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Results for “emergency generator”

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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Visualization and quantum control of light-accelerated condensates by terahertz multi-dimensional coherent spectroscopy

Abstract Characterizing and controlling high-order correlation of quantum systems is key for developing quantum devices and switching technologies. Although conventional static and ultrafast spectroscopy gives access to collective excitations characterizing quantum states, more exotic correlations cannot be easily separated from other contributions. Here we develop density matrix simulations to show that seventh-order-wave-mixing peaks with distinct temperature and field dependences in two-dimensional terahertz nonlinear spectra reveal light-induced correlations in non-equilibrium superconducting states. Above critical terahertz driving, these emerging peaks split from conventional peaks along the second axis introduced by pump-probe relative phase in two-dimensional frequency space. They are photo-generated by correlations between two-photon fluctuations and interacting quasi-particle and quasi-particle/Higgs superconductor excitations. By photo-inducing persistent symmetry breaking via light-wave propagation, we also demonstrate seventh-order-wave-mixing sensing of Higgs collective modes. Our theory suggests to use multi-dimensional spectroscopy for quantum sensing of light-driven superconductivity and paves a path for quantum operations by few-cycle-THz-periodic photocurrent modulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Electronic glasses from a broken gauge symmetry in disorder-free systems

Glass phases can be stabilized by quenched disorders, as in most spin-glass materials, or self-generated through kinetic freezing in disorder-free systems. A canonical example of the latter is structural glasses, which have been extensively studied for many decades. Yet, how the rugged energy landscape of a glass phase is spontaneously generated in disorder-free systems remains one of the key questions in glass physics. Here, in this work, we present a general electronic mechanism for the emergence of glassy phase using the example of itinerant electrons coupled to XY spins on a lattice. This model can also be viewed as the mean-field theory of a superconducting system with attractive density-density interactions. Intriguingly, the electron gauge symmetry in the strong pairing limit gives rise to a macroscopic degeneracy of XY spins. In the presence of electron hopping that breaks the gauge symmetry, the lifting of the extensive degeneracy leads to a glass phase with disordered pairings. Our findings highlight a scenario in which a glassy state originates from the breaking of quantum gauge symmetry without quenched disorders.

XY model↗
DOE OSTI2021

Phase-engineered bosonic quantum codes

Continuous-variable systems protected by bosonic quantum codes have emerged as a promising platform for quantum information. To date, the design of code words has centered on optimizing the state occupation in the relevant basis to generate the distance needed for error correction. Here, we show tuning the phase degree of freedom in the design of code words can affect, and potentially enhance, the protection against Markovian errors that involve excitation exchange with the environment. As illustrations, we first consider phase engineering bosonic codes with uniform spacing in the Fock basis that correct excitation loss with a Kerr unitary and show that these modified codes feature destructive interference between error code words and, with an adapted “two-level” recovery, the error protection is significantly enhanced. We then study protection against energy decay with the presence of mode nonlinearities and analyze the role of phase for optimal code designs. As a result, we extend the principle of phase engineering to bosonic codes defined in other bases and multiqubit codes, demonstrating its broad applicability in quantum error correction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Direct experimental evidence of tunable charge transfer at the LaNiO 3 / CaMnO 3 ferromagnetic interface

Interfacial charge transfer in oxide heterostructures gives rise to a rich variety of electronic and magnetic phenomena. Designing heterostructures where one of the thin-film components exhibits a metal-insulator transition opens a promising avenue for controlling such phenomena both statically and dynamically. In this work, we utilize a combination of depth-resolved soft x-ray standing-wave and hard x-ray photoelectron spectroscopies in conjunction with polarization-dependent x-ray absorption spectroscopy to investigate the effects of the metal-insulator transition in LaNiO 3 on the electronic and magnetic states at the LaNiO 3 /CaMnO 3 interface. Here, we report a direct observation of the reduced effective valence state of the interfacial Mn cations in the metallic superlattice with an above-critical LaNiO 3 thickness (6 unit cells, u.c.) facilitated by the charge transfer of itinerant Ni 3d e g electrons into the interfacial CaMnO 3 layer. Conversely, in an insulating superlattice with a below-critical LaNiO 3 thickness of 2 u.c., a homogeneous effective valence state of Mn is observed throughout the CaMnO 3 layers due to the blockage of charge transfer across the interface. The ability to switch and tune interfacial charge transfer enables precise control of the emergent ferromagnetic state at the LaNiO 3 /CaMnO 3 interface and, thus, has far-reaching consequences on the future strategies for the design of next-generation spintronic devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Four-Spin Terms and the Origin of the Chiral Spin Liquid in Mott Insulators on the Triangular Lattice

At strong repulsion, the triangular-lattice Hubbard model is described by s=1/2 spins with nearest-neighbor antiferromagnetic Heisenberg interactions and exhibits conventional 120° order. Using the infinite density matrix renormalization group and exact diagonalization, we study the effect of the additional four-spin interactions naturally generated from the underlying Mott-insulator physics of electrons as the repulsion decreases. Although these interactions have historically been connected with a gapless ground state with emergent spinon Fermi surface, we find that, at physically relevant parameters, they stabilize a chiral spin liquid (CSL) of Kalmeyer-Laughlin (KL) type, clarifying observations in recent studies of the Hubbard model. Finally, we present a self-consistent solution based on a mean-field rewriting of the interaction to obtain a Hamiltonian with similarities to the parent Hamiltonian of the KL state, providing a physical understanding for the origin of the CSL.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Investigating Scientific Data Change with User Research Methods

Scientific datasets are continually expanding and changing due to fluctuations with instruments, quality assessment and quality control processes, and modifications to software pipelines. Datasets include minimal information about these changes or their effects requiring scientists manually assess modifications through a number of labor intensive and ad-hoc steps. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists systematically identify and make decisions around data changes. Currently, there is a lack of understanding, and common practices, for identifying and evaluating changes in datasets since systematically measuring and managing data change is under explored in scientific work. We are conducting user research to address this need by exploring scientist's conceptualizations, behaviors, needs, and motivations when dealing with changing datasets. Our user research utilizes multiple methods to produce foundational, generative insights and evaluate research products produced by our team. In this paper, we detail our user research process and outline our findings about data change that emerge from our studies. Our work illustrates how scientific software teams can push beyond just usability testing user interfaces or tools to better probe the underlying ideas they are developing solutions to address.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Power Supply Options for the Marpi Landfill, Saipan: Feasibility Study

The Marpi Landfill, located on the northern end of the island of Saipan in the Commonwealth of the Northern Mariana Islands (CNMI), is powered by an on-site diesel generator that only operates when the landfill is open and staffed. The CNMI Office of Planning and Development (OPD) aspires to provide the Marpi Landfill with 24-hour power availability despite its remote location and to increase the use of sustainable energy within the CNMI. CNMI has a 20% target for renewable energy consumption, as documented in Sustainable Development Goal #7 in the Comprehensive Sustainable Development Plan (OPD 2021) and the renewable portfolio standard (GPO 2014). To accomplish these goals, the U.S. Department of Energy, through its Interagency Reimbursable Work Agreement with the Federal Emergency Management Agency, funded this feasibility study to assess and prioritize power supply options for the landfill. The availability of solar and wind resources varies seasonally, as does the load. A BESS can help to balance mismatches between generation and load on short (hourly or daily) timescales, but not across seasons. The microgrid scenarios evaluated for Marpi consider options for technology combinations that will both meet the load and utilize available resources, despite the challenge presented by higher loads and lower solar and wind availability during the rainy season, depicted in Figure ES-2. The seven scenarios evaluated are summarized in Table ES-1. Each scenario’s configuration was optimized to include component capacities that reduce capital and operating costs, meet the load, and minimize carbon emissions, as feasible. The costs and levelized cost of energy (LCOE) shown do not assume the use of any grant funding or incentives, although these options were also evaluated. To assist with decision-making, a prioritization matrix (Table ES-3) was created to compare the microgrid scenarios evaluated in this feasibility study according to various stakeholder priorities. The prioritization metrics were chosen based on discussions with OPD and will be finalized through stakeholder feedback. The scenarios were given a score between 1 and 7 for each prioritization metric (the lower the score, the higher the priority), and total scores were calculated using assigned weights based on the relative priority of each metric. The total scores were then ranked to produce a prioritized list of microgrid scenarios based on the metrics most important to the project stakeholders. As shown, scenario 4 (100 kW of solar PV, a 75 kW/300 kWh BESS, and 160 kW of diesel generation) ranks highest.

14 SOLAR ENERGY↗
DOE OSTI2021

Generation of electric-field stabilized zirconium monoxide secondary phase within cubic zirconia

Flash sintering of cubic yttria-stabilized zirconia has been studied via in situ energy dispersive diffraction. A secondary rocksalt-phase zirconium monoxide was observed emerging from the primary fluorite-phase zirconium dioxide, previously only observed as a thin interlayer at metal-oxide interfaces, upon application of a direct current electric field. The average secondary phase intensity rose over extended flow of direct current through the ceramic, faded upon removal of the field and disappeared entirely upon application of an alternating current electric field. The results indicate that the sustained application of a direct current electric field can result in significant electrochemical reduction of zirconia under high current density conditions. Poor sinterability and cracking under direct current is apparent and potential mechanisms discussed therein.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multi-energy ion irradiation effects and distinctive features of color center generation in yttria-stabilized zirconia driven by structural discrepancy

Regarding a requirement for inert matrix fuel (IMF) to burn minor actinides and plutonium and high-level waste immobilization, Yttria-stabilized zirconia (ZrO 2 -6.5 wt% Y 2 O 3 ) (YSZ) crystals with cubic phase are selected to comprehensively evaluate the irradiation resistance by irradiation-induced structural discrepancies across multiple energy conditions. Electronic excitation and nuclear collisions reveal distinct color centers, influenced by varying component ratios that reflect their formation mechanisms. Key factors driving ultra-fast structural transitions include collision cascades, pressure waves, and energy dissipation from electronic excitation. In this work, we find that in the electronic energy loss (E ele )-dominant region, internal latent tracks with unique surface nanostructures emerge, distinct from the defect clusters seen in the nuclear energy loss (E nuc )-dominant region, while the threshold for latent track formation and melting are identified. In conclusion, structural discrepancies driven by different energy-loss mechanisms promote the generation of singly ionized and nearest-neighbor doubly ionized oxygen vacancies, which respectively dominate the formation of F⁺ and T-centers, resulting in bandgap narrowing (4.80 eV → 4.73 eV), and furthermore triggering visible light emission (2.17 eV → 2.20 eV) in irradiated YSZ crystals, thus, enabling the design of novel irradiation-tailored material functionalities.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Peculiarities of planar shockwave interaction with air–water interface and solid target

We present the results of the research on underwater electrical explosion of planar copper wire arrays, accompanied by the generation of a planar shock, using the synchrotron-based phase-contrast radiography imaging capabilities of the ID19 beamline at the European Synchrotron Radiation Facility. It is shown that the interaction of a strong shock with an air–water interface leads to additional acceleration of the wire expansion due to a rarefaction wave along with the emergence of micro-jets. In the case of a target placed above the array, we observed the formation of a cavity between the array and the target due to the interaction of two rarefaction waves. Furthermore, the results of two-dimensional hydrodynamic simulations of the wire explosion and the interaction of the generated shock with the water–air and water-target interfaces showed good agreement with experimental results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Developing Microalgae-Based Non-Isocyanate Polyurethane Foam Materials

Polyurethane is a versatile material with a wide range of applications in the production of foam products such as car seats, mattresses, footwear, insulation foam, and more. The traditional process for producing polyurethane foam involves the fast reaction of isocyanate with water, which generates CO2 as a blowing agent. However, the use of isocyanate has raised concerns due to its potential for causing allergic reactions and aspiration symptoms. This has led to increased regulation of isocyanate, leading to a growing interest in developing alternatives. Non-isocyanate polyurethane (NIPU) has emerged as a promising alternative to traditional toxic PU production. The most promising approach for producing NIPU is the aminolysis of cyclic carbonate with diamine. The NIPU produced through this process has a polyhydroxyurethane structure, which is similar to traditional PU chemistry. We have demonstrated that microalgal oil is a favored feedstock, as it can provide high reactivity for industrial applications. However, the NIPU production process does not generate gas, and a blowing agent is required to achieve the desired foam structure. One of the challenges in producing NIPU foam is to match the bubble formation and curing rates. We have developed a novel approach to producing NIPU foam that utilizes carbamate as a bifunctional blowing and crosslinking agent. We have used vegetable oil and microalgal oil as feedstocks to produce various NIPU for characterization. The development of microalgal NIPU provides an exciting opportunity for reducing the environmental impact of foam production and improving the safety of the materials used in the production process. The production of value-added NIPU foam can also drive down the cost of microalgal biorefinery, advancing the commercialization of microalgal biofuel.

algae↗
DOE OSTI2025

An argument for using anaerobes as microbial cell factories to advance synthetic biology and biomanufacturing

Anaerobes thrive in the absence of oxygen and are an untapped reservoir of biotechnological potential. Therefore, bioprospecting efforts focused on anaerobic microbial diversity could rapidly uncover new enzymes, pathways, and chassis organisms to drive biotechnology innovation. Despite their potential utility, anaerobic fermenters are viewed as inefficient from a biochemical perspective because their metabolisms produce fewer ATP (~2) per molecule of glucose processed than heterotrophic respirers (~32–38 ATP). While aerobes excel at ATP generation, they are often less efficient than anaerobes at processes that compete with ATP generation for cellular resources. This perspective highlights how anaerobic adaptations are advantageous for synthetic biology and biomanufacturing applications through the engineering of microbial cell factories. We further highlight emerging applications of anaerobic bioprocessing, including the use of anaerobic metabolisms for lignocellulosic bioprocessing, human and environmental health, and value-added bioproduction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Machine learning based approach to predict ductile damage model parameters for polycrystalline metals

Damage models for ductile materials typically need to be parameterized, often with the appropriate parameters changing for a given material depending on the loading conditions. This can make parameterizing these models computationally expensive, since an inverse problem must be solved for each loading condition. Using standard inverse modeling techniques typically requires hundreds or thousands of high-fidelity computer simulations to estimate the optimal parameters. Additionally, the time of a human expert is required to set up the inverse model. Machine learning has recently emerged as an alternative approach to inverse modeling in these settings, where the machine learning model is trained in an offline manner and new parameters can be quickly generated on the fly, after training is complete. Here, this work utilizes such a workflow to enable the rapid parameterization of a ductile damage model called TEPLA with a machine learning inverse model. The machine learning model can efficiently estimate the model parameters much faster, as compared to previously employed methods, such as Bayesian calibration. The results demonstrate good accuracy on a synthetic test dataset and is validated against experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Stochastic AC optimal power flow: A data-driven approach

There is an emerging need for efficient solutions to stochastic AC Optimal Power Flow (AC-OPF) to ensure optimal and reliable grid operations in the presence of increasing demand and generation uncertainty. Herein this paper presents a highly scalable data-driven algorithm for stochastic AC-OPF that has extremely low sample requirement. The novelty behind the algorithm’s performance involves an iterative scenario design approach that merges information regarding constraint violations in the system with data-driven sparse regression. Compared to conventional methods with random scenario sampling, our approach is able to provide feasible operating points for realistic systems with much lower sample requirements. Furthermore, multiple sub-tasks in our approach can be easily paralleled and based on historical data to enhance its performance and application. We demonstrate the computational improvements of our approach through simulations on different test cases in the IEEE PES PGLib-OPF benchmark library.

42 ENGINEERING↗
DOE OSTI2024

Discovery of a Peptoid-Based Nanoparticle Platform for Therapeutic mRNA Delivery via Diverse Library Clustering and Structural Parametrization

Nanoparticle-mediated mRNA delivery has emerged as a promising therapeutic modality, but its growth is still limited by the discovery and optimization of effective and well-tolerated delivery strategies. Lipid nanoparticles containing charged or ionizable lipids are an emerging standard for in vivo mRNA delivery, so creating facile, tunable strategies to synthesize these key lipid-like molecules is essential to advance the field. Here, we generate a library of N-substituted glycine oligomers, peptoids, and undertake a multistage down-selection process to identify lead candidate peptoids as the ionizable component in our Nutshell nanoparticle platform. First, we identify a promising peptoid structural motif by clustering a library of >200 molecules based on predicted physical properties and evaluate members of each cluster for reporter gene expression in vivo. Then, the lead peptoid motif is optimized using design of experiments methodology to explore variations on the charged and lipophilic portions of the peptoid, facilitating the discovery of trends between structural elements and nanoparticle properties. We further demonstrate that peptoid-based Nutshells leads to expression of therapeutically relevant levels of an anti-respiratory syncytial virus antibody in mice with minimal tolerability concerns or induced immune responses compared to benchmark ionizable lipid, DLin-MC3-DMA. Through this work, we present peptoid-based nanoparticles as a tunable delivery platform that can be optimized toward a range of therapeutic programs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Identification of Solid-Electrolyte Interphase Species by Joint Characterization of Li-Ion Battery Chemistry by Mass Spectrometry and Electrochemical Reaction Networks

The formation and stability of the solid-electrolyte interphase (SEI) play central roles in determining the long-term performance and safety of modern electrochemical energy storage systems. Despite decades of research, the SEI’s heterogeneous, dynamic, and multiphase nature has defied comprehensive molecular-level characterization, creating a critical knowledge gap that limits rational battery design. In this work, we introduce a computational−experimental framework that integrates high-throughput quantum chemistry calculations, data-driven electrochemical reaction networks (eCRNs), stochastic algorithms, and laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (LDI-FTICR-MS) to unravel SEI formation in carbonatebased electrolytes without imposing predefined mechanisms. We constructed the most comprehensive eCRN to date, spanning over 10,000 species and 209 million reactions. Through stochastic network analysis, we successfully recovered 27 species that were previously reported in the literature and predicted 28 novel SEI species nearly doubling our scientific knowledge in this area. Each new species was rigorously confirmed through advanced mass spectral analysis of its distinct molecular and isotopic signatures. We kinetically refined the formation pathways for a select set of both previously reported and novel SEI products, revealing kinetically feasible elementary reaction mechanisms with activation barriers below 1 eV. This computational−experimental approach deepens our molecular-level understanding of SEI chemistry by resolving which species form and through which decomposition mechanisms they emerge. Such knowledge provides the foundation necessary to connect electrolyte composition to the resulting SEI components, a critical step toward a more informed electrolyte development in next-generation lithium-based batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Macroscopic weavable fibers of carbon nanotubes with giant thermoelectric power factor

Low-dimensional materials have recently attracted much interest as thermoelectric materials because of their charge carrier confinement leading to thermoelectric performance enhancement. Carbon nanotubes are promising candidates because of their one-dimensionality in addition to their unique advantages such as flexibility and light weight. However, preserving the large power factor of individual carbon nanotubes in macroscopic assemblies has been challenging, primarily due to poor sample morphology and a lack of proper Fermi energy tuning. Here, we report an ultrahigh value of power factor (14± 5 mW m -1 K -2 ) for macroscopic weavable fibers of aligned carbon nanotubes with ultrahigh electrical and thermal conductivity. The observed giant power factor originates from the ultrahigh electrical conductivity achieved through excellent sample morphology, combined with an enhanced Seebeck coefficient through Fermi energy tuning. We fabricate a textile thermoelectric generator based on these carbon nanotube fibers, which demonstrates high thermoelectric performance, weavability, and scalability. The giant power factor we observe make these fibers strong candidates for the emerging field of thermoelectric active cooling, which requires a large thermoelectric power factor and a large thermal conductivity at the same time.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Probing many-body localization on a noisy quantum computer

A disordered quantum system of interacting particles exhibits localized behavior when the disorder is large compared to the interaction strength. Studying this phenomenon on a quantum computer with no, or limited, error correction is challenging because even weak coupling to a thermal environment destroys most signatures of localization. Fortunately, spectral functions of local operators are known to contain features that can survive the presence of noise. In these spectra, discrete peaks and a soft gap at low frequencies compared to the thermal phase indicate localization. Here, we present the computation of spectral functions on a trapped-ion quantum computer for a one-dimensional Heisenberg model with disorder. Further, we design an error-mitigation technique which is effective at removing the noise from the measurement allowing clear signatures of localization to emerge as the disorder increases. Furthermore, we show that spectral functions can serve as a robust and scalable diagnostic of many-body localization on current and future generations of quantum computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗