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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

High-Pressure Synthesis of Metal–Inorganic Frameworks Hf 4 N 20 ·N 2 , WN 8 ·N 2 , and Os 5 N 28 ·3 N 2 with Polymeric Nitrogen Linkers

Polynitrides are intrinsically thermodynamically unstable at ambient conditions and require peculiar synthetic approaches. Now, a one-step synthesis of metal–inorganic frameworks Hf 4 N 20 ·N 2 , WN 8 ·N 2 , and Os 5 N 28 ·3 N 2 via direct reactions between elements in a diamond anvil cell at pressures exceeding 100 GPa is reported. The porous frameworks (Hf 4 N 20 , WN 8 , and Os 5 N 28 ) are built from transition-metal atoms linked either by polymeric polydiazenediyl (polyacetylene-like) nitrogen chains or through dinitrogen units. Triply bound dinitrogen molecules occupy channels of these frameworks. Owing to conjugated polydiazenediyl chains, these compounds exhibit metallic properties. The high-pressure reaction between Hf and N 2 also leads to a non-centrosymmetric polynitride Hf 2 N 11 that features double-helix catena-poly[tetraz-1-ene-1,4-diyl] nitrogen chains [–N–N–N=N–] ∞ .

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

Evaluation of a New Chemical Mechanism for 2-Amino-2-methyl-1-propanol in a Reactive Environment from CSIRO Smog Chamber Experiments

Amines are considered as an emerging class of atmospheric pollutants that are of great importance to atmospheric chemistry and new particle formation. As a typical amine, 2-amino-2-methyl-1-propanol (AMP) is one of the proposed solvents for capturing CO 2 from flue gas streams in amine-based post-combustion CO 2 capture plants, and it is expected to result in AMP emission and secondary products formation in the atmosphere. However, the current knowledge of its atmospheric chemistry and kinetics is poorly understood, particularly in a reactive environment. As such, in this work we used the CSIRO smog chamber to study the photo-oxidation of AMP in the presence of VOCs–NOx surrogate mixtures over a range of initial amine concentrations. O 3 formation was significantly inhibited when AMP was added to the surrogate VOCs–NOx mixtures, implying that AMP could alter known atmospheric chemical reaction pathways and the prevailing reactivity. Simultaneously, a large amount of AMP-derived secondary aerosol was formed, with a considerably high aerosol mass yield (i.e. ratio of aerosol formed to reacted AMP) of 1.06±0.20. Based on updated knowledge of its kinetics, oxidation pathways and product yields, we have developed a new mechanism (designated as CSIAMP-19) and integrated into the Carbon Bond 6 (CB6) chemical mechanism, and evaluated it against available smog chamber data. Compared with the existing AMP mechanism (designated as CarterAMP-08), the modified CB6 with CSIAMP-19 mechanism improves prediction against AMP–VOCs–NOx experiments across a range of initial AMP concentrations, within ±10% model error for gross ozone production. Our results contribute to scientific understanding of AMP photochemistry and to the development of the chemical mechanism of other amines. The updated AMP chemical reactions scheme can be further embedded into the chemical transport model for regional modelling scenarios where AMP-related emissions are of concern.

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

Development of a Reactive Force Field for Simulating Photoinitiated Acrylate Polymerization

Light-driven and photo-curable polymer based additive manufacturing (AM) has enormous potential due to its excellent resolution and precision. Acrylated radical chain-growth polymerized resins are widely used in photopolymer AM due to their fast kinetics, and often serve as a departure point for developing other resin materials for photopolymer-based AM technologies. For successful control of the photopolymer resins, the molecular basis of the acrylate free-radical polymerization has to be understood in detail. We present an optimized reactive force field (ReaxFF) for molecular dynamics (MD) simulations of acrylate polymer resins that captures radical polymerization thermodynamics and kinetics. The force field is trained against an extensive training set including density functional theory (DFT) calculations of reaction pathways along the radical polymerization from methyl acrylate to methyl butyrate, bond dissociation energies, and structures and partial charges of several molecules and radicals. We also found that it was critical to train the force field against an incorrect, nonphysical reaction pathway observed in simulations that used parameters not optimized for acrylate polymerization. As a result, the parameterization process utilizes a parallelized search algorithm, and the resulting model can describe polymer resin formation, crosslinking density, conversion rate, and residual monomers of the complex acrylate mixtures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Atomic cluster expansion potential for large scale simulations of hydrocarbons under shock compression

We present an Atomic Cluster Expansion (ACE) machine learned potential developed for high-fidelity atomistic simulations of hydrocarbons, targeting pressures and temperatures near and above supercritical fluid regimes for molecular fluids. A diverse set of stoichiometries were covered in training, including 1:0 (pure carbon), 1:4 (methane), and 1:1 (benzene), and rich bonding environments sampled at supercritical temperatures, hydrogen rich, reactive mixtures where metastable stoichiometries arise, including 1:2 (ethylene) and 1:3 (ethane). A high-fidelity training database was constructed by performing large-scale quantum molecular dynamic simulations [density functional theory (DFT) MD] of diamond, graphite, methane, and benzene. A novel approach to selecting structures from DFT MD is also presented, which allows for the rapid selection of unique DFT MD frames from complex trajectories. Comparisons to DFT and experimental data demonstrate that the presented ACE potential accurately reproduces isotherms, carbon melting curves, radial distribution functions, and shock Hugoniots for carbon and hydrocarbon systems for pressures up to 100 GPa and temperatures up to 6000 K for hydrocarbon systems and up to 9000 K for pure carbon systems. This work delivers a potential that can be used for accurate, large-scale simulations of shocked hydrocarbons and demonstrates a methodology for fitting and validating machine learning interatomic potentials to complex molecular environments, which can be applied to energetic materials in future works.

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

Data and Scripts Associated with the Manuscript “Water Column Respiration in the Yakima River Basin is Explained by Temperature, Nutrients and Suspended Solids”

This data package is associated with the publication “Water Column Respiration in the Yakima River Basin is Explained by Temperature, Nutrients and Suspended Solids” published in EGU Biogeochemistry (Laan et al. 2025). In this research, water column respiration (ERwc) data, surface water chemistry data, organic matter (OM) chemistry data, and publicly available geospatial data were used in analysis to evaluate the variability in ERwc at 47 sites across the Yakima River basin in Washington, USA. In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. The data package includes the data inputs, and outputs, and R scripts to reproduce all the analyses performed in the manuscript and create manuscript figures. The data package is comprised of three main folders (Code, Data, and Figures). The Code folder is comprised of four scripts and three analysis-specific subfolders that contain the R scripts to perform the analyses described in the publication and create publication figures. The Data folder is comprised of two “.csv” files and four subfolders that contain data input and output files. The Published_Data folder contains a readme that directs the user to download the appropriate files and add to this folder when using scripts. The Figures folder includes figures from the manuscript in “.pdf” and “.png” formats and a folder with intermediate figure files. This data package is associated with a GitHub repository which can be found at https://github.com/river-corridors-sfa/rcsfa-RC2-SPS-ERwc. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Contributions to Lignomics: Stochastic Generation of Oligomeric Lignin Structures for Interpretation of MALDI–FT‐ICR‐MS Results

The lack of standards to identify oligomeric molecules is a challenge for the analysis of complex organic mixtures. High-resolution mass spectrometry—specifically, Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS)—offers new opportunities for analysis of oligomers with the assignment of formulae (C x H y O z ) to detected peaks. However, matching a specific structure to a given formula remains a challenge due to the inability of FT-ICR MS to distinguish between isomers. Additional separation techniques and other analyses (e.g., NMR spectroscopy) coupled with comparison of results to those from pure compounds is one route for assignment of MS peaks. Unfortunately, this strategy may be impractical for complete analysis of complex, heterogeneous samples. In this study we use computational stochastic generation of lignin oligomers to generate a molecular library for supporting the assignment of potential candidate structures to compounds detected during FT-ICR MS analysis. Furthermore, this approach may also be feasible for other macromolecules beyond lignin.

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

Influence of heterocyclic N-donors on the structural topologies and vibrational spectra of uranyl selenate phases

Uranyl (U(VI)O 2 2+ ) selenate compounds represent a well-studied family of structures with diverse structural arrays. Differences in the overall topology and bonding with the uranyl cation combined with additional intermolecular interactions can lead to variation in the resulting spectroscopic signals. Here, in the current study, we evaluated the structural chemistry and vibrational spectroscopy for uranyl selenates crystallized with heterocyclic N-donors. Five compounds ((C 4 H 12 N 2 )[(UO 2 )(SeO 4 ) 2 (H 2 O)]·H 2 O (USe_pip), (C 4 H 5 N 2 ) 2 [(UO 2 )(SeO 4 ) 2 (H 2 O)] (USe_pyrdz), (C 5 H 5 N) 2 [(UO 2 ) 2 (SeO 4 ) 3 (H 2 O)] ∙ 3H 2 O (USe_pyrmd), (H 3 O) 2 (C 4 H 5 N 2 ) 2 [(UO 2 ) 3 (SeO 4 ) 5 (H 2 O)]·H 2 O (USe_pyrz), and (C 5 H 6 N) 2 [(UO 2 ) 2 (SeO 4 ) 3 (H 2 O)] ∙ 3H 2 O (USe_pyr)) were characterized using X-ray diffraction (single-crystal and powder) and vibrational (Raman and IR) spectroscopy. Two one-dimensional (1-D) chain and three two-dimensional sheet (2-D) topologies were identified and classified based upon previous graphical representations. Overall, the arrangement of the heteroatoms could be linked to the hydrogen bonding network associated with the heterocycles and selenate anions. Vibrational spectra of the solid-state compounds were complex, with multiple bands associated with the uranyl cation, selenate anion, and heteroatoms. The ν 1 symmetric stretching band of the uranyl was relatively consistent across all compounds, whereas differences were observed for the ν 3 asymmetric band between the 1-D and 2-D structural topologies.

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

Routes to Acetonitrile-Supported Trifluoromethyl and Perfluorometallacyclopentane Complexes of Cobalt

In this report, synthetic routes to [(MeCN) 3 Co(CF 3 ) 3 ], [Co(MeCN) 6 ][PF 6 ] 2 , [(MeCN) 4 Co(CF 3 ) 2 ][PF 6 ], [(MeCN) 2 (py)Co(CF 3 ) 3 ], [(MeCN)(py) 2 Co(CF 3 ) 3 ], and [(MeCN) 4 Co(C 4 F 8 )][PF 6 ] are described. The unusual [(py) 2 (CF 3 ) 2 Co(μ-CH 2 CN)] 2 has also been identified as a decomposition product of [(py) 2 (MeCN)Co(CF 3 ) 3 ]. In conclusion, the aforementioned compounds, all of which have been characterized by X-ray crystallography, are expected to serve as useful precursors to cobalt trifluoromethyl- and C 4 F 8 -containing derivatives.

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

(CAAC)Copper Catalysis Enables Regioselective Three-Component Carboboration of Terminal Alkynes

Here, cyclic(alkyl)(amino)carbene (CAAC) ligands are found to perturb regioselectivity of the copper-catalyzed carboboration of terminal alkynes, favoring the less commonly observed internal alkenylboron regiosomer through an α-selective borylcupration step. A variety of carbon electrophiles participate in the reaction, including allyl alcohols derivatives and alkyl halides. The method provides a straightforward and selective route to versatile tri-substituted alkenylboron compounds that are otherwise challenging to access.

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

Using GANs with adaptive training data to search for new molecules

The process of drug discovery involves a search over the space of all possible chemical compounds. Generative Adversarial Networks (GANs) provide a valuable tool towards exploring chemical space and optimizing known compounds for a desired functionality. Standard approaches to training GANs, however, can result in mode collapse, in which the generator primarily produces samples closely related to a small subset of the training data. In contrast, the search for novel compounds necessitates exploration beyond the original data. In this work, we present an approach to training GANs that promotes incremental exploration and limits the impacts of mode collapse using concepts from Genetic Algorithms. In our approach, valid samples from the generator are used to replace samples from the training data. We consider both random and guided selection along with recombination during replacement. By tracking the number of novel compounds produced during training, we show that updates to the training data drastically outperform the traditional approach, increasing potential applications for GANs in drug discovery.

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

Solvent for non-aqueous battery

A solvent useful for lithium batteries comprises a compound of Formula (I): (R1)(R2)(R3)Si—R4—O—C(O)—[(O—R5)n—(O—C(O)]m—O—R6—X1. Each of R1 and R2 independently is alkyl; R3 is alkyl, —X2—Si(R7)(R8)(R9), or —CH2—O—C(O)—O—R10; X1 is H or —Si(R11)(R12)(R13); each of R4 and R6 independently is alkylene; each R5 independently is C2 to C6 alkylene; each of R7, R8, R9, and R10 independently is alkyl; X2 is O or alkylene; each of R11 and R12 independently is alkyl; R13 is alkyl or —X3—Si(R14)(R15)(R16); each of R14, R15, and R16 independently is alkyl; X3 is O or alkylene; m is 0 or 1, and n is 1-3; and when m is 0 and R3 is alkyl, X1 is —Si(R11)(R12)(R13). Also described is a method for manufacturing a compound of Formula (II): (R17)(R18)(R19)Si—CH2—O—C(O)—O—R20 where each R17, R18, R19, and R20 is alkyl.

25 ENERGY STORAGE↗
DOE OSTI2020

Electrocatalytic hydrogenation of muconic acid

Various embodiments disclosed relate to electrocatalytic hydrogenation of muconic acid and polymers formed from the reaction products thereof. In various embodiments, the present invention provides an electrocatalytic method to prepare 3-hexene-1,6-dioic acid, 2-hexene-1,6-dioic acid, adipic acid, or a combination thereof, from muconic acid. The method includes passing current through a catalytic cathode in a reactor including an aqueous acidic solution including muconic acid, a supporting electrolyte, and an anode, so as to generate atomic hydrogen on the cathode surface in an amount effective to hydrogenate the muconic acid to yield a product including 3-hexene-1,6-dioic acid, 2-hexene-1,6-dioic acid, adipic acid, or a mixture thereof. Also disclosed is the polymerization of 3-hexene-1,6-dioic acid, 2-hexene-1,6-dioic acid, or a combination thereof with another compound, such as a diamine or a dialcohol, to form a polymer, such as a polyamide or a polyester.

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

The Effect of Adsorbed Volatile Organic Compounds on an Ultrathin Water Film Measurement

Using surface plasmon resonance imaging (SPRi), we have recently shown for the first time the existence of a monolayer water film between droplets during dropwise condensation. This study examines the effect of adsorbed volatile organic compounds (VOCs) on the ultrathin film measurement using SPRi. Further, the work presents the proper surface-treatment process that enables measurements of the ultrathin water layer during high-speed imaging of dropwise condensation at 3000 frame per second. In this study, two methods were applied for cleaning the surface (gold-coated glass)—(1) standard cleaning procedure (SCP) using acetone, isopropyl alcohol, and deionized water and (2) SCP followed by air plasma cleaning. This work discusses the effect of the cleaning procedures on surface roughness, contact angle, and surface chemistry using atomic force microscopy, optical microscopy, and an X-ray photoelectron spectroscope meter. The results showed that SCP before the SPRi is a proper surface-treatment method. The effect of adsorbed VOCs during dropwise condensation on a surface treated with SCP was measured to be 0.0025 (reflectivity unit), which was 70% smaller than the reflectance associated with a monolayer water film. The results of this work confirm a monolayer water film observation during the dropwise condensation, which has been reported before.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tunable broadband luminescence in lead-free hybrid copper halides

Metal halides are an important class of optoelectronic materials combining exceptional optical and electronic properties. An inherent advantage of metal halides is their solution synthesis and processability, which render them as low-cost and environmentally friendly materials for a range of applications from photovoltaics and photodetection to solid-state lighting (SSL). Here, in this study, we synthesized three previously unreported lead-free organic–inorganic hybrid copper halides: (OA) 4 CuX 5 (X = Br, I; OA + = C 8 H 17 NH 3+ , n-octylammonium cation) and (HA) 2 CuI 3 (HA + = C 6 H 13 NH 3 + , n-hexylammonium cation), all of which exhibit broadband emissions arising from self-trapped excitons (STEs). Among these compounds, (OA) 4 CuI 5 demonstrates tunable dual-band white-light emission with a high color rendering index value of 91 at room temperature. Temperature-dependent photoluminescence measurements and first-principles calculations reveal distinct behaviors between the two emission states in (OA) 4 CuI 5 . These findings highlight the potential of copper halide compounds for optoelectronic applications, particularly in the development of environmentally friendly solid-state lighting technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Stream Chemistry, Synoptic Surveys, East Fork Poplar Creek Watershed, TN, USA; April 2023 to February 2025

Impacts of developed land cover on stream chemistry can be difficult to discern from natural variability, particularly in carbonate watersheds where weathering of urban infrastructure and lithology generate similar signatures. We evaluated how spatial patterns of stream chemistry varied across perennial and non-perennial tributaries spanning an urban-to-forested gradient in a mid-order, carbonate-dominated watershed. This data package contains a processed and compiled summary of stream chemistry and properties obtained from 12 synoptic surveys of 54 stream sites across the East Fork Poplar Creek watershed located near Oak Ridge, TN, United States. The sites include non-perennial tributaries, perennial tributaries, and the main stem and span forested to urban (highly developed) land cover gradients. The data package includes the processed and flagged chemical data (WaDE_SynopticSummary_FinalChemistry), metadata describing data flagging and analysis (WaDE_SynopticSummary_Metadata), information about each site and its contributing subcatchment (WaDE_SynopticSummary_SiteInformation), and a comparison of instrument and field detection limits used to determine method detection limits for the study (WaDE_SynopticSummary_DetectionLimitComparison). Stream chemistry includes stream parameters measured in situ using multiparameter probes (dissolved oxygen, pH, specific conductance, temperature) and solutes including nutrients (nitrate, ammonium, soluble reactive phosphorus), dissolved organic carbon, dissolved inorganic carbon, major cations (calcium, magnesium, potassium, sodium), major anions (chloride, sulfate), and a broad suite of minor and trace elements.

EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE ↗
DOE OSTI2020

Oxidation of phenolic compounds during autothermal pyrolysis of lignocellulose

Fast pyrolysis is traditionally defined as the rapid decomposition of organic material in the absence of oxygen to produce primarily a liquid product known as bio-oil. However, the introduction of small amounts of oxygen to the process holds prospects of internally generating the energy needed for pyrolysis. The present study investigates the partial oxidation of lignin-derived compounds during pyrolysis, which generates both carbon oxides and aromatic carbonyl compounds. Analysis of lignin derived phenolic compounds was performed to determine if the composition had changed under oxidative conditions. NMR analyses indicates aromatic carbonyls increased under oxidative conditions, with a corresponding decrease in phenolic hydroxyl groups. Finally, model phenolic compounds were pyrolyzed to help understand the role of partial oxidation during autothermal pyrolysis of lignocellulosic biomass.

09 BIOMASS FUELS↗
DOE OSTI2023

Deep Learning-Enabled MS/MS Spectrum Prediction Facilitates Automated Identification Of Novel Psychoactive Substances

The market for illicit drugs has been reshaped by the emergence of more than 1100 new psychoactive substances (NPS) over the past decade, posing a major challenge to the forensic and toxicological laboratories tasked with detecting and identifying them. Tandem mass spectrometry (MS/MS) is the primary method used to screen for NPS within seized materials or biological samples. The most contemporary workflows necessitate labor-intensive and expensive MS/MS reference standards, which may not be available for recently emerged NPS on the illicit market. Here, we present NPS-MS, a deep learning method capable of accurately predicting the MS/MS spectra of known and hypothesized NPS from their chemical structures alone. NPS-MS is trained by transfer learning from a generic MS/MS prediction model on a large data set of MS/MS spectra. We show that this approach enables a more accurate identification of NPS from experimentally acquired MS/MS spectra than any existing method. We demonstrate the application of NPS-MS to identify a novel derivative of phencyclidine (PCP) within an unknown powder seized in Denmark without the use of any reference standards. We anticipate that NPS-MS will allow forensic laboratories to identify more rapidly both known and newly emerging NPS. NPS-MS is available as a web server at https://nps-ms.ca/, which provides MS/MS spectra prediction capabilities for given NPS compounds. Additionally, it offers MS/MS spectra identification against a vast database comprising approximately 8.7 million predicted NPS compounds from DarkNPS and 24.5 million predicted ESI-QToF-MS/MS spectra for these compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗