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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Effects of X-rays on Perovskite Solar Cells

Synchrotron micro- and nanoprobe beamlines have demonstrated great potential to advance photovoltaic devices. Most importantly, their small X-ray spot size has enabled the direct correlation of electrical performance with elemental composition at subgrain resolution for a variety of polycrystalline solar cells. Whereas the bulk of most inorganic semiconductors is stable under the high X-ray flux of focused X-ray beams, semiconductors with organic components are prone to a variety of degradation mechanisms. This is particularly critical to evaluate for the emerging organometal halide perovskite solar cells. In this study, we investigate the effects of hard X-rays on the nanoscale performance and elemental distribution of these solar cells. We show that their composition does not change during common operando and in situ measurements at synchrotron nanoprobes. However, we found a significant X-ray-induced electronic degradation of solar cells with methylammonium lead iodide absorbers. Time- and dose-dependent measurements unveiled two characteristic degradation time constants on the order of 12 and 200 s that are independent of the X-ray flux. On the basis of heat and dose simulations, we attribute the fast decay to the dose-driven creation of recombination centers, while the slow decay is compatible with the observation of compositional changes. Finally, we detail how degradation-induced measurement artifacts can be outrun and showcase the high correlation of the X-ray-beam-induced current with the iodine and lead distribution.

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

Mechanocatalytic Ammonia Synthesis over TiN in Transient Microenvironments

Environmentally friendly and energy-efficient ways to produce ammonia are essential to meet global food demands. In this study, a new approach for ammonia production at nominally ambient conditions is introduced. As proof of concept, ammonia is synthesized mechanocatalytically by ball milling titanium in a continuous gas flow. The ammonia synthesis reaction is proposed to follow a transient Mars–van Krevelen mechanism under mechanically activated conditions, where molecular nitrogen incorporation into the titanium lattice and titanium nitride hydrogenation occur in thermodynamically distinct environments. X-ray powder diffraction and X-ray absorption spectroscopy confirm the formation of titanium nitride from titanium and N2. The reactivity of nitrided titanium supports that lattice nitrogen plays a role in ammonia formation. The in situ formed titanium nitride is catalytically active, and the nitride regeneration reaction is determined to be the rate-limiting step. A preliminary technoeconomic analysis shows that this approach could be feasible for distributed ammonia production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Feature learning and generalization in deep networks with orthogonal weights

Fully-connected deep neural networks with weights initialized from independent Gaussian distributions can be tuned to criticality, which prevents the exponential growth or decay of signals propagating through the network. However, such networks still exhibit fluctuations that grow linearly with the depth of the network, which may impair the training of networks with width comparable to depth. We show analytically that rectangular networks with tanh activations and weights initialized from the ensemble of orthogonal matrices have corresponding preactivation fluctuations which are independent of depth, to leading order in inverse width. Moreover, we demonstrate numerically that, at initialization, all correlators involving the neural tangent kernel (NTK) and its descendants at leading order in inverse width—which govern the evolution of observables during training—saturate at a depth of ~20, rather than growing without bound as in the case of Gaussian initializations. We speculate that this structure preserves finite-width feature learning while reducing overall noise, thus improving both generalization and training speed in deep networks with depth comparable to width. We provide some experimental justification by relating empirical measurements of the NTK to the superior performance of deep non-linear orthogonal networks trained under full-batch gradient descent on the MNIST and CIFAR-10 classification tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Improved Verification and Validation Testing and Tools [Slides]

All MCNP team supported V&V test suites are now developed in a separate repository from the MCNP source code within a Python-based framework. This entire framework will be distributed with the upcoming MCNP6.3 release. Most V&V test suites distributed with MCNP6.2 will be distributed in new framework. New V&V test suites are done or being worked on for the MCNP6.3 release.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Verification and validation testing and tools: comparison between MCNP code versions and nuclear data libraries [Slides]

This presentation discusses the primary goal of software testing which is to test the code for correctness. It also discusses the results for individual suites and the role of validation and verification also referred to in the presentation as V&V. In summation, the V&V framework enables easy comparison between calculations performed with different code versions and/or nuclear data libraries. This entire framework will be distributed with the upcoming MCNP6.3 release. V&V test suites shown and several that were not (Criticality, LAQGSM, Lockwood) will be distributed in the new framework.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Investigation of design principles for metal-binding and conductive protein assemblies

Throughout the lifetime of this initiative, including renewals, we focused on understanding the fundamental principles of protein-protein interface design that enable predictable and modular spatial and kinetic control of multi-component protein self-assembly in 1D, 2D, and 3D, including the interface with inorganic materials, small molecules, and metal ions. We designed individual protein components that bind specific metal ions, including REEs and transport ions across lipid membranes. We created helical 1D filaments of repeating units with programmed periodicity, pitch, and multi-component environmentally responsive self-assembling protein fibers. We showed that these filaments reversibly assemble and disassemble under specific pH conditions and created end-specific caps that independently tune the balance of attachment and detachment rates at each terminus of the filament. Using similar filaments, we succeeded in binding arrays of heme and chlorophyll molecules and assembling patterned helical coatings around carbon nanotubes in efforts to create de novo conductive nanowires. By arraying REE binding sites in a large circular tandem array with a repeat protein-based cyclic oligomer, we created a molecular scaffold for superradiance and paramagnetic quantum sensing. We created a range of one-component and two-component self-assembling 2D arrays and showed that when designed to engage cell receptors, these arrays can control cell behavior from outside the cell signal to inside the cell. We designed helical repeat proteins with variable lengths displaying charged residues in a pattern matched to the cation lattice of mica. achieved a range of ordered states with an epitaxial match to the underlying crystal lattice. We further applied the learned principles of protein-induced biomineralization to design proteins with an interface lattice matching CaCO 3 and guide the formation of specific crystal forms of CaCO 3 from solution, a significant advance toward the global need to manage carbon. In all cases of mineral lattice matching and biomineralization, we followed assembly using molecularly resolved in situ AFM imaging and extracted information about assembly pathways and energetics, applying deep learning to quantify the dynamics of protein self-organization. We developed techniques for using dynamic metal-dependent interfaces on protein nanopores for discriminatively sensing dilute REEs in solution and demonstrated the use of strong metal-binding interfaces to drive nanocage disassembly for conditional nanocompartmentalization applications. This grant supported 11 people, including Asim Bera, Evans Brackenbrough, Andrew Borst, Nikita Hanikel, Timothy Huddy, Emily Joyce, Alex Young-Seug Kang, Ryan Kibler, Joshua Morris Lubner, Harley Pyles, and Shuai Zhang. The research effort culminated in the production of published papers and theses. Electronic Thesis/Dissertation are distributed by ProQuest/UMI Dissertation Publishing and made available on an open access basis through UW Libraries ResearchWorks Service.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Four Isotope-Labeled Recombination Pathways of Ozone Formation

A theoretical approach is developed for the description of all possible recombination pathways in the ozone forming reaction, without neglecting any process a priori, and without decoupling the individual pathways one from another. These pathways become physically distinct when a rare isotope of oxygen is introduced, such as 18 O, which represents a sensitive probe of the ozone forming reaction. Each isotopologue of O 3 contains two types of physically distinct entrance channels and two types of physically distinct product wells, creating four recombination pathways. Calculations are done for singly and doubly substituted isotopologues of ozone, eight rate coefficients total. Two pathways for the formation of asymmetric ozone isotopomer exhibit rather different rate coefficients, indicating large isotope effect driven by ΔZPE-difference. Rate coefficient for the formation of symmetric isotopomer of ozone (third pathway) is found to be in between of those two, while the rate of insertion pathway is smaller by two orders of magnitude. These trends are in good agreement with experiments, for both singly and doubly substituted ozone. The total formation rates for asymmetric isotopomers are found to be somewhat larger than those for symmetric isotopomers, but not as much as in the experiment. Altogether, the distribution of lifetimes is found to be very similar for the metastable states in symmetric and asymmetric ozone isotopomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Digital Twin: Visualizing the Future of the Power Grid [Slides]

The energy systems are generating data at a scale and complexity that increasingly outpaces our ability to analyze it. This talk argues that rigorous, large-scale visualization is a critical tool for meeting that challenge. Drawing on recent work in the Computational Science Center at the National Laboratory of the Rockies, we trace a progression of visualization research culminating in an immersive digital twin of a real campus power grid. Along the way, we examine why visualization matters at all, where widely-used techniques quietly fail, and what becomes analytically possible when you match the display environment to the scale of the problem.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Integrating Immersive Visualization in Molten-Salt Reactor Waste Management for Experimental Design and Planning

Molten-salt reactors (MSRs) represent a promising solution for next-generation nuclear energy, offering advantages in safety, fuel efficiency, and waste minimization. However, their liquid-fueled design presents unique challenges for spent fuel management, making post-shutdown waste characterization essential for developing effective strategies. Despite this need, there is a notable absence of visualization platforms specifically tailored to the unique characteristics and analytical requirements of MSR waste management. Existing tools in the nuclear industry are primarily designed for reactor operations or generic data exploration and lack both integration with MSR-specific multiphysics frameworks and the ability to simultaneously visualize time-dependent thermal fields, chemical composition evolution, and radiation distribution patterns. To address these limitations, this paper presents an immersive virtual reality (VR) visualization platform that processes and displays high-fidelity multiphysics simulation output from the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework in real-time, using Unity. The platform visualizes MSR waste characteristics such as nuclide decay, salt cooling, and corrosion by using Exodus II output data and running on a VR headset. It includes a user-friendly interface with features such as visibility toggling, cross-sectional slicing, and time-series animation for exploring simulation data. These capabilities support experimental design, stakeholder engagement, and public communication by making complex reactor behavior more accessible and understandable. By enhancing spatial reasoning and reducing cognitive load, this immersive environment fosters more effective communication and decision-making in MSR waste management.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

A Mechanistic Understanding of Nonclassical Crystal Growth in Hydrothermally Synthesized Sodium Yttrium Fluoride Nanowires

Sodium yttrium fluoride (NaYF 4 ) is an important upconverting material with many potential uses in chemistry, materials science, and biology, which can be synthesized hydrothermally in both cubic (α) and hexagonal (β) crystallographic polymorphs. Understanding the mechanisms underlying the phase conversion between the cubic and hexagonal polymorphs is of great interest to help inform future synthetic efforts, for example in the design of atomically precise quantum materials with well-defined sizes and morphologies. In this work, we use a combination of analytical transmission electron microscopy (TEM), scanning transmission electron microscopy (STEM), powder X-ray diffraction (XRD), in situ liquid cell TEM, atom probe tomography (APT), and extended X-ray absorption fine structure (EXAFS) measurements to show that the hexagonal NaYF 4 nanowires form through a nonclassical crystal growth mechanism involving the formation and subsequent oriented attachment of mesocrystals consisting of cubic (α) phase units. Additionally, EXAFS measurements suggest that substitutional Yb 3+ point defects within NaYF 4 are distributed evenly throughout the crystal lattice without clustering and also that they may exhibit selective substitution into one of the two possible trivalent yttrium sites in the unit cell for hydrothermally synthesized β-NaYF 4 .

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

Distributed heterogeneous compute infrastructure for the study of additive manufacturing systems

We present the current status of a large-scale computing framework to address the need of the multidisciplinary effort to study chemical dynamics. Specifically, we are enabling scientists to process and store experimental data, run large-scale computationally expensive high-fidelity physical simulation, and analyze these results using the state-of-the-art data analytics tools, machine learning, and uncertainty quantification methods using heterogeneous computing resources, such as CPU and GPU cluster. The framework can integrate or abstract out multiple domains based on roles. In order to develop this framework, we have leveraged an existing framework coupled with in-house heterogeneous computing resources. We present the results of using this framework on a single metadata triggered workflow to accelerate an additive manufacturing use case.

heterogeneous computing, hpc, workflows, reproduci↗
DOE OSTI2020

Designing an Epitaxially-Integrated DBR for Dislocation Mitigation in Monolithic GaAsP/Si Tandem Solar Cells

This work explores epitaxially-integrated distributed Bragg reflectors (DBR) as a strategy to mitigate the impact of threading dislocations on the performance of monolithic GaAs 0.75 P 0.25 /Si tandem solar cells. The constraints present due to materials availability and the optical transmission profile of the GaAs 0.75 P 0.25 top cell require the use of an enhanced bandwidth DBR design achieved by combining two narrow-band DBR’s with different central wavelengths. Here, the impact of this DBR structure on JSC, along with the competing effects of threading dislocation density (TDD), are investigated using a robust, experimentally informed analytical model. Implementing this DBR within the GaAs 0.75 P 0.25 /Si tandem cell structure is predicted to yield a short circuit current enhancement equivalent to an ~1.8× reduction in TDD, providing a clear demonstration of its promise as a design methodology for mitigating the impact of non-negligible defect populations.

14 SOLAR ENERGY↗
DOE OSTI2025

Hydrogen Production from Polyethylene Pyrolysis

Hydrogen is anticipated to play a pivotal role in the future of clean energy and decarbonization efforts, serving as an energy storage medium, a power generation source, and a clean fuel for transportation. While most hydrogen is produced from carbonaceous fossil feedstocks like natural gas, petroleum, and coal, there is growing interest in using refuse-derived fuels such as waste plastics and municipal solid waste (MSW) as alternative feedstocks. Thermochemical processes such as pyrolysis and catalytic cracking can convert nonrecyclable plastics and organic MSW components to produce hydrogen with lower life cycle greenhouse gas emissions when coupled with CO 2 capture. Such approaches not only address waste-management challenges but also reduce methane emissions from landfills. Furthermore, waste feedstocks are low cost and can support meeting demands for hydrogen across various industries. In this work we examined production of hydrogen from high-density polyethylene (HDPE) as a model polymer using pyrolysis. Analytical studies of pyrolysis utilizing gas chromatography–mass spectrometry (GC/MS) provide insights into conversion pathways for plastic waste, potentially reducing the environmental footprint of traditional hydrogen production methods. This work generates a baseline methodology for hydrogen production from plastic pyrolysis with and without a catalyst and the necessary product distribution baseline from key single plastics. The effect of pyrolysis temperature on the conversion of HDPE was evaluated both with and without a catalyst(s), and the product distributions measured via GC/MS were identified and hydrogen formation was quantified. These results will help guide future research efforts to optimize catalysts and processes for more efficient hydrogen production and mixed plastic waste management.

Catalysts↗
DOE OSTI2023

Thermal conductivity of a laser plasma

Here, we present a model of the electron thermal conductivity of a laser-produced plasma. The model, supported by Vlasov–Fokker–Planck simulations, predicts that laser absorption reduces conductivity by forcing electrons out of a Maxwell–Boltzmann equilibrium, which results in depletion of both low-velocity bulk electrons and high-velocity tail electrons. We show that both the bulk and tail electrons approximately follow super-Gaussian distributions, but with distinct exponents that each depend on the laser intensity and wavelength through the parameter a = Zv$^{2}_{E}$/v$^{2}_{T}$. For a value of a = 0.5, tail depletion reduces the thermal conductivity to half its zero-intensity value. We present our results as simple analytic fits that can be readily implemented in any radiation-hydrodynamics code or used to correct the local limit of non-local conduction models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Nickel-incorporated Oxide Composites for Fiber-Optic Based Gas Sensing

Numerous high-value applications within the energy sector involve environmental conditions that are incompatible with traditional sensor technology due to degradation of electrical interconnects, packaging, or the sensors themselves. These can include chemically harsh conditions, high temperature operation, or the presence of electromagnetic interference due to high voltage. The fiber optic platform, constructed of robust, electrically insulating glass or single crystal oxides, offers a versatile and often low cost per node solution to this problem, especially with the integration of distributed sensing techniques such as optical time-domain and frequency-domain reflectometry (OTDR, OFDR). A major challenge of gas and chemical sensing on the optical fiber platform is the fabrication of robust and stable sensing materials that interact quickly and reversibly to the presence of the target analytes. In this work, we discuss the utilization of nickel-incorporated oxides on evanescent-field optical fiber sensors for gas sensing under harsh conditions relevant to multiple energy infrastructure applications. This paper will discuss a Ni/GDC (Ni / Gd-doped ceria) based sensing layer targeting conditions relevant for high-temperature (up to at least 800 oC) hydrogen sensing applications (e.g., for operation within a solid oxide fuel cell or electrolyzer). The impact of hydrogen at elevated temperatures on the optical properties of Ni/GDC will be shown and the material mechanisms for the optical response will be discussed.

gas sensors↗
DOE OSTI2025

Nickel-incorporated Oxide Composites for Fiber-Optic Based Gas Sensing

Numerous high-value applications within the energy sector involve environmental conditions that are incompatible with traditional sensor technology due to degradation of electrical interconnects, packaging, or the sensors themselves. These can include chemically harsh conditions, high temperature operation, or the presence of electromagnetic interference due to high voltage. The fiber optic platform, constructed of robust, electrically insulating glass or single crystal oxides, offers a versatile and often low cost per node solution to this problem, especially with the integration of distributed sensing techniques such as optical time-domain and frequency-domain reflectometry (OTDR, OFDR). A major challenge of gas and chemical sensing on the optical fiber platform is the fabrication of robust and stable sensing materials that interact quickly and reversibly to the presence of the target analytes. In this work, we discuss the utilization of nickel-incorporated oxides on evanescent-field optical fiber sensors for gas sensing under harsh conditions relevant to multiple energy infrastructure applications. This paper will discuss a Ni/GDC (Ni / Gd-doped ceria) based sensing layer targeting conditions relevant for high-temperature (up to at least 800oC) hydrogen sensing applications (e.g., for operation within a solid oxide fuel cell or electrolyzer). The impact of hydrogen at elevated temperatures on the optical properties of Ni/GDC will be shown and the material mechanisms for the optical response will be discussed.

gas sensors↗