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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 955 records · Page 53

Tuning Hole Transport Layer Using Urea for High-Performance Perovskite Solar Cells

Interface engineering is critical to the development of highly efficient perovskite solar cells. Here, urea treatment of hole transport layer (e.g., poly(3,4-ethylene dioxythiophene):polystyrene sulfonate (PEDOT:PSS)) is reported to effectively tune its morphology, conductivity, and work function for improving the efficiency and stability of inverted MAPbI 3 perovskite solar cells (PSCs). This treatment has significantly increased MAPbI 3 photovoltaic performance to 18.8% for the urea treated PEDOT:PSS PSCs from 14.4% for pristine PEDOT:PSS devices. The use of urea controls phase separation between PEDOT and PSS segments, leading to the formation of a unique fiber-shaped PEDOT:PSS film morphology with well-organized charge transport pathways for improved conductivity from 0.2 S cm -1 for pristine PEDOT:PSS to 12.75 S cm -1 for 5 wt% urea treated PEDOT:PSS. The urea-treatment also addresses a general challenge associated with the acidic nature of PEDOT:PSS, leading to a much improved ambient stability of PSCs. Additionally, the device hysteresis is significantly minimized by optimizing the urea content in the treatment.

14 SOLAR ENERGY↗

Hypersonic Jets of Detonation Products in the Hydrodynamic Collapse of Macroscopic Voids

Localizing the energetic output from detonation waves has been a long-standing challenge in applied detonation physics. Here, energy localization is achieved via machined millimeter scale voids in pressed samples of PBX 9501, an HMX (1,3,5,7-Tetranitro-1,3,5,7-tetrazocane)-based plastic bonded explosive. A main mechanism of energy localization in these systems, the formation of hydrodynamic jets of dense product gases, is characterized experimentally using a semicylindrical geometry in witness plate impact experiments and streak imaging of the jet propagating into the air. The distance at which the jet is optimally developed is identified and the supersonic flow structure in the vicinity of this feature is explored using hydrocode simulations. This analysis found that most of the kinetic energy of the hydrodynamic jet arises from pressure gradients induced by geometrically mediated squeeze flow lateral to the direction of detonation propagation. This work presents a new development in the control of energetic output from detonation waves and applications to detonation wave shaping are discussed.

42 ENGINEERING↗

Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers

Abstract This work presents the PORTALS framework (Rodriguez-Fernandez et al 2022 Nucl. Fusion 62 076036), which leverages surrogate modeling and optimization techniques to enable the prediction of core plasma profiles and performance with nonlinear gyrokinetic simulations at significantly reduced cost, with no loss of accuracy. The efficiency of PORTALS is benchmarked against standard methods, and its full potential is demonstrated on a unique, simultaneous 5-channel (electron temperature, ion temperature, electron density, impurity density and angular rotation) prediction of steady-state profiles in a DIII-D ITER Similar Shape plasma with GPU-accelerated, nonlinear CGYRO (Candy et al 2016 J. Comput. Phys. 324 73–93). This paper also provides general guidelines for accurate performance predictions in burning plasmas and the impact of transport modeling in fusion pilot plants studies.

Physics↗

Pt 8 cluster on alumina under a pressure of hydrogen: Support-dependent reconstruction from first-principles global optimization

Alumina supported Pt nano clusters under hydrogen environment play a crucial role for many heterogeneous catalysis applications. As such, we conducted grand canonical genetic algorithm (GCGA) simulations for supported Pt 8 clusters in hydrogen gas environment to study the intra-cluster, cluster-support, and cluster-adsorbate interactions. Two alumina surfaces, α-Al 2 O 3 (0001) and $γ$-Al 2 O 3 (100), and two conditions T=600°C, p H2 = 0.1bar and T=25°C, p H2 = 1.0 bar were considered corresponding to low and high hydrogen chemical potential $μ$ H , respectively. The low free energy ensemble of Pt 8 is decorated by a medium (2–12 H), resp. high (20–30 H), number of hydrogen atoms under equilibrium at low $μ$ H , respectively, high $μ$ H , and undergoes different morphology transformations on the two surfaces. On α-Al2O3(0001), Pt8 is mostly 3D but very fluxional in structure at low μH and converts to open one-layer 2D structures with minimal fluxionality at high μH, whereas on $γ$-Al 2 O 3 (100), the exact opposite occurs, and Pt 8 clusters present one-layer 2D shapes at low $μ$ H and switch into compact 3D shapes under high $μ$ H , during which the Pt 8 cluster preserves moderate fluxionality. Further analysis reveals similar Pt–Pt bond length increase when switching from low $μ$ H to high $μ$ H on both surfaces, though morphology transformations are different. Electronic structure analysis shows the existence of bonding interactions between Pt and Lewis acidic Al 3+ sites along with the Pt – O interaction, which implies the necessity to include Al neighbors to discuss the electronic structure of small Pt clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Parallel physics-informed neural networks via domain decomposition

Here we develop a distributed framework for the physics-informed neural networks (PINNs) based on two recent extensions, namely conservative PINNs (cPINNs) and extended PINNs (XPINNs), which employ domain decomposition in space and in time-space, respectively. This domain decomposition endows cPINNs and XPINNs with several advantages over the vanilla PINNs, such as parallelization capacity, large representation capacity, efficient hyperparameter tuning, and is particularly effective for multi-scale and multi-physics problems. Here, we present a parallel algorithm for cPINNs and XPINNs constructed with a hybrid programming model described by MPI + X, where X ∈ {CPUs, GPUs}. The main advantage of cPINN and XPINN over the more classical data and model parallel approaches is the flexibility of optimizing all hyperparameters of each neural network separately in each subdomain. We compare the performance of distributed cPINNs and XPINNs for various forward problems, using both weak and strong scalings. Our results indicate that for space domain decomposition, cPINNs are more efficient in terms of communication cost but XPINNs provide greater flexibility as they can also handle time-domain decomposition for any differential equations, and can deal with any arbitrarily shaped complex subdomains. To this end, we also present an application of the parallel XPINN method for solving an inverse diffusion problem with variable conductivity on the United States map, using ten regions as subdomains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optimization of a high-yield, low-areal-density fusion product source at the National Ignition Facility with applications in nucleosynthesis experiments

Polar-direct-drive exploding pushers are used as a high-yield, low-areal-density fusion product source at the National Ignition Facility with applications including diagnostic calibration, nuclear security, backlighting, electron-ion equilibration, and nucleosynthesis-relevant experiments. In this paper, two different paths to improving the performance of this platform are explored: (i) optimizing the laser drive, and (ii) optimizing the target. While the present study is specifically geared towards nucleosynthesis experiments, the results are generally applicable. Example data from T 2 / 3 He-gas-filled implosions with trace deuterium are used to show that yield and ion temperature (Tion) from 1.6 mm-outer-diameter thin-glass-shell capsule implosions are improved at a set laser energy by switching from a ramped to a square laser pulse shape, and that increased laser energy further improves yield and Tion, although by factors lower than predicted by 1 D simulations. Using data from D2-3He-gas-filled implosions, yield at a set Tion is experimentally verified to increase with capsule size. Uniform D-3He-proton spectra from 3 mm-outer-diameter CH shell implosions demonstrate the utility of this platform for studying charged-particle-producing reactions relevant to stellar nucleosynthesis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Correcting the PFNS for more consistent fission modeling

For FY20, we had a deliverable to write a report detailing efforts to simultaneously evaluate both the prompt neutron multiplicity, $\overline{ν}$, and the prompt neutron fission neutron spectrum, PFNS, using CGMF. CGMF is the LANL-developed fission fragment decay code that consistently evaporates prompt neutrons and γ rays using the Hauser-Feshbach statistical theory of compound reactions. The decay begins by constructing the initial conditions of the fission fragments, then decaying each one from the excited state by neutrons and γ rays, conserving energy, momentum, spin, and parity in each step of the emission. The initial conditions of the fragments, along with the multiplicity, energy, and direction of each emitted neutron or γ ray, are recorded, allowing for the full reconstruction of the fission event. These event histories allow us to reconstruct average quantities, as well as correlations between observables, that can be compared with experimental or evaluated data. In that initial report, although there was already a favorable comparison between $\overline{ν}$ from CGMF, experiment, and the current ENDF/B-VIII.0 evaluation, we showed that there was still significant work to be done to improve the PFNS from CGMF. Historically, the PFNS is calculated too soft by Hauser-Feshbach fission models, and CGMF is no exception. The incorrect shape presents a significant challenge in fission modeling, including for our understanding of the fission process and for our ability to consistently calculate and predict a variety of prompt fission observables (such as fission fragment initial conditions, neutron and γ-ray multiplicities and energies, and the correlations between all observables). In our companion report, we detail our success in using CGMF to evaluate $\overline{ν}$. Although not included in the optimization explicitly, we also keep the initial conditions of the fission fragments physical, along with reproducing reasonably well the neutron multiplicity distribution. As we would expect from the sensitivities calculations from, the average neutron energies change very little from the $\overline{ν}$ optimization along with the PFNS (as will be shown in Sec. 2.6). The conclusion was that the global and statistical models would have to be investigated instead of just the fission fragment initial conditions (as is sufficient for $\overline{ν}$). This report details those efforts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Efficient Automated Driving Strategies Leveraging Anticipation and Optimal Control

Automated vehicles and advanced driver assistance systems bring computation, sensing, and communication technologies that exceed human abilities in some ways. For example, automated vehicles may sense a panorama all at once, do not suffer from human impairments and distractions, and could wirelessly communicate precise data with neighboring vehicles. Prototype and commercial deployments have demonstrated the capability to relieve human operators of some driving tasks up to and including fully autonomous taxi rides in some areas. The ultimate impact of this technology’s large-scale market penetration on energy efficiency remains unclear, with potential negative factors like road use by empty vehicles competing with positive ones like automatic eco-driving. Fundamentally enabled by historic and look-ahead data, this dissertation addresses the use of automated driving and driver assistance to optimize vehicle motion for energy efficiency. Facets of this problem include car following, co-optimized acceleration and lane change planning, and collaborative multi-agent guidance. Optimal control, especially model predictive control, is used extensively to improve energy efficiency while maintaining safe and timely driving via constraints. Techniques including chance constraints and mixed integer programming help overcome uncertainty and non-convexity challenges. Extensions of these techniques to tractor trailers on sloping roads are provided by making use of linear parameter-varying models. To approach the wheel-input energy eco-driving problem over generally shaped sloping roads with the computational potential for closed-loop implementation, a linear programming formulation is constructed. Distributed and collaborative techniques that enable connected and automated vehicles to accommodate their neighbors in traffic are also explored and compared to centralized control. Using simulations and vehicle-in-the-loop car following experiments, the proposed algorithms are benchmarked against others that do not make use of look-ahead information.

Dollar, Robert Austin↗

Custom-form iron trifluoride Li-batteries using material extrusion and electrolyte exchanged ionogels

Custom-form factor batteries fabricated in non-conventional shapes can maximize the overall energy density of the systems they power, particularly when used in conjunction with energy dense materials (e.g., Li metal anodes and conversion cathodes). Additive manufacturing (AM), and specifically material extrusion (ME), have been shown as effective methods for producing custom-form cell components, particularly electrodes. However, the AM of several promising energy dense materials (conversion electrodes such as iron trifluoride) have yet to be demonstrated or optimized. Furthermore, the integration of multiple AM produced cell components, such as electrodes and separators, along with a custom package remains largely unexplored. In this work, iron trifluoride (FeF 3 ) and ionogel (IG) separators are conformally printed using ME onto non-planar surfaces to enable the fabrication of custom-form Li-FeF 3 batteries. Further, to demonstrate printing on non-planar surfaces, cathodes and separators were deposited onto cylindrical rods using a 5-axis ME printer. ME printed FeF 3 was shown to have performance commensurate with FeF 3 cast using conventional means, both in coin cell and cylindrical rod formats, with capacities exceeding 700 mAh/g on the first cycle and ranging between 600 and 400 mAh/g over the next 50 cycles. Additionally, a ME process for printing polyvinylidene fluoride-co-hexafluoropropylene (PVDF-HFP) based IGs directly onto FeF 3 is developed and enabled using an electrolyte exchange process. In coin cells, this process is shown to produce cells with similar capacity to cells built with Celgard separators out to 50 cycles, with the exception that cycling instabilities are observed during cycles 8–20. When using printed and exchanged IGs in a custom cylindrical cell package, 6 stable high-capacity cycles are achieved. Overall, this work demonstrates approaches for producing high-energy-density Li-FeF 3 cells in coin and cylindrical rod formats, which are translatable to customized, arbitrary geometries compatible with ME printing and electrolyte exchange.

25 ENERGY STORAGE↗

An improved guess for the variational calculation of charge-transfer excitations in large systems

Ab initio quantum-chemical methods that perform well for computing the electronic ground state are not straightforwardly transferable to electronically excited states, particularly in large molecular systems. Wave function theory offers high accuracy, but is often prohibitively expensive. Methods based on time-dependent density functional theory (TD-DFT) are crucially sensitive to the chosen exchange-correlation functional (XCF) parameterization, and system-specific tuning protocols were therefore proposed to address the method's robustness. Methods based on the variational relaxation of the excited-state electron density showcased promising results for the calculation of charge-transfer excitations, but the complex shape of the electronic hypersurface makes convergence to a specific excited state much more difficult than for the ground state when standard variational techniques are applied. We address the latter aspect by providing suitable initial guesses, which we obtain by two separate constrained algorithms. Combined with the squared-gradient minimization algorithm for all-electrons relaxation in a freeze-and-release scheme (FRZ-SGM), we demonstrate that orbital-optimized density functional theory (OO-DFT) calculations can reliably converge to the charge-transfer states of interest even for large molecular systems. We test the FRZ-SGM method on a phenothiazine-anthraquinone CT excitation in a supramolecular Pd(II) coordination cage complex as a function of the cage conformation. This compound has been studied experimentally prior to our work. We compare this freeze-and-release scheme to two XCF reparameterizations, which were recently proposed as low-cost TD-DFT-based alternatives to variational methods. Two dye-semiconductor complexes, which were previously investigated in the context of photovoltaic applications, serve as a second example to investigate the convergence and stability of the FRZ-SGM approach. Our results demonstrate that FRZ-SGM provides reliable convergence for charge-transfer excited states and avoids variational collapse to lower-lying electronic states, whereas time-dependent DFT calculations with an adequate tuning procedure for the range-separation parameter provide a computationally efficient initial estimate of the corresponding energies, with a computational cost comparable to that of configuration-interaction singles (CIS) calculations.

Bogo, Nicola↗

Optimal and robust reconstruction of BAO, redshift-space distortions and the Alcock-Paczynski effect

The goal of this project is to optimally reconstruct cosmological information that has been lost from large-scale clustering of galaxies due to cosmic structure growth. The outcome of our research will be used to improve dark energy and other cosmological constraints from the ongoing extended Baryon Oscillation Spectroscopic Survey (eBOSS) and the upcoming Dark Energy Spectroscopic Instrument (DESI). The large-scale galaxy clustering data contain two important features: the Baryon Acoustic Oscillations (BAO) and the overall shape from small to large scales.

79 ASTRONOMY AND ASTROPHYSICS↗

Optimization of a Lithium Ion Battery Bioleaching Process Utilizing Organic Acids Produced by Gluconobacter oxydans

Growing our global economic and environmental focus relies, in part, on our development of a sustainable system to recycle valuable metals. This endeavor to recycle these elements falls within the scope of Idaho National Laboratories (INL) mission to pursue new sustainable energy systems that are competitive. To succeed in this endeavor in not only a low-cost but environmentally safe practice, Gluconobacter oxydans was utilized for its ability to produce a bio-lixiviant known for its critical material leaching abilities. G. oxydans is a rod-shaped, gram negative, acidophilic, and obligately aerobic organism. Unlike many other aerobic organisms, it does not completely oxidize its carbon sources to water and carbon dioxide. Instead it incompletely oxidizes its substrates to aldehydes, ketones and organic acids. Because of this metabolic pathway, it was utilized in a batch reactor setting to produce sufficient amounts of a low-pH bio-lixiviant so that leaching processes could be performed on lithium ion battery cathode powders. Some of these processes included adding different molar ratios of a redox agent to the produced bio-lixiviant, alternating concentrations of lithium ion battery cathode powders, varying leaching time, and changing the temperature each leach was performed at. From this, a biohydrometallurgy process was successfully created for the leaching of cobalt from lithium ion cathode powders This project provided a multitude of laboratory and research experiences that resulted in ample opportunity for professional and personal growth. In addition to this, the INL experience fostered the development of many personal skills and business skills to assist in future career opportunities.

25 ENERGY STORAGE↗

Microstructure Optimization and Novel Processing Development of ODS Steels for Fusion Environments (Final ARPA-E Report)

This project aimed to develop scalable, cost-effective fabrication of high-performance, oxide- dispersion-strengthened (ODS) steel using advanced manufacturing methods (AMMs) for fusion blanket-breeding applications. Gas atomization reaction synthesis (GARS) enables the synthesis of precursor ODS steel powders without prolonged mechanical alloying. This process creates a chromium (Cr)-enriched surface oxide with yttrium/titanium (Y/Ti)-enriched intermetallics in powder interiors. GARS powders were consolidated to >99% of the theoretical density using a first-of-a-kind shear assisted processing and extrusion (ShAPE) and laser-based powder bed fusion (L-PBF) AM processes. These processes led to ODS steels containing a high-density of nano-oxide dispersoids that enhance high-temperature mechanical properties. Such scalable, cost-effective fabrication of ODS steels can enable efficient power conversion cycles (=40%) at operating temperatures beyond 900 K in future fusion power plants.

36 MATERIALS SCIENCE↗

Additive manufacturing of complexly shaped SiC with high density via extrusion-based technique – Effects of slurry thixotropic behavior and 3D printing parameters

Here, additive manufacturing of dense SiC parts was achieved via an extrusion-based process followed by electrical-field assisted pressure-less sintering. The aim of this research was to study the effect of the rheological behavior of SiC slurry on the printing process and quality, as well as the influence of 3D printing parameters on the dimensions of the extruded filament, which are directly related to the printing precision and quality. Different solid contents and dispersant- Darvan 821A concentrations were studied to optimize the viscosity, thixotropy and sedimentation rate of the slurry. The optimal slurry was composed of 77.5 wt% SiC, Y 2 O 3 and Al 2 O 3 powders, 0.25 wt% dispersant and 0.01 wt% defoamer. The printing parameters studied included extrusion pressure, nozzle size, layer height and printing speed; the one that had the most prominent effect on filament width and height was indicated as layer height. The nozzle inner diameter of 1.04 mm, speed of 350 mm/min, layer height of 0.7 mm and extrusion air pressure of 0.31 MPa were the optimal printing parameters. Furthermore, the relationship between the printing parameters and the filament dimensions was successfully predicted by using machine learning and grey system theory. Finally, the relative density of the printed SiC parts sintered at 1900 oC reached 94.7±1.5%.

36 MATERIALS SCIENCE↗

DIII-D research advancing the physics basis for optimizing the tokamak approach to fusion energy

DIII-D physics research addresses critical challenges for the operation of ITER and the next generation of fusion energy devices. This is done through a focus on innovations to provide solutions for high performance long pulse operation, coupled with fundamental plasma physics understanding and model validation, to drive scenario development by integrating high performance core and boundary plasmas. Substantial increases in off-axis current drive efficiency from an innovative top launch system for EC power, and in pressure broadening for Alfven eigenmode control from a co-/counter-I p steerable off-axis neutral beam, all improve the prospects for optimization of future long pulse/steady state high performance tokamak operation. Fundamental studies into the modes that drive the evolution of the pedestal pressure profile and electron vs ion heat flux validate predictive models of pedestal recovery after ELMs. Understanding the physics mechanisms of ELM control and density pumpout by 3D magnetic perturbation fields leads to confident predictions for ITER and future devices. Validated modeling of high-Z shattered pellet injection for disruption mitigation, runaway electron dissipation, and techniques for disruption prediction and avoidance including machine learning, give confidence in handling disruptivity for future devices. For the non-nuclear phase of ITER, two actuators are identified to lower the L–H threshold power in hydrogen plasmas. With this physics understanding and suite of capabilities, a high poloidal beta optimized-core scenario with an internal transport barrier that projects nearly to Q = 10 in ITER at ~8 MA was coupled to a detached divertor, and a near super H-mode optimized-pedestal scenario with co-I p beam injection was coupled to a radiative divertor. The hybrid core scenario was achieved directly, without the need for anomalous current diffusion, using off-axis current drive actuators. Also, a controller to assess proximity to stability limits and regulate β N in the ITER baseline scenario, based on plasma response to probing 3D fields, was demonstrated. Finally, innovative tokamak operation using a negative triangularity shape showed many attractive features for future pilot plant operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Tangential System of Thomson Scattering for Tokamak T-15

Two systems of Thomson scattering diagnostics, with vertical and tangential probing, are used in the D-shaped plasma cross section in tokamak T-15. The tangential system allows measuring plasma temperature and density profiles along the major radius of the tokamak. This paper presents the tangential system project. The system is based on a Nd:YAG laser with wavelength of 1064 nm, pulse energy of 3 J, pulse duration of 10 ns, and repetition rate of 100 Hz. The chosen geometry allows collecting light from ten uniformly spaced points. Optimization of the registration system has been accomplished. The collected light will be transmitted through an optical fiber bundle with diameter of 3 mm and quartz fibers (numerical aperture is 0.22). Six-channel polychromators based on high-contrast interference filters have been chosen as spectral equipment. The radiation will be registered by avalanche photodiodes. The technique of electron temperature and density measurement is described, and estimation of its accuracy is carried out. The proposed system allows measuring the electron temperature with accuracy not worse than 10% within the range of 50 eV to 10 keV on the pinch edge over the internal contour, from 20 eV to 9 keV in the plasma central region, and from 2 eV to 400 eV on the pinch edge over the outer contour. The estimation is made for electron density of not less than 2.6 × 10{sup 13} cm{sup –3}.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Deducing subnanometer cluster size and shape distributions of heterogeneous supported catalysts

Abstract Infrared (IR) spectra of adsorbate vibrational modes are sensitive to adsorbate/metal interactions, accurate, and easily obtainable in-situ or operando. While they are the gold standards for characterizing single-crystals and large nanoparticles, analogous spectra for highly dispersed heterogeneous catalysts consisting of single-atoms and ultra-small clusters are lacking. Here, we combine data-based approaches with physics-driven surrogate models to generate synthetic IR spectra from first-principles. We bypass the vast combinatorial space of clusters by determining viable, low-energy structures using machine-learned Hamiltonians, genetic algorithm optimization, and grand canonical Monte Carlo calculations. We obtain first-principles vibrations on this tractable ensemble and generate single-cluster primary spectra analogous to pure component gas-phase IR spectra. With such spectra as standards, we predict cluster size distributions from computational and experimental data, demonstrated in the case of CO adsorption on Pd/CeO 2 (111) catalysts, and quantify uncertainty using Bayesian Inference. We discuss extensions for characterizing complex materials towards closing the materials gap.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Magnetic properties and crystallization kinetics of (Fe 100–x Ni x ) 80 Nb 4 Si 2 B 14 metal amorphous nanocomposites

Fe-Ni based metal amorphous nanocomposites (MANCs) are investigated in the pseudo-binary alloys (Fe 100–x Ni x ) 80 Nb 4 Si 2 B 14 . To optimize the soft magnetic properties of the nanocomposites, primary and secondary crystallization kinetics must be understood. As such, primary and secondary crystallization temperatures are determined by differential scanning calorimetry, and activation energies are calculated, along with the resulting crystalline phases. Time-temperature-transformation diagrams for primary and secondary crystallization in (Fe 70 Ni 30 ) 80 Nb 4 Si 2 B 14 are presented. Saturation magnetization and Curie temperature are determined. In conclusion, the shape of magnetization vs. time curves for (Fe 30 Ni 70 ) 80 Nb 4 Si 2 B 14 at various temperatures suggest that the secondary crystal product often consumes some of the primary crystalline product.

36 MATERIALS SCIENCE↗