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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 OSTI2020

A comparison of computational models for predicting yield sooting index

Sooting propensity, a measurement of how much particulate matter is produced when a fuel is burned, is a property of significant interest among researchers who are striving to discover the next generation of cleaner, more efficient fuels and fuel additives. Many compounds are not viable as fuels and/or fuel additives, and as a result, designing cleaner-burning biofuels using only experimental techniques is inefficient. Predictive models have been instrumental in reducing this inherent difficulty, providing researchers with a tool to preemptively screen compounds before production and testing. The present work compares the accuracies and interpretabilities of existing models used to predict a particular measure of sooting propensity, Yield Sooting Index (YSI). These models include artificial neural networks, graph neural networks, and multivariate equations. A novel equation for predicting YSI based on atom path count and bond order is proposed, which can highlight key structural components that contribute to YSI. It was found that artificial neural networks slightly outperform graph neural networks and greatly outperform multivariate equations in blind (test set) prediction accuracy; however, graph neural networks and multivariate equations provide significantly more interpretability as to how compound structure relates to YSI. Predictions of YSI are compared to experimental measurements for previously un-tested compounds with cetane numbers comparable to diesel fuel (50-60) (butyl decanoate, ethyl decanoate, 1,4-bis(ethenoxymethyl)cyclohexane, and 5-heptyloxolan-2-one), and it was found that these compounds produce significantly less soot compared to diesel fuel.

09 BIOMASS FUELS↗
DOE OSTI2022

High-Octane Gasoline from Lignocellulosic Biomass via Syngas and Methanol/Dimethyl Ether Intermediates (2021 State of Technology)

The 2021 state of technology (SOT) assessment for the indirect liquefaction (IDL) of lignocellulosic biomass to high-octane gasoline (HOG) via methanol and dimethyl ether (DME) intermediates details the techno-economic analysis (TEA) results and technical progress of the pathway since the 2020 SOT report. A detailed process description and collection of underlying assumptions is given the 2015 design report. In 2021, research efforts rigorously quantified the selectivity of DME to aromatic compounds. As a result, the overall carbon selectivity to hydrocarbon products was updated based upon new findings. Additionally, research conducted over the past few years resulted in successful lower temperature regeneration of NREL's Cu/BEA catalyst with favorable implications on catalyst longevity. Discussions with an engineering firm resulted in an update to the excess air requirement for process combustors (including the char combustor, tar reformer combustor, and catalyst regenerator) in which excess air was reduced from 20% excess to 10%. The cumulative effect of the above efforts was used to calculate a minimum fuel selling price for the modeled pathway. Sensitivity cases examining federal carbon tax credits from CO 2 capture, product selectivity and yield, catalyst lifetime, and other key financial and process parameters were also considered in this assessment.

09 BIOMASS FUELS↗
DOE OSTI2021

Efficient production of oxidized terpenoids via engineering fusion proteins of terpene synthase and cytochrome P450

The functionalization of terpenes using cytochrome P450 enzymes is a versatile route to the production of useful derivatives that can be further converted to value-added products. Many terpenes are hydrophobic and volatile making their availability as a substrate for P450 enzymes significantly limited during microbial production. In this study, we developed a strategy to improve the accessibility of terpene molecules for the P450 reaction by linking terpene synthase and P450 together. As a model system, fusion proteins of 1,8-cineole synthase (CS) and P450 cin were investigated and it showed an improved hydroxylation of the monoterpenoid 1,8-cineole up to 5.4-fold. Structural analysis of the CS-P450 cin fusion proteins by SEC-SAXS indicated a dimer formation with preferred orientations of the active sites of the two domains. We also applied the enzyme fusion strategy to the oxidation of a sesquiterpene epi-isozizaene and the fusion enzymes significantly improved albaflavenol production in engineered E. coli. From the analysis of positive and negative examples of the fusion strategy, we proposed key factors in structure-based prediction and evaluation of fusion enzymes. Developing fusion enzymes for terpene synthase and P450 presents an efficient strategy toward oxidation of hydrophobic terpene compounds. This strategy could be widely applicable to improve the biosynthetic titer of the functionalized products from hydrophobic terpene intermediates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Artificial Intelligence for Autonomous Molecular Design: A Perspective

Domain-aware artificial intelligence has been increasingly adopted in recent years to expedite molecular design in various applications, including drug design and discovery. Recent advances in areas such as physics-informed machine learning and reasoning, software engineering, high-end hardware development, and computing infrastructures are providing opportunities to build scalable and explainable AI molecular discovery systems. This could improve a design hypothesis through feedback analysis, data integration that can provide a basis for the introduction of end-to-end automation for compound discovery and optimization, and enable more intelligent searches of chemical space. Several state-of-the-art ML architectures are predominantly and independently used for predicting the properties of small molecules, their high throughput synthesis, and screening, iteratively identifying and optimizing lead therapeutic candidates. However, such deep learning and ML approaches also raise considerable conceptual, technical, scalability, and end-to-end error quantification challenges, as well as skepticism about the current AI hype to build automated tools. To this end, synergistically and intelligently using these individual components along with robust quantum physics-based molecular representation and data generation tools in a closed-loop holds enormous promise for accelerated therapeutic design to critically analyze the opportunities and challenges for their more widespread application. This article aims to identify the most recent technology and breakthrough achieved by each of the components and discusses how such autonomous AI and ML workflows can be integrated to radically accelerate the protein target or disease model-based probe design that can be iteratively validated experimentally. Taken together, this could significantly reduce the timeline for end-to-end therapeutic discovery and optimization upon the arrival of any novel zoonotic transmission event. Our article serves as a guide for medicinal, computational chemistry and biology, analytical chemistry, and the ML community to practice autonomous molecular design in precision medicine and drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Chemical-damage MINE: A database of curated and predicted spontaneous metabolic reactions

Spontaneous reactions between metabolites are often neglected in favor of emphasizing enzyme-catalyzed chemistry because spontaneous reaction rates are assumed to be insignificant under physiological conditions. However, synthetic biology and engineering efforts can raise natural metabolites' levels or introduce unnatural ones, so that previously innocuous or nonexistent spontaneous reactions become an issue. Problems arise when spontaneous reaction rates exceed the capacity of a platform organism to dispose of toxic or chemically active reaction products. While various reliable sources list competing or toxic enzymatic pathways' side-reactions, no corresponding compilation of spontaneous side-reactions exists, nor is it possible to predict their occurrence. We addressed this deficiency by creating the Chemical Damage (CD)-MINE resource. First, we used literature data to construct a comprehensive database of metabolite reactions that occur spontaneously in physiological conditions. We then leveraged this data to construct 148 reaction rules describing the known spontaneous chemistry in a substrate-generic way. We applied these rules to all compounds in the ModelSEED database, predicting 180,891 spontaneous reactions. The resulting (CD)-MINE is available at https://minedatabase.mcs.anl. gov/cdmine/#/home and through developer tools. We also demonstrate how damage-prone intermediates and end products are widely distributed among metabolic pathways, and how predicting spontaneous chemical damage helps rationalize toxicity and carbon loss using examples from published pathways to commercial products. We explain how analyzing damage-prone areas in metabolism helps design effective engineering strategies. Finally, we use the CD-MINE toolset to predict the formation of the novel damage product N-carbamoyl proline, and present mass spectrometric evidence for its presence in Escherichia coli.

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

Control and synchronization of rapid nanoscale DNA heat engine by local heating

To further activate devices based on DNA nanotechnology, we introduce an approach that notably enhances both the speed and force of DNA powered machines and artificial hinge machine. A microheater, with millisecond response, heats or recools DNA origami constructs, hybridizing or dehybridizing sticky ends. Because anything within 20 micrometers of the heater equilibrates to a programmed temperature change in milliseconds, sticky ends of a compound DNA origami machine can open and close synchronously and operate cooperatively, in phase, additively increasing the drive force compared to single pair of sticky ends DNA machine (the six-helix bundle DNA origami hinge machine). In our demonstrations, we fold and unfold two square origami with 10 pairs of complementary sticky ends to drive a bead on the end of a rod like origami to speeds exceeding 30 micrometers per second. Our device envisions the creation of complex, synchronized DNA machines.

Science & Technology - Other Topics↗
DOE OSTI2023

Facet-dependent electron transfer induces distinct arsenic reallocations on hematite

The interfacial electron transfer (ET) between electron shuttling compounds and iron (Fe) oxyhydroxides plays a crucial role in the reductive dissolution of Fe minerals and the fate of surface-bound arsenic (As). However, the impact of exposed facets of highly crystalline hematite on reductive dissolution and As immobilization is poorly understood. In this study, we systematically investigated the interfacial processes of the electron shuttling compound cysteine (Cys) on various facets of hematite and the reallocations of surface-bound As(III) or As(V) on the respective surfaces. Our results demonstrate that the ET process between Cys and hematite generates Fe(II) and leads to reductive dissolution, with more Fe(II) generated on {001} facets of exposed hematite nanoplates (HNPs). Reductive dissolution of hematite leads to significantly enhanced As(V) reallocations on hematite. Nevertheless, upon the addition of Cys, a raipd release of As(III) can be halted by its prompt re-adsorption, leaving the extent of As(III) immobilization on hematite unchanged throughout the course of reductive dissolution. This is due to that Fe(II) can form new precipitates with As(V), a process that is facet-dependent and influenced by water chemistry. Electrochemical analysis reveals that HNPs exhibit higher conductivity and ET ability, which is beneficial for reductive dissolution and As reallocations on hematite. In conclusion, these findings highlight the facet-dependent reallocations of As(III) and As(V) facilitated by electron shuttling compounds and have implications for the biogeochemical processes of As in soil and subsurface environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A topological kagome magnet in high entropy form

AbstractTopological kagome magnets RMn 6 Sn 6 (R = rare earth element) attract numerous interests due to their non-trivial band topology and room-temperature magnetism. Here, we report a high entropy version of kagome magnet, (Gd 0.38 Tb 0.27 Dy 0.20 Ho 0.15 )Mn 6 Sn 6 . Such a high entropy material exhibits multiple spin reorientation transitions, which is not seen in all the related parent compounds and can be understood in terms of competing magnetic interactions enabled by high entropy. Furthermore, we also observed an intrinsic anomalous Hall effect, indicating that the high entropy phase preserves the non-trivial band topology. These results suggest that high entropy may provide a route to engineer the magnetic structure and expand the horizon of topological materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Improved Methods for Modeling Functional Transition Metal Compounds in Complex Environments: Ground States, Excited States, and Spectroscopies

Rapid advances in energy applications require new theory and computational models to provide guidance for interpretation of experimental results and mechanistic understanding. New theory development is necessary to treat systems of increasing complexity, size, and relevance to real applications. Functional transition metal compounds, including molecules, clusters, nanoparticles, surfaces, and solids, provide particular promise for magnetic, optical, and catalytic applications. However, such systems can be exceptionally challenging to model. To make progress in understanding and designing transition metal compounds for energy applications, theory must be able to simulate such systems in complex environments, as well as simulate the spectra of such complex systems to provide direct connections with experiment. Leveraging the independent expertise of the team’s members, this project aimed to make inroads to the theoretical and computational challenges associated with studying transition metal compounds, their reaction chemistry, photophysics and photochemistry, and response to spectroscopic interrogation.

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

Layered and Low-Dimensional Lead, Silver, and Bismuth Halide Perovskites Directed by Halogen-Substituted Spacer Cations

Hybrid organic–inorganic metal halides provide a diverse parameter space in which the optoelectronic properties can be tuned through the composition. The compositional tunability extends to the metal site, which can be expanded from single valent metals (e.g., Pb 2+ ) to multivalent metals (e.g., Ag + and Bi 3+ ), and the dimension (2D, 1D, or 0D). However, a deeper understanding of how the organic cations template these metal halide structures is needed. Here, we synthesize and study the structures of a series of new layered and low-dimensional metal (Pb, Ag, and Bi) halides templated by the halogenated aryl spacer cations 2-chlorobenzylammonium (2ClBZ) and 3-chloro-2-fluorobenzylammonium (3Cl2FBZ). We report new lead perovskites, (3Cl2FBZ) 2 PbBr 4 , (2ClBZ) 3 PbI 5 , and (3Cl2FBZ) 2 PbI 4 , and compare them to their silver and/or bismuth analogs (2ClBZ) 4 AgBiBr 8 , (3Cl2FBZ) 4 AgBiBr 8 , (2ClBZ) 3 Bi 2 I 9 , and (3Cl2FBZ) 4 Bi 2 I 10 . In all structures, the halogen-substituted cations result in 2D or “pseudo-2D” layering, but the different halogen substituents introduce different distortions (tilting, octahedral distortion) and dimensional reduction to 1D or 0D depending on the metal and halide compositions. Optical absorption measurements reveal the bandgaps are tunable through metal sites, dimension, and cations to different extents. Furthermore, the 1D (3Cl2FBZ) 4 Bi 2 I 10 crystallizes in the noncentrosymmetric space group Cmc2 1 and exhibits second-harmonic generation (SHG). Furthermore, the organic–inorganic interactions and resultant structural distortions examined here provide insights toward the engineering of noncentrosymmetry and dimensional control in hybrid metal halide perovskites.

Cations↗
DOE OSTI2020

Controlling $T_c$ through Band Structure and Correlation Engineering in Collapsed and Uncollapsed Phases of Iron Arsenides

Recent observations of selective emergence (suppression) of superconductivity in the uncollapsed (collapsed) tetragonal phase of LaFe 2 As 2 has rekindled interest in understanding what features of the band structure control the superconducting $T_c$. In this work, we show that the proximity of the narrow Fe-$d_{xy}$ state to the Fermi energy emerges as the primary factor. In the uncollapsed phase this state is at the Fermi energy, and is most strongly correlated and a source of enhanced scattering in both single and two particle channels. The resulting intense and broad low energy spin fluctuations suppress magnetic ordering and simultaneously provide glue for Cooper pair formation. In the collapsed tetragonal phase, the $d_{xy}$ state is driven far below the Fermi energy, which suppresses the low-energy scattering and blocks superconductivity. A similar source of broad spin excitation appears in uncollapsed and collapsed phases of CaFe 2 As 2 . This suggests controlling coherence provides a way to engineer $T_c$ in unconventional superconductors primarily mediated through spin fluctuations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Separating Miscible Liquid–Liquid Mixtures Using Supported Ionic Liquid Membranes

Supported liquid membranes (SLMs) are promising in separating miscible liquid–liquid mixtures, which has been a key challenge in wastewater treatment and other applications. However, SLMs suffer from poor durability due to the loss of the liquid phase. In current work, ionic liquids (ILs) with high stability have been impregnated into polyvinylidene fluoride membranes to separate miscible benzene–heptane mixtures. The two imidazolium-based ILs, that is, 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF 6 ]) and 1-butyl-3-methylimidazolium tris(pentafluoroethyl) trifluorophosphate ([BMIM][FAP]), were tested in supported ionic liquid membranes (SILMs) for the benzene–heptane separation. Both ILs show successful separation within 48 h as indicated by nuclear magnetic resonance results. Compared to the SILM with [BMIM][FAP], the SILM with [BMIM][PF 6 ] has lower throughput and higher selectivity. The higher selectivity can be attributed to the higher hydrophilicity of [BMIM][PF 6 ], which results in strong repulsion against heptane. The lower throughput can be attributed to the higher hydrophilicity as well since it lowers the solubility of benzene in [BMIM][PF 6 ]. The stability of IL in SILMs has also been investigated via multiple separation cycles. The scanning electron microscopy, weight change of SILMs, and separation results indicate that the separation efficiency of the [BMIM][PF 6 ] SILM does not degrade for up to 144 h. The SILM has been further optimized with curvature design (i.e., curved SILM) to increase the interfacial area and thus increase the separation throughput, where the curved SILM separation device was 3D-printed. Here, the findings here have important implications on design and application of SILMs in separating miscible liquid–liquid mixtures.

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

Engineering Pseudomonas putida KT2440 for chain length tailored free fatty acid and oleochemical production

Abstract Despite advances in understanding the metabolism of Pseudomonas putida KT2440, a promising bacterial host for producing valuable chemicals from plant-derived feedstocks, a strain capable of producing free fatty acid-derived chemicals has not been developed. Guided by functional genomics, we engineered P. putida to produce medium- and long-chain free fatty acids (FFAs) to titers of up to 670 mg/L. Additionally, by taking advantage of the varying substrate preferences of paralogous native fatty acyl-CoA ligases, we employed a strategy to control FFA chain length that resulted in a P. putida strain specialized in producing medium-chain FFAs. Finally, we demonstrate the production of oleochemicals in these strains by synthesizing medium-chain fatty acid methyl esters, compounds useful as biodiesel blending agents, in various media including sorghum hydrolysate at titers greater than 300 mg/L. This work paves the road to produce high-value oleochemicals and biofuels from cheap feedstocks, such as plant biomass, using this host.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Interband Transitions and Critical Points of Single-Crystal Thoria Compared with Urania

The interband transitions of UO 2 are validated independently through cathode luminescence. A picture emerges consistent with density functional theory. While theory is generally consistent with experiment, it is evident from the comparison of UO 2 and ThO 2 that the choice of functional can significantly alter the bandgap and some details of the band structure, in particular at the conduction band minimum. Strictly ab initio predictions of the optical properties of the actinide compounds, based on density functional theory alone, continue to be somewhat elusive.

42 ENGINEERING↗
DOE OSTI2025

Shifting the MLCT of d 6 metal complexes to the red and NIR

Light-active d 6 -coordination compounds hold great promise for light energy conversion, sensors and therapeutic applications. However, the activity in the red-to-NIR spectral region is highly desirable to convert solar light more efficiently, use low-cost red-light sources and activate these chromophores in biological tissue environment. Due to their versatility, tunability and broad intense absorption, d 6 -coordination compounds with metalto-ligand charge transfer (MLCT) transitions are especially interesting. This review article offers a comprehensive collection of strategies to tune MLCT excited states in d 6 metal complexes and gives insights on group 6 to group 9 transition metals and their respective state-of-the-art MLCT engineering towards red-shifted absorption and emission properties with long-lived excited states. Strategies comprise lowering the π* level of the ligands, destabilizing and mixing of the metal-based HOMO, switching within a group of transition metals, matrix effects and insights into dealing with excited state deactivation in the context of the energy gap law.

Metal to ligand charge transfer (MLCT)↗
DOE OSTI2024

Desorption lifetimes and activation energies influencing gas–surface interactions and multiphase chemical kinetics

Abstract. Adsorption and desorption of gases on liquid or solid substrates are involved in multiphase processes and heterogeneous chemical reactions. The desorption energy (Edes0), which depends on the intermolecular forces between adsorbate and substrate, determines the residence time of chemical species at interfaces. We show how Edes0 and temperature influence the net uptake or release of gas species, the rates of surface–bulk exchange and surface or bulk reactions, and the equilibration timescales of gas–particle partitioning. Using literature data, we derive a parameterization to estimate Edes0 for a wide range of chemical species based on the molecular mass, polarizability, and oxygen-to-carbon ratio of the desorbing species independent of substrate-specific properties, which is possible because of the dominant role of the desorbing species' properties. Correlations between Edes0 and the enthalpies of vaporization and solvation are rooted in molecular interactions. The relation between Edes0 and desorption kinetics reflects the key role of interfacial exchange in multiphase processes. For small molecules and semi-volatile organics (VOC, IVOC, SVOC), Edes0 values around 10–100 kJ mol−1 correspond to desorption lifetimes around nanoseconds to days at room temperature. Even higher values up to years are obtained at low temperatures and for low volatile organic compounds (LVOC, ELVOC/ULVOC) relevant for secondary organic aerosols (SOA). Implications are discussed for SOA formation, gas–particle partitioning, organic phase changes, and indoor surface chemistry. We expect these insights to advance the mechanistic and kinetic understanding of multiphase processes in atmospheric and environmental physical chemistry, aerosol science, materials science, and chemical engineering.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sooting tendencies of 20 bio-derived fuels for advanced spark-ignition engines

The sooting tendencies of 20 bio-derived fuels indicated as potential blendstocks for spark-ignition engines by the Co-Optimization of Fuels & Engines (Co-Optima) Initiative are studied. The Yield Sooting Index (YSI) is used to quantify the sooting tendencies. The Co-Optima Chemical Model is used to predict the numerical YSIs for all test fuels, and these results are compared with measurements. Experimental YSIs are newly measured for 2 furans and are taken from our previous work for the other compounds. Overall, the predicted YSIs agree well with measurements, within the experimental uncertainties, except for 2,5-dimethylfuran (2,5-DMF). It is found that Polycyclic Aromatic Hydrocarbons (PAH) growth reactions have little influence on the relative soot production from each fuel and therefore on YSI predictions. A modified sensitivity coefficient formulation is proposed to evaluate reaction sensitivities specifically for YSI. This formulation is applied to the 2,5-DMF-doped flame, and six 2,5-DMF initial decomposition reactions, which lead to different major soot precursors, are identified as the most sensitive reactions. The impact of the chemical kinetic uncertainties embedded in these reactions is quantified by randomly perturbing their reaction rates within a factor of two. The resulting prediction uncertainty in the 2,5-DMF-doped flame is found to be ± 8 YSI units (±11%), which demonstrates that the test-fuel-specific decomposition reactions indeed have considerable influence on its YSI prediction. Our research suggests that more accurate kinetic parameters for fuel initial decomposition reactions can potentially improve YSI predictions effectively, without altering the YSI predictions of other fuels with significantly different molecular structures.

09 BIOMASS FUELS↗
DOE OSTI2022

Data Fusion via Neural Network Entropy Minimization for Target Detection and Multi-Sensor Event Classification

Broadly applicable solutions to multimodal and multisensory fusion problems across domains remain a challenge because effective solutions often require substantive domain knowledge and engineering. The chief questions that arise for data fusion are in when to share information from different data sources, and how to accomplish the integration of information. The solutions explored in this work remain agnostic to input representation and terminal decision fusion approaches by sharing information through the learning objective as a compound objective function. The objective function this work uses assumes a one-to-one learning paradigm within a one-to-many domain which allows the assumption that consistency can be enforced across the one-to-many dimension. The domains and tasks we explore in this work include multi-sensor fusion for seismic event location and multimodal hyperspectral target discrimination. We find that our domain- informed consistency objectives are challenging to implement in stable and successful learning because of intersections between inherent data complexity and practical parameter optimization. While multimodal hyperspectral target discrimination was not enhanced across a range of different experiments by the fusion strategies put forward in this work, seismic event location benefited substantially, but only for label-limited scenarios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗