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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A general approach to seismic inversion with automatic differentiation

Imaging Earth structure or seismic sources from seismic data involves minimizing a target misfit function, and is commonly solved through gradient-based optimization. The adjoint-state method has been developed to compute the gradient efficiently; however, its implementation can be time-consuming and difficult. We develop a general seismic inversion framework to calculate gradients using reverse-mode automatic differentiation. The central idea is that adjoint-state methods and reverse-mode automatic differentiation are mathematically equivalent. Here, the mapping between numerical PDE simulation and deep learning allows us to build a seismic inverse modeling library, ADSeismic, based on deep learning frameworks, which supports high performance reverse-mode automatic differentiation on CPUs and GPUs. We demonstrate the performance of ADSeismic on inverse problems related to velocity model estimation, rupture imaging, earthquake location, and source time function retrieval. ADSeismic has the potential to solve a wide variety of inverse modeling applications within a unified framework.

58 GEOSCIENCES↗
DOE OSTI2022

Te(IV) immobilization by siderite: Reaction kinetics, mechanism, and Te isotopic fractionation

Mining and industrial use over recent decades have released tellurium (Te) into the environment where it potentially contaminates soils, water supplies and food sources. Therefore, it is important to find ways of removing mobile and bioavailable Te from aqueous environments. Here, we report aqueous Te(IV) removal by siderite at varying Te concentrations (2, 6 and 10 mg mL –1 Te(IV)) and pH values (7, 7.9 and 9), together with associated isotope fractionation (ε 130 Te/ 125 Te). Our results show effective immobilization of Te(IV) that follows pseudo-first order rate kinetics. Formation of magnetite indicates reduction of Te(IV) on siderite surfaces and the formation of Te(0). The overall isotope fractionation (ε) is small (–0.23 ± 0.06‰) providing evidence that it is primarily controlled by adsorption of Te(IV) occurring simultaneously with reduction of Te(IV). Therefore, Te(IV) removal by siderite under mildly reducing ferruginous conditions may be identifiable by the characteristically small isotopic fractionation during both natural attenuation and active remediation. To our knowledge, this is the first study reporting reaction mechanisms of Te(IV) immobilization by an environmentally relevant Fe(II) mineral.

58 GEOSCIENCES↗
DOE OSTI2023

Inhibition of enzyme hydrolysis of cellulose by phenols from hydrothermally pretreated sugarcane straw

Relatively few studies have addressed the characterization of sugarcane straw (SCS) for production of fermentable sugars through enzyme hydrolysis. Straw is a major co-product of the sugarcane harvest in Brazil that has potential to sustainably increase cellulosic feedstocks in Brazil by 50%. Pretreatment of 10% w/v straw with liquid hot water (LHW) at 180°C for 50 min (severity, S of 4.05), solubilizes hemicellulose, preserves glucan, and generates 4.49 g/L soluble phenolic compounds in the resulting liquid. Extracts from washing pretreated solids with excess hot water followed by acetone resulted in 1.10 and 0.83 g/L phenolics, respectively. Here, acetone-derived extracts were more inhibitory and decreased glucose yield for enzyme hydrolysis of Solka Floc (a lignin-free cellulose) by 42%. In comparison, pretreated straw washed with hot water or acetone was readily hydrolyzed to 92% and 97% by cellulase enzyme. Hydrothermally treated SCS has the potential to provide a valuable and added source of fermentable sugars suitable for bioprocessing into biofuels and bioproducts when cellulase enzyme inhibitors are removed after pretreatment.

Deactivation↗
DOE OSTI2021

A Simple Criterion for Feasibility of Heat Integration between Distillation Streams Based on Relative Volatilities

In a multicomponent distillation configuration, there are numerous sources and sinks of heat, and a potential way to reduce the heat duty requirement is to perform heat integration. Unfortunately, an algorithmic search of the optimal heat integration opportunities is intractable when the required temperatures of intermediate streams are computed via complex models. Instead, in this work, we introduce pressure-scaled pseudo relative volatility, a new metric to compare stream temperatures. Here, we justify the use of pseudo relative volatility by proving that this variable is a monotonically increasing function of the liquid fraction in a saturated mixture stream. Using this metric, we derive a shortcut criterion to check the feasibility of various heat integration opportunities, such as thermal coupling via heat transfer (TCH). The advantage of this approach is that it circumvents the need for explicit temperatures and instead relies on composition, component relative volatilities, and pressure—quantities that are readily available in shortcut models for optimization of distillation configurations. Leveraging this fact, we propose a new optimization framework that identifies feasible TCHs that we consider within the formulation while minimizing the total heat duty of a distillation configuration. We demonstrate, on a few examples, that our formulation can identify heat duty efficient configurations, some of which are multieffect configurations. Using this methodology, we discover configurations that are not only simpler than the fully thermally coupled (FTC) configuration but also have a much lower heat duty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Global Nuclear Explosion Discrimination Using a Convolutional Neural Network

Using P-wave seismograms, we trained a seismic source classifier using a Convolutional Neural Network. We trained for three classes: earthquake P-wave, underground nuclear explosion (UNE) P-wave, and noise. With the current absence of nuclear testing by countries that have signed the Comprehensive Test Ban Treaty, high quality seismic data from UNEs is limited. Even with limited training data, our model can accurately characterize most events recorded at regional and teleseismic distances, finding over 95% signals in the validation set. We applied the model on holdout datasets of the North Korean test explosions to evaluate the performance on unique region and station-source pairs, with promising results. Additionally, we tested on the Source Physics Experiment events to investigate the potential for chemical explosions to act as a surrogate for nuclear explosions. We anticipate that machine-learning models like our classifier system can have broad application for other seismic signals including volcanic and non-volcanic tremor, anomalous earthquakes, ice-quakes or landslide-quakes.

58 GEOSCIENCES↗
DOE OSTI2024

Simulating Global Terrestrial Carbon and Nitrogen Biogeochemical Cycles With Implicit and Explicit Representations of Soil Microbial Activity

Abstract Nutrient limitation is widespread in terrestrial ecosystems. Accordingly, representations of nitrogen (N) limitation in land models typically dampen rates of terrestrial carbon (C) accrual, compared with C‐only simulations. These previous findings, however, rely on soil biogeochemical models that implicitly represent microbial activity and physiology. Here we present results from a biogeochemical model testbed that allows us to investigate how an explicit versus implicit representation of soil microbial activity, as represented in the MIcrobial‐MIneral Carbon Stabilization (MIMICS) and Carnegie‐Ames‐Stanford Approach (CASA) soil biogeochemical models, respectively, influence plant productivity, and terrestrial C and N fluxes at initialization and over the historical period. When forced with common boundary conditions, larger soil C pools simulated by the MIMICS model reflect longer inferred soil organic matter (SOM) turnover times than those simulated by CASA. At steady state, terrestrial ecosystems experience greater N limitation when using the MIMICS‐CN model, which also increases the inferred SOM turnover time. Over the historical period, however, warming‐induced acceleration of SOM decomposition over high latitude ecosystems increases rates of N mineralization in MIMICS‐CN. This reduces N limitation and results in faster rates of vegetation C accrual. Moreover, as SOM stoichiometry is an emergent property of MIMICS‐CN, we highlight opportunities to deepen understanding of sources of persistent SOM and explore its potential sensitivity to environmental change. Our findings underscore the need to improve understanding and representation of plant and microbial resource allocation and competition in land models that represent coupled biogeochemical cycles under global change scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An efficient and durable anode for ammonia protonic ceramic fuel cells

Ammonia protonic ceramic fuel cells (PCFCs) have the potential to be a highly efficient power source with high energy density. However, the inadequate catalytic activity of the existing anodes for utilization of ammonia greatly limits the performance of PCFCs. In this study, we report an Fe-modified state-of-the-art Ni cermet anode with greatly enhanced activity and durability toward utilization of ammonia. Cells with an Fe-decorated Ni-BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3 (Ni–BZCYYb) anode demonstrate an excellent performance, achieving peak power densities of 0.360, 0.723, 1.257, and 1.609 W cm –2 at 550, 600, 650, and 700 °C, respectively, which reveal the highest performance of solid oxide fuel cells fueled on ammonia. In addition, the cells show an excellent durability when operated at a constant current density of 0.5 A cm –2 (or a power density of ~0.435 W cm –2 ) at 650 °C. The superior activity and durability of the Fe-modified Ni/BZCYYb anode are attributed to the alternation of NH 3 adsorption strength and N 2 desorption barrier heights, as confirmed by first-principles based mechanistic and microkinetic modeling. Our research provides a valuable guidance for the development of efficient electro-catalysts for ammonia PCFCs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Techno-economic and life cycle analysis of bio-hydrogen production using bio-based waste streams through the integration of dark fermentation and microbial electrolysis

Hydrogen derived from bio-based sources, or biohydrogen (bioH 2 ), has the potential to reduce GHG emissions from industrial and transportation sectors, owing to the low carbon footprint and myriad applications like refinery operation, ammonia production, steel production, fuel cell, etc. To evaluate the commercialization potential of bioH 2 production, we modeled bioH 2 production and conducted techno-economic analysis (TEA) and life cycle analysis (LCA) of two facilities producing 50 metric tonnes of bioH 2 per day from cheese whey (CW) and solid food waste (SFW) through the integration of dark fermentation (DF) and microbial electrolysis cell (MEC) technologies. LCA results showed that CW and SFW can produce carbon-negative bioH 2 , with emissions of −8.6 and −8.0 kg GHG kg −1 bioH 2 with carbon sequestration and renewable electricity resources, respectively, making bioH 2 potentially eligible for a tax credit of $\$3$ kg −1 H 2 based on provision 45 V of the U.S. Inflation Reduction Act (IRA). In this study, bioH 2 production treats waste streams to generate fresh water, thus, potentially can receive waste water treatment fee that varies with regions. The MEC capital cost dominates the bioH 2 cost, which is mainly determined by current density. With a current density of 20 A m −2 , the production cost for CW input varied between $\$17$ and $\$24$ kg −1 bioH 2 , while that for SFW input ranged from $\$29$ to $\$30$ kg −1 bioH 2 under different operating conditions, considering the 45 V tax credit, waste water treatment fee and production revenue. If the current density increases to 100 A m −2 , the bioH 2 cost decreases to a range of $\$4.0$–$\$6.9$ for CW and $\$5$–$\$6$ for SFW scenarios. This study also shows that low-cost bioH 2 can be produced using CW waste stream as feedstock.

Ganguly, Arna [Argonne National Laboratory (ANL), ↗
DOE OSTI2021

Modular horizontal pendulum wave energy converter: Exploring feasibility to power ocean observation applications in the U.S. pacific northwest

Abstract Marine renewable energy as a power source for ocean observation applications has the potential to allow longer deployment operations due to the consistent, higher, and denser energy available from this resource. This additionally could encourage deployments in remote locations where maintenance is costly or resource availability is low if dependent on solar power. More importantly, gaps in spatial data could be filled. This paper examines the feasibility of a modular horizontal pendulum wave energy converter to power National Data Buoy Center's Self‐Contained Ocean Observations Payload (SCOOP) off the coast of Washington State, U.S. The effect on power output was studied when the pendulum's radius arm, mass, and power take‐off damping were varied. Results using Matlab toolbox WEC‐Sim revealed positive correlation between radius arm length and mass to power output, where power maximised for optimal damping values. Seasonal trends in power were not significant, where a 20 kg pendulum mass was needed to meet the SCOOP base power requirement of 5 W throughout the year.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Quasi-static magnetic compression of field-reversed configuration plasma: amended scalings and limits from two-dimensional MHD equilibrium

In this work, several key scaling laws of the quasi-static magnetic compression of field reversed configuration (FRC) plasma (Spencer et al 1983 Phys. Fluids 26 1564) are amended from a series of two-dimensional FRC MHD equilibriums numerically obtained using the Grad–Shafranov equation solver NIMEQ. Based on the new scaling for the elongation and the magnetic fields at the separatrix and the wall, the empirically stable limits for the compression ratio, the fusion gain, and the neutron yield are evaluated, which may serve as a more accurate estimate for the upper ceiling of performance from the magnetic compression of FRC plasma as a potential fusion energy as well as neutron source devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Mapping hidden space-charge distributions across crystalline metal oxide/group IV semiconductor interfaces

The electronic structures of semiconducting heterojunctions are critically dependent on composition including the presence and concentrations of dopants, both intended and unintended. Dopant profiles in the interfacial region can have major effects on band energies which in turn drive transport properties. Here, in this study, we use core-level photoelectron line shapes excited with hard x rays to extract information about electric fields resulting from internal charge transfer in epitaxial La 0.03 Sr 0.97 Zr x Ti 1–x O 3 /Ge(001) (0.1≤x≤0.7) heterostructures. Experiments were carried out for heterojunctions involving both n- and p-type Ge substrates. These heterojunctions were not amenable to electronic characterization of all regions by transport measurements because the doped substrates act as electrical shunts, precluding probing the more resistive films and masking interface conductivity. However, the core-level line shapes were found to be a rich source of information on built-in potentials that exist throughout the heterostructure, and yielded valuable insight into the impact of band bending on band alignment at the buried interfaces. The electronic effects expected for Ge with uniform n- and p-type doping are eclipsed by those of unintended oxygen dopants in the Ge near the interface. This study illustrates the power of hard x-ray photoemission spectroscopy and related modeling to determine electronic structure in material systems for which insight from traditional transport measurements is limited.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Temporal dynamics of free‐living nitrogen fixation in the switchgrass rhizosphere

Abstract Free‐living nitrogen fixation (FLNF) represents an important terrestrial N source and is gaining interest for its potential to contribute plant available N to bioenergy cropping systems. Switchgrass, a cellulosic bioenergy crop, may be particularly reliant on FLNF when grown on low N systems, like marginal lands. However, the potential contributions of FLNF to switchgrass as well as the controls on this process are not well understood. In this study, we evaluated drivers of FLNF rates and N‐fixing microbial (diazotrophic) community composition in field‐grown switchgrass systems over two growing seasons with high temporal sampling. We found that climate variables are strong drivers of FLNF rates in switchgrass systems, compared to other environmental and biological factors including soil nutrients and diazotrophic community composition. Increased soil moisture availability generally promoted FLNF rates, but extreme rainfall events were detrimental. These climate‐related responses suggest a potential for loss of FLNF‐derived N contributions under projected climate shifts. We found a significant, but weak correlation between diazotrophic community composition and FLNF rates. We also observed a significant shift in the diazotrophic community composition between 2017 and 2018 and similarly measured a significant difference in FLNF rates between growing seasons. Lastly, we found that seasonal FLNF N contributions, based on measurement with high temporal resolution, has the potential to meet up to 80% of switchgrass N demands suggesting that FLNF measurements extrapolated from fewer time points or locations may underestimate these potential N contributions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Environmental matrix and moisture influence soil microbial phenotypes in a simplified porous media incubation

Soil moisture and porosity regulate microbial metabolism by influencing factors, such as system chemistry, substrate availability, and soil connectivity. However, accurately representing the soil environment and establishing a tractable microbial community that limits confounding variables is difficult. Here, we use a reduced-complexity microbial consortium grown in a glass bead porous media amended with chitin to test the effects of moisture and a structural matrix on microbial phenotypes. Leveraging metagenomes, metatranscriptomes, metaproteomes, and metabolomes, we saw that our porous media system significantly altered microbial phenotypes compared with the liquid incubations, denoting the importance of incorporating pores and surfaces for understanding microbial phenotypes in soils. These phenotypic shifts were mainly driven by differences in expression of Streptomyces and Ensifer, which included a significant decrease in overall chitin degradation between porous media and liquid. Our findings suggest that the success of Ensifer in porous media is likely related to its ability to repurpose carbon via the glyoxylate shunt amidst a lack of chitin degradation byproducts while potentially using polyhydroxyalkanoate granules as a C source. We also identified traits expressed by Ensifer and others, including motility, stress resistance, and carbon conservation, that likely influence the metabolic profiles observed across treatments. Together, these results demonstrate that porous media incubations promote structure-induced microbial phenotypes and are likely a better proxy for soil conditions than liquid culture systems. Furthermore, they emphasize that microbial phenotypes encompass not only the multi-enzyme pathways involved in metabolism but also include the complex interactions with the environment and other community members.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Lithium-Ion Batteries with Lithium Manganese Iron Phosphate Cathodes and Lithium Titanate Anodes: Linking Electrode Dynamics to Cell Performance

This study examines the electrochemical performance, impedance behavior, and aging mechanisms of lithium-ion cells pairing lithium manganese iron phosphate (LiMn 0.6 Fe 0.4 PO 4 , LMFP64) cathodes with lithium titanate (Li 4 Ti 5 O 12 , LTO) anodes. LMFP64 half-cells display distinct Fe and Mn redox plateaus at ∼3.5 and ∼4.1 V, respectively, and deliver excellent rate capability. Three-electrode measurements show that LMFP64 dominates cell impedance, which changes sharply across the Fe–Mn redox transition and decreases with increasing temperature (30 °C–50 °C). Voltage hysteresis arises mainly from the cathode, with higher C-rates shortening redox plateaus and broadening the transition region. Elevated temperature lowers impedance, especially near the Mn-redox and transition regions, but accelerates capacity fade. Post-cycling analyses of electrodes confirm structural stability of LMFP64 and indicate loss of lithium inventory (LLI) as the source of capacity fade. This LLI causes potential slippage between the LMFP64 and LTO electrodes, which decreases the Fe-redox plateau width. Long-term cycling highlights the critical role of electrode overhang: cathode overhang mitigates capacity fade by buffering lithium loss, whereas anode overhang cells experience faster capacity decline due to uncompensated lithium depletion. These results clarify LMFP64/LTO battery impedance evolution, thermal effects, and degradation pathways and provide insights for their applications in electric vehicles.

Area Specific Impedance↗
DOE OSTI2021

CO2ROpt (Feedstock Allocation Optimization Model) [SWR-22-13]

Reducing greenhouse gas emissions remains a critical challenge for the transportation and chemical sectors. The electrochemical reduction of carbon dioxide is a potential pathway for production of fuels and chemicals that uses atmospheric carbon dioxide as a feedstock. Here we present an analysis of the potential for carbon dioxide captured from point sources and via direct air capture to be utilized in electrochemical reduction under different market scenarios. Using a numerical optimization framework and national data sets, scenarios for nationwide production of ethylene, formate, and carbon monoxide are evaluated at scales comparable to current production of these molecules in the United States. We show that developing a network for production of these products at scale requires capture and utilization of significant portions of the carbon dioxide that is currently emitted from large stationary point sources. Because carbon dioxide point sources are spatially and compositionally variable, their use for carbon dioxide reduction depends on electricity prices, capture cost, and location. If the power sector in the United States is decarbonized, carbon dioxide supply decreases significantly, increasing the importance of utilizing other carbon dioxide streams, and increasing the likelihood that direct air capture plays a role in supplying carbon dioxide feedstocks. These findings provide a first insight into the feedstock and energy constraints for carbon dioxide reduction.

Badgett, Alex↗
DOE OSTI2023

Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems

The high complexity and multiscale nature of many engineered systems—such as those in nuclear power plants—make representing and forecasting their dynamic behavior challenging. Physics-based models can be overly complex and computationally intractable, whereas machine learning (ML) tools are often data-hungry and prone to unphysical solutions. This study proposes a knowledge-informed ML-aided hybrid residual modeling approach that offers accurate and efficient time series forecasting for the operation of dynamical engineered systems. Hybrid residual modeling entails a baseline solution from domain knowledge and known physics expressions about the system dynamics integrated with an ML model to capture undiscovered information from the mismatch (i.e., residuals) between true states from measurements and baseline-predicted outputs. This study further quantifies the ML model uncertainty to provide trustworthy solutions. Real-time operational data from thermal-hydraulic flow loops of the cryogenic moderator system in Oak Ridge National Laboratory’s Spallation Neutron Source facility were used to demonstrate the potential of knowledge-informed uncertainty-aware ML in real-world applications. The state variables of the cryogenic helium loop were modeled with (1) first principles–based system identification (sysID), (2) long short-term memory (LSTM) neural network, and (3) hybrid sysID (baseline) + LSTM (residual). The superior predictive capability of the sysID+LSTM model versus stand-alone sysID and LSTM is confirmed by average performance metrics and individual data points across different prediction horizons. By creating a robust representation of the underlying physical system, the widely applicable hybrid residual modeling approach will enable the future development of digital twins for performance prediction, prognostics, and operation control.

Zhao, Xingang↗
DOE OSTI2020

Regional Geology Capstone Report for the Midwestern Regional Carbon Sequestration Partnership (Volume V)

The Midwest Regional Carbon Sequestration Partnership (MRCSP) was founded in 2003 as part of the U.S. Department of Energy’s (DOE’s) Regional Carbon Sequestration Partnership initiative. Since its founding, MRCSP has made significant strides toward making CCUS a viable option for states in the region. The public/private consortium, funded through the DOE Regional Carbon Sequestration Initiative, brings together nearly 40 industry partners and 10 states. Battelle, as the project lead, oversees research, development and operations and coordinates activities among the partners. The incremental, phased approach has built a valuable knowledge base for the industry and paved the way for commercial-scale adoption of CCUS technologies. From 2008 to 2020, MRCSP Phase III focused on the development of large-scale injection projects. This report is part of a series of reports prepared under the Midwestern Regional Carbon Sequestration Partnership (MRCSP) Phase III (Development Phase). These reports summarize and detail the findings of the work conducted under the Phase III project. The MRCSP regional geology Capstone report summarizes the regional characterization of geologic storage subtasks performed under MRCSP Phase III. The regional characterization work was completed by the state geological surveys of Delaware, Indiana, Kentucky, Maryland, New York, Ohio, Pennsylvania, and West Virginia along with Western Michigan University and Rutgers University. Building on the Phases I and II, the Phase III research was focused on key research topics identified in previous MRCSP efforts: [1] Regional Geologic Cross Sections for Potential Storage and Containment Zones; [2] Appalachian Basin: Enhanced Recovery Opportunities; [3] Michigan Basin: Assessment of Enhanced Oil Recovery Using Carbon Dioxide in Silurian Pinnacle Reefs; [4] Mid-Atlantic Coastal Plain and Adjacent Offshore Region: Characterization of Carbon Storage Targets; [5] Ordovician-Cambrian Units: Hierarchical Evaluation of Geologic Carbon Storage Resource Estimates; [6] Upper Silurian to Middle Devonian Strata of Ohio: Structural Characterization of Potential CO 2 Reservoirs and Adjacent Strata; [7] Triassic Rift Basins: Preliminary Study of Long-Term CO 2 Storage Potential Together, the regional characterization effort developed useful products to support project developers, policy makers and other stakeholders in the MRCSP region seeking to understand where potential storage exists relative to large stationary sources of CO 2 emissions.

01 COAL, LIGNITE, AND PEAT↗