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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 883 records · Page 49
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DOE OSTI2022

Inexact Newton-CG algorithms with complexity guarantees

Abstract We consider variants of a recently developed Newton-CG algorithm for nonconvex problems (Royer, C. W. & Wright, S. J. (2018) Complexity analysis of second-order line-search algorithms for smooth nonconvex optimization. SIAM J. Optim., 28, 1448–1477) in which inexact estimates of the gradient and the Hessian information are used for various steps. Under certain conditions on the inexactness measures, we derive iteration complexity bounds for achieving $\epsilon $-approximate second-order optimality that match best-known lower bounds. Our inexactness condition on the gradient is adaptive, allowing for crude accuracy in regions with large gradients. We describe two variants of our approach, one in which the step size along the computed search direction is chosen adaptively, and another in which the step size is pre-defined. To obtain second-order optimality, our algorithms will make use of a negative curvature direction on some steps. These directions can be obtained, with high probability, using the randomized Lanczos algorithm. In this sense, all of our results hold with high probability over the run of the algorithm. We evaluate the performance of our proposed algorithms empirically on several machine learning models. Our approach is a first attempt to introduce inexact Hessian and/or gradient information into the Newton-CG algorithm of Royer & Wright (2018, Complexity analysis of second-order line-search algorithms for smooth nonconvex optimization. SIAM J. Optim., 28, 1448–1477).

Mathematics↗
DOE OSTI2022

Iterative reconstruction excursions for Baryon Acoustic Oscillations and beyond

ABSTRACT The density field reconstruction technique has been widely used for recovering the baryon acoustic oscillation (BAO) feature in galaxy surveys that has been degraded due to non-linearities. Recent studies advocated adopting iterative steps to improve the recovery much beyond that of the standard technique. In this paper, we investigate the performance of a few selected iterative reconstruction techniques focusing on the BAO and the broad-band shape of the two-point clustering. We include redshift-space distortions, halo bias, and shot noise and inspect the components of the reconstructed field in Fourier space and in configuration space using both density field-based reconstruction and displacement field-based reconstruction. We find that the displacement field reconstruction becomes quickly challenging in the presence of non-negligible shot noise and therefore present surrogate methods that can be practically applied to a much more sparse field such as galaxies. For a galaxy field, implementing a debiasing step to remove the Lagrangian bias appears crucial for the displacement field reconstruction. We show that the iterative reconstruction does not substantially improve the BAO feature beyond an aggressively optimized standard reconstruction with a small smoothing kernel. However, we find taking iterative steps allows us to use a small smoothing kernel more ‘stably’, i.e. without causing a substantial deviation from the linear power spectrum on large scales. In one specific example we studied, we find that a deviation of 13 per cent in $P(k\sim 0.1\, h{\rm \,\,Mpc^{-1}})$ with an aggressive standard reconstruction can reduce to 3–4 per cent with iterative steps.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Alternative approach to quantum imaginary time evolution

There is increasing interest in quantum algorithms (QAs) that are based on the imaginary time evolution (ITE), a successful classical numerical approach to obtain ground states. However, most of the proposals so far require heavy postprocessing computational steps on a classical computer, such as solving linear equations. Here we provide an alternative approach to implement ITE. A key feature in our approach is the use of an orthogonal basis set: the propagated state is efficiently expressed in terms of orthogonal basis states at every step of the evolution. We argue that the number of basis states needed at those steps to achieve an accurate solution can be kept on the order of n , the number of qubits, by controlling the precision (number of significant digits) and the imaginary time increment. The number of quantum gates per imaginary time step is estimated to be polynomial in n . Additionally, while in many QAs the locality of the Hamiltonian is a key assumption, in our algorithm this restriction is not required. This characteristic of our algorithm renders it useful for studying highly nonlocal systems, such as the occupation-representation nuclear shell model. Here, we illustrate our algorithm through numerical implementation on an IBM quantum simulator.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Dyson maps and unitary evolution for Maxwell equations in tensor dielectric media

The propagation and scattering of electromagnetic waves in dielectric media is of theoretical and experimental interest in a wide variety of fields. An understanding of observational results generally requires a numerical solution of Maxwell equations—usually implemented on conventional computers using sophisticated numerical algorithms. In recent years, advances in quantum information science and in the development of quantum computers have piqued curiosity about taking advantage of these resources for an alternate numerical approach to Maxwell equations. This requires a reformulation of the classical Maxwell equations into a form suitable for quantum computers which, unlike conventional computers, are limited to unitary operations. In this paper, a unitary framework is developed for the propagation of electromagnetic waves in a spatially inhomogeneous, passive, nondispersive, and anisotropic dielectric medium. For such a medium, generally, the evolution operator in the combined Faraday-Ampere equations is not unitary. There are two steps needed to convert this equation into a unitary evolution equation. In the first step, a weighted Hilbert space is formulated in which the generator of dynamics is a pseudo-Hermitian operator. In the second step, a Dyson map is constructed which maps the weighted-physical-Hilbert space to the original Hilbert space. Furthermore, the resulting evolution equation for the electromagnetic wave fields is unitary. Utilizing the framework developed in these steps, a unitary evolution equation is derived for electromagnetic wave propagation in a uniaxial dielectric medium. The resulting form is suitable for quantum computing.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

$O(N)$ ab initio calculation scheme for large-scale moiré structures

Here we present a two-step method specifically tailored for band structure calculation of the small-angle moiré-pattern materials which contain tens of thousands of atoms in a unit cell. In the first step, the self-consistent field calculation for the ground state is performed with the O(N) Krylov subspace method implemented in openmx. Second, the crystal momentum-dependent Bloch Hamiltonian and overlap matrix are constructed from the results obtained in the first step and only a small number of eigenvalues near the Fermi energy are solved with shift-invert and Lanczos techniques. By systematically tuning two key parameters, the cutoff radius for electron hopping interaction and the dimension of the Krylov subspace, we obtained the band structures for both rigid and corrugated twisted bilayer graphene structures down to the first magic angle (θ = 1.08°) with high enough accuracy at affordable costs. The band structures are in good agreement with those from tight-binding models, continuum models, plane-wave pseudopotential based ab initio calculations, and experimental observations. This method is also shown to be efficient in twisted double-bilayer graphene and bilayer WSe 2 . We think this two-step method can play a crucial role in other twisted two-dimensional materials, especially those with much more complex band structure and where the effective model is hard to construct.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electronic density of states of a U ( 1 ) quantum spin liquid with spinon Fermi surface. I. Orbital magnetic field effects

A quantum spin liquid with a spinon Fermi surface is an exotic insulator that hosts neutral Fermi surfaces inside the insulating gap. In an external magnetic field, it has been pointed out that the neutral Fermi surfaces are Landau quantized to form Landau levels due to the coupling to the induced emergent gauge magnetic field. In this paper, we calculate the electronic density of states (as observed in tunneling experiments) of the quantum spin liquid in an orbital magnetic field. Here, we find that the Landau levels from the neutral Fermi surfaces give rise to a set of steps emerging at the upper and lower Hubbard band edges. Each of the Hubbard band edge steps further develop into a band edge resonance peak when a weak gauge binding arising from the gauge field fluctuations is taken into account. Importantly, each Hubbard band edge step and its resulting resonance peak in the weak gauge binding are found to have a corresponding Landau level from the neutral Fermi surfaces, so the Hubbard band edge steps and the band edge resonance peaks provide signatures to the unique feature that characterizes the Landau quantization of the in-gap neutral Fermi surfaces in the spin liquid. We further consider the strong gauge-binding regime where the band edge resonance peaks move into the Mott gap and develop into true in-gap bound states. In the strong gauge binding regime, we solve the Landau-level spectrum of the in-gap bound states in an orbital magnetic field. For the in-gap bound state with a Mexican-hat-like band dispersion, we find that the envelop energy to have a state excited from the bound state Landau levels decreases quadratically with the magnetic field. The quadratic decrease behavior of the envelop energy is consistent with the intuition that applying magnetic field localizes the states and energetically promotes the in-gap bound states formation. Finally, we discuss the connection of our results to the electronic density of states spectra measured in the layered 1T-TaS 2 . We point out that a quantum spin liquid with a quasibound state in the upper Hubbard band can give the density of states spectra similar to the one measured in the experiment.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Fractional AC Josephson effect in a topological insulator proximitized by a self-formed superconductor

A lateral Josephson junction in which the surface of a 3D topological insulator serves as the weak link should support topologically protected excitations related to Majorana fermions. The resulting 4π-periodic current-phase relationship could be detected under high-frequency excitation by the suppression of odd Shapiro steps. Here, in this study, we demonstrate such devices through the self-formation of a Pd-Te superconducting layer from a telluride topological insulator, and observe suppressed first and third Shapiro steps. Other devices, including those where the Pd-Te layer is bolstered by an additional Al layer, show no suppression of Shapiro steps, a difference supported by simulations. Though we rule out the known trivial causes of suppressed Shapiro steps in our devices, we nevertheless argue that corroborating measurements and disorder-aware theoretical descriptions of these systems are needed before confidently claiming the observation of Majorana states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

An Algorithmic and Software Pipeline for Very Large Scale Scientific Data Compression with Error Guarantees

Efficient data compression is becoming increasingly critical for storing scientific data because many scientific applications produce vast amounts of data. This paper presents an end-to-end algorithmic and software pipeline for data compression that guarantees both error bounds on primary data (PD) and derived data, known as Quantities of Interest (QoI).We demonstrate the effectiveness of the pipeline by compressing fusion data generated by a large-scale fusion code, XGC, which produces tens of petabytes of data in a single day. We demonstrate that the compression is conducted by setting aside computational resources known as staging nodes, and does not impact the simulation performance. For efficient parallel I/O, the pipeline uses ADIOS2, which many codes such as XGC already use for their parallel I/O. We show that our approach can compress the data by two orders of magnitude while guaranteeing high accuracy on both the PD and the QoIs. Further, the amount of resources required by compression is a few percent of the resources required by simulation while ensuring that the compression time for each stage is less than the corresponding simulation time.This pipeline consists of three main steps. The first step decomposes the data using domain decomposition into small subdomains. Each subdomain is then compressed independently to achieve a high level of parallelism. The second step uses existing techniques that guarantee error bounds on the primary data for each subdomain. The third step uses a post-processing optimization technique based on Lagrange multipliers to reduce the QoI errors for data corresponding to each subdomain. The Lagrange multipliers generated can be further quantized or truncated to increase the compression level. All of the above characteristics of our approach make it highly practical to apply on-the-fly compression while guaranteeing errors on QoIs that are critical to the scientists.

Banerjee, Tania↗
DOE OSTI2022

Robust Event Classification Using Imperfect Real-world PMU Data

Here, this paper studies robust event classification using imperfect real-world phasor measurement unit (PMU) data. By analyzing the real-world PMU data, we find it is challenging to directly use this dataset for event classifiers due to the low data quality observed in PMU measurements and event logs. To address these challenges, we develop a novel machine learning framework for training robust event classifiers, which consists of three main steps: data preprocessing, fine-grained event data extraction, and feature engineering. Specifically, the data preprocessing step addresses the data quality issues of PMU measurements (e.g., bad data and missing data); in the fine-grained event data extraction step, a model-free event detection method is developed to accurately localize the events from the inaccurate event timestamps in the event logs; and the feature engineering step constructs the event features based on the patterns of different event types, in order to improve the performance and the interpretability of the event classifiers. Based on the proposed framework, we develop a workflow for event classification using the real-world PMU data streaming into the system in real time. Using the proposed framework, robust event classifiers can be efficiently trained based on many off-the-shelf lightweight machine learning models. Numerical experiments using the real-world dataset from the Western Interconnection of the U.S power transmission grid show that the event classifiers trained under the proposed framework can achieve high classification accuracy while being robust against low-quality data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Influence of Tabula Rasa on Process- and Light-Induced Degradation of Solar Cells Fabricated From Czochralski Silicon

Monocrystalline Si solar cells are fabricated from Czochralski (Cz) Si, which contains 10 17 –10 18 cm -3 oxygen atoms. Cz Si undergoes degradation during high-temperature thermal processing steps, such as dopant diffusion to form the p - n junction. This degradation in the bulk minority carrier lifetime can be related to the formation of oxygen precipitates. We found that a high-temperature annealing process known as tabula rasa (TR) not only mitigates process-induced degradation via oxygen precipitate nuclei dissolution, but also modifies subsequent light-induced degradation. We report on the bulk carrier lifetime of n - and p -type Cz Si after TR, which homogenizes the interstitial oxygen in the bulk Si to its monoatomic form in either an N 2 or O 2 environment. A control sample, which was not subjected to a TR processing step, experienced severe process-induced degradation during a boron emitter thermal budget as oxygen precipitates were formed in the Si bulk. These precipitates could be imaged using photoluminescence. Additionally, samples that underwent a TR processing step prior to the boron emitter thermal budget show efficient gettering of metallic impurities compared to the control sample, which showed a decline in the implied open-circuit voltage after the gettering step. Furthermore, modification of the interstitial oxygen bonding by TR had a strong effect on the light-induced degradation kinetics. Instead of a typically observed monotonic decrease, minority carrier lifetime increases first, followed by a nonmonotonic decrease over a ~20 h period. Finally, we conclude that by modifying the interstitial oxygen bonding via TR pretreatment, p -type Cz Si wafers become substantially resistant to harsh solar cell processes and strongly modified light-induced degradation, which would open alternative ways to mitigate this degradation mechanism.

14 SOLAR ENERGY↗
DOE OSTI2021

Quasi-Static Time Series Fatigue Simulation for PV Inverter Semiconductors with Long-Term Solar Profile

Power system simulations with long-term data tend to have large time steps varying from one second to a few minutes. However, for PV inverter semiconductors, the minimum thermal stresses cycle is with line frequency. This requires the time step of the fatigue simulation to be much smaller than the line period. This small time step results in poor simulation speed, especially for long-term simulations. This paper proposes a fast fatigue simulation for inverter semiconductors using the quasi-static time series (QSTS) simulation concept. The fatigue analysis typically focuses on the peak and valley values of a strain and neglect the transients from peaks to valleys. The proposed simulation utilizes this property of fatigue analysis and calculates the steady state of the semiconductor junction temperature only. The resulting time step of the fatigue simulation is 15 minutes, which is consistent with the solar dataset without losing accuracy.

fast simulation↗
DOE OSTI2022

Arbitrage and Capacity Firming in Coordination with Day-Ahead Bidding of a Hybrid PV Plant

A hybrid PV plant (HPP) combines a photovoltaic (PV) plant with a battery energy storage system (BESS), which is considered a promising step towards the future of renewable power plants by the U.S. Department of Energy. When the renewable penetration reaches a significant level, a hybrid PV plant can bid in as a controllable thermal plant in the future electricity market. In this study, a bidding and BESS scheduling model is proposed for the HPP. The robust optimization (RO) technique has been utilized to identify the worst-case scenario of uncertainties during the bidding process. To address the overly conservative issue of the single-stage RO, we have decoupled the BESS schedule for arbitrage and PV capacity firming by a two-stage RO formulation. By comparing the output of single-stage RO and two-stage RO, the two-stage RO bids and schedules in a more aggressive manner, which increases the income of HPP. Also, the penalty of under-generation is considered in our model so that the day-ahead bidding decision and arbitrage schedules can be adjusted based on the potential UNDER-GENERATION penalty. Because the proposed model is non-convex and contains multi-stages, the Column-and-Constraint Generation (C&CG) algorithm is applied to the model as the solution. The proposed model has shown better economic performance compared to a state-of-art single-stage bidding method in case studies.

BESS scheduling↗
DOE OSTI2021

Calculation of the Thermodynamic Voltage Limit of CdSeTe Solar Cells

The first step to understand the origin of losses in any photovoltaic solar cell is to determine the fundamental thermodynamic efficiency and voltage limits of such a device. In this contribution, we detail techniques to calculate the voltage limit in the case of cadmium selenium telluride (CdSeTe) solar cells, and how approaches based on bandgap alone—i.e., the Shockley-Queisser approach with step-function absorptance—can overestimate the thermodynamic open-circuit voltage limit Voc,ideal . This is particularly true for arsenic-doped samples, which tend to exhibit below-bandgap absorptance.

absorptance↗
DOE OSTI2020

Switch Opening and Exchange Method for Stochastic Distribution Network Reconfiguration

The purpose of distribution network reconfiguration (DNR) is to determine the optimal topology of an electricity distribution network, which is an efficient measure to reduce network power losses. Electricity load demand and photovoltaic (PV) output are uncertain and vary with time of day, and will affect the optimal network topology. Single-hour deterministic DNR is incapable of handling this uncertainty and variability. Therefore, this paper proposes to solve a multi-hour stochastic DNR (SDNR). Existing solution methods for DNR are either inaccurate or excessively time-consuming, and are therefore incapable of solving multi-hour SDNRs for large distribution networks. In this regard, a switch opening and exchange (SOE) method is proposed. Starting from a looped network with all switches closed, the SOE consists of three steps. The first step is to sequentially open the switches until all of the loops are opened. The second and third steps modify the status of branches obtained in the first step to obtain better radial topologies. Five test systems are used to validate the accuracy and fast solution speed of the SOE and the superiority of multi-hour SDNR over single-hour deterministic DNR.

distribution network reconfiguration↗
DOE OSTI2026

Plasma-assisted atomic layer etching of single-crystal diamond

Applications of near-surface nitrogen-vacancy (NV) centers in diamond are often limited by surface defects created during processing. Understanding and controlling plasma-induced surface damage is important for preserving the optical and spin properties of diamond NV centers. We report molecular dynamics simulations of a novel form of plasma-aided atomic layer etching of diamond. In this proposed scheme, the initial surface modification step consists of Ar + ion bombardment. This creates an amorphous layer at the surface, the thickness of which is controlled by the ion energy. Amorphization is known to help smooth the surface, at least locally, and would also serve to sputter clean an initially contaminated surface. A second step impacts the amorphous carbon layer with O + between about 1 and 5 eV. Simulations show that this energy range will remove the amorphous carbon but will not etch the underlying diamond. Though this energy range is not trivial to achieve in a conventional low-temperature plasma, potential methods for creating these low-energy O + ions are discussed. In addition to a-C etching, the O + impacts are predicted to remove any isolated (100) diamond terraces by selectively attacking the edges of the terraces. The proposed atomic layer etching (ALE) approach reverses the conventional ALE sequence in which the surface modification step is usually chemical modification (oxidation in this case), followed by a removal step using Ar + impacts. This plasma ALE procedure is predicted to create a diamond surface that is atomically flat and defect free.

Draney, J. S. [Princeton University, NJ (United St↗
DOE OSTI2022

Thixotropic spectra and Ashby-style charts for thixotropy

There is no universal model for thixotropy, and comparing thixotropic effects between different fluids is a subtle yet challenging problem. We introduce a generalized (model-insensitive) framework for comparing thixotropic properties based on thixotropic spectra. A superposition of exponential stress modes distributed over thixotropic time scales is used to quantify buildup and breakdown times and mode strengths in response to step-change input. This mathematical framework is tested with several experimental step-shear rate data on colloidal suspensions. Low-dimensional metrics based on moments of the distribution reveal characteristic average thixotropic properties, which are visualized on Ashby-style diagrams. This method outlines a framework for describing thixotropy across a diverse range of microstructures, supporting scientific studies as well as material selection for engineering design applications.

Mechanics↗
DOE OSTI2022

New insights on carbon black suspension rheology—Anisotropic thixotropy and antithixotropy

We report a detailed experimental study of peculiar thixotropic dynamics of carbon black (CB, Vulcan XC-72) suspensions in mineral oil, specifically the observation of sequential stress increase then decrease at a fixed shear rate in a step-down test. We verify that such dynamics, though peculiar, come from a true material response rather than experimental artifacts. We also reveal how this long-time stress decay is associated with antithixotropic structural change rather than viscoelastic stress relaxation by using orthogonal superposition (OSP) rheometry to probe viscoelastic moduli during the step-down tests. The orthogonal storage and loss moduli are present, showing this two-timescale recovery then decay response, which demonstrates that this response is antithixotropic, and it involves shear-induced structuring. We further show a mechanical anisotropy in the CB suspension under shear using OSP. Based on the rheological results, a microstructural schematic is proposed, considering qualitatively thixotropic structure build-up, antithixotropic densification, and anisotropic structure evolution. Our observation for these CB suspensions is outside the standard paradigm of thixotropic structure-parameter models, and the elastic response provides us with new insight into the transient dynamics of CB suspensions.

Mechanics↗
DOE OSTI2023

Inferring microbial co-occurrence networks from amplicon data: a systematic evaluation

Microbes commonly organize into communities consisting of hundreds of species involved in complex interactions with each other. 16S ribosomal RNA (16S rRNA) amplicon profiling provides snapshots that reveal the phylogenies and abundance profiles of these microbial communities. These snapshots, when collected from multiple samples, can reveal the co-occurrence of microbes, providing a glimpse into the network of associations in these communities. However, the inference of networks from 16S data involves numerous steps, each requiring specific tools and parameter choices. Moreover, the extent to which these steps affect the final network is still unclear. In this study, we perform a meticulous analysis of each step of a pipeline that can convert 16S sequencing data into a network of microbial associations. Through this process, we map how different choices of algorithms and parameters affect the co-occurrence network and identify the steps that contribute substantially to the variance. We further determine the tools and parameters that generate robust co-occurrence networks and develop consensus network algorithms based on benchmarks with mock and synthetic data sets. The Microbial Co-occurrence Network Explorer, or MiCoNE (available at https://github.com/segrelab/MiCoNE) follows these default tools and parameters and can help explore the outcome of these combinations of choices on the inferred networks. We envisage that this pipeline could be used for integrating multiple data sets and generating comparative analyses and consensus networks that can guide our understanding of microbial community assembly in different biomes.

16S rRNA↗