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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evaluating large scale aqueous organic redox flow battery performance with a hybrid numerical and machine learning framework

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low-capacity degradation in 10 cm$^2$ cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier to commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm$^2$ DHP-based AORFB by combining a physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. Such combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
DOE OSTI2025

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
DOE OSTI2025

Energy performance of an operational government building retrofitted with ceiling phase change material tiles in a mixed-humid climate

The aging U.S. building stock requires various retrofit measures to enhance their energy efficiency. Here, this study explores the integration of thermal energy storage and advanced building controls as viable retrofit solutions for load flexibility and peak demand response while maintaining the occupants' comfort. A detailed assessment is conducted on the energy use of an administrative building in Sumner County, Kansas, focusing on the implementation of phase change materials (PCMs) in the ceiling of occupied zones. First, a time-resolved, whole-building energy model is developed in EnergyPlus, incorporating complex thermal behaviors such as air exchange between the plenum space and occupied zones, envelope leakage, and operational schedules. The model is then validated using experimental field test data, and subsequently a parametric assessment of key PCM properties and application strategies is performed to evaluate cooling electricity demand benefits. The parametric study shows that the optimal retrofit strategy, comprising a PCM with 23°C peak melting temperature, 0.125 in. (3.17 mm) thickness, and 150 kJ/kg latent heat, combined with active controls that include 8 h of precooling, forced convection under the ceiling, and a 2°C thermostat setback during peak hours, can result in a maximum load shift during the peak period of 99.6 % and the total electricity savings during the peak period of 98.9 % for the optimum case and thus provide significant cost savings under time-of-use pricing scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Oxygen–Chlorine Chemisorption Scaling for Seawater Electrolysis on Transition Metals: The Role of Redox

To clarify what controls species oxidation selectivity in seawater electrolysis, density functional theory (DFT) is used to identify chemisorption enthalpy trends and scaling relations for the simplest relevant adsorbates (O, Cl, and H) on relevant surfaces of 3d transition metals, as well as Pd and Pt, in face-centered-cubic and, if different, their ground-state crystal structures. Approximations are tested for electron exchange-correlation (XC) and van der Waals interactions to assess their ability to reproduce experimental adsorption enthalpies of H and O on Pt(111). The vdW-uncorrected generalized gradient approximation to XC of Perdew, Burke, and Ernzerhof (PBE) agrees most closely with experiments. Using DFT-PBE thereafter, it is determined that the O chemisorption enthalpy on this wide range of transition-metal surfaces is proportional to the sum of first and second atomic ionization energies, akin to a Born–Haber cycle for a redox reaction, indicating that metal redox activity controls O chemisorption strength. Then it is shown that the O and Cl chemisorption enthalpies are strongly correlated, suggesting that the transition metals considered will oxidize unselectively water and Cl – . This strong correlation appears also for crystal reduction potentials of binary oxides and chlorides, indicating a fundamental challenge for future seawater electrode materials design.

08 HYDROGEN↗
DOE OSTI2022

Overview of the TJ-II stellarator research programme towards model validation in fusion plasmas

TJ-II stellarator results on modelling and validation of plasma flow asymmetries due to on-surface potential variations, plasma fuelling physics, Alfvén eigenmodes (AEs) control and stability, the interplay between turbulence and neoclassical (NC) mechanisms and liquid metals are reported. Regarding the validation of the neoclassically predicted potential asymmetries, its impact on the radial electric field along the flux surface has been successfully validated against Doppler reflectometry measurements. Research on the physics and modelling of plasma core fuelling with pellets and tracer encapsulated solid pellet injection has shown that, although post-injection particle radial redistributions can be understood qualitatively from NC mechanisms, turbulence and fluctuations are strongly affected during the ablation process. Advanced analysis tools based on transfer entropy have shown that radial electric fields do not only affect the radial turbulence correlation length but are also capable of reducing the propagation of turbulence from the edge into the scrape-off layer. Direct experimental observation of long range correlated structures show that zonal flow structures are ubiquitous in the whole plasma cross-section in the TJ-II stellarator. Alfvénic activity control strategies using ECRH and ECCD as well as the relation between zonal structures and AEs are reported. Finally, the behaviour of liquid metals exposed to hot and cold plasmas in a capillary porous system container was investigated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Comparative physiological and genomic characterization of a novel Nitrobacter vulgaris strain from a nitrate-contaminated subsurface

Nitrite-oxidizing bacteria (NOB) represent a crucial node in the global nitrogen cycle. By catalyzing the second step of nitrification—the oxidation of nitrite to nitrate to generate energy for growth—NOB activity controls the fate of nitrite (NO 2 - ) in aerobic environments. Despite thriving in diverse environments, including soils, freshwater, marine ecosystems, subsurface habitats, and water treatment systems, organisms capable of nitrite oxidation are confined to Nitrobacter, Nitrospira, Nitrospina, Nitrotoga, and a few other specific lineages. The genus Nitrobacter, recognized for its facultative heterotrophic metabolism, is often associated with high-nitrogen environments. Here, we report the physiological characterization of a novel strain, Nitrobacter vulgaris strain MLSD-S22, isolated from a nitrate- and heavy-metal-contaminated subsurface. Growth inhibition experiments revealed that strain MLSD-S22 and the N. vulgaris type strain Z exhibited similar sensitivities to nitrite and nitrate, with nitrite being the most inhibitory. Microrespirometry demonstrated that the two N. vulgaris strains and Nitrobacter winogradskyi Nb-255 possessed higher affinities for nitrite and oxygen than previously reported for Nitrobacter, suggesting potential to compete in low-substrate environments. Long-read DNA sequencing provided a complete genome for strain MLSD-S22, revealing two plasmids and an intact nitrous oxide (N 2 O) reduction operon—an unexpected feature for Nitrobacter. While N 2 O reduction activity was not observed under the tested conditions, this discovery raises questions about the contribution of Nitrobacter NOB to the N 2 O sink. These findings broaden the physiological and genomic diversity of Nitrobacter, offering new insights into their adaptation strategies and providing a framework for future evaluation of their potential roles in nitrogen loss.

Nitrobacter↗
DOE OSTI2021

Ultrafast Carrier and Lattice Dynamics in Plasmonic Nanocrystalline Copper Sulfide Films

Excited carrier dynamics in plasmonic nanostructures determines many important optical properties such as nonlinear optical response and photocatalytic activity. Here it is shown that mesoscopic plasmonic covellite nanocrystals with low free-carrier concentration exhibit a much faster carrier relaxation than in traditional plasmonic materials. A nonequilibrium hot-carrier population thermalizes within first 20 fs after photoexcitation. A decreased thermalization time in nanocrystals compared to a bulk covellite is consistent with the reduced Coulomb screening in ultrathin films. The subsequent relaxation of thermalized, equilibrium electron gas is faster than in traditional plasmonic metals due to the lower carrier concentration and agrees well with that in a bulk covellite showing no evidence of quantum confinement or hot-hole trapping at the surface states. The excitation of coherent optical phonon modes in a covellite is also demonstrated, revealing coherent lattice dynamics in plasmonic materials, which until now was mainly limited to dielectrics, semiconductors, and semimetals. These findings show advantages of this new mesoscopic plasmonic material for active control of optical processes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

From fault-detection to automated fault correction: A field study

A fault detection and diagnostics (FDD) tool, as addressed by this study, is a tool that continuously identifies the presence of faults and efficiency improvement opportunities through a one-way interface to the building automation system and the application of automated analytics. Although FDD tools can inform operators of building operational faults, currently an action is always required to correct the faults to generate energy savings. Fault auto-correction integrating with commercial FDD technology offerings can close the loop between the passive diagnostics and active control, increase the savings generated by FDD tools, and reduce the reliance on human intervention. This paper presents the field study of seven fault auto-correction algorithms implemented in commercial FDD platforms. Implementation includes software changes in the FDD tools and additional controls hardware or software changes in the BAS that were required to enable the execution of different types of auto-correction algorithms in real buildings. The routines successfully and automatically correct faults and improve the operation of large built-up Heating, Ventilation, and Air Conditioning (HVAC) systems, common in most commercial buildings. The auto-correction algorithms are tested across four buildings and three different building automation systems, following a rigorous procedure to make sure they work properly and do not negatively impact the system and building occupants. Finally, technology benefits, market drivers, and scalability changes are drawn from the implementation effort and test results, to drive future research and industry engagement.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Thermal performance of an absorption-assisted two-stage ejector air-to-water heat pump

In this work, a gas-fired air-to-water ejector heat pump (EHP) for domestic hot water production is proposed and analyzed thermodynamically. The COP of the EHP is improved by using binary fluids (HFE7500 and water), and the high backpressure in the primary ejector (first-stage) is actively controlled by either a second-stage ejector and/or a LiBr-H 2 O absorption subsystem. A thermodynamic model is established for analysis and performance evaluation. A case study shows the backpressure of the first-stage ejector is reduced by 53.5%, and the backpressure control using the second-stage ejector increases the system COP by 21.0% compared with that using LiBr-H 2 O absorption. Parametric studies are conducted to investigate the roles of the first-stage ejector, the second-stage ejector, and the LiBr-H 2 O absorption subsystem. The first-stage ejector plays a dominant role in the EHP system performance. The EHP’s heating COP can reach 2.0 with an entrainment ratio of 0.12 in the first-stage ejector. EHP performance can be improved with a high entrainment ratio and a low-temperature primary working fluid in the first-stage and second-stage ejectors, a low condensation temperature in the first-stage ejector, and a high generating temperature and a low concentration of the LiBr-H 2 O solution.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Accelerated version of NUBEAM capabilities in DIII-D using neural networks

A neural network model of the effects of neutral beam injection on DIII-D has been developed. The training and testing data used by the model have been generated by the NUBEAM module of TRANSP for experimental discharges from the 2018 DIII-D campaign. Using a principle component analysis to reduce the dimensionality of profile data, the model has been shown to reproduce the results of the Monte Carlo code NUBEAM with a high level of accuracy and an execution time orders of magnitude faster than the execution time of NUBEAM. Furthermore, this makes the neural network model uniquely suited to applications in model-based scenario planning (off-line) and active control (on-line), where a large number of simulation runs are required by the associated optimization tasks that need to be performed before and during the discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Experimental measurements of fuel and water crossover in an active DMFC

This work measured polarization curves as well as the high-frequency resistance of active direct methanol fuel cell (DMFC) operates at around 80 °C with active controls of temperature, methanol concentration, airflow rate, and relative humidity. The relative humidity of the air did not have noticeable impacts on the fuel cell unless the operating temperature was near the evaporation temperature of water (100 °C). The hydrophobic water management layer (WML) between the membrane electrode assembly (MEA) and cathode air channel increases the mass transfer resistance and improves the water retention in MEA. Adding a WML increased the peak power density, decreased the ohmic resistance, and improved the fuel efficiency of the fuel cell, especially when it operated near 100 °C. This study also quantitatively measured methanol and water crossover as well as the fuel efficiency at different operating currents. The fuel efficiency increased significantly with the increase of the current density. Using a hydrophobic fuel management layer (FML) between the anode fuel channel and MEA reduced the fuel and water crossover rates and increased the ohmic resistance due to the decrease of the water content of the Nafion membrane. The FML improved fuel efficiency by reducing the methanol crossover. The combination of the FML and WML enabled the steady operation of DMFC using highly concentrated methanol solutions (up to 75 wt%).

08 HYDROGEN↗
DOE OSTI2023

Bayesian optimal experimental design for constitutive model calibration

Computational simulation is increasingly relied upon for high/consequence engineering decisions, which necessitates a high confidence in the calibration of and predictions from complex material models. However, the calibration and validation of material models is often a discrete, multi-stage process that is decoupled from material characterization activities, which means the data collected does not always align with the data that is needed. To address this issue, an integrated workflow for delivering an enhanced characterization and calibration procedure—Interlaced Characterization and Calibration (ICC)—is introduced and demonstrated. Further, this framework leverages Bayesian optimal experimental design (BOED), which creates a line of communication between model calibration needs and data collection capabilities in order to optimize the information content gathered from the experiments for model calibration. Eventually, the ICC framework will be used in quasi real-time to actively control experiments of complex specimens for the calibration of a high-fidelity material model. This work presents the critical first piece of algorithm development and a demonstration in determining the optimal load path of a cruciform specimen with simulated data. Calibration results, obtained via Bayesian inference, from the integrated ICC approach are compared to calibrations performed by choosing the load path a priori based on human intuition, as is traditionally done. The calibration results are communicated through parameter uncertainties which are propagated to the model output space (i.e. stress–strain). In these exemplar problems, data generated within the ICC framework resulted in calibrated model parameters with reduced measures of uncertainty compared to the traditional approaches.

42 ENGINEERING↗
DOE OSTI2025

The role of the Pt-group dehydrogenation catalyst in alkane metathesis for polyolefin deconstruction

Recent proposed approaches in the depolymerization of waste plastics employ an olefin intermediate to produce alkanes or alkenes using olefin metathesis in tandem chemistry. Here, in this study, we investigated the role of the dehydrogenation catalyst on reaction rate, kinetics, and product distribution in heterogeneous tandem dehydrogenation and olefin metathesis (alkane metathesis) of three different alkane reactants, including polyethylene. We found that many properties to which alkane dehydrogenation rates were sensitive-including metal composition, nanoparticle size, and surface doping of Re species also controlled activity in Tandem D/OM. When comparing Pd, Pt, and Pt 3 Sn 1 , supported Pd in tandem with a Re 2 O 7 olefin metathesis catalyst showed four-fold higher activity (surface area basis) compared to Pt or Pt 3 Sn 1 catalysts on the same support, mainly due to differences in the rate of hydrogenation. Catalyst preparation resulted in metal nanoparticles partially covered by ReO x , as seen from elemental mapping. Co-location of Re 2 O 7 and Pd correlated with increased rates of hydrogenation (i.e., an increase in the rate of alkane formation and simultaneous lowering of the rate of alkene formation), with a reaction order in catalyst study that further supported this conclusion. The Pd and Re 2 O 7 system displayed marked improvement compared to Pt or Pt 3 Sn 1 with Re 2 O 7 , and previous work, in the depolymerization rate of a linear polyethylene feedstock, with over 94 % reduction in polymer molecular weight in 15 h at 190 °C using less catalyst and increased reactant loadings, while keeping solvent to polymer consumption below 2.5.

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

Electro-strengthening of the additively manufactured Ti–6Al–4V alloy

Structure-property-processing relationship has been studied in additively manufactured Ti–6Al–4V alloy. The processing was performed using in-situ electron microscope (EM) at a moderate current density of 5 × 105 A/cm2 applied for 5 min, and by suppressing Joule heating with massive heat sinks such that the temperature rise was <180 °C and the mechanical properties were not compromised. Overall, the results show that while the grain size increased by ~15%, the nanohardness increased by 16%. This is attributed to the pronounced dislocation generation, regeneration, and clustering as well as defect healing. Ultimately, there is a reduction in the residual strain and a significant increase in the intrinsic strength as evidenced by the high Taylor factor of the electric current processed specimen. This novel processing technique represents an alternative pathway for active controlling of microstructure and internal defects for parts that might be sensitive to high-temperature processing or conventional methods.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Heterogeneity and Hysteresis in the Polymer Collapse of Single Core–Shell Stimuli-Responsive Plasmonic Nanohybrids

Broad application of polymeric stimuli-responsive smart nanohybrids requires understanding the mechanisms governing active control. Ensemble techniques have identified inhomogeneous polymer collapse in microgels that potentially arise from heterogeneous interchain interactions and differences in core size. A single-particle examination would establish the influence of core size and internal polymer network heterogeneity on local interactions that contribute to the observed inhomogeneous polymer collapse dynamics of nanohybrids. Using single-particle dark-field spectroscopy, we investigated the complex polymer collapse profiles of core–shell plasmonic nanohybrids comprising thermoresponsive poly(N-isopropylacrylamide) (pNIPAM)-encapsulated gold nanorods (AuNRs). We report that the polymer collapse behavior was independent of the core size. For thinner polymer shells, we observed hysteresis in the collapse of AuNR@pNIPAMs, likely related to local pNIPAM aggregation due to interchain hydrogen bonding. For thicker polymer shells, we observed a broad polymer collapse distribution that we attributed to a two-step phase transition that arises from a polymer network density gradient. Furthermore, our single-particle approach relates the internal heterogeneity of the polymer network of nanohybrids to the mechanisms underlying heterogeneous phase transitions that traditional, ensemble-averaged approaches are unable to discern.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

In Situ Monitoring the Nucleation and Growth of Nanoscale CaCO 3 at the Oil–Water Interface

Interfaces can actively control the nucleation kinetics, orientations, and polymorphs of calcium carbonate (CaCO 3 ). Prior studies have revealed that CaCO 3 formation can be affected by the interplay between chemical functional moieties on solid–liquid or air–liquid interfaces as well as CaCO 3 ’s precursors and facets. Yet little is known about the roles of a liquid–liquid interface, specifically an oil–liquid interface, in directing CaCO 3 mineralization which are common in natural and engineered systems. Here, in this study, by using in situ X-ray scattering techniques to locate a meniscus formed between water and a representative oil, isooctane, we successfully monitored CaCO 3 formation at the pliable isooctane–water interface and systematically investigated the pivotal roles of the interface in the formation of CaCO 3 (i.e., particle size, its spatial distribution with respect to the interface, and its mineral phase). Different from bulk solution, ∼5 nm CaCO 3 nanoparticles form at the isooctane–water interface. They stably exist for a long time (36 h), which can result from interface-stabilized dehydrated prenucleation clusters of CaCO 3 . There is a clear tendency for enhanced amounts and faster crystallization of CaCO 3 at locations closer to isooctane, which is attributed to a higher pH and an easier dehydration environment created by the interface and oil. Our study provides insights into CaCO 3 nucleation at an oil–water interface, which can deepen our understanding of pliable interfaces interacting with CaCO 3 and benefit mineral scaling control during energy-related subsurface operation.

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

Tuning the interfacial spin-orbit coupling with ferroelectricity

Detection and manipulation of spin current lie in the core of spintronics. Here we report an active control of a net spin Hall angle, θ SHE (net), in Pt at an interface with a ferroelectric material PZT (PbZr 0.2 Ti 0.8 O 3 ), using its ferroelectric polarization. The spin Hall angle in the ultra-thin Pt layer is measured using the inverse spin Hall effect with a pulsed tunneling current from a ferromagnetic La 0.67 Sr 0.33 MnO 3 electrode. The effect of the ferroelectric polarization on θ SHE (net) is enhanced when the thickness of the Pt layer is reduced. When the Pt layer is thinner than 6 nm, switching the ferroelectric polarization even changes the sign of θ SHE (net). This is attributed to the reversed polarity of the spin Hall angle in the 1 st -layer Pt at the PZT/Pt interface when the ferroelectric polarization is inverted, as supported by the first-principles calculations. These findings suggest a route for designing future energy efficient spin-orbitronic devices using ferroelectric control.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Integration of full divertor detachment with improved core confinement for tokamak fusion plasmas

Divertor detachment offers a promising solution to the challenge of plasma-wall interactions for steady-state operation of fusion reactors. Here, we demonstrate the excellent compatibility of actively controlled full divertor detachment with a high-performance (β N ~ 3, H 98 ~ 1.5) core plasma, using high-β p (poloidal beta, β p > 2) scenario characterized by a sustained core internal transport barrier (ITB) and a modest edge transport barrier (ETB) in DIII-D tokamak. The high-β p high-confinement scenario facilitates divertor detachment which, in turn, promotes the development of an even stronger ITB at large radius with a weaker ETB. This self-organized synergy between ITB and ETB, leads to a net gain in energy confinement, in contrast to the net confinement loss caused by divertor detachment in standard H-modes. These results show the potential of integrating excellent core plasma performance with an efficient divertor solution, an essential step towards steady-state operation of reactor-grade plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗