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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Repurposing Inactive Oil and Gas Wells for Energy Storage: Maximizing the Potential Via Optimal Drivetrain Control: Preprint

In recent years, there has been a growing emphasis on utilizing energy storage to enhance grid resilience against disruptive events. While renewable energy supply continues to expand, gravity-based solutions like pumped hydro remain dominant in the commercial space. However, their geographical limitations constrain availability, scalability, and increase costs for co-locating solar and wind energy. An alternative approach proposes repurposing idle oil and gas wells located closer to existing grid infrastructure, offering a promising and cost-effective solution. This paper addresses the optimization and control of a regenerative drive system coupled to an interior permanent magnet synchronous machine in a 300-meter well with a 100-Newton weight. The study employs a dynamic MATLAB/Simulink model to simulate the operation of the electric drivetrain system during storage and discharge operations. The results demonstrate an initial round-trip efficiency of 85.9% for the electrical system alone and identify crucial factors for maximizing efficiency. The optimized operation and control of the electromechanical drivetrain system hold great potential for minimizing the levelized cost of storage while maximizing efficiency and revenue generation.

ENERGY STORAGE,ENGINEERING↗
DOE OSTI2024

Wind Turbine Design Optimization for Hydrogen Production

To help meet the need for inexpensive green fuels, we are working on wind turbine design optimization specifically for hydrogen production. We have thus far achieved a 1.53% decrease in LCOH as compared to a turbine optimized for LCOE using the same code, design variables, and models. We accomplished this by optimizing some components of the wind turbine tower, rotor, and drivetrain design with hydrogen production and costs in the design loop.

hydrogen↗
DOE OSTI2020

The role of iron in magnetic damping of Mg(Al,Fe) 2 O 4 spinel ferrite thin films

© 2020 Author(s). We have investigated magnesium aluminum ferrite thin films with a range of iron concentrations and identified the optimal iron content to obtain high crystalline quality thin films with the low magnetic damping required for spin current-based applications. Epitaxial MgAl 2-x FexO4 films with 0.8 < x < 2.0 were grown by pulsed laser deposition on single crystal MgAl2O4 substrates and were characterized structurally and magnetically. We find that the x = 1.5 composition minimizes the room-temperature magnetic damping with a typical Gilbert damping parameter of α eff = 1.8 × 10-3. This minimized damping is governed by a competition between the more robust magnetic ordering with increased iron content, x, and the more defective structure due to larger film-substrate lattice mismatch with increased iron content. The temperature-dependent magnetization curves indicate that Tc is suppressed below room temperature for iron content x ≤ 1.2 and eventually suppressed entirely for x = 0.8. X-ray magnetic circular dichroism results indicate that for all x the magnetic moment is dominated by Fe 3 + cations distributed in a 60:40 ratio on the octahedral and tetrahedral sites, with minimal contribution from Fe 2 + cations. Films with x = 1.4-1.6 exhibit very strong ferromagnetic resonance and low Gilbert damping with α eff = (1.8-6) × 10-3, making them ideal candidates for microwave and spintronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Exploring poly-crystallization in semiconductors through assumption-less growth simulations: CdTe/CdS case study

Crystal growth is a complex process with far-reaching implications for high-performance materials across various fields. Recent advancements in structural analysis methods such as polyhedral template matching, which allows semiconductor-specific analysis, coupled with simulation technology, have enabled the comprehensive study of crystallization dynamics in semiconductors. However, the exploration of polycrystalline semiconductors created with minimal external intervention of the crystallization processes is relatively uncharted in comparison with metals. In this study, we employ molecular dynamics to simulate the growth of polycrystalline CdTe/CdS with the assumptions of classical mechanics, a Stillinger–Weber potential, an amorphous substrate, and common vapor growth conditions to allow the polycrystalline structures to evolve naturally. Post-simulation, we identify and analyze impactful structures and events, comparing them to theory and experiment to gain insight into various modes of crystallization dynamics. Two research questions guided the study: (1) How realistic are assumption-less simulated polycrystalline semiconductor structures? (2) To what extent can the approach provide insight into crystallization? The simulations, performed with minimal external control, yield polycrystalline structures mirroring experimental findings. The analysis reveals key crystallization insights, such as the role of amorphous atoms in the transition from nucleation to grain growth and the transformative impact of single events, such as dislocations, on crystallization dynamics. The method paves the way for reproducing and analyzing realistic polycrystalline semiconductor structures with minimal simulation assumptions across various growth modes.

Abdullah, Sharmin↗
DOE OSTI2024

Full-wave simulations on helicon and parasitic excitation of slow waves near the edge plasma

Helicon waves are thought to be promising in various tokamaks, such as DIII-D, because they can penetrate reactor-grade high-density cores and drive the off-axis current with higher efficiency. In the frequency regime ~476 MHz, both slow electrostatic and fast electromagnetic helicon waves can coexist in DIII-D. If the antenna parasitically excites the slow mode, these waves can propagate along the magnetic field line into the scrape-off layer (SOL). Although the importance of the misalignment of the Faraday screen and the electron density in the SOL on the excitation and propagation of slow modes is well known, the conditions for minimizing slow mode excitation have yet to be optimized. Using the Petra-M simulation code in the 2D domain, we analyze the effects of the misalignment of the antenna in the poloidal direction, the misalignment of the Faraday screen in the toroidal direction, and the density in front of the antenna on slow mode generation. Our results suggest that the misalignment of the Faraday screen is a critical factor in reducing the slow mode and that the misalignment angle should be below ~5° to minimize the slow wave excitation. When the electron density is higher than 3.5 x 10 18 m –3 in the SOL, the generation of the slow mode from the antenna is minimized and unaffected by the misalignment of the Faraday screen.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Learning to learn by using nonequilibrium training protocols for adaptable materials

Evolution in time-varying environments naturally leads to adaptable biological systems that can easily switch functionalities. Advances in the synthesis of environmentally responsive materials therefore open up the possibility of creating a wide range of synthetic materials which can also be trained for adaptability. We consider high-dimensional inverse problems for materials where any particular functionality can be realized by numerous equivalent choices of design parameters. By periodically switching targets in a given design algorithm, we can teach a material to perform incompatible functionalities with minimal changes in design parameters. We exhibit this learning strategy for adaptability in two simulated settings: elastic networks that are designed to switch deformation modes with minimal bond changes and heteropolymers whose folding pathway selections are controlled by a minimal set of monomer affinities. The resulting designs can reveal physical principles, such as nucleation-controlled folding, that enable such adaptability.

Science & Technology - Other Topics↗
DOE OSTI2021

Cost- and Risk-Based Seismic Design Optimization of Nuclear Power Plant Safety Systems

Seismic analysis, design, and qualification of systems, structures, and components (SSCs) is a significant contributor to the capital cost of a nuclear power plant. To reduce capital costs of advanced nuclear power plants and make commercial nuclear energy more competitive, innovations are needed in their structural design and construction, and not just in the reactor core and associated systems. Seismic isolation has been identified as an important cost-cutting technology that enables standardization of equipment across various sites. This paper develops and demonstrates a cost- and risk-based seismic design optimization of a representative safety system in a nuclear power plant with the dual goals of minimizing overnight capital cost and meeting safety goals. The design optimization can also include component seismic isolation, in which case, the optimized design includes a set of equipment that needs to be seismically isolated to minimize capital cost. The open-source codes MASTODON and Dakota are used for seismic probabilistic risk assessment and design optimization, respectively. A generic nuclear facility with a safety system comprising SSCs that are common to nuclear power plants is considered for the demonstration of the design optimization and is assumed to be located at the Idaho National Laboratory site. Generic costs and seismic design cost functions are assumed for the SSCs of the safety system. The sum of the costs of the SSCs is minimized in the optimization process, while the risk of failure of the safety system is provided as a constraint. Furthermore, results show that the optimization process reduces capital costs significantly while automatically prioritizing the safety of SSCs that contribute most to the risk of the safety system.

42 ENGINEERING↗
DOE OSTI2023

Contribution of carbon pricing to meeting a mid-century net zero target

A mid-century net zero target creates a challenge for reducing the emissions of emissions-intensive, trade-exposed sectors with high cost mitigation options. These sectors include aluminium, cement, chemicals, iron and steel, lime, pulp and paper and petroleum refining. Available studies agree that decarbonization of these sectors is possible by mid-century if more ambitious policies are implemented soon. Existing carbon pricing policies have had limited impact on the emissions of these sectors because their marginal abatement costs almost always exceed the tax rate or allowance price. But emissions trading systems with free allowance allocations to emissions-intensive, trade-exposed sectors have minimized the adverse economic impacts and associated leakage. Internationally coordinated policies are unlikely, so implementing more ambitious policies creates a risk of leakage. This paper presents policy packages a country can implement to accelerate emission reduction by these sectors with minimal risk of leakage. To comply with international trade law the policy packages differ for producers whose goods compete with imports in the domestic market and producers whose goods are exported. Carbon pricing is a critical component of each package due its ability to minimize the risk of adverse economic impacts on domestic industry, support innovation and generate revenue. The revenue can be used to assist groups adversely impacted by the domestic price and production changes due to carbon pricing and to build public support for the policies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A rotationally invariant approach based on Gutzwiller wave function for correlated electron systems

Here, we introduce a rotationally invariant approach combined with the Gutzwiller conjugate gradient minimization method to study correlated electron systems. In the approach, the Gutzwiller projector is parametrized based on the number of electrons occupying the onsite orbitals instead of the onsite configurations. The approach efficiently groups the onsite orbitals according to their symmetry and greatly reduces the computational complexity, which yields a speedup of $20 \sim 50 \times $ in the minimal basis energy calculation of dimers. The computationally efficient approach promotes more accurate calculations beyond the minimal basis that is inapplicable in the original approach. A large-basis energy calculation of F 2 demonstrates favorable agreements with standard quantum-chemical calculations Bytautas et al (2007 J. Chem. Phys. 127 164317).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Machine learning method for enforcing variable independence in background estimation with LHC data: ABCDisCoTEC

A novel solution is presented for the problem of estimating the backgrounds of a signal search using observed data while simultaneously maximizing the sensitivity of the search to the signal. The 'ABCD method' provides a reliable framework for background estimation by partitioning events into one signal-enhanced region (A) and three background-enhanced control regions (B, C, and D) via two smoothly varying, statistically independent variables. In practice, even slight correlations between the two variables can significantly undermine the method's performance. Thus, choosing appropriate variables by hand can present a formidable challenge, especially when background and signal differ only subtly. To address this issue, the ABCD with distance correlation (ABCDisCo) method was developed to construct two learned variables via a neural network trained to provide strong signal-background discrimination with small values of the distance correlation (DisCo) measure between the two learned variables. However, relying solely on minimizing the DisCo can result in learned variables that may not have distributions of background events that are smoothly varying and localized at extreme values, as necessary for the validity of the background estimation. The ABCDisCo training enhanced with closure (ABCDisCoTEC) method is introduced to solve this issue by directly minimizing the nonclosure, expressed as a dedicated differentiable loss term. This extended method is applied to a data set of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the CMS detector at the CERN Large Hadron Collider. Additionally, given the complexity of the minimization problem with constraints on multiple loss terms, the modified differential method of multipliers is applied and shown to greatly improve the stability and robustness of the ABCDisCoTEC method, compared to grid search hyperparameter optimization procedures.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗
DOE OSTI2021

A variant selection framework for genome graphs

Abstract Motivation Variation graph representations are projected to either replace or supplement conventional single genome references due to their ability to capture population genetic diversity and reduce reference bias. Vast catalogues of genetic variants for many species now exist, and it is natural to ask which among these are crucial to circumvent reference bias during read mapping. Results In this work, we propose a novel mathematical framework for variant selection, by casting it in terms of minimizing variation graph size subject to preserving paths of length α with at most δ differences. This framework leads to a rich set of problems based on the types of variants [e.g. single nucleotide polymorphisms (SNPs), indels or structural variants (SVs)], and whether the goal is to minimize the number of positions at which variants are listed or to minimize the total number of variants listed. We classify the computational complexity of these problems and provide efficient algorithms along with their software implementation when feasible. We empirically evaluate the magnitude of graph reduction achieved in human chromosome variation graphs using multiple α and δ parameter values corresponding to short and long-read resequencing characteristics. When our algorithm is run with parameter settings amenable to long-read mapping (α = 10 kbp, δ = 1000), 99.99% SNPs and 73% SVs can be safely excluded from human chromosome 1 variation graph. The graph size reduction can benefit downstream pan-genome analysis. Availability and implementation https://github.com/AT-CG/VF. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Sharp detection of low-dimensional structure in probability measures via dimensional logarithmic Sobolev inequalities

Identifying low-dimensional structure in high-dimensional probability measures is an essential pre-processing step for efficient sampling. To identify this structure, we approximate the target measure as a perturbation of an arbitrary reference measure along a few directions in $\mathbb{R}^{d}$. These directions are determined by minimizing an upper bound on the Kullback–Leibler (KL) divergence between the target and its approximation. Our contribution improves upon previous works by leveraging dimensional logarithmic Sobolev inequalities to refine the bound on the KL divergence. These inequalities lead to a uniformly tighter bound on the KL divergence, thereby enhancing the identification of the most significant perturbation directions. In particular, when the target and reference are both Gaussian, minimizing the resulting bound is equivalent to minimizing the KL divergence. We further demonstrate the applicability of this analysis to the squared Hellinger distance, where analogous reasoning shows that the dimensional Poincaré inequality offers improved bounds.

Bayesian inference↗
DOE OSTI2022

Latitudinal shifts of soil microbial biomass seasonality

Soil microbes ultimately drive the mineralization of soil organic carbon and thus ecosystem functions. We compiled a dataset of the seasonality of microbial biomass carbon (MBC) and developed a semi-mechanistic model to map monthly MBC across the globe. MBC exhibits an equatorially symmetric seasonality between the Northern and Southern Hemispheres. In the Northern Hemisphere, MBC peaks in autumn and is minimal in spring at low latitudes (<25°N), peaks in the spring and is minimal in autumn at mid-latitudes (25°N to 50°N), while peaks in autumn and is minimal in spring at high latitudes (>50°N). This latitudinal shift of MBC seasonality is attributed to an interaction of soil temperature, soil moisture, and substrate availability. The MBC seasonality is inconsistent with patterns of heterotrophic respiration, indicating that MBC as a proxy for microbial activity is inappropriate at this resolution. This study highlights the need to explicitly represent microbial physiology in microbial models. The interactive controls of environments and substrate on microbial seasonality provide insights for better representing microbial mechanisms in simulating ecosystem functions at the seasonal scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Ordering the topological order in the fractional quantum Hall effect

Here, we discuss the possible topological order/topological quantum field theory of different quantum Hall systems. Given the value of the Hall conductivity, we constrain the global symmetry of the low-energy theory and its anomaly. Specifically, the one-form global symmetry and its anomaly are presented as the organizing principle of these systems. This information is powerful enough to lead to a unique minimal topological order (or a small number of minimal topological orders). Almost all of the known experimentally discovered topological orders are these minimal theories. Since this work is interdisciplinary, we made a special effort to relate to researchers with different backgrounds by providing translations between different perspectives.

Anyons↗
DOE OSTI2020

Polymorphous nature of cubic halide perovskites

Many common crystal structures can be described by a single (or very few) repeated structural motif (“monomorphous structures”) such as octahedron in cubic halide perovskites. Interestingly, recent accumulated evidence suggests that electronic structure calculations based on such macroscopically averaged monomorphous cubic ($\textit{Pm} – 3m$) halide perovskites obtained from x-ray diffraction, show intriguing deviations from experiment. These include systematically too small band gaps, dielectric constants dominated by the electronic, negative mixing enthalpy of alloys, and significant deviations from the measured pair distribution function. We show here that a minimization of the systems $\textit{T}$ = 0 internal energy via density functional theory reveals a distribution of different low-symmetry local motifs, including tilting, rotations, and B-atom displacements (“polymorphous networks”). This is found only if one allows for larger-than-minimal cell size that does not geometrically exclude low symmetry motifs. As the (super) cell size increases, the energy is lowered relative to the monomorphous cell, and stabilizes after ~32 formula units (≥160 atoms) are included. Being a result of nonthermal energy minimization in the internal energy without entropy, this correlated set of displacements must represent the intrinsic geometry preferred by the underlying chemical bonding (lone pair bonding), and as such has a different origin than the normal, dynamic thermal disorder modeled by molecular dynamics. Indeed, the polymorphous network, not the monomorphous ansatz, is the kernel structure from which high temperature thermal agitation develops. The emerging physical picture is that the polymorphous network has an average structure with high symmetry, yet the local structural motifs have low symmetries. In this work we find that, compared with monomorphous counterparts, the polymorphous networks have significantly lower predicted total energies, larger band gaps, and ionic dominated dielectric constants, and agree much more closely with the observed pair distribution functions. An analogous polymorphous situation is found in the paraelectric phase of a few cubic oxide perovskites where local polarization takes the role of local displacements in halide perovskites, and in the paramagnetic phases of a few 3 d oxides where the local spin configuration takes that role.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Understanding electronic peculiarities in tetragonal FeSe as local structural symmetry breaking

Traditional band theory of perfect crystalline solids often uses as input the structure deduced from diffraction experiments; when modeled by the minimal unit cell this often produces a spatially averaged model. The present study illustrates that this is not always a safe practice unless one examines if the intrinsic bonding mechanism is capable of benefiting from the formation of a distribution of lower symmetry local environments that differ from the macroscopically averaged structure. This can happen either due to positional or to magnetic symmetry breaking. By removing the constraint of a small crystallographic cell, the energy minimization in the density functional theory finds atomic and spin symmetry breaking, not evident in conventional diffraction experiments but being found by local probes such as atomic pair distribution function analysis. Here in this paper we report that large atomic and electronic anomalies in bulk tetragonal FeSe emerge from the existence of distributions of local positional and magnetic moment motifs. The found symmetry-broken motifs obtained by minimization of the internal energy represent what chemical bonding in the tetragonal phase prefers as intrinsic energy lowering (stabilizing) static distortions. This explains observations of band renormalization, predicts orbital order and enhanced nematicity, and provides unprecedented close agreement with spectral function measured by photoemission and local atomic environment revealed by the pair distribution function. While the symmetry-restricted strong correlation approach has been argued previously to be the exclusive theory needed for describing the main peculiarities of FeSe, we show here that the symmetry-broken mean-field approach addresses numerous aspects of the problem, provides intuitive insight into the electronic structure, and opens the door for large-scale mean-field calculations for similar d -electron quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Precision unification and the scale of supersymmetry

In this paper, we study the implications of precise gauge coupling unification on supersymmetric particle masses. We argue that precise unification favors the superpartner masses that are in the range of several TeV and well beyond. We demonstrate this in the minimal supersymmetric theory with a common sparticle mass threshold, and two simple high-scale scenarios; minimal supergravity and minimal anomaly-mediated supersymmetry. We also identify candidate models with a Higgsino or a wino dark matter candidate. Finally, the analysis shows unambiguously that unless one takes foggy naturalness notions too seriously, the lack of direct superpartner discoveries at the LHC has not diminished the viability of supersymmetric unified theories in general nor even precision unification in particular. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Flavor patterns of fundamental particles from quantum entanglement?

The Cabibbo-Kobayashi-Maskawa (CKM) matrix, which controls flavor mixing between the three generations of quark fermions, is a key input to the standard model of particle physics. In this paper, we identify a surprising connection between quantum entanglement and the degree of quark mixing. Focusing on a specific limit of 2 → 2 quark scattering mediated by electroweak bosons, we find that the quantum entanglement generated by scattering is minimized when the CKM matrix is almost (but not exactly) diagonal, in qualitative agreement with observation. With the discovery of neutrino masses and mixings, additional angles are needed to parametrize the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) matrix in the lepton sector. Applying the same logic, we find that quantum entanglement is minimized when the PMNS matrix features two large angles and a smaller one, again in qualitative agreement with observation, plus a hint for suppressed C P violation. We speculate on the (unlikely but tantalizing) possibility that minimization of quantum entanglement might be a fundamental principle that determines particle physics input parameters. Published by the American Physical Society 2025

Thaler, Jesse (ORCID:0000000224068160)↗