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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 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Good Practices in Free-energy Calculations

As access to computational resources continues to increase, free-energy calculations have emerged as a powerful tool that can play a predictive role in drug design. Yet, in a number of instances, the reliability of these calculations can be improved significantly if a number of precepts, or good practices are followed. For the most part, the theory upon which these good practices rely has been known for many years, but often overlooked, or simply ignored. In other cases, the theoretical developments are too recent for their potential to be fully grasped and merged into popular platforms for the computation of free-energy differences. The current best practices for carrying out free-energy calculations will be reviewed demonstrating that, at little to no additional cost, free-energy estimates could be markedly improved and bounded by meaningful error estimates. In energy perturbation and nonequilibrium work methods, monitoring the probability distributions that underlie the transformation between the states of interest, performing the calculation bidirectionally, stratifying the reaction pathway and choosing the most appropriate paradigms and algorithms for transforming between states offer significant gains in both accuracy and precision. In thermodynamic integration and probability distribution (histogramming) methods, properly designed adaptive techniques yield nearly uniform sampling of the relevant degrees of freedom and, by doing so, could markedly improve efficiency and accuracy of free energy calculations without incurring any additional computational expense.

Pohorille, Andrew↗
NASA NTRS2022

Connecting Energy Input With Ionospheric Upflow and Outflow

The connection between energy inputs and the generation of ion upflows and outflows is a topic of keen scientific interest and the subject of a number of empirical studies. Despite this interest, it remains uncertain how different ion species respond to energy input, what defines the upper and lower bounds of the ion flux, and what role solar illumination plays in regulating the relationship between energy input and ion upflows/outflows. This work simulates how ion flux scales with low and high altitude energization, and to a combination of both. Furthermore, we examine the influence of solar illumination on these relationships by considering how the scaling of ion flux with energy input changes over the solar cycle, comparing solar minimum and maximum, as well as how they change from day to night conditions. We find O -+ flux tends to respond more strongly to energy inputs than H -+ flux, with the O -+ flux often exhibiting a lower activation energy and a greater dynamic range. The lower bound of the ion flux at 4,000 km is typically defined by the polar wind H -+ , although O -+ upflows can dominate at low altitudes in the presence of significant frictional heating of the ion gas or soft electron precipitation. However, when significant soft electron precipitation and wave-particle interactions are present simultaneously the lower bound of the ion flux at 4,000 km is defined by the O -+ . Finally, we find a difference between the steady state response of the outflow to energy input and the peak response.

A. Glocer↗
DOE OSTI2025

Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks

Physics-informed deep learning has emerged as a promising alternative for solving partial differential equations. However, for complex problems, training these networks can still be challenging, often resulting in unsatisfactory accuracy and efficiency. In this work, we demonstrate that the failure of plain physics-informed neural networks arises from the significant discrepancy in the convergence rate of residuals at different training points, where the slowest convergence rate dominates the overall solution convergence. Based on these observations, we propose a pointwise adaptive weighting method that balances the residual decay rate across different training points. The performance of our proposed adaptive weighting method is compared with current state-of-the-art adaptive weighting methods on benchmark problems for both physics-informed neural networks and physics-informed deep operator networks. In conclusion, through extensive numerical results we demonstrate that our proposed approach of balanced residual decay rates offers several advantages, including bounded weights, high prediction accuracy, fast convergence rate, low training uncertainty, low computational cost, and ease of hyperparameter tuning.

Balanced convergence rate↗
DOE OSTI2025

Orthogonality broadcasting and quantum position verification

The no-cloning theorem leads to information-theoretic security in various quantum cryptographic protocols. However, this security typically derives from a possibly weaker property that classical information encoded in certain quantum states cannot be broadcast. To formally capture this property, we introduce the study of ‘orthogonality broadcasting.’ When attempting to broadcast the orthogonality of two different qubit bases, we establish that the power of classical and quantum communication is equivalent. However, quantum communication is shown to be strictly more powerful for broadcasting orthogonality in higher dimensions. We then relate orthogonality broadcasting to quantum position verification and provide a new method for establishing error bounds in the no pre-shared entanglement model that can address protocols previous methods could not. Our key technical contribution is an uncertainty relation that uses the geometric relation of the states that undergo broadcasting rather than the non-commutative aspect of the final measurements.

quantum cryptography↗
DOE OSTI2024

Modulating spin-valley relaxation in WSe 2 with variable thickness VOPc layers

Combining the synthetic tunability of molecular compounds with the optical selection rules of transition metal dichalcogenides (TMDCs) that derive from spin-valley coupling could provide interesting opportunities for the readout of quantum information. However, little is known about the electronic and spin interactions at such interfaces and the influence on spin-valley relaxation. Here, in this work, vanadyl phthalocyanine (VOPc) molecular layers are thermally evaporated on WSe 2 to explore the effect of molecular layer thickness on excited-state spin-valley polarization. The thinnest molecular layer supports an interfacial state which destroys the spin-valley polarization almost instantaneously, whereas a thicker molecular layer results in longer-lived spin-valley polarization than the WSe 2 monolayer alone. The mechanism appears to involve a tightly bound species at the molecule/TMDC interface that strengthens exchange interactions and is largely avoided in thicker VOPc layers that isolate electrons from WSe 2 holes.

2D materials↗
DOE OSTI2023

GPS Spoofing Mitigation and Timing Risk Analysis in Networked Phasor Measurement Units via Stochastic Reachability

To address phasor measurement unit (PMU) vulnerability to spoofing, we propose the use of a set-valued state estimation technique known as stochastic reachability (SR)-based distributed Kalman filter (DKF) that computes secure global positioning system (GPS) timing across a network of receivers. Utilizing SR, we estimate not only GPS time but also its stochastic reachable set, which is parameterized by probabilistic zonotope (p-Zonotope). While requiring known measurement error bounds in only non-spoofed conditions, we designed a two-tiered approach. We first performed measurement-level spoofing mitigation via deviation of a measurement innovation from its expected p-Zonotope. We then performed state-level timing risk analysis via a determination of the intersection probability of the estimated p-Zonotope with an unsafe set that violates IEEE C37.118.1a-2014 standards. Finally, we validated our SR-DKF algorithm by subjecting it to a simulated receiver network to coordinate signal-level spoofing. We demonstrate improved timing accuracy and successful spoofing mitigation via the use of our SR-DKF algorithm. We also validated the robustness of the estimated timing risk as the number of receivers were varied.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Light-induced dimension crossover dictated by excitonic correlations

In low-dimensional systems with strong electronic correlations, the application of an ultrashort laser pulse often yields novel phases that are otherwise inaccessible. The central challenge in understanding such phenomena is to determine how dimensionality and many-body correlations together govern the pathway of a non-adiabatic transition. To this end, we examine a layered compound, 1T-TiSe 2 , whose three-dimensional charge-density-wave (3D CDW) state also features exciton condensation due to strong electron-hole interactions. We find that photoexcitation suppresses the equilibrium 3D CDW while creating a nonequilibrium 2D CDW. Remarkably, the dimension reduction does not occur unless bound electron-hole pairs are broken. This relation suggests that excitonic correlations maintain the out-of-plane CDW coherence, settling a long-standing debate over their role in the CDW transition. Our findings demonstrate how optical manipulation of electronic interaction enables one to control the dimensionality of a broken-symmetry order, paving the way for realizing other emergent states in strongly correlated systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1991

An error bound for instantaneous coverage

An error bound is derived for a reliability model approximation method. The approximation method is appropriate for the semi-Markov models of reconfigurable systems that are designed to achieve extremely high reliability. The semi-Markov models of these system are complex, and a significant amount of their complexity arises from the detailed descriptions of the reconfiguration processes. The reliability model approximation method consists of replacing a detailed description of a reconfiguration process with the probabilities of the possible outcomes of the reconfiguration process. These probabilities are included in the model as instantaneous jumps from the fault-occurrence state. Since little time is spent in the reconfiguration states, instantaneous jumps are a close approximation to the original model. This approximation procedure is shown to produce an overestimation for the probability of system failure, and an error bound is derived for this overestimation.

White, Allan L.↗
DOE OSTI2020

Ultrafast Relaxations in Ruthenium Polypyridyl Chromophores Determined by Stochastic Kinetics Simulations

Maximizing the efficiency of solar energy conversion using dye assemblies rests on understanding where the energy goes following absorption. Transient spectroscopies in solution are useful for this purpose, and the time-resolved data are usually analyzed with a sum of exponentials. This treatment assumes that dynamic events are well separated in time, and that the resulting exponential prefactors and phenomenological lifetimes are related directly to primary physical values. Such assumptions break down for coincident absorption, emission, and excited state relaxation that occur in transient absorption and photoluminescence of tris(2,2'-bipyridine)ruthenium(2+) derivatives, confounding the physical meaning of the reported lifetimes. Here, we use inductive modeling and stochastic chemical kinetics to develop a detailed description of the primary ultrafast photophysics in transient spectroscopies of a series of Ru dyes, as an alternative to sums of exponential analysis. Commonly invoked three-level schemes involving absorption, intersystem crossing (ISC), and slow nonradiative relaxation and incoherent emission to the ground state cannot reproduce the experimentally measured spectra. The kinetics simulations reveal that ultrafast decay from the singlet excited state manifold to the ground state competes with ISC to the triplet excited state, whose efficiency was determined to be less than unity. The populations predicted by the simulations are used to estimate the magnitudes of transition dipoles for excited state excitations and evaluate the influence of specific ligands. The mechanistic framework and methodology presented here are entirely general, applicable to other dye classes, and can be extended to include charge injection by molecules bound to semiconductor surfaces.

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

Comparing temperature convergence of shocked thin films of tin and iron to a bulk temperature source

An outstanding challenge in developing a complete equation of state for materials at elevated pressure and temperature is a robust method of determining the bulk temperature state under dynamic conditions. In metals, the determination of bulk temperature states by optical pyrometry is complicated by the small optical depth and thermal conduction effects. These effects lead to observed temperatures differing by 20% or more from the bulk temperature state. In this work, we show the presence of thermal conduction effects in temperature measurements of tin and iron coatings during dynamic compression experiments. We demonstrate that tin, in contrast to iron, coatings can fail to converge to a bulk temperature source over the time scale of the experiment, requiring the experimenter to modify assumptions, design, or analysis. This work bounds thermal transport at shocked conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Rapid Quantum Ground State Preparation via Dissipative Dynamics

Inspired by natural cooling processes, dissipation has become a promising approach for preparing low-energy states of quantum systems. However, the potential of dissipative protocols remains unclear beyond certain commuting Hamiltonians. This work provides significant analytical and numerical insights into the power of dissipation for preparing the ground state of noncommuting Hamiltonians. For quasi-free dissipative dynamics, including certain 1D spin systems with boundary dissipation, our results reveal a new connection between the mixing time in trace distance and the spectral properties of a non-Hermitian Hamiltonian, leading to an explicit and sharp bound on the mixing time that scales polynomially with system size. For more general spin systems, we develop a tensor network-based algorithm for constructing the Lindblad jump operator and for simulating the dynamics. Using this algorithm, we demonstrate numerically that dissipative ground state preparation protocols can achieve rapid mixing for certain 1D local Hamiltonians under bulk dissipation, with a mixing time that scales logarithmically with the system size. We then prove the rapid mixing result for certain weakly interacting spin and fermionic systems in arbitrary dimensions, extending recent results for high-temperature quantum Gibbs samplers to the zero-temperature regime. Together, these results show that dissipation can be a powerful tool for ground state preparation, with potential applications across condensed matter physics, quantum materials science, and beyond.

decoherence↗
DOE OSTI2025

Allosteric prediction via convolutional neural networks and protein structural and dynamical features

Allostery is the phenomenon whereby a binding event or covalent modification at one site in a protein modulates function at a distal site, thus changing a protein’s functional state. As such, it is a ubiquitous aspect of protein functional regulation. Computationally predicting allosteric states is important as part of the broader challenge of functional annotation, but it also has practical implications for drug development, as targeting an allosteric site often affords greater specificity compared with targeting an orthosteric site. This study introduces a machine learning approach to predict the allosteric functional state using the small G-protein KRas as the model system, due to its implication in many types of cancer and being well studied as a result with many x-ray crystallographic structures of KRas available with different mutations and ligands bound. Using structural and dynamical features that can be cast as images, namely interatomic distances, contact maps, covariance, and mutual information, supervised learning was performed using convolutional neural networks. Two pretrained convolutional neural network architectures, GoogLeNet and ResNet18, were fine-tuned to classify KRas into active or inactive states based on these features. Across training regimes, atomic contact maps emerged as the most effective structural feature, whereas linearized mutual information outperformed covariance in capturing dynamical correlations relevant to allostery. Models achieved significant validation accuracy, with atomic contact maps yielding up to 90% accuracy. In conclusion, the findings suggest that integrating global structural rearrangements and correlated motion patterns with deep learning can reliably predict protein allosteric states, offering a promising framework for understanding allosteric regulation and developing targeted therapeutics.

Rajeshwar T., Rajitha [Oak Ridge National Laborato↗
DOE OSTI2025

Multistage economic MPC for systems with a cyclic steady state: A gas network case study

Multistage model predictive control (MPC) provides a robust control strategy for dynamic systems with uncertainties and a setpoint tracking objective. Moreover, extending MPC to minimize an economic cost instead of tracking a pre-calculated optimal setpoint improves controller performance. This paper presents a novel multistage economic nonlinear model predictive control (E-NMPC) framework for dynamic systems operating under uncertainty, with specific application to natural gas transmission networks. A key innovation lies in the integration of cyclic steady-state (CSS) constraints within the multistage MPC formulation, enabling the controller to manage periodic operating conditions commonly observed in energy systems. A Lyapunov-based descent condition is enforced to ensure robust stability of the controller. The multistage economic MPC framework is validated on two gas pipeline case studies, where it successfully minimizes net energy consumption, respects operational constraints under uncertain demand profiles, and guides the network to optimal cyclic operation. The Lyapunov function remains bounded in both case studies, validating the robust stability of multistage E-NMPC.

03 NATURAL GAS↗
DOE OSTI2023

Evaluation of BISON metallic fuel performance modeling against experimental measurements within FIPD and IMIS databases

Simulations were conducted using the BISON fuel performance code on an automated process to read initial and operating conditions from two databases—the Fuels Irradiation and Physics Database (FIPD) and Integral Fast Reactor Materials Information System (IMIS) database. These databases contain metallic fuel data from the Experimental Breeder Reactor-II (EBR-II) and the Fast Flux Test Facility (FFTF). The work demonstrates use of an integrated framework to access EBR-II fuel pin data for evaluating fuel performance models contained within BISON to predict fuel performance of next-generation metallic fuel systems. Between IMIS and FIPD, there is enough information to conduct 1,977 unique EBR-II metallic fuel pin histories from 29 different experiments, and 338 pins from FFTF MFF-3 and MFF-5 with varying levels of details between the two databases. Each of these fuel performance histories includes a high-resolution power history, flux history, coolant channel flow rates, and coolant channel temperatures, and new model developments in BISON since the initial demonstration of this integrated framework. Fission gas release (FGR), cumulative damage fraction, fuel axial swelling, FCCI wastage thickness, cladding profilometry, and burnup were all simulated in BISON and compared to post-irradiation examination (PIE) results to evaluate BISON fuel performance modeling. Implementation of new fuel performance models into a generic BISON input file coupled with IMIS and FIPD yielded results with a better representation of physics than the initial evaluation of the integrated framework. Cladding profilometry, FGR, and fuel axial swelling were found to be in good agreement with PIE measurements for most of the pins simulated. The chosen mechanical contact solver was found to significantly impact the axial fuel swelling and cladding strain predictions when used in conjunction with the U-Pu-Zr hot-pressing model since it bound the fuel to prevent further swelling and increased hydrostatic stresses. This work suggests that fuel performance modeling in BISON under steady-state conditions represents the PIE data well and should be reassessed when new PIE data become available in IMIS and FIPD databases and when improved physical models to better capture fuel performance are added to BISON.

Paaren, Kyle M.↗
DOE OSTI2023

Efficient SABRE-SHEATH Hyperpolarization of Potent Branched-Chain-Amino-Acid Metabolic Probe [1-13C]ketoisocaproate

Efficient 13C hyperpolarization of ketoisocaproate is demonstrated in natural isotopic abundance and [1-13C]enriched forms via SABRE-SHEATH (Signal Amplification By Reversible Exchange in SHield Enables Alignment Transfer to Heteronuclei). Parahydrogen, as the source of nuclear spin order, and ketoisocaproate undergo simultaneous chemical exchange with an Ir-IMes-based hexacoordinate complex in CD3OD. SABRE-SHEATH enables spontaneous polarization transfer from parahydrogen-derived hydrides to the 13C nucleus of transiently bound ketoisocaproate. 13C polarization values of up to 18% are achieved at the 1-13C site in 1 min in the liquid state at 30 mM substrate concentration. The efficient polarization build-up becomes possible due to favorable relaxation dynamics. Specifically, the exponential build-up time constant (14.3 ± 0.6 s) is substantially lower than the corresponding polarization decay time constant (22.8 ± 1.2 s) at the optimum polarization transfer field (0.4 microtesla) and temperature (10 °C). The experiments with natural abundance ketoisocaproate revealed polarization level on the 13C-2 site of less than 1%—i.e., one order of magnitude lower than that of the 1-13C site—which is only partially due to more-efficient relaxation dynamics in sub-microtesla fields. We rationalize the overall much lower 13C-2 polarization efficiency in part by less favorable catalyst-binding dynamics of the C-2 site. Pilot SABRE experiments at pH 4.0 (acidified sample) versus pH 6.1 (unaltered sodium [1-13C]ketoisocaproate) reveal substantial modulation of SABRE-SHEATH processes by pH, warranting future systematic pH titration studies of ketoisocaproate, as well as other structurally similar ketocarboxylate motifs including pyruvate and alpha-ketoglutarate, with the overarching goal of maximizing 13C polarization levels in these potent molecular probes. Finally, we also report on the pilot post-mortem use of HP [1-13C]ketoisocaproate in a euthanized mouse, demonstrating that SABRE-hyperpolarized 13C contrast agents hold promise for future metabolic studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Computation of instability and transition

The state of transition calculations in 1989 and desirable future trends are analyzed within the framework of aeronautical applications with emphasis on wall-bounded flows. A shift to studies of the early stages of transition, particularly to receptivity, from studies of the late stages in excessively confined periodic domains is proposed. It is pointed out that early-stage studies require a larger computational domain and more difficult boundary conditions but not a very fine grid. Intermediate strategies, more involved than the classical Orr-Sommerfeld equation but much more economical than full Navier-Stokes equations, are emphasized, along with the need for compressible calculations.

Spalart, P. R.↗
NASA NTRS1992

L-shell X-ray opacity of many-electron atoms

The study presents a formulation for obtaining the L-shell photoelectric cross section (sigma sub L) for many-electron atomic systems. A scaling law is suggested for the evaluation of the contribution to sigma sub L from 2s and 2p ejection from a general system in any ionization state. The formula is expressed in terms of the effective nuclear charge (Z sub 2s and Z sub 2p) seen by the corresponding bound electrons, with Z sub 2s and Z sub 2p, obtained from improved screening constants derived in a recent investigation. A comparison is made of Hartree-Fock and hydrogenic expressions for sigma sub L with experimental results for atomic neon at X-ray photon energies, providing the basis for the scaling law and an approximate energy dependence for the cross sections. The special case of sigma sub L for atomic Fe is considered in detail. This L edge has structure because of the different threshold for 2s and 2p photoejection; the latter has fine structure.

Jung, Young-Dae↗
NASA NTRS2019

Pulsed Plasma Acceleration Modeling in Detonation and Deflagration Modes

Gas-fed electromagnetic pulsed plasma accelerators discharge electrical energy into a gas to ionize and electromagnetically accelerate propellant in the domain. Efforts to model pulsed accelerators have either assumed that the discharge is short and completely transient, accelerating the gas by entraining it in a moving current sheet, or that the discharge is relatively long, establishing a stable quasi-steady current distribution pattern that accelerates a plasma flowing through it. There have been pulsed plasma accelerator tests that appear to fit somewhere between these two bounds, exhibiting some properties that are associated with the purely transient devices while also showing others that are associated with quasi-steady-state plasma acceleration. A model is presented based upon the premise that all pulsed plasma accelerators first form an accelerating current sheet (detonation mode accelerator). Depending upon the pulse length and the gas conditions in the dis- charge channel, the plasma sheet may reach the end of the accelerator before the discharge has completed a full half-cycle, wherein the proposed model transitions to a quasi-steady description of the acceleration process (deflagration mode accelerator). A review of the entire model is presented, highlighting improvements and upgrades implemented to aid in the stability of the numerical scheme used to model the gas flow in the channel and an improved treatment of current sheet mass shedding, which adds gas to the wake of the sheet. The assumptions employed to model the transition from detonation to deflagration mode are presented and used to generate solutions to the governing equations. The modeling of the deflagration-mode under the present assumptions results in very low deflagration impulse bits relative to those obtained at the end of the detonation mode, implying that the present assumptions and modeling of the deflagration mode may not represent a fruitful approach.

Polzin, Kurt A.↗