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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 OSTI2026

High-Fidelity, Low-Dissipation/Symmetry-Preserving Numerical Scheme for Solving the Euler Equations with Unstructured, Metric-Based Mesh Adaptation

This work presents an overview of a high-fidelity compressible Euler solver that utilizes the continuous Galerkin (CG) method with added artificial numerical diffusion for stabilization to solve a variety of unsteady and steady benchmark inviscid flow problems. This work shows that discretizing the Euler equations with this CG approach and first order basis functions produces a cost-effective stencil as well as simple well-posed boundary conditions. We show through convergence testing with manufactured solutions that the reduced stencil of CG, combined with the low amount of artificial diffusion required when using the stabilization method outlined in this work, leads to stable and highly accurate results for a variety of unsteady and steady applications. When combined with the adaptive mesh refinement approach used for many of the cases in this work, our results show that the flow solver achieves even more accurate results. A variety of inviscid flow cases are presented in this work, including transient 2D cases with complex shock structures and several steady 3D airfoils sections with a constant span.

Doetsch, Kevin [ORNL] (ORCID:0000000267051705)↗
DOE OSTI2025

Impact of solvation on the electronic resonances in uracil

Interactions of low-energy electrons with the DNA and RNA nucleobases are known to form metastable states, known as electronic resonances. In this work, we study electron attachment to solvated uracil, an RNA nucleobase, using the orbital stabilization method at the Equation of Motion-Coupled Cluster for Electron Affinities with Singles and Doubles (EOM-EA-CCSD) level of theory with the Effective Fragment Potential (EFP) solvation method. We benchmarked the approach using multireference methods, as well as by comparing EFP and full quantum calculations. The impact of solvation on the first one particle (1p) shape resonance, formed by electron attachment to the π* LUMO orbital, as well as the first two particle one hole (2p1h) resonance, formed by electron attachment to neutral uracil's π–π* excited state, was investigated. We used molecular dynamics simulations for solvent configurations and applied charge stabilization technique-based biased sampling to procure configurations adequate to cover the entire range of the electron attachment energy distribution. The electron attachment energy in solution is found to be distributed over a wide range of energies, between 4.6 eV to 6.8 eV for the 2p1h resonance, and between −0.1 eV to 2 eV for the 1p resonance. The solvent effects were similar for the two resonances, indicating that the exact electron density of the state is not as important as the solvent configurations. Multireference calculations extended the findings showing that solvation effects are similar for the lowest four resonances, further indicating that the specific solute electron density is not as important, but rather the water configurations play the most important role in solvation effects. Lastly, by comparing bulk solvation to clusters of uracil with a few water molecules around it, we find that the impact of microsolvation is very different from that of bulk solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Stability and accuracy of 3D neutron transport simulations using the 2D/1D method in MPACT

A consistent “2D/1D” neutron transport method is derived from the 3D Boltzmann transport equation, to calculate fuel-pin-resolved neutron fluxes for realistic full-core Pressurized Water Reactor (PWR) problems. The 2D/1D method employs the Method of Characteristics to discretize the radial variables and a lower order transport solution to discretize the axial variable. This paper describes the theory of the 2D/1D method and its implementation in the MPACT code, which has become the whole-core deterministic neutron transport solver for the Consortium for Advanced Simulations of Light Water Reactors (CASL) core simulator VERA-CS. Several applications have been performed on both leadership-class and industry-class computing clusters. Results are presented for whole-core solutions of the Watts Bar Nuclear Power Station Unit 1 and compared to both continuous-energy Monte Carlo results and plant data.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

A Riccati Solution for the Ideal MHD Plasma Response with Applications to Real-time Stability Control

To effectuate near real-time feedback control of ideal MHD instabilities in a tokamak geometry, a rapid solution for stability analysis is a prerequisite. Toward this end, we reformulate the δW stability method with a Hamilton-Jacobi theory, elucidating analytical and numerical features of the generic tokamak ideal MHD stability problem. The plasma response matrix is demonstrated to be the solution of an ideal MHD matrix Riccati differential equation (MRDE). Since Riccati equations are prevalent in the control theory literature, such a shift in perspective brings to bear a range of numerical methods that are well-suited to the robust, fast solution of control problems. We discuss the usefulness of Riccati techniques in solving the stiff ODEs often encountered in ideal MHD stability analyses-—for example, in tokamak edge and stellarator physics. We then demonstrate the applicability of such methods to an existing 2D ideal MHD stability code—DCON—enabling its parallel operation in near real-time. Output is shown to match with high accuracy, and with wall-clock time ≪ 1s. Such speed may help enable active feedback ideal MHD stability control, especially in tokamak plasmas whose ideal MHD equilibria evolve with inductive timescale τ > 1s-—as in ITER.

Parallel↗
DOE OSTI2018

Efficient second derivative methods with extended stability regions for non-stiff IVPs

We describe the construction of explicit Nordsieck sequential second derivative general linear methods with a large region of absolute stability. The constructed methods are of order p=q=s, where q and s are the stage order and the number of internal stages, respectively. To compare, we also construct methods in this class which possess Runge–Kutta stability property. Implementation of the constructed methods in a variable stepsize mode is discussed and efficiency of these methods is verified by some numerical experiments in fixed and variable stepsize environment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Shape regulation of high-index facet nanoparticles by dealloying

Tetrahexahedral particles (~10 to ~500 nanometers) composed of platinum (Pt), palladium, rhodium, nickel, and cobalt, as well as a library of bimetallic compositions, were synthesized on silicon wafers and on catalytic supports by a ligand-free, solid-state reaction that used trace elements [antimony (Sb), bismuth (Bi), lead, or tellurium] to stabilize high-index facets. Both simulation and experiment confirmed that this method stabilized the {210} planes. A study of the PtSb system showed that the tetrahexahedron shape resulted from the evaporative removal of Sb from the initial alloy—a shape-regulating process fundamentally different from solution-phase, ligand-dependent processes. The current density at a fixed potential for the electro-oxidation of formic acid with a commercial Pt/carbon catalyst increased by a factor of 20 after transformation with Bi into tetrahexahedral particles.

Huang, Liliang (ORCID:0000000234740846)↗
DOE OSTI2016

Bio-Oil Separation and Stabilization by Near-Critical Propane Fractionation

Bio-oils produced by thermal process are promising sources of sustainable, low greenhouse gas alternative fuels. These thermal processes are also well suited to decentralized energy production due to low capital and operating costs. Algae feedstocks for bio-oil production are of particular interest, due in part to their high-energy growth yields. Further, algae can be grown in non-arable areas in fresh, brackish, salt water, or even waste water. Unfortunately, bio-oils produced by thermal processes present significant stability challenges. These oils have complex chemical compositions, are viscous, reactive, and thermally unstable. Further, the components within the oils are difficult to separate by fractional distillation. By far, the most effective separation and stabilization method has been solvent extraction. However, liquid phase extraction processes pose two main obstacles to commercialization; they require a significant amount of energy to remove and recover the solvent from the product, and they have a propensity for the solvent to become contaminated with minerals from the char and ash present in the original bio-oil. Separation and fractionation of thermally produced bio-oils using supercritical fluids (SCF) offers the advantages of liquid solvent extraction while drastically reducing energy demands and the predisposition to carry over solids into the extracted phase. SCFs are dense fluids with liquid-like solvent properties and gas-like transport properties. Further, SCF density and solvent strength can be tuned with minor adjustments in pressure, co-solvent addition, or gas anti-solvent addition. Catalytic pyrolysis oils were produced from Scenedesmus dimorphus algae using a fluid catalytic cracking catalyst. Bio-oil produced from catalytic fast pyrolysis (CFP) was separated using critical fluids. Propane extraction was performed at 65 °C at a fluid reduced pressure of 2.0 (85 bar) using an eight to one solvent to feed ratio by weight. Extraction of catalytic fast pyrolysis oil with near critical propane produced an oil extract that was physically and chemically different from and more stable than the original oil. The propane extract displayed lower viscosity and lower average molecular weight. The species present in the propane extract were likely the less polar that would be expected from using a non-polar solvent (propane). Carbonyl containing species in the extract were likely ketones and esters. The raffinate contained a higher amnount of OH bonded species along with the more polar more polar acids, amides, and alcohols. The higher concentration of nitrogen in the raffinate may confirm the presence of amides. Viscosity of the propane extract increased only half as much as that of the CFP bio-oil. Further, In situ NMR aging studies showed that the propane extract was more stable than the raw oil. In conclusion, propane extraction is a promising method to decrease the nitrogen content of bio-oils and to improve the stability of bio-oils obtained by the catalytic pyrolysis of algae based biomass.

09 BIOMASS FUELS↗
DOE OSTI2016

Interaction of turbulent premixed flames with combustion products: Role of stoichiometry

Stabilization methods of turbulent flames often involve mixing of reactants with hot products of combustion. The stabilizing effect of combustion product enthalpy has been long recognized, but the role played by the chemical composition of the product gases is typically overlooked. We employ a counterflow system to pinpoint the effects of the combustion product stoichiometry on the structure of turbulent premixed flames under conditions of both stable burning and local extinction. To that end, a turbulent jet of lean-to-rich, CH 4 /O 2 /N 2 -premixed reactants at a turbulent Reynolds number of 1050 was opposed to a stream of hot products of combustion that were generated in a preburner. While the combustion product stream temperature was kept constant, its stoichiometry was varied independently from that of the reactant stream, leading to reactant-to-product stratification of relevance to practical combustion systems. The detailed structure of the turbulent flame front was analyzed in two series of experiments using laser-induced fluorescence (LIF): joint CH 2 O LIF and OH LIF measurements and joint CO LIF and OH LIF measurements. Results revealed that a decrease in local CH 2 O+OH and CO+OH reaction rates coincide with the depletion of OH radicals in the vicinity of the combustion product stream. These critical combustion reaction rates were more readily quenched in the presence of products of combustion from a stoichiometric flame, whereas they were favored by lean combustion products. As a result, stoichiometric combustion products contributed to a greater occurrence of local extinction. Furthermore, they limited the capacity of premixed reactants to ignite and of the turbulent premixed flames to stabilize. In contrast, lean and rich combustion products facilitated flame ignition and stability and reduced the rate of local extinction. The influence of the combustion product stream on the turbulent flame front was limited to a zone of approximately two millimeters from the gas mixing layer interface (GMLI) of the product stream. As a result, flame fronts that were separated from the GMLI by larger distances were unaffected by the product stream stoichiometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

A unified neural-network framework for nucleon imaging from numerical simulations of QCD

Parton distributions encode the momentum-space structure and, in their generalizations, the spatial tomography of quarks and gluons inside hadrons, the building blocks of visible matter. We present a unified neural-network approach that learns these distributions directly from matrix elements calculated via numerical simulations of quantum chromodynamics (QCD) on the lattice by fitting two complementary inputs simultaneously: data matched to physical quantities via known momentum-space and coordinate-space formalisms. Utilizing data from both methods stabilizes the extraction and mitigates biases that can arise when either is used alone. We validate the method on controlled mock data and apply it to lattice-QCD matrix elements to extract parton distribution functions (PDFs). We show benefits of such an approach for determining the physical quantities. We further extend the framework to zero-skewness generalized parton distributions and demonstrate nucleon tomography within the same neural-network parameterization. Our results provide an adaptable and systematically improvable approach for extracting partonic distributions from Euclidean correlators. It can incorporate polarization, additional channels, and future experimental constraints from current and future facilities, such as the Electron-Ion Collider.

Hadronic Spectroscopy↗
DOE OSTI2016

Active stabilization of a diode laser injection lock

We report on a device to electronically stabilize the optical injection lock of a semiconductor diode laser. Our technique uses as discriminator the peak height of the laser’s transmission signal on a scanning Fabry-Perot cavity and feeds back to the diode current, thereby maintaining maximum optical power in the injected mode. A two-component feedback algorithm provides constant optimization of the injection lock, keeping it robust to slow thermal drifts and allowing fast recovery from sudden failures such as temporary occlusion of the injection beam. We demonstrate the successful performance of our stabilization method in a diode laser setup at 399 nm used for laser cooling of Yb atoms. The device eases the requirements on passive stabilization and can benefit any diode laser injection lock application, particularly those where several such locks are employed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Long-term stabilization of intensity-difference squeezing from four-wave mixing in rubidium vapor

Generation of quantum states of light through off-resonance four-wave mixing in rubidium vapor is a straightforward and well-established technique. However, achieving a sufficiently high and consistent level of intensity difference squeezing (IDS) and intrinsic quantum correlations between photon pairs over an extended timescale, necessary for quantum-light-based nonlinear optical spectroscopy and microscopy, remains challenging and largely unexplored. Here, we report a simple stabilization method combining an active periodic laser frequency retuning with an automatic control algorithm based on quantitatively assessing the factors affecting the IDS level and squeezed light intensity. Validation of our method was performed by acquiring data over a 5-hour period, and the results demonstrate a remarkably stable squeezing level of -7.8 dB in combination with a > 4× reduction of the standard deviation of IDS level from 0.46 dB to 0.10 dB. The achieved stabilization further enables us to quantitatively assess the IDS reduction due to the scattering in a polystyrene bead suspension as a function of sample transmission. Our approach should enable a variety of applications requiring an extended squeezing stability over multiple hours, especially for those following biological processes and chemical reactions in real time.

Allen, Christian Harry [Oak Ridge National Laborat↗
DOE OSTI2023

Bioinspired stability enhancement in deuterium-substituted organic–inorganic hybrid perovskite solar cells

Abstract In hybrid perovskite solar cells (PSCs), the reaction of hydrogens (H) located in the amino group of the organic A-site cations with their neighboring halides plays a central role in degradation. Inspired by the retarded biological activities of cells in heavy water, we replaced the light H atom with its abundant, twice-as-heavy, nonradioactive isotope, deuterium (D) to hamper the motion of H. This D substitution retarded the formation kinetics of the detrimental H halides in Pb-based PSCs, as well as the H bond-mediated oxidation of Sn2+ in Sn–Pb-based narrow-bandgap PSCs, evidenced by accelerated stability studies. A computational study indicated that the zero point energy of D-based formamidinium (FA) is lower than that of pristine FA. In addition, the smaller increase in entropy in D-based FA than in pristine FA accounts for the increased formation free energy of the Sn2+ vacancies, which leads to the retarded oxidation kinetics of Sn2+. In this study, we show that substituting active H with D in organic cations is an effective way to enhance the stability of PSCs without sacrificing photovoltaic (PV) performance. This approach is also adaptable to other stabilizing methods.

14 SOLAR ENERGY↗
DOE OSTI2022

225 Ac-MACROPATATE: A Novel α-Particle Peptide Receptor Radionuclide Therapy for Neuroendocrine Tumors

Neuroendocrine tumors (NETs) express somatostatin receptors (SSTRs) 2 and 5. Modified variants of somatostatin, the cognate ligand for SSTR2 and SSTR5, are used in treatment for metastatic and locoregional disease. Peptide receptor radionuclide therapy with 177 Lu-DOTATATE (DOTA-octreotate), a β-particle–emitting somatostatin derivative, has demonstrated survival benefit in patients with SSTR-positive NETs. Despite excellent results, a subset of patients has tumors that are resistant to treatment, and alternative agents are needed. Targeted α-particle therapy has been shown to kill tumors that are resistant to targeted β-particle therapy, suggesting that targeted α-particle therapy may offer a promising treatment option for patients with 177 Lu-DOTATATE–resistant disease. Although DOTATATE can chelate the clinically relevant α-particle–emitting radionuclide 225 Ac, the labeling reaction requires high temperatures, and the resulting radioconjugate has suboptimal stability. Methods: We designed and synthesized MACROPATATE (MACROPA-octreotate), a novel radioconjugate capable of chelating 225 Ac at room temperature, and assessed its in vitro and in vivo performance. Results: MACROPATATE demonstrated comparable affinity to DOTATATE (dissociation constant, 21 nM) in U2-OS-SSTR2, a SSTR2-positive transfected cell line. 225 Ac-MACROPATATE demonstrated superior serum stability at 37°C over time compared with 225 Ac-DOTATATE. Biodistribution studies demonstrated higher tumor uptake of 225 Ac-MACROPATATE than of 225 Ac-DOTATATE in mice engrafted with subcutaneous H69 NETs. Therapy studies showed that 225 Ac-MACROPATATE exhibits significant antitumor and survival benefit compared with saline control in mice engrafted with SSTR-positive tumors. However, the increased accumulation of 225 Ac-MACROPATATE in liver and kidneys and subsequent toxicity to these organs decreased its therapeutic index compared with 225 Ac-DOTATATE. Conclusion: 225 Ac-MACROPATATE and 225 Ac-DOTATATE exhibit favorable therapeutic efficacy in animal models. Because of elevated liver and kidney accumulation and lower administered activity for dose-limiting toxicity of 225 Ac-MACROPATATE, 225 Ac-DOTATATE was deemed the superior agent for targeted α-particle peptide receptor radionuclide therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Construction of the Nordsieck second derivative methods with RK stability for stiff ODEs

In this paper, we study the construction and implementation of special Nordsieck second derivative general linear methods of order p and stage order q=p in which the number of input and output values is r=p rather than r=p+1. We will construct A- and L-stable methods of orders three and four in this form with Runge–Kutta stability properties. The efficiency of the constructed methods and reliability of the proposed error estimates are shown by implementing of the methods in a variable stepsize environment on some well-known stiff problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The Adjoint Petrov–Galerkin method for non-linear model reduction

Here, we formulate a new projection-based reduced-order modeling technique for non-linear dynamical systems. The proposed technique, which we refer to as the Adjoint Petrov–Galerkin (APG) method, is derived by decomposing the generalized coordinates of a dynamical system into a resolved coarse-scale set and an unresolved fine-scale set. A Markovian finite memory assumption within the Mori–Zwanzig formalism is then used to develop a reduced-order representation of the coarse scales. This procedure leads to a closed reduced-order model that displays commonalities with the adjoint stabilization method used in finite elements. The formulation is shown to be equivalent to a Petrov–Galerkin method with a non-linear, time-varying test basis, thus sharing some similarities with the Least-Squares Petrov–Galerkin method. Theoretical analysis examining a priori error bounds and computational cost is presented. Numerical experiments on the compressible Navier–Stokes equations demonstrate that the proposed method can lead to improvements in numerical accuracy, robustness, and computational efficiency over the Galerkin method on problems of practical interest. Improvements in numerical accuracy and computational efficiency over the Least-Squares Petrov–Galerkin method are observed in most cases.

42 ENGINEERING↗
DOE OSTI2022

Data-driven Minimum Entropy Control for Stochastic Nonlinear Systems using the Cumulant-Generating Function

Here, we present a novel minimum entropy control algorithm for a class of stochastic nonlinear systems subjected to non-Gaussian noises. The entropy control can be considered as an optimization problem for the system randomness attenuation, but the mean value has to be considered separately. To overcome this disadvantage, a new representation of the system stochastic properties was given using the cumulant-generating function based on the moment-generating function, in which the mean value and the entropy was reflected by the shape of the cumulant-generating function. Based on the samples of the system output and control input, a time-variant linear model was identified, and the minimum entropy optimization was transformed to system stabilization. Then, an optimal control strategy was developed to achieve the randomness attenuation, and the boundedness of the controlled system output was analyzed. The effectiveness of the presented control algorithm was demonstrated by a numerical example. In this paper, a data-driven minimum entropy design is presented without pre-knowledge of the system model; entropy optimization is achieved by the system stabilization approach in which the stochastic distribution control and minimum entropy are unified using the same identified structure; and a potential framework is obtained since all the existing system stabilization methods can be adopted to achieve the minimum entropy objective.

42 ENGINEERING↗
DOE OSTI2021

Assessment of the Amplification Factor Transport Transition Model for High-Mach Number Flows

In its present state, the Amplification Factor Transport (AFT) model provides an efficient alternative for high-fidelity stability methods for complex geometries subject to low-speed conditions considered in the industrial-production CFD environment. Its performance has not yet been documented for the typical transition scenarios in hypersonic conditions. The goal of the present study is to apply the AFT model to a yawed- and flared-cone configuration, for which the laminar flows respectively support the crossflow and second-mode instability mechanisms, and to compare the amplification results against high-fidelity results computed with Linear Parabolized Stability Equations (LPSE). High-resolution viscous-flow solutions are provided with OVERFLOW and COFFE. For the yawed-cone case, the AFT model yields the largest amplification in a region of the flow where the expected crossflow instability is not amplified (in the leeward symmetry plane) according to LPSE. For the flared-cone case with a wall-temperature slightly lower than the adiabatic value, the AFT model yields extremely large amplification factors (in excess of 100), exceeding the computed LPSE amplification of second-mode instability results by a factor 14. Upon considering a cold-wall condition, the model shows much smaller amplification factors, which is the opposite with respect to the expected behavior of the second mode. The AFT model does not adequately capture the crossflow and second-mode instability mechanisms in its present state.

Groot, Koen J.↗
DOE OSTI2024

Supramolecular assembly of polycation/mRNA nanoparticles and in vivo monocyte programming

Size-dependent phagocytosis is a well-characterized phenomenon in monocytes and macrophages. However, this size effect for preferential gene delivery to these important cell targets has not been fully exploited because commonly adopted stabilization methods for electrostatically complexed nucleic acid nanoparticles, such as PEGylation and charge repulsion, typically arrest the vehicle size below 200 nm. Here, we bridge the technical gap in scalable synthesis of larger submicron gene delivery vehicles by electrostatic self-assembly of charged nanoparticles, facilitated by a polymer structurally designed to modulate internanoparticle Coulombic and van der Waals forces. Specifically, our strategy permits controlled assembly of small poly(β-amino ester)/messenger ribonucleic acid (mRNA) nanoparticles into particles with a size that is kinetically tunable between 200 and 1,000 nm with high colloidal stability in physiological media. We found that assembled particles with an average size of 400 nm safely and most efficiently transfect monocytes following intravenous administration and mediate their differentiation into macrophages in the periphery. When a CpG adjuvant is co-loaded into the particles with an antigen mRNA, the monocytes differentiate into inflammatory dendritic cells and prime adaptive anticancer immunity in the tumor-draining lymph node. This platform technology offers a unique ligand-independent, particle-size-mediated strategy for preferential mRNA delivery and enables therapeutic paradigmsviamonocyte programming.

Science & Technology - Other Topics↗