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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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DOE OSTI2022

Hidden Sectors from Multiple Line Bundles for the B−L$B-L$ MSSM

Abstract We give a formalism for constructing hidden sector bundles as extensions of sums of line bundles in heterotic M‐theory. Although this construction is generic, we present it within the context of the specific Schoen threefold that leads to the physically realistic MSSM model. We discuss the embedding of the line bundles, the existence of the extension bundle, and a number of necessary conditions for the resulting bundle to be slope‐stable and thus supersymmetric. An explicit example is presented, where two line bundles are embedded into the factor of the maximal subgroup of the hidden sector E 8 gauge group, and then enhanced to a non‐Abelian bundle by extension. For this example, there are in fact six inequivalent extension branches, significantly generalizing that space of solutions compared with hidden sectors constructed from a single line bundle.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Co-Assembly of Carbon Nanotube Porins into Biomimetic Peptoid Membranes

Robust and cost-effective membrane-based separations are essential to solving many global crises, such as the lack of clean water. Even though the current polymer-based membranes are widely used for separations, their performance and precision can be enhanced by using a biomimetic membrane architecture that consists of highly permeable and selective channels embedded in a universal membrane matrix. Researchers have shown that artificial water and ion channels, such as carbon nanotube porins (CNTPs), embedded in lipid membranes can deliver strong separation performance. However, their applications are limited by the relative fragility and low stability of the lipid matrix. In this work, we demonstrate that CNTPs can co-assemble into two-dimension (2D) peptoid membrane nanosheets, opening up a way to produce highly programmable synthetic membranes with superior crystallinity and robustness. A combination of molecular dynamics (MD) simulations, Raman spectroscopy, X-ray diffraction (XRD), and atomic force microscopy (AFM) measurements to verify the co-assembly of CNTP and peptoids are used and show that it does not disrupt peptoid monomer packing within the membrane. In conclusion, these results provide a new option for designing affordable artificial membranes and highly robust nanoporous solids.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fibers add flavor. Part II. 5d SCFTs, gauge theories, and dualities

In [1, 2] we proposed an approach based on graphs to characterize 5d superconformal field theories (SCFTs), which arise as compactifications of 6d $$ \mathcal{N} $$ N = (1 , 0) SCFTs. The graphs, so-called combined fiber diagrams (CFDs), are derived using the realization of 5d SCFTs via M-theory on a non-compact Calabi-Yau threefold with a canonical singularity. In this paper we complement this geometric approach by connecting the CFD of an SCFT to its weakly coupled gauge theory or quiver descriptions and demonstrate that the CFD as recovered from the gauge theory approach is consistent with that as determined by geometry. To each quiver description we also associate a graph, and the embedding of this graph into the CFD that is associated to an SCFT provides a systematic way to enumerate all possible consistent weakly coupled gauge theory descriptions of this SCFT. Furthermore, different embeddings of gauge theory graphs into a fixed CFD can give rise to new UV-dualities for which we provide evidence through an analysis of the prepotential, and which, for some examples, we substantiate by constructing the M-theory geometry in which the dual quiver descriptions are manifest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Axion domain walls, small instantons, and non-invertible symmetry breaking

Non-invertible global symmetry often predicts degeneracy in axion potentials and carries important information about the global form of the gauge group. When these symmetries are spontaneously broken they can lead to the formation of stable axion domain wall networks which support topological degrees of freedom on their worldvolume. Such non-invertible symmetries can be broken by embedding into appropriate larger UV gauge groups where small instanton contributions lift the vacuum degeneracy, and provide a possible solution to the domain wall problem. We explain these ideas in simple illustrative examples and then apply them to the Standard Model, whose gauge algebra and matter content are consistent with several possible global structures. Each possible global structure leads to different selection rules on the axion couplings, and various UV completions of the Standard Model lead to more specific relations. As a proof of principle, we also present an example of a UV embedding of the Standard Model which can solve the axion domain wall problem. The formation and annihilation of the long-lived axion domain walls can lead to observables, such as gravitational wave signals. Observing such signals, in combination with the axion coupling measurements, can provide valuable insight into the global structure of the Standard Model, as well as its UV completion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Janus on the brane

We present a non-supersymmetric deformation of probe branes describing conformal defects of codimension two in AdS/CFT. The worldvolume of the probe branes is deformed from AdS p × S 1 embedded in an AdS p+2 × M D–p–2 background to an embedding of Janus form, which uses an AdS p–1 slicing of AdS p and in which the brane bends along the slicing coordinate. In field theory terms this realizes conformal interfaces on codimension-two defects. We discuss these "Janus on the brane" solutions for AdS 3 × S 1 D3-branes in the AdS 5 × S 5 solution of Type IIB, realizing interfaces on surface defects in N = 4 SYM, and show that similar solutions exist for probe branes in AdS p+2 × S 9–p vacua of M-theory and in the AdS 6 × S 4 solution of massive Type IIA.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Trinification from E 6 symmetry breaking

In the context of E 6 Grand Unified Theories (GUTs), an intriguing possibility for symmetry breaking to the Standard Model (SM) group involves an intermediate stage characterized by either SU(3) × SU(3) × SU(3) (trinification) or SU(6) × SU(2). The more common choices of SU(5) and SO(10) GUT symmetry groups do not offer such breaking chains. We argue that the presence of a real (rank 2 tensor) representation 650 of E 6 in the scalar sector is the minimal and likely only reasonable possibility to obtain one of the novel intermediate stages. We analyze the renormalizable scalar potential of a single copy of the 650 and find vacuum solutions that support regularly embedded subgroups SU(3) × SU(3) × SU(3), SU(6) × SU(2), and SO(10) × U(1), as well as specially embedded subgroups F 4 and SU(3) × G 2 that do not contain the SM gauge symmetry. We show that for a suitable choice of parameters, each of the regular cases can be obtained as the lowest among the analyzed minima in the potential.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

A Study of Intermittent Turbulence in Stable Arctic Boundary Layers

Abstract Polar boundary layers are difficult to model due to the existence of intermittent turbulence within stable layers. Here we present a case study evaluation of coherent structures in a stable boundary layer observed during a series of flights with an uncrewed aircraft system (DataHawk2) on 19 October 2016 at Oliktok Point, Alaska as part of the ERASMUS (Evaluation of Routine Atmospheric Sounding Measurements using Unmanned Systems) field campaign. During a sequence of five flights over a nine-hour period, 57 profiles of atmospheric properties (0–400 m a.g.l) were collected. Turbulence was identified using derived Richardson Number, temperature structure function parameter, and turbulence kinetic energy dissipation. Throughout all flights on this strongly stable day, intermittent turbulence was observed. These turbulent layers showed well-mixed potential temperature profiles embedded within otherwise stable potential temperature profiles; often resulting in a characteristic staircase pattern. Turbulent layers ranged from 1 to 30 m deep, with most individual layers being 1–2 m deep. Vertical propagation velocities of layers in the lower atmosphere were on the order of a few cm s −1 , typical of non-convective environments. In different regions of the profile, turbulence was driven by a different balance of buoyancy and shear forces, with turbulence in the near surface environment driven by strong shear forces overcoming strong resistance to buoyancy, while turbulence in elevated layers characterized by weaker shear forces overcoming weaker resistance to buoyancy. We discuss the potential of such datasets for improving subgrid parameterizations of small-scale turbulence embedded within stable boundary layers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

EPR studies of ferredoxin in spinach and cyanobacterial thylakoids related to photosystem I-driven NADP + reduction

Photosynthetic light-dependent reactions occur in thylakoid membranes where embedded proteins capture light energy and convert it to chemical energy in the form of ATP and NADPH for use in carbon fixation. One of these integral membrane proteins is Photosystem I (PSI). PSI catalyzes light-driven transmembrane electron transfer from plastocyanin (Pc) to oxidized ferredoxin (Fd). Electrons from reduced Fd are used by the enzyme ferredoxin-NADP + reductase (FNR) for the reduction of NADP + to NADPH. Fd and Pc are both small soluble proteins whereas the larger FNR enzyme is associated with the membrane. To investigate electron shuttling between these diffusible and embedded proteins, thylakoid photoreduction of NADP + was studied. As isolated, both spinach and cyanobacterial thylakoids generate NADPH upon illumination without extraneous addition of Fd. These findings indicate that isolated thylakoids either (i) retain a “pool” of Fd which diffuses between PSI and membrane bound FNR or (ii) that a fraction of PSI is associated with Fd, with the membrane environment facilitating PSI-Fd-FNR interactions which enable multiple turnovers of the complex with a single Fd. To explore the functional association of Fd with PSI in thylakoids, electron paramagnetic resonance (EPR) spectroscopic methodologies were developed to distinguish the signals for the reduced Fe-S clusters of PSI and Fd. Temperature-dependent EPR studies show that the EPR signals of the terminal [4Fe-4S] cluster of PSI can be distinguished from the [2Fe-2S] cluster of Fd at > 30 K. At 50 K, the cw X-band EPR spectra of cyanobacterial and spinach thylakoids reduced with dithionite exhibit EPR signals of a [2Fe-2S] cluster with g-values g x = 2.05, g y = 1.96, and g z = 1.89, confirming that Fd is present in thylakoid preparations capable of NADP + photoreduction. Quantitation of the EPR signals of P 700 + and dithionite reduced Fd reveal that Fd is present at a ratio of ~ 1 Fd per PSI monomer in both spinach and cyanobacterial thylakoids. Light-driven electron transfer from PSI to Fd in thylakoids confirms Fd is functionally associated (< 0.4 Fd/PSI) with the acceptor end of PSI in isolated cyanobacterial thylakoids. Furthermore, these EPR experiments provide a benchmark for future spectroscopic characterization of Fd interactions involved in multistep relay of electrons following PSI charge separation in the context of photosynthetic thylakoid microenvironments.

Electron paramagnetic resonance↗
DOE OSTI2023

Solving larger maximum clique problems using parallel quantum annealing

Quantum annealing has the potential to find low energy solutions of NP-hard problems that can be expressed as quadratic unconstrained binary optimization problems. However, the hardware of the quantum annealer manufactured by D-Wave Systems, which we consider in this work, is sparsely connected and moderately sized (on the order of thousands of qubits), thus necessitating a minor-embedding of a logical problem onto the physical qubit hardware. The combination of relatively small hardware sizes and the necessity of a minor-embedding can mean that solving large optimization problems is not possible on current quantum annealers. In this research, we show that a hybrid approach combining parallel quantum annealing with graph decomposition allows one to solve larger optimization problem accurately. We apply the approach to the Maximum Clique problem on graphs with up to 120 nodes and 6395 edges.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Phenomenological Model of Nonlinear Dynamics and Deterministic Chaotic Gas Migration in Bentonite: Experimental Evidence and Diagnostic Parameters

Understanding gas migration in compacted clay materials, e.g., bentonite and claystone, is important for the design and performance assessment of an engineered barrier system of a radioactive waste repository system, as well as many practical applications. Existing field and laboratory data on gas migration processes in low-permeability clay materials demonstrate the complexity of flow and transport processes, including various types of instabilities, caused by nonlinear dynamics of coupled processes of liquid–gas exchange, dilation, fracturing, fracture healing, etc., which cannot be described by classical models of fluid dynamics in porous media. We here show that the complexity of gas migration processes can be explained using a phenomenological concept of nonlinear dynamics and deterministic chaos theory. To do so, we analyzed gas pressure and gas influx (i.e., input) and outflux (i.e., output), recorded during the gas injection experiment in the compact Mx80-D bentonite sample, and calculated a set of the diagnostic parameters of nonlinear dynamics and chaos, such a global embedding dimension, a correlation dimension, an information dimension, and a spectrum of Lyapunov exponents, as well as plotted 2D and 3D pseudo-phase-space strange attractors, based on the univariate influx and outflux time series data. These results indicate the presence of phenomena of low-dimensional deterministic chaotic behavior of gas migration in bentonite. In particular, during the onset of gas influx in the bentonite core, before the breakthrough, the development of gas flow pathways is characterized by the process of chaotic gas diffusion. After the breakthrough, with inlet-to-outlet movement of gas, the prevailing process is chaotic advection. During the final phase of the experiment, with no influx to the sample, the relaxation pattern of gas outflux is resumed back to a process of chaotic diffusion. The types of data analysis and a proposed phenomenological model can be used to establish the basic principles of experimental data-gathering, modeling predictions, and a research design.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Decomposition Algorithms for Solving NP-hard Problems on a Quantum Annealer

NP-hard problems such as the maximum clique or minimum vertex cover problems, two of Karp’s 21 NP-hard problems, have several applications in computational chemistry, biochemistry and computer network security. Adiabatic quantum annealers can search for the optimum value of such NP-hard optimization problems, given the problem can be embedded on their hardware. However, this is often not possible due to certain limitations of the hardware connectivity structure of the annealer. This paper studies a general framework for a decomposition algorithm for NP-hard graph problems aiming to identify an optimal set of vertices. Our generic algorithm allows us to recursively divide an instance until the generated subproblems can be embedded on the quantum annealer hardware and subsequently solved. Furthermore, the framework is applied to the maximum clique and minimum vertex cover problems, and we propose several pruning and reduction techniques to speed up the recursive decomposition. The performance of both algorithms is assessed in a detailed simulation study.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Direct NeTS sampling of nuclear graphite $S(α, β, T)$ in Serpent

For advanced reactor applications, Neural Thermal Scattering (NeTS) modules were developed to predict the thermal scattering law (TSL or $S(α, β, T)$) of a nuclear graphite neutron moderator. NeTS are multi-layer, feedforward artificial neural networks, which act as universal function approximators designed for TSL datasets. In this case, a 4-layer neural network with 164 neurons per layer is trained using FLASSH evaluated data in PyTorch and serialized as a torchscript dictionary to predict $S(α, β, T)$ on-the-fly. Relative, absolute and maximum percent deviations of NeTS from File 7 data generated using the FLASSH code are on the order of 0.01%, 0.1% and 1%, respectively, with low inference latencies of 0.000172 s per $S(α, β, T)$ at a given temperature. Capturing the full dimensionality of possible inelastic neutron-lattice interactions, NeTS functionality is embedded in the Serpent Monte Carlo code, where $S(α, β, T)_{NeTS}$ sampling is conducted on-the-fly and compared to ACE look-up-tables for predicting TREAT criticality. k-eff differences between sampling algorithms of 6 pcm are observed and are within the order of Monte Carlo uncertainty. Compared to discrete and continuous-energy ACE files (30 MB and 131 MB per temperature), the NeTS format is on the order of 200–300 kB for a continuous-temperature, interpolation-free representation of $S(α, β, T)$ and cross sections. NeTS-in-Serpent runtimes comparable with ACE look-up tables are achieved by scaling NeTS for high performance computing architectures with hybrid OpenMP + MPI parallelization. This work validates a novel, self-contained reactor physics framework for predictive cross sections, and demonstrates a general methodology for embedding modern machine learning libraries within existing neutronic analysis frameworks.

Nuclear Criticality Safety Program (NCSP)↗
DOE OSTI2019

Gravastars in (3+1) dimensions admitting Karmarkar condition

Highlights: • Model of Gravastar in (3+1) dimensions is studied under GR. • Karmarkar condition of Embedding class 1 has been incorporated. • The class 1 condition provides an exact solution of three regions of gravastar. • Surface redshift confirms the stability of the model which is non-singular. - Abstract: The development of gravastar model by Mazur and Mottola (2004) is one of the most acceptable alternatives of conventional classical black hole. They have studied phase transition of the collapsing stellar objects at low temperature near event horizon which leads to the condensate phase, i.e. Bose–Einstein condensation. In the present study we have obtained a unique solution of this gravastar model under Einstein’s GR in (3+1) dimensions by incorporating the Karmarkar condition for embedding class 1. The most important motive of this work is to find an exact solution of the shell without taking the thin shell approximation. We have obtained singularity free finite solutions for the interior of the gravastar.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

High spatial resolution temperature profile measurements of solid-oxide fuel cells

Temperature gradients resulting from local electrochemical reactions, current distribution and geometry of gas flow channels in solid oxide fuel cells (SOFCs) create thermal stresses, localized thermophysical property gradients and uneven property evolution, contributing to SOFC degradation. This paper presents a new method to perform temperature measurements (up to 800°C) at high spatial resolutions to monitor the operation of SOFCs. Using femtosecond laser irradiation, distributed fiber sensors were hardened for high temperature environment applications. Distributed fiber sensors were embedded in interconnected plates using an additive manufacturing method to perform temperature measurements with 4-mm spatial resolution during the operation of a planar fuel cell. The measurement revealed the impact of various H 2 fuel concentrations and current loads have on temperature profiles of the SOFC tested. Temperature variation on the anode side was found to be less than 5°C, and 3°C on the cathode side. The measurements were compared to results from a multiphysics fuel cell performance model simulating similar conditions. These simulations predicted similar temperature gradients, indicating the experimental data obtained is reasonable. The model also predicts that the effect of the embedded sensor has on the local temperature will be minimal and that the gradient of temperature in the gas channels will be captured despite the separation between the sensor and the gas flow. Finally, the high spatial resolution data harnessed by these distributed fiber sensors provides experimental support for model-based design and optimization to improve the operational efficiency and longevity of solid oxide fuel cells and fuel cell assemblies.

25 ENERGY STORAGE↗
DOE OSTI2020

Comparison of electro-thermal performance of advanced cooling techniques for electric vehicle motors

Permanent magnet synchronous motors are commonly used in the powertrain of electric vehicles because of their high power and torque densities. Attempts to increase power and torque densities beyond the state-of-the-art often suffer from thermal limitations of the adopted winding-wire insulation class. In this paper, overall effectiveness of four different cooling technologies, namely conventional stator jacket cooling, embedded circular and rectangular cooling channels within stator core, and direct winding heat exchangers have been studied numerically. Here, by realizing temperature dependent magnetic and material properties, winding and core losses, a two-way coupling algorithm has been utilized to study the detailed electro-magnetic and thermal performance of BMW i3 motor with aforementioned cooling techniques. The numerical results illustrated that the direct winding heat exchangers approach provides better electro-thermal performance in comparison to the other cooling techniques analyzed. On the contrary, embedded rectangular and circular channel in stator core adversely affect the electro-magnetic performance and overall efficiency of the motor, despite their superior thermal performance compared to the jacket cooling

42 ENGINEERING↗
DOE OSTI2021

Measurement of 227 Ac impurity in 225 Ac using decay energy spectroscopy

225 Ac is a valuable medical radionuclide for targeted $\alpha$ therapy, but 227 Ac is an undesirable byproduct of an accelerator-based synthesis method under investigation. Sufficient detector sensitivity is critical for quantifying the trace impurity of 227 Ac, with the 227 Ac/ 225 Ac activity ratio predicted to be approximately 0.15% by end-of-bombardment (EOB). Superconducting transition edge sensor (TES) microcalorimeters offer high resolution energy spectroscopy using the normal-to-superconducting phase transition to measure small changes in temperature. By embedding 225 Ac production samples in a gold foil thermally coupled to a TES microcalorimeter we can measure the decay energies of the radionuclides embedded with high resolution and 100% detection efficiency. This technique, known as decay energy spectroscopy (DES), collapses several peaks from $\alpha$ decays into single Q-value peaks. In practice there are more complex factors in the interpretation of data using DES, which we will discuss in this paper. Using this technique we measured the EOB 227 Ac impurity to be (0.142 ± 0.005)% for a single production sample. This demonstration has shown that DES is a useful tool for quantitative measurements of complicated spectra.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

Data-driven prediction of α IIb β 3 integrin activation paths using manifold learning and deep generative modeling

The integrin heterodimer is a transmembrane protein critical for driving cellular process and is a therapeutic target in the treatment of multiple diseases linked to its malfunction. Activation of integrin involves conformational transitions between bent and extended states. Some of the conformations that are intermediate between bent and extended states of the heterodimer have been experimentally characterized, but the full activation pathways remain unresolved both experimentally due to their transient nature and computationally due to the challenges in simulating rare barrier crossing events in these large molecular systems. An understanding of the activation pathways can provide new fundamental understanding of the biophysical processes associated with the dynamic interconversions between bent and extended states and unveil new putative therapeutic targets. In this work, we apply nonlinear manifold learning to coarse-grained molecular dynamics simulations of bent, extended, and two intermediate states of αI I b β3 integrin to learn a low-dimensional embedding of the configurational phase space. We then train deep generative models to learn an inverse mapping between the low-dimensional embedding and high-dimensional molecular space and use these models to interpolate the molecular configurations constituting the activation pathways between the experimentally characterized states. Furthermore, this work furnishes plausible predictions of integrin activation pathways and reports a generic and transferable multi-scale technique to predict transition pathways for biomolecular systems.

97 MATHEMATICS AND COMPUTING↗