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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

CRADA Number NFE-18-07313 with Nth Cycle, Inc. (CRADA Final Report)

Cooperative Research and Development Agreement (CRADA) NFE-18-07313 between Oak Ridge National Laboratory (ORNL) and Nth Cycle Inc. focused on developing a technology for sustainable recycling of rare earth and specialty metals (e.g., Y, Co, Li; RESE), as well as bulk and precious metals from industrial manufacturing and waste streams through the use of electrochemical carbon nanotube-enabled filters. The project outcome was expected to be a stronger mechanistic understanding of the electrochemical recovery of metals from real manufacturing process streams and e-waste streams, and the development of an optimized high-throughput pilot-scale device ready for commercialization. Testing, design, and development of a v1 prototype to prove the technology was unsuccessful (we were not able to reach the go/no-go outlined in Objective 1) and we were unable to continue our redesign due to COVID-19 lockdown and no access to lab from March 2020 – until our graduation from the program.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Harnessing large language models’ zero-shot and few-shot learning capabilities for regulatory research

Abstract Large language models (LLMs) are sophisticated AI-driven models trained on vast sources of natural language data. They are adept at generating responses that closely mimic human conversational patterns. One of the most notable examples is OpenAI's ChatGPT, which has been extensively used across diverse sectors. Despite their flexibility, a significant challenge arises as most users must transmit their data to the servers of companies operating these models. Utilizing ChatGPT or similar models online may inadvertently expose sensitive information to the risk of data breaches. Therefore, implementing LLMs that are open source and smaller in scale within a secure local network becomes a crucial step for organizations where ensuring data privacy and protection has the highest priority, such as regulatory agencies. As a feasibility evaluation, we implemented a series of open-source LLMs within a regulatory agency’s local network and assessed their performance on specific tasks involving extracting relevant clinical pharmacology information from regulatory drug labels. Our research shows that some models work well in the context of few- or zero-shot learning, achieving performance comparable, or even better than, neural network models that needed thousands of training samples. One of the models was selected to address a real-world issue of finding intrinsic factors that affect drugs' clinical exposure without any training or fine-tuning. In a dataset of over 700 000 sentences, the model showed a 78.5% accuracy rate. Our work pointed to the possibility of implementing open-source LLMs within a secure local network and using these models to perform various natural language processing tasks when large numbers of training examples are unavailable.

Biochemistry & Molecular Biology↗
DOE OSTI2019

Dynamic spin localization and γ -magnets

Here, we explore an unusual type of quantum matter that can be realized by qubits having different physical origins. Interactions in this matter are described by essentially different coupling operators for all qubits. We show that the simplest such models, which can be realized with localized states in Dirac materials, satisfy integrability conditions that we use to describe pseudospin dynamics in a linearly time-dependent magnetic field. Generalizing to an arbitrary number of qubits, we construct a spin Hamiltonian, which we call the γ -magnet. This system does not conserve polarization of any spin and the net spin polarization. Nevertheless, for arbitrarily strong interactions, nonadiabatic dynamics, and any initial eigenstate, we find that quantum interference suppresses spin flips. This behavior resembles many-body localization but occurs in phase space of many spins rather than real space. This effect may not have a counterpart in classical physics and can be a signature of a new type of spin ordering, which is different from both disordered spin glasses and ordered phases of spin lattices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

thevenin: An Equivalent Circuit Modeling Package [SWR-24-132]

This package is a wrapper for the well-known Thevenin equivalent circuit model for simulating battery behavior with a focus on ease of use. The model is comprised of a single series resistor followed by any number of parallel RC pairs. The package includes an intuitive "experiment" interface, which simplifies the programming of constant or dynamic current, voltage, and/or power-driven loads, making it ideal for a wide range of applications, from basic tests to complex simulations. It also supports state-of-charge (SOC) and temperature-dependent properties, allowing the model to be more easily calibrated against real cells.

Randall, Corey↗
DOE OSTI2023

MASK4 Test Campaign for Sandia WaveBot Device

This data and report details the findings from a wave tank test focused on production of useful work of a wave energy converter (WEC) device. The experimental system and test were specifically designed to validate models for power transmission throughout the WEC system. Additionally, the validity of co-design informed changes to the power take-off (PTO) were assessed and shown to provide the expected improvements in system performance. These data describe the "MASK4" wave tank test of the Sandia WaveBot device. The WaveBot device has been tested a number of times in different permutations at the US Navy's Maneuvering and Sea Keeping (MASK) basin. Each test in this series is referred to as MASK1, MASK2, etc. The WaveBot device was first tested in one degree of freedom (heave) in 2016. This MASK1 test focused primarily on system identification and modeling. After MASK1, major modifications were performed to improve the overall real-time control and measurement system, improve the heave drive train, and add surge and pitch degrees of freedom. The second set of testing, which was broken up in to two stages: MASK2A and MASK2B, focused on bench testing and closed-loop control performance as well as nonlinear modeling. MASK3 then focused on multi-input, multi-output modeling and control for maximization of electrical power. The attached report presents the results from MASK4, which focuses on detailed modeling of the power conversion chain and validation co-design principles by way of the introduction of a magnetic spring. The test log, report, and data from the MASK4 test of the WaveBot augmented with a tunable magnetic spring. Processing codes can be found at the Github link below.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Initial-State Dependent Optimization of Controlled Gate Operations with Quantum Computer

There is no unique way to encode a quantum algorithm into a quantum circuit. With limited qubit counts, connectivity, and coherence times, a quantum circuit optimization is essential to make the best use of near-term quantum devices. We introduce a new circuit optimizer called AQCEL, which aims to remove redundant controlled operations from controlled gates, depending on initial states of the circuit. Especially, the AQCEL can remove unnecessary qubit controls from multi-controlled gates in polynomial computational resources, even when all the relevant qubits are entangled, by identifying zero-amplitude computational basis states using a quantum computer. As a benchmark, the AQCEL is deployed on a quantum algorithm designed to model final state radiation in high energy physics. For this benchmark, we have demonstrated that the AQCEL-optimized circuit can produce equivalent final states with much smaller number of gates. Moreover, when deploying AQCEL with a noisy intermediate scale quantum computer, it efficiently produces a quantum circuit that approximates the original circuit with high fidelity by truncating low-amplitude computational basis states below certain thresholds. Our technique is useful for a wide variety of quantum algorithms, opening up new possibilities to further simplify quantum circuits to be more effective for real devices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Characterizing Current THD’s Dependency on Solar Irradiance and Supraharmonics Profiling for a Grid-Tied Photovoltaic Power Plant

The rapidly increasing distributed energy resources (DERs) in power systems are now getting interconnected to set community grid structures, where power quality will be a major concern. The grid-to-grid (G2G) bidirectional power transfer among the distribution microgrid will not be considered commercially feasible unless the upstream harmonics are under the limits. The aggregation of such harmonics, measured as total harmonic distortion (THD), is feared to be beyond tolerable limits with the progression of rooftop grid-tied PV-like installations. Hence, this THD needs to be characterized with DER generation end variables. In this work, the photovoltaic (PV) DERs’ dependency on environment variables such as irradiance was profiled in the context of generating and injecting harmonics into the grid. A mathematical model of a grid-tied three-phase PV DER was developed as part of this correlation characterization, matching the fundamental unit structure of a 1.4 MW solar canopy located on the Florida International University (FIU) Miami campus. To determine the qualitative association with produced THD patterns, the model was evaluated with various irradiance settings. A real-time digital simulation (RTDS) platform was used to verify it. Following this confirmation, sets of data from power quality meters at the point of common coupling and FIU field sensors were utilized to validate further the correlation model. The results showed that the grid current’s THD exhibited a high correlation with the irradiance profile and its variation over time. The early morning and late afternoon periods of the day, associated with a low irradiance, constantly had higher harmonics generated from the PV DER. The midday THD was rather rational with partial shadings, hence a geolocation-dependent factor. These findings were verified by an RTDS and validated by real field data. In quantifying the THD injected by a single DER at a high-frequency (2–150 kHz) supraharmonics (SH) level, a 3% peak increment in magnitude was observed from the high-fixed to the low-fixed irradiance profile. The correlation characteristics depicted that the hybrid microgrid suffered from a daytime-dependent harmonic insertion from the grid-tied DER. This is a global problem unless specific measures are taken to mitigate the harmonics. The electrically notorious higher-frequency SH was found to increase proportionally. The G2G power transfer can be limited because of the higher THD in the early morning and late afternoon, which will also worsen because the numbers of grid-tied PV DERs (i.e., rooftop solar and industrial solar) are likely to increase rapidly soon. The community grid structure can thus have a controlled harmonics filtration setup purposefully designed to address the findings of this work, which also fall within the scope of our future research.

14 SOLAR ENERGY↗
DOE OSTI2020

Dirty bosons on the Cayley tree: Bose-Einstein condensation versus ergodicity breaking

Building on large-scale quantum Monte Carlo simulations, we investigate the zero-temperature phase diagram of hard-core bosons in a random potential on site-centered Cayley trees with branching number K=2. In order to follow how the Bose-Einstein condensate (BEC) is affected by the disorder, we focus on both the zero-momentum density, probing the quantum coherence, and the one-body density matrix (1BDM) whose largest eigenvalue monitors the off-diagonal long-range order. We further study its associated eigenstate which brings useful information about the real-space properties of this leading eigenmode. Upon increasing randomness, we find that the system undergoes a quantum phase transition at finite disorder strength between a long-range ordered BEC state, fully ergodic at large scale, and a new disordered Bose glass regime showing conventional localization for the coherence fraction while the 1BDM displays a nontrivial algebraic vanishing BEC density together with a nonergodic occupation in real space. These peculiar properties can be analytically captured by a simple phenomenological description on the Cayley tree which provides a physical picture of the Bose glass regime.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Inference-Based Quantum Sensing

In a standard quantum sensing (QS) task one aims at estimating an unknown parameter θ, encoded into an n-qubit probe state, via measurements of the system. The success of this task hinges on the ability to correlate changes in the parameter to changes in the system response $\mathscr{R}$⁡(θ) (i.e., changes in the measurement outcomes). For simple cases the form of $\mathscr{R}$⁡(θ) is known, but the same cannot be said for realistic scenarios, as no general closed-form expression exists. Here, in this Letter, we present an inference-based scheme for QS. We show that, for a general class of unitary families of encoding, $\mathscr{R}$⁡(θ) can be fully characterized by only measuring the system response at 2⁢n+1 parameters. This allows us to infer the value of an unknown parameter given the measured response, as well as to determine the sensitivity of the scheme, which characterizes its overall performance. We show that inference error is, with high probability, smaller than δ, if one measures the system response with a number of shots that scales only as Ω⁢(log 3 ⁡(n)/δ 2 ). Furthermore, the framework presented can be broadly applied as it remains valid for arbitrary probe states and measurement schemes, and, even holds in the presence of quantum noise. We also discuss how to extend our results beyond unitary families. Finally, to showcase our method we implement it for a QS task on real quantum hardware, and in numerical simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Probing Quantum Telecloning on Superconducting Quantum Processors

Quantum information cannot be perfectly cloned, but approximate copies of quantum information can be generated. Quantum telecloning combines approximate quantum cloning, more typically referred to as quantum cloning, and quantum teleportation. Quantum telecloning allows approximate copies of quantum information to be constructed by separate parties, using the classical results of a Bell measurement made on a prepared quantum telecloning state. Quantum telecloning can be implemented as a circuit on quantum computers using a classical coprocessor to compute classical feedforward instructions using if statements based on the results of a midcircuit Bell measurement in real time. We present universal symmetric optimal 1 → M telecloning circuits and experimentally demonstrate these quantum telecloning circuits for M = 2 up to M = 10, natively executed with real-time classical control systems on IBM Quantum superconducting processors, known as dynamic circuits. We perform the cloning procedure on many different message states across the Bloch sphere, on seven IBM Quantum processors, optionally using the error suppression technique X–X sequence digital dynamical decoupling. Two circuit optimizations are utilized: one that removes ancilla qubits for M = 2,3 , and one that reduces the total number of gates in the circuit but still uses ancilla qubits. Parallel single-qubit tomography with maximum likelihood estimation density matrix reconstruction is used in order to compute the mixed-state density matrices of the clone qubits, and clone quality is measured using quantum fidelity. These results present one of the largest and most comprehensive noisy intermediate-scale quantum computer experimental analyses on (single qubit) quantum telecloning to date. The clone fidelity sharply decreases to 0.5 for M > 5 , but for M = 2 , we are able to achieve a mean clone fidelity of up to 0.79 using dynamical decoupling.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

EV Hosting Capacity Analysis on Distribution Grids: Preprint

Increasing electric vehicle (EV) charging loads can increase the magnitude and duration of conventional peaks in demand profiles and even shift them significantly, causing operational violations in the distribution grid. It is important to develop tools to quantify the impacts of injecting large number of EV charging loads and determine the available capacity of the existing distribution feeder for the safe operation of the grid. Such tools would enable utilities to better prepare for grid operations in the near future while exploring the impact and effectiveness of strategies such as peak pricing and smart charging in managing these loads. This paper evaluates the hosting capacity of some real-world feeders to accommodate EV charging loads, including extreme fast-charging (xFC) options.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Orientation reversal and the Chern-Simons natural boundary

We show that the fundamental property of preservation of relations, underlying resurgent analysis, provides a new perspective on crossing a natural boundary, an important general problem in theoretical and mathematical physics. This reveals a deeper rigidity aspect of resurgence in a quantum field theory path integral. The physical context here is the non-perturbative completion of complex Chern-Simons theory that associates to a 3-manifold a collection of q-series invariants labeled by Spinc structures, for which crossing the natural boundary corresponds to orientation reversal of the 3-manifold. Our new resurgent perspective leads to a practical numerical algorithm that generates q-series which are dual to unary q-series composed of false theta functions. Until recently, these duals were only known in a limited number of cases, essentially based on Ramanujan’s mock theta functions, and the common belief was that the duals might not even exist in the general case. Resurgence analysis identifies as primary objects Mordell integrals: up to changes of variables, they are Laplace transforms of resurgent functions. Their unique Borel summed transseries decomposition on either side of the Stokes line is simply the unique decomposition into real and imaginary parts. In turn, the latter are combinations of unary q-series in terms of q and its modular counterpart $\overset{\sim }{q}$ , and are resurgent by construction. The Mordell integral is analytic across the natural boundary of the q and $\overset{\sim }{q}$ series, and uniqueness of a similar decomposition which preserves algebraic relations on the other side of the boundary defines the unique boundary crossing of the q series. We demonstrate that this continuation can be efficiently implemented numerically. In the cases where unique mock modular identities are known, they are found by this numerical procedure, but the procedure can go well beyond the known list of identities. A particularly interesting feature of the resurgent approach is that it reveals new aspects, and is very different from other known approaches based on indefinite theta series, Appell-Lerch sums, and representation theory of logarithmic vertex operator algebras.

Chern-Simons theories↗
DOE OSTI2021

Spin–spin interactions in defects in solids from mixed all-electron and pseudopotential first-principles calculations

Abstract Understanding the quantum dynamics of spin defects and their coherence properties requires an accurate modeling of spin-spin interaction in solids and molecules, for example by using spin Hamiltonians with parameters obtained from first principles calculations. We present a real-space approach based on density functional theory for the calculation of spin-Hamiltonian parameters, where only selected atoms are treated at the all-electron level, while the rest of the system is described with the pseudopotential approximation. Our approach permits calculations for systems containing more than 1000 atoms, as demonstrated for defects in diamond and silicon carbide. We show that only a small number of atoms surrounding the defect needs to be treated at the all-electron level, in order to obtain an overall all-electron accuracy for hyperfine and zero-field splitting tensors. We also present results for coherence times, computed with the cluster correlation expansion method, highlighting the importance of accurate spin-Hamiltonian parameters for quantitative predictions of spin dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Prevalence and scalable control of localized networks

The ability to control network dynamics is essential for ensuring desirable functionality of many technological, biological, and social systems. Such systems often consist of a large number of network elements, and controlling large-scale networks remains challenging because the computation and communication requirements increase prohibitively fast with network size. Here, we introduce a notion of network locality that can be exploited to make the control of networks scalable, even when the dynamics are nonlinear. We show that network locality is captured by an information metric and is almost universally observed across real and model networks. In localized networks, the optimal control actions and system responses are both shown to be necessarily concentrated in small neighborhoods induced by the information metric. This allows us to develop localized algorithms for determining network controllability and optimizing the placement of driver nodes. This also allows us to develop a localized algorithm for designing local feedback controllers that approach the performance of the corresponding best global controllers, while incurring a computational cost orders-of-magnitude lower. Here, we validate the locality, performance, and efficiency of the algorithms in Kuramoto oscillator networks, as well as three large empirical networks: synchronization dynamics in the Eastern US power grid, epidemic spreading mediated by the global air-transportation network, and Alzheimer’s disease dynamics in a human brain network. Taken together, our results establish that large networks can be controlled with computation and communication costs comparable to those for small networks.

42 ENGINEERING↗
DOE OSTI2022

Investigating color screening in proton-nucleus collisions with complex potentials*

Abstract Color screening and parton inelastic scattering modify the heavy-quark antiquark potential in mediums consisting of particles from quantum chromodynamics (QCD), leading to the suppression of quarkonium production in relativistic heavy-ion collisions. Owing to the small charm/anti-charm ( ) pair production number in proton-nucleus ( pA ) collisions, the correlation between different pairs is negligible, which makes the Schrödinger equation viable for tracking the evolution of only one pair. We employ the time-dependent Schrödinger equation with an in-medium potential to study the evolution of charmonium wave functions in a hydrodynamic-like QCD medium produced in pA collisions. We explore different parametrizations of real and imaginary parts of the potential and calculate the nuclear modification factors ( ) of and in TeV energy p -Pb collisions at the Large Hadron Collider (LHC). Comparing strong and weak screening scenarios with experimental data in this approach, we arrive at the conclusion that color screening is weak at temperatures close to the deconfined phase transition. Moreover, the imaginary part of the potential is crucial in describing the experimental data, which is consistent with widely studied semi-classical approaches, where dissociation rates are essential.

Physics↗
DOE OSTI2024

Trapped-ion quantum simulation of electron transfer models with tunable dissipation

Electron transfer is at the heart of many fundamental physical, chemical, and biochemical processes essential for life. The exact simulation of these reactions is often hindered by the large number of degrees of freedom and by the essential role of quantum effects. Here, we experimentally simulate a paradigmatic model of molecular electron transfer using a multispecies trapped-ion crystal, where the donor-acceptor gap, the electronic and vibronic couplings, and the bath relaxation dynamics can all be controlled independently. By manipulating both the ground-state and optical qubits, we observe the real-time dynamics of the spin excitation, measuring the transfer rate in several regimes of adiabaticity and relaxation dynamics. Our results provide a testing ground for increasingly rich models of molecular excitation transfer processes that are relevant for molecular electronics and light-harvesting systems.

Science & Technology - Other Topics↗
DOE OSTI2022

Multicolor multifocal 3D microscopy using in-situ optimization of a spatial light modulator

Abstract Multifocal microscopy enables high-speed three-dimensional (3D) volume imaging by using a multifocal grating in the emission path. This grating is typically designed to afford a uniform illumination of multifocal subimages for a single emission wavelength. Using the same grating for multicolor imaging results in non-uniform subimage intensities in emission wavelengths for which the grating is not designed. This has restricted multifocal microscopy applications for samples having multicolored fluorophores. In this paper, we present a multicolor multifocal microscope implementation which uses a Spatial Light Modulator (SLM) as a single multifocal grating to realize near-uniform multifocal subimage intensities across multiple wavelength emission bands. Using real-time control of an in-situ-optimized SLM implemented as a multifocal grating, we demonstrate multicolor multifocal 3D imaging over three emission bands by imaging multicolored particles as well as Escherichia coli ( E. coli ) interacting with human liver cancer cells, at $$\sim 2.5$$ ∼ 2.5 multicolor 3D volumes per second acquisition speed. Our multicolor multifocal method is adaptable across SLM hardware, emission wavelength band locations and number of emission bands, making it particularly suited for researchers investigating fast processes occurring across a volume where multiple species are involved.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

MONACO: accurate biological network alignment through optimal neighborhood matching between focal nodes

Motivation: Alignment of protein–protein interaction networks can be used for the unsupervised prediction of functional modules, such as protein complexes and signaling pathways, that are conserved across different species. To date, various algorithms have been proposed for biological network alignment, many of which attempt to incorporate topological similarity between the networks into the alignment process with the goal of constructing accurate and biologically meaningful alignments. Especially, random walk models have been shown to be effective for quantifying the global topological relatedness between nodes that belong to different networks by diffusing node-level similarity along the interaction edges. However, these schemes are not ideal for capturing the local topological similarity between nodes. Results: Here, we propose MONACO, a novel and versatile network alignment algorithm that finds highly accurate pairwise and multiple network alignments through the iterative optimal matching of ‘local’ neighborhoods around focal nodes. Extensive performance assessment based on real networks as well as synthetic networks, for which the ground truth is known, demonstrates that MONACO clearly and consistently outperforms all other state-of-the-art network alignment algorithms that we have tested, in terms of accuracy, coherence and topological quality of the aligned network regions. Furthermore, despite the sharply enhanced alignment accuracy, MONACO remains computationally efficient and it scales well with increasing size and number of networks.

97 MATHEMATICS AND COMPUTING↗