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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Close Companions around Young Stars

Multiplicity is a fundamental property that is set early during stellar lifetimes, and it is a stringent probe of the physics of star formation. The distribution of close companions around young stars is still poorly constrained by observations. We present an analysis of stellar multiplicity derived from Apache Point Observatory Galactic Evolution Experiment-2 spectra obtained in targeted observations of nearby star-forming regions. This is the largest homogeneously observed sample of high-resolution spectra of young stars. We developed an autonomous method to identify double-lined spectroscopic binaries (SB2s). Out of 5007 sources spanning the mass range of ∼0.05–1.5 M {sub ⊙}, we find 399 binaries, including both radial velocity (RV) variables and SB2s. The mass ratio distribution of SB2s is consistent with being uniform for q < 0.95 with an excess of twins for q > 0.95. The period distribution is consistent with what has been observed in close binaries (<10 au) in the evolved populations. Three systems are found to have q ∼ 0.1, with a companion located within the brown dwarf desert. There are no strong trends in the multiplicity fraction as a function of cluster age from 1 to 100 Myr. There is a weak dependence on stellar density, with companions being most numerous at Σ{sub *} ∼ 30 stars/pc{sup −2} and decreasing in more diffuse regions. Finally, disk-bearing sources are deficient in SB2s (but not RV variables) by a factor of ∼2; this deficit is recovered by the systems without disks. This may indicate a quick dispersal of disk material in short-period equal-mass systems that is less effective in binaries with lower q.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Control-oriented core-SOL-divertor model to address integrated burn and divertor control challenges in ITER

The real-time regulation of a burning plasma’s temperature and density, or burn control, will be necessary to produce high fusion power in future tokamaks like ITER. This is made more challenging due to the plasma’s nonlinear characteristics and the interdependence between the core-plasma and edge-plasma regions. For example, a raising plasma temperature leads to increasing reactivity and therefore to more alpha-particle heating, which further increases temperature. Furthermore, a raise of the fusion power increases the heat flow through the scrape-off-layer (SOL), which can compromise the integrity of the divertor without proper safeguards. For control design, a model-based approach is attractive because it can directly incorporate the nonlinear, coupled, burning-plasma dynamics into the design. To facilitate this design approach, a control-oriented core-SOL-divertor (CSD) model is presented in this work. In this CSD model, a core-plasma model captures the nonlinear dynamics of the core’s density and temperature, and a SOL-divertor model defines the plasma conditions at the separatrix and divertor including the heat load on the target plates. The core-plasma and SOL-divertor models are coupled through the exchange of various variables. In particular, the SOL-divertor model yields the separatrix temperature and the influx of recycled particles into the core-plasma. Further, these variables influence the power and particle balances captured by the core-plasma model. In return, the core-plasma model determines the intensity of the heat and particles fluxes across the separatrix, and this outflow strongly impacts the SOL-divertor model. Therefore, the power and density of the core-plasma, which can be readily modulated through external heating systems and pellet injection, can be viewed as control knobs for the SOL-divertor region in addition to the gas puffing. In simulations of the CSD model, it is demonstrated how external actuation can be utilized to meet burn control and divertor control objectives simultaneously.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1982

A spectrophotometric survey of cataclysmic variable stars

A sample of dwarf novae and other cataclysmic variable stars were observed using the multichannel spectrophotometer on the 5-m Hale reflector. A preliminary qualitative description of the continuum distributions is given and a discussion of the Balmer emission-line fluxes is made. For the spectral energy distributions, the logarithm of the monochromatic flux density is plotted against the inverse of the wavelength. It is concluded that the presence or absence of evident flux from a late-type stellar component is consistent with the standard picture which has been developed for the structure of cataclysmic variable stars. The presence of the Balmer jump in emission or absorption can be understood in terms of the relative importance of an optically thick accreting disk characteristic of nova-like variables and dwarf novae in outburst and an optically thin outer accreting disk characteristic of quiescent dwarf novae.

Oke, J. B.↗
DOE OSTI2023

Bayesian Inference with Latent Hamiltonian Neural Networks (L-HNNs)

When sampling for Bayesian inference, one popular approach is to use Hamiltonian Monte Carlo (HMC) and the No-U-Turn Sampler (NUTS). However, HMC and NUTS can require numerous numerical gradients of the target density and can prove slow in practice. We propose Hamiltonian neural networks (HNNs) with HMC and NUTS for solving Bayesian inference problems [1, 2]. Once trained, HNNs do not require gradients of the target density while sampling. Moreover, they satisfy important properties such as perfect time reversibility and Hamiltonian conservation, making them well suited for use within HMC and NUTS because stationarity can be shown. We also propose an HNN extension called latent HNNs (L-HNNs), which predict latent variable outputs. Compared to HNNs, L-HNNs offer improved expressivity and a reduction in integration errors. Finally, we propose employing L-HNNs in NUTS with an online error monitoring scheme to prevent degeneracy of the sampling in regions of low probability density. We demonstrate L-HNNs in NUTS with online error monitoring by using several example cases involving complex, heavy-tailed, and high local curvature probability densities. Overall, L-HNNs in NUTS with online error monitoring satisfactorily inferred these probability densities. Compared to traditional NUTS, L-HNNs in NUTS with online error monitoring improved the effective sample size (ESS) per gradient by an order of magnitude.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Combined Machine Learning and High-Energy X-ray Diffraction Approach to Understanding Liquid and Amorphous Metal Oxides

Determining the structure-property relations of liquid and amorphous metal oxides is challenging, due to their variable short-range order and polyhedral connectivity. To predict chemically realistic structures, we have developed a Machine Learned, Gaussian Approximation Potential (GAP) for HfO 2 , with a focus on enhanced sampling of the training database and accurate density functional theory calculations. By using training datasets for the GAP model at the level of Density Functional Theory-Strongly Constrained and Appropriately Normed (DFT-SCAN) level of theory, our results show that the topology of both the low viscosity liquid and the amorphous form are dominated by edge-shared chains and small corner-shared rings of polyhedra. This topology is shown to be consistent with the structure of other liquid and amorphous transition metal oxides of variable ion size, such as TiO 2 and ZrO 2 . Current limitations of the ML-GAP modeling method for obtaining glass structures and future perspectives are also discussed.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Mechanisms of anode power deposition in a low pressure free burning arc

Anode power deposition is a dominant power loss mechanism for arc jets and MPD thrusters. In this study, a free burning arc experiment was operated at pressures and current densities similar to those in arc jets and MPD thrusters in an attempt to identify the physics controlling this loss mechanism. Use of a free burning arc allowed for the isolation of independent variables controlling anode power deposition and provided a convenient and flexible way to cover a broad range of currents, anode surface pressures, and applied magnetic field strengths and orientations using an argon gas. Test results showed that anode power deposition decreased with increasing anode surface pressure up to 6.7 Pa (0.05 torr) and then became insensitive to pressure. Anode power increased with increasing arc current while the electron number density near the anode surface increased linearity. Anode power also increased with increasing applied magnetic field strength due to an increasing anode fall voltage. Applied magnetic field orientation had an effect only at high currents and low anode surface pressures, where anode power decreased when applied field lines intercepted the anode surface. The results demonstrated that anode power deposition was dominated by the current carrying electrons and that the anode fall voltage was the largest contributor. Furthermore, the results showed that anode power deposition can be reduced by operating at increased anode pressures, reduced arc currents, and applied magnetic field strengths and with magnetic field lines intercepting the anode.

Soulas, George C.↗
NASA NTRS2024

Storm-Time Variability of Terrestrial Hydrogen Exosphere: Kinetic Simulation Results

Recent studies of TWINS Lyman-α observations have reported an increase in geocoronal column brightness during geomagnetic storms, indicating enhanced exospheric hydrogen atom density (NH). This suggests a complex role of exospheric neutrals in determining storm-time magnetosphere dynamics and their energy release through charge-exchange processes. We developed a Model for Analyzing Terrestrial Exosphere (MATE) to investigate storm-time exospheric behaviors and their physical drivers. MATE traces test hydrogen atoms backward in time from locations in the exosphere to a nominal exobase altitude of 500 km, employing Newtonian mechanics with gravitational force. The model then calculates the phase-space densities (PSDs) of test hydrogen atoms at the exobase using the Maxwellian distribution with physics-based exobase conditions from the TIMEGCM upper atmosphere model. MATE maps PSDs at the exobase to the exosphere using Liouville’s Theorem under collisionless assumptions and derives NH by integrating the PSDs across velocity space. We conducted MATE simulation before, during, and after a minor geomagnetic storm from 12 to 18 June 2008, and compared the model results with NH estimates from the TWINS geocorona data. MATE reproduces storm-time density enhancements soon after the minimum Dst is reached, matching well with a general trend of TWINS NH estimates. The results suggest that upper atmospheric heating during a geomagnetic storm increases the number of ballistic and escaping hydrogen atoms entering the exosphere from the exobase, thereby boosting NH. However, the magnitude of modeled NH mismatches the TWINS NH estimates. The potential mechanisms of this density discrepancy include the physics excluded in the MATE model — such as neutralneutral collisions, neutral-plasma charge exchange, solar radiation pressure, and photoionization — as well as the higher exobase hydrogen density of TIMEGCM compared to typical empirical values, which will be addressed in future.

Hyunju K Connor↗
NASA NTRS1996

Validation of Spectral Analysis as a Noninvasive Tool to Assess Autonomic Regulation of Cardiovascular Function

A major focus of our program has been to develop a sensitive noninvasive procedure to quantify early weightlessness-induced changes in cardiovascular function or potential dysfunction. Forty studies of healthy young volunteers (10 men and 10 women, each studied twice) were conducted to determine changes in the sympatho-vagal balance of autonomic control of cardiovascular regulation during graded headward and footward blood volume shifts. Changes in sympatho-vagal balance were classified by changes in the mean levels and spectral content of cardiovascular variables and verified by changes in circulating levels of catecholamines and pancreatic polypeptide. Possible shifts in intra/extravascular fluid were assessed from changes in hematocrit and plasma mass density while changes in the stimulus to regulate plasma volume were determined from Plasma Renin Activity (PRA). Autonomic blockade was used to unmask the relative contribution of sympathetic and parasympathetic efferent influences in response to 10 min each of 0, 20 and 40 mmHg Lower Body Negative Pressure (LBNP) and 15 and 30 mmHg Positive Pressure (LBPP). The combination of muscarinic blockade with graded LBNP and LBPP was used to evoke graded increases and decreases in sympathetic activity without parasympathetic contributions. The combination of beta blockade with graded LBNP and LBPP was used to produce graded increases and decreases in parasympathetic activity without beta sympathetic contributions. Finally, a combination of both beta and muscarinic blockades with LBNP and LBPP was used to determine the contribution from other, primarily alpha adrenergic, sources. Mean values, spectral analyses and time frequency analysis of R-R interval (HR), Arterial Pressure (AP), peripheral blood flow (RF), Stroke Volume (SV) and peripheral resistance (TPR) were performed for all phases of the study. Skin blood Flow (SF) was also measured in other studies and similarly analyzed. Spectra were examined for changes in three frequency regions (low 0.006 - 0.005 Hz (LF), mid 0.05 - 0.15 Hz (W), and high 0.15 - 0.45 Hz (EF)). The primary objective of the study was to indicate which changes in the mean values and/or spectra of cardiovascular variables consistently correlated with changes in sympatho-vagal balance in response to headward and footward fluid shifts. A secondaey objective was to quantify the vascular and extravascular fluid shifts evoked by LBNP and LBPP. The principal hypothesis being tested was that headward fluid shifts would evoke an increase in parasympathetic activity and footward fluid shifts would evoke an increase in sympathetic activity both of which would be detected by spectral analysis and verified by circulating hormones. Hematocrit (HCT), plasma mass density and plasma renin activity increased with muscarinic blockade and with LBNP, a response indicative of a plasma shift to extravascular spaces. Beta blockade alone or after muscarinic blockade had no effect on HCT or plasma mass density. With respect to intravascular fluid volume distribution, LBNP and LBPP produced sufficient upper body vascular fluid shifts to evoke appropriate autonomic regulatory responses.

Knapp, Charles F.↗
NASA NTRSDate not supplied

Improved Prediction of Losses with Large Eddy Simulation in a Low-Pressure Turbine

There is a need to improve predictions of losses resulting from large eddy simulations (LES) of low-pressure turbines (LPT) in gas turbines. This may be done by assessing the accuracy of predictions against validation data and understanding the source of any inaccuracies. LES is a promising approach for capturing the laminar/turbulent transition process in a LPT. In previous studies, the authors utilized LES to model the flow field over a Variable Speed Power Turbine (VSPT) blade and successfully captured characteristic features of separation/reattachment and transition on the suction side at both the cruise (positive incidence) and take-off conditions (negative incidence) and as well, simulated the effect of freestream turbulence (FST) on those phenomena. The predicted pressure loading profiles agreed well with the experimental data for both a high and a low FST case at a Reynolds number of Reex=220,000. In this paper, we present wake profiles resulting from computations for a range of FST values. Although the predicted wake profiles for the lowest FST case (Tu=0.5%) matched the experimental data, at higher FST (Tu=10-15%,) the wake was wider than the experimentally measured wake and for both cases were displaced laterally when compared to the experimental measurements. In our investigation of the causes of the said discrepancies we have identified important effects which could strongly influence the predicted wake profile. Predicted losses were improved by assuring the validity of the flow solution. This was done by utilizing spectral analysis to scrutinize the dynamic behavior of the wake and determine solution accuracy resulting from low mesh density and low accuracy of convective modeling.

CFD↗
NASA NTRSDate not supplied

Use of Design of Experiments and Rule-Based Inference in Determining Neural Network Architectures for Loss of Control Detection

In this work, we describe methods for selecting the neural network architectures and input spaces to implement belief state inference on generic commercial transport aircraft. First, we highlight a case study on the planning, execution, and analysis of a set of experiments to determine the configurations of a conditional variational autoencoder (CVAE). We present a structured method that can be used in a number of aerospace applications, to optimize the structure and training parameters of the CVAE for belief state inference, using Design of Experiments (DOE) statistical methodologies. The motivation for this specific DOE was to identify the appropriate hyperparameters for measuring the CVAE reconstruction probability and latent space, such that the measurements can be used to infer qualitative state changes for the aircraft. We demonstrate that this process yields information about a trained neural network’s utility for this specific application, along with a quantifiable range of certainty. We execute 84 experiments using loss-of-control flight maneuver data from a NASA T-2 aircraft, demonstrating that this empirical process allows us to construct cheap and simple models with specific attributes amenable to belief state inference in aerospace applications. While theoretically, we could create a single CVAE with an input space the size of all measurable flight variables and environmental dynamics, it becomes intractable to use such a neural network in an in-situ intelligent multi-agent system. Using the recommendations from our case study, we introduce a technical approach for feasibly describing the belief space by (1) identifying significant statistical relationships among flight variables using rule induction, (2) using a set of rules that cover all features to define the input space of multiple CVAEs, and (3) forming a belief space based on the joint probability density of their collective latent spaces. This results in a series of relatively small matrix multiplications that can be performed in real time, as opposed to large matrix computations in a single CVAE. We demonstrate the application of this approach on the T-2 flight loss-of control experiments, using the architecture and hyperparameter recommendations from the case study. We compare the utilities of an individual CVAE trained on all flight variables and multiple CVAEs defined on subsets of flight variables for detecting qualitative changes in flight. We demonstrate that the use of multiple CVAEs with smaller input spaces permits the CVAE to capture more granular relationships in the latent space, permitting better state space characterization and loss-of-control detection.

Design of experiments↗
NASA NTRS1992

Effect of leg exercise training on vascular volumes during 30 days of 6 degrees head-down bed rest

Plasma and red cell volumes, body density, and water balance were measured in 19 men (32-42 yr) confined to bed rest (BR). One group (n = 5) had no exercise training (NOE), another near-maximal variable-intensity isotonic exercise for 60 min/day (ITE; n = 7), and the third near-maximal intermittent isokinetic exercise for 60 min/day (IKE; n = 7). Caloric intake was 2,678-2,840 kcal/day; mean body weight (n = 19) decreased by 0.58 +/- 0.35 (SE) kg during BR due to a negative fluid balance (diuresis) on day 1. Mean energy costs for the NOE, and IKE, and ITE regimens were 83 (3.6 +/- 0.2 ml O2.min-1.kg-1), 214 (8.9 +/- 0.5 ml.min-1.kg-1), and 446 kcal/h (18.8 +/- 1.6 ml.min-1.kg-1), respectively. Body densities within groups and mean urine volumes (1,752-1,846 ml/day) between groups were unchanged during BR. Resting changes in plasma volume (ml/kg) after BR were -1.5 +/- 2.3% (NS) in ITE, -14.7 +/- 2.8% (P less than 0.05) in NOE, and -16.8 +/- 2.9% (P less than 0.05) in IKE, and mean water balances during BR were +295, -106, and +169 ml/24 h, respectively. Changes in red cell volume followed changes in plasma volume. The significant chronic decreases in plasma volume in the IKE and NOE groups and its maintenance in the ITE group could not be accounted for by water balance or by responses of the plasma osmotic, protein, vasopressin, or aldosterone concentrations or plasma renin activity. There was close coupling between resting plasma volume and plasma protein and osmotic content.(ABSTRACT TRUNCATED AT 250 WORDS).

NASA Discipline Regulatory Physiology↗
DOE OSTI2019

From Farms to Forests: Landscape Carbon Balance after 50 Years of Afforestation, Harvesting, and Prescribed Fire

Establishing reliable carbon baselines for landowners desiring to sustain carbon sequestration and identify opportunities to mitigate land management impacts on carbon balance is important; however, national and regional assessments are not designed to support individual landowners. Such baselines become increasingly valuable when landowners convert land use, change management, or when disturbance occurs. We used forest inventories to quantify carbon stocks, estimate annual carbon fluxes, and determine net biome production (NBP) over a 50-year period coinciding with a massive afforestation effort across ~80,000 ha of land in the South Carolina Coastal Plain. Forested land increased from 48,714 ha to 73,824 ha between 1951 and 2001. Total forest biomass increased from 1.73–3.03 Gg to 17.8–18.3 Gg, corresponding to biomass density increases from 35.6–62.2 Mg ha−1 to 231.4–240.0 Mg ha−1. Harvesting removed 1340.3 Gg C between 1955 and 2001, but annual removals were variable. Fire consumed 527.1 Gg C between 1952 and 2001. Carbon exported by streams was <0.5% of total export. Carbon from roots and other harvested material that remained in-use or in landfills comprised 49.3% of total harvested carbon. Mineral soil carbon accounted for 41.6 to 50% of 2001 carbon stocks when considering depths of 1.0 or 1.5 m, respectively, and was disproportionately concentrated in wetlands. Moreover, we identified a soil carbon deficit of 19–20 Mg C ha−1, suggesting opportunities for future soil carbon sequestration in post-agricultural soils. Our results provide a robust baseline for this site that can be used to understand how land conversion, forest management, and disturbance impacts carbon balance of this landscape and highlight the value of these baseline data for other sites. Our work also identifies the need to manage forests for multiple purposes, especially promotion of soil carbon accumulation in low-density pine savannas that are managed for red-cockaded woodpeckers and therefore demand low aboveground carbon stocks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Modeling neutral defects in III-V ternary alloys with a special quasirandom structure: Analysis of As- and III-site point defects in InGaAs

While first-principles density functional theory modeling has become a vital tool to investigate defect properties in semiconductors, the lack of crystalline periodicity in pseudobinary random composition alloys, such as In 1−𝑥 ⁢Ga 𝑥 ⁢As, complicates such analyses. We present a simulation strategy to systematically take into account the variability in the local defect environment in order to predict statistical properties of neutral intrinsic defects in In 1−𝑥⁢ Ga 𝑥 ⁢As. We use a comprehensive sampling from a modest-sized 64-atom special quasirandom structure (SQS) to define a statistically representative set of defects, and use a 512-atom hypercell, a 2 × 2 × 2 supercell of SQS supercells, to achieve cell-size convergence. We articulate an equivalent site principle and describe how it constrains atomic chemical reference energies in computation of defect formation energies in pseudobinary alloys. A simple protocol for estimating reference energies for the Ga and In atoms sharing the III site succeeds in obtaining the equivalence of defects at Ga-sites and In sites in the SQS supercell, (<30 meV differences in average formation energies). For III-site defects, such as the As antisite As III , the statistical variability in formation energies is modest, ≈ 0.1–0.2 eV. The variability in formation energy at As-site defects, such as the As vacancy 𝑣 As , can be much larger, >1 eV. The As antisite is shown to be a low-energy defect and the most likely to be present in as-grown materials, just as in GaAs. All other defects are higher-energy defects unlikely to be important in native material, but potentially important in radiation-damaged material. With a strong variability in defect energies, especially on the As-site, explicit consideration of statistical variability due to compositional randomness will be imperative for meaningful and quantitative comparisons to experiment.

Density functional theory↗
DOE OSTI2025

Enhancing biomass flowability for entrained flow Gasification: The role of densification and torrefaction

Gasification presents a key strategy in addressing future energy demands while minimizing environmental impact. This has been recognized as a promising method to convert biomass to higher value products such as biofuels or hydrogen. Among gasification technologies, high-temperature and high-pressure reactors, particularly the R-GAS® system, emerge as an advanced option boasting superior conversion efficiency. However, akin to conventional high-temperature and high-pressure gasifiers, R-GAS® necessitates small particle sizes for optimal carbon conversion, a requirement yet to be fully explored for biomass. Hence, this study investigated the effectiveness of combined mechanical and thermal preprocessing techniques in modifying the physicochemical properties of biomass to suit gasification systems. Mechanical techniques including densification and pulverization, alongside thermal techniques such as torrefaction and steam explosion, were examined. The results demonstrate that torrefaction fosters producing of uniform granular material, enhancing flowability and reducing energy requirements for pulverization compared to steam explosion. Notably, torrefied corn stover exhibited lower internal friction angles and effective cohesion (40.09 ± 0.22° and 0.56 ± 0.01 kPa, respectively) compared to steam exploded corn stover (41.87 ± 0.65° and 0.83 ± 0.06 kPa, respectively), indicative of improved flowability. Additionally, pulverization of torrefied corn stover required approximately 16 % less energy than steam exploded corn stover and 91 % less energy than raw corn stover. Furthermore, the torrefaction-induced alterations in particle size, shape, and packing densities emphasize its potential to optimize flow and handling processes for gasification. These findings underline that densification followed by torrefaction effectively addresses biomass variability, leading to more efficient and sustainable energy conversion.

09 - BIOMASS FUELS↗
DOE OSTI2017

XRD and EBSD analysis of anisotropic microstructure development in cold rolled F138 stainless steel

The microstructural characteristics of deformation-processed materials highly influence their mechanical properties. For a complete characterization of a microstructure both local and global information must be gathered, which requires the combination of different analysis techniques. X-ray and Electron Backscatter Diffraction were used in the present paper to characterize the deformation induced in a cold rolled F138 austenitic stainless steel sample. The results obtained using laboratory and synchrotron X-ray sources were compared and combined with EBSD quantitative results, allowing the global and local characterization and orientation dependence of the deformation microstructure. A particular behavior was observed in the XRD data corresponding to the planes with < 220 >∥ ND, likely due to a smaller amount of defects accumulated in the crystals with that particular orientation. EBSD was used to separate the scans data into partitions and to calculate misorientation variables and parameters, showing that this behavior can be attributed to a combination of larger grain sizes, lower local boundary misorientations and dislocation densities for crystals having < 220 >∥ ND. Several conclusions, of general validity for the evaluation of microstructure anisotropy, can be extracted from the results. - Highlights: •Combined XRD and EBSD for studying microstructure gave a superb insight on anisotropic accumulation of defects. •W-H and CMWP methods were applied for checking consistency of results. •XRD showed that a smaller accumulation of defects occurred in crystals with < 220 >∥ ND. •High brilliance X-ray beam allowed to study the anisotropy of defect accumulation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Nature of Zirconia on a Copper Inverse Catalyst Under CO 2 Hydrogenation Conditions

The growing concern over the escalating levels of anthropogenic CO 2 emissions necessitates effective strategies for its conversion to valuable chemicals and fuels. In this research, we embark on a comprehensive investigation of the nature of zirconia on a copper inverse catalyst under the conditions of CO 2 hydrogenation to methanol. We employ density functional theory calculations in combination with the Grand Canonical Basin Hopping method, enabling an exploration of the free energy surface including a variable amount of adsorbates within the relevant reaction conditions. Our focus centers on a model three-atom Zr cluster on a Cu(111) surface decorated with various OH, O, and formate ligands, noted Zr 3 O x (OH) y (HCOO) z /Cu(111), revealing major changes in the active site induced by various reaction parameters such as the gas pressure, temperature, conversion levels, and CO 2 /H 2 feed ratios. Further, through our analysis, we have unveiled insights into the dynamic behavior of the catalyst. Specifically, under reaction conditions, we observe a large number of composition and structures with similar free energy for the catalyst, with respect to changing the type, number, and binding sites of adsorbates, suggesting that the active site should be regarded as a statistical ensemble of diverse structures that interconvert.

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

Achieving 5,000-h and 8,000-h Low-PGM Electrode Durability on Automotive Drive Cycles

Whereas total Pt loading in anode and cathode catalysts below 0.125 mg cm −2 is required to meet the stringent cost target for automotive fuel cell systems (FCS) for light duty vehicles, low-loaded cathode catalysts are susceptible to unacceptable aging-related performance losses at high current densities. A framework model, validated by accelerated stress test data, has identified cell voltage, relative humidity (RH) and temperature as the key operating variables that affect degradation of a high-activity d-PtCo/C cathode catalyst with 0.1 mg cm −2 Pt loading. Drive cycle simulations indicate that these can be controlled by properly selecting the minimum FCS power, compressor-expander module (CEM) turndown, and stack coolant temperature. The optimum system parameters are 4-kW e minimum power for an 80-kW e FCS, CEM turndown of 12.5, and 66 °C average coolant exit temperature that combine to limit the maximum cell voltage to 850 mV and outlet RH to 90%–100%. Depending on Pt loading, the mismatch between actual and allowable degradation for 10% power loss over 5,000-h lifetime requires the stack to be oversized by 2.4%–5%, resulting in 8.4%–41% lower Pt utilization and 7.1%–20.5% penalty in stack cost. The corresponding results for 8,000-h lifetime are 10.3%-14% stack oversizing, 23%–51.8% lower Pt utilization, and 24.1%–35.4% stack cost penalty.

08 HYDROGEN↗