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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Carbon Block Density

Within the framework of the Neutron Target Demonstrator about 1 m 3 of reactor grade graphite is available at LANSCE. In order to evaluate its suitability as a moderator, knowledge about the exact density is important, since it strongly affects the average time neutrons spend in the volume. The graphite is available in different shapes. A brief analysis was done on three different carbon blocks to determine the density of the material as well as the uncertainty in that measurement.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Updated Manufactured Cost Analysis for Proton Exchange Membrane Water Electrolyzers

Enabling rapid and extensive decarbonization within the electric power and industrial sectors is likely to require high levels of renewable energy deployment, supported by technologies that store and transform renewable electricity into other useful forms. Within hard to decarbonize sectors such as organic chemicals and heavy-duty transportation, the use of low-carbon intensity hydrogen as a fuel and chemical building block is emerging as a near-term alternative to reduce their fossil-fuel dependency. Water splitting electrolysis to produce hydrogen requires only water and electricity as inputs, eliminating the use of natural gas in steam methane reforming, which is the conventional hydrogen production pathway. When powered by low-carbon electricity, electrolysis represents an important pathway towards cross-sectoral decarbonization.

08 HYDROGEN↗
DOE OSTI2026

Carbon source-induced changes in the transcriptional landscape of Novacetimonas hansenii

Novacetimonas hansenii is a model organism for bacterial cellulose (BC) production, a biopolymer with broad industrial applications. To better understand its carbon source-dependent metabolism, we conducted the first time-resolved transcriptomic analysis of N. hansenii ATCC 23769 grown on five carbon sources (glucose, fructose, mannitol, galactose, and sucrose) across five time points (24–120h). Glucose, fructose, and mannitol supported growth and efficient BC production, whereas galactose and sucrose resulted in poor yields, likely due to limited transport and enzymatic capacity. Solid-state NMR revealed that cellulose crystallinity and polymorphism were carbon source-dependent, with reduced bcsD expression correlating with lower crystallinity. Transcriptomic profiling showed distinct metabolic responses. Cultures containing glucose and mannitol activated core metabolic pathways, fructose induced a delayed adaptive shift, and galactose and sucrose triggered stress-related gene expression. These results highlight the metabolic plasticity of N. hansenii and offer insights for enhancing BC production through carbon source optomization.

Bacterial cellulose↗
DOE OSTI2021

Big Adaptive Rotor Phase I (Final Report)

The Big Adaptive Rotor (BAR) project was initiate by DOE in 2018 with the goal of identifying novel technologies that can enable large (>100m) blades for low specific power (SP) turbines. Five distinct tasks were completed to achieve this goal: 1. Assess trends, impacts, and value of low-SP turbines, 2. Wind turbine blade cost reduction roadmap study, 3. Research and Development (R&D) opportunity screening, 4. Detailed design and analysis, and 5. Low-cost carbon fiber. These tasks were completed by the national lab team consisting of Sandia National Laboratories (SNL), the National Renewable Energy Laboratory (NREL), and Lawrence Berkeley National Laboratory (LBNL). The objective of Task 1 was to assess the historical trends of low-SP of onshore deployments, and to assess the impact and value of low-SP turbines. Analysis under this task showed that there is significant value for low-SP turbines, especially in markets where there is a higher saturation of wind energy on the grid. This has to do with the fact that low-SP turbines have increased capacity factors, and can contribute more reliable energy to the grid, even in lower wind conditions. This bodes well as higher renewable scenarios are likely in the coming years. Task 2 was a detailed analysis on the logistical challenges of deploying very large (>100m) onshore blade. This work was completed by experts at DNV-GL. The report looked at various ways to get around the current transportation constraints which are estimated to be around 75m in length. The report concluded that there are viable solutions to this issue including: segmented blades (which the industry is already pursuing), lighter than air (LTA) transportation, on-site manufacturing, and controlled bending of blades on rail. The final option was recommended for further analysis and study by DOE and the national labs because keeping a single piece blade reduces manufacturing and operations and maintenance (O&M) costs. Task 3 focused on identifying novel concepts that are capable of enabling a cost effective 5MW 206m rotor for onshore deployment. The findings from the first two tasks were considered in the analysis, in that the concepts identified must be able to overcome the transportation logistics challenges. Around 20 concepts were identified and evaluated by experts within the industry. Additionally, science and engineering challenges were identified for each concept. Based on these evaluations six concepts were deemed the most impactful and were selected for further analysis in Task 4. The concepts were: highly flexible rail transportable blades, downwind rotors, distributed aerodynamic control (DAC) devices, inflatable blade, bi-wing blade, and 4/5 bladed rotors. Task 4 conducted detailed design, optimization, and analysis on the selected BAR concepts. A modeling gaps analysis was conducted, and modeling improvements were implemented that allowed for the study and design of the novel concepts. The BAR team established a set of baseline designs by which to compare the selected designs through a technoeconomic analysis. It was found that the highly flexible rail transportable blade, the downwind rotor, and the DAC devices have the most promise to deliver the BAR targets. A Phase II for BAR has been proposed to further mature these concepts and address the open science and engineering challenges identified in Task 3. Task 5 conducted research on optimized carbon fiber materials that were used throughout the BAR Phase I project. Overall, the BAR project has identified low-SP turbines as important to continued LCOE reductions for onshore turbines. Furthermore, the project has identified viable solutions to the technical and logistical challenges to realizing these goals. The most promising technologies that were identified in Phase I of the project will be further matured and de-risked in Phase II of the BAR project.

17 WIND ENERGY↗
DOE OSTI2020

Techno-Economic Analysis for GTI's Compact Hydrogen Generator

A technoeconomic analysis of the compact hydrogen generator compared to a traditional steam methane reformer (SMR) was performed for both processes with and without carbon capture. The project goal for the technoeconomic analysis was to demonstrate a minimum of 20% lower CAPEX and 15% lower levelized cost of hydrogen compared to SMR with and without carbon capture. GTI obtained baseline capital and costs for the SMR with and without and methodology to calculate the levelized cost of hydrogen from an IEAGHG Technical Report: 2017-02 Techno-Economic Evaluation of SMR Based Standalone (Merchant) Hydrogen Plant with CCS. This methodology was then applied to GTI’s compact hydrogen generator using direct material costs previously obtained from a reputable engineering procurement and construction company, CB&I Howe-Baker. The analysis was performed for plants producing 90MMSCFD (million standard cubic feed per day) of hydrogen. Direct material costs were converted to total installed costs and total capital requirements using the same multiplying factors for both processes. We have found that the direct materials cost of the compact hydrogen generator is less than half the direct materials cost required for SMR without capture, and about one quarter the direct materials cost of SMR with carbon capture. This low materials cost translates into a significant CAPEX savings and lower levelized cost of hydrogen that exceed the goals of the techno-economic assessment. We have found that the CHG has a 43% lower installed cost and capital requirement compared to SMR without capture, that results in a levelized cost of hydrogen that is 19% lower than SMR. When 90% CO2 capture is added to the plants, the advantages is even better. The CHG has a 51% lower installed and capital requirement compared to SMR with capture, resulting in a 28% lower levelized cost of hydrogen. A sensitivity analysis was performed and showed natural gas feedstock cost and discount rate to be the main contributors to hydrogen price sensitivity. Given these significant cost advantages, GTI is encouraged to continue to develop the technology and market the economic advantages as well as the efficiency gains and ability to inherently capture CO2.

08 HYDROGEN↗
DOE OSTI2025

Carbon Dioxide Removal Measurement, Reporting, and Verification Simulation toolkit (CDR MRVSim) v0.1

CDR MRVSim is a statistical software toolkit for techno-economic analysis of measurement, reporting, and verification of multiple carbon dioxide removal technologies. The current version applies Monte Carlo simulation to existing datasets estimate the cost and uncertainty of measuring the soil organic carbon (SOC) content of agricultural land, accounting for multiple sources of uncertainty, using data from field measurements. We are planning to incorporate enhanced rock weathering and other technologies into the software. The current model leverages existing data to characterize underlying variability in soil organic carbon and related parameters, including bulk density, in an agricultural field attempting to increase its SOC. We then simulate baseline and post-intervention "measurement campaigns" in which some number of SOC and bulk density measurements are conducted using a selected technology. This enables estimates of the cost and accuracy of measuring changes in SOC in the simulated field. The primary advantages over similar software are: 1) ability to quantify tradeoffs between cost and uncertainty in MRV across a range of possible MRV approaches 2) focus on guiding development of novel sensors by determining desirable sets of characteristics

Sherwin, Evan [Lawrence Berkeley National Laborato↗
DOE OSTI2021

Tribocatalytically-activated formation of protective friction and wear reducing carbon coatings from alkane environment

Minimizing the wear of the surfaces exposed to mechanical shear stresses is a critical challenge for maximizing the lifespan of rotary mechanical parts. In this study, we have discovered the anti-wear capability of a series of metal nitride-copper nanocomposite coatings tested in a liquid hydrocarbon environment. The results indicate substantial reduction of the wear in comparison to the uncoated steel substrate. Analysis of the wear tracks indicates the formation of carbon-based protective films directly at the sliding interface during the tribological tests. Raman spectroscopy mapping of the wear track suggests the amorphous carbon (a-C) nature of the formed tribofilm. Further analysis of the tribocatalytic activity of the best coating candidate, MoN-Cu, as a function of load (0.25–1 N) and temperature (25 °C and 50 °C) was performed in three alkane solutions, decane, dodecane, and hexadecane. Results indicated that elevated temperature and high contact pressure lead to different tribological characteristics of the coating tested in different environments. The elemental energy dispersive x-ray spectroscopy analysis and Raman analysis revealed formation of the amorphous carbon film that facilitates easy shearing at the contact interface thus enabling more stable friction behavior and lower wear of the tribocatalytic coating. These findings provide new insights into the tribocatalysis mechanism that enables the formation of zero-wear coatings.

36 MATERIALS SCIENCE↗
DOE OSTI2026

CO2 Handling & Electrolyzer Efficiency Scaling Evaluator

CHEESE is an interactive dashboard tool for estimating the performance and material requirements of carbon dioxide electrolysis systems. It helps users evaluate how electrode area, current density, product selectivity, gas flow, cell voltage, and the number of cells in a stack affect system operation. The dashboard provides simple and advanced modes so it can be used for both quick estimates and more detailed engineering analysis. Users can estimate product output, carbon dioxide use, electrical power, electrode area, gas and liquid flow rates, energy efficiency, material cost per test, and the effect of scaling from a single cell to a multi cell stack. It also includes tools for examining carbon balance, equipment durability, component replacement, and changes in performance over time. This is intended to help both academia and industry researchers who are either getting into CO2 electrolysis on lab-scale or are trying to establish a larger footprint. CHEESE presents results through tables, charts, and simplified cell and stack diagrams. It is intended to support research planning, experimental design, comparison of operating conditions, and early stage scale up studies.

Prajapati, Aditya [Lawrence Livermore National Lab↗
DOE OSTI2025

High-pressure reduction of carbon dioxide in reactive liquid mixtures

Density-functional theory based molecular-dynamics simulations were used to investigate high-pressure chemical reactions in liquid mixtures of CO 2 with several elements (Si, Mn, and Fe) at high temperatures of 2000-3000 K. Our ab initio simulations indicate that these reactant elements can reduce CO 2 to C at high pressures (20 GPa) leading to the formation of C-C chains, with Si by far the most effective carbon-reducing agent. A combined chemical analysis using Bader charge analysis and Crystal Orbital Hamilton Population (COHP) on simulation snapshots shows that significant charge transfer from the reducing element to the C atoms creates instability in the C-O covalent bonds. COHP analysis further shows that Mn/Fe-O and Mn/Fe-C bonding interactions are weaker compared to the Si counterparts. These results further our understanding of the redox chemistry of CO 2 at conditions relevant to planetary mantle interiors and demonstrate the effectiveness of high pressure in the reduction of CO 2 directly to solid carbon.

Ab initio molecular dynamics↗
DOE OSTI2020

Predictions of the glass transition temperature and viscosity of organic aerosols from volatility distributions

Abstract. Volatility and viscosity are important properties of organic aerosols (OA), affecting aerosol processes such as formation, evolution, and partitioning of OA. Volatility distributions of ambient OA particles have often been measured, while viscosity measurements are scarce. We have previously developed a method to estimate the glass transition temperature (Tg) of an organic compound containing carbon, hydrogen, and oxygen. Based on analysis of over 2400 organic compounds including oxygenated organic compounds, as well as nitrogen- and sulfur-containing organic compounds, we extend this method to include nitrogen- and sulfur-containing compounds based on elemental composition. In addition, parameterizations are developed to predict Tg as a function of volatility and the atomic oxygen-to-carbon ratio based on a negative correlation between Tg and volatility. This prediction method of Tg is applied to ambient observations of volatility distributions at 11 field sites. The predicted Tg values of OA under dry conditions vary mainly from 290 to 339 K and the predicted viscosities are consistent with the results of ambient particle-phase-state measurements in the southeastern US and the Amazonian rain forest. Reducing the uncertainties in measured volatility distributions would improve predictions of viscosity, especially at low relative humidity. We also predict the Tg of OA components identified via positive matrix factorization of aerosol mass spectrometer (AMS) data. The predicted viscosity of oxidized OA is consistent with previously reported viscosity of secondary organic aerosols (SOA) derived from α-pinene, toluene, isoprene epoxydiol (IEPOX), and diesel fuel. Comparison of the predicted viscosity based on the observed volatility distributions with the viscosity simulated by a chemical transport model implies that missing low volatility compounds in a global model can lead to underestimation of OA viscosity at some sites. The relation between volatility and viscosity can be applied in the molecular corridor or volatility basis set approaches to improve OA simulations in chemical transport models by consideration of effects of particle viscosity in OA formation and evolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Microbial extracellular polysaccharide production and aggregate stability controlled by switchgrass ( Panicum virgatum ) root biomass and soil water potential

Deep-rooting perennial grasses are promising feedstocks for biofuel production, especially in marginal soils lacking organic material, nutrients, and/or that experience significant water stress. Perennial grass roots influence surrounding soil conditions and microbial activities, and produce extracellular polymeric substances (EPS) composed primarily of extracellular polysaccharides (EPSac). These polymers can alleviate microbial moisture and nutrient stress, and enhance soil characteristics through improved water retention and aggregate stability—which may in turn enhance carbon persistence. Here, we used a 13 CO 2 greenhouse tracer experiment to examine the effect of switchgrass cultivation on EPSac production and origin in a marginal soil with five fertilization/water treatments (control, +N, +NP, +P, low water), and compared these results with measurements of field soils collected after long-term switchgrass cultivation. Soils with added nitrogen and phosphorus (+NP) had the highest root biomass, EPSac and percentage of water-stable soil aggregates. Multiple linear regression analyses revealed that root biomass and soil water potential were important determinants of soil EPSac production, potentially by controlling carbon supply and diurnal changes in moisture stress. Path analysis showed that soil aggregation was positively correlated with bulk soil EPSac content and also regulated by soil water potential. High mannose content indicated the majority of EPSac was of microbial origin and 13 CO 2 labeling indicated that 0.18% of newly fixed plant carbon was incorporated into EPSac. Analysis of field soils suggests that EPSac is significantly enhanced after long-term switchgrass cultivation. Taken as a whole, our greenhouse and field results demonstrate that switchgrass cultivation can promote microbial production of EPSac, providing a mechanism to enhance aggregation in marginal soils.

13c labeling↗
DOE OSTI2023

How does uncertainty of soil organic carbon stock affect the calculation of carbon budgets and soil carbon credits for croplands in the U.S. Midwest?

Cropland carbon budget depicts the amount of carbon flowing in and out of agroecosystems and the changes in carbon stocks of soil and living biomass during the same period. Soil carbon credit is the additional change in soil carbon stock under certain farming practices compared with the business-as-usual practices. Accurately calculating cropland carbon budget and soil carbon credit is critical to assessing climate change mitigation potential in agroecosystems. The calculation of cropland carbon budget and soil carbon credit is sensitive to local soil and climatic conditions, especially initial soil organic carbon (SOC) stock, which is determined by both SOC concentration (SOC%) and bulk density (Bulk_Density). SOC stock data are either from soil sampling or gridded public survey data. In agroecosystem models, SOC stock data are a key model input for quantifying cropland carbon budget and soil carbon credit. However, various types and degrees of uncertainties exist in SOC stock datasets, which propagate to the quantification of SOC stock change. In particular, a large discrepancy is found in two widely used SOC stock datasets — Rapid Carbon Assessment dataset (RaCA) and Gridded Soil Survey Geographic Database (gSSURGO) — in the U.S. Midwest, with a relative difference (quantified using Normalized Root Mean Square Error, NRMSE) of 48.0% for 0–30 cm SOC stock between the two datasets. It remains largely unclear how uncertainty in SOC stocks affects the calculation of cropland carbon budget and soil carbon credit. To address this question, we used a well-validated process-based agroecosystem model, ecosys, to assess the impacts of SOC stock uncertainty on carbon budget and soil carbon credit calculation in the U.S. Midwestern corn-soybean rotation systems. Our results reveal the following findings: (1) A sizable discrepancy exists in simulated cropland carbon budget between using gSSURGO and using RaCA for their SOC% and Bulk_Density as model inputs, with a Pearson correlation coefficient (r) of only 0.4 for simulated change of SOC stock (ΔSOC) using these two different soil datasets. (2) Simulated cropland carbon budget components were more sensitive to initial SOC% than to Bulk_Density. For example, the upper and lower quartiles of multi-year averaged ΔSOC were –29.8 and 4.8 gC/m 2 /year for the selected counties respectively, with an uncertainty of 13.7 and 0.7 gC/m 2 /year induced by uncertainties in initial SOC% and Bulk_Density, respectively. (3) Both simulated ΔSOC and its uncertainty were negatively correlated with initial SOC%, whereas ΔSOC was negatively correlated with air temperature, and ΔSOC uncertainty was positively correlated with air temperature. (4) The uncertainty of calculated soil carbon credits was much smaller compared with the uncertainty of calculated absolute carbon budgets assuming the same SOC stock uncertainty level in the inputs. Specifically, in our assessment comparing planting cover crops vs no cover crop, the uncertainty of calculated soil carbon credits induced by initial SOC% uncertainty was less than 4% (relative to the quantified value of the soil carbon credits) for 90% of the cases. Our analysis highlights that high accuracy measurement of SOC% as inputs is needed for the calculation of cropland carbon budgets; however, soil carbon credit quantification is much less sensitive to the initial SOC% inputs, and the current publicly available soil datasets (e.g., gSSURGO) are largely suitable for the calculation of soil

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Baseload Hydrogen Production Using Nuclear and Renewable Energy: A Comparative Analysis

As the global push towards net zero carbon gains momentum, the demand for clean hydrogen is expected to grow rapidly across various sectors, including transportation, industries and electrical grids. To meet this growing hydrogen demand, baseload hydrogen production facilities capable of providing a continuous and reliable supply of hydrogen will be necessary throughout the world. This paper explores the technoeconomic feasibility of establishing baseload electrolytic hydrogen production facilities in the United States, utilizing different clean generation resources. The key criteria include maintaining a consistent supply of clean hydrogen without putting baseload demand stress to already vulnerable power grid. In order to do that, the proposed facilities will host onsite clean power generation and energy storage technologies. The proposed facilities can capitalize on available investment and production incentives and have ability to export excess electricity to the utility at a bulk price. Several scenarios are considered based on the clean energy resources to support the electrolysis process including light water reactors (LWRs) currently evaluating retirement options, wind, solar PVs, and advanced small modular reactors (SMRs). For each scenario, a hypothetical hydrogen production facility is considered in a location in the US where the primary generation resource is at its peak strength. Comparative analysis in this paper reveal that the nuclear power plants are most economically viable for baseload hydrogen production facilities, outperforming renewable-based facilities with significantly lower levelized cost of hydrogen (LCOH). Even under best-case scenarios for resource availability, incentives and export prices, renewable-based facilities face challenges due to daily and seasonal generation variability, resulting in large installation sizes and lower capacity factors. Among renewable-based facilities, complementarity hybrids, providing more stable power supply, demonstrate superior economics compared to facilities based on a single renewable technology. While LWR-powered facility can achieve a negative LCOH with incentives, SMR-powered facilities can provide economic hydrogen supply with LCOH below $1/kg with high temperature electrolysis option. The analysis in this paper underscores the pivotal role of nuclear energy in the future hydrogen economy.

08 - HYDROGEN↗
DOE OSTI2024

Curating Carbon Storage Data for Reuse: Enabling Research and Modeling from Earth’s Surface to Subsurface

The volume of public geologic carbon storage (GCS) data resources has continued to increase in recent years as the result of an increase in funding from government, industry, and academia towards national, basin, regional and field scale studies to ensure carbon capture and storage becomes a commercially viable operation. Despite the increasing volume of data, GCS data applied towards analyses such as geologic, cost, and risk modeling continues to be multi-sourced and often disparate in nature, published across government agencies, websites, data repositories and buried in derivative reports and documents. Much of the time preparing for an analysis and derivative product development is spent collecting, aggregating, transforming and preparing input data. There have been significant efforts within the DOE National Energy Technology Laboratory’s Carbon Storage Program to optimize multi-source, multi-scale subsurface geologic data curation and aggregation to support data discovery, interoperability, and reuse. Methods include the use of artificial intelligence, machine learning, and data science techniques. This talk will discuss the workflows, best practices, and processes developed to support the aggregation and curation of data through the whole system – surface to subsurface data - that support multi-scale, multi-purpose analysis for carbon storage research.

Morkner, Paige↗
DOE OSTI2022

Soil Respiration Response to Simulated Precipitation Change Depends on Ecosystem Type and Study Duration

Soil respiration—the flow of biologically-generated CO 2 from the soil surface to the atmosphere—is a major component of global carbon cycling, but the long-term response of this flux to altered precipitation regimes remains uncertain, due to different responses of soil respiration in distinct ecosystems with varying degrees of water limitation. We conducted a meta-analysis to determine the role of soil characteristics (organic carbon stock and clay content), study duration, and ecosystem type (e.g., forest, grassland, etc) in modifying the response of soil respiration to precipitation change. In general, decreased precipitation (N = 128 effect size pairs) decreased soil respiration rates. In contrast, increased precipitation (N = 141) had a more variable and on-average weak positive effect on this flux; significantly increasing soil respiration only in desert ecosystems. The long-term response of ecosystems varied, with those that are less constrained by water-availability (e.g., forests) showing acclimation over time to altered precipitation. Soil organic carbon stock strongly modified the response of soil respiration to decreased precipitation (p < 0.0001), but only weakly modified the response to increased precipitation (p < 0.01). Our results suggest that ecosystems with limited soil water-holding capacity and strong inherent water-limitation will show long-term dynamic change in soil respiration regardless of the direction of precipitation change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Life‐cycle greenhouse gas emissions associated with nuclear power generation in the United States

Under the 2022 Inflation Reduction Act, tax credits of up to $3/kgH 2 are available to hydrogen producers if they generate emissions at levels below 0.45 kgCO 2 e/kgH 2 , spurring producers to explore how hydrogen production via electrolysis using electricity generated by nuclear power may qualify for such tax credits. With uranium as a primary fuel for nuclear power plants (NPPs) and no on-site emissions, the upstream emissions associated with nuclear fuel supply chains largely determine the carbon intensity of nuclear energy. Using the GREET (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model, we evaluated the life-cycle greenhouse gas (GHG) emissions of uranium production and the use of uranium to generate electricity in light water reactor (LWR) NPPs. We evaluated the process chemicals and energy inputs throughout the nuclear fuel supply chain to identify the major contributors to nuclear fuel cycle GHG emissions. Such emissions are estimated at 3.0 gCO 2 e/kWh at NPPs in the United States. The greatest share of nuclear fuel cycle GHG emissions—comprising 53% of total emissions—are associated with electricity consumption throughout the fuel supply chain. We extended the analysis to include an evaluation of the carbon intensity of H 2 production via electrolysis using nuclear power from LWRs. Finally, we examined the impact of future (2035 and 2050) electricity supply chain scenarios on nuclear fuel cycle GHG emissions. Our analysis revealed a decrease of 33% (2035) and 46% (2050) in the carbon intensity of nuclear electricity relative to current nuclear fuel cycle GHG emissions.

greenhouse gas emissions↗
DOE OSTI2025

Spatially Resolved Raman Spectroscopy of Thin Carbon Interphase in SiC Ceramic Matrix Composites

A dedicated analysis method is presented to extract the Raman spectrum of an interphase layer thinner than the laser spot size. We focused on spatial correlations between the contrast of optical micrographs and Raman hyperspectral data to predict the constituents of the mixed spectra measured near the interphase. By employing a mapping step size of 0.1 μm, the Raman spectrum of approximately 0.3-μm-thick carbon interphase in a SiC fiber-reinforced SiC matrix composite was extracted from data acquired with a theoretical spot size of about 0.7 μm. Notably, conventional chemometrics procedures were unable to isolate the interphase signal, instead producing a spectrum representing a mixture of interphase and matrix. This study used another composite with approximately 0.9-μm-thick interphase to validate the analysis method, enabling direct measurement of the interphase spectrum. The proposed Raman analysis method has advantages in specimen volume and turnaround time compared to traditional characterization methods, such as transmission electron microscopy. In conclusion, this study also evaluates the applicability of the analysis method to different composite materials and identifies key requirements of the measurements, including the ratio of interphase thickness to spot size and the homogeneity of the surrounding matrix.

ceramic matrix composite↗
DOE OSTI2020

Carbon ablator areal density at fusion burn: Observations and trends at the National Ignition Facility

For inertial confinement fusion experiments, the pusher is composed of a high-density deuterium tritium cyrogenic fuel layer and an ablator, often made of carbon. In an ideal, no-mix implosion, increasing the areal density of the pusher transfers more pressure to the hot spot and increases the hot spot confinement time. There has been a lack of knowledge about the final compressed state of the ablator for implosions at the National Ignition Facility. 14 MeV fusion neutrons inelastically scattering on the remaining carbon ablator excites a nuclear metastable state that emits a prompt 4.4 MeV gamma ray. The gamma reaction history diagnostic data, when reduced by a new data analysis technique, can isolate and measure the carbon gamma rays, which are proportional to the areal density of the ablator during fusion burn. The trends over many National Ignition Facility campaigns show that the ablator areal density is weakly sensitive to the maximum shell velocity, the cold fuel radius, the ablator mass remaining, or the laser picket intensity. Controlled parameter scans reveal that, for specific campaigns, ablator compression has a strong dependence on laser coast time, high Z dopants, and the laser drive foot duration. Using a model of the compressed ablator density profile reveals that the greatest variation of the ablator areal density comes from its thickness, with highly compressed, thin layers having high areal density values. The compression and thickness of the ablator are other metrics that designers should understand to differentiate the types of capsule degradation and maximize the inertial confinement fusion performance.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗