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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

A first-principles theoretical approach to heterogeneous nanocatalysis

A theoretical approach to heterogeneous catalysis by sub-nanometre supported metal clusters and alloys is presented and discussed. Its goal is to perform a computational sampling of the reaction paths in nanocatalysis via a global search in the phase space of structures and stoichiometry combined with filtering which takes into account the given experimental conditions (catalytically relevant temperature and reactant pressure), and corresponds to an incremental exploration of the disconnectivity diagram of the system. The approach is implemented and applied to the study of propylene partial oxidation by Ag3 supported on MgO(100). First-principles density-functional theory calculations coupled with a Reactive Global Optimization algorithm are performed, finding that: (1) the presence of an oxide support drastically changes the potential energy landscape of the system with respect to the gas phase, favoring configurations which interact positively with the electrostatic field generated by the surface; (2) the reaction energy barriers for the various mechanisms are crucial in the competition between thermodynamically and kinetically favored reaction products; (3) a topological database of structures and saddle points is produced which has general validity and can serve for future studies or for deriving general trends; (4) the MgO(100) surface captures some major features of the effect of an oxide support and appears to be a good model of a simple oxide substrate; (5) strong cooperative effects are found in the co-adsorption of O2 and other ligands on small metal clusters. The proposed approach appears as a viable route to advance the role of predictive computational science in the field of heterogeneous nanocatalysis.

Chemistry↗
DOE OSTI2021

Toward autonomous design and synthesis of novel inorganic materials

Autonomous experimentation driven by artificial intelligence (AI) provides an exciting opportunity to revolutionize inorganic materials discovery and development. Herein, we review recent progress in the design of self-driving laboratories, including robotics to automate materials synthesis and characterization, in conjunction with AI to interpret experimental outcomes and propose new experimental procedures. We focus on efforts to automate inorganic synthesis through solution-based routes, solid-state reactions, and thin film deposition. In each case, connections are made to relevant work in organic chemistry, where automation is more common. Characterization techniques are primarily discussed in the context of phase identification, as this task is critical to understand what products have formed during synthesis. The application of deep learning to analyze multivariate characterization data and perform phase identification is examined. To achieve “closed-loop” materials synthesis and design, we further provide a detailed overview of optimization algorithms that use active learning to rationally guide experimental iterations. Lastly, we highlight several key opportunities and challenges for the future development of self-driving inorganic materials synthesis platforms.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Analytical Identification Method of Generalized Short‐Circuit Ratio Using Phasor Measurement Units

This paper introduces a novel analytical approach for the identification of the admittance matrix and the generalized short-circuit ratio (gSCR) in power systems integrated with renewable energy sources. The proposed method leverages voltage and current measurements from phasor measurement units (PMUs) to construct a least squares objective function, which is then solved using matrix calculus and partial derivatives. Unlike conventional optimization algorithms, this approach provides an analytical solution that substantially reduces data requirements, enabling the efficient and accurate identification of the gSCR with smaller datasets. Additionally, its fixed computational complexity allows for real-time updates as new data are collected, ensuring continuous refinement of the system of equations and enabling rapid, precise gSCR calculations. The method also exhibits strong robustness against measurement noise, making it well-suited for practical applications in dynamic power systems. The combination of reduced data requirements, real-time adaptability, noise robustness and fixed computational load establishes this method as a highly efficient and reliable tool for real-time power system stability analysis. Case studies on an EPRI 36-bus system demonstrate the method's effectiveness, highlighting its accuracy in closely matching true gSCR values, even under diverse disturbances and noisy conditions.

Han, Zelei [Hohai University, Nanjing (China)] (OR↗
DOE OSTI2014

The metallization and superconductivity of dense hydrogen sulfide

Hydrogen sulfide (H{sub 2}S) is a prototype molecular system and a sister molecule of water (H{sub 2}O). The phase diagram of solid H{sub 2}S at high pressures remains largely unexplored arising from the challenges in dealing with the pressure-induced weakening of S–H bond and larger atomic core difference between H and S. Metallization is yet achieved for H{sub 2}O, but it was observed for H{sub 2}S above 96 GPa. However, the metallic structure of H{sub 2}S remains elusive, greatly impeding the understanding of its metallicity and the potential superconductivity. We have performed an extensive structural study on solid H{sub 2}S at pressure ranges of 10–200 GPa through an unbiased structure prediction method based on particle swarm optimization algorithm. Besides the findings of candidate structures for nonmetallic phases IV and V, we are able to establish stable metallic structures violating an earlier proposal of elemental decomposition into sulfur and hydrogen [R. Rousseau, M. Boero, M. Bernasconi, M. Parrinello, and K. Terakura, Phys. Rev. Lett. 85, 1254 (2000)]. Our study unravels a superconductive potential of metallic H{sub 2}S with an estimated maximal transition temperature of ∼80 K at 160 GPa, higher than those predicted for most archetypal hydrogen-containing compounds (e.g., SiH{sub 4}, GeH{sub 4}, etc.)

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Predicted boron-carbide compounds: A first-principles study

By using developed particle swarm optimization algorithm on crystal structural prediction, we have explored the possible crystal structures of B-C system. Their structures, stability, elastic properties, electronic structure, and chemical bonding have been investigated by first-principles calculations with density functional theory. The results show that all the predicted structures are mechanically and dynamically stable. An analysis of calculated enthalpy with pressure indicates that increasing of boron content will increase the stability of boron carbides under low pressure. Moreover, the boron carbides with rich carbon content become more stable under high pressure. The negative formation energy of predicted B{sub 5}C indicates its high stability. The density of states of B{sub 5}C show that it is p-type semiconducting. The calculated theoretical Vickers hardnesses of B-C exceed 40 GPa except B{sub 4}C, BC, and BC{sub 4}, indicating they are potential superhard materials. An analysis of Debye temperature and electronic localization function provides further understanding chemical and physical properties of boron carbide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Universal tight binding model for chemical reactions in solution and at surfaces. I. Organic molecules

As is now well established, a first order expansion of the Hohenberg–Kohn total energy density functional about a trial input density, namely, the Harris–Foulkes functional, can be used to rationalize a non self consistent tight binding model. If the expansion is taken to second order then the energy and electron density matrix need to be calculated self consistently and from this functional one can derive a charge self consistent tight binding theory. In this paper we have used this to describe a polarizable ion tight binding model which has the benefit of treating charge transfer in point multipoles. This admits a ready description of ionic polarizability and crystal field splitting. It is necessary in constructing such a model to find a number of parameters that mimic their more exact counterparts in the density functional theory. We describe in detail how this is done using a combination of intuition, exact analytical fitting, and a genetic optimization algorithm. Having obtained model parameters we show that this constitutes a transferable scheme that can be applied rather universally to small and medium sized organic molecules. We have shown that the model gives a good account of static structural and dynamic vibrational properties of a library of molecules, and finally we demonstrate the model's capability by showing a real time simulation of an enolization reaction in aqueous solution. In two subsequent papers, we show that the model is a great deal more general in that it will describe solvents and solid substrates and that therefore we have created a self consistent quantum mechanical scheme that may be applied to simulations in heterogeneous catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

An ultra-efficient energy transfer beyond plasmonic light scattering

The energy transfer between nano-particles is of great importance for, solar cells, light-emitting diodes, nano-particle waveguides, and other photonic devices. This study shows through novel design and algorithm optimization, the energy transfer efficiency between plasmonic and dielectric nano-particles can be greatly improved. Using versatile designs including core-shell wrapping, supercells and dielectric mediated plasmonic scattering, 0.05 dB/μm attenuation can be achieved, which is 20-fold reduction over the baseline plasmonic nano-particle chain, and 8-fold reduction over the baseline dielectric nano-particle chain. In addition, it is also found that the dielectric nano-particle chains can actually be more efficient than the plasmonic ones, at their respective optimized geometry. The underlying physics is that although plasmonic nano-particles provide stronger coupling and field emission, the effect of plasmonic absorption loss is actually more dominant resulting in high attenuation. Finally, the group velocity for all design schemes proposed in this work is shown to be maintained above 0.4c, and it is found that the geometry optimization for transmission also boosts the group velocity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Stochastic inverse problems: Models and metrics

In past work, we introduced model-based inverse methods, and applied them to problems in which the anomaly could be reasonably modeled by simple canonical shapes, such as rectangular solids. In these cases the parameters to be inverted would be length, width and height, as well as the occasional probe lift-off or rotation. We are now developing a formulation that allows more flexibility in modeling complex flaws. The idea consists of expanding the flaw in a sequence of basis functions, and then solving for the expansion coefficients of this sequence, which are modeled as independent random variables, uniformly distributed over their range of values. There are a number of applications of such modeling: 1. Connected cracks and multiple half-moons, which we have noted in a POD set. Ideally we would like to distinguish connected cracks from one long shallow crack. 2. Cracks of irregular profile and shape which have appeared in cold work holes during bolt-hole eddy-current inspection. One side of such cracks is much deeper than other. 3. L or C shaped crack profiles at the surface, examples of which have been seen in bolt-hole cracks. By formulating problems in a stochastic sense, we are able to leverage the stochastic global optimization algorithms in NLSE, which is resident in VIC-3D®, to answer questions of global minimization and to compute confidence bounds using the sensitivity coefficient that we get from NLSE. We will also address the issue of surrogate functions which are used during the inversion process, and how they contribute to the quality of the estimation of the bounds.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Analysis of the scintillation mechanism in a pressurized {sup 4}He fast neutron detector using pulse shape fitting

An empirical investigation of the scintillation mechanism in a pressurized {sup 4}He gas fast neutron detector was conducted using pulse shape fitting. Scintillation signals from neutron interactions were measured and averaged to produce a single generic neutron pulse shape from both a {sup 252}Cf spontaneous fission source and a (d,d) neutron generator. An expression for light output over time was then developed by treating the decay of helium excited states in the same manner as the decay of radioactive isotopes. This pulse shape expression was fitted to the measured neutron pulse shape using a least-squares optimization algorithm, allowing an empirical analysis of the mechanism of scintillation inside the {sup 4}He detector. A further understanding of this mechanism in the {sup 4}He detector will advance the use of this system as a neutron spectrometer. For {sup 252}Cf neutrons, the triplet and singlet time constants were found to be 970 ns and 686 ns, respectively. For neutrons from the (d,d) generator, the time constants were found to be 884 ns and 636 ns. Differences were noted in the magnitude of these parameters compared to previously published data, however the general relationships were noted to be the same and checked with expected trends from theory. Of the excited helium states produced from a {sup 252}Cf neutron interaction, 76% were found to be born as triplet states, similar to the result from the neutron generator of 71%. The two sources yielded similar pulse shapes despite having very different neutron energy spectra, validating the robustness of the fits across various neutron energies.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Reference Correlation for the Viscosity of Ethane

A new representation of the viscosity for the fluid phase of ethane includes a zero-density correlation and a contribution for the critical enhancement, initially both developed separately, but based on experimental data. The higher-density contributions are correlated as a function of the reduced density δ = ρ/ρ{sub c} and of the reciprocal reduced temperature τ = T{sub c}/T (ρ{sub c}—critical density and T{sub c}—critical temperature). The final formulation contains 14 coefficients obtained using a state-of-the-art linear optimization algorithm. The evaluation and choice of the selected primary data sets is reviewed, in particular with respect to the assessment used in earlier viscosity correlations. The new viscosity surface correlation makes use of the reference equation of state for the thermodynamic properties of ethane by Bücker and Wagner [J. Phys. Chem. Ref. Data 35, 205 (2006)] and is valid in the fluid region from the melting line to temperatures of 675 K and pressures of 100 MPa. The viscosity in the limit of zero density is described with an expanded uncertainty of 0.5% (coverage factor k = 2) for temperatures 290 < T/K < 625, increasing to 1.0% at temperatures down to 212 K. The uncertainty of the correlated values is 1.5% in the range 290 < T/K < 430 at pressures up to 30 MPa on the basis of recent measurements judged to be very reliable as well as 4.0% and 6.0% in further regions. The uncertainty in the near-critical region (1.001 < 1/τ < 1.010 and 0.8 < δ < 1.2) increases with decreasing temperature up to 3.0% considering the available reliable data. Tables of the viscosity calculated from the correlation are listed in an appendix for the single-phase region, for the vapor–liquid phase boundary, and for the near-critical region.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Highly accurate thickness measurement of multi-layered automotive paints using terahertz technology

In this contribution, we present a highly accurate approach for thickness measurements of multi-layered automotive paints using terahertz time domain spectroscopy in reflection geometry. The proposed method combines the benefits of a model-based material parameters extraction method to calibrate the paint coatings, a generalized Rouard's method to simulate the terahertz radiation behavior within arbitrary thin films, and the robustness of a powerful evolutionary optimization algorithm to increase the sensitivity of the minimum thickness measurement limit. Within the framework of this work, a self-calibration model is introduced, which takes into consideration the real industrial challenges such as the effect of wet-on-wet spray in the painting process.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Structural refinement of Pbnm-type perovskite films from analysis of half-order diffraction peaks

Engineering structural modifications of epitaxial perovskite thin films is an effective route to induce new functionalities or enhance existing properties due to the close relation of the electronic ground state to the local bonding environment. As such, there is a necessity to systematically refine and precisely quantify these structural displacements, particularly those of the oxygen octahedra, which is a challenge due to the weak scattering factor of oxygen and the small diffraction volume of thin films. In this paper, we present an optimized algorithm to refine the octahedral rotation angles using specific unit-cell-doubling half-order diffraction peaks for the a - a - c + Pbnm structure. The oxygen and A-site positions can be obtained by minimizing the squared-error between calculated and experimentally determined peak intensities using the (1/2 1/2 3/2) and (1/2 1/2 5/2) reflections to determine the rotation angle α about in-plane axes and the (1/2 5/2 1), (1/2 3/2 1), and (1/2 3/2 2) reflections to determine the rotation angle γ about the out-of-plane axis, whereas the convoluting A-site displacements associated with the octahedral rotation pattern can be determined using (1 1 1/2) and (1/2 1/2 1/2) reflections to independently determine A-site positions. The validity of the approach is confirmed by applying the refinement procedure to determine the A-site and oxygen displacements in a NdGaO 3 single crystal. Finally, the ability to refine both the oxygen and A-site displacements relative to the undistorted perovskite structure enables a deeper understanding of how structural modifications alter functionality properties in epitaxial films exhibiting this commonly occurring crystal structure.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Machine learning framework for quantum sampling of highly constrained, continuous optimization problems

In recent years, there is growing interest in using quantum computers for solving combinatorial optimization problems. In this work, we developed a generic, machine learning-based framework for mapping continuous-space inverse design problems into surrogate quadratic unconstrained binary optimization (QUBO) problems by employing a binary variational autoencoder and a factorization machine. The factorization machine is trained as a low-dimensional, binary surrogate model for the continuous design space and sampled using various QUBO samplers. Using the D-Wave Advantage hybrid sampler and simulated annealing, we demonstrate that by repeated resampling and retraining of the factorization machine, our framework finds designs that exhibit figures of merit exceeding those of its training set. We showcase the framework’s performance on two inverse design problems by optimizing (i) thermal emitter topologies for thermophotovoltaic applications and (ii) diffractive meta-gratings for highly efficient beam steering. This technique can be further scaled to leverage future developments in quantum optimization to solve advanced inverse design problems for science and engineering applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Bridging material models across scales: An integrated approach to equation of state and molecular dynamics modeling of copper

New uncertainty-aware equation of state (EOS) and electrical conductivity (EC) models for copper have been developed. The multiphase EOS/EC models are fit to experimental solid/liquid EC isobar measurements as well as density-functional theory molecular dynamics (DFT-MD) EC calculations in both expanded and compressed regimes (0.1–16 g/ cm 3 ⁠). The liquid and solid EOS phases were fit to available experimental data along with additional DFT-MD data over the same range as the EC. Leveraging the DFT-MD data, a corresponding machine-learned interatomic potential (MLIAP) for copper was trained using genetic-algorithm optimization. The copper MLIAP was constrained by EOS shock points at high compressions. The final EOS bounded MLIAP proves to be stable over a large density range (approximately 0.1–20 g/ cm 3 ) with good agreement to an isothermal compression curve, shock Hugoniot, and liquid speed of sound measurements at high pressures (100s of GPa).

Acoustic measurements and instrumentation↗
DOE OSTI2026

Role of electron correlation on the adenine dimer interaction for non-equilibrium geometries: a benchmark Quantum Monte Carlo study

The accurate description of non-covalent interactions is critical for understanding the structure, dynamics, and eventual function of biomolecules. The adenine dimer serves as a benchmark system for computational methods due to its role in nucleic acid structures and its rich conformational landscape. In this study, we employ benchmark diffusion quantum Monte Carlo (DMC) methods to investigate the relative energies and role of electron correlation on a set of adenine dimer conformations generated via a search of the potential energy landscape using the global optimizer algorithm. Relative DMC energies are compared against a wide range of density functional theory (DFT) approximation results. We find that although most of the DFT functionals perform well for low-energy structures, their accuracy varies significantly for higher-energy conformations, including stacked and T-shaped structures. A large fraction of the variation is due to the treatment of the van der Waals interaction. BLYP, B3LYP, and PBE0 significantly improve with added D4 dispersion, while the recent r2SCAN-D4 and ωB97M-V functionals show the least scatter and closest agreement with the DMC. These findings highlight the delicate nature of these interactions in biomolecular systems and provide guidance for simulations of their structure and dynamics and for the development of machine learned interatomic potentials.

Washburn, Laurel [ORNL] (ORCID:0000000324179335)↗
DOE OSTI2023

Nonequilibrium design strategies for functional colloidal assemblies

Here, we use a nonequilibrium variational principle to optimize the steady-state, shear-induced interconversion of self-assembled nanoclusters of DNA-coated colloids. Employing this principle within a stochastic optimization algorithm allows us to identify design strategies for functional materials. We find that far-from-equilibrium shear flow can significantly enhance the flux between specific colloidal states by decoupling trade-offs between stability and reactivity required by systems in equilibrium. For isolated nanoclusters, we find nonequilibrium strategies for amplifying transition rates by coupling a given reaction coordinate to the background shear flow. We also find that shear flow can be made to selectively break detailed balance and maximize probability currents by coupling orientational degrees of freedom to conformational transitions. For a microphase consisting of many nanoclusters, we study the flux of colloids hopping between clusters. We find that a shear flow can amplify the flux without a proportional compromise on the microphase structure. This approach provides a general means of uncovering design principles for nanoscale, autonomous, functional materials driven far from equilibrium.

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

Utilizing a Virtual Sodium-Cooled Fast Reactor Digital Twin to Aid in Diversion Pathway Analysis for International Safeguards Applications

We report digital twin technology has the potential to improve the effectiveness of international safeguards inspectors by providing a tool which can: first, perform an accurate diversion path analysis, identify their indicators, and required sensors to detect them; and second, monitor facilities in real-time using critical data streams that benefit from this safeguards-by-design approach. Safeguards inspectors are required to visit facilities and verify the nuclear material to ensure no diversion has taken place and detect misuse of the facility; however, this analysis and verification effort is time consuming, and with limited funding it is imperative that time spent at a nuclear facility is focused on key areas. A virtual digital twin of three prototypic sodium fast reactors was developed, where diversion and misuse scenarios were explored to determine how a digital twin could provide inspectors with an understanding of how proliferation may occur and where the most likely areas for proliferation would be. For each of the three reactors, an optimization algorithm was able to find core designs which would be difficult to detect via sensors alone; however, the use of a machine learning adapter provided by the digital twin was able to show general trends in where proliferation as likely to take place.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

AN ELECTRON-TRACKING COMPTON TELESCOPE FOR A SURVEY OF THE DEEP UNIVERSE BY MeV GAMMA-RAYS

Photon imaging for MeV gammas has serious difficulties due to huge backgrounds and unclearness in images, which originate from incompleteness in determining the physical parameters of Compton scattering in detection, e.g., lack of the directional information of the recoil electrons. The recent major mission/instrument in the MeV band, Compton Gamma Ray Observatory/COMPTEL, which was Compton Camera (CC), detected a mere ∼30 persistent sources. It is in stark contrast with the ∼2000 sources in the GeV band. Here we report the performance of an Electron-Tracking Compton Camera (ETCC), and prove that it has a good potential to break through this stagnation in MeV gamma-ray astronomy. The ETCC provides all the parameters of Compton-scattering by measuring 3D recoil electron tracks; then the Scatter Plane Deviation (SPD) lost in CCs is recovered. The energy loss rate (dE/dx), which CCs cannot measure, is also obtained, and is found to be helpful to reduce the background under conditions similar to those in space. Accordingly, the significance in gamma detection is improved severalfold. On the other hand, SPD is essential to determine the point-spread function (PSF) quantitatively. The SPD resolution is improved close to the theoretical limit for multiple scattering of recoil electrons. With such a well-determined PSF, we demonstrate for the first time that it is possible to provide reliable sensitivity in Compton imaging without utilizing an optimization algorithm. As such, this study highlights the fundamental weak-points of CCs. In contrast we demonstrate the possibility of ETCC reaching the sensitivity below 1 × 10{sup −12} erg cm{sup −2} s{sup −1} at 1 MeV.

79 ASTRONOMY AND ASTROPHYSICS↗