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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Milliwatt-level UV generation using sidewall poled lithium niobate

Integrated coherent sources of ultra-violet (UV) light are essential for a wide range of applications, from ion-based quantum computing and optical clocks to gas sensing and microscopy. Recently, approaches that use frequency upconversion have received considerable attention. Among these, the integrated thin-film lithium niobate (TFLN) photonic platform shows particular promise. However, to date, the high propagation losses and lack of reliable techniques for consistent poling of cm-long waveguides with small poling periods have impeded progress. Here, we present a sidewall poled lithium niobate (SPLN) waveguide approach that overcomes these obstacles and results in a two-orders-of-magnitude increase in generated UV power. We demonstrate SPLN waveguides featuring record-low propagation losses of 2.3 dB/cm, complete domain inversion across the waveguide cross-section, and an optimum 50% duty cycle, resulting in a record-high normalized conversion efficiency of 5050%W$^{−1}$cm$^{−2}$, and 4.2 mW of generated on-chip power at 390 nm wavelength. This advancement makes the TFLN platform a viable option for high-quality on-chip UV generation, benefiting emerging applications.

Franken, C. A.A. [Harvard U.; Twente U., Enschede]↗
DOE OSTI2026

Learning turbulent flows with generative models for super resolution and sparse flow reconstruction

Neural operators are promising surrogates for dynamical systems but when trained with standard L 2 losses they tend to oversmooth fine-scale turbulent structures. Here, we show that combining operator learning with generative modeling overcomes this limitation. We consider three practical turbulent-flow challenges where conventional neural operators fail: spatio-temporal super-resolution, forecasting, and sparse flow reconstruction. For Schlieren jet super-resolution, an adversarially trained neural operator (adv-NO) reduces the energy-spectrum error by 15 × while preserving sharp gradients at neural operator-like inference cost. For 3D homogeneous isotropic turbulence, adv-NO trained on only 160 timesteps from a single trajectory forecasts accurately for five eddy-turnover times and offers 114 × wall-clock speed-up at inference than the baseline diffusion-based forecasters, enabling near-real-time rollouts. For reconstructing cylinder wake flows from highly sparse Particle Tracking Velocimetry-like inputs, a conditional generative model infers full 3D velocity and pressure fields with correct phase alignment and statistics. These advances enable accurate reconstruction and forecasting at low compute cost, bringing near-real-time analysis and control within reach in experimental and computational fluid mechanics.

Fluid dynamics↗
DOE OSTI2023

High-fidelity trapped-ion qubit operations with scalable photonic modulators

Abstract Experiments with trapped ions and neutral atoms typically employ optical modulators in order to control the phase, frequency, and amplitude of light directed to individual atoms. These elements are expensive, bulky, consume substantial power, and often rely on free-space I/O channels, all of which pose scaling challenges. To support many-ion systems like trapped-ion quantum computers or miniaturized deployable devices like clocks and sensors, these elements must ultimately be microfabricated, ideally monolithically with the trap to avoid losses associated with optical coupling between physically separate components. In this work we design, fabricate, and test an optical modulator capable of monolithic integration with a surface-electrode ion trap. These devices consist of piezo-optomechanical photonic integrated circuits configured as multi-stage Mach-Zehnder modulators that are used to control the intensity of light delivered to a single trapped ion on a separate chip. We use quantum tomography employing hundreds of multi-gate sequences to enhance the sensitivity of the fidelity to the types and magnitudes of gate errors relevant to quantum computing and better characterize the performance of the modulators, ultimately measuring single qubit gate fidelities that exceed 99.7%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Quantum networks with neutral atom processing nodes

Abstract Quantum networks providing shared entanglement over a mesh of quantum nodes will revolutionize the field of quantum information science by offering novel applications in quantum computation, enhanced precision in networks of sensors and clocks, and efficient quantum communication over large distances. Recent experimental progress with individual neutral atoms demonstrates a high potential for implementing the crucial components of such networks. We highlight latest developments and near-term prospects on how arrays of individually controlled neutral atoms are suited for both efficient remote entanglement generation and large-scale quantum information processing, thereby providing the necessary features for sharing high-fidelity and error-corrected multi-qubit entangled states between the nodes. We describe both the functionality requirements and several examples for advanced, large-scale quantum networks composed of neutral atom processing nodes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Laser cooling of antihydrogen atoms

The photon—the quantum excitation of the electromagnetic field—is massless but carries momentum. A photon can therefore exert a force on an object upon collision 1 . Slowing the translational motion of atoms and ions by application of such a force 2,3 , known as laser cooling, was first demonstrated 40 years ago 4,5 . It revolutionized atomic physics over the following decades 6–8 , and it is now a workhorse in many fields, including studies on quantum degenerate gases, quantum information, atomic clocks and tests of fundamental physics. However, this technique has not yet been applied to antimatter. Here we demonstrate laser cooling of antihydrogen 9 , the antimatter atom consisting of an antiproton and a positron. By exciting the 1S–2P transition in antihydrogen with pulsed, narrow-linewidth, Lyman-α laser radiation 10,11 , we Doppler-cool a sample of magnetically trapped antihydrogen. Although we apply laser cooling in only one dimension, the trap couples the longitudinal and transverse motions of the anti-atoms, leading to cooling in all three dimensions. We observe a reduction in the median transverse energy by more than an order of magnitude—with a substantial fraction of the anti-atoms attaining submicroelectronvolt transverse kinetic energies. We also report the observation of the laser-driven 1S–2S transition in samples of laser-cooled antihydrogen atoms. The observed spectral line is approximately four times narrower than that obtained without laser cooling. The demonstration of laser cooling and its immediate application has far-reaching implications for antimatter studies. A more localized, denser and colder sample of antihydrogen will drastically improve spectroscopic 11–13 and gravitational 14 studies of antihydrogen in ongoing experiments. Furthermore, the demonstrated ability to manipulate the motion of antimatter atoms by laser light will potentially provide ground-breaking opportunities for future experiments, such as anti-atomic fountains, anti-atom interferometry and the creation of antimatter molecules.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Structural evidence for intermediates during O 2 formation in photosystem II

In natural photosynthesis, the light-driven splitting of water into electrons, protons and molecular oxygen forms the first step of the solar-to-chemical energy conversion process. The reaction takes place in photosystem II, where the Mn 4 CaO 5 cluster first stores four oxidizing equivalents, the S 0 to S 4 intermediate states in the Kok cycle, sequentially generated by photochemical charge separations in the reaction center and then catalyzes the O–O bond formation chemistry. Here, we report room temperature snapshots by serial femtosecond X-ray crystallography to provide structural insights into the final reaction step of Kok’s photosynthetic water oxidation cycle, the S 3 →[S 4 ]→S 0 transition where O 2 is formed and Kok’s water oxidation clock is reset. Our data reveal a complex sequence of events, which occur over micro- to milliseconds, comprising changes at the Mn 4 CaO 5 cluster, its ligands and water pathways as well as controlled proton release through the hydrogen-bonding network of the Cl1 channel. Importantly, the extra O atom O x , which was introduced as a bridging ligand between Ca and Mn1 during the S 2 →S 3 transition disappears or relocates in parallel with Y z reduction starting at approximately 700 μs after the third flash. The onset of O 2 evolution, as indicated by the shortening of the Mn1–Mn4 distance, occurs at around 1,200 μs, signifying the presence of a reduced intermediate, possibly a bound peroxide.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

3D-printed micro ion trap technology for quantum information applications

Trapped-ion applications, such as in quantum information processing1, precision measurements, optical clocks and mass spectrometry, rely on specialized high-performance ion traps. The last three of these applications typically use traditional machining to customize macroscopic 3D Paul traps, whereas quantum information processing experiments usually rely on photolithographic techniques to miniaturize the traps and meet scalability requirements. Using photolithography, however, it is challenging to fabricate the complex 3D electrode structures required for optimal confinement. Here, in this work, we demonstrate a high-resolution 3D printing technology based on two-photon polymerization (2PP) that is capable of fabricating large arrays of high-performance miniaturized 3D traps. We show that 3D-printed ion traps combine the advantages, such as strong radial confinement, of traditionally machined 3D traps with on-chip miniaturization. We trap calcium ions in 3D-printed ion traps with radial trap frequencies ranging from 2 MHz to 24 MHz. The tight confinement eases ion cooling requirements and allows us to implement high-quality Rabi oscillations with Doppler cooling only. Also, we demonstrate a two-qubit gate with a Bell-state fidelity of 0.978 ± 0.012. With 3D printing technology, the design freedom is greatly expanded without sacrificing scalability and precision, so that ion trap geometries can be optimized for higher performance and better functionality.

quantum information↗
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↗