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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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A non-aqueous redox flow battery includes a catholyte including a compound of formula (I): wherein E1 and E2 are independently O, S, S═O, S(═O)2, Se, NR11, or PR11; The compounds of the present technology are capable of undergoing a reversible two-electron transfer process, thus leading to high efficiency of molecular design and an increase in the overall energy density.
Methods for assessing fiber and bundle orientations and mechanical properties of fiber reinforced composite materials using Thermal Digital Image Correlation (TDIC) are disclosed. In some examples, the method comprises exposing the composite material to a temperature change; imaging the composite material at a plurality of time points before, during and/or after the temperature change; and assessing the characteristic of the composite material based on the imaging. In others, temperature changes naturally occur during the cooling process after manufacturing can be employed for this method such as compression molding process, injection molding process, resin transfer molding processes and its variants.
A mesoporous, nanocrystalline, metal oxide construct particularly suited for capacitive energy storage that has an architecture with short diffusion path lengths and large surface areas and a method for production are provided. Energy density is substantially increased without compromising the capacitive charge storage kinetics and electrode demonstrates long term cycling stability. Charge storage devices with electrodes using the construct can use three different charge storage mechanisms immersed in an electrolyte: (1) cations can be stored in a thin double layer at the electrode/electrolyte interface (non-faradaic mechanism); (2) cations can interact with the bulk of an electroactive material which then undergoes a redox reaction or phase change, as in conventional batteries (faradaic mechanism); or (3) cations can electrochemically adsorb onto the surface of a material through charge transfer processes (faradaic mechanism).
Recently, there has been renewed interest in the Molten Salt Reactor (MSR) concept. This interest is mainly due to its advantages over Light Water Reactors (LWRs). Among these advantages are the flexibility in the fuel choice and the possibility to burn actinides [1]. Currently, two molten research reactors are under development. A 2 MW molten salt experimental reactor has been constructed and is planned for operation in China. A 1 MW Molten Salt Research Reactor is under construction in the United States [2]. Thus, Research and Development (R&D) programs are needed for the MSR technology. Reactor dynamics studies are crucial safety evaluation studies. The development of reactor dynamics tools for MSRs started during the Molten Salt Reactor Program (MSRP) at ORNL, focusing on the Molten Salt Reactor Experiment (MSRE) [3]. Although various dynamic simulation tools are available, R&D efforts to develop specialized tools for MSRs are still ongoing [4]. The primary motivation for this interest is the goal of commercializing MSRs. Developing a dynamics tool for MSRs is crucial for analyzing their safety and supporting their demonstration efforts. A crucial safety issue in MSRs is ensuring that the fuel salt in the primary loop remains molten. This concern becomes particularly important when the reactor operates at lower power levels. Most chloride and fluoride salts used as fuel have a melting point of approximately 450 °C [5]. Therefore, maintaining fuel salt temperatures above this melting point is essential to prevent it from freezing. Freezing of the fuel salt can lead to volume expansion, potentially causing damage to reactor components [6]. Moreover, it can create local blockages within fuel salt channels, reducing cooling efficiency and resulting in hot spots [7]. Various methods can prevent fuel salt from freezing at low power levels. These include reducing the fuel mass flow rate in the primary loop, decreasing heat exchange between the primary and secondary loops in the reactor, and using electric fuel salt heaters. Reducing the mass flow rate of fuel salt in the primary loop can increase the fuel salt transit time in the core, enhancing heat production and increasing temperature. However, it can potentially lead to challenges. These include increasing the potential for fuel salt deposition on the reactor channel walls [8], affecting the overall heat transfer processes. Thus, alternative methods should be used [9]. This research investigates the effects of fuel salt heaters on the dynamics and stability during MSR operation. The investigation includes studying the reactor stability with the fuel salt heaters on and off. In addition, the reactor response to transients is compared with and without the operation of fuel salt heaters. These transients include reactivity insertion, primary and secondary pump failure, and heat sink temperature increase. The results of the reactivity insertion transient are presented in the summary.
The goal of this research program is to establish the mechanism governing local grain boundary motion, which is needed to design and process desirable microstructures for better performance, by identifying the relative contributions of grain boundary (GB) energy and mobility to grain growth. Classical models for grain growth assume that the primary mechanism for reducing the total interfacial energy is area reduction and that GB restructuring is not significant. This assumption implies that grain growth is locally driven by curvature. However, recent experimental observations using new non-destructive 3D x-ray diffraction microscopy techniques (3D-XRM) reveal that classic descriptors (i.e., curvature, number of neighbors, grain size) do not predict real grain growth. Instead, local GB motion appears to be governed by its energy relative to its neighbors such that low-energy boundaries replace those of higher energy. However, simulations that incorporate GB energy anisotropy still fail to reproduce these observations. These discrepancies suggest that the common assumption for grain growth theory must be re-examined to predict and, thus, control microstructure evolution in real polycrystals. A significant challenge to testing this assumption is due to anisotropic GB mobility. Mobility may cause abnormal grain growth or affect the final grain shapes or growth rate but its true contributions are unknown because it is difficult to measure. For example, observations in Fe have found that grains associated with high energy and high mobility boundaries tend to experience abnormal grain growth, whereas abnormal grain growth is associated with low energy and high mobility boundaries in alumina. As mobility and energy both control GB motion, it is challenging to isolate the local driving forces necessary to test the common assumption that the primary mechanism is area reduction. The novelty of this work is the use of machine learning tools to capture GB mobility and energy from 3D-XRM measurements in polycrystals to test the common assumption used in grain growth models. Machine learning can capture high-order correlations in dynamic systems like those found in the evolving GB topology. The PIs have developed a physics-regularized interpretable machine learning microstructure evolution (PRIMME) model that accurately replicates the grain growth behavior of its trained data set.
Excitation energy transfer (EET) is a key photoinduced process in biological chromophoric assemblies. Here we investigate the factors which can drive EET into efficient ultrafast sub-ps regimes. We demonstrate how a coherent transport of electronic population could facilitate this in water solvated NADH coenzyme and uncover the role of an intermediate dark charge-transfer state. High temporal resolution ultrafast optical spectroscopy gives a 54 ± 11 fs time constant for the EET process. Nonadiabatic quantum dynamical simulations computed through the time-evolution of multidimensional wavepackets suggest that the population transfer is mediated by photoexcited molecular vibrations due to strong coupling between the electronic states. The polar aqueous solvent environment leads to the active participation of a dark charge transfer state, accelerating the vibronically coherent EET process in favorably stacked conformers and solvent cavities. Our work demonstrates how the interplay of structural and environmental factors leads to diverse pathways for the EET process in flexible heterodimers and provides general insights relevant for coherent EET processes in stacked multichromophoric aggregates like DNA strands.
SolVap_StarTer is an open-source solvent evaporation GUI. The software combines previously published (peer-reviewed scientific journals) evaporation and crystallization physics into an easy-to-use graphical interface. The software will allow the user to specify a coating composition and drying environment, and then predict the evolution of the film as it dries. Potential applications include tracking the change in multi-solvent composition and solute concentration in solution-processed perovskites films, predicting the point of crystallization, and calculating equivalent processing parameters for transferring a process between different coating and drying methods. Github repo: https://github.com/NatLabRockies/SolVap Streamlit app: https://solvap.streamlit.app/
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Wire arc additive manufacturing (AM) is the process by which a large, metallic structure is built layer-by-layer using a welding arc to melt a wire feedstock. A novel opportunity exists to alter the shielding gas composition to fabricate distinct geometrical features without altering the other AM parameters. In this paper, shielding gases with varied concentrations of Argon (Ar) and CO 2 was used to deposit three distinct geometric shapes (walls, infill, and overhang) using a wire-based additive manufacturing system utilizing the gas metal arc welding (GMAW) surface tension transfer (STT) process. Computer-aided design (CAD) models were sliced with a custom-built slicer, and the sliced algorithm was converted into optimal robotic toolpaths. A custom virtual instrument (VI) was built in LabVIEW to compare the temperature profiles on the surface during each deposition process. After each deposition, the geometric features were scanned, and the surface waviness value was evaluated. Tensile and Charpy impact coupons were extracted from the wall geometries in the longitudinal and transverse directions and tested. The results indicated that a higher CO 2 content produced higher melt pool temperatures to an extent, while lower contents of CO 2 resulted in a dimensionally accurate geometry. The data also indicated that the 2%/98% CO 2 /Ar blend produced scatter in tensile strength and the analysis of variance (ANOVA) shows significant difference. However, the intermediate range of CO 2 (5–10%) resulted in uniform tensile properties. Altogether, these results indicate that a 5%/95% CO 2 /Ar blend is the ideal shielding gas for lowering process temperatures and improving mechanical properties in wire arc additive manufacturing using the gas metal arc welding surface tension transfer process. Additionally, varying concentrations of Ar/CO 2 can be used within the same part in order to modify the local properties or process parameters such as strength, toughness, temperature, or dimensional features. This may improve overall manufacturing quality without sacrificing specific properties.
Controlling the intensity of emitted light and charge current is the basis of transferring and processing information. By contrast, robust information storage and magnetic random-access memories are implemented using the spin of the carrier and the associated magnetization in ferromagnets. In this study, the missing link between the respective disciplines of photonics, electronics and spintronics is to modulate the circular polarization of the emitted light, rather than its intensity, by electrically controlled magnetization. Here we demonstrate that this missing link is established at room temperature and zero applied magnetic field in light-emitting diodes through the transfer of angular momentum between photons, electrons and ferromagnets. With spin-orbit torque a charge current generates also a spin current to electrically switch the magnetization. This switching determines the spin orientation of injected carriers into semiconductors, in which the transfer of angular momentum from the electron spin to photon controls the circular polarization of the emitted light. The spin-photon conversion with the nonvolatile control of magnetization opens paths to seamlessly integrate information transfer, processing and storage. Our results provide substantial advances towards electrically controlled ultrafast modulation of circular polarization and spin injection with magnetization dynamics for the next-generation information and communication technology, including space-light data transfer. The same operating principle in scaled-down structures or using two-dimensional materials will enable transformative opportunities for quantum information processing with spin-controlled single-photon sources, as well as for implementing spin-dependent time-resolved spectroscopies.
We combine deep Gaussian processes (DGPs) with multitask and transfer learning for the performance modeling and optimization of HPC applications. Deep Gaussian processes merge the uncertainty quantification advantage of Gaussian processes (GPs) with the predictive power of deep learning. Multitask and transfer learning allow for improved learning efficiency when several similar tasks are to be learned simultaneously and when previous learned models are sought to help in the learning of new tasks, respectively. A comparison with state-of-the-art autotuners shows the advantage of our approach on two application problems. In this article, we combine DGPs with multitask and transfer learning to allow for both an improved tuning of an application parameters on problems of interest but also the prediction of parameters on any potential problem the application might encounter.
A process for liquefying hydrogen gas into liquid hydrogen that includes:
Ni-based hydroxides are promising electrocatalysts for biomass oxidation reactions, supplanting the oxygen evolution reaction (OER) due to lower overpotentials while producing value-added chemicals. The identification and subsequent engineering of their catalytically active sites are essential to facilitate these anodic reactions. Herein, the proportional relationship between catalysts’ deprotonation propensity and Faradic efficiency of 5-hydroxymethylfurfural (5-HMF)-to-2,5 furandicarboxylic acid (FDCA, FEFDCA) is revealed by thorough density functional theory (DFT) simulations and atomic-scale characterizations, including in situ synchrotron diffraction and spectroscopy methods. The deprotonation capability of ultrathin layer-double hydroxides (UT-LDHs) is regulated by tuning the covalency of metal (M)-oxygen (O) motifs through defect site engineering and selection of M 3+ co-chemistry. NiMn UT-LDHs show an ultrahigh FE FDCA of 99% at 1.37 V versus reversible hydrogen electrode (RHE) and retain a high FE FDCA of 92.7% in the OER-operating window at 1.52 V, about 2× that of NiFe UT-LDHs (49.5%) at 1.52 V. Ni–O and Mn–O motifs function as dual active sites for HMF electrooxidation, where the continuous deprotonation of Mn–OH sites plays a dominant role in achieving high selectivity while suppressing OER at high potentials. The results showcase a universal concept of modulating competing anodic reactions in aqueous biomass electrolysis by electronically engineering the deprotonation behavior of metal hydroxides, anticipated to be translatable across various biomass substrates.
Carbon dioxide removal (CDR) technologies will play a significant role in limiting global warming if implemented on a large scale. Direct air capture (DAC) is a scalable approach for removing atmospheric carbon, yet the true scope of its scalability remains unclear due to the early stage of technology development and high first plant costs. This study provides groundwork for understanding the technoeconomic trade-offs in developing DAC systems using laminate-structured gas–solid contactors, encompassing the analysis of both contactor and process design spaces. The robust mass transfer and process models outlined in this study provide tools for evaluating DAC processes and designing DAC plants based on cost and energy analysis. First, the key contactor geometrical parameters are identified to understand the CO 2 productivity–energy demand trade-offs, where geometries yielding higher mass transfer rates can achieve higher CO 2 productivities at the expense of energy consumption by fans and steam use. Next, a detailed process parametric study is conducted for DAC systems coupled with steam-assisted temperature-vacuum swing adsorption (S-TVSA) to visualize the trade-offs in the multidimensional design space. The main cost driver dramatically changes over different process conditions, but the operating cost prevailed on the Pareto front, with potential to operate as low as 150 $/tonne-CO 2 (within the cost range of 148–504 $/tonne-CO 2 in this study where the DAC system is coupled with industrial facilities for steam production).
N-type metal oxides such as hematite (α-Fe 2 O 3 ) and bismuth vanadate (BiVO 4 ) are promising candidate materials for efficient photoelectrochemical water splitting; however, their short minority carrier diffusion length and restricted carrier lifetime result in undesired rapid charge recombination. In this paper, a 2D arranged globular Au nanosphere (NS) monolayer array with a highly ordered hexagonal hole pattern (hereafter, Au array) is introduced onto the surface of photoanodes comprised of metal oxide films via a facile drying and transfer-printing process. Through plasmon-induced resonance energy transfer, the Au array provides a strong electromagnetic field in the near-surface area of the metal oxide film. The near-field coupling interaction and amplification of the electromagnetic field suppress the charge recombination with long-lived photogenerated holes and simultaneously enhance the light harvesting and charge transfer efficiencies. Consequently, an over 3.3-fold higher photocurrent density at 1.23 V versus reversible hydrogen electrode (RHE) is achieved for the Au array/α-Fe 2 O 3 . Furthermore, the high versatility of this transfer printing of Au arrays is demonstrated by introducing it on the molybdenum-doped BiVO 4 film, resulting in 1.5-fold higher photocurrent density at 1.23 V versus RHE. The tailored metal film design can provide a potential strategy for the versatile application in various light-mediated energy conversion and optoelectronic devices.
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An innovative post-combustion process using aqueous sodium glycinates solutions (SGS) for CO 2 capture from a split flue gas stream emitted from the 600 MWe coal power plant, used in the Wolverine Clean Energy Venture (WCEV) project, was developed in Aspen Plus v.10. The flue gas flow rate used in the process was 12.43 kg/s (at 353.15 K and 101.33 kPa) and contained 0.0023 and 13.33 mol% of SO 2 and CO 2 , respectively. The overall process includes 5 main units designed to remove all SO 2 and capture more than 90 mol% of CO 2 in the flue gas stream, while producing high-value, salable sodium bicarbonate (NaHCO 3 ) nanomaterials to offset the total process costs. The hydraulics, mass transfer characteristics, and process performance obtained using Aspen Plus were discussed. Also, the capital expenditure (CAPEX), operating expenditure (OPEX), and Levelized cost of CO 2 capture (LCOC) were calculated to assess the feasibility of this process. Further, the hydraulics in the SO 2 washing and CO 2 capture units showed a pressure drop of 12 and 1 kPa, respectively, and the behaviors of the liquid holdup and normalized packing specific wetted surface area were similar in both units. The gas-side mass transfer coefficients were orders of magnitude greater than the liquid-side mass transfer coefficients. The process was able to capture 2.352 kg/s of CO 2 and produce 4.486 kg/s of valuable NaHCO 3 nanomaterials. Also, the calculated CAPEX, OPEX, and LCOC of the process for a 30-year plant lifetime were ($\$ $4,450,552), (233.00 $\$ $/h) and (35.49 $\$ $/ton of CO 2 captured), respectively.