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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Pore Aperture Control Toward Size‐Exclusion‐Based Hydrocarbon Separations

Abstract Metal–organic frameworks (MOFs) have been proposed as a promising material for non‐thermal chemical separations owing to their high structural diversity and tunability. Here, we report the synthesis of a zinc‐based MOF containing a three‐dimensional (3D) linker, bicyclo[2.2.2]octane‐1,4‐dicarboxylic acid, with high thermal stability towards the separation of hexane isomers. The incorporation of the 3D linker enhances the structural stability and provides well‐defined pore apertures/channels with sub‐Ångstrom precision. This precision allowed for the separation of similarly sized hexane isomers based on subtle differences in their kinetic diameters. Multi‐component liquid phase batch experiments confirmed the separation of hexanes mixture into linear, monobranched, and dibranched isomers. This work represents a significant milestone in the construction of stable Zn‐based MOFs and the incorporation of 3D linkers as a potential solution to challenging separations.

Lal, Bhajan↗
DOE OSTI2020

A Strategy for Constructing Pore-Space-Partitioned MOFs with High Uptake Capacity for C 2 Hydrocarbons and CO 2

Introduction of pore partition agents into hexagonal channels of MIL-88 type (acs topology) endows materials with high tunability in gas sorption. Here, we report a strategy to partition acs framework into pacs (partitioned acs) crystalline porous materials (CPM). This strategy is based on insertion of in situ synthesized 4, 4'-dipyridylsulfide (dps) ligands. As a result, one third of open metal sites in the parent acs net are retained in pacs MOFs, while two thirds are used for pore space partition. The newly synthesized Co 2 V-pacs MOFs, with optimized pore space and open metal sites, exhibit near or at record high uptake capacities for C 2 H 2 , C 2 H 4 , C 2 H 6 , and CO 2 among MOFs. For example, the storage capacity of C 2 H 2 is 234 cm 3 /g -1 (298 K) and 330 cm 3 /g -1 (273K) at 1 atm for CPM-733-dps (the Co 2 V-BDC form, BDC=1,4-benzenedicarboxylate), higher than benchmark MOFs such as MOF-74 and all other pacs members. These high uptake capacities are accomplished with low heat of adsorption, a feature desirable for low-energy-cost adsorbent regeneration. CPM-733-dps is stable and shows no loss of C 2 H 2 adsorption capacity following multiple adsorption–desorption cycles.

25 ENERGY STORAGE↗
DOE OSTI2023

Pore Aperture Control Toward Size‐Exclusion‐Based Hydrocarbon Separations

Metal–organic frameworks (MOFs) have been proposed as a promising material for non-thermal chemical separations owing to their high structural diversity and tunability. Here, we report the synthesis of a zinc-based MOF containing a three-dimensional (3D) linker, bicyclo[2.2.2]octane-1,4-dicarboxylic acid, with high thermal stability towards the separation of hexane isomers. The incorporation of the 3D linker enhances the structural stability and provides well-defined pore apertures/channels with sub-Ångstrom precision. This precision allowed for the separation of similarly sized hexane isomers based on subtle differences in their kinetic diameters. Multi-component liquid phase batch experiments confirmed the separation of hexanes mixture into linear, monobranched, and dibranched isomers. This work represents a significant milestone in the construction of stable Zn-based MOFs and the incorporation of 3D linkers as a potential solution to challenging separations.

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

“Third-body” collision parameters for hydrocarbons, alcohols, and hydroperoxides and an effective internal rotor approach for estimating them

Collision rate constants and third-body collision efficiencies are calculated for more than 300 alkanes, alcohols, and hydroperoxides, for the bath gases He, Ar, H 2 , and N 2 , and from 300 to 2000 K. The data set includes highly branched species and species with as many as 16 nonhydrogen atoms N , and it is analyzed to develop strategies for estimating collision properties more generally. Simple analytic formulas describing the Lennard-Jones collision parameters $σ$ and $ε$ are obtained for each of the three classes of systems as a function of N . Trends in the collision efficiency range parameter $α$ = $\langle$Δ E d $\rangle$ are more complicated, and a method is developed and validated for estimating $α$ based on the numbers and types of internal rotors and oxygen-containing groups. Specifically, the approach maps the expected value of $α$ for a branched alkane, alcohol, or hydroperoxide onto those for the corresponding normal (linear) series via an effective number of nonhydrogen atoms N eff . The prescription for N eff is based on counting internal rotor types and is shown to be insensitive to temperature and fairly insensitive to the identity of the bath gas. Together, these strategies allow for the ready estimation of the collision parameters $σ$, $ε$, and $α$ so long as results for the associated linear series are available.

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

Reinforcement learning based automated history matching for improved hydrocarbon production forecast

History matching aims to find a numerical reservoir model that can be used to predict the reservoir performance. An engineer and model calibration (data inversion) method are required to adjust various parameters/properties of the numerical model in order to match the reservoir production history. In this study, we develop deep neural networks within the reinforcement learning framework to achieve automated history matching that will reduce engineers’ efforts, human bias, automatically and intelligently explore the parameter space, and remove the need of large set of labeled training data. To that end, a fast-marching-based reservoir simulator is encapsulated as an environment for the proposed reinforcement learning. The deep neural-network-based learning agent interacts with the reservoir simulator within reinforcement learning framework to achieve the automated history matching. Reinforcement learning techniques, such as discrete Deep Q Network and continuous Deep Deterministic Policy Gradients, are used toth, used to train the learning agents. The continuous actions enable the Deep Deterministic Policy Gradients to explore more states at each iteration in a a learning episode; consequently, a better history matching is achieved using this algorithm as compared to Deep Q Network. For simplified dual-target composite reservoir models, the best history-matching performances of the discrete and continuous learning methods in terms of normalized root mean square errors are 0.0447 and 0.0038, respectively. Furthermore, our study shows that continuous action space achieved by the deep deterministic policy gradient drastically outperforms deep Q network.

42 ENGINEERING↗
DOE OSTI2022

Turbulent transport and reactions of plant-emitted hydrocarbons in an Amazonian rain forest

The processes governing the temporal and spatial patterns of isoprene and monoterpenes emitted by a rainforest in the central Amazon region of Brazil is investigated using a combination of field experiments and numerical simulations. Specifically, Large Eddy Simulations (LES) were used to resolve emissions of isoprene and monoterpenes, turbulent transport, and air chemistry. The coupled chemistry-transport LES included the effects of isoprene and monoterpenes reactivity due to reactions with hydroxyl radical and ozone. The LES results are used to compute vertically resolved budgets of isoprene and monoterpenes in the rainforest canopy in response to emissions, turbulent transport, surface deposition, and air chemistry. Our results indicated that emission and dispersion dominated the isoprene budget as the gases were transported out of the canopy space. In a region limited by nitrogen oxides (with prevailing nitric oxide levels of < 0.5 parts per billion), the in-canopy chemical destruction removed approximately 10% of locally emitted monoterpenes. Hydroxyl radical production rates from the ozonolysis of monoterpenes amounted to ≈ 2 x 10 6 radicals cm -3 s -1 and had similar magnitude to the light-dependent hydroxyl radical formation. One key conclusion was that the Amazonia rainforest abundantly emitted monoterpenes whose in-canopy ozonolysis yielded hydroxyl radicals in amounts similar to the magnitude of light-dependent formation. Reactions of monoterpenes and isoprene with hydroxyl radical and ozone were necessary for the maintenance of the Amazon rainforest canopy as a photochemically active environment suitable to generate oxidants and secondary organic aerosols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Spatially resolved X-ray imaging and molecular characterisation of sulfur and iron in organic- and sulfur-rich hydrocarbon source mudstones

Sulfurisation of organic matter (OM) is a prominent preservation mechanism, however iron sulfide precipitation, particularly pyrite (FeS2), can counteract this mechanism. There is a dearth of high-resolution, spatially-resolved spectroscopic (redox) information on sulfur and iron inventories within organic-rich rocks that would improve our understanding of prevailing environmental conditions during deposition. Here, state-of-the-art synchrotron-based X-ray absorption and fluorescence analyses of key organic- and sulfur-rich mudstones demonstrate the potential of these techniques to non-destructively map and produce detailed spectroscopic information. Detailed high-resolution analyses (μm- to mm-scale) reveal the presence of widespread sulfurised OM in the Blackstone Band of the Kimmeridge Clay Formation, in line with a persistence of euxinia over a long temporal span and low reactive iron input, facilitating the preservation of OM through sulfurisation. In contrast, the presence of sulfurised OM was transitional in the Monterey Formation, consistent with fluctuating water column redox conditions, and is less significant in the Whitby Mudstone Formation, likely due to the high reactive iron concentrations outcompeting sulfurised OM formation. Analyses of sulfur species using model compounds further indicate that the Whitby Formation is strongly enriched in inorganic reduced sulfur minerals, while both the Kimmeridge Clay and Monterey Formations are dominated by organic sulfur species. These synchrotron-based observations improve our understanding of environmental conditions during the time of deposition of these mudstones and thus show great promise in the study of organic-rich sediments, especially in allowing their depositional settings to be more accurately reconstructed.

Kimmeridge Clay Formation↗