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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

BETO 2021 Peer Review - Biological Upgrading of Sugars (BUS) 2.3.2.105

The Biological Upgrading of Sugars (BUS) project directly targets the anaerobic conversion of lignocellulosic feedstocks into intermediate molecules readily upgradeable to fuel precursors. Recent efforts on the BUS project have a particular emphasis on the biological production of butyric acid, an intermediate that can be readily upgraded to sustainable aviation fuel, diesel blend-stocks, and high value chemicals. The BUS project approaches this direction through a combination of strain engineering, fermentation process engineering, development of novel separations technologies, and the design and build of pilot scale systems. Our ultimate project goal is to develop an integrated cost-effective process at pilot scale to achieve DOE's MYPP targets of $2.50/GGE. The major thrust of the BUS project over the last project cycle was on the development of integrated processes surrounding the anaerobic production of carboxylic acids using diverse Clostridium species. We developed and expanded genetic tools for several Clostridium species and rewired microbial metabolism in an attempt to maximize substrate utilization and flux towards butyric acid. We designed and built novel bioreactors with an in situ product recovery system enabling the biological production and recovery of highly purified acids. We leveraged this system to generate 100s of grams of acid from corn stover hydrolysate. In this presentation we highlight data surrounding our proposed process and accompanying results from technoeconomic and life-cycle analyses of our integrated process. Finally, we detail plans of our pilot scale reactor system that is in process and discuss our future routes towards achieving economically viable and sustainable diesel and jet blendstocks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Determining failure properties of as-received and hydrided unirradiated Zircaloy-4 from ring compression tests

An integrated experimental and computational approach was developed to determine the plastic strain at fracture and to investigate the fracture energy of as-received and hydrided unirradiated Zircaloy-4 nuclear cladding tubes in the hoop direction at room temperature from ring compression testing (RCT). This work builds on previous methods in the literature that were developed to obtain the mechanical properties of nuclear cladding before fracture (Young’s modulus, yield stress, and strain-hardening parameters) from experimental RCT results and extends the characterization of this material class to include material failure properties. Furthermore, a ductile damage approach was developed and implemented in a validated finite element model to predict material failure, evaluate fracture energy, and quantify the plastic strain at fracture initiation. The hydrogen content of the Zircaloy-4 specimens was varied up to 610 wppm when the failure became brittle. As expected, increasing hydrogen content caused embrittlement of the Zircaloy-4 samples tested and the plastic strain at fracture and fracture energy to decrease.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Direct Optical Lithography of CsPbX 3 Nanocrystals via Photoinduced Ligand Cleavage with Postpatterning Chemical Modification and Electronic Coupling

Microscale patterning of solution-processed nanomaterials is important for integration in functional devices. Colloidal lead halide perovskite (LHP) nanocrystals (NCs) can be particularly challenging to pattern due to their incompatibility with polar solvents and lability of surface ligands. Here, we introduce a direct photopatterning approach for LHP NCs through the binding and subsequent cleavage of a photosensitive oxime sulfonate ester (-C=N-OSOO-). The photosensitizer binds to the NCs through its sulfonate group and is cleaved at the N-O bond during photoirradiation with 405 nm light. This bond cleavage decreases the solubility of the NCs, which allows patterns to emerge upon development with toluene. Postpatterning ligand exchange results in photoluminescence quantum yields of up to 79%, while anion exchange provides tunability in the emission wavelength. Finally, the patterned NC films show photoconductive behavior, demonstrating that good electrical contact between the NCs can be established.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

The theory of transport in helical spin-structure crystals

Abstract We study helical structures in spin-spiral single crystals. In the continuum approach for the helicity potential energy the simple electronic band splits into two non-parabolic bands. For low exchange integrals, the lower band is described by a surface with a saddle shape in the direction of the helicity axis. Using the Boltzmann equation with the relaxation due to acoustic phonons, we discover the dependence of the current on the angle between the electric field and helicity axis leading to the both parallel and perpendicular to the electric field components in the electroconductivity. The latter can be interpreted as a planar Hall effect. In addition, we find that the transition rates depend on an electron spin allowing the transition between the bands. The electric conductivities exhibit nonlinear behaviors with respect to chemical potential µ . We explain this effect as the interference of the band anisotropy, spin conservation, and interband transitions. The proposed theory with the spherical model in the effective mass approximation for conduction electrons can elucidate nonlinear dependencies that can be identified in experiments. We find the excellent agreement between the theoretical and experimental data for parallel resistivity depending on temperature at the phase transition from helical to ferromagnetic state in a M n P single crystal. In addition, we predict that the perpendicular resistivity abruptly drops to zero in the ferromagnetic phase.

Physics↗
DOE OSTI2021

Enabling Long-range Exploration in Minimization of Multimodal Functions

We consider the problem of minimizing multi-modal loss functions with a large number of local optima. Since the local gradient points to the direction of the steepest slope in an infinitesimal neighborhood, an optimizer guided by the local gradient is often trapped in a local minimum. To address this issue, we develop a novel nonlocal gradient to skip small local minima by capturing major structures of the loss’s landscape in black-box optimization. The nonlocal gradient is defined by a directional Gaussian smoothing (DGS) approach. The key idea of DGS is to conducts 1D long-range exploration with a large smoothing radius along d orthogonal directions in Rd, each of which defines a nonlocal directional derivative as a 1D integral. Such long-range exploration enables the nonlocal gradient to skip small local minima. The d directional derivatives are then assembled to form the nonlocal gradient. We use the Gauss-Hermite quadrature rule to approximate the d 1D integrals to obtain an accurate estimator. The superior performance of our method is demonstrated in three sets of examples, including benchmark functions for global optimization, and two real-world scientific problems.

Zhang, Jiaxin↗
DOE OSTI2023

Operational Intelligence in the ATLAS Continuous Integration System

Describes the role of the ATLAS Continuous Integration (CI) System in the ATLAS offline software development infrastructure • Outlines the CI system components and processes • Details Operational Intelligence techniques to accelerate CI jobs and lower operating costs • Explains the Directed Acyclic Graph (DAG) approach in CI pipelines • Reports achieved improvements

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Adapting Existing Energy Planning, Simulation, and Operational Models for Resilience Analysis

Resilience is a topic receiving much attention in relation to energy systems, with particular attention being paid to the supply of electricity. As a result, research communities have proposed a plethora of candidate indicators and metrics for resilience, most of which remain immature at different scales and segments within the energy system. Given the complexity of resilience analyses and mitigation strategies, there is limited value in attempting to identify a single resilience metric, as no one metric can quantify resilience or its associated value for all stakeholders. Instead, a necessary focus of the research community should lie in implementing, testing, and validating resilience metrics and analysis approaches in energy sector models, which will be invaluable for informing resilience planning and investment decisions. Recognizing that implementing, testing, and validating resilience metrics are challenges that need to be addressed, the National Renewable Energy Laboratory (NREL) dedicated staff and time to researching how to effectively integrate resilience considerations into energy sector models and tools, as part of the Laboratory Directed Research and Development (LDRD) program. The overarching goal of the effort was to evaluate the data needs, methodologies, and outcomes - including consequences and/or changes in investment or operational decisions due to avoided consequences - based on resilience analysis in a range of existing tools. In particular, we selected five models originally built at NREL to explore non-resilience energy research questions to implement and exercise resilience metrics and analysis approaches.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

The Future of Renewable Energy Transmission: An Autonomous Energy Grid

The drastic price reduction in variable renewable energy, such as wind and solar, coupled with the ease of use of smart technologies at the consumer level, is driving dramatic changes to the power system that will significantly transform how power is made, delivered, and used. Distributed energy resources (DERs)—which can include solar photovoltaic (PV), fuel cells, microturbines, gensets, distributed energy storage (e.g., batteries, ice storage), and new loads (e.g., electric vehicles (EVs), light-emitting diode (LED) lighting, smart appliances, and electric heat pumps)—are being added to electric grids and causing bidirectional power flows and voltage fluctuations that can impact optimal control and system operation. Residential solar installations, customer battery systems, and EVs are all seeing rapid increases in deployments. With DER seeing such increased use, it is not unreasonable to imagine a residential electricity customer having at least five controllable DERs. In future electric grids, as more DERs are integrated, the number of active control points will be too much for current control approaches to effectively manage.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Manipulating high-temperature superconductivity by oxygen doping in Bi2Sr2CaCu2O8+δ thin flakes

Abstract Harnessing the fascinating properties of correlated oxides requires precise control of their carrier density. Compared to other methods, oxygen doping provides an effective and more direct way to tune the electronic properties of correlated oxides. Although several approaches, such as thermal annealing and oxygen migration, have been introduced to change the oxygen content, a continuous and reversible solution that can be integrated with modern electronic technology is much in demand. Here, we report a novel ionic field-effect transistor using solid Gd-doped CeO2 as the gate dielectric, which shows a remarkable carrier-density-tuning ability via electric-field-controlled oxygen concentration at room temperature. In Bi2Sr2CaCu2O8+δ (Bi-2212) thin flakes, we achieve a reversible superconductor–insulator transition by driving oxygen ions in and out of the samples with electric fields, and map out the phase diagram all the way from the insulating regime to the over-doped superconducting regime by continuously changing the oxygen doping level. Scaling analysis indicates that the reversible superconductor–insulator transition for the Bi-2212 thin flakes follows the theoretical description of a two-dimensional quantum phase transition. Our work provides a route for realizing electric-field control of phase transition in correlated oxides. Moreover, the configuration of this type of transistor makes heterostructure/interface engineering possible, thus having the potential to serve as the next-generation all-solid-state field-effect transistor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Learning Forecasts of Rare Stratospheric Transitions from Short Simulations

Abstract Rare events arising in nonlinear atmospheric dynamics remain hard to predict and attribute. We address the problem of forecasting rare events in a prototypical example, sudden stratospheric warmings (SSWs). Approximately once every other winter, the boreal stratospheric polar vortex rapidly breaks down, shifting midlatitude surface weather patterns for months. We focus on two key quantities of interest: the probability of an SSW occurring, and the expected lead time if it does occur, as functions of initial condition. These optimal forecasts concretely measure the event’s progress. Direct numerical simulation can estimate them in principle but is prohibitively expensive in practice: each rare event requires a long integration to observe, and the cost of each integration grows with model complexity. We describe an alternative approach using integrations that are short compared to the time scale of the warming event. We compute the probability and lead time efficiently by solving equations involving the transition operator, which encodes all information about the dynamics. We relate these optimal forecasts to a small number of interpretable physical variables, suggesting optimal measurements for forecasting. We illustrate the methodology on a prototype SSW model developed by Holton and Mass and modified by stochastic forcing. While highly idealized, this model captures the essential nonlinear dynamics of SSWs and exhibits the key forecasting challenge: the dramatic separation in time scales between a single event and the return time between successive events. Our methodology is designed to fully exploit high-dimensional data from models and observations, and has the potential to identify detailed predictors of many complex rare events in meteorology.

Finkel, Justin↗
DOE OSTI2025

Chromatin structures from integrated AI and polymer physics model

The physical organization of the genome in three-dimensional space regulates many biological processes, including gene expression and cell differentiation. Three-dimensional characterization of genome structure is critical to understanding these biological processes. Direct experimental measurements of genome structure are challenging; computational models of chromatin structure are therefore necessary. We develop an approach that combines a particle-based chromatin polymer model, molecular simulation, and machine learning to efficiently and accurately estimate chromatin structure fromindirectmeasures of genome structure. More specifically, we introduce a new approach where the interaction parameters of the polymer model are extracted from experimental Hi-C data using a graph neural network (GNN). We train the GNN on simulated data from the underlying polymer model, avoiding the need for large quantities of experimental data. The resulting approach accurately estimates chromatin structures across all chromosomes and across several experimental cell lines despite being trained almost exclusively on simulated data. The proposed approach can be viewed as a general framework for combining physical modeling with machine learning, and it could be extended to integrate additional biological data modalities. Ultimately, we achieve accurate and high-throughput estimations of chromatin structure from Hi-C data, which will be necessary as experimental methodologies, such as single-cell Hi-C, improve.

Biochemistry & Molecular Biology↗
DOE OSTI2024

Machine learning-guided design of direct methanol fuel cells with a platinum group metal-free cathode

Direct methanol fuel cells (DMFCs) offer a promising solution for clean electricity generation, particularly in small electronics and remote auxiliary power units. However, optimizing their efficiency and performance is challenging due to the complex interactions between various factors. Here, we present a novel approach that integrates experiments with machine learning to model and predict the performance of these fuel cells using atomically dispersed platinum group metal (PGM)-free catalysts at the cathode. Further, our machine learning models, trained on diverse input parameters, allow for the comprehensive optimization of DMFC performance prior to fabrication and testing. Through extensive experimental validation, we demonstrate that this data-driven approach accurately predicts key performance metrics, such as maximum power output and polarization curves. By combining our models with interpretable game-theory methods, we provide deep insights into the factors governing fuel cell performance, ultimately paving the way for the design of scalable and efficient DMFC technologies.

25 ENERGY STORAGE↗
DOE OSTI2024

Scaleup and Site-Specific Engineering Design for Global Thermostat Direct Air Capture Technology

The overall goal of the project is completion of an initial design of a commercial-scale, Carbon Capture, Utilization, and Storage Direct Air Capture (CCUS-DAC) plant design at three different sites that captures a net of at least 100,000 tonnes per year (TPY) carbon dioxide (CO 2 ) from the atmosphere and considers compression and conditioning of the captured CO 2 for purpose of pipeline transportation to different geological formation sites for deep well injection and underground storage. In addition to the leading system consisting of a scaled-up Global Thermostat DAC unit, overall plant design includes a combined Heat and Power (CHP) unit integrated with a conventional liquid amine-based carbon capture system (90% capture) and compression facilities. These are considered balance of plant (BOP) systems and are required to provide low carbon-intensity steam and power to the DAC process. A second approach involving provision of DAC units modified to directly capture emissions from the CHP unit was initially assessed as an alternative and it was determined to be less mature than considered approach and not included in the scaled-up plant design efforts. Three geographically diverse continental United States locations were selected to better understand the effect of local/regional ambient conditions on scaled-up DAC system performance and project costs: Bucks, Alabama (hot wet climate), Odessa, Texas (dry hot climate), and Goose Creek, Illinois (mid continental climate). The team focused on initial engineering design activities, including the development of project design criteria, initiation of site-specific studies and investigations, completion of DAC system process and equipment design, and definition of balance of plant (BOP) engineering. The purpose of the activities were to develop Technoeconomic Analysis (TEA), Life-Cycle Analysis (LCA), and Environmental, Health, and Safety (EH&S) analysis, and Business Case Analysis (BCA) to validate that the project engineering and scale-up plans of the DAC systems, at each of the three distinct case studies considered, are technically, economically, and environmentally feasible for commercial-scale operation.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Preliminary Design of a New Pulsed-Neutron Die--Away Experiments with Absorbers (IER-552 CED-1)

This report presents the preliminary design (CED-1) of IER-552, pulsed-neutron die-away (PNDA) experiments with absorbers, to be conducted by Lawrence Livermore National Laboratory (LLNL). The goal of the PNDA experiments with absorbing materials is to produce high-quality, low-cost integral benchmarks that can be used to validate cross sections that are high priority nuclear data for the Department of Energy’s Nuclear Criticality Safety Program (NCSP). PNDA experiments can be used to generate nuclear data validation benchmarks quickly and cheaply, as they do not require fissile material or a nuclear facility to conduct them. The original PNDA experiments were set up at LLNL under IER-501. Extending the PNDA experiments to include absorbing materials leverages existing facilities and resources at LLNL to validate cross sections, with a basic experiment design that uses a neutron generator to impinge a short, mono-energetic neutron pulse on a poisoned, moderating target sample. The neutron pulse lasts 100 µs, after which the neutron population in the sample reaches thermal equilibrium and later spatial equilibrium. In this fully equilibrized state, the neutron population has a characteristic decay-time eigenvalue. The eigenvalue can be used as an integral parameter to validate nuclear data involved with neutron scattering and absorption. Two observables can be measured: the neutron population and the population of secondary γ-rays produced by inelastic and capture reactions. This report explores the feasibility of both approaches. For γ-ray measurements, this allows for direct measurement of reactions of interest for validation. During the neutron burst time, inelastic (prompt) γ-rays dominate, and these data can be isolated for validation of neutron inelastic scattering data. After the pulse ends, neutron capture (delayed) γ-rays dominate and are produced by many reaction channels as neutrons slow down to thermal energies. Two sets of γ-ray spectra (inelastic, capture) can be produced for validation. Additionally, the time-dependent decay of the capture γ-ray population when the neutron population is thermalized and in its fundamental mode can be used for validation. Two experiments can be imagined where pulsed neutrons are used to validate the nuclear data of absorbing materials. The first integrates well into the existing PNDA testbed at LLNL. The absorber material would be introduced into a moderating target and the same neutron generator, neutron detectors, electronics, and shielding box used for IER-501 would be employed. From the same experimental setup, many absorbing materials can be validated by simply changing the neutron poison in the moderator. The only significant modification would be the introduction of a γ-ray detector. Such an experiment would primarily serve to validate nuclear data in the thermal energy range. The second kind of experiment would validate the fast and epithermal energy range. It would involve pulsing neutron into a bare assembly of the absorber material and measuring the die-away of neutrons. The fast leakage of such an assembly requires nanosecond neutron-generator pulse widths and fast detectors/electronics that could measure ~200 ns die-away curves. This kind of experiment would ideally be performed at a cyclotron, like that available at Lawrence Berkeley National Laboratory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Describing Function Analysis of Transformer Magnetizing Inductance for Direct Power Control of Back-to-Back Modular Multilevel Converters with Advanced Grid Support

This paper provides a detailed investigation into the application of describing function-based analysis for assessing transformer magnetizing inductance and its impact on system performance. The focus is on a back-to-back modular multilevel converter architecture, designed to interconnect systems operating at different frequencies. The study explores the implementation of a Direct Power Control strategy, examining its effects on transformer magnetizing inductance saturation and offering effective mitigation techniques. Furthermore, the integration of advanced grid support functionalities is highlighted, demonstrating how these enhancements bolster the converter's ability to improve grid stability and power quality, positioning it as a robust solution for modern power systems. The proposed approach is validated through extensive computer simulations based MAT LAB/Simulink domain, supported by significant case study results, confirming its practical effectiveness.

back-to-back modular multilevel converters (B2B- M↗
DOE OSTI2026

Electric field dependence of nanoscale cathodoluminescence inside Cr doped β-Ga 2 O 3 interfaces

Chromium (Cr) is a common impurity in β-Ga 2 O 3 crystals, where its characteristic R1 and R2 luminescence lines are susceptible to both the host crystal field and externally applied fields. Here, in this work, we demonstrate that the Cr cathodoluminescence (CL) quenches toward the bulk of the crystal but enhances with applied reverse bias, reflecting the effect of free carrier depletion with increasing electric field. Furthermore, we illustrate that the R1/R2 CL intensity ratio, measured as the integrated area ratio of R1 to R2, can be used as a direct probe of the electric field in a Ni-β-Ga 2 O 3 : Cr Schottky diode. This optical calibration method provides a complementary approach to conventional C–V and I–V measurements for determining electric field strength in the depletion region of β-Ga 2 O 3 -based Schottky diodes and can be extended to other semiconductors and multilayer device structures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A New Approach to Evaluate and Reduce Uncertainty of Model-Based Biodiversity Projections for Conservation Policy Formulation

Biodiversity projections with uncertainty estimates under different climate, land-use, and policy scenarios are essential to setting and achieving international targets to mitigate biodiversity loss. Evaluating and improving biodiversity predictions to better inform policy decisions remains a central conservation goal and challenge. A comprehensive strategy to evaluate and reduce uncertainty of model outputs against observed measurements and multiple models would help to produce more robust biodiversity predictions. We propose an approach that integrates biodiversity models and emerging remote sensing and in-situ data streams to evaluate and reduce uncertainty with the goal of improving policy-relevant biodiversity predictions. In this work, we describe a multivariate approach to directly and indirectly evaluate and constrain model uncertainty, demonstrate a proof of concept of this approach, embed the concept within the broader context of model evaluation and scenario analysis for conservation policy, and highlight lessons from other modeling communities.

essential biodiversity variables↗
DOE OSTI2024

Direct Air Capture Recovery of Energy for CCUS Partnership (DAC RECO 2 UP) Final Technical Report

The “Direct Air Capture Recovery of Energy for CCUS Partnership (DAC RECO 2 UP)” project employs a team approach and supports the U.S. Department of Energy Office of Fossil Energy and Carbon Management’s (DOE-FECM) goal to decrease the cost of capture through the testing of existing direct air capture (DAC) materials in integrated field units that produce a concentrated carbon dioxide (CO 2 ) stream of at least 95% purity. Solid-amine CO 2 adsorption-desorption contactor technology, proven in the laboratory, is undergoing high-fidelity design/validation. Recoverable energy is readily available from a large number of commercial locations where DAC can be deployed; therefore, advancing the fidelity of energy recovery to directly reduce the cost of DAC is a key project objective. In addition, many commercial facilities have low-concentration CO 2 vents that are uneconomical to treat alone but could provide more efficient mass and thermal transport to DAC systems with integrated energy recovery and flexible CO 2 treatment capabilities. Technology scale-up leverages past research and occurs in a commercially relevant environment at the National Carbon Capture Center. Prescreening techno-economic analysis, risk assessments, and life cycle analysis are being performed by experienced team members. Results of the project will address critical technical barriers that, when solved, will improve the capital and operating costs of DAC while validating commercial relevance of cost and product quality/need.

54 ENVIRONMENTAL SCIENCES↗