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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Electron-ion coincidence measurements of molecular dynamics with intense X-ray pulses

Molecules can sequentially absorb multiple photons when irradiated by an intense X-ray pulse from a free-electron laser. If the time delay between two photoabsorption events can be determined, this enables pump-probe experiments with a single X-ray pulse, where the absorption of the first photon induces electronic and nuclear dynamics that are probed by the absorption of the second photon. Here we show a realization of such a single-pulse X-ray pump-probe scheme on N 2 molecules, using the X-ray induced dissociation process as an internal clock that is read out via coincident detection of photoelectrons and fragment ions. By coincidence analysis of the kinetic energies of the ionic fragments and photoelectrons, the transition from a bound molecular dication to two isolated atomic ions is observed through the energy shift of the inner-shell electrons. Via ab-initio simulations, we are able to map characteristic features in the kinetic energy release and photoelectron spectrum to specific delay times between photoabsorptions. In contrast to previous studies where nuclear motions were typically revealed by measuring ion kinetics, our work shows that inner-shell photoelectron energies can also be sensitive probes of nuclear dynamics, which adds one more dimension to the study of light-matter interactions with X-ray pulses.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Freely scalable and reconfigurable optical hardware for deep learning

Abstract As deep neural network (DNN) models grow ever-larger, they can achieve higher accuracy and solve more complex problems. This trend has been enabled by an increase in available compute power; however, efforts to continue to scale electronic processors are impeded by the costs of communication, thermal management, power delivery and clocking. To improve scalability, we propose a digital optical neural network (DONN) with intralayer optical interconnects and reconfigurable input values. The path-length-independence of optical energy consumption enables information locality between a transmitter and a large number of arbitrarily arranged receivers, which allows greater flexibility in architecture design to circumvent scaling limitations. In a proof-of-concept experiment, we demonstrate optical multicast in the classification of 500 MNIST images with a 3-layer, fully-connected network. We also analyze the energy consumption of the DONN and find that digital optical data transfer is beneficial over electronics when the spacing of computational units is on the order of $$>10\,\upmu $$ > 10 μ m.

42 ENGINEERING↗
DOE OSTI2021

Structural insights into photoactivation of plant Cryptochrome-2

Cryptochromes (CRYs) are evolutionarily conserved photoreceptors that mediate various light-induced responses in bacteria, plants, and animals. Plant cryptochromes govern a variety of critical growth and developmental processes including seed germination, flowering time and entrainment of the circadian clock. CRY’s photocycle involves reduction of their flavin adenine dinucleotide (FAD)-bound chromophore, which is completely oxidized in the dark and semi to fully reduced in the light signaling-active state. Despite the progress in characterizing cryptochromes, important aspects of their photochemistry, regulation, and light-induced structural changes remain to be addressed. In this study, we determine the crystal structure of the photosensory domain of Arabidopsis CRY2 in a tetrameric active state. Systematic structure-based analyses of photo-activated and inactive plant CRYs elucidate distinct structural elements and critical residues that dynamically partake in photo-induced oligomerization. Our study offers an updated model of CRYs photoactivation mechanism as well as the mode of its regulation by interacting proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Enhancement of chemical oscillations by self-generated convective flows

Chemical feedback loops in fluids can produce not only chemical oscillations, but also density variations that generate solutal buoyancy forces, which in turn initiate fluid flow. Using analytical and computational models, we herein examine how the reaction-induced flows alter the chemical oscillations in a fluid-filled chamber whose top and bottom walls are coated with different enzymes. Due to this chemo-fluidic coupling, the systems form oscillating flow patterns, which combine the characteristic size of the buoyancy-driven convection rolls with the frequency of the chemical oscillations. With changes in the distance between the enzyme-coated walls, the convective flows not only enhance or suppress the chemical oscillations, but also substantially increase the amplitude and frequency of the oscillations and extend the regime of the oscillatory behavior. These design principles can facilitate the development of artificial biochemical networks that act as chemical clocks.

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

Light-wave control of correlated materials using quantum magnetism during time-periodic modulation of coherent transport

Light–wave quantum electronics utilizes the oscillating carrier wave to control electronic properties with intense laser pulses. Without direct light–spin interactions, however, magnetic properties can only be indirectly affected by the light electric field, mostly at later times. A grand challenge is how to establish a universal principle for quantum control of charge and spin fluctuations, which can allow for faster-than-THz clock rates. Using quantum kinetic equations for the density matrix describing non–equilibrium states of Hubbard quasiparticles, here we show that time–periodic modulation of electronic hopping during few cycles of carrier–wave oscillations can dynamically steer an antiferromagnetic insulating state into a metalic state with transient magnetization. While nonlinearities associated with quasi-stationary Floquet states have been achieved before, magneto–electronics based on quasiparticle acceleration by time–periodic multi–cycle fields and quantum femtosecond/attosecond magnetism via strongly–coupled charge–spin quantum excitations represents an alternative way of controlling magnetic moments in sync with quantum transport.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Quantum sensing for emerging energy technologies

The ability to exploit quantum phenomena has enabled sensing technologies with detection limits below the classical limit. Sensors with applications in energy discovery, production, transportation, and consumption can be enhanced through quantum or hybrid quantum-classical sensors. Here, in this Review, we provide an overview of commercial and emerging quantum sensor platforms and their opportunity areas specific to advanced energy technologies. Key examples include: power grid-enhancing-technologies, where quantum magnetometers can detect powerline and transformer faults; electric vehicle-to-grid applications, where chip-scale atomic clocks can enable grid synchronization; and carbon capture and storage, where quantum gravimeters and single-photo LiDAR can detect microscopic leaks. Quantum sensor deployment requires further research into miniaturization and ruggedization for field deployment, cost-reduction, and workforce development. The maturation of clean energy technologies and quantum sensors provide opportunities for synergy, with the integration of quantum sensors into advanced energy technologies maximizing their security, reliability, and efficiency.

critical metals↗
DOE OSTI2021

Numerical solution of large scale Hartree–Fock–Bogoliubov equations

The Hartree–Fock–Bogoliubov (HFB) theory is the starting point for treating superconducting systems. However, the computational cost for solving large scale HFB equations can be much larger than that of the Hartree–Fock equations, particularly when the Hamiltonian matrix is sparse, and the number of electrons N is relatively small compared to the matrix size N b . We first provide a concise and relatively self-contained review of the HFB theory for general finite sized quantum systems, with special focus on the treatment of spin symmetries from a linear algebra perspective. We then demonstrate that the pole expansion and selected inversion (PEXSI) method can be particularly well suited for solving large scale HFB equations. For a Hubbard-type Hamiltonian, the cost of PEXSI is at most $\mathcal{O}$(N b 2 ) for both gapped and gapless systems, which can be significantly faster than the standard cubic scaling diagonalization methods. We show that PEXSI can solve a two-dimensional Hubbard-Hofstadter model with N b up to 2.88 × 10 6 , and the wall clock time is less than 100 s using 17 280 CPU cores. Finally, this enables the simulation of physical systems under experimentally realizable magnetic fields, which cannot be otherwise simulated with smaller systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Proactive Operations and Investment Planning via Stochastic Optimization to Enhance Power Systems’ Extreme Weather Resilience

We present scalable stochastic optimization approaches for improving power systems’ resilience to extreme weather events. We consider both proactive redispatch and transmission line hardening as alternatives for mitigating expected load shed due to extreme weather, resulting in large-scale stochastic linear programs (LPs) and mixed-integer linear programs (MILPs). We solve these stochastic optimization problems with progressive hedging (PH), a parallel, scenario-based decomposition algorithm. Our computational experiments indicate that our proposed method for enhancing power system resilience can provide high-quality solutions efficiently. With up to 128 scenarios on a 2,000-bus network, the operations (redispatch) and investment (hardening) resilience problems can be solved in approximately 6 min and 2 h of wall-clock time, respectively. Additionally, we solve the investment problems with up to 512 scenarios, demonstrating that the approach scales very well with the number of scenarios. Moreover, the method produces high quality solutions that result in statistically significant reductions in expected load shed. Our proposed approach can be augmented to incorporate a variety of other operational and investment resilience strategies, or a combination of such strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Deep learning for NLTE spectral opacities

Computer simulations of high energy density science experiments are computationally challenging, consisting of multiple physics calculations including radiation transport, hydrodynamics, atomic physics, nuclear reactions, laser–plasma interactions, and more. To simulate inertial confinement fusion (ICF) experiments at high fidelity, each of these physics calculations should be as detailed as possible. However, this quickly becomes too computationally expensive even for modern supercomputers, and thus many simplifying assumptions are made to reduce the required computational time. Much of the research has focused on acceleration techniques for the various packages in multiphysics codes. In this work, we explore a novel method for accelerating physics packages via machine learning. The non-local thermodynamic equilibrium (NLTE) package is one of the most expensive calculations in the simulations of indirect drive inertial confinement fusion, taking several tens of percent of the total wall clock time. We explore the use of machine learning to accelerate this package, by essentially replacing the physics calculation with a deep neural network that has been trained to emulate the physics code. Overall, we demonstrate the feasibility of this approach on a simple problem and perform a side-by-side comparison of the physics calculation and the neural network inline in an ICF Hohlraum simulation. We show that the neural network achieves a 10× speed up in NLTE computational time while achieving good agreement with the physics code for several quantities of interest.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Low-loss low thermo-optic coefficient Ta 2 O 5 on crystal quartz planar optical waveguides

Optical resonator-based frequency stabilization plays a critical role in ultra-low linewidth laser emission and precision sensing, atom clocks, and quantum applications. However, there has been limited success in translating traditional bench-top stabilization cavities to compact on-chip integrated waveguide structures that are compatible with photonic integration. The challenge lies in realizing waveguides that not only deliver low optical loss but also exhibit a low thermo-optic coefficient and frequency noise stability. Given the problematic sources of frequency noise within dielectrics, such as thermorefractive noise, resonators with small thermo-optic response are desirable for on-chip reference cavities. We report the first demonstration of a Ta 2 O 5 (tantala) waveguide core fabricated on a crystal quartz substrate lower cladding with TEOS-PECVD SiO 2 upper cladding. This waveguide offers significant advantages over other waveguides in terms of its low thermo-optic coefficient and reduced thermorefractive-related frequency noise. We describe the waveguide structure and key design parameters as well as fabrication considerations for processing tantala on quartz waveguides. We report a waveguide thermo-optic coefficient of -1.14 × 10 -6 RIU/K, a value that is over 6 times smaller in magnitude than that of SiO 2 -substrate tantala waveguides, with a propagation loss of 1.19 dB/cm at 1550 nm and <1.33 dB/cm across the 1525 nm–1610 nm wavelength range. Within a 1.6 mm radius ring resonator, we demonstrate a 2.54 × 10 5 intrinsic Q factor. With the potential for very low loss and the ability to control the thermal response, this waveguide platform takes a key step toward creating thermally stable integrated resonators for on-chip laser frequency stabilization and other applications.

42 ENGINEERING↗
DOE OSTI2021

A modified Villain formulation of fractons and other exotic theories

We reformulate known exotic theories (including theories of fractons) on a Euclidean spacetime lattice. We write them using the Villain approach and then we modify them to a convenient range of parameters. The new lattice models are closer to the continuum limit than the original lattice versions. In particular, they exhibit many of the recently found properties of the continuum theories including emergent global symmetries and surprising dualities. Also, these new models provide a clear and rigorous formulation to the continuum models and their singularities. In appendices, we use this approach to review well-studied lattice models and their continuum limits. These include the XY-model, the $\mathbb{Z}_N$ clock-model, and various gauge theories in diverse dimensions. Here, this presentation clarifies the relation between the condensed-matter and the high-energy views of these systems. It emphasizes the role of symmetries associated with the topology of field space, duality, and various anomalies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Resonant amplification of enzymatic chemical oscillations by oscillating flow

Using theory and simulation, we analyzed the resonant amplification of chemical oscillations that occur due to externally imposed oscillatory fluid flows. The chemical reactions are promoted by two enzyme-coated patches located sequentially on the inner surface of a pipe that transports the enclosed chemical solution. In the case of diffusion-limited systems, the period of oscillations in chemical reaction networks is determined by the rate of the chemical transport, which is diffusive in nature and, therefore, can be effectively accelerated by the imposed fluid flows. In this work, we first identify the natural frequencies of the chemical oscillations in the unperturbed reaction–diffusion system and, then, use the frequencies as a forcing input to drive the system to resonance. We demonstrate that flow-induced resonance can be used to amplify the amplitude of the chemical oscillations and to synchronize their frequency to the external forcing. In particular, we show that even 10% perturbations in the flow velocities can double the amplitude of the resulting chemical oscillations. Particularly, effective control can be achieved for the two-step chemical reactions where during the first half-period, the fluid flow accelerates the chemical flux toward the second catalytic patch, while during the second half-period, the flow amplifies the flux to the first patch. The results can provide design rules for regulating the dynamics of coupled reaction–diffusion processes and can facilitate the development of chemical reaction networks that act as chemical clocks.

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

Massively parallel GPU enabled third-order cluster perturbation excitation energies for cost-effective large scale excitation energy calculations

We present here a massively parallel implementation of the recently developed CPS(D-3) excitation energy model that is based on cluster perturbation theory. The new algorithm extends the one developed in Baudin et al. [J. Chem. Phys., 150, 134110 (2019)] to leverage multiple nodes and utilize graphical processing units for the acceleration of heavy tensor contractions. Furthermore, we show that the extended algorithm scales efficiently with increasing amounts of computational resources and that the developed code enables CPS(D-3) excitation energy calculations on large molecular systems with a low time-to-solution. More specifically, calculations on systems with over 100 atoms and 1000 basis functions are possible in a few hours of wall clock time. This establishes CPS(D-3) excitation energies as a computationally efficient alternative to those obtained from the coupled-cluster singles and doubles model.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Isotope study of the nonlinear pressure shifts of 85 Rb and 87 Rb hyperfine resonances in Ar, Kr, and Xe buffer gases

Measurements of the 0–0 hyperfine resonant frequencies of ground-state 85 Rb atoms show a nonlinear dependence on the pressure of the buffer gases Ar, Kr, and Xe. The nonlinearities are similar to those previously observed with 87 Rb and 133 Cs and presumed to come from alkali-metal–noble-gas van der Waals molecules. However, the shape of the nonlinearity observed for Xe conflicts with previous theory, and the nonlinearities for Ar and Kr disagree with the expected isotopic scaling of previous 87 Rb results. Improving the modeling alleviates most of these discrepancies by treating rotation quantum mechanically and considering additional spin interactions in the molecules. Including the dipolar-hyperfine interaction allows simultaneous fitting of the linear and nonlinear shifts of both 85 Rb and 87 Rb in either Ar, Kr, or Xe buffer gases with a minimal set of shared, isotope-independent parameters. To the limit of experimental accuracy, the shifts in He and N 2 were linear with pressure. Further, the results are of practical interest to vapor-cell atomic clocks and related devices.

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

Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models

Three machine learning techniques (multilayer perceptron, random forest, and Gaussian process) provide fast surrogate models for lower hybrid current drive (LHCD) simulations. A single GENRAY/CQL3D simulation without radial diffusion of fast electrons requires several minutes of wall-clock time to complete, which is acceptable for many purposes, but too slow for integrated modeling and real-time control applications. More accurate simulations with fast electron diffusion are even slower, requiring multiple hours of run time with parallel processing. The machine learning models use a database of 16,000+ GEN-RAY/CQL3D simulations for training, validation, and testing. Latin hypercube sampling methods implemented in πScope ensure that the database covers the range of 9 input parameters (n e0 , T e0 , I p , B t , R 0 , n ∥︀ , Z e f f , V loop , P LHCD ) with sufficient density in all regions of parameter space. The surrogate models reduce the computation time from minutes-hours to ms with high accuracy across the input parameter space. Data-driven surrogate models also allow for solving inverse and “lateral” problems. A surrogate model for the inverse problem maps from a desired current drive or power deposition profile to a set of input parameters that would result in such a profile, while a surrogate model for the lateral problem maps from a measured experimental quantity such as hard x-ray emission to a current drive or power deposition profile. In conclusion, the πScope database creation workflow is flexible and applicable to other RF simulation codes such as TORIC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Generalised hyper-Ramsey spectroscopy of two-level atoms in an optically dense medium

The peculiarities of Ramsey resonance and its sensitivity to the light shift from an optically dense medium of cold atoms are investigated. Different composite pulse protocols for clock spectroscopy, including hyper-Ramsey, modified and generalised hyper-Ramsey schemes, are compared. Error signals change significantly due to the processes of absorption and dispersion in the atomic medium. The dependence of the position of the central fringe resonance with a residual uncompensated light shift of the atomic transition is studied with the attenuation of the radiation intensity in the medium taken into account. It is shown that using a combination of generalised hyper-Ramsey error signals allows one to suppress the sensitivity to the light shift for any length of the medium. (laser cooling of atoms)

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Compensation of residual amplitude modulation fluctuations in an optoelectronic system for laser radiation frequency stabilisation

Fluctuations of residual amplitude modulation in a scheme of laser frequency stabilisation by a Fabry – Perot cavity reduce the frequency stability of the laser systems intended for interrogating clock transitions of atoms and ions. The dependences of the residual amplitude modulation on a temperature of the waveguide-based electro-optical modulator used for modulating the radiation phase and on polarisation of the radiation are measured. The parameters are found, at which the influence of the residual amplitude modulation on the frequency stability is minimal. A system for active compensation is created, which reduces the contribution of fluctuations of residual amplitude modulation to the instability down to 2.1 × 10{sup −16}, which makes it possible to reach the thermal noise limit of a silicon cryogenic cavity. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Compact ultrastable laser system for spectroscopy of {sup 2}S{sub 1/2} → {sup 2}D{sub 3/2} quadrupole transition in {sup 171}Yb{sup +} ion

We report the results of studying a compact laser system designed for manipulating a quantum state of the optical qubit based on the {sup 2}S{sub 1/2} → {sup 2}D{sub 3/2} quadrupole transition in the {sup 171}Yb{sup +} ion at a wavelength of 435.5 nm. An emission power of the laser system reaches 500 μW at λ = 435.5 nm and the relative frequency instability of at most 3 × 10{sup −15} is achieved at averaging intervals from 0.5 to 50 s with a subtracted linear frequency drift. The compactness of the developed system makes it possible to employ it in transportable systems including optical clocks. (laser spectroscopy)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗