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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Mapping glyceride species in biodiesel by high-temperature gas chromatography combined with chemical ionization mass spectrometry.

Accurate and comprehensive identification of residual glycerides in biodiesel is an important part of the fuel characterization, due to the impact of glycerides on the fuel physicochemical properties. However, analysis of bound glycerol in biodiesel samples faces challenges due to lack of readily available standards of structurally complex glyceride species in non-traditional biodiesel feedstocks, and a risk of misannotation in the presence of impurities in gas chromatographic separations. Here we evaluate methane and isobutane chemical ionization – single quadrupole mass spectrometry combined with high temperature gas chromatography separations for mapping monoacylglycerols, diacylglycerols and triacylglycerols in biodiesel. Unlike the electron impact ionization which produces mostly in-source fragments, isobutane chemical ionization spectra of tetramethylsilyl (TMS) derivatized monoacylglycerols and diacylglycerols are dominated by molecular ions and M-SiO(CH3)3+ ions, which provide important diagnostic information. We demonstrate the utility of isobutane chemical ionization in identifying structurally complex glycerolipid standards as well as species in biodiesel samples from different plant and animal feedstocks.

biodiesel, chemcial ionization mass spectrometry↗
DOE OSTI2025

Ionic Liquids in Analytical Chemistry: Fundamentals, Technological Advances, and Future Outlook

The development of new analytical methods most often focus on novel materials used to impart selectivity or sensitivity to the protocol. Ionic liquids (ILs) are a class of solvents that have been extensively explored as promising materials for various applications and continue to be explored due to their tunable physicochemical properties. These materials possess melting temperatures below 100 °C and can interact with analytes through a multitude of interactions afforded by their readily tunable chemical structure. These interactions include electrostatic, dispersive, hydrogen bonding, π–π, and dipolar interactions and can be modulated or strengthened based on the functional groups present within the chemical structure. ILs consist predominately of organic cations and either inorganic or organic anions, both of which can be functionalized with desired moieties. Common cation and anions found in IL chemical structures are presented in Figure 1. The unique polarity afforded by the ionic structure has also led to their increasing use in areas including sample preparation, chemical separations, electrochemistry, mass spectrometry, and spectroscopy.

Zeger, Victoria R. [Iowa State Univ., Ames, IA (Un↗
DOE OSTI2021

Hierarchical Nanomaterials Assembled from Peptoids and Other Sequence-Defined Synthetic Polymers

In nature, the self-assembly of sequence-specific biopolymers into hierarchical structures plays an essential role in the construction of functional biomaterials. To develop synthetic materials that can mimic and surpass the function of these natural counterparts, various sequence-defined bio- and biomimetic polymers have been developed and exploited as building blocks for hierarchical self-assembly. This review summarizes the recent advances in the molecular self-assembly of hierarchical nanomaterials based on peptoids (or poly-N-substituted glycines) and other sequence-defined synthetic polymers. Modern techniques to monitor the assembly mechanisms and characterize the physicochemical properties of these self-assembly systems are highlighted. In addition, discussions about their potential applications in biomedical sciences and renewable energy are also included. Furthermore, this review aims to highlight essential features of sequence-defined synthetic polymers (e.g., high stability and protein-like high-information content) and how these unique features enable the construction of robust biomimetic functional materials with high programmability and predictability, with an emphasis on peptoids and their self-assembled nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Recent Advances in the Use of Ionic Liquids and Deep Eutectic Solvents for Lignocellulosic Biorefineries and Biobased Chemical and Material Production

Biorefineries, which process biomass feedstocks into valuable (bio)products, aim to replace fossil fuel-based refineries to produce energy and chemicals, reducing environmental and health hazards, including climate change, and supporting a sustainable economy. In particular, lignocellulose-based biorefineries, utilizing the most abundant renewable feedstock on Earth, have significant potential to supply sustainable energy, chemicals and materials. Ionic liquids (ILs, organic salts with low melting temperatures) and deep eutectic solvents (DESs, mixtures with eutectic points lower than the ideal mixture) are capable of dissolving some of the key lignocellulose polymers, and even the whole biomass. Furthermore, they have intrinsic advantages over molecular solvents, including safer usage profiles and high tunability, which allow tailored physicochemical properties. Such properties provide unique opportunities for the development of new processes that could unlock the full potential of future biorefineries. Here, we review the current state of lignocellulosic biomass processing with ILs and DESs, with a specific focus on the pretreatment chemistry, process flow and products from each component; followed by discussions on sustainability assessments and technological challenges. We aim to inform the research community about the opportunities, challenges and perspectives in developing truly sustainable lignocellulose-based biorefineries.

09 BIOMASS FUELS↗
DOE OSTI2026

Modeling Single-Crystal Battery Materials: From Fundamental Understanding to Performance Evaluation

The performance of rechargeable batteries is fundamentally influenced by the physicochemical properties and microstructural features of their key material components. Recent experimental advancements have highlighted the potential of single-crystal (SC) morphologies to address inherent limitations of polycrystalline (PC) electrodes and solid-state electrolytes, offering tunable charge transport kinetics and improved cell cycling performance. Here, this review examines how state-of-the-art computational modeling, from atomistic and mesoscale to continuum-level approaches, including machine learning methodologies, has been utilized to investigate the critical factors governing the electrochemical behavior of SC battery materials. We explore how predictive modeling can elucidate the processing–structure–property–performance relationships of SC cathodes, anodes, and solid-state electrolytes, with a focus on unique SC characteristics such as crystallographic anisotropy, size effects, and facet-dependent properties. Additionally, we identify limitations in commonly used modeling techniques and discuss strategies to address these challenges. By integrating high-fidelity simulations with experimental insights, this review aims to outline a clear path for the rational design and optimization of SC battery components, paving the way for accelerated advancements in energy storage technologies.

Materials science↗
DOE OSTI2023

Hydroxyls on CeO 2 Support Promoting CuO/CeO 2 Catalyst for Efficient CO Oxidation and NO Reduction by CO

Transition metal catalysts, such as copper oxide, are more attractive alternatives to noble metal catalysts for emission control due to their higher abundance, lower cost, and excellent catalytic activity. Here, in this study, we report the preparation and application of a novel CuO/CeO 2 catalyst using a hydroxyl-rich Ce(OH) x support for CO oxidation and NO reduction by CO. Compared to the catalyst prepared from a regular CeO 2 support, the new CuO/CeO 2 catalyst prepared from the OH-rich Ce(OH) x (CuO/CeO 2 –OH) showed significantly higher catalytic activity under different testing conditions. The effect of OH species in the CeO 2 support on the catalytic performance and physicochemical properties of the CuO/CeO 2 catalyst was characterized in detail. It is demonstrated that the abundant OH species enhanced the CuO x dispersion on CeO 2 , increased the CuO x –CeO 2 interfaces and surface defects, promoted the oxygen activation and mobility, and boosted the NO adsorption and dissociation on CuO/CeO 2 –OH, thus contributing to its superior catalytic activity for both CO oxidation and NO reduction by CO. These results suggest that the OH-rich Ce(OH) x is a superior support for the preparation of highly efficient metal catalysts for different applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Sources and Composition of Organic Aerosols in the Central Arctic during Spring and Summer

Organic aerosols (OA) are a major component of Arctic aerosol mass and influence the region’s radiation budget, yet their sources and physicochemical properties remain largely unknown. We investigate OA sources and climate-relevant characteristics over the central Arctic Ocean in spring and summer, by applying positive matrix factorization to aerosol mass spectrometry data from two ship-based expeditions (2018 and 2020), complemented by total and interstitial aerosol measurements during fog periods. Six distinct OA factors were identified: haze-related OA, Arctic oxygenated OA, two mixed-OA types resembling biomass burning and primary marine OA linked to warm-air intrusions, marine OA, and hydrocarbon-related OA. Seasonal transitions strongly shaped OA composition. Following polar sunrise, highly oxygenated OA, likely formed secondarily from photo-oxidized volatile organic compounds, became dominant. After the polar vortex collapsed in May, episodic spikes in marine OA from the marginal ice zone appeared, alongside a reduced influence from Eurasian anthropogenic sources. These transitions influenced OA oxidation state and related properties including volatility, acidity, and hygroscopicity, highlighting the role of the Arctic spring atmosphere as an active photochemical reactor. Overall, OA was highly oxidized, with particles activated in fog during summer showing even greater oxidation, suggesting that central Arctic OA can be highly cloud active.

Arctic haze↗
DOE OSTI2024

Formation of Inorganic Sulfate and Volatile Nonsulfated Products from Heterogeneous Hydroxyl Radical Oxidation of 2-Methyltetrol Sulfate Aerosols: Mechanisms and Atmospheric Implications

Chemical transformation of 2-methyltetrol sulfates (2-MTS), key isoprene-derived secondary organic aerosol (SOA) constituents, through heterogeneous hydroxyl radical ( • OH) oxidation can result in the formation of previously unidentified atmospheric organosulfates (OSs). However, detected OSs cannot fully account for the sulfur content released from reacted 2-MTS, indicating the existence of sulfur in forms other than OSs, such as inorganic sulfates. This work investigated the formation of inorganic sulfates through heterogeneous • OH oxidation of 2-MTS aerosols. Remarkably, high yields of inorganic sulfates, defined as the moles of inorganic sulfates produced per mole of reacted 2-MTS, were observed in the range from 0.48 ± 0.07 to 0.68 ± 0.07. These could be explained by the production of sulfate (SO 4 •- ) and sulfite (SO 3 •- ) radicals through the cleavage of C-O(S) and (C)O-S bonds, followed by aerosol-phase reactions. Additionally, non-sulfated products resulting from bond cleavage were likely volatile and evaporated into gas phase, as evidenced by observed aerosol mass loss (up to 25%) and concurrent size reduction upon oxidation. This investigation highlights the significant transformation of sulfur from its organic to inorganic forms during the heterogeneous oxidation of 2-MTS aerosols, potentially influencing the physicochemical properties and environmental impacts of isoprene-derived SOA.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Linear versus Bent Uranium(II) Metallocenes—A Local Vibrational Mode Study

Uranium metallocenes have recently attracted attention driven by their use as catalysts in organometallic synthesis. In addition to bent U(IV) and U(III), an U(II) metallocene [(η 5 -C 5 i Pr 5 ) 2 U] was synthesized with an unusual linear Cp–U–Cp angle. Here, in this work, we investigated 22 U(II) metallocenes, (i) assessing the intrinsic strength of the U-ring interactions in these complexes with a novel bond strength measure based on our local vibrational mode analysis and (ii) systematically exploring what makes these U(II) metallocenes bent. We included relativistic effects through the NESCau Hamiltonian and complemented the local mode analysis with natural bonding orbital (NBO) and quantum theory of atoms in molecules (QTAIM) data. Our study led to the following results: (i) reduction of bulky U-ring ligand substituents does not lead to bent complexes for alkyl substituents ( i Pr and i Bu) in contrast to SiMe 3 ring substituents, which are all bent. (ii) The most bent complexes are [(η 5 -C 5 H 4 SiMe 3 ) 2 U] (130°) and [η 5 -P 5 H 5 ) 2 U] (143°). (iii) Linear complexes showed one hybridized NBO with s/d character, while bent structures were characterized by s/d/f mixing. (iv) We did not observe a correlation between the strength of the U-ring interaction and the amount of the ring-U-ring bend; the strongest interaction was found for [η 5 -Cp) 2 U] and the weakest for [η 5 -P 5 H 5 ) 2 U]. In conclusion, our results provide a foundation for the design of U(II) metallocenes with specific physicochemical properties and increased reactivity.

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

Comparative Assessment of Pose Prediction Accuracy in RNA–Ligand Docking

Structure-based virtual high-throughput screening is used in early-stage drug discovery. Over the years, docking protocols and scoring functions for protein–ligand complexes have evolved to improve the accuracy in the computation of binding strengths and poses. In the past decade, RNA has also emerged as a target class for new small-molecule drugs. However, most ligand docking programs have been validated and tested for proteins and not RNA. Here, we test the docking power (pose prediction accuracy) of three state-of-the-art docking protocols on 173 RNA–small molecule crystal structures. The programs are AutoDock4 (AD4) and AutoDock Vina (Vina), which were designed for protein targets, and rDock, which was designed for both protein and nucleic acid targets. AD4 performed relatively poorly. For RNA targets for which a crystal structure of a bound ligand used to limit the docking search space is available and for which the goal is to identify new molecules for the same pocket, rDock performs slightly better than Vina, with success rates of 48% and 63%, respectively. However, in the more common type of early-stage drug discovery setting, in which no structure of a ligand–target complex is known and for which a larger search space is defined, rDock performed similarly to Vina, with a low success rate of ~27%. Further, Vina was found to have bias for ligands with certain physicochemical properties, whereas rDock performs similarly for all ligand properties. Thus, for projects where no ligand–protein structure already exists, Vina and rDock are both applicable. However, the relatively poor performance of all methods relative to protein–target docking illustrates a need for further methods refinement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Navigating Large Chemical Spaces Using Graph Theory and Integer Programming

Navigating and analyzing large chemical spaces are necessary to accelerate the design and discovery of new molecules and chemical processes. In this work, we introduce a computational framework that integrates graph theory and integer programming to enable the efficient navigation of large chemical spaces. Our framework represents the chemical space as a graph, wherein nodes represent molecules and edges represent the degree of similarity or connectivity based on domain-specific information. Using the graph representation, we identify representative molecules by computing the so-called minimum dominating set (MDS), which in our context is the minimum set of molecules that is connected to all other molecules. We present a suite of solution strategies for the MDS problem including heuristic and rigorous integer programming (IP) approaches. We show that these approaches allow us to capture physicochemical properties and domain-specific logic and constraints, facilitating the identification of molecules with the target properties. We demonstrate the effectiveness of the proposed approach by navigating the chemical space of per- and polyfluoroalkyl substances (PFAS); this comprises approximately 15,000 molecular structures. We compare our framework against traditional dimensionality reduction and clustering methods such as t-SNE and K-means clustering.

Chemical structure↗
DOE OSTI2020

Electron Affinity and Electronic Structure of Hexafluoroacetone (HFA) Revealed by Photodetaching the [HFA] •– Radical Anion

A great deal of effort has been focused on developing a metal-free catalytic system for epoxidation of unreactive alkenes. Fluoroketones are thought as remarkably promising catalysts for epoxidation reactions. The combination of fluorinated alcohols and catalytic amounts of hexafluoroacetone (HFA) gives a versatile and effective medium for epoxidation of various olefins with hydrogen peroxide. However, the fundamental physicochemical properties of HFA remained largely unclear, although they were very important to understand the related interactions. Here, in this study, we performed a joint study on the electron affinity and electronic structure of HFA employing negative ion photoelectron (NIPE) spectroscopy and quantum chemistry calculations. Two distinct bands with complicated vibrational progressions were observed in the 193 nm NIPE spectrum. The adiabatic/vertical detachment energies (ADE/VDE) were derived to be 1.42/2.06 and 4.43/4.86 eV for the ground singlet state and excited triplet state, respectively. Using the optimized geometries and vibrational frequencies of the anion and the neutral, the Franck–Condon factors were calculated for electron detachments to produce HFA in its lowest singlet and triplet states. Good agreements are obtained hereby for both bands between the experimental and calculated NIPE spectra, when taking into account combination vibrational excitations, unequivocally revealing that HFA possesses a singlet ground state with a giant singlet–triplet energy difference (ΔE ST ). The electron affinity (EA) and ΔE ST of HFA were therefore determined to be EA = 1.42 ± 0.02 eV and ΔE ST = −3.01 eV.

Wang, Lei↗
DOE OSTI2026

Accurate Prediction of pKb in Amines: Validation of the CAM-B3LYP/6-311+G(d,p)/SMD Model

Amines play several key roles in chemistry and biology and are involved in numerous industrial processes, often with significant economic impacts. Recently, amines are also garnering interest as catalysts for polymer synthesis and for CO 2 fixation, incentivizing the need to rapidly design and screen new amino compounds. Hence, developing reliable methods to predict their physicochemical properties, e.g., the base dissociation constant (pKb), is pivotal. Here, a density functional theory (DFT)-based approach was employed to compute the pKb of substituted amines, exploring the impact of several key parameters, including (i) the number of explicit water molecules at the reaction center, (ii) the van der Waals (vdW) surface, and (iii) solvent polarizability. In previous work, it was determined that including two explicit water molecules at the reaction center resulted in highly accurate pKb estimates for primary amines. Here, we find that including a third water molecule at the reaction center is essential for accurate pKb for secondary and tertiary amines. The revised methodology was then applied to a wider selection of amines, obtaining a minimum average error (MAE) < 0.4. In conclusion, this result represents an extension of our “easy-to-use method,” a simple and direct DFT approach exploiting CAM-B3LYP/SMD/6-311G+(d,p) to compute pKb without post facto modifications.

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

Solvent-Induced Swelling Behaviors of Microphase-Separated Polystyrene- block -Poly(ethylene oxide) Thin Films Investigated Using In Situ Spectroscopic Ellipsometry and Single-Molecule Fluorescence Microscopy

Block copolymers have attracted considerable interest in the fields of nanoscience and nanotechnology, because these polymers afford well-defined nanostructures via self-assembly. An in-depth understanding of solvent effects on the physicochemical properties of these microdomains is crucial for their preparation and utilization. Herein, we employed in situ spectroscopic ellipsometry and single-molecule fluorescence techniques to gain detailed insights into microdomain properties in polystyrene-block-poly(ethylene oxide) (PS-b-PEO) films exposed to ethanol- and water-saturated N 2 . We observed a quick increase and a subsequent gradual decrease in the ellipsometric thickness of PS-b-PEO films upon exposure to ethanol-saturated N 2 . This observation was unexpected because ethanol-saturated N 2 induced negligible thickness change for PS and PEO homopolymer films. The similarity in maximum thickness gain observed under ethanol- and water-saturated N 2 implied the swelling of PEO microdomains. Ethanol vapor permeation through the PEO microdomains was supported by the red-shift of the ensemble and single-molecule fluorescence emission of Nile red in PS-b-PEO films. Single-molecule tracking data showed the initial enhancement and subsequent reduction of the diffusion of hydrophilic sulforhodamine B molecules in PS-b-PEO films upon exposure to ethanol-saturated N 2 , consistent with the spectroscopic ellipsometry results. Furthermore, the higher ethanol susceptibility of the PEO microdomains was attributable to their amorphous nature, as shown by FTIR data.

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

Latent Representation Learning for Structural Characterization of Catalysts

Supervised machine learning-enabled mapping of the X-ray absorption near edge structure (XANES) spectra to local structural descriptors offers new methods for understanding the structure and function of working nanocatalysts. We briefly summarize a status of XANES analysis approaches by supervised machine learning methods. We present an example of an autoencoder-based, unsupervised machine learning approach for latent representation learning of XANES spectra. This new approach produces a lower-dimensional latent representation, which retains a spectrum–structure relationship that can be eventually mapped to physicochemical properties. Furthermore, the latent space of the autoencoder also provides a pathway to interpret the information content “hidden” in the X-ray absorption coefficient. Our approach (that we named latent space analysis of spectra, or LSAS) is demonstrated for the supported Pd nanoparticle catalyst studied during the formation of Pd hydride. By employing the low-dimensional representation of Pd K-edge XANES, the LSAS method was able to isolate the key factors responsible for the observed spectral changes.

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

Real-Space Local Dynamics of Molten Inorganic Salts Using Van Hove Correlation Function

Molten inorganic salts are attracting resurgent attention because of their unique physicochemical properties, making them promising media for next-generation concentrating solar power systems and molten salt reactors. The dynamics of these highly disordered ionic media is largely studied by theoretical simulations, while the robust experimental techniques capable of observing local dynamics are not well-developed. To provide fundamental insights into the atomic-scale transport properties of molten salts, we report the real-space dynamics of molten magnesium chloride at high temperatures employing the Van Hove correlation function obtained by inelastic neutron scattering. Overall, our results directly depict the distance-dependent dynamics of a molten salt on the picosecond time scale. This study demonstrates the capability of the developed approach to describe the locally correlated- and self-dynamics in molten salts, significantly improving our understanding of the interplay between microscopic structural parameters and their dynamics that ultimately control physical properties of condensed matter in extreme environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Expanded View of NMR Spin–Lattice Relaxation in Fluorine-Containing Ionic Liquids

Fluorine-containing anions are widely used in ionic liquids due to their unique physicochemical properties. However, the local dynamics of both cations and anions and their associated relaxation mechanisms remain incompletely understood. Here, we present a 1 H and 19 F spin–lattice relaxation rate (R1) study as a function of frequency over a broad frequency range from 30 kHz to 800 MHz for ionic liquids containing BF 4 – , PF 6 – , TFSI – , and FSI – anions and EMIM + cation. By combining experimental R 1 H and R 1 F NMR dispersion (NMRD) profiles with relaxation models for both dipolar spin interactions and chemical shift anisotropy (CSA) contributions, we demonstrate that CSA is needed to accurately describe the R 1 F relaxation behavior above ∼300 MHz, the extent of which depends on the anion structure. These findings challenge the long-standing assumption that dipolar contribution is the main source of 19 F relaxation in these systems and highlight the importance of including CSA to accurately interpret 19 F relaxation in ionic liquids, particularly at high frequencies. This work provides new insights into the molecular dynamics of fluorine-containing species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Accurate and Efficient Prediction of p K w in Aqueous Electrolytes Using Local Electrostatic Potentials

The K w =10 -pK w in aqueous electrolytes exhibit significant variations as a function of ion concentration. This behavior is not well-described by the Pitzer model, particularly at high concentrations. Here, we provide a molecular interpretation of the concentration dependent trends in p K w and develop a new method that accurately predicts the dissociation constant based upon the local electrostatic potential of the water oxygen that is determined by its nearest neighbors. The method is computationally efficient, relying only upon sampling of the local configurations (via molecular dynamics) and a small set of experimentally measured p K w . It is extensible to a range of salt compositions and the molecular understanding of the local potentials provides new routes toward the development of electrolytes with tailored physicochemical properties like p K w .

anions↗