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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Accelerated Steam Methane Reforming by Dynamically Applied Charges

Catalyst design has traditionally focused on tuning active site properties to optimally bind reaction intermediates and balance the kinetic requirements of multiple competing chemical processes, as necessitated by the Sabatier principle. It has recently been proposed that for reactions following certain potential energy landscapes, the activity limit imposed by the Sabatier principle may be overcome by using programmed oscillations of surface electron density at the timescales of surface reactions (i.e., “catalytic resonance”). Here, we use a combination of density functional theory (DFT) simulations and transient kinetic models (TKMs) to simulate the kinetics of steam methane reforming (SMR) on Ru(211) surfaces under statically and dynamically applied charges. DFT-calculated binding energies of SMR intermediates and transition states exhibit strong sensitivity to positively applied charges and follow unique scaling relationships that deviate from linear periodic trends across transition metals. Our simulations demonstrate that applying a small positive charge to Ru dramatically enhances the steady-state turnover frequency (TOF) of SMR by up to 5 orders of magnitude above the TOF observed over neutral Ru. Thus, statically charging Ru catalysts may be an effective strategy to lower the temperature requirements for SMR. Dynamic square-wave oscillations in charge resulted in SMR catalytic resonance with an onset frequency f ∼ 106 Hz and the corresponding average TOFs exceeding the statically charged Ru surface by an additional 15%. Here, based on sensitivity analyses performed for the two end points of oscillation, we propose that dynamic TOF improvement beyond the Sabatier maximum can be expected when the system oscillates between two kinetic regimes that are uniquely controlled by distinct elementary steps.

Catalysts↗
DOE OSTI2026

Unlocking plant-microbial interactions in deep Mollisols in the Midwestern US: Linking depth gradients in roots, microbial activity, and soil carbon in agroecosystems

Deep-rooted plants may build soil carbon (C) stocks, but most research has focused on shallow soils, leaving gaps in our understanding of how shifts in the balance between decomposition and C inputs drive soil C accumulation with depth. Thus, our objectives were to: (1) link depth gradients in root biomass with microbial activity and soil C stocks down to 1 m, and (2) examine the potential of simple C inputs to prime soil C across depths. To this end, we dug 5 quantitative soil pits in Argiudolls under mature perennial miscanthus plots in the SoyFACE Farm (Champaign-Urbana, IL). We added 13 C labeled glucose to our soils to determine the fate of simple C inputs with depth. We found that fine root biomass, total soil C, mineral-associated organic C (MAOC), particulate organic C (POC), and microbial activity (as measured by potential enzyme activity) declined with depth. POC declined more rapidly than MAOC, resulting in an increase in the ratio of MAOC-to-POC. Root biomass, enzyme activity (either acid phosphatase or n-acetyl-glucosaminadase) activity, and microbial respiration explained 74% and 38% of the variability in soil total C and MAOC, respectively, while POC was dependent on root biomass and microbial respiration (47%). Although the incorporation of simple 13 C inputs into MAOC was similar across depths, these inputs led to greater net MAOC losses in shallow soils than in deeper soils between 50 and 100 cm. The divergent impact of simple C inputs across depths may suggest that MAOC in shallow soils is more susceptible to priming losses, while C inputs into deep soils may instead be more persistent. Collectively, our results suggest that depth gradients in soil C stocks represents a balance between inputs, decomposition, and microbial necromass production and that increases in root C inputs by deep-rooted plants may have the potential to build stable MAOC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

BONCAT-FACS-Seq reveals the active fraction of a biocrust community undergoing a wet-up event

Determining which microorganisms are active within soil communities remains a major technical endeavor in microbial ecology research. One promising method to accomplish this is coupling bioorthogonal non-canonical amino acid tagging (BONCAT) with fluorescence activated cell sorting (FACS) which sorts cells based on whether or not they are producing new proteins. Combined with shotgun metagenomic sequencing (Seq), we apply this method to profile the diversity and potential functional capabilities of both active and inactive microorganisms in a biocrust community after being resuscitated by a simulated rain event. We find that BONCAT-FACS-Seq is capable of discerning the pools of active and inactive microorganisms, especially within hours of applying the BONCAT probe. The active and inactive components of the biocrust community differed in species richness and composition at both 4 and 21 h after the wetting event. The active fraction of the biocrust community is marked by taxa commonly observed in other biocrust communities, many of which play important roles in species interactions and nutrient transformations. Among these, 11 families within the Firmicutes are enriched in the active fraction, supporting previous reports indicating that the Firmicutes are key early responders to biocrust wetting. We highlight the apparent inactivity of many Actinobacteria and Proteobacteria through 21 h after wetting, and note that members of the Chitinophagaceae, enriched in the active fraction, may play important ecological roles following wetting. Based on the enrichment of COGs in the active fraction, predation by phage and other bacterial members, as well as scavenging and recycling of labile nutrients, appear to be important ecological processes soon after wetting. To our knowledge, this is the first time BONCAT-FACS-Seq has been applied to biocrust samples, and therefore we discuss the potential advantages and shortcomings of coupling metagenomics to BONCAT to intact soil communities such as biocrust. In all, by pairing BONCAT-FACS and metagenomics, we are capable of highlighting the taxa and potential functions that typifies the microbes actively responding to a rain event.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

High-temperature nanoindentation creep studies on castable and sintered nanostructured low-activation ferritic-martensitic alloys

In this article, we present the creep characteristics of two reduced activation ferritic-martensitic steels of identical starting compositions formed by different fabrication routes: a nanostructured ferritic alloy commonly referred to as a castable nanostructured alloy (CNA) and a sintered nanostructured alloy (SNA) variant. Through a series of nanoindentation experiments spanning a temperature range of 25 °C to 650 °C, with a maximum load of 100 mN, we find creep behaviors in the cast and sintered materials to be remarkably similar. The creep stress exponent (n) for CNA and SNA were found to be in the range of 8–35 and the activation volume was ∼14–42b 3 , underscoring a dominance of dislocation-mediated mechanisms in both alloys. Notably, we observed a decline in the creep stress exponent with increasing temperature, attributable to the heightened influence of thermally activated dislocations. This phenomenon suggests a potential transition in the deformation mechanism towards a thermally activated dislocation climb process, significantly impacting the observed creep behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Near-Zero Power MOF-Based Sensors for NO 2 Detection

Detection and capture of toxic nitrogen oxides (NO x ) is important for emissions control of exhaust gases and general public health. The ability to directly electrically detect trace (0.5–5 ppm) NO 2 by a metal–organic framework (MOF)-74-based sensor at relatively low temperatures (50 °C) is demonstrated via changes in electrical properties of M-MOF-74, M = Co, Mg, Ni. The magnitude of the change is ordered Ni > Co > Mg and explained by each variant's NO 2 adsorption capacity and specific chemical interaction. Ni-MOF-74 provides the highest sensitivity to NO 2 ; a 725× decrease in resistance at 5 ppm NO2 and detection limit <0.5 ppm, levels relevant for industry and public health. Furthermore, the Ni-MOF-74-based sensor is selective to NO 2 over N 2 , SO 2 , and air. Linking this fundamental research with future technologies, the high impedance of MOF-74 enables applications requiring a near-zero power sensor or dosimeter, with the active material drawing <15 pW for a macroscale device 35 mm 2 with 0.8 mg MOF-74. Finally, this represents a 10 4 –10 6 × decrease in power consumption compared to other MOF sensors and demonstrates the potential for MOFs as active components for long-lived, near-zero power chemical sensors in smart industrial systems and the internet of things.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Rapid Polyolefin Hydrogenolysis by a Single‐Site Organo‐Tantalum Catalyst on a Super‐Acidic Support: Structure and Mechanism

Abstract The novel electrophilic organo‐tantalum catalyst AlS/TaNp x ( 1 ) (Np=neopentyl) is prepared by chemisorption of the alkylidene Np 3 Ta=CH t Bu onto highly Brønsted acidic sulfated alumina (AlS). The proposed catalyst structure is supported by EXAFS, XANES, ICP, DRIFTS, elemental analysis, and SSNMR measurements and is in good agreement with DFT analysis. Catalyst 1 is highly effective for the hydrogenolysis of diverse linear and branched hydrocarbons, ranging from C2 to polyolefins. To the best of our knowledge, 1 exhibits one of the highest polyolefin hydrogenolysis activities (9,800 (CH 2 units) ⋅ mol(Ta) −1 ⋅ h −1 at 200 °C/17 atm H 2 ) reported to date in the peer‐reviewed literature. Unlike the AlS/ZrNp 2 analog, the Ta catalyst is more thermally stable and offers multiple potential C−C bond activation pathways. For hydrogenolysis, AlS/TaNp x is effective for a wide variety of pre‐ and post‐consumer polyolefin plastics and is not significantly deactivated by standard polyolefin additives at typical industrial concentrations.

Lai, Qingheng↗
DOE OSTI2023

AL4GAP: Active learning workflow for generating DFT-SCAN accurate machine-learning potentials for combinatorial molten salt mixtures

Machine learning interatomic potentials have emerged as a powerful tool for bypassing the spatiotemporal limitations of ab initio simulations, but major challenges remain in their efficient parameterization. We present AL4GAP, an ensemble active learning software workflow for generating multicomposition Gaussian approximation potentials (GAP) for arbitrary molten salt mixtures. The workflow capabilities include: (1) setting up user-defined combinatorial chemical spaces of charge neutral mixtures of arbitrary molten mixtures spanning 11 cations (Li, Na, K, Rb, Cs, Mg, Ca, Sr, Ba and two heavy species, Nd, and Th) and 4 anions (F, Cl, Br, and I), (2) configurational sampling using low-cost empirical parameterizations, (3) active learning for down-selecting configurational samples for single point density functional theory calculations at the level of Strongly Constrained and Appropriately Normed (SCAN) exchange-correlation functional, and (4) Bayesian optimization for hyperparameter tuning of two-body and many-body GAP models. Here, we apply the AL4GAP workflow to showcase high throughput generation of five independent GAP models for multicomposition binary-mixture melts, each of increasing complexity with respect to charge valency and electronic structure, namely: LiCl–KCl, NaCl–CaCl 2 , KCl–NdCl 3 , CaCl 2 –NdCl 3 , and KCl–ThCl 4 . Our results indicate that GAP models can accurately predict structure for diverse molten salt mixture with density functional theory (DFT)-SCAN accuracy, capturing the intermediate range ordering characteristic of the multivalent cationic melts.

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

Rapid Polyolefin Hydrogenolysis by a Single‐Site Organo‐Tantalum Catalyst on a Super‐Acidic Support: Structure and Mechanism

The novel electrophilic organo-tantalum catalyst AlS/TaNp x (1) (Np=neopentyl) is prepared by chemisorption of the alkylidene Np 3 Ta=CH t Bu onto highly Brønsted acidic sulfated alumina (AlS). Here, the proposed catalyst structure is supported by EXAFS, XANES, ICP, DRIFTS, elemental analysis, and SSNMR measurements and is in good agreement with DFT analysis. Catalyst 1 is highly effective for the hydrogenolysis of diverse linear and branched hydrocarbons, ranging from C2 to polyolefins. To the best of our knowledge, 1 exhibits one of the highest polyolefin hydrogenolysis activities (9,800 (CH 2 units) ⋅ mol(Ta) −1 ⋅ h −1 at 200 °C/17 atm H 2 ) reported to date in the peer-reviewed literature. Unlike the AlS/ZrNp 2 analog, the Ta catalyst is more thermally stable and offers multiple potential C−C bond activation pathways. For hydrogenolysis, AlS/TaNp x is effective for a wide variety of pre- and post-consumer polyolefin plastics and is not significantly deactivated by standard polyolefin additives at typical industrial concentrations.

03 NATURAL GAS↗
DOE OSTI2023

Laboratory investigation of hydraulic fracturing in granitic rocks using active and passive seismic monitoring

SUMMARY Knowledge of the fracturing processes can be important for the optimization of pressurized fluid injection operations in the deep underground rock mass. Active and passive seismic monitoring techniques have been used in the field for tracking or mapping the propagating hydraulic fracture. Although both these monitoring techniques provide valuable information about the generated fracture network, it is difficult for either technique to comprehensibly identify the different processes associated with hydraulic fracturing. The combined active and passive monitoring has the potential for better characterization of the complex hydraulic fracturing phenomena. In this study, laboratory hydraulic fracturing experiments with combined active and passive seismic monitoring were conducted on true triaxially loaded Barre granite cubes with different fluid injection rates. The seismic inelastic fracturing was detected by 16 passive acoustic emission sensors, where 3678 and 2370 seismic source events were detected for the high and low injection rate experiments, respectively. For active monitoring, strong variations in the attributes of signals were observed which were transmitted through four source–receiver pairs, placed both perpendicular and parallel to the generated hydraulic fracture. Positive velocity changes were observed for active sensor pairs with ray paths passing through the generated hydraulic fracture indicating fluid permeation, whereas isolated dry deformation was characterized by a slight but permanent velocity decrease. Compared to velocity, the energy of the active signals was 1–2 orders of magnitude more sensitive to different hydraulic fracturing processes. However, the sensitivity and signatures of the active signal attributes were found to be dependent on the frequency range and direction of ray path with respect to the location of the generated fracture network. Using the coupled evaluation of the active and passive signals we were able to systematically identify various hydraulic fracturing processes including: (1) aseismic deformation, (2) fracture initiation and fluid permeation, (3) pressure build-up, (4) fracture propagation and (5) pressure release and leak-off. The results of this study showed that combining the respective advantages of active and passive seismic techniques and using both of them to monitor the failure processes can facilitate a more comprehensive understanding and better control of the hydraulic stimulations in subsurface operations.

Geochemistry & Geophysics↗
DOE OSTI2024

Arsenic stress triggers active exudation of arsenic–phytochelatin complexes from Lupinus albus roots

Abstract Arsenic (As) contamination of soils threatens the health of millions globally through accumulation in crops. While plants detoxify As via phytochelatin (PC) complexation and efflux of arsenite from roots, arsenite efflux mechanisms are not fully understood. Here, white lupin (Lupinus albus) was grown in semi-hydroponics, and exudation of glutathione (GSH) derivatives and PCs in response to As was measured using LC-MS/MS. Inhibiting synthesis of the PC precursor GSH with l-buthionine sulfoximine (BSO) or ABC transporters with vanadate drastically reduced (>22%) GSH derivative and PC2 exudation, but not PC3 exudation. This was accompanied by As hypersensitivity in plants treated with BSO and moderate sensitivity with vanadate treatment. Investigating As–PC complexation revealed two distinct As–PC complexes, As bound to GSH and PC2 (GS–As–PC2) and As bound to PC3 (As–PC3), in exudates of As-treated lupin plants. Vanadate inhibited As–PC exudation, while BSO inhibited both the synthesis and exudation of As–PC complexes. These results demonstrate a role for GSH derivatives and PC exudation in lupin As tolerance and reveal As–PC exudation as a new potential mechanism contributing to active As efflux in plants. Overall, this study uncovers insights into rhizosphere As detoxification with potential to help mitigate pollution and reduce As accumulation in crops.

Plant Sciences↗
DOE OSTI2020

Single-phase Ru 1- x-y Mn x Co y O 2 nanoparticles as highly effective oxygen reduction electrocatalysts in alkaline media with enhanced stability and fuel-tolerance

Here, a series of single-phase binary and ternary ruthenium and transition metal oxide nanoparticles supported on Vulcan - Ru 1-x MnxO2/C, Ru1-xCoxO 2 /C, Ru 1-x-y MnxCo y O 2 /C, Ru 1-x Fe x O 2 /C, Ru 1-x Ni x O 2 /C and Ru 1-x V x O 2 /C, as well as RuO 2 /C, MnO 2 /C, Co 3 O 4 /C and Mn 3-x Co x O 4 /C - were synthesized via a facile method and studied for their oxygen reduction reaction (ORR) activity in alkaline media. Single-phase Ru 1-x Mn x O 2 /C, Ru 1-x-y Mn x Co y O 2 /C and Ru 1-x Co x O 2 /C catalysts significantly boosted ORR kinetics in alkaline media. Moreover, they were H 2 and methanol tolerant, and exhibited long term stability due to their single-phase structure. Ru 0.85 Mn 0.15 O 2 /C stood out as the most active catalyst among them. A volcano relationship of the ORR activity of these binary and ternary metal oxide catalysts vs. the O adsorption energy was found, with the maximum activity observed for the Ru 1-x Mn x O 2 /C, Ru 1-x-y Mn x Co y O 2 /C and Ru 1-x Co x O 2 /C catalysts due to their optimal O binding energy. These materials have potential applications as highly active ORR catalysts in alkaline fuel cells and metal-air batteries.

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

Mesoporous Textured Fe-N-C Electrocatalysts as Highly Efficient Cathodes for Proton Exchange Membrane Fuel Cells

A new platinum group metal (PGM)-free proton exchange membrane fuel cell (PEMFC) cathode catalyst materials, synthesized using the VariPore™ method by Pajarito Powder, LLC, are characterized for their structure and activity. The physico-chemical analysis of the iron-nitrogen-carbon (Fe-N-C) electrocatalysts show mesoporous carbon material effectively doped with iron and nitrogen. The materials have an average pore size of 7-8 nm and high specific surface area. The Fe-N-C catalysts exhibit good oxygen reduction reaction (ORR) activity in 0.5 M H2SO4 electrolyte with high half-wave potential and sustainable electrochemical stability over 10,000 repeated potential cycles with insignificant losses in their activities. As cathode catalysts in a PEMFC, the Fe-N-C materials deliver remarkably good fuel cell performance at low overpotential approaching that of the commercial Pt catalyst. The high ORR electrocatalytic activity of these Fe-N-C catalysts is credited to the synergy between nitrogen-moieties, specifically pyrrolic-N, pyridinic-N, and graphitic-N, and iron in addition to the high mesoporosity that facilitate an effective reaction path in boosting the electrocatalytic activity and stability.

DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Enhancing sorption kinetics by oriented and single crystalline array-structured ZSM-5 film on monoliths

Abstract To enhance the reaction kinetics without sacrificing activity in porous materials, one potential solution is to utilize the anisotropic distribution of pores and channels besides enriching active centers at the reactive surfaces. Herein, by designing a unique distribution of oriented pores and single crystalline array structures in the presence of abundant acid sites as demonstrated in the ZSM-5 nanorod arrays grown on monoliths, both enhanced dynamics and improved capacity are exhibited simultaneously in propene capture at low temperature within a short duration. Meanwhile, the ZSM-5 array also helps mitigate the long-chain HCs and coking formation due to the enhanced diffusion of reactants in and reaction products out of the array structures. Further integrating the ZSM-5 array with Co 3 O 4 nanoarray enables comprehensive propene removal throughout a wider temperature range. The array structured film design could offer energy-efficient solutions to overcome both sorption and reaction kinetic restrictions in various solid porous materials for various energy and chemical transformation applications.

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

Genome-Resolved Metagenomics of Nitrogen Transformations in the Switchgrass Rhizosphere Microbiome on Marginal Lands

Switchgrass (Panicum virgatum L.) remains the preeminent American perennial (C4) bioenergy crop for cellulosic ethanol, that could help displace over a quarter of the US current petroleum consumption. Intriguingly, there is often little response to nitrogen fertilizer once stands are established. The rhizosphere microbiome plays a critical role in nitrogen cycling and overall plant nutrient uptake. We used high-throughput metagenomic sequencing to characterize the switchgrass rhizosphere microbial community before and after a nitrogen fertilization event for established stands on marginal land. We examined community structure and bulk metabolic potential, and resolved 29 individual bacteria genomes via metagenomic de novo assembly. Community structure and diversity were not significantly different before and after fertilization; however, the bulk metabolic potential of carbohydrate-active enzymes was depleted after fertilization. We resolved 29 metagenomic assembled genomes, including some from the ‘most wanted’ soil taxa such as Verrucomicrobia, Candidate phyla UBA10199, Acidobacteria (rare subgroup 23), Dormibacterota, and the very rare Candidatus Eisenbacteria. The Dormibacterota (formally candidate division AD3) we identified have the potential for autotrophic CO utilization, which may impact carbon partitioning and storage. Our study also suggests that the rhizosphere microbiome may be involved in providing associative nitrogen fixation (ANF) via the novel diazotroph Janthinobacterium to switchgrass.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

DMRG on Top of Plane-Wave Kohn–Sham Orbitals: A Case Study of Defected Boron Nitride

In this paper, we analyze the numerical aspects of the inherent multi reference density matrix renormalization group (DMRG) calculations on top of the periodic Kohn-Sham density functional theory using the complete active space approach. The potential of the framework is illustrated by studying hexagonal boron nitride nanoflakes embedding a charged single boron vacancy point defect by revealing a vertical energy spectrum with a prominent multireference character. We investigate the consistency of the DMRG energy spectrum from the perspective of sample size, basis size, and active space selection protocol. Results obtained from standard quantum chemical atom-centered basis calculations and plane-wave based counterparts show excellent agreement. Furthermore, we also discuss the spectrum of the periodic sheet which is in good agreement with extrapolated data of finite clusters. These results pave the way toward applying the DMRG method in extended correlated solid-state systems, such as point defect qubit in wide band gap semiconductors.

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

Machine learning for the redox potential prediction of molecules in organic redox flow battery

Here, organic redox flow batteries (ORFB) are recognized as an innovative technology for the large-scale storage of renewable energy. The redox potential of organic redox-active molecules plays a vital role in their performance. Advanced screening techniques like high-throughput experiment and machine learning (ML) have significantly enhanced organic material performance and transformed the field of ORFB. However, the scarcity of experimental data poses a considerable challenge for ML model development in this domain. In our study, we developed lightweight graph-based Gaussian process regression (GPR) models with GPU-accelerated marginalized graph kernel and hybrid kernel to predict the redox potentials of organic redox-active molecules for ORFBs, specifically focusing on small datasets. To evaluate model accuracy, we created a new experimental database of organic redox-active molecules by the data from hundreds of published papers and assembled previous computational datasets. We also considered some key parameters, such as pH conditions and solvent type, to assess their impact on redox potential prediction. Our GPR model predicted redox potentials with high accuracy across all datasets using minimal training data. The study provides powerful tools for molecule screening and design and delivers valuable guidance on designing training datasets for costly experiments.

25 ENERGY STORAGE↗