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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Molecular Characterization of Organosulfate-Dominated Aerosols over Agricultural Fields from the Southern Great Plains by High-Resolution Mass Spectrometry

The molecular composition of organic aerosols, especially for day/nighttime variations of organosulfates above agricultural fields, is not well understood despite profound impacts on regional climate, crop production, air quality, and human health. Here, nanospray desorption electrospray ionization with high-resolution mass spectrometry (nano-DESI-HRMS) is used to interrogate the molecular composition of organic aerosols collected at the Southern Great Plains, located in an agricultural region of Oklahoma. Identified molecular formulae featured carbon, hydrogen, oxygen (CHO), nitrogen (CHNO), and/or sulfur (CHOS, CHNOS), with higher organosulfate proportions during daytime (41%) compared to nighttime (30%). In this work, nighttime aerosols featured increases in CHO, CHNO, and extremely low volatility organic carbon (ELVOC) species. However, due to high relative humidity, the nighttime aerosols phase state was found to be more liquid-like than daytime aerosols using parametrized glass transition temperatures. Aerosol molecular composition from an anthropogenically influenced plume (southerly winds) showed significant increases in CHOS and ELVOC species. By comparison with chamber studies, CHOS species are suspected to be of mixed biogenic and anthropogenic origin, whereas CHNOS species (not identified in the southerly winds) are suggested to predominately be of biogenic origin. Overall, this study provides key insight into organosulfates above agricultural fields, demonstrating dependence upon day/night cycles and episodic anthropogenic emissions.

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

Mechanistic Insights into the Conversion of Biorenewable Levoglucosanol to Dideoxysugars

Here, a molecular understanding of the conversion of biorenewable threo- and erythro-levoglucosanol (LGOL) to 3,4-dideoxysugars in aqueous medium is provided based on first-principles simulations. The synthetic importance of this transformation is that these intermediates can be quantitatively hydrogenated to (S,S)/(S,R) hexane-1,2,5,6-tetrol (tetrol), whose stereochemistry depends on which dideoxy sugar intermediates are formed during LGOL conversion. The thermodynamic and kinetic feasibility of the acetal (R 2 C(OR) 2 ) hydrolysis in LGOL is investigated via computing the free energy profile. In aqueous medium, the rate-determining step of LGOL hydrolysis is the protonation of the anhydro-bridge oxygen atom of LGOL concurrent with ring opening, yielding the cyclic forms of 3,4-dideoxymannose (DDM) and 3,4-dideoxyglucose (DDG) from threo- and erythro-LGOL, respectively. The measured activation energies of LGOL hydrolysis are 20.5 and 23.6 kcal/mol for DDM and DDG formation, respectively. These values are in agreement with the computed protonation free energies of 17.1 and 18.2 kcal/mol, respectively. Based on the simulations, a Bronsted base-catalyzed isomerization from DDG or DDM to 3,4-dideoxy fructose (DDF) is preferred with lower apparent activation free energy barriers compared to the acid-catalyzed isomerization. In summary, this study provides mechanistic information about the conversion of the biomass-derived anhydro-sugar LGOL to 3,4-dideoxy sugars, which are precursors to renewable high-value chemicals.

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

LoTToR: An Algorithm for Missing-Wedge Correction of the Low-Tilt Tomographic 3D Reconstruction of a Single-Molecule Structure

A single-molecule three-dimensional (3D) structure is essential for understanding the thermal vibrations and dynamics as well as the conformational changes during the chemical reaction of macromolecules. Individual-particle electron tomography (IPET) is an approach for obtaining a snap-shot 3D structure of an individual macromolecule particle by aligning the tilt series of electron tomographic (ET) images of a targeted particle through a focused iterative 3D reconstruction method. The method can reduce the influence on the 3D reconstruction from large-scale image distortion and deformation. Due to the mechanical tilt limitation, 3D reconstruction often contains missing-wedge artifacts, presented as elongation and an anisotropic resolution. Here, we report a post-processing method to correct the missing-wedge artifact. This low-tilt tomographic reconstruction (LoTToR) method contains a model-free iteration process under a set of constraints in real and reciprocal spaces. A proof of concept is conducted by using the LoTToR on a phantom, i.e., a simulated 3D reconstruction from a low-tilt series of images, including that within a tilt range of ±15°. The method is validated by using both negative-staining (NS) and cryo-electron tomography (cryo-ET) experimental data. A significantly reduced missing-wedge artifact verifies the capability of LoTToR, suggesting a new tool to support the future study of macromolecular dynamics, fluctuation and chemical activity from the viewpoint of single-molecule 3D structure determination.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A framework to evaluate machine learning crystal stability predictions

The rapid adoption of machine learning in various scientific domains calls for the development of best practices and community agreed-upon benchmarking tasks and metrics. We present Matbench Discovery as an example evaluation framework for machine learning energy models, here applied as pre-filters to first-principles computed data in a high-throughput search for stable inorganic crystals. We address the disconnect between (1) thermodynamic stability and formation energy and (2) retrospective and prospective benchmarking for materials discovery. Alongside this paper, we publish a Python package to aid with future model submissions and a growing online leaderboard with adaptive user-defined weighting of various performance metrics allowing researchers to prioritize the metrics they value most. To answer the question of which machine learning methodology performs best at materials discovery, our initial release includes random forests, graph neural networks, one-shot predictors, iterative Bayesian optimizers and universal interatomic potentials. We highlight a misalignment between commonly used regression metrics and more task-relevant classification metrics for materials discovery. Accurate regressors are susceptible to unexpectedly high false-positive rates if those accurate predictions lie close to the decision boundary at 0 eV per atom above the convex hull. The benchmark results demonstrate that universal interatomic potentials have advanced sufficiently to effectively and cheaply pre-screen thermodynamic stable hypothetical materials in future expansions of high-throughput materials databases.

Riebesell, Janosh↗
DOE OSTI2026

Modeling the behavior of concentrated aqueous HNO 3 using machine learning interatomic potentials

We develop two multi-defect machine learning interatomic potentials (MLIPs) trained at the BLYP-D2 and PBE-D3 density functional theories using the DeepMD-kit, allowing for the investigation of structural and thermodynamic properties of nitric acid over a wide range of concentrations via molecular dynamics (MD) simulations. We directly compute the degree of dissociation, α, and pK a from MD simulations, revealing that HNO 3 behaves as a weaker acid at higher concentrations, noting that our standard-state pK a value is in excellent agreement with the experimental one. In general, good agreement is observed with experimental results such as α and density outside the training dataset, with only modest deviations at low-to-medium concentrations. We benchmark our custom multi-defect DeepMD MLIPs against foundational models MACE-MP0 and MACE-OFF23. The foundation models capture some aspects of HNO 3 /NO 3 − solvation in concentrated nitric acid but show noticeable density errors and miss subtle structural features relevant to spectroscopy, whereas the bespoke DeepMD MLIPs yield more compact solvation shells, reproduce density-concentration trends, and run ∼12–15× faster than MACE-MP0. Although classical FFs are still more efficient and match experimental densities better, they lack chemical reactivity and thus cannot predict α or pK a , underscoring the need for system-specific reactive MLIPs beyond universal MLIPs.

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗
DOE OSTI2025

Towards a Deeper Fundamental Understanding of (Al,Sc)N Ferroelectric Nitrides

Density functional theory (DFT) calculations, within the virtual crystal alloy approximation, are performed, along with the development of a Landau-type model employing a symmetry-allowed analytical expression of the internal energy and having parameters determined from first principles, to investigate properties and energetics of Al1-xScxN ferroelectric nitrides in their hexagonal forms. These DFT computations and this model predict the existence of two different types of minima, namely, the fourfold-coordinated wurtzite (WZ) polar structure and a five-fold coordinated paraelectric hexagonal phase (denoted as H5), for any Sc composition up to 40%. The H5 minimum progressively becomes the lowest-energy state within hexagonal symmetry as the Sc concentration increases from 0 to 0.4. Furthermore, the model points to several key findings. Examples include the crucial role of the coupling between polarization and strains to create the WZ minimum, in addition to polar and elastic energies, and that the origin of the H5 state overcoming the WZ phase as the global minimum within hexagonal symmetry when increasing the Sc composition mostly lies in the compositional dependency of only two parameters-one linked to the polarization and another one being purely elastic in nature. Other examples are that forcing Al1-xScxN systems to have no or a weak change in lattice parameters when heating them allows us to reproduce their finite-temperature polar properties well and that a value of the axial ratio close to that of the ideal WZ structure implies a large polarization at low temperatures but not necessarily at high temperatures because of the ordered-disordered character of the temperature-induced formation of the WZ state. Such findings should allow for a better fundamental understanding of (Al,Sc)N ferroelectric nitrides, which may be used to design efficient devices having, e.g., low operating voltages.

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

pnnl/Pathway_Controlled_Optimization

A method for prediction of cell regulation to maximize cell growth rate while maintaining the solvent capacity of the cell. Prediction is formulated as an optimization problem using a thermodynamic framework that can leverage experimental data. We develop a formulation and variable initialization procedure that allows for computing solutions of the optimization with an interior point method

Central, PNNL Developer↗
DOE OSTI2021

Cooperative Research and Development Agreement among National Energy Technology Laboratory, Advanced Manufacturing LLC, and Connecticut Center for Advanced Technology [Abstract]

The National Energy Technology Laboratory (NETL), Advanced Manufacturing LLC (AMLLC) and Connecticut Center for Advanced Technology (CCAT) will collaborate to develop and manufacture cost-effective, oxide dispersion-strengthened, NiCrFeCo-rich high entropy alloys that are superior to Nickel-based superalloys (e.g. IN740) for repair or replacement service in extreme environments. The new alloys can result in higher efficiency and reduced cost of advanced power systems such as advanced ultra-supercritical (AUSC) boilers and gas turbines. High throughput, multiscale computational modeling will be performed to accelerate alloy discovery by interrogating the intrinsic properties of the alloys including thermodynamic, kinetic, and mechanical properties. Validation and evaluation will be performed, including additive manufacturing, microstructure characterization, and mechanical properties tests.

36 MATERIALS SCIENCE↗
DOE OSTI2023

An approach to learn regulation to maximize growth and entropy production rates in metabolism

Elucidating cell regulation remains a challenging task due to the complexity of metabolism and the difficulty of experimental measurements. Here we present a method for prediction of cell regulation to maximize cell growth rate while maintaining the solvent capacity of the cell. Prediction is formulated as an optimization problem using a thermodynamic framework that can leverage experimental data. We develop a formulation and variable initialization procedure that allows for computing solutions of the optimization with an interior point method. The approach is applied to photoheterotrophic growth of Rhodospirilium rubrum using ethanol as a carbon source, which has applications to biosynthesis of ethylene production. Growth is captured as the rate of synthesis of amino acids into proteins, and synthesis of nucleotide triphoshaptes into RNA and DNA. The method predicts regulation that produces a high rate of protein and RNA synthesis while DNA synthesis is reduced close to zero in agreement with production of DNA being turned off for much of the cell cycle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Divergent carbon use efficiency-growth rate tradeoff in popular biological growth models

Carbon use efficiency (CUE) is an important trait emerging from processes regulating biological growth. CUE can be computed either based on the growth of structural biomass or total biomass divided by substrate uptake rate. Nonequilibrium thermodynamics and observations suggest that, for an exponentially growing population of cells, structural biomass CUE should first increase, then peak, and finally decrease with specific growth rate; meanwhile, total biomass CUE increases asymptotically with specific growth rate. We compared predictions from six popular models that are often used for plant and microbial growth in existing ecosystem models. We found that, for an exponentially growing population of biological cells, (1) the source-driven Pirt and Compromise models predict that structural biomass CUE increase asymptotically with growth rate; (2) the apparent sink-driven modified Droop model predicts that structural biomass CUE decreases with growth rate; and (3) the sink-driven variable internal storage model and two dynamic energy budget models predict that structural biomass CUE first increases, then peaks, and finally decreases with growth rate. Moreover, the modified Droop model predicts that total biomass CUE is constant with growth rate, while all other five models predict that total biomass CUE increases with growth rate asymptotically. For non-exponential biological growth, we show that there is no static relationship between total biomass CUE or structural biomass CUE with respect to either growth rate or temperature. Therefore, we contend that biological growth models should explicitly represent interactions between substrate acquisition, substate transformation, and maintenance respiration to better capture observed CUE dynamics, and the sink-driven model should be preferred for general ecosystem biogeochemistry modeling.

Tang, Jinyun [Lawrence Berkeley National Laborator↗
NASA NTRS1985

Component-specific modeling

Accomplishments are described for the second year effort of a 3-year program to develop methodology for component specific modeling of aircraft engine hot section components (turbine blades, turbine vanes, and burner liners). These accomplishments include: (1) engine thermodynamic and mission models; (2) geometry model generators; (3) remeshing; (4) specialty 3-D inelastic stuctural analysis; (5) computationally efficient solvers, (6) adaptive solution strategies; (7) engine performance parameters/component response variables decomposition and synthesis; (8) integrated software architecture and development, and (9) validation cases for software developed.

Mcknight, R. L.↗
DOE OSTI2026

RidgeAlloy: A high pressure die casting alloy that captures the approaching wave of automotive body sheet scrap

Oak Ridge National Laboratory (ORNL) has recently launched an effort to economically expand the North American aluminum supply chain by designing and developing a new family of Al-Mg-Si-Fe-Mn structural die cast aluminum alloys that can be made from up to 100% mixed 5xxx and 6xxx series automotive post-consumer sheet scrap and do not require heat treatment. The goal is to develop an alloy capable of capturing the approaching scrap wave of aluminum sheet intensive vehicles (in the 2030’s) into integrated structural high pressure die castings, rather than down-cycling these high-grade sheet alloys into non-structural castings. ORNL discovered a significant gap in the commercial thermodynamic databases that were unable to predict the trends of a key primary intermetallic phase as a function of composition. Experiments were performed to correct this gap and to create a unique, corrected quaternary database for Al-Mg-Si-Fe. High throughput computational methods, including solidification simulations, were used to identify a composition volume capable of avoiding this embrittling primary intermetallic phase, even at higher Fe + Si contents. Laboratory scale castings validated the thermodynamic and solidification predictions and resulted in lab-cast alloys with little primary intermetallic, and which met or exceeded structural casting properties requirements for yield strength and ductility. An accelerated demonstration of an HPDC automotive part was conducted in collaboration with two U.S. small businesses. Ingots made from 100% recycled 5xxx and 6xxx series scrap (plus Fe) were used to die cast one variant of this new family of Al-Mg-Si-Fe-Mn alloys (with high Si + Fe content) into a mid-sized HPDC structural-type automotive component. The HPDC alloy demonstration part showed good properties (especially ductility) and good castability for a complex component.

Plotkowski, Alex [ORNL] (ORCID:0000000154718681)↗
NASA NTRS1986

Effect of subcooling on the on-orbit pressurization rate of cryogenic propellant tankage

The SOLA-ECLIPSE code is being developed to enable prediction of the behavior of cryogenic propellants in spacecraft tankage. A brief description of the formulations used for modeling heat transfer and for determining thermodynamic state is presented. Code performance is verified through comparison to experimental data for the self-pressurization of scale model liquid hydrogen tanks. SOLA-ECLIPSE is used to examine the effect of initial subcooling of the liquid phase on the self-pressurization rate of an on-orbit full scale liquid hydrogen tank typical for a chemical propulsion Orbital Transfer Vehicle. The computational predictions show that even small amounts of subcooling will significantly decrease the self-pressurization rate. Further, if the cooling is provided by a Thermodynamic Vent System, it is concluded that small levels of subcooling will maximize propellant conservation.

Hochstein, J. I.↗
NASA NTRS1986

Simplified curve fits for the thermodynamic properties of equilibrium air

New improved curve fits for the thermodynamic properties of equilibrium air were developed. The curve fits are for p = p(e,rho), a = a(e,rho), T = T(e,rho), s = s(e,rho), T = T(p,rho), h = h(p,rho), rho = rho(p,s), e = e(p,s) and a = a(p,s). These curve fits can be readily incorporated into new or existing Computational Fluid Dynamics (CFD) codes if real-gas effects are desired. The curve fits were constructed using Grabau-type transition functions to model the thermodynamic surfaces in a piecewise manner. The accuracies and continuity of these curve fits are substantially improved over those of previous curve fits appearing in NASA CR-2470. These improvements were due to the incorporation of a small number of additional terms in the approximating polynomials and careful choices of the transition functions. The ranges of validity of the new curve fits are temperatures up to 25,000 K and densities from 10 to the minus 7th to 100 amagats (rho/rho sub 0).

Srinivasan, S.↗
DOE OSTI2026

Time irreversibility as an indicator of approaching tipping points in Earth subsystems

With shifting environmental trends, many Earth system elements may be poised to undergo critical transitions or ‘tipping’. Reliable anticipation of these tipping elements is vital to inform policy decisions. Many of the current methods for tipping point detection are based on loss of resilience or ‘critical slowdown’ of the system as it approaches a tipping point. However, these methods are prone to false alarms; the detected slowdown may be an artifact of nonstationary noise unrelated to tipping behavior. Here, we explore the efficacy of early warning signs based on a nonequilibrium thermodynamics framework. The model-free detection method relies on the increased intrinsic time-irreversibility due to detailed balance breaking, preceding the onset of tipping or instabilities. We demonstrate that these EWSs are effective for tipping point detection and robust against false alarms due to nonstationary noise, using idealized models for two key elements of the Earth system that are prone to tipping: the Atlantic Meridional Overturning Circulation and Arctic sea-ice loss.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Prediction of self-pressurization rate of cryogenic propellant tankage

The SOLA-ECLIPSE code is being developed to enable prediction of the behavior of cryogenic propellants in spacecraft tankage. A brief description of the formulations used for modeling heat transfer and for determining the thermodynamic state is presented. Code performance is verified through comparison to experimental data for the self-pressurization of scale-model liquid hydrogen tanks. SOLA-ECLIPSE is used to examine the effect of initial subcooling of the liquid phase on the self-pressurization rate of an on-orbit full-scale liquid hydrogen tank typical for a chemical-propulsion orbit transfer vehicle. The computational predictions show that even small amounts of subcooling will significantly decrease the self-pressurization rate. Further, if the cooling is provided by a thermodynamic vent system, it is concluded that small levels of subcooling will maximize propellant conservation.

Hochstein, John I.↗
DOE OSTI2025

Proton, Electron, and Hydrogen-Atom Transfer Thermodynamics of the Metal–Organic Framework, Ti-MIL-125, Are Intrinsically Correlated to the Structural Disorder

Interfacial charge transfer reactions involving protons and/or electrons are fundamental to heterogeneous catalysis and many other reactions relevant to energy, chemical, and biological sectors. Metal–organic frameworks (MOFs) with redox-active metal-oxo nodes have emerged as candidate materials to examine these reactions with near-atomic-level precision, given their crystalline nature. Here, we employed a colloidally stable, Ti-based MOF, Ti-MIL-125, with different crystal sizes to examine catalytically relevant charge transfer thermodynamics. The Ti 8 (μ 2 -O) 8 (μ 2 -OH) 4 nodes structurally mimic TiO 2 , which has shown some PCET reactivity toward reactions of H 2 , O 2 , and others. In this report, we have demonstrated that a change in crystal size induces different amounts of structural disorder to the Ti-oxo node, further changing the thermodynamics of proton/electron/hydrogen-atom transfer reactions. Using electrochemical open-circuit potential (E OCP ) measurements, we have determined that all crystallites undergo a 1H + /1e – redox reaction, which, given the stoichiometry, can be considered as a net H atom transfer (HAT) reaction. The thermodynamics of this HAT reaction, the Ti 3+ O–H bond dissociation free energy (BDFE), was dependent on the crystal size of the MOF, as the decrease in crystal size induced more structural disorder. Our computational calculations have indicated that this difference in BDFE is due to a local change in the geometry of Ti cations, rather than the commonly invoked defects, such as the “missing-linker” defect sites. Individual proton/electron transfer (PT/ET) thermodynamics were also highly dependent on the crystal sizes. These were probed using pK a or band gaps (E g ), respectively. These findings suggest that, particularly when MOFs are nanosized with a large amount of structural disorder, they should no longer be considered “true” single-site catalysts; this is an implicit, but widespread assumption within the MOF-based catalysis field. Implications of these findings will be contrasted with structurally similar metal oxides like TiO 2 and other redox-active MOFs.

Bond dissociation free energy↗
DOE OSTI2024

Quantum computation of stopping power for inertial fusion target design

Stopping power is the rate at which a material absorbs the kinetic energy of a charged particle passing through it—one of many properties needed over a wide range of thermodynamic conditions in modeling inertial fusion implosions. First-principles stopping calculations are classically challenging because they involve the dynamics of large electronic systems far from equilibrium, with accuracies that are particularly difficult to constrain and assess in the warm-dense conditions preceding ignition. Here, we describe a protocol for using a fault-tolerant quantum computer to calculate stopping power from a first-quantized representation of the electrons and projectile. Our approach builds upon the electronic structure block encodings of Su et al. [ PRX Quant. 2 , 040332 (2021)], adapting and optimizing those algorithms to estimate observables of interest from the non-Born–Oppenheimer dynamics of multiple particle species at finite temperature. We also work out the constant factors associated with an implementation of a high-order Trotter approach to simulating a grid representation of these systems. Ultimately, we report logical qubit requirements and leading-order Toffoli costs for computing the stopping power of various projectile/target combinations relevant to interpreting and designing inertial fusion experiments. We estimate that scientifically interesting and classically intractable stopping power calculations can be quantum simulated with roughly the same number of logical qubits and about one hundred times more Toffoli gates than is required for state-of-the-art quantum simulations of industrially relevant molecules such as FeMoco or P450.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗