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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Notable Contributions of Aerosols to the Predictability of Hail Precipitation

There is an increasing concern of the uncertainty produced by aerosols in forecasting precipitation including hail precipitation. This study provides an assessment of the uncertainties in hail and total precipitation by varying initial cloud condensation nuclei (CCN) number concentration (CCNC) and meteorological conditions based on 1200 cloud-resolving simulations of an idealized hailstorm. Although the meteorological perturbations produce large uncertainties in hail precipitation (including rate and maximum hail size) as well as total precipitation, varying CCNC by an order of magnitude can cause even larger uncertainties, especially pairing with the thermodynamics perturbation (i.e., potential temperature and water vapor). Changing CCNC modifies the predictability of hail precipitation, with a higher predictability in moderate polluted environments compared with the very clean and polluted environments. Increasing CCNC consistently leads a non-monotonic response of ensemble mean with an optimal CCNC for hail precipitation but a monotonic decreasing response of total precipitation with the various meteorological perturbations, meaning the initial meteorological perturbations does not qualitatively change the aerosol effects. Investigation with 10-fold reduced initial perturbation further supports the large CCN effects are not dependent of metrological perturbations. The findings suggest the importance of considering CCN effects in severe weather simulations and forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

An investigation of the physical and chemical changes of Pd nanoparticles on carbon supports in response to the release of hydrogen from aqueous formate solutions

Palladium nanoparticles on carbon supports (Pd/C) are effective for catalyzing hydrogen release from aqueous formate solutions but typically suffer from a gradual decrease of activity. This study finds two primary factors influencing activity: (i) the number of available surface Pd sites, and (ii) metal-support interactions which depend on the nature of the C support. We propose that the Pd/C catalyst is structure insensitive and undergoes Ostwald ripening to yield an active ‘conditioned’ catalyst with dispersion plateauing between ca. 15–20 %. Contrary to earlier studies, in-situ XANES experiments show that PdO is not an active catalyst for formate dehydrogenation. Calcination of Pd/C before dehydrogenation increases the catalytic activity which suggests a beneficial, albeit temporary, modification of the metal support interaction. N-containing supports minimize nanoparticle growth and also increase activity through a metal-support interaction. In conclusion, these findings advance our understanding of catalyst evolution and stability in formate dehydrogenation systems.

Formate dehydrogenation↗
DOE OSTI2022

In Situ Studies of the Formation of MoP Catalysts and Their Structure under Reaction Conditions for Higher Alcohol Synthesis: The Role of Promoters and Mesoporous Supports

Three formulations of a molybdenum phosphide (MoP) catalyst system were characterized for the higher alcohol synthesis (HAS) reaction using in situ X-ray absorption spectroscopy (XAS) and X-ray diffraction (XRD), monitoring the chemical phase evolution during activation and under reaction conditions. Here, the in situ study herein provides important insights into the effect of the support and of K that lead to high performance in HAS for K-promoted MoP supported on carbon, as evidenced by previous studies (ethanol selectivity: 29%; conversion: 5%). During the activation process, XAS shows that the carbon-supported samples reduce and reach a highly crystalline state at a lower temperature than the SBA-15-supported sample, indicating a substantial difference in catalyst activation. After activation, the samples are introduced to relevant reaction conditions resulting in spectra fairly similar to one another. XRD results corroborate the difference in the degree of crystallinity of these samples, in alignment with the XAS, and reveal the formation of crystalline potassium pyrophosphate (K 4 P 2 O 7 ) during the activation period of the K-promoted samples. This K 4 P 2 O 7 phase remains present under reaction conditions. Taken together, these results provide insights into the roles played by the carbon support and K promotion, connecting activity to electronic and crystal structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Prediction of Substrate Distortion in Powder DED Using Finite Element Model

Abstract Leveraging the capabilities of both additive and subtractive manufacturing to repair tooling and other high value items can result in significant cost and time saving opportunities. However, when dimensional accuracy of the repaired component must be held within a specified tolerance, distortion of the component induced during repair can lead to an out of specification final component. This work presents simulation of a novel method to mitigate part distortion using sacrificial support structures. A blown powder directed energy deposition system was utilized for deposition of sacrificial support structures and clad surface depositions. Sacrificial support structures were deposited on the underside of the substrate with varying geometries prior to clad surface depositions. A finite element model was developed and verified using experimental results. The simulation and experimental control results were found to match within 6%. It has been shown that simulation can be used to predict effects of sacrificial support structures on substrate distortion in a blown powder directed energy deposition process.

Burl, Alan G.↗
DOE OSTI2019

Current Role of the Total Artificial Heart in the Management of Advanced Heart Failure

The total artificial heart (TAH) is a form of mechanical circulatory support that involves resection of the native ventricles followed by placement of a device that can restore total pulmonary and systemic flow. Given the increasing burden of congestive heart failure and cardiovascular disease, the number of people in need of cardiac replacement therapy will continue to grow. Despite aggressive efforts to expand the donor pool, the number of heart transplants in the United States (US) has plateaued at less than 3000 per year. In addition, there is increasing recognition of the long-term complications of current generation left ventricular assist devices such as progressive aortic insufficiency, complications related to blood trauma, and both early and delayed right ventricular failure. These factors may serve to expand the role of the TAH in the treatment of patients with end-stage heart failure particularly if new generation devices are developed that are durable, have an improved safety profile, and are totally implantable. Purpose of Review: To review the role and current evidence of the use of the TAH in the management of advanced heart failure and discuss development of recent TAHs that may have an impact on the field in the near future. Recent Findings: Many patients that receive a heart transplant are bridged with a mechanical support device, most commonly a left ventricular assist device (LVAD). However, there is a small subset of patients with profound biventricular (BV) failure or structural abnormalities that preclude LVAD placement, who will require support with a biventricular assist device (BiVAD) or TAH. There are numerous studies showing the efficacy of the TAH in bridging to transplantation. Also, recent studies have shown equal rates of bridging to transplantation between patients receiving a TAH compared to a BiVAD. However, BiVAD support has a higher incidence of stroke in addition to complications related to the native heart such as arrhythmias and valve dysfunction. Currently, there are multiple new generation artificial hearts in both preclinical development and in clinical trials for both bridge to transplant and destination therapy. Summary: TAH have been shown to be effective for circulatory support in select patients with end-stage heart failure. Current LVADs are associated with significant long-term complications related to retention of the native heart and pump design. Many of these complications may be addressed by the increased use of cardiac replacement therapy, i.e., total artificial hearts. Multiple generations of both pulsatile and advanced design continuous flow TAH are under development which have the potential to expand the role of TAHs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Recombination between 13 C and 2 H to Form Acetylide ( 13 C 2 2 H – ) Probes Nanoscale Interactions in Lipid Bilayers via Dynamic Secondary Ion Mass Spectrometry: Cholesterol and GM 1 Clustering

Although it is thought that there is lateral heterogeneity of lipid and protein components within biological membranes, probing this heterogeneity has proven challenging. The difficulty in such experiments is due to both the small length scale over which such heterogeneity can occur, and the significant perturbation resulting from fluorescent or spin labeling on the delicate interactions within bilayers. Atomic recombination during dynamic nanoscale secondary ion imaging mass spectrometry (NanoSIMS) is a non-perturbative method for examining nanoscale bilayer interactions. Atomic recombination is a variation on conventional NanoSIMS imaging, whereby an isotope on one molecule combines with a different isotope on another molecule during the ionization process, forming an isotopically enriched polyatomic ion in a distance-dependent manner. In this work, we show that the recombinant ion, 13 C 2 2 H – , is formed in high yield from 13 C- and 2 H-labeled lipids. The low natural abundance of triply labeled acetylide also makes it an ideal ion to probe GM 1 clusters in model membranes and the effects of cholesterol on lipid–lipid interactions. We find evidence supporting the cholesterol condensation effect as well as the presence of nanoscale GM 1 clusters in model membranes.

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

Understanding the Origin of Negative Temperature Dependence and Activity of N-Coordinated Cobalt Sites During Ethylene Dimerization

The on-demand production of short-chain linear alpha olefins (LAOs; C4-C8) via C2H4 dimerization and oligomerization is industrially attractive, prompting extensive research on designing active, selective, and stable catalysts for industrial use. Cobalt supported on ammoniated carbon (Co(NH3)x/C) catalysts have shown remarkable activity and selectivity in this process. However, critical aspects such as the active phase, active site structure, the role of the catalyst support, cobalt loading effects, and the inverse correlation of the reaction rate with temperature remain inadequately understood. This study systematically explores these factors using a combination of steady-state differential catalytic tests, in situ molecular characterization including diffuse reflectance UV-Vis (DR-UV-Vis), Infrared, and Raman spectroscopies, and ex situ X-ray diffraction (XRD) and high annular aberration-corrected dark field transmission electron microscopy (HAADF-STEM). Various supports (SiO2, Al2O3, NH4-ZSM-5, g-C3N4, and C) and cobalt loadings (1.0-3.0 Co nm-2) were studied to determine the optimal catalyst composition and identify the active phase and sites. Carbon-supported catalysts uniquely produce C4-8 LAOs during C2H4 dimerization, with site-time-yield remaining constant (~10-3 s-1) for 1.0-4.0 Co nm-2 at prolonged reaction times (24-48?h time-on-stream). At higher loadings of 6.0 Co nm-2, the formation of crystalline CoO and Co3O4 phases reduces catalytic activity and LAO selectivity. Our findings show that active catalysts lack crystalline cobalt oxides and instead feature dispersed Co2+ sites, tetra-coordinated to a mix of N/NH3 and O/H2O ligands, which catalyze C2H4 dimerization via the Cossee-Arlman mechanism, exhibiting 1st order dependence on C2H4 concentration. The observed inverse rate-temperature correlation is attributed to compensation effects (i.e., presence of Cremer-Constable relationship) linked to changes in adsorption enthalpic and entropic factors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Bell inequalities in 2-2 scattering

We consider Bell inequalities in 2-2 scattering of photons, gravitons, fermions, and pions. We choose measurement settings that give maximum Bell violation for maximally entangled states and calculate the relevant Bell inequalities for these processes. For photon scattering at low energies, quantum electrodynamics exhibits Bell violation for all scattering angles except for a small transverse region. This leads to a fine-tuning problem. Incorporating a light axion/axionlike particle removes the fine-tuning problem and constrains the axion-coupling–axion-mass parameters. Allowing for graviton exchange and demanding Bell violation in photon scattering, we find that the weak-gravity conjecture is satisfied. Quantum gravity effects on axion coupling is discussed. For 2-2 graviton scattering, we find that CEMZ bounds allow for, at most, small Bell violations. Restriction on the Weinberg angle is found by demanding Bell violation in Bhabha scattering. We use recent $S$-matrix bootstrap data for pions and photons to study the Bell parameter in the space of allowed $S$-matrices. In the photon case, we study the Bell parameters as a function of energy and find support for the effective field theory observations. We discuss Bell parameter for pion $S$-matrices, which are qutrits. For pions, we find that there is a minimization of a suitable Bell parameter for $S$-matrices which exhibit Regge behavior.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Elucidating the role of surface species in CO oxidation catalyzed by boron nitride nanotube supported transition metal oxides

Boron nitride nanotube (BNNT) is considered a highly promising catalyst support due to its outstanding thermal stability and chemical inertness. These characteristics make BNNT an attractive alternative for high-temperature applications. However, most studies to date have focused on incorporating platinum group metals (PGMs) to achieve high activity. Although BNNT-supported PGM catalysts are highly effective, their scarcity and high cost hinder widespread use in industrial processes. In this study, BNNT-supported transition metal oxides (TMO x /BNNT; TM = Fe, Co, Ni, and Cu) catalysts were investigated, and CO oxidation was applied as a model reaction to evaluate their catalytic performance. Several characterization techniques, including SEM-EDX, TEM, SXRD, H 2 -TPR, and XPS, were employed to examine their physicochemical properties. Notably, the particle size of the metal oxides differed significantly depending on the metal type. This variation is primarily attributed to the inherent metal–support interactions and the thermodynamic stability of each oxide during synthesis. These properties also affected catalytic activity, and various parameters, such as oxygen mobility and redox behavior, played important roles in determining performance. Finally, in situ DRIFTS, CO-TPSR, reaction-order analysis, and 18 O 2 isotope-labeling experiment were used to investigate the reaction mechanism. In conclusion, the findings provide insights into the design of cost-effective BNNT-supported catalysts and highlight their potential applicability in oxidation reactions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

On the Investigation of Phase Fault Classification in Power Grid Signals: A Case Study for Support Vector Machines, Decision Tree and Random Forest

In monitoring the power grid, an ability to differentiate between fault types is essential to ensuring electrical safety. Accordingly, this study introduces a fault detection and classification method by considering different machine learning (ML) and feature extraction (FE) methods combinations. Specifically, the proposed method is established in two classification layers; the first layer determines the fault, and the second layer distinguishes the type of fault. Based on the proposed system model, this study seeks to determine the influential data attributes in a power grid signal using FE methods, including fast Fourier transform, power spectral density (PSD), auto-correlation, and wavelet transform (WT). A cross-comparison of the effectiveness of the Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF) is also performed to accomplish the classification layers of the proposed method. The designed algorithm is analyzed under the various combinations of FE and ML methods, and outcomes are presented by considering the trade-off between computational complexity and prediction accuracy. The results reveal that the RF-based ML algorithm shows the most accurate classification performance with PSD, and the most time-saving of the models is the DT WT. Also, SVM emerges superior on a subsequent test of the simulated models on real-world signals.

Galbraith, Kelli↗
DOE OSTI2025

Optimization of Ag Electrocatalyst Performance for CO2 to CO Conversion: Pairing Atomic Simulations with Experiments

Density-functional theory- based calculations that complement our series of experimental efforts on optimizing Ag electrocatalyst performance for CO2 to CO conversion were presented. Three key findings are drawn out from the combined UHV surface science, STM and electrochemical measurements: (1) Using a series of Ag nanoparticles with 2-6 nm average diameters, CO2 reduction reaction (CO2RR) activity increases, with particle between 2 nm and ∼4 nm demonstrating the highest combination of activity and selectivity; (2) Electronic metal−support interactions (EMSIs) between Ag and C dramatically improve CO2RR performance as evidenced by a scaling relationship between particle size and the relative Ag−C EMSIs strength, which improves the CO2-to-CO Faradaic efficiency of sub-2 nm Ag particles from 2 to ∼100% and increases the CO turnover frequency ∼15-fold compared with similarly sized bare Ag particles; (3) The performance Ag electrocatalysts is improved when supported on S-doped C materials. Computational modeling of 1−10 nm Ag particles predicts a nearly identical size-dependent trend with maximum CO2RR activity predicted for 3.7nm particles. The calculations support the promotional effect of C materials, showing a large charge transfer of 1.02 e from Ag clusters to defective C and a 0.41 eV less endergonic step of forming COOH intermediate on Ag/defective-C compared to the Ag/C system. Calculations indicate a more favorable energetic pathway of CO2-to-CO at the C-S-Ag interface, consistent with experiments.

CO2 utilization↗
DOE OSTI2021

Effect of Catalyst and Catalyst Layer Composition on Catalyst Support Durability

Polymer electrolyte membrane fuel cells (PEMFCs) are efficient, zero-emission engines for the automotive sector. However, cost and durability are major barriers for the commercialization of PEMFCs. Degradation of the carbon support in the cathode catalyst layer due to high potential excursions caused by unmitigated events like H 2 starvation, or start-up/shutdown are still a major durability issue in PEMFCs. Catalyst support durability was studied by accelerated stress tests (ASTs) that included repeated potential cycling from 1.0 to 1.5 V. The effect of catalyst layer composition on carbon corrosion was studied using membrane electrode assemblies with different catalysts (Pt, PtCo), catalyst composition (catalyst wt.%, supports), ionomer composition (loading, and equivalent weights). The corrosion of the carbon support is similar between Pt and PtCo catalysts. However, the performance degradation rate is higher for the alloy catalysts due to differences in catalyst particle size and the transition metal’s leaching accelerating the performance degradation. The carbon loss is lower for catalysts with lower initial carbon loading (or higher catalyst wt.%), which is better for durability. However, the cumulative loss of carbon is identical for electrodes with the same catalyst support irrespective of catalyst and ionomer composition in the catalyst layer.

25 ENERGY STORAGE↗
DOE OSTI2023

Modeling plasma-induced surface charge effects on CO 2 activation by single atom catalysts supported on reducible and irreducible metal oxides

Abstract The accumulation of negative surface charge on catalytic surfaces in the presence of low-temperature plasma (LTP) could influence catalytic performance. However, it is difficult to disentangle the role of surface charging and other LTP catalytic effects in experiment. Herein, we use density functional theory (DFT) modeling to understand the effect of plasma-induced surface charging on CO 2 activation by atomically dispersed single atom (SA) catalysts on both reducible and irreducible metal oxide supports. We model CO 2 adsorption strength and CO 2 dissociation barriers for Co 1 , Ni 1 , Cu 1 , Rh 1 , Pd 1 , and Ag 1 SAs on both reducible and irreducible supports, namely, CeO 2 (100), TiO 2 (101), and γ -Al 2 O 3 (110), to elucidate trends. We find that accumulated surface charge on the SA increases the CO 2 adsorption strength and decreases the CO 2 dissociation barrier for all studied SA/support combinations. For both charged and uncharged (neutral) systems, SAs on the reducible CeO 2 (100) support generally adsorb CO 2 more weakly compared to when on irreducible supports like γ -Al 2 O 3 (110). SAs on γ -Al 2 O 3 (110) typically have larger barriers for CO 2 dissociation for both charged and uncharged systems compared to TiO 2 (101) and CeO 2 (100). The magnitude of surface charging effects on CO 2 binding energies and dissociation barriers depends sensitively on both the SA and the support. In some cases, the CO 2 activation trends qualitatively change between neutral and charged systems for a fixed SA across different supports. This DFT modeling study demonstrates that surface charging should be considered in strong electric fields because it can have a large effect on molecule adsorption and bond-breaking on catalytic surfaces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Deploying Automation Technology Supporting Packaging and Transportation Operations

Various United States Department of Energy (DOE) sites are investigating the deployment of robotics to provide safer, effective, and more efficient operations. By implementing robotics in packaging and transportation operations, improvements toward production efficiency, worker ergonomics, radiological dose reduction, and security assurance can be realized. Robotic Systems must be designed and implemented in concert with a facility’s safety basis, classification, and security constraints, while improving overall operational effectiveness. The desired robotic implementation should provide a path to potential long-term cost savings, reduce/eliminate hazardous conditions and radiological exposure, while improving quality and reliability of an operation process. The Savannah River Site (SRS), a DOE Site located in Aiken South Carolina, has initiated several large scale projects supporting future nuclear material disposition activities. Incorporation of automation and robotic equipment in system designs will support effective and efficient material handling operations, including container movements and packaging activities. Robotic systems will execute tasks that are precise, procedural and integrated with control systems to verify and record data for material inventory and historical archiving. An overview of the current robotic system development to perform receipt inspection, packaging, storage and shipment preparation activities of designated Type A and B shipping packages will be presented.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Advances in versatile nanoscale catalyst for the reductive catalytic fractionation of lignin

In the past five years, biomass derived-biofuel and biochemicals were widely studied both in academia and industry as a promising alternative to petroleum. In this review article, the latest progress of the synthesis and fabrication of porous nano-catalysts that are used in catalytic transformations involving hydrogenolysis of lignin is reviewed in terms of their textural property, catalytic activity, and stability. A particular emphasis is dedicated to the catalyst design for the hydrogenolysis of lignin and/or lignin model compounds. Furthermore, the effects of different supports on the lignin hydrogenolysis/hydrogenation are discussed in detail. Finally, the challenges and future opportunities of lignin hydrogenolysis over nanomaterials supported catalysts are also presented.

09 BIOMASS FUELS↗
DOE OSTI2025

Hydraulic constraints to stomatal conductance in flooded trees

Stomatal closure is a pervasive response among trees exposed to flooded soil. We tested whether this response is caused by reduced hydraulic conductance in the soil-to-leaf hydraulic continuum (k total ), and particularly by reduced root hydraulic conductance (k root ), which has been widely hypothesized. We tracked stomatal conductance at the leaf level (g s ) and canopy scale (G s ) along with physiological conditions in two temperate tree species, Magnolia grandiflora and Quercus virginiana, that were subjected to flood and control conditions in a greenhouse experiment. Flooding reduced g s , G s , k root and k total . Path analysis showed strong support for direct effects of k total on g s and for flood duration on k total , but not k root on k total . A process-based model that accounted for the k total reduction predicted the timeseries of G s in flood and control treatment trees reasonably well (predicted versus observed G s R 2 = 0.80 and 0.51 for M. grandiflora and Q. virginiana, respectively). However, accounting only for k root reduction in flooded trees was insufficient for predicting observed G s reduction. Together, these results suggest that hydraulic constraints were not limited to roots and highlight the need to account for flooding effects on k total when projecting forest ecosystem function using process-based models.

Plant stress↗
DOE OSTI2026

Ten questions concerning Large Language Models (LLMs) for building applications

Large Language Models (LLMs) are emerging as powerful AI tools capable of transforming how building information is collected, processed, analyzed, and applied across diverse research areas. Their capabilities can help building operators, facility managers and other stakeholders such as designers, architects and engineers by providing actionable insights for decision-making across planning, construction, operations, and maintenance of buildings and facilities. This paper explores ten key questions concerning the role of LLMs in shaping sustainable, intelligent, and human-centric buildings. From fundamental definitions to advanced applications, we examine how LLMs facilitate decision-making across the life cycle of buildings and energy systems. LLMs can enhance life cycle assessments (LCA), building energy simulations, and real-time data integration, empowering more efficient and adaptive human-AI environments. They can also contribute to streamlining regulatory compliance, improving post-occupancy evaluations, and fostering more inclusive and participatory design processes. Additionally, this paper addresses the ethical challenges posed by LLMs, such as bias, data privacy, and environmental impacts, and explores their potentials in advancing intelligent digital twins (DT) for ongoing building operations and maintenance. Built upon our applied research using LLMs and the review of tools, datasets, and research gaps, we provide a forward-looking perspective on how LLMs can drive innovation, collaboration, and productivity in the built environment while supporting ethical and effective implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗