Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “TaN”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Biorefinery upgrading of herbaceous biomass to renewable hydrocarbon fuels, Part 1: Process modeling and mass balance analysis

Process simulation has long been a well-established tool to track key operational, design, and mass and energy balance metrics for pre-commercial technologies such as advanced lignocellulosic biofuels. While tools such as this are well-documented in the public literature around 2nd-generation cellulosic ethanol technologies (which have been scaled up to commercial deployment to some degree over the past decade), such models and analysis information remain more sparse for more complex biorefinery pathways focused on producing drop-in hydrocarbon fuels and blend-stocks, particularly regarding information required to support air emissions or other environmental analysis. In this work, we summarize key details for an established "design case" modeling the conversion of herbaceous lignocellulosic biomass into a renewable diesel hydrocarbon blend-stock based on a representative lipid pathway from oleaginous yeast. The process is based on a biochemical deconstruction and upgrading approach utilizing deacetylation and dilute acid pretreatment, followed by enzymatic hydrolysis, fermentation, and catalytic upgrading of hydrolysate sugars to fuels. We provide key mass and energy balance outputs from the process models, with accompanying stream tables and component-level flowrates. A total of 12 model scenarios are presented spanning two feedstocks, three biorefinery scales, and two processing approaches for the lignin/residual solids waste streams. This "Part 1" manuscript presents the resulting impacts across the 12 cases on fuel yields and key output streams, focused here on direct biorefinery air emissions for selected components including CO 2 as well as sulfur (SOx) and nitrogen oxides (NOx). In the context of cleaner production, the latter focus on selected biorefinery air emission outputs establishes an initial baseline estimate and accompanying framework of the model cases, upon which an accompanying "Part 2" study will build to refine the values for these and other air pollutants across these scenarios, also considering mitigation options to comply with applicable regulatory standards. We also highlight further optimization opportunities based on potential tradeoffs identified here between air emissions versus life-cycle greenhouse gas profiles attributed to the disposition of lignin/residual solids.

09 BIOMASS FUELS↗
DOE OSTI2026

Chemical-Free Lithium Separation from High-Salinity Brines Using Model-Informed and Machine Learning-Optimized Multi-Column Zwitterionic Chromatography

Direct Lithium Extraction (DLE) technologies often struggle to produce high-purity lithium salts from high-salinity brines, as current approaches require chemical-based elution, regeneration, and precipitation steps, resulting in significant environmental footprints. A novel salt fractionation approach using carboxybetaine resin, known as zwitterionic chromatography (ZIC), has demonstrated that lithium ions can be separated from divalent cations under high-salinity conditions using only water as eluent, with no regeneration required. To enable continuous and scalable deployment of this approach, we developed a chemical-free Multi-column Zwitterionic Chromatography (MZC) process and its theoretical and process models. To predict and optimize this nontraditional separation system, we introduced a novel anti-Langmuir isotherm, and the isotherm parameters were estimated through a machine learning-driven optimization based on artificial neural network ensembles with numerical feasibility assessment. Using machine learning-driven optimization, the MZC process achieved 98.0% lithium recovery, 99.5 % Li/(Li + Mg + Ca) purity, a 31.3% productivity increase, and a 33% reduction in water use compared to batch operation. The proposed MZC process enables lithium separation at $0.6-1.2 kg-1 Li, with costs dominated by resin manufacturing, while offering lower separation costs and carbon footprint compared with conventional carbonation. Overall, these findings position the MZC process as an effective polishing step within scalable and sustainable lithium production pipelines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Sequential ensemble transform for Bayesian inverse problems

In this work, we present the Sequential Ensemble Transform (SET) method, an approach for generating approximate samples from a Bayesian posterior distribution. The method explores the posterior distribution by solving a sequence of discrete optimal transport problems to produce a series of transport plans which map prior samples to posterior samples. We prove that the sequence of Dirac mixture distributions produced by the SET method converges weakly to the true posterior as the sample size approaches infinity. Furthermore, our numerical results indicate that, when compared to standard Sequential Monte Carlo (SMC) methods, the SET approach is more robust to the choice of Markov mutation kernels and requires less computational efforts to reach a similar accuracy when used to explore complex posterior distributions. Finally, we describe adaptive schemes that allow to completely automate the use of the SET method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

An epitaxial surface heterostructure anchoring approach for high-performance Ni-rich layered cathodes

Nickel-rich (Ni≥90%) layered oxides materials have emerged as a promising candidate for next-generation high-energy-density lithium-ion batteries (LIBs). However, their widespread application is hindered by structural fatigue and lattice oxygen loss. In this work, an epitaxial surface rock-salt nanolayer is successfully developed on the LiNi 0.9 Co 0.1 O 2 sub-surface via heteroatom anchoring utilizing high-valence element molybdenum modification. This in-situ formed conformal buffer phase with a thickness of 1.2nm effectively suppresses the continuous interphase side-reactions, and thus maintains the excellent structure integrity at high voltage. Furthermore, theoretical calculations indicate that the lattice oxygen reversibility in the anion framework of the optimized sample is obviously enhanced due to the higher content of O 2p states near the Fermi level than that of the pristine one. Meanwhile, the stronger Mo–O bond further reduces cell volume alteration, which improves the bulk structure stability of modified materials. Besides, the detailed charge compensation mechanism suggests that the average oxidation state of Ni is reduced, which induces more active Li + participating in the redox reactions, boosting the cell energy density. As a result, the uniquely designed cathode materials exhibit an extraordinary discharge capacity of 245.4 mAh g −1 at 0.1 C, remarkable rate performance of 169.3 mAh g −1 at 10 C at 4.5V, and a high capacity retention of 70.5% after 1000 cycles in full cells at a high cut-off voltage of 4.4V. Further, this strategy provides an valuable insight into constructing distinctive heterostructure on high-performance Ni-rich layered cathodes for LIBs.

25 ENERGY STORAGE↗
DOE OSTI2024

Pd-CeO 2 catalyst facilely derived from one-pot generated Pd@Ce-BTC for low temperature CO oxidation

Due to the capacity to offer abundant catalytic sites within porous solids featuring high surface areas, metal-organic frameworks (MOFs) and their derivatives have garnered considerable attention as prospective catalysts in environmental catalysis. Here, to promote the industrial application of MOFs, there is an urgent need for an effective and environmental-friendly preparation approach. Breaking through the limitation of the traditional two-step preparation method that Pd was introduced to the already prepared Ce-BTC (Pd/Ce-BTC, BTC = 1, 3, 5 benzenetricarboxylate), in this work, we present a novel one-pot solvothermal method for synthesizing the Pd material supported by Ce-BTC (Pd@Ce-BTC). After pyrolysis in N 2 flow or air flow, Pd-CeO 2 catalysts derived from Pd@Ce-BTC exhibited much higher CO oxidation activity than those from Pd/Ce-BTC. Moreover, Pd/Ce-BTC and Pd@Ce-BTC pyrolyzed in N 2 flow (Pd/Ce-BTC-N and Pd@Ce-BTC-N) could better catalyze the oxidation of CO than Pd/Ce-BTC and Pd@Ce-BTC pyrolyzed in air flow (Pd/Ce-BTC-A and Pd@Ce-BTC-A). Further characterizations revealed that the abundant surface Ce 3+ species, rich surface adsorbed oxygen species and superior redox properties were the main reasons for the superior CO oxidation activity of Pd@Ce-BTC-N.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ensemble modeling of global lake evaporation under climate change

Global projections of lake evaporation are typically based on simulations using single mechanistic models. However, because of its complex interactions with various lake physical properties, environmental and anthropogenic drivers, lake evaporation is highly variable and sensitive to the choice of model used. In this study, we present a multi-model analysis to investigate differences across global simulations of lake evaporation during the warm-season using three different lake models driven by outputs from four general circulation models (GCM) (i.e. 12 model combinations in total) for historic and future scenarios. Our results suggest substantial differences among lake-climate model simulations of lake evaporation. These differences varied throughout the 20th and 21st century, with model driver data explaining 74% of the variance in future projections of warm- season lake evaporation. Our projections indicate that, by the end of the 21st century (2070–2099), global annual lake evaporation rates will increase by 10–27% under Representative Concentration Pathways (RCPs) 2.6–8.5. Finally, we highlight the importance of using a multi-model approach for the prediction of future global lake evaporation responses to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Improving the prediction of daily reservoir releases over the CONUS using conditioned LSTM

Reservoirs play a vital role in regulating streamflow timing and variability for hydroelectricity, flood control, water supply, irrigation, and recreation. Despite their importance, many reservoirs lack comprehensive operational guidelines, making their management complex due to conflicting operational objectives. Hence traditional policy-based reservoir models often fail to capture real-world conditions accurately and they depend on perfect streamflow predictions, which are not always available. In contrast, data-driven models like Long Short-Term Memory (LSTM) networks offer a robust alternative. This study introduces an approach that integrates reservoir characteristics—such as main use, climate, and maximum capacity—into the LSTM model to enhance reservoir release predictions. Using data from nearly 200 reservoirs in the contiguous United States (CONUS), our conditioned LSTM model (LSTM_cond) was compared with both the vanila LSTM and a traditional policy-based approach. Furthermore, our results show that while both LSTM_cond and LSTM perfoms better than the policy-based approach, LSTM_cond consistently outperforms LSTM for hydroelectric, water supply, irrigation, and recreation reservoirs. The KGE median values for LSTM_cond for out-sample reservoirs are 0.764, 0.565, 0.821, and 0.779, respectively, for the aforementioned reservoir types, which are consistently higher that the corresponding KGE values of 0.737, 0.413, 0.775, and 0.713 of LSTM, demonstrating its advantages in improving generalizability.

CONUS↗
DOE OSTI2026

Systematic Evaluation of Atmospheric Forcing, Surface Datasets, and Mesh Effects on Kilometer-Scale Land Surface and River Modeling

Earth system models are advancing toward kilometer-scale resolution to capture local climate impacts and extremes. High-resolution land and river modeling depends on multiple factors, including mesh, surface datasets, and atmospheric forcing, but their relative effects at kilometer scales remain unquantified. We evaluated five Energy Exascale Earth System Model land and river configurations over the Mid-Atlantic region using two mesh (1/8° structured versus variable-resolution unstructured mesh), two surface datasets (default versus newly developed), and three atmospheric forcings (NLDAS2, MSWX, GSWP). Evaluation against satellite, reanalysis, and in situ benchmarks across water, energy, and carbon cycles quantifies how these factors affect model performance. Forcing selection produces the largest bias reductions (12-99% across variables), followed by surface datasets (7-75%) and mesh (up to 21%). Forcing effects vary by variable, with MSWX reducing biases for snow water equivalent, evapotranspiration, albedo, temperature, and gross primary productivity, GSWP for snow cover and runoff, and NLDAS for soil moisture and streamflow. The use of newly developed surface datasets improves gross primary productivity (58% bias reduction) and evapotranspiration but increase soil moisture and albedo biases due to current modeling limitations. Variable-resolution unstructured mesh improves the simulation of small-basin streamflow through better capturing drainage networks, though mesh minimally affects other land variables. These findings provide important guidance for high-resolution modeling development and actionable science.

Land and River modeling↗
DOE OSTI2026

X-ray observation of individual Ti-6Al-4V spherical powder particle impact in an in-situ operando laser directed energy deposition system

Understanding the particle capture mechanism in the laser directed energy deposition additive manufacturing process provides a foundation for improving productivity and reducing material loss. Capturing this phenomenon is challenging due to its highly transient time interval. To analyze the impact behavior of spherical Ti-6Al-4V powder, a custom laser directed energy deposition system was designed to control the deposition of individual particles. Synchrotron X-ray imaging at 24 kHz monitored the impact dynamics of individual powder particles. A multi-physics model based on the Smoothed-Particle Hydrodynamics scheme supported the analysis by providing the temperature and velocity fields of the molten pool. Results revealed that in laser directed energy deposition, surface tension forces dominated the powder–molten pool interaction. Hydrophobic Ti-6Al-4V powder particles had an equilibrium contact angle of 121 degrees with their molten state. Furthermore, Ti-6Al-4V powder particles required a high impact velocity (6 to 12 m/s) to transition from oscillation to submergence behavior. Lastly, oscillating powder particles that impacted near the location of the laser beam exhibited faster melting, highlighting the contribution of the laser beam to the melting mechanism. This work lays the foundation for investigations of powder particle impact in laser directed deposition and supports the validation of numerical models of powder–molten pool interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A novel design of transitional layer structure between reduced activation ferritic martensitic steels and tungsten for plasma facing materials

Plasma-facing components (PFCs) are among the most critical gaps for fusion energy to establish technical and economic feasibility. Tungsten as a first wall/blanket material in PFCs requires to be integrating with reduced activation ferritic martensitic (RAFM) steels as a structural component. Currently, major drawbacks are the requirement of brazing, the formation of a brittle interface, and a large difference between the coefficients of thermal expansion of tungsten and steel. Here, a novel transitional multilayer structure was designed and investigated to join tungsten and RAFM steels using three interlayers. The composition of each interlayer was selected based on computational thermodynamics and diffusion kinetics to ensure a body-centered cubic (bcc) single-phase structure and prevent the formation of a brittle intermetallic phase region in the temperature range of 600–1150 °C. Although the transitional layer structure was designed for additive manufacturing, spark plasma sintering (SPS) as proof of concept was used to bond the individual layers. Interfaces were investigated using scanning and transmission electron microscopy methods but no layered intermetallic phase was observed. Nanoindentation maps across the interface suggest major hardness differences at the interface between tungsten and the vanadium interlayer, as well as the interface between RAFM steel and the FeCrAl interlayer.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effects of carbonitrides and carbides on microstructure and properties of castable nanostructured alloys

In this work, to develop advanced reduced-activation ferritic-martensitic (RAFM) steels for fusion reactor structural applications, both carbonitride- and carbide-strengthened castable nanostructured alloys (CNAs) were explored for higher densities of MX (M = Ti/Ta/V/etc. and X = C/N) nanoprecipitates. Additionally, systematic comparisons between the two types of CNAs indicated generally similar microstructures and comparable tensile properties and creep resistance. However, the carbide-CNAs did show some advantages over the carbonitride-CNAs in terms of the uniformly distributed higher density of MC nanoprecipitates, greater Charpy impact upper shelf energies, less deuterium retention and swelling, and potentially less transmutation-induced composition changes and consequently thermodynamically more stable carbides. The carbide-CNAs showed the best-balanced high performance in the examined properties, in contrast to the significantly varied performance of oxide-dispersion-strengthened alloys and the generally lower performance of current RAFM steels.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effects of helium on irradiation response of reduced-activation ferritic-martensitic steels: Using nickel isotopes to simulate fusion neutron response

Understanding the effects of helium on microstructures and mechanical properties of reduced-activation ferritic-martensitic steels is important to use of these steels in fusion reactor structures. The 9Cr-2WVTa steels were doped with 58Ni and 60Ni isotopes at 2 weight percent to control the rate of transmutation helium generation. The samples were irradiated in the High Flux Isotope Reactor to ~24 displacements per atom at nominal temperatures of 300, 400, and 500°C, producing 228 and 7 atomic parts-per-million helium in the 58 Ni- and 60 Ni-doped samples, respectively. Transmission electron microscopy revealed a variety of precipitates and the radiation-induced dislocation loops and cavities (voids or helium bubbles). Tensile tests of the irradiated samples at the irradiation temperatures showed radiation-induced hardening at 300°C and radiation-induced softening at 400°C. Analysis indicates that the hardening primarily originated from the loops and cavities. The 58 Ni-doped samples had greater strengthening contributions from loops and cavities, leading to higher hardening with lower ductility than the 60 Ni-doped samples. The greater helium production of 58 Ni did not show pronounced reductions in ductility of the samples.

36 MATERIALS SCIENCE↗