lead to EGAI with natural gas, including effects of fuel reactivity, engine operating parameters, and exhaust gas recirculation (EGR). A Three-Pressure Analysis, performed with GT-Power, was used to estimate initial and boundary conditions for the three-dimensional CFD model. CONVERGE CFD v2.4 was used for the three-dimensional CFD modeling where the level set G-Equation model and SAGE detailed chemical kinetics solver were used. An assessment of the different modeling approaches is also provided to evaluate their limitations, advantages and disadvantages, and for which situations they are most applicable. Model validation was performed with experimental data taken with a CFR engine over varying compression ratio, CA50, EGR fraction, and IMEP and shows good agreement in Peak Cylinder Pressure (PCP), PCP crank angle, and the location of the 10%, 50%, and 90% mass fraction burned (CA10, CA50, and CA90, respectively). The models can predict the onset crank angle and pressure rise rate for light, medium, and heavy EGAI under a variety of fuel reactivities and engine operating conditions.

Bestel, Diego↗

DOE OSTI2019

The Structural, Electronic, and Magnetic Properties of Binary Heusler Alloys ZCl{sub 3} (Z = Li, Na, K, Rb) with DO{sub 3}-Type Structure from First Principle Calculations

The structural, electronic, and magnetic properties of binary Heusler alloys ZCl{sub 3} (Z = Li, Na, K, Rb) with DO{sub 3}-type structure have been studied by means of the first principle calculations. The calculated results reveal that all four alloys are half-metallic (HM) materials at the stable ferromagnetic ground state. The total magnetic moments (M{sub t}) of LiCl{sub 3}, NaCl{sub 3}, KCl{sub 3,} and RbCl{sub 3} alloys are all 2.000 μ{sub B}/f.u., following the Slater-Pauling rule M{sub t} = 24 − Z{sub t} for the former two alloys, while satisfying the Slater-Pauling rule M{sub t} = 30 − Z{sub t} for the latter two alloys. The spin-up band gaps of the binary Heusler alloys ZCl{sub 3} (Z = Li, Na, K, Rb) are 5.598, 5.687, 6.744, and 6.745 eV at equilibrium lattice constants 7.076, 7.237, 7.588, and 7.819 Å, respectively. The positive cohesion energy and negative formation energy indicate that they are thermodynamically stable. Moreover, wide HM regions for binary Heusler alloys ZCl{sub 3} (Z = Li, Na, K, Rb) show their HM characters are robust when the lattices are expanded or compressed under uniform and tetragonal strains. Finally, the total charge density, magnetic charge density, and charge density difference of the (110) plane for LiCl{sub 3} alloy are analyzed in detail.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

Discrete element modeling of deformable pinewood chips in cyclic loading test

The design of efficient lignocellulosic biomass feedstock systems is challenging, as current laboratory characterization and design methods were developed primarily for fine powders with relatively low compressibility. Here, the discrete element method (DEM) is gaining prominence as an alternative method for modeling the bulk flow and transport of particulate materials in hoppers and feeders. However, prior DEM simulations investigating the flow of wood chips modeled the particles as simple rigid geometries such as spheres, rods or blocks, and neglected the effects of particle deformability and irregular shapes. As a consequence, those simplified DEM models may not provide enough key diagnosis to help improve the design of biomass feeding and handling equipment. This work presents a bonded-sphere DEM approach for characterizing the mechanical behavior of bulk flexible, deformable pinewood chips in a cyclic stress loading test. Clustered spheres that can bend and twist via elastic bonds are used to model irregular-shape particles in real pinewood chip samples. An axial compression tester, which contains 0.06 million bonded-sphere particles (1.35 million spheres) in a quarter cylinder, is simulated with a domain size similar to the experiments. With careful calibration, the simulations have delivered the bulk densities and the bulk moduli of elasticity that are in good agreement with those measured in the corresponding experiments. However, it is also been found challenging for the present DEM model to accurately predict the overall stress-strain behavior of bulk pinewood chips, especially the large sustained plastic deformation during unloading. Additional numerical tests have shown that the adjustment in certain contact parameters (e.g. bond stiffness) can lead to profound solution improvement, but meanwhile will induce extra challenges such as increased computing time. Future work will include an elasto-plastic particle bond model to enhance the simulation fidelity.

42 ENGINEERING↗

DOE OSTI2022

Unified many-worlds browsing of arbitrary physics-based animations

Manually tuning physics-based animation parameters to explore a simulation outcome space or achieve desired motion outcomes can be notoriously tedious. This problem has motivated many sophisticated and specialized optimization-based methods for fine-grained (keyframe) control, each of which are typically limited to specific animation phenomena, usually complicated, and, unfortunately, not widely used. In this paper, we propose Unified Many-Worlds Browsing (UMWB), a practical method for sample-level control and exploration of physics-based animations. Our approach supports browsing of large simulation ensembles of arbitrary animation phenomena by using a unified volumetric WORLDPACK representation based on spatiotemporally compressed voxel data associated with geometric occupancy and other low-fidelity animation state. Beyond memory reduction, the WORLDPACK representation also enables unified query support for interactive browsing: it provides fast evaluation of approximate spatiotemporal queries, such as occupancy tests that find ensemble samples ("worlds") where material is either IN or NOT IN a user-specified spacetime region. WORLDPACKS also support real-time hardware-accelerated voxel rendering by exploiting the spatially hierarchical and temporal RLE raster data structure. Our UMWB implementation supports interactive browsing (and offline refinement) of ensembles containing thousands of simulation samples, and fast spatiotemporal queries and ranking. We show UMWB results using a wide variety of physics-based animation phenomena---not just JELL-O ® .

Computer Science↗

DOE OSTI2024

Super Resolving Unrolled Neural Networks for Remote Sensing

In remote sensing systems, the capabilities of the system are constrained by the complex interactions between size, weight, and power (SWAP) of potential designs. In electro-optical (EO) systems, examples of these critical parameters include the system’s sensitivity and resolution. Those parameters can be increased by ever larger optical apertures and focal planes but at the cost of more SWAP. Multi-image super resolution (MISR) techniques allow resolution to be enhanced via computation rather than more sophisticated optical hardware. These algorithms combine multiple images together into a single, higher resolution image, trading temporal resolution and computation for spatial resolution. Fielded MISR techniques, such as Drizzle, can require several hundred images to create a single super resolved image, implying reduced temporal resolution, increased data acquisition load, and limiting mission applications. Iterative techniques, such as model-based image reconstruction and compressive sensing, have been shown to create super resolved images using fewer images than Drizzle. They do this by posing an optimization problem that balances accuracy between a highly accurate physical model and an image model. In the case of super resolution, the physical model is defined by the relation between low resolution input images and the desired high resolution output image. The image model encodes some assumptions about the super resolved image. These assumptions are meant to suppress reconstruction artifacts that arise due to deterministic physical model error, stochastic measurement noise, and potential undersampling. In practice, the performance of iterative methods are limited by imaging models compatible with optimization. Deep learning-based methods can effectively learn image models of arbitrary complexity, but lack the theoretical explainability and robustness of iterative techniques. Consensus equilibrium (CE) generalizes the iterative techniques beyond optimization, enabling blackbox algorithms such as traditional and neural image denoisers to be used as the image model. CE-based approaches retain much of the explainability and robustness of iterative techniques while allowing the expressiveness of machine learning image models to be used. Additionally, by unrolling iterations of CE with an embedded image denoiser, the image denoiser can be further trained and specialized to the specific application with potentially higher quality reconstructions. Under this project, we demonstrated the feasibility of training an unrolled neural network based upon CE. While we didn’t train one, we showed that the CE process is differentiable and its gradient can be tractably computed. We also explored the usage of a variants of CE akin to generative neural works. Most importantly, we applied the CE framework to a number of problems including non-blind deconvolution, upsampling, single-image super resolution, MISR, event-based sensing, and saturated deconvolution. Our MISR prototype creates high quality reconstructions with an order of magnitude fewer images than previous approaches and, critically, produces these reconstructions fast enough for practical usage.

47 OTHER INSTRUMENTATION↗

DOE OSTI2019

CFD-Guided Combustion System Optimization of a Gasoline Range Fuel in a Heavy-Duty Compression Ignition Engine Using Automatic Piston Geometry Generation and a Supercomputer

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty diesel engine running with a gasoline fuel that has a research octane number (RON) of 80. The goal was to optimize the gasoline compression ignition (GCI) combustion recipe (piston bowl geometry, injector spray pattern, in-cylinder swirl motion, and thermal boundary conditions) for improved fuel efficiency while maintaining engine-out NO x within a 1-1.5 g/kW-hr window. The numerical model was developed using the multi-dimensional CFD software CONVERGE. A two-stage design of experiments (DoE) approach was employed with the first stage focusing on the piston bowl shape optimization and the second addressing refinement of the combustion recipe. For optimizing the piston bowl geometry, a software tool, CAESES, was utilized to automatically perturb key bowl design parameters. This led to the generation of 256 combustion chamber designs evaluated at several engine operating conditions. The second DoE campaign was conducted to optimize injector spray patterns, fuel injection strategies and in-cylinder swirl motion for the best performing piston bowl designs from the first DoE campaign. This comprehensive optimization study was performed on a supercomputer, Mira, to accelerate the development of an optimized fuel-efficiency focused design. Compared to the production combustion system in the baseline engine, the new combustion recipe from this study showed significantly improved closed-cycle fuel efficiency across key engine operating points while meeting the engine-out NO x targets. Optimized piston bowl designs and injector spray patterns were predicted to provide enhanced in-cylinder air utilization and more rapid mixing-controlled combustion, thereby leading to a fuel efficiency improvement. In addition, shifting the engine thermal boundary conditions toward leaner operation was also key to the improved fuel efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

A synthetic building operation dataset

Abstract This paper presents a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with 1395 annual simulations using the U.S. DOE detailed medium-sized reference office building, and 30 years’ historical weather data in three typical climates including Miami, San Francisco, and Chicago. Three energy efficiency levels of the building and systems are considered. Assumptions regarding occupant movements, occupants’ diverse temperature preferences, lighting, and MELs are adopted to reflect realistic building operations. A semantic building metadata schema - BRICK, is used to store the building metadata. The dataset is saved in a 1.2 TB of compressed HDF5 file. This dataset can be used in various applications, including building energy and load shape benchmarking, energy model calibration, evaluation of occupant and weather variability and their influences on building performance, algorithm development and testing for thermal and energy load prediction, model predictive control, policy development for reinforcement learning based building controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

AlphaBuilding - Synthetic Buildings Operation Dataset

This is a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with 1395 annual simulations using the U.S. DOE detailed medium-sized reference office building, and 30 years' historical weather data in three typical climates including Miami, San Francisco, and Chicago. Three energy efficiency levels of the building and systems are considered. Assumptions regarding occupant movements, occupants' diverse temperature preferences, lighting, and MELs are adopted to reflect realistic building operations. A semantic building metadata schema - BRICK, is used to store the building metadata. The dataset is saved in a 1.2 TB of compressed HDF5 file. This dataset can be used in various applications, including building energy and load shape benchmarking, energy model calibration, evaluation of occupant and weather variability and their influences on building performance, algorithm development and testing for thermal and energy load prediction, model predictive control, policy development for reinforcement learning based building controls.

AlphaBuilding↗

DOE OSTI2023

Synthesis and Thermal Oxidation Resistance of Boron-Rich Boron–Carbide Material

A boron-rich boron–carbide material (B4+δC) was synthesized by spark plasma sintering of a ball-milled mixture of high-purity boron powder and graphitic carbon at a pressure of 7 MPa and a temperature of 1930 °C. This high-pressure, high-temperature synthesized material was recovered and characterized by X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy, Vickers hardness measurements, and thermal oxidation studies. The X-ray diffraction studies revealed a single-phase rhombohedral structure (space group R-3m) with lattice parameters in hexagonal representation as a = 5.609 ± 0.007 Å and c = 12.082 ± 0.02 Å. The experimental lattice parameters result in a value of δ = 0.55, or the composition of the synthesized compound as B4.55C. The high-resolution scans of boron binding energy reveal the existence of a B-C bond at 188.5 eV. Raman spectroscopy reveals the existence of a 386 cm−1 vibrational mode representative of C-B-B linear chain formation due to excess boron in the lattice. The measured Vickers microhardness at a load of 200 gf shows a high hardness value of 33.8 ± 2.3 GPa. Thermal gravimetric studies on B4.55C were conducted at a temperature of 1300 °C in a compressed dry air environment, and its behavior is compared to other high-temperature ceramic materials such as high-entropy transition metal boride. The high neutron absorption cross section, high melting point, high mechanical strength, and thermal oxidation resistance make this material ideal for applications in extreme environments.

36 MATERIALS SCIENCE↗

NASA NTRS1974

Comparison of several methods for predicting separation in a compressible turbulent boundary layer

Several methods for predicting the separation point for a compressible turbulent boundary layer were applied to the flow over a bump on a wind-tunnel wall. Measured pressure distributions were used as input. Two integral boundary-layer methods, three finite-difference boundary-layer methods, and three simple methods were applied at five free-stream Mach numbers ranging from 0.354 to 0.7325. Each of the boundary-layer methods failed to explicitly predict separation. However, by relaxing the theoretical separation criteria, several boundary-layer methods were made to yield reasonable separation predictions, but none of the methods accurately predicted the important boundary-layer parameters at separation. Only one of the simple methods consistently predicted separation with reasonable accuracy in a manner consistent with the theory. The other methods either indicated several possible separation locations or only sometimes predicted separation.

Gerhart, P. M.↗

NASA NTRS1984

SSME thrust chamber simulation using Navier-Stokes equations

The capability of the PHOENICS fluid dynamics code in predicting two-dimensional, compressible, and reacting flow in the combustion chamber and nozzle of the space shuttle main engine (SSME) was evaluated. A non-orthogonal body fitted coordinate system was used to represent the nozzle geometry. The Navier-Stokes equations were solved for the entire nozzle with a turbulence model. The wall boundary conditions were calculated based on the wall functions which account for pressure gradients. Results of the demonstration test case reveal all expected features of the transonic nozzle flows. Of particular interest are the locations of normal and barrel shocks, and regions of highest temperature gradients. Calculated performance (global) parameters such as thrust chamber flow rate, thrust, and specific impulse are also in good agreement with available data.

Przekwas, A. J.↗

DOE OSTI2019

Hot Flow Curve Description of CuFe2 Alloy via Different Artificial Neural Network Approaches

In this research, a mathematical description of hot flow curves of CuFe2 copper alloy has been assembled. Experimental flow curves of the investigated alloy were created on the basis of hot compression dataset. This dataset was acquired in the temperature range of 923-1223 K and the strain rate range of 0.1-10 s{sup −1}, with the maximum true strain value of 1.0. The experimental flow curves were described by two artificial neural network approaches. In the first case, a neural network has been created to approximate the experimental flow curves with respect to the true strain, strain rate and temperature. In the second case, a hybrid approach based on the combination of predictive models with neural networks has been utilized. In this case, five neural networks were used to describe parameters of these models in relation to the temperature and strain rate. Results have shown that the hybrid approach allows an accurate description of the experimental data and also provides more reliable prediction.

36 MATERIALS SCIENCE↗

DOE OSTI2020

High-temperature superconductivity in LaH 10

The recent discovery of a high critical temperature $T_c$ in compressed H 3 S has been followed by the prediction of Liu et al. of $T_c$ ≈ 250 K in the clathrate LaH 10 structure. This report has been confirmed experimentally by Somayazulu et al. and Drozdov et al. Additional theoretical work by Wang et al. and Quan et al. further established the mechanism of electron-phonon interaction and the dominant role of hydrogen. In the present Rapid Communication we follow the classic McMillan paper, which separates the electron and phonon contributions to the electron-phonon coupling λ. We first compute the numerator of McMillan's expression, the Hopfield parameter η, using the theory of Gaspari and Gyorffy (GG), and obtain the force constants in the denominator from Wang et al. and Quan et al. The resulting λ is used in the Allen-Dynes equation to calculate $T_c$. The value of $T_c$ reaches a maximum in the range of 236–263 K at pressures of 255 GPa and decreases for smaller or larger pressures. Further, we provide a thorough analysis of the different terms of the GG equation and draw the conclusion that the $\textit{sp}$ channel of the hydrogen is the most important contribution to obtain high values of $T_c$ in this material. Consistent with Wang et al., we find large values of λ that decrease with increasing pressure. In addition, we find that the hydrogen sites are the largest contributors to the total value of the coupling constant λ. That is, the acoustic mode associated with La contributes only 2% to the total λ, while the optic modes associated with H contribute 18% for the H1 site and 80% for the H2 site. These relative contributions to λ are consistent with those given by Wang et al. and by Quan et al. Thus, our results strongly support the view that LaH 10 is a metallic hydrogen superconductor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗