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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Artificial dynamical effects in quantum field theory

In Newtonian mechanics, studying a system in a non-Galilean reference frame can lead to inertial pseudoforces appearing, such as the centrifugal force that seems to arise in dynamics analysed in a rotating frame. Likewise, artificial effects may arise in relativistic quantum field theory (QFT) if a system is studied in a framework that violates Poincaré invariance. Here, we highlight how such issues complicate the traditional canonical quantization of QFTs and can lead to a subjective description of natural phenomena. By contrast, the treatment of the same problem using light-front quantization is free from spurious pseudoeffects because Poincaré invariance is effectively preserved for all practical intents and purposes. We illustrate these statements using several examples: the Gerasimov-Drell-Hearn (GDH) relation, a fundamental feature of QFT; the absence of any measurable impact of Lorentz contraction in high-energy collisions; and the fictitious character of vacuum fluctuation contributions to the cosmological constant.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Nitrogen management during decarbonization

Decarbonization is crucial to combat climate change. However, some decarbonization strategies could profoundly impact the nitrogen cycle. Here, in this Review, we explore the nitrogen requirements of five major decarbonization strategies to reveal the complex interconnections between the carbon and nitrogen cycles and identify opportunities to enhance their mutually sustainable management. Some decarbonization strategies require substantial new nitrogen production, potentially leading to increased nutrient pollution and exacerbation of eutrophication in aquatic systems. For example, the strategy of substituting 44% of fossil fuels used in marine shipping with ammonia-based fuels could reduce CO 2 emissions by up to 0.38 Gt CO 2 -eq yr -1 but would require a corresponding increase in new nitrogen synthesis of 212 Tg N yr -1 . Similarly, using biofuels to achieve 0.7 ± 0.3 Gt CO 2 -eq yr -1 mitigation would require new nitrogen inputs to croplands of 21–42 Tg N yr -1 . To avoid increasing nitrogen losses and exacerbating eutrophication, decarbonization efforts should be designed to provide carbon–nitrogen co-benefits. Reducing the use of carbon-intensive synthetic nitrogen fertilizer is one example that can simultaneously reduce both nitrogen inputs by 14 Tg N yr -1 and CO 2 emissions by 0.04 (0.03–0.06) Gt CO 2 -eq yr -1 . Future research should guide decarbonization efforts to mitigate eutrophication and enhance nitrogen use efficiency in agriculture, food and energy systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Irrigation-induced land water depletion aggravated by climate change

Agricultural irrigation has experienced rapid expansion, and its growing freshwater consumption is potentially exacerbating water scarcity issues. Previous studies predominantly relied on observations or land-only simulations, often neglecting land–atmosphere interactions or failing to capture long-term evolution. We therefore analyse the effects of historical irrigation expansion on water fluxes and resources using seven Earth system models. Here we show that irrigation expansion in many regions substantially decreases the net water influx from the atmosphere to land, further aggravating the existing drying trends caused by climate change. For example, irrigation expansion changed the trend of this net influx from −0.664 ( ± 0.283) to −1.461 ( ± 0.261) mm yr −2 in South Asia after 1960. Consequently, the local terrestrial water storage depletion rate is substantially enlarged by irrigation expansion (for example, from −2.559 ( ± 0.094) to −16.008 ( ± 0.557) mm yr −1 ). Our results attribute the land water loss to irrigation expansion and climate change, calling for immediate solutions to tackle the negative trends.

irrigation↗
DOE OSTI2025

Scalable, biologically sourced depolymerizable polydienes with intrinsically weakened carbon–carbon bonds

Currently, there are few examples of circularly recyclable polymers with all-carbon backbones, probably owing to the challenge of using selective C–C bond cleavage to efficiently produce monomers in recycling processes. Furthermore, here we demonstrate a series of biologically sourced polymuconate polymers synthesized via simple free-radical polymerization that exhibit intrinsically weakened C–C bonds and controlled chemical recycling to monomers. Modifying the side chains and copolymerization ratios allows a wide range of mechanical property tuning, achieving performances comparable to those of commercial plastics such as polystyrene, polymethyl methacrylate and polybutadiene. Techno-economic analysis and life cycle assessment for production at a scale of 100 kilotons per year show that the materials are currently slightly more expensive and environmentally intensive compared with conventional rubbers. However, use of recycled materials via depolymerization can greatly decrease the cost and environmental impacts of polymuconate production (for example, down to US$1.59 per kilogram) to outperform its commercial counterparts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Chapter 3: Ultrathin Oxides for Solar Cells

This chapter discusses the many uses of ultrathin oxide layers across a broad range of photovoltaic (PV) technologies. The chapter is broken down into six sections, working from the solar absorber outwards: passivation layers, selective contact/buffer layers, recombination layers, barrier layers, anti-reflective coatings, and anti-soiling layers. The goal is to introduce the layer function, outline the scientific mechanisms behind each function, and provide illustrative examples from academic literature and industry. One theme in this chapter is the multifunctionality of oxide layers in the PV device stack, that is, a single layer rarely has only one purpose and therefore certain ideas will build upon other sections. The chapter covers a wide range of material and the discussions and examples are by no means exhaustive. The best efforts have been made to capture the central concepts for each topic and direct the reader to additional resources that have been found by the authors to be useful and relevant.

anti-reflection coatings↗
DOE OSTI2021

A mathematical analysis of carbon fixing materials that grow, reinforce, and self-heal from atmospheric carbon dioxide

Carbon fixing materials are a new class of self-healing, self-reinforcing materials we have introduced that utilize ambient CO 2 to chemically add to an ever extending carbon backbone. This class of materials can utilize biological or non-biological photocatalysts and support a wide range of potential backbone chemistries. However, there is no analysis to date that describes their fundamental limits in terms of chemical kinetics and mass transfer. In this computational study, we employ a reaction engineering, and materials science analysis to answer basic questions about the maximum growth rate, photocatalytic requirements and limits of applicable materials. Our proposed mathematical framework envelops three main functions required for carbon fixing materials: (1) adsorption of CO 2 from air, (2) photocatalytic reduction of CO 2 into selected monomers, and (3) polymerization of CO 2 -derived monomers. First, by performing a Damköhler number analysis, we derive criteria for the cross over from kinetic control to mass transfer limited growth, setting upper limits on performance of a potential photocatalyst. Next, we analyze photocatalytic reduction of CO 2 to single carbon products, using known catalytic pathways and kinetic data. We identify formaldehyde as a C1 intermediate having unique potential for incorporation into the material backbone of carbon fixing materials. As an example, we find that a diamond-shaped reaction network graph for CO 2 reduction, passing through CO and HCOOH intermediates, accurately describes kinetic data for cobalt-promoted TiO 2 nanoparticles at room temperature and 1 atm CO 2 . Finally, as an applied case study, we consider and analyze the example of a carbon fixing poly(oxymethylene) system with embedded catalyst promoting the photocatalytic reduction of CO 2 to formaldehyde. The latter then trimerizes to a trioxane monomer which subsequently polymerizes to polyoxymethylene. This reaction engineering analysis introduces benchmarks for carbon fixing materials with respect to achievable rates of photocatalysis, adsorption, and polymerization. These results should prove valuable for the design, evaluation, and benchmarking of this emergent and new class of environmentally sustainable materials.

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

Review of low-cost self-driving laboratories in chemistry and materials science: the “frugal twin” concept

This review proposes the concept of a “frugal twin,” similar to a digital twin, but for physical experiments. Frugal twins range from simple toy examples to low-cost surrogates of high-cost research systems. For example, a color-mixing self-driving laboratory (SDL) can serve as a low-cost version of a costly multi-step chemical discovery SDL. Frugal twins already provide hands-on experience for SDLs with low costs and low risks. They can also offer as test beds for software prototyping (e.g., optimization, data infrastructure), and a low barrier to entry for democratizing SDLs. However, there is room for improvement. The true value of frugal twins can be realized in three core areas. Firstly, hardware and software modularity; secondly, purpose-built design (human-inspired vs. hardware-centric vs. human-in-the-loop); and thirdly state-of-the-art (SOTA) software (e.g., multi-fidelity optimization). We also describe the ethical benefits and risks that come with the democratization of science through frugal twins. For future work, we suggest ideas for new frugal twins, SDL educational course outcomes, and a classification scheme for autonomy levels.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Light-driven hydrogen evolution via a novel pincer/no pincer mechanism including a possible concerted proton electron transfer

The road to efficient molecular catalysts for artificial photosynthesis requires a great deal of basic research to address the challenges of anthropogenic global warming. An unexpected result of such research is a novel pincer/no pincer mechanism discovered for the DFT-calculated catalytic cycle of PNP-C2 complexes. Structural parameters from theoretical modeling are supported by single crystal X-ray data for the corresponding complexes. Using the examples of [M(II)Cl(PNP-C2-R)] + (M = Pd 2+ , Ni 2+ ; R = CH 3 , H; PNP-C2 = N,N-bis{(di(2-methoxy-phenyl)phosphanyl)ethyl}-N-alkylamine) this pincer/no pincer mechanism is supported by differential pulse voltammetric, cyclic voltammetric, UV-Vis spectroscopic (combined with voltammetry) and 31 P nuclear magnetic resonance spectroscopic studies. The efficiency of hydrogen evolution during artificial photosynthesis depends significantly on the ratio of photosensitiser and water reduction catalysts. At first sight, the results from irradiation experiments (gas chromatography and mass spectrometry) seem obvious, but show a considerable impact of secondary and tertiary amines within the pincer structure. The best result obtained for the palladium pincer complex was with a secondary amine as a proton relay, delivering a turnover number of 2237 after only 2.5 hours. In contrast the analogous water reduction catalyst with a methylated (tertiary) amine instead of a secondary one gives only 972 turnovers under the same experimental conditions, over the same time. For all photocatalytic measurements the amount of hydrogen is approximately 2.5-times higher when a secondary amine is used as the proton relay. The influences of these different amines on the activity of water reduction catalysts during irradiation experiments in H 2 O or D 2 O lead to evidence of a kinetic isotope effect, supporting a possible concerted proton electron transfer. DFT calculations of reaction enthalpies, activation energies and intrinsic reaction coordinates of the catalytic cycle support the high efficiency of the presented catalysts. In particular, results from secondary amines suggest new candidates as examples of the rarely known concerted proton electron transfer.

14 SOLAR ENERGY↗
DOE OSTI2025

Modeling active nematics via the nematic locking principle

Active nematic systems consist of rod-like internally driven subunits that interact with one another to form large-scale coherent flows. They are important examples of far-from-equilibrium fluids, which exhibit a wealth of nonlinear behavior. This includes active turbulence, in which topological defects in the nematic order braid around one another in a chaotic fashion. One of the most studied examples of active nematics consists of a dense two-dimensional layer of microtubules, crosslinked by kinesin molecular motors that inject extensile deformations into the fluid. Though numerous theoretical studies have modeled microtubule-based active nematics, no consensus has emerged on how to fully and quantitatively capture the features of the experimental system. Here, to better understand the theoretical foundations for modeling this system, we propose a fundamental principle we call the nematic locking principle—individual microtubules cannot rotate without all neighboring microtubules also rotating. Physically, this is justified by the high density of the microtubules, their elongated nature, and their corresponding steric interactions. We assert that the nematic locking principle holds throughout the majority of the material, but breaks down in the neighborhood of topological defects and other regions of low density. We derive the most general nematic transport equation consistent with this principle and also derive the most general term that violates it, introducing fracturing into the material. We then examine the standard Beris–Edwards approach, commonly used to model this system, and show that it violates the nematic locking principle throughout the majority of the material due to fracturing. We then propose a modification to the Beris–Edwards model that enforces nematic locking nearly everywhere. This modification shuts off fracturing except in regions where the order parameter (a proxy for density) is reduced. In these regions fracturing is turned on. The resulting simulations in turn show strong nematic locking throughout the bulk of the material, with narrow bands of fracturing, consistent with experimental observation. One additional advantage of enforcing nematic locking is that nontrivial stationary state solutions, common in Beris–Edwards simulations but not seen in experiments, are eliminated.

Mitchell, Kevin A. [Univ. of California, Merced, C↗
DOE OSTI2020

Bringing heterogeneity to the CMS software framework

The advent of computing resources with co-processors, for example Graphics Processing Units (GPU) or Field-Programmable Gate Arrays (FPGA), for use cases like the CMS High-Level Trigger (HLT) or data processing at leadership-class supercomputers imposes challenges for the current data processing frameworks. These challenges include developing a model for algorithms to offload their computations on the co-processors as well as keeping the traditional CPU busy doing other work. The CMS data processing framework, CMSSW, implements multithreading using the Intel Threading Building Blocks (TBB) library, that utilizes tasks as concurrent units of work. In this paper we will discuss a generic mechanism to interact effectively with non-CPU resources that has been implemented in CMSSW. In addition, configuring such a heterogeneous system is challenging. In CMSSW an application is configured with a configuration file written in the Python language. The algorithm types are part of the configuration. The challenge therefore is to unify the CPU and co-processor settings while allowing their implementations to be separate. We will explain how we solved these challenges while minimizing the necessary changes to the CMSSW framework. We will also discuss on a concrete example how algorithms would offload work to NVIDIA GPUs using directly the CUDA API.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

The Extension of the Hauser-Feshbach Fission Fragment Decay Model to Multi-chance Fission and its Application to 239 Pu

The Hauser-Feshbach fission fragment decay model, HF3D, calculates the statistical decay of fission fragments through both prompt and delayed neutron and γ-ray emissions in a deterministic manner. While previously limited to the calculation of only first-chance fission, the model has recently been extended to include multi-chance fission, up to neutron incident energies of 20 MeV. The deterministic decay takes as input prescission quantities–fission probabilities, pre-fission neutron energies, and the average energy causing fission– and post-scission quantities–yields in mass, charge, total kinetic energy, spin, and parity. From those fission fragment initial conditions, the full decay is followed through both prompt and delayed particle emissions. The evaporation of the prompt neutrons and γ rays is calculated through the Hauser-Feshbach statistical theory, taking into account the competition between neutron and γ-ray emission, conserving energy, spin, and parity. The delayed emission is taken into account using time-independent calculation using decay data. This whole formulation allows for the calculation of prompt neutron and γ-ray properties, such as multiplicities and energy distributions, both independent and cumulative fission yields, and delayed neutron observables, in a consistent framework. Here, we describe the implementation of multi-chance fission into the HF 3 D model, and show an example of prompt and delayed quantities beyond first-chance fission, using the example of neutron-induced fission on 239 Pu. This expansion represents significant progress in consistently modeling the emission of prompt and delayed particles from fissile systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Bayesian Monte Carlo Evaluation of Imperfect (n, 233 U) Data and Model

Conventional nuclear data evaluation methods using generalized linear least squares make the following assumptions: prior and posterior probability distribution functions (PDFs) of all model parameters and data are normal (Gaussian); the linear approximation is sufficiently accurate to minimize the cost function (even for nonlinear models); the model (e.g., of neutron cross section) and experimental data (including covariance data) are without defect and prior PDFs of parameters and measured data are known perfectly. Neglect of covariance between model parameters and measured data in conventional evaluations contributes to imperfections. These assumptions are inherent to the generalized linear least squares minimization method commonly used for resolved resonance region neutron cross section evaluations but are often not justified due to the presence of non-normal PDFs, nonlinear models (e.g., R-matrix formalism), and inherent imperfections in data and models (e.g., imperfect covariance data). Here, these assumptions are removed in a mathematical framework of Bayes’ theorem, which is implemented using the Metropolis-Hastings Monte Carlo method. Most importantly, new parameters are introduced to parameterize discrepancies between the theoretical model and measured data to quantify judgement about discrepancies or imperfections in a reproducible manner. An evaluation of 233U in the eV region using the ENDF-B/VIII.0 library and transmission data (Guber et al.) is presented, and posterior parameters are compared to those obtained by conventional evaluation methods. This example illustrates the effects of removing the most harmful assumption: that of model-data perfection.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

A generalized forward fit for neutron detectors with energy-dependent response functions

To date, most analysis of neutron time-of-flight data from inertial confinement fusion experiments has focused on the relatively small range of energies corresponding to the primary neutrons from DD and DT fusion, and have therefore employed instrument response functions (IRF’s) corresponding to monoenergetic 2.45-MeV or 14.03-MeV neutrons. For analysis of time-of-flight signals corresponding to broader ranges of neutron energies, accurate treatment of the data requires the use of an energy-dependent IRF. Here, this work describes interpolation of the IRF for neutrons of arbitrary energy, construction of an energy-dependent IRF, and application of this IRF in a forward fit via matrix multiplication. As an example of the application of this method, an analysis of synthetic data relevant to TT fusion experiments at the Omega Laser Facility is discussed. This example is used to illustrate the differences between a forward fit that uses an energy-dependent IRF and a forward fit that uses a monoenergetic IRF. Use of the energy-dependent IRF is shown to result in accurate inference of the fit parameters of interest.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Sample test array and recovery (STAR) platform at the National Ignition Facility

We have developed the Sample Test Array and Recovery (STAR) platform for the National Ignition Facility (NIF) for studying the thermal and hydrodynamic responses of materials in extreme environments. The STAR platform expands the range of obtainable fluences and quadruples the rate that materials experiments can be conducted at the NIF. Example configurations are demonstrated for fluences spanning 0.56–34 J/cm 2 with environmental isolation for post-shot material recovery and inspection and up to 1740 J/cm 2 without isolation, with surface heating rates of up to 2 × 10 14 K/s. Lastly, an example experiment involving thermally driven shock and spallation of aluminum alloy 7075 is briefly discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Overlap junctions for superconducting quantum electronics and amplifiers

Due to their unique properties as lossless, nonlinear circuit elements, Josephson junctions lie at the heart of superconducting quantum information processing. Previously, we demonstrated a two-layer, submicrometer-scale overlap junction fabrication process suitable for qubits with long coherence times. Here, we extend the overlap junction fabrication process to micrometer-scale junctions. This allows us to fabricate other superconducting quantum devices. For example, we demonstrate an overlap junction-based Josephson parametric amplifier that uses only two layers. This efficient fabrication process yields frequency-tunable devices with negligible insertion loss, a gain of ∼30 dB, and quantum limited noise performance. Compared to other processes, the overlap junction allows for fabrication with minimal infrastructure, high yield, and state-of-the-art device performance.

Bal, Mustafa (ORCID:0000000307516774)↗
DOE OSTI2021

Two-dimensional electronic–vibrational spectroscopy: Exploring the interplay of electrons and nuclei in excited state molecular dynamics

Two-dimensional electronic-vibrational spectroscopy (2DEVS) is an emerging spectroscopic technique which exploits two different frequency ranges for the excitation (visible) and detection (infrared) axes of a 2D spectrum. In contrast to degenerate 2D techniques, such as 2D electronic or 2D infrared spectroscopy, the spectral features of a 2DEV spectrum report cross correlations between fluctuating electronic and vibrational energy gaps rather than autocorrelations as in the degenerate spectroscopies. The center line slope of the spectral features reports on this cross correlation function directly and can reveal specific electronic-vibrational couplings and rapid changes in the electronic structure, for example. The involvement of the two types of transition moments, visible and infrared, makes 2DEVS very sensitive to electronic and vibronic mixing. 2DEV spectra also feature improved spectral resolution, making the method valuable for unraveling the highly congested spectra of molecular complexes. The unique features of 2DEVS are illustrated in this paper with specific examples and their origin described at an intuitive level with references to formal derivations provided. Although early in its development and far from fully explored, 2DEVS has already proven to be a valuable addition to the tool box of ultrafast nonlinear optical spectroscopy and is of promising potential in future efforts to explore the intricate connection between electronic and vibrational nuclear degrees of freedom in energy and charge transport applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

On closures for reduced order models - A spectrum of first-principle to machine-learned avenues

For over a century, reduced order models (ROMs) have been a fundamental discipline of theoretical fluid mechanics. Early examples include Galerkin models inspired by the Orr–Sommerfeld stability equation and numerous vortex models, of which the von Karman vortex street is one of the most prominent. Subsequent ROMs typically relied on first principles, like mathematical Galerkin models, weakly nonlinear stability theory, and two- and three-dimensional vortex models pioneered the data-driven proper orthogonal decomposition (POD) modeling. In early POD modeling, available data were used to build an optimal basis, which was then utilized in a classical Galerkin procedure to construct the ROM, but data have made a profound impact on ROMs beyond the Galerkin expansion. In this paper, we take a modest step and illustrate the impact of data-driven modeling on one significant ROM area. Specifically, we focus on ROM closures, which are correction terms that are added to the classical ROMs in order to model the effect of the discarded ROM modes in under-resolved simulations. Through simple examples, we illustrate the main modeling principles used to construct the classical ROMs, motivate and introduce modern ROM closures, and show how data-driven modeling, artificial intelligence, and machine learning have changed the standard ROM methodology over the last two decades. Finally, we outline our vision on how the state-of-the-art data-driven modeling can continue to reshape the field of reduced order modeling.

42 ENGINEERING↗
DOE OSTI2021

Stellarator optimization for good magnetic surfaces at the same time as quasisymmetry

A method is demonstrated to optimize a stellarator's geometry to eliminate magnetic islands and achieve other desired physics properties at the same time. For many physics quantities that have been used in stellarator optimization, including quasisymmetry, neoclassical transport, and magnetohydrodynamic stability, it is convenient to use a magnetic equilibrium representation that assures the existence of magnetic surfaces. However, this representation hides the possible presence of magnetic islands, which are typically undesirable. To include both surface-based objectives and island widths in a single optimization, two fixed-boundary equilibrium calculations are run at each iteration of the optimization: one that enforces the existence of magnetic surfaces (the Variational Moments Equilibrium Code) [S. P. Hirshman and J. C. Whitson, Phys. Fluids 26, 3553 (1983)] and one that does not (the Stepped Pressure Equilibrium Code) [Hudson et al., Phys. Plasmas 19, 112502 (2012)]. By penalizing the island residues in the objective function, the two magnetic field representations are brought into agreement during the optimization. Here, an example is presented in which, particularly on the surface where quasisymmetry was targeted, quasisymmetry is achieved more accurately than in previously published examples.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗