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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

New Architectures for Designed Catalysts: Selective Oxidation using AgAu Nanoparticles on Colloid-Templated Silica

A highly modular synthesis of designed catalysts with controlled bimetallic nanoparticle size and composition and a well-defined structural hierarchy is shown. Exemplary catalysts—bimetallic dilute Ag-in-Au nanoparticles partially embedded in a porous SiO 2 matrix (SiO 2 –Ag x Au y )—were synthesized by the decoration of polymeric colloids with the bimetallic nanoparticles followed by assembly into a colloidal crystal backfilled with the matrix precursor and subsequent removal of the polymeric template. This work reports that these new catalyst architectures are significantly better than nanoporous dilute AgAu alloy catalysts (nanoporous Ag 3 Au 97 ) while retaining a clear predictive relationship between their surface reactivity with that of single-crystal Au surfaces. This paves the way for broadening the range of new catalyst architectures required for translating the designed principles developed under controlled conditions to designed catalysts under operating conditions for highly selective coupling of alcohols to form esters. Excellent catalytic performance of the porous SiO 2 –Ag x Au y structure for selective oxidation of both methanol and ethanol to produce esters with high conversion efficiency, selectivity, and stability was demonstrated, illustrating the ability to translate design principles developed for support-free materials to the colloid-templated structures. The synthetic methodology reported is customizable for the design of a wide range of robust catalytic systems inspired by design principles derived from model studies. Fine control over the composition, morphology, size, distribution, and availability of the supported nanoparticles was discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Elucidating the Active Site and the Role of Alkali Metals in Selective Hydrodeoxygenation of Phenols over Iron-Carbide-based Catalyst

In this study, iron-carbide-based catalysts have been explored in the selective hydrodeoxygenation (HDO) of phenol, aiming at elucidating the role of active site and alkali metal. Complementary characterization such as X-ray diffraction, X-ray photoelectron spectroscopy, high-resolution transmission electron microscopy, and scanning transmission electron microscopy coupled with electron energy loss spectroscopy, together with catalytic evaluations revealed a rapid structural reconstruction of iron carbide (Fe 3 C) catalysts, leading to a stable defective graphene-covered metallic Fe active phase (G@Fe) under reaction conditions. Further studies using different alkali metals (i.e., Na, K, and Cs) revealed that alkali metals showed negligible effect on the phase transformation of Fe 3 C. However, the reconstructed G@Fe doped with alkali metals inhibited the tautomerization, a facile reaction pathway to saturation of the aromatic ring, leading to enhanced selectivity to arene. The extent of inhibition of tautomerization or selectivity to arene was closely related to the degree of electron donation of alkali metal to Fe.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Chiral-selective etching effects on carbon nanotube growth at edge carbon atoms

We report that chemical vapor deposition (CVD) utilizing metal cluster nanoparticle catalysts is commonly used to synthesize carbon nanotubes (CNT), with oxygen-containing species such as water or alcohol included in the feedstock for enhanced yield. However, the etching effect of these additives on the growth mechanism has rarely been investigated, despite evidence suggesting that etching potentially affects the chirality distribution of product CNTs. We used quantum chemical methods to study how water-based etchant radicals (OH and H) may enhance the chiral selectivity during CVD growth using CNT cap models. Chemical reactivities of the caps with the etchant radicals were evaluated using density functional theory (DFT). It was found that the reactivities on the cap edges correlate with the chirality of the caps. Finally, these results suggest that proper selection of etchant species can provide opportunities for selective chirality control of the product CNTs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Structures of Hsp90α and Hsp90β bound to a purine-scaffold inhibitor reveal an exploitable residue for drug selectivity

Hsp90α and Hsp90β are implicated in a number of cancers and neurodegenerative disorders but the lack of selective pharmacological probes confounds efforts to identify their individual roles. Here, we analyzed the binding of an Hsp90α-selective PU compound, PU-11-trans, to the two cytosolic paralogs. We determined the co-crystal structures of Hsp90α and Hsp90β bound to PU-11-trans, as well as the structure of the apo Hsp90β NTD. The two inhibitor-bound structures reveal that Ser52, a nonconserved residue in the ATP binding pocket in Hsp90α, provides additional stability to PU-11-trans through a water-mediated hydrogen-bonding network. Mutation of Ser52 to alanine, as found in Hsp90β, alters the dissociation constant of Hsp90α for PU-11-trans to match that of Hsp90β. Our results provide a structural explanation for the binding preference of PU inhibitors for Hsp90α and demonstrate that the single nonconserved residue in the ATP-binding pocket may be exploited for α/β selectivity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Examining robustness of model selection with half-normal and LASSO plots for unreplicated factorial designs

When there are constraints on resources, an unreplicated factorial or fractional factorial design can allow efficient exploration of numerous factor and interaction effects. A half-normal plot is a common graphical tool used to compare the relative magnitude of effects and to identify important effects from these experiments when no estimate of error from the experiment is available. An alternative is to use a least absolute shrinkage and selection operation plot to examine the pattern of model selection terms from an experiment. We examine how both the half-normal and least absolute shrinkage and selection operation plots are impacted by the absence of individual observations or an outlier, and the robustness of conclusions obtained from these 2 techniques for identifying important effects from factorial experiments. As a result, the methods are illustrated with 2 examples from the literature.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Eco-Material Selection for Auto Bodies

In the last decades, majority of automakers started to include lightweight materials in their vehicles to meet hard environmental regulations and to improve fuel efficiency of their vehicles. As a result, eco-material selection for vehicles emerged as a new discipline under design for environment. This chapter will summarize methods of eco-material selections for automotive applications with more emphasis into auto-bodies. A set of metrics for eco-material selection that takes into account all economic, environmental and social factors will be developed using numerical and qualitative methods. These metrics cover products' environmental impact, functionality and manufacturability, in addition to the economic and societal factors.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Eco-Material Selection for Auto Bodies

Over the last decades, most automakers have started to include lightweight materials in their vehicles to meet stringent environmental regulations and to improve fuel efficiency of their vehicles. As a result, eco-material selection for vehicles emerged as a new discipline under design for environment. This chapter will summarize methods of eco-material selections for automotive applications with an emphasis on auto bodies. A set of metrics for eco-material selection that takes into account all economic, environmental, and societal factors will be developed using numerical and qualitative methods. These metrics cover products' environmental impact, functionality, and manufacturability, in addition to economic and societal factors.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Selection-enriched genomic loci (SEGL) reveals genetic loci for environmental adaptation and photosynthetic productivity in Chlamydomonas reinhardtii

This work demonstrates an approach to produce and select hybrid algal strains exhibiting increased photosynthetic productivity under multiple environmental conditions. This simultaneously addresses two major impediments to improving algal bioenergy production: 1) generating new genetic variants with improved performance; and 2) disentangling complex interactions between genetic and physiological factors contributing to these improvements. We pooled progeny generated from mating two environmental isolates of the green alga Chlamydomonas reinhardtii and cultured the pools under multiple environmental conditions. Strains from the outcompeting populations showed substantial (in some cases over 3 fold) increases in productivity over the parental lines under certain environments related to biomass production, including laboratory conditions as well as hyperoxia, fluctuating light, high salinity and high temperature. The results indicate that C. reinhardtii has remarkable, untapped, directed evolution capacity that may be harnessed using breeding and competition approaches. The populations were deep sequenced at multiple time points to identify “Selection-Enriched Genomic Loci” (SEGL) that accumulated in the populations, and thus likely confer increased fitness under the respective environmental conditions. With improved resolution, SEGL mapping can identify allelic combinations used for targeted breeding approaches, generating elite algal lines with multiple desirable traits, as well as to further understand the genetic and mechanistic bases of photosynthetic productivity. Increasing the photosynthetic efficiency of algae during biomass production is perhaps the most critical hurdle for economically sustainable algal based biofuels. This presents unique challenges because modifications designed to increase photosynthesis often result in decreased fitness, due to production of toxic reactive oxygen species when photosynthesis is not adequately regulated. These problems are exacerbated under natural and outdoor production environments because of the complex nature of photosynthesis and the multifaceted interactions between genetic, environmental and physiological factors. Here, we demonstrate a high throughput biotechnological screening approach that simultaneously produces algal strains with highly increased autotrophic productivity and identifies genomic loci contributing to these improvements. Our results demonstrate that Chlamydomonas reinhardtii exhibits high directed evolutionary capacity readily accessed through breeding and selection.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Short-term apartment-level load forecasting using a modified neural network with selected auto-regressive features

Residential electricity load profiles and their diversity have become increasingly important to realize the benefits of Smart or Transactive Energy Networks (TENs). An important element of TENs will be practical, accurate, and implementable residential load forecasting techniques. While there have been many approaches to short-term load forecasting, few have included forecasting for individual households, partly because the high volatility and idiosyncrasies present in individual household load data can pose significant challenges. In this study, we develop a Convolutional Long Short-Term Memory-based neural network with Selected Autoregressive Features (termed a CLSAF model) to improve short-term household electricity load forecasting accuracy by employing three strategies: autoregressive features selection, exogenous features selection, and a “default” state to avoid overfitting at times of high load volatility. We include aggregations of apartments to floor and building level, because utilities may favor transactive approaches that rely on aggregator models, e.g., a cluster of consumers as opposed to an individual. We demonstrate that the CLSAF model, by virtue of its enhanced feature representation and modest computational resources, can accomplish load forecasting in a multi-family residential building across three spatial granularities (individual apartment/household, floor, and building levels), with an accuracy improvement of up to 25% compared to a persistence model. We propose a data screening technique to characterize time-series electricity-load data. This technique is suitable for integration into a TEN ecosystem and allows one to estimate confidence levels of the load forecasts to optimize computational resources and the risks associated with uncertain forecasts.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Selective recovery of native copper from basalt tailings using alkaline glycinate solution

Mafic and ultramafic rocks present an intriguing pathway for CO 2 capture through strategic enhancements to the natural silicate weathering cycle. Simultaneously, these rock types are often hosts to appreciable amounts of metals critical to U.S. energy independence, particularly in the context of alkaline mine tailings from historical metal mining. The research and scientific prerogative, then, is to identify promising mafic and ultramafic feedstocks and conduct exploratory studies to effectively recover these critical minerals while preserving the potential for mineral carbonation. The Keweenaw Peninsula of Michigan hosts the largest native Cu reservoir within basalt in the world and experienced a rich history of Cu production spanning from pre-historic times to the mid-1900s. Today, much of the Cu mining legacy remains as mine waste tailings. In this study, we examined the Cu extractability from Keweenaw Basalt tailings using a sodium glycinate solution, in comparison with acid and sodium hydroxide leaching. Experimental results showed an 85 % Cu extraction rate using sodium glycinate as the extraction solution with negligible release of other cations from the basalt. The kinetic and extraction mechanisms of Cu selective recovery using glycinate solution were discussed using time-resolved experimental data and kinetic geochemical modeling. Theoretical estimation of carbon mineralization potential of all the existing basalt waste tailings (∼500 million tons) can reach 85.5 MMT CO 2 . A total of 0.786 MMT Cu can be recovered with sodium glycinate, with a value of 7.7 billion USD. In conclusion, this novel application of alkaline glycinate for selective Cu recovery from basalt mine tailings demonstrates the viability of selective metal recovery using a non-hazardous chemical while preserving CO 2 capture potential and presents a potential pathway toward reducing energy-related emissions and providing an unconventional domestic source of critical minerals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The effect of catholyte and catalyst layer binders on CO 2 electroreduction selectivity

Electrochemical reduction of carbon dioxide (CO 2 ) is an attractive technology for converting CO 2 to value-added chemicals by using renewably generated electricity. This work combines both experimental and theoretical analyses to investigate the role of different catalysts (Ag/Vu and SnO 2 /Vu), binder materials, and catholyte compositions on the selectivity of a CO 2 electrolysis cell to the two-electron CO 2 reduction products CO and formate. As a complementary effort, a 2D multi-physics transport model was developed to elucidate the fundamental processes and species concentrations in the cathode components. It was shown that the selectivity of CO 2 reduction to CO can change significantly when different catholyte compositions and binder materials are used, whereas the selectivity of CO 2 to formate is relatively stable across the conditions studied. These insights can be used to inform decisions regarding the electrode development and system design in CO 2 electrolyzers and ultimately contribute to scaling energy-efficient electrochemical CO 2 -reduction systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Strong Evidence of the Role of H 2 O in Affecting Methanol Selectivity from CO 2 Hydrogenation over Cu-ZnO-ZrO 2

CO 2 hydrogenation to methanol with renewable H 2 is an ideal process for coupling reduction of greenhouse gas and development of sustainable methanol economy, and Cu-ZnO-ZrO 2 is regarded as a promising catalyst for this process. Identification of the key descriptors that control the catalytic activity and selectivity is one of the most important issues for this reaction. In this work, we identify the role of water in the hydrogenation of CO 2 to methanol, which strongly affects the selectivity and yield of methanol. Our results reveal that methanol is generated via the hydrolysis of methoxy formed by the hydrogenation of formate, and the desorbed water vapor facilitates the hydrolysis of methoxy. A suitable amount of water in the feed can promote the formation of methanol. The enhancement on the water vapor diffusion in catalysts by structural and/or surface modification offers a new strategy for tuning the selectivity and yield of methanol.

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

An automated and portable method for selecting an optimal GPU frequency

Power consumption poses a significant challenge in current and emerging graphics processing unit (GPU) enabled high-performance computing systems. In modern GPUs, dynamic voltage frequency scaling (DVFS) appears to be a reliable control to regulate power consumption and performance. However, the DVFS design space is large - hence, brute-force approaches are infeasible to select the optimal frequency. Furthermore, no single frequency can be universally optimal for applications with varying computational intensities. Thus, the application's complexity and the availability of a wide range of frequency settings are a challenge in selecting the optimal frequency configuration for a given GPU workload. To that end, this paper proposes a systematic approach that consists of three steps. The feature characterization study identifies the fine-grain GPU utilization metrics that influence the power consumption and execution time of a given workload. To understand the performance, power, and energy consumption behaviors of a workload across GPU's DVFS design space, we derived analytical power and performance models using the identified fine-grain features. Here, it is shown that the same set of GPU utilization metrics can estimate both the power consumption and execution time while being agnostic of changes to frequency and input sizes. Applying a power control with the single objective of reducing power may cause performance degradation, leading to more energy consumption. A multi-objective approach is proposed to select the optimal GPU DVFS configuration for a workload that reduces power consumption with negligible degradation in performance. The evaluation was conducted using SPEC ACCEL benchmarks and three real applications - NAMD LAMMPS, and LSTM on NVIDIA GV100, GA100, and AMD MI210 GPUs. On average, real applications showed 29.6% energy savings with a performance loss of 5.2% on GA100 and 22.6% energy savings with a performance loss of 4.7% on GV100. Moreover, the proposed models are portable to real applications, GPU architectures, and vendors, and require metric collection at only the default frequency rather than all supported DVFS configurations. Additionally, we conducted a comparison between our models and the GPU assembly instructions (PTX)-based static models. The results revealed a significant reduction in the average error rates, with a decrease from 19.7% to 3.1% for power models and from 29.4% to 5.2% for performance models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

CO 2 capture from natural gas power plants using selective exhaust gas recycle membrane designs

This paper describes membrane processes to capture the CO 2 produced by combustion gas turbines in natural gas combined cycle power plants. Because combustion turbines typically use a large excess of air, the resulting turbine exhaust gas is relatively dilute (only 3–4% CO 2 ), making subsequent CO 2 capture difficult and costly. Previously, we’ve shown that a membrane process can be used to selectively recycle CO 2 to the combustion step, which significantly increases the CO 2 content in the exhaust gas. In this way, selective exhaust gas recycle (S-EGR) makes CO 2 capture energetically easier. Here, various membrane design concepts incorporating S-EGR are described and compared. Furthermore, a combination of S-EGR with non-selective exhaust gas recycle (EGR) is shown to offer advantages in reduced capital, while retaining most of the energy benefits of S-EGR alone. For all of the membrane designs analyzed, the energy and cost of capture vary with the capture rate. Generally, if flue gas compression is not used, the lowest capture cost ($\$$/tonne CO 2 ) for membranes occurs at partial capture rates of 60–70%. Of the process designs studied, the lowest cost of capture (~$44/t) is achieved by an integrated turbine/membrane design that would require changes to existing turbines.

03 NATURAL GAS↗
DOE OSTI2021

A refined design concept for sulfur-tolerant Pd catalyst supported on zeolite by shape-selective exclusion and hydrogen spillover for hydrogenation of aromatics

Sulfur poisoning of noble metal catalysts has been a major challenge for decades. This work demonstrates the superior sulfur tolerance of a hybrid zeolite-supported Pd catalyst for hydrogenation of tetralin containing benzothiophene. The hybrid catalyst consists of Pd supported on a large-pore acidic zeolite Y (Pd/HY) and a small-pore zeolite A without (Pd/HA) or with surface metal passivation by chemical vapor deposition of SiO 2 (SiO 2 -Pd/HA) and with potassium ion exchange (SiO 2 -Pd/KA). Pd/HY is very active for tetralin hydrogenation but quickly deactivates after exposure to benzothiophene at high concentration of 100 ppm sulfur. The SiO 2 -coated Pd/HA shows no activity for tetralin hydrogenation, but continues to activate H 2 and serve as a source of hydrogen spillover from Pd/HA since these metal sites are protected from thiophenic sulfur due to size-selective exclusion. Adding K ion-exchanged and SiO 2 -coated catalyst SiO 2 -Pd/KA to Pd/HY is even more effective for enhancing sulfur tolerance, both for tetralin hydrogenation and for isomerization of cis-decalin to trans-decalin in the presence of benzothiophene. The turnover frequencies (TOF) of all the catalysts are similar at the exposed sulfur/Pd atomic ratio of around 0.5. With further increase in sulfur/Pd ratio, rapid decline in TOF was observed on Pd/HY, but SiO 2 -Pd/KA + Pd/HY hybrid catalyst shows a significantly higher TOF than that over Pd/HY, even though SiO 2 -Pd/KA or SiO 2 -Pd/HA alone shows no TOF for tetralin hydrogenation. Even after high-dose poisoning at 400 ppm sulfur, the SiO 2 -Pd/KA + Pd/HY hybrid recovered activity more quickly than SiO 2 -Pd/HA + Pd/HY, while the latter in turn is much better than Pd/HY alone. These results point to the higher activity for hydrogen spillover from SiO 2 -Pd/KA where Pd metal sites are protected from not only thiophenic sulfur but also inorganic sulfur H 2 S by shape-selective exclusion. The present work further establishes the validity of shape-selective exclusion and hydrogen spillover in the design concept proposed for a sulfur-tolerant bimodal acidic zeolite-supported metal catalyst for hydrogenation of naphthalene [C.S. Song, Chemtech, 29 (1999) 26–30], and refines the design concept further for limiting the size of small pore in hybrid catalysts to~3 Å for restricting access of H 2 S but allowing entrance of H 2 . Further, this refined design concept is applicable to other supported monometallic and bimetallic catalysts.

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

Understanding hydrogen pressure control of furfural hydrogenation selectivity on a Pd(1 1 1) model catalyst

We investigate the postulate that hydrogen pressure influences the furfural hydrogenation selectivity on palladium to form decarbonylation products at low hydrogen pressures, but 2-methyl furan at higher pressures. This change is caused by co-adsorbed hydrogen changing the orientation of adsorbed furfural; low hydrogen coverages favor flat-lying furfural, higher coverages form tilted species. This was tested for hydrogenation of furfural on a Pd(1 1 1) single crystal. The product distribution agreed with the postulate, with 100% selectivity to furan and tetrahydrofuran for low hydrogen pressures, with 2-methyl furan increasing with hydrogen pressure. The origin of the effect is explored using reflection–absorption infrared spectroscopy. This showed that co-adsorbed hydrogen influenced the orientation in a way predicted by theory. It was also found that other co-adsorbates displayed similar effects implying that a range of molecules in the reaction mixture could have significant effects on the furfural selectivity.

09 BIOMASS FUELS↗
DOE OSTI2018

Selective Brookite Polymorph Formation Related to the Amorphous Precursor State in TiO 2 Thin Films

A wide variety of brookite TiO 2 synthesis methods have been published over the past several decades, but few studies discuss the underlying mechanism that stabilizes brookite over its stable counterparts, rutile and anatase. Here in this study, we investigate of the effect of pulsed laser deposition parameters on the as-deposited amorphous precursor titania thin films, which subsequently crystallize into stable and metastable TiO 2 polymorphs upon annealing. We find that oxygen pressure in the deposition chamber strongly influences the non-equilibrium state of the amorphous precursor, which ultimately allows for selective polymorph formation. Rutile forms as the dominant phase at low pO 2 < 0.1 mTorr, while anatase is favored at high pO 2 > 5 mTorr. Brookite forms primarily at intermediate pO 2 (0.5-1.0 mTorr). Controlling the amorphous structure (i.e. Ti - O bonding and polyhedral arrangement) of the precursors via oxygen deficiency is therefore likely for the selective formation of crystalline TiO 2 polymorphs from sub-stoichiometric amorphous precursors. Lastly, directing phase selectivity by manipulating the structure and internal energy of the precursor amorphous state may have tremendous potential for synthesis of metastable crystalline phases that exhibit more desirable properties in comparison to their stable counterparts.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Protecting groups in insertion chemistry: Site-selective positioning of lithium ions in intercalation hosts

The expanding toolbox of functionalization chemistries for selectively installing moieties on specific sites of a substrate underpins almost all modern organic and biochemical syntheses. Likewise, the installation of mobile guest ions in specific interstitial sites and their transport along specific diffusion pathways forms the basis of modern lithium (Li)-ion battery electrodes. Many insertion hosts afford a diverse range of accessible interstitial sites. However, site-selective positioning of cations with atomic precision remains almost entirely unexplored. Here, we show that by deciphering site preferences of co/pre-intercalated cations, we can position Li ions in four distinct sites within a 1D ζ-V 2 O 5 insertion host. The use of topochemistry to effect single-crystal-to-single-crystal transformations enables atomic-resolution mapping of the selective positioning of Li ions through single-crystal X-ray diffraction. Here we image interstitial sites that are occupied at high depths of discharge, thereby obtaining unprecedented structural insight into “fully stuffed” frameworks critical for the realization of high-energy-density intercalation electrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗