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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Formation of Disordered Cocontinuous Phases by Randomly Linked Star Copolymers

Cocontinuous polymeric nanostructures have garnered significant interest due to their ability to combine different properties of two separate polymer domains. Randomly linked copolymer networks have proven to be especially robust for formation of disordered cocontinuous phases across wide composition ranges (≈30 wt % or more). While theoretical treatments of microphase-separated networks have focused primarily on the role of random elastic forces imposed on the self-assembled nanostructures by virtue of the network architecture, experimental studies seeking to disentangle these contributions from other potential effects, such as dispersity in preferred interfacial curvatures, have been scarce. To provide insight into this matter, we here study the self-assembly of randomly linked star copolymers (RSCs), constructed by linking premade polymer arms of polystyrene (PS) and poly(d,l-lactide) (PLA) using 3, 4, and 6-functional connectors. This architecture yields similar distributions of preferred curvature as networks made using corresponding difunctional strands, but lacks the elastic forces imposed by a network architecture. Gravimetry and small-angle X-ray scattering, coupled with scanning electron microscopy, were performed to identify the percolation of PS/PLA RSCs. Remarkably, the 4-arm RSC system exhibited a disordered cocontinuous window of ≈25 wt %, indicating that dispersity in preferred curvature can in some cases be sufficient to robustly drive formation of this morphology. However, the other RSC architectures showed smaller cocontinuous ranges, which we interpret in terms of the influence of homopolymer stars in the 3-arm case and the narrower distribution of preferred interfacial curvatures in the 6-arm case. Finally, thin layers of interconnected porous PS were achieved by solution-processing, suggesting that RSCs have the potential to serve as a robust and easily processable cocontinuous polymeric nanomaterials in both bulk and membrane geometries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Magnetized directly-driven ICF capsules: increased instability growth from non-uniform laser drive

Simulations anticipate increased perturbation growth from non-uniform laser heating for magnetized direct-drive implosions. At the capsule pole, where the magnetic field is normal to the ablator surface, the field remains in the conduction zone and suppresses non-radial thermal conduction; in unmagnetized implosions this non-radial heat-flow is crucial in mitigating laser heating imbalances. Single-mode simulations show the magnetic field particularly amplifying short wavelength perturbations, whose behavior is dominated by thermal conduction. The most unstable wavelength can also become shorter. 3D multi-mode simulations of the capsule pole reinforce these findings, with increased perturbation growth anticipated across a wide range of scales. Finally, the results indicate that high-gain spherical direct-drive implosions require greater constraints on the laser heating uniformity when magnetized.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Longwave infrared (6.6–11.4 µm) dual-comb spectroscopy with 240,000 comb-mode-resolved data points at video rate

Using sub-3-cycle pulses from mode-locked Cr:ZnS lasers at λ ≈ 2.4 µm as a driving source, we performed high-resolution dual-frequency-comb spectroscopy in the longwave infrared (LWIR) range. A duo of highly coherent broadband (6.6–11.4 µm) frequency combs were produced via intrapulse difference frequency generation in zinc germanium phosphide (ZGP) crystals. Fast (up to 0.1 s per spectrum) acquisition of 240,000 comb-mode-resolved data points, spaced by 80 MHz and referenced to a Rb clock, was demonstrated, resulting in metrology grade molecular spectra of N 2 O (nitrous oxide) and CH 3 OH (methane). The key to high-speed massive spectral data acquisition was low intensity and phase noise of the LWIR combs and high (7.5%) downconversion efficiency, resulting in a LWIR power of 300 mW for each comb.

Vasilyev, Sergey (ORCID:0000000225203547)↗
DOE OSTI2023

Time-dependent density-functional-theory calculations of the nonlocal electron stopping range for inertial confinement fusion applications

Nonlocal electron transport is important for understanding laser-target coupling for laser-direct-drive (LDD) inertial confinement fusion (ICF) simulations. Current models for the nonlocal electron mean free path in radiation-hydrodynamic codes are based on plasma-physics models developed decades ago; improvements are needed to accurately predict the electron conduction in LDD simulations of ICF target implosions. Here we utilized time-dependent density functional theory (TD-DFT) to calculate the electron stopping power (SP) in the so-called conduction-zone plasmas of polystyrene in a wide range of densities and temperatures relevant to LDD. Compared with the modified Lee-More model, the TD-DFT calculations indicated a lower SP and a higher stopping range for nonlocal electrons. We fit these electron SP calculations to obtain a global analytical model for the electron stopping range as a function of plasma conditions and the nonlocal electron kinetic energy. This model was implemented in the one-dimensional radiation-hydrodynamic code LILAC to perform simulations of LDD ICF implosions, which are further compared with simulations by the standard modified Lee-More model. In conclusion, results from these integrated simulations are discussed in terms of the implications of this TD-DFT-based mean-free-path model to ICF simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Separation of K + and Bi 3+ displacements in a Pb-free, monoclinic piezoelectric at the morphotropic phase boundary

The best piezoelectric properties of any perovskite oxide known are found in the solid solution of the relaxor Pb (Mg 1/3 Nb 2/3 )O 3 and ferroelectric PbTiO 3 . Despite its impressive properties, this system has limited analogy. We present the compositional exploration of the Pb-free analogue (1-x)(K 1/2 Bi 1/2 )(Mg 1/3 Nb 2/3 )O 3 -x(K 1/2 Bi 1/2 )TiO 3 (KBMN-KBT). We locate the morphotropic phase boundary between x = 0.86 and 0.88 changing from Cm to Pm symmetry and the optimally performing composition at x = 0.88. We report a piezoelectric figure of merit (d 33 *) of 192 pm V —1 from strain measurements. Diffraction methods reveal disordered displacements of K + and Bi 3+ which persist from the KBMN endmember through multiple changes in symmetry. Rearrangement of the Bi 3+ displacements along the uncommon [011] c direction drives the physical response. Ferroelectric, dielectric, and piezoresponse force microscopy are used to study the progression of physical properties through the MPB and attribute the mechanism to a polarization rotation. Taking account for local, short-range, and average structural features yield a balanced perspective on the structure and properties of this system, isolating the driving force within this system to the Bi 3+ bonding configuration. This work yields a strong analogy to the Pb-based analogue, and provides strategies for further optimization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Electric Drive Technology Trends, Challenges, and Opportunities for Future Electric Vehicles

The transition to electric road transport technologies requires electric traction drive systems to offer improved performances and capabilities, such as fuel efficiency (in terms of MPGe, i.e., miles per gallon of gasoline-equivalent), extended range, and fast-charging options. The enhanced electrification and transformed mobility are translating to a demand for higher power and more efficient electric traction drive systems that lead to better fuel economy for a given battery charge. To accelerate the mass-market adoption of electrified transportation, the U.S. Department of Energy (DOE), in collaboration with the automotive industry, has announced the technical targets for light-duty electric vehicles (EVs) for 2025. This article discusses the electric drive technology trends for passenger electric and hybrid EVs with commercially available solutions in terms of materials, electric machine and inverter designs, maximum speed, component cooling, power density, and performance. Additionally, the emerging materials and technologies for power electronics and electric motors are presented, identifying the challenges and opportunities for even more aggressive designs to meet the need for next-generation EVs. Some innovative drive and motor designs with the potential to meet the DOE 2025 targets are also discussed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Optimized Gear Selection to Maximize Energy Savings in Electric Traction Drives for Medium and Heavy Duty Vehicles

Multi‑gear transmission systems are commonly used in electric traction drives for medium and heavy‑duty vehicles, while most passenger‑vehicle electric drivetrains rely on a single fixed ratio to reduce cost, weight, and complexity. Using multiple gear ratios can enable downsizing of the motor and inverter while still meeting performance requirements. Additionally, appropriately chosen ratios allow the motor to operate more frequently in high‑efficiency regions, improving overall energy usage and reducing operating costs over the drive cycle. This paper presents a systematic approach for selecting optimal gear ratios for electric drive systems. A neural‑network model is first developed to represent motor losses across the full torque–speed range using data generated from finite element analysis. This model enables fast, accurate evaluation of motor efficiency under varying operating conditions. A genetic‑algorithm‑based optimization framework is then applied to identify gear ratios that maximize energy cost savings over the drive cycle, with the resulting optimal ratios stored for real‑time implementation.

Gadiyar, Nishanth [ORNL] (ORCID:0000000348267524)↗
DOE OSTI2021

Reconfiguration of Amorphous Complex Oxides: A Route to a Broad Range of Assembly Phenomena, Hybrid Materials, and Novel Functionalities

This work demonstrate that reconfiguration of amorphous oxide layers drives the assembly of oxide-based and freestanding nanomembranes into 3D structures with a radius of a few hundred nanometers. Reconfiguration-driven assembly is a versatile approach to impart large strains and strain gradients in a broad palette of complex oxides. This capability allows for manipulating and enhancing ferroelectricity, flexoelectricity, piezoelectricity, superconductivity, and ferromagnetism in complex oxides. Moreover, by the approach presented in this work, strain-engineered oxides are obtained in the form of 3D structures that can be fabricated in parallel on any substrate, including large-area and single crystalline semiconductor substrates. This approach will create a vast expanse of possibilities to investigate and leverage strain-tunable effects in amorphous, poly-crystalline, and single-crystalline complex oxides. Reconfiguration-driven assembly of NMs also allows combining different materials in a radial geometry and through scalable processes. For example, radial superlattices of Si (or GaAs) and various complex oxides or alternating layers of different complex oxides (e.g., SrTiO 3 and LaAlO 3 ) could be fabricated by release and heating of bilayer NMs. Here, a broad palette of electronic band structures and spin–orbit interactions could then be obtained by tailoring the curvature of the self-assembled NMs and the materials that the heterostructure comprises.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Decision support for United States—Canada energy integration is impaired by fragmentary environmental and electricity system modeling capacity

The renewable energy transition is leading to increased electricity trade between the United States and Canada, with Canadian hydropower providing firm lower-carbon power and buffering variability of wind and solar generation in the U.S. However, long-term power purchase agreements and transborder transmission projects are controversial, with two of four proposed transmission lines between Quebec, Canada and the northeast U.S. cancelled since 2018. Here, we argue that controversies are exacerbated by a lack of open-source data and tools to understand tradeoffs of new hydropower generation and transmission infrastructure in comparison to alternatives. This gap includes impacts that incremental transmission and generation projects have on the economics of the entire system, for example, how new transmission projects affect exports to existing markets or incentivize new generation. We identify priority areas for data synthesis and model development, such as integrating linked hydropower and hydrologic interactions in energy system models and openly releasing (by utilities) or back-calculating (by researchers) hydropower generation and operational parameters. Publicly available environmental (e.g. streamflow, precipitation) and techno-economic (e.g. costs, reservoir size,) data can be used to parameterize freely usable and extensible models. Existing models have been calibrated with operational data from Canadian utilities that are not publicly available, limiting the range of scientific and commercial questions these tools have been used to answer and the range of parties that have been involved. Studies conducted using highly resolved, national-scale public data exist in other countries, notably, the United States, and demonstrate how greater transparency and extensibility can drive industry action. Improved data availability in Canada could facilitate approaches that (1) increase participation in decarbonization planning by a broader range of actors; (2) allow independent characterizations of environmental, health, and economic outcomes of interest to the public; and (3) identify decarbonization pathways consistent with community values.

13 HYDRO ENERGY↗
DOE OSTI2025

Hydrophobins from Aspergillus Mediate Fungal Interactions with Microplastics

Microplastics cause negative environmental consequences such as the release of toxic additive leachates, increased greenhouse gas emissions during degradation, and threaten food chains . Microplastic particles are known to serve as a vector for transport of microbes (fungi and bacteria) to new environments, threatening biodiversity. Robust biofilm formation makes fungi a candidate to collect and remediate environmental microplastics. However, fungal-microplastic colonization mechanisms have yet to be explored. In this work, we aim to understand which fungal molecules mediate microplastics binding. We examine common fungal genus Aspergillus , which we found binds microplastics tightly, removing particles from suspension. Upon inoculation of Aspergilli with microplastics particles, up to 3.85 ± 1.48 g of microplastics were flocculated per gram of dry fungal biomass; this phenomenon was observed across various plastics ranging in size from 0.05 to 5 mm. Gene knockouts revealed that hydrophobins drive microplastic-fungi binding, evidenced by a decrease in flocculation relative to wild-type Aspergillus fumigatus. Moreover, purified hydrophobins flocculated microplastics independently of the fungus, validating their ability to bind to microplastics. Furthermore, our work elucidates a role for hydrophobins in fungal colonization of microplastics and highlights a target for mitigating the harm of microplastics through engineered fungal-microplastic interactions.

biofilms↗
DOE OSTI2021

Nonlinear Optical Microscopy with Ultralow Quantum Light

Nonlinear optical (NLO) microscopy relies on multiple light–matter interactions to provide unique contrast mechanisms and imaging capabilities that are inaccessible to traditional linear optical imaging approaches, making them versatile tools to understand a wide range of complex systems. However, the strong excitation fields that are necessary to drive higher-order optical processes efficiently are often responsible for photobleaching, photodegradation, and interruption in many systems of interest. This is especially true for imaging living biological samples over prolonged periods of time or in accessing intrinsic dynamics of electronic excited-state processes in spatially heterogeneous materials. This perspective outlines some of the key limitations of two NLO imaging modalities implemented in our lab and highlights the unique potential afforded by the quantum properties of light, especially entangled two-photon absorption based NLO spectroscopy and microscopy. Here, we further review some of the recent exciting advances in this emerging filed and highlight some major challenges facing the realization of quantum-light-enabled NLO imaging modalities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Estimating Interplanetary Magnetic Field Conditions at Mercury's Orbit From MESSENGER Magnetosheath Observations Using a Feedforward Neural Network

Abstract Mercury's small magnetosphere is embedded in the dynamic and intense solar wind environment characteristic of the inner heliosphere. Both the magnitude and orientation of the interplanetary magnetic field (IMF) significantly influence the solar wind‐magnetospheric interaction at Mercury, driving phenomena such as magnetic reconnection. The MErcury Surface, Space Environment, Geochemistry and Ranging (MESSENGER) spacecraft provided in‐situ magnetic field measurements of the solar wind, the magnetosheath, and the magnetosphere along each orbit. However, it is a challenge to directly assess the IMF's impact on Mercury's plasma environment due to the temporal separation between observations within the solar wind and the magnetosphere, especially in the absence of an upstream monitor. Here, we present a feedforward neural network (FNN) trained on a subset of magnetosheath observations to estimate the strength and orientation of the IMF upstream of the bow shock. Utilizing magnetosheath magnetic field, cylindrical spatial coordinates, and heliocentric distance measurements, the FNN predicts upstream IMF conditions with an score of 0.70 and mean averaged error of 5.3 nT, thereby greatly decreasing the temporal separation between IMF estimates and magnetospheric measurements throughout the MESSENGER mission. This approach yields IMF estimates for all magnetosheath data measured by MESSENGER, providing a useful tool for future investigations of the IMF impact on Mercury's magnetosphere. This method will be integrable with the dual‐spacecraft BepiColombo magnetosheath measurements, providing useful estimates of upstream IMF conditions particularly during the extended periods in which neither spacecraft sample the solar wind. Our results demonstrate the utility of machine learning techniques on advancing space science research.

Bowers, Charles F.↗
DOE OSTI2023

Structural inference of networked dynamical systems with universal differential equations

Networked dynamical systems are common throughout science in engineering; e.g., biological networks, reaction networks, power systems, and the like. For many such systems, nonlinearity drives populations of identical (or near-identical) units to exhibit a wide range of nontrivial behaviors, such as the emergence of coherent structures (e.g., waves and patterns) or otherwise notable dynamics (e.g., synchrony and chaos). Here, we seek to infer (i) the intrinsic physics of a base unit of a population, (ii) the underlying graphical structure shared between units, and (iii) the coupling physics of a given networked dynamical system given observations of nodal states. These tasks are formulated around the notion of the Universal Differential Equation, whereby unknown dynamical systems can be approximated with neural networks, mathematical terms known a priori (albeit with unknown parameterizations), or combinations of the two. We demonstrate the value of these inference tasks by investigating not only future state predictions but also the inference of system behavior on varied network topologies. The effectiveness and utility of these methods are shown with their application to canonical networked nonlinear coupled oscillators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Exact Landau Level Description of Geometry and Interaction in a Flatband

Flatbands appear in many condensed matter systems, including the two-dimensional electron gas in a high magnetic field, correlated materials, and moiré heterostructures. They are characterized by intrinsic geometric properties such as the Berry curvature and Fubini-Study metric. The influence of the band geometry on electron-electron interaction is difficult to understand analytically because the geometry is in general nonuniform in momentum space. In this work, we study the topological flatband of Chern number C = 1 with a momentum-dependent but positive definite Berry curvature that fluctuates in sync with Fubini-Study metric. We derive an exact correspondence between such ideal flatbands and Landau levels and show that the band geometry fluctuation gives rise to a new type of interaction in the corresponding Landau levels that depends on the center of mass of two particles. We characterize such interactions by generalizing the usual Haldane pseudopotentials. This mapping gives exact zero-energy ground states for short-ranged repulsive generalized pseudopotentials in flatbands, in analogy to fractional quantum Hall systems. Driving the center-of-mass interactions beyond the repulsive regime leads to a dramatic reconstruction of the ground states towards gapless phases. The generalized pseudopotential could be a useful basis for future numerical studies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Study of electron-induced chemical transformations in polymers

In extreme ultraviolet (EUV) photoresist exposure, the primary and secondary electrons drive chemistry rather than the EUV photons themselves. These electrons have a wide range of energies below approximately 80 eV, which are capable of complex network of reactions during exposure. To better understand the ability of electrons of different energies within the EUV primary and secondary electron range, we want to characterize and compare the chemistry induced in pure polymer films by direct exposure to electrons. Thin films of poly(tert-butyl methacrylate), poly(methyl methacrylate), and poly(4-hydroxystyrene) were exposed to a 20 to 80 eV electron beam. Outgassing during exposure was characterized in-situ using a quadrupole residual gas analyzer. The thickness changes were measured using ellipsometry and chemical bond structure data were collected using Fourier-transform infrared spectroscopy (FTIR) after exposure to compare different exposure conditions. Poly(4-hydroxystyrene) demonstrated stability during electron exposures. Exposures of the other two materials led to outgassing of protecting groups, the intensity of which decayed in time. Outgassing, FTIR, and thickness loss data exhibited approximately linear relationships to each other.

Mueller, Maximillian↗
DOE OSTI2023

Completely Positive Map for Noisy Driven Quantum Systems Derived by Keldysh Expansion

Accurate modeling of decoherence errors in quantum processors is crucial for analyzing and improving gate fidelities. To increase the accuracy beyond that of the Lindblad dynamical map, several generalizations have been proposed, and the exploration of simpler and more systematic frameworks is still ongoing. In this paper, we introduce a decoherence model based on the Keldysh formalism. This formalism allows us to include non-periodic drives and correlated quantum noise in our model. In addition to its wide range of applications, our method is also numerically simple, and yields a CPTP map. These features allow us to integrate the Keldysh map with quantum-optimal-control techniques. We demonstrate that this strategy generates pulses that mitigate correlated quantum noise in qubit state-transfer and gate operations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Diffraction of radio-frequency waves by plasma turbulence in the edge of a tokamak

The Mie-Lorenz-Debye theory of scattering of radio frequency waves (RF) by filamentary structures in the edge of a tokamak plasma has been established in prior publications. These results have been verified. Theory and computations show that RF can be reflected, refracted, and diffracted by turbulence. Furthermore, the filamentary structures lead to side scattering of waves and excitation of wave modes different from the launched RF. It is important to quantify the overall effect of turbulence on the propagation of RF since efficiency of heating and current drive by RF waves depends upon the wave characteristics. The commonly used RF ranges vary from the low frequency ion-cyclotron (IC) waves, to medium frequency lower-hybrid (LH) waves, to high-frequency electron cyclotron (EC) waves with wavelengths respectively, large, comparable, or smaller than the radial dimensions of the filaments. Currently, we discuss the scattering as well as the forces exerted by different RF in the edge plasma. Also, we present a code for 3D full wave scattering analysis of arbitrary tensor permittivity and plasma density profiles. The study is applicable to ITER-like plasmas, as well as to plasmas in medium sized tokamaks such as TCV, ASDEX-U and DIII-D and high field concepts like SPARC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Identifying and tracking bubbles and drops in simulations: A toolbox for obtaining sizes, lineages, and breakup and coalescence statistics

Knowledge of bubble and drop size distributions in two-phase flows is important for characterizing a wide range of phenomena, including combustor ignition, sonar communication, and cloud formation. The physical mechanisms driving the background flow also drive the time evolution of these distributions. Accurate and robust identification and tracking algorithms for the dispersed phase are necessary to reliably measure this evolution and thereby quantify the underlying mechanisms in interface-resolving flow simulations. The identification of individual bubbles and drops traditionally relies on an algorithm used to identify connected regions. This traditional algorithm can be sensitive to the presence of spurious structures. A cost-effective refinement is proposed to maximize volume accuracy while minimizing the identification of spurious bubbles and drops. An accurate identification scheme is crucial for distinguishing bubble and drop pairs with large size ratios. The identified bubbles and drops need to be tracked in time to obtain breakup and coalescence statistics that characterize the evolution of the size distribution, including breakup and coalescence frequencies, and the probability distributions of parent and child bubble and drop sizes. An algorithm based on mass conservation is proposed to construct bubble and drop lineages using simulation snapshots that are not necessarily from consecutive time steps. These lineages are then used to detect breakup and coalescence events, and obtain the desired statistics. Accurate identification of large-size-ratio bubble and drop pairs enables accurate detection of breakup and coalescence events over a large size range. Accurate detection of successive breakup and coalescence events requires that the snapshot interval be an order of magnitude smaller than the characteristic breakup and coalescence times to capture these successive events while minimizing the identification of repeated confounding events. Together, these algorithms serve as a toolbox for detailed analysis of two-phase simulations, and enable insights into the mechanisms behind bubble and drop formation and evolution in flows of practical importance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗