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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Optimization of anionic conductivity through the coexistence of ionomer cluster and backbone-backbone morphologies in anion exchange membranes

Random copolymers of poly(4-vinylpyridine) and polyisoprene were synthesized, and subsequently quaternized with 1-alkylbromides. The number of carbons on the pendant side-chain of the resultant comb-shaped polymer, n, ranged from 2-8. The comb-shaped polymers were crosslinked employing thiol-ene chemistry to give mechanically robust ion conducting membranes. Analysis by wide and medium-angle X-ray scattering show three morphology regimes that are dependent on the number of carbons on the pendant side-chains. When n = 2, ionomer cluster morphology was dominant, when n = 8 backbone-backbone morphology was dominant, and when n = 3-6, the membrane showed a coexistence of both ionomer cluster and backbone-backbone morphologies. Evaluation of the water uptake of the membranes showed a maximum water uptake per cation of 9.5 when n = 5 at 95% relative humidity (RH) and 60 degrees C. Finally, conductivity of the samples characterized by electrochemical impedance spectroscopy showed bromide conductivity as high as 110 mS/cm when n = 3 at 95% RH and 90 degrees C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Greenhouse gas emissions reduction strategies that maximize portfolio-wide life cycle cost reduction, resilience, and environmental justice benefits

While strategies to achieve net-zero emissions at an individual site are well understood, new analysis methods are required for organizations seeking to achieve net-zero across multiple facilities, each with concurrent priority goals. At a portfolio level, distinct locations present varied challenges that cannot be addressed through singular solutions, and competing goals can take precedence with the assumption that net-zero emissions strategies deter from energy resilience and cost savings, therefore negatively impacting nearby communities. This study tests these assumptions by analyzing 16 diverse sites (varying in size, climate, and energy use) to identify strategies that reduce emissions and assess the impact these strategies have on life cycle costs, resilience, and communities with environmental justice concerns. Methods were developed to approximate missing information essential to net-zero evaluation. Established methods were augmented to evaluate life cycle costs, resilience, and environmental justice impacts across a set of strategies and accommodate the multi-criteria analyses. Potential benefits from identified strategies were quantified using site characteristics and a set of corresponding metrics. The net-zero analysis found that 11 sites could use on-site strategies to eliminate all but 2% of emissions generated. The remaining emissions can be offset, for instance through sequestration, executed at the portfolio scale. On-site carbon-free energy was found to reduce 51% of emissions across all sites; efficiency reduced 19% of emissions; sequestration 16%; procured carbon-free energy 15%; fuel switching 1.6%; and fleet electrification 1.3%. Building electrification, however, increased emissions by 4.4%. Different strategies also provide cost, resilience, and/or environmental justice benefits—the degree to which varies with individual site conditions. The findings indicate an advantage to considering the strategies as a comprehensive set, which leads to co-benefits, both in the ability to achieve net-zero goals and in advancing other goals. The results present the case for comprehensive advanced planning at the portfolio level to prioritize investments that will balance the minimization of emissions and life cycle cost with the maximization of resilience and environmental justice benefits. The novel methods for evaluation and integration, valuation of benefits, and consideration at the portfolio scale allow organizations to select investments that simultaneously address multiple key priorities.

Net-Zero Emissions↗
DOE OSTI2021

Making Data-Driven Policy Decisions for the Nation’s First Building Energy Performance Standards

Nearly every major U.S. city has committed itself to ambitious climate action goals – for Washington, DC this means a 50 percent reduction in greenhouse gases by 2032 and carbon neutrality by 2050. In support of these goals, Washington, DC has passed one of the most aggressive and practical climate action bills in the nation—with the Clean Energy DC Omnibus Act, DC became the first city in the U.S. to adopt energy performance standards for existing buildings. DC’s Building Energy Performance Standards (BEPS) require energy efficiency improvements for all commercial and multifamily buildings that do not meet a sector-specific minimum ENERGY STAR score or equivalent metric, with iterative compliance cycles every five years that will accelerate the pace of whole building retrofits. This paper explores this revolutionary policy framework and uses two data analysis projects that DC conducted to evaluate the potential impact of the BEPS and move towards carbon neutrality. First, we analyze the potential energy savings and greenhouse gas reductions, as well as potential cost impacts, from the implementation of a BEPS policy in DC We then examine the role of BEPS in a carbon neutrality strategy, how BEPS savings iterate over time, and what additional existing building improvements will be driven by the gravitational pull of new building codes on median performance. The paper highlights the benefits and limitations of such data-driven approaches to support policy decisions. Finally, we will review ongoing BEPS implementation, including expected policy directions, critical supportive programs, and lessons learned to date.

Bergfeld, Katie↗
DOE OSTI2024

Accuracy, transferability, and computational efficiency of interatomic potentials for simulations of carbon under extreme conditions

Large-scale atomistic molecular dynamics (MD) simulations provide an exceptional opportunity to advance the fundamental understanding of carbon under extreme conditions of high pressures and temperatures. However, the fidelity of these simulations depends heavily on the accuracy of classical interatomic potentials governing the dynamics of many-atom systems. Here, this study critically assesses several popular empirical potentials for carbon, as well as machine learning interatomic potentials (MLIPs), in their ability to simulate a range of physical properties at high pressures and temperatures, including the diamond equation of state, its melting line, shock Hugoniot, uniaxial compressions, and the structure of liquid carbon. Empirical potentials fail to accurately predict the behavior of carbon under high pressure–temperature conditions. In contrast, MLIPs demonstrate quantum accuracy, with Spectral Neighbor Analysis Potential (SNAP) and atomic cluster expansion (ACE) being the most accurate in reproducing the density functional theory results. ACE displays remarkable transferability despite not being specifically trained for extreme conditions. Furthermore, ACE and SNAP exhibit superior computational performance on graphics processing unit-based systems in billion atom MD simulations, with SNAP emerging as the fastest. In addition to offering practical guidance in selecting an interatomic potential with a fine balance of accuracy, transferability, and computational efficiency, this work also highlights transformative opportunities for groundbreaking scientific discoveries facilitated by quantum-accurate MD simulations with MLIPs on emerging exascale supercomputers.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Comprehensive Review and Qualitative Analysis of Micro-Combined Heat and Power Modeling Approaches

Concurrent production of electrical and thermal energy from a Combined Heat and Power (CHP) device is an attractive tool to address the growing energy needs of the planet. Micro CHP (µCHP) systems can reduce a building’s primary energy consumption, reduce carbon footprint, and enhance resiliency. Modeling of the µCHP helps understand the system from multiple perspectives and helps discover errors earlier, improves impact analysis and simulation of system solutions for ease of integration with the building. Consequently, there is a need for analysis of the impact of µCHP modeling approach on its reliability and flexibility. The primary objective of this paper is to review the state-of-the art models in the µCHP space with a focus towards internal combustion engine as the primary mover (PM) and limit the study to system modeling, calibration, and validation methodologies. Based on the analysis, recommendations for further model considerations and refinements are presented.

42 ENGINEERING↗
DOE OSTI2021

Metals and methylotrophy: Via global gene expression studies

A number of minerals, such as copper, cobalt, and rare earth elements (REE), are essential modulators of microbial one-carbon metabolism. This chapter provides an overview of the gene expression study design and analysis protocols for uncovering REE-induced changes in methylotrophic bacteria. By interrogating relationships and differences in total gene expression induced by mineral micronutrients, a deeper understanding of gene regulation at a systems scale can be gained. With careful design and execution of RNA-sequencing experiments, thorough processing and assessment of read quality can be utilized to assess and adjust for possible biases. Here, by ensuring only quality data are utilized in downstream processes, differential gene expression, overrepresented analyses, and gene-set enrichment analyses provide reliable and reproducible representation of pathways and functions which are being affected by changes in environmental conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Metal-supported solid oxide fuel cells operating with reformed natural gas and sulfur

The performance, long-term durability, and thermal cycling tolerance of metal supported solid oxide fuel cells (MS-SOFCs) operating with natural gas reformate fuels is assessed. Symmetric MS-SOFCs with composite SDC-Ni anode catalysts and PrO x cathode catalysts are operated with simulated natural gas steam-reformate and partial-oxidation-reformate fuels with 1 ppm and 5 ppm of sulfur. Cells are operated for 1000 h with initial degradation rates similar to humidified H 2 , and initial performance differences attributed to the lower H 2 concentration in reformate fuels. Additionally, cells tolerate many aggressive thermal cycles with sulfur present, with minimal impact on performance. Post mortem analysis suggests that Ni particle coarsening and Cr deposition are sources of degradation, while carbon and sulfur deposition are not observed. Overall, MS-SOFCs operate successfully with reformed natural gas.

08 HYDROGEN↗
DOE OSTI2021

MuSIC@Indiana: An effective tool for accurate measurement of fusion with low-intensity radioactive beams

The design, construction, and characterization of the Multi-Sampling Ionization Chamber, MuSIC@Indiana, are described. This detector provides efficient and accurate measurement of the fusion cross-section at near-barrier energies. The response of the detector to low-intensity beams of 17,18 O, 19 F, 23 Na, 24,26 Mg, 27 Al, and 28 Si at E lab 50–60MeV was examined. MuSIC@Indiana was commissioned by measuring the 18 O+ 12 C fusion excitation function for 11 < E cm < 20 MeV using CH 4 gas. Here, a simple, effective analysis cleanly distinguishes proton capture and two-body scattering events from fusion on carbon. With MuSIC@Indiana, measurement of 15 points on the excitation function for a single incident beam energy is achieved. The resulting excitation function is shown to be in good agreement with literature data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Methane Catalytic Pyrolysis by Microwave and Thermal Heating over Carbon Nanotube-Supported Catalysts: Productivity, Kinetics, and Energy Efficiency

Methane catalytic pyrolysis, which is the reaction to produce hydrogen and carbon without emitting CO 2 , represents an approach for decarbonization using natural gas as an energy resource. In this work, the endothermic pyrolysis reaction was carried out under two heating scenarios: convective thermal heating and microwave-driven irradiative heating. The pyrolysis reaction was conducted at 550-600 °C over carbon nanotube-supported Ni-Pd and Ni-Cu catalysts. On both catalysts, an enhanced methane conversion rate was observed under microwave irradiation. The enhanced catalytic activity was hypothetically caused by the presence of free electrons in the carbon atoms within CNT that enabled the CNT support to absorb microwave energy effectively and to be heated efficiently by microwave. The microwave catalytic pyrolysis has shown improvement in kinetics, where the apparent activation energy dropped from 45.5 kJ/mol under conventional convective heating to 24.8 kJ/mol under microwave irradiation. When the methane conversion rate is increased by 37 %, the microwave power consumption only changed by 10.8 %. The research demonstrated the potential of transforming natural gas to clean hydrogen and value-added carbon in a more energy-efficient way. Process simulation and techno-economic analysis showed that potentially hydrogen minimum selling price of about $1 /kg H 2 could be achieved.

03 NATURAL GAS↗
DOE OSTI2020

Internal Fragments Generated by Electron Ionization Dissociation Enhance Protein Top-Down Mass Spectrometry

Top-down proteomics by mass spectrometry (MS) involves the mass measurement of an intact protein followed by subsequent activation of the protein to generate product ions. Electron-based fragmentation methods like electron capture dissociation and electron transfer dissociation are widely used for these types of analyses. Recently, electron ionization dissociation (EID), which utilizes higher energy electrons (>20 eV) has been suggested to be more efficient for top-down protein fragmentation compared to other electron-based dissociation methods. In this paper, we demonstrate that the use of EID enhances protein fragmentation and subsequent detection of protein fragments. Protein product ions can form by either single cleavage events, resulting in terminal fragments containing the C-terminus or N-terminus of the protein, or by multiple cleavage events to give rise to internal fragments that include neither the C-terminus nor the N-terminus of the protein. Conventionally, internal fragments have been disregarded, as reliable assignments of these fragments were limited. Here, we demonstrate that internal fragments generated by EID can account for ~20–40% of the mass spectral signals detected by top-down EID-MS experiments. By including internal fragments, the extent of the protein sequence that can be explained from a single tandem mass spectrum increases from ~50 to ~99% for 29 kDa carbonic anhydrase II and 8.6 kDa ubiquitin. When searching for internal fragments during data analysis, previously unassigned peaks can be readily and accurately assigned to confirm a given protein sequence and to enhance the utility of top-down protein sequencing experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

SOLPS analysis of the necessary conditions for detachment cliff

SOLPS modeling including full cross-filed drifts is used, for the first time, to reproduce the step-like detachment onset observed in the DIII-D tokamak previously simulated with UEDGE [Jaervinen A. E. et al., 2018 Phys. Rev. Lett.121 075001], and to further investigate the underlying physics processes. The SOLPS analysis reveals a strong interplay between the E×B drift-driven flows and carbon radiation in DIII-D. The modeling shows that the high confinement H-mode facilitates the formation of such a detachment cliff due to the narrow SOL width and hence steep radial gradients near the separatrix, which enhances the poloidal E×B drift. Furthermore, the SOLPS modeling indicates that carbon radiation also plays a key role in the formation of the detachment cliff in DIII-D without additional impurity seeding. These findings may have significant implications for the control and maintenance of divertor detachment for the steady-state operation of high-power fusion devices.

Physics - Plasma physics↗
DOE OSTI2021

NRAP-Open-IAM: Open Wellbore Component (V.2.0)

The Open Wellbore component of NRAP-Open-IAM is applicable to the calculation of Area of Review at a carbon storage site and fast estimation of dense gas dispersion from multiple continuous CO 2 surface leakage sources for risk assessment. The Open Wellbore Component of NRAP-Open-IAM is a lookup table model based on the drift-flux approach. The National Research Assessment Partnership’s second-generation integrated assessment model, NRAP-Open-IAM, is open-source software written in Python for use in performance and quantitative risk assessment of geologic carbon storage (GCS) systems. The look-up table for open well leakage is an updated version the previous model which provides finer resolution of reservoir depth and more accurate fluid properties than the previous open well look-up table, especially in calculating the gas (CO 2 -rich) phase properties. The component model input parameters include the reservoir transmissivity, aquifer transmissivity, brine salinity, well radius, and well top and bottom depths. The reservoir transmissivity and brine salinity were set to values consistent with the reservoir component, and the well top and bottom depths varied with location. The possible outputs from the Open Wellbore component are leakage rates of CO 2 and brine to either an aquifer or atmosphere, depending on the depth of the well top. Several python test scripts are presented that demonstrate that the Open Wellbore component works correctly. Use of the open wellbore model in NRAP-Open-IAM may result in a large CO 2 leakage rates, comparable to the leakage rates of CO 2 blow out.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

An Advanced Meso-Scale Peridynamic Modeling Technology using High-Performance Computing for Cost-Effective Product Design and Testing of Carbon Fiber Reinforced Polymer Composites in Light-weight Vehicles

We study a peridynamic composite modeling technology based on the discontinuous Galerkin finite element method, implemented in the commercial LS-DYNA software, for modeling and prediction of failure in carbon fiber reinforced polymer composites. The proposed technology is developed for the material failure analysis at the meso-scale, which provides the prevailing fiber-matrix interaction mechanism, without adoption of the representative volume element method and thus avoiding complicated numerical calibration procedures. Three types of experimental tests—in-plane coupon test, out-of-plane coupon test, and a component crash test—are simulated in a high-performance computing environment to assess the performance of the proposed peridynamic composite modeling technology.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electron Beam Treatment of Ballast Water

Members from the Great Waters Research Collaborative (GWRC), a project of the University of Wisconsin-Superior (UWS) Lake Superior Research Institute (LSRI), will be bringing two water types to simulate the electron beam removal process for ballast waters. These two types are named low challenge and high challenge. The Low Challenge water is highly transparent water with very low concentration of total suspended solids and dissolved organic carbon. The High Challenge water is like Duluth-Superior Harbor water with low transparency and higher concentration of total suspended solids and dissolved organic carbon. Both water types will undergo a series of applied electron beam radiations and analysis to meet ballast water discharge standards. For the analysis there are standard test organisms that will be evaluated for mortality. Heterotrophic bacteria (E. coli) along with Selenastrum capricornutum will be used and then Eucyclops spp. (or Hyalella azteca) and Daphnia magna will also be evaluated.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Quantifying air quality co-benefits to industrial decarbonization: the local Air Emissions Tracking Atlas

Many decarbonization technologies have the added co-benefit of reducing short-lived climate pollutants, such as particulate matter (PM), nitrogen oxides (NO x ), and sulfur dioxide (SO 2 ), creating a unique opportunity for identifying strategies that promote both climate change solutions and opportunities for air quality improvement. However, stakeholders and decision-makers may struggle to quantify how these co-benefits will impact public health for the communities most affected by industrial air pollution. To address this problem, the LOCal Air Emissions Tracking Atlas (LOCAETA) fills a data availability and analysis gap by providing estimated air quality benefits from industrial decarbonization options, such as carbon capture and storage (CCS). These co-benefits are calculated using an algorithm that connects disparate datasets that separately report greenhouse gas emissions and other pollutants at U.S. industrial facilities. Version 1.0 of LOCAETA displays the estimated primary PM 2.5 emission reduction co-benefits from additional pretreatment equipment for CCS on industrial and power facilities across the state of Louisiana, as well as the potential for VOC and NH 3 generation. The emission reductions are presented in the tool alongside facility pollutant emissions information and relevant air quality, environmental, demographic, and public health datasets, such as air toxics cancer risk, satellite and in situ pollutant measurements, and population vulnerability metrics. LOCAETA enables regulators, policymakers, environmental justice communities, and industrial and commercial users to compare and contrast quantifiable public health benefits due to air quality impacts from various climate change mitigation strategies using a free and publicly-available tool. Additional pollutant reductions can be calculated using the same methodology and will be available in future versions of the tool.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Impacts of Curing-Induced Phase Segregation in Silicon Nanoparticle-Based Electrodes

We report the investigation of silicon nanoparticle composite anodes for Li-ion batteries, using a combination of two nm-scale atomic force microscopy-based techniques: scanning spreading resistance microscopy for electrical conduction mapping and contact resonance and force volume for elastic modulus mapping, along with scanning electron microscopy-based energy dispersion spectroscopy, nanoindentation, and electrochemical analysis. Thermally curing the composite anode—made of polyethylene oxide-treated Si nanoparticles, carbon black, and polyimide binder—reportedly improves the anode electrochemical performance significantly. This work demonstrates phase segregation resulting from thermal curing, where alternating bands of carbon and silicon active material are observed. This electrode morphology is retained after extensive cycling, where the electrical conduction of the carbon-rich bands remains relatively unchanged, but the mechanical modulus of the bands decreases distinctly. These electrical and mechanical factors may contribute to performance improvement, with carbon bands serving as a mechanical buffer for Si deformation and providing electrical conduction pathways. This work motivates future efforts to engineer similar morphologies for mitigating capacity loss in silicon electrodes.

25 ENERGY STORAGE↗
DOE OSTI2024

CCUS Perspectives: Assessing Historical Contexts, Current Realities, and Future Prospects

CCUS technologies are crucial solutions for mitigating climate change by reducing CO2 emissions from industrial operations and energy sectors. This review critically examines the current state of CCUS technologies, and highlights advancements, challenges, regulatory frameworks, and future directions. It comprehensively analyzes carbon capture methods, such as pre-combustion, post-combustion, and oxy-fuel combustion capture, while comparing their efficiencies and limitations. The review also explores carbon utilization techniques, such as direct and indirect utilization, emphasizing their potential applications and technological constraints. Additionally, it assesses various carbon storage methods, focusing on geological, ocean, and mineralization storage, and discusses their capacity, feasibility, and environmental implications. The study reviews the policy and regulatory frameworks, economic viability, market trends, and environmental sustainability of CCUS. By identifying research gaps and recommending future research priorities, this review aims to guide the development of more efficient/effective, and cost-effective CCUS technology, ensuring their role in a sustaining low-carbon future. This review provides a forward-looking perspective, a critical and interdisciplinary analysis that assesses the current state of CCUS technologies, and further provides a roadmap for future development.

Energy & Fuels↗