Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “High Temperature Methods”

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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Solution‐Phase Metathesis of Li 3 N and FeCl 3 to Synthesize Fe 2 N/Fe 3 N Nanoparticles

Soft magnetic materials play key roles in the flow of energy in electrically driven machines and power conversion electronics, and there is a great need for improvements in their magnetic properties to provide the right combination of high saturation magnetization, low coercivity, and high permeability. Most phases of iron nitride (Fe x N) are soft magnetic materials with these characteristics, but they exist as numerous phases which are not all stoichiometric compounds. While the production and magnetic properties of the different phases of bulk iron nitride are well known, accessing phase‐pure nanoscale iron nitride consistently remains a challenge. Most methods for the synthesis of iron nitride nanoparticles require complicated apparatus to achieve high‐temperature nitriding of nanoparticle precursors with gaseous nitrogen sources such as ammonia. The first solution‐phase metathesis reaction between FeCl 3 and Li 3 N in oleylamine is developed to directly synthesize Fe 2 N/Fe 3 N nanoparticles, requiring only a fume hood, glove box, standard chemistry laboratory glassware, and equipment. Finally, the ≈10–15 nm spheres display nearly soft magnetic behavior with a saturation magnetization ≈50–60 A m 2 kg −1 , coercivities between 40–50 kA m −1 , and susceptibility values from 0.0001–0.0006 m 3 kg −1 , well within the ranges reported with other published Fe x N nanoparticle synthesis methods.

iron nitride↗
DOE OSTI2021

Image processing methods for Rayleigh scattering measurements of diesel spray mixing at high repetition rate

This work describes the diagnostic implementation and image processing methods to quantitatively measure diesel spray mixing injected into a high-pressure, high-temperature environment. We used a high-repetition-rate pulse-burst laser developed in-house, a high-speed CMOS camera, and optimized the optical configuration to capture Rayleigh scattering images of the vaporized fuel jets inside a constant volume chamber. The experimental installation was modified to reduce reflections and flare levels to maximize the images’ signal-to-noise ratios by anti-reflection coatings on windows and surfaces, as well as series of optical baffles. Because of the specificities of the high-speed system, several image processing techniques had to be developed and implemented to provide quantitative fuel concentration measurements. We find that these methods involve various correction procedures such as camera linearity, laser intensity fluctuation, dynamic background flare, as well as beam-steering effects. Image inpainting was also applied to correct the Rayleigh scattering signal from large scatterers (e.g. particulates). The experiments demonstrate that applying planar laser Rayleigh scattering at high repetition rate to quantitatively resolve the mixing of fuel and ambient gases in diesel jets is challenging, but possible. The thorough analysis of the experimental uncertainty and comparisons to past data prove that such measurements can be accurate, whilst providing valuable information about the mixing processes of high-pressure diesel jets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

An impermeable copper surface monolayer with high-temperature oxidation resistance

Despite numerous efforts involving surface coating, doping, and alloying, maintaining surface stability of metal at high temperatures without compromising intrinsic properties has remained challenging. Here, we present a pragmatic method to address the accelerated oxidation of Cu, Ni, and Fe at temperatures exceeding 200 °C. Inspired by the concept that oxygen (O) itself can effectively obstruct the pathway of O infiltration, this study proposes the immobilization of O on the metal surface. Through extensive calculations considering various elements (C, Al, Si, Ge, Ga, In, and Sn) to anchor O on Cu surfaces, Si emerges as the optimal element. The theoretical findings are validated through systematic sputtering deposition experiments. The introduction of anchoring elements to reinforce Cu–O bonds enables the formation of an atomically thin barrier on the Cu surface, rendering it impermeable to O even at high temperatures (400 °C) while preserving its intrinsic conductivity. This oxidation resistance, facilitated by the impermeable atomic monolayer, opens promising opportunities for researchers and industries to overcome limitations associated with the use of oxidizable metal films.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Temperature-Dependent Configurational Entropy Calculations for Refractory High-Entropy Alloys

The cluster expansion formalism for alloys is used to construct surrogate models for three refractory high-entropy alloys (NbTiVZr, HfNbTaTiZr, and AlHfNbTaTiZr). These cluster expansion models are then used along with Monte Carlo methods and thermodynamic integration to calculate the configurational entropy of these refractory high-entropy alloys as a function of temperature. Many solid solution alloy design guidelines are based on the ideal entropy of mixing, which increases monotonically with N , the number of elements in the alloy. However, our results show that at low temperatures, the configurational entropy of these materials is largely independent of N , and the assumption described above only holds in the high-temperature limit. This suggests that alloy design guidelines based on the ideal entropy of mixing require further examination.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Aluminum alloy compositions and methods of making and using the same

The present disclosure concerns embodiments of aluminum alloy compositions exhibiting superior microstructural stability and strength at high temperatures. The disclosed aluminum alloy compositions comprise particular combinations of components that contribute the ability of the alloys to exhibit improved microstructural stability and hot tearing resistance as compared to conventional alloys. Also disclosed herein are embodiments of methods of making and using the alloys.

Shyam, Amit↗
DOE OSTI2023

In Situ Study on Cu-to-Cu Thermal Compression Bonding

Cu-to-Cu thermal compression bonding (TCB) has emerged as a promising solution for ultrafine pitch packaging in 3D integrated circuit technologies. Despite the progress made by conventional Cu-to-Cu TCB methods in achieving good mechanical strength of the Cu bonds, the bonding processes generally require high temperature and high pressure, which may degrade the performance and reliability of the device. Therefore, it is imperative to investigate the processing parameters to understand the bonding mechanism and achieve effective TCB at a low temperature and low pressure. Here, we developed an in situ TCB technique inside a scanning electron microscope. The in situ TCB method enables a real-time observation of bonding development, which provides critical insights into how the texture and microstructure of Cu bumps may influence the creep and surface diffusion during the bonding process. This work features a strategy to advance our understanding of the bonding mechanisms and provides insight into tailoring the microstructure of Cu for bonding at a low temperature and low pressure.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Correlating Nb-SRF Surface Processing with Evolution of Surface Electronic States

The few nanometers of the surface exposed to RF field plays a major role in defining the RF performance of superconducting cavities. Over the past two decades, several pioneering surface treatment and processing methods have emerged, enabling remarkable improvements in cavity performance by simultaneously achieving high Q with increasing Eacc. These processing methods include: thermal treatment under ultra-high vacuum (UHV) conditions across lo¬¬¬¬¬¬¬w-, mid-, and high-temperature ranges and high temperature treatments under controlled N2 atmosphere. These processes also produce distinct surface oxide configurations with different valence states, thicknesses, and uniformity, as well as different oxygen concentration profiles in bulk Nb. In this work, we are trying to understand how do surface-processing methods and the resulting oxide/oxygen profiles affect the electronic structure of surface and the mechanism of superconductivity? With the help of Fermilab’s in-house X-ray photoemission facility and, in collaboration with the synchrotron-based angle-resolved photoemission (ARPES) facility at Argonne National Laboratory, we are investigating how the valence band structure and density of states (DoS) near the Fermi level modify with different surface treatments. Our observations show that different surface-processing methods lead to distinct evolutions of the valence-band states near the Fermi level during the superconducting transition. This behavior suggests variations in Nb-O orbital hybridizations and points towards the possibility of different underlying mechanisms of superconductivity governed by the surface chemistry and oxide configuration. We also correlate these distinct superconducting mechanisms with RF cavity performance, specifically focusing on measured surface resistance, the nature of the Q-slope, and quench fields observed in SRF measurements. These results will enable us to identify the potential limiting factors and relevant controllable parameters that can be further optimized to improve the performance of SRF cavities.

Tripathi, Malvika [Fermilab]↗
DOE OSTI2025

Evaluating probabilistic deep learning methods for uncertainty quantification of temperature downscaling

Deep learning (DL) has emerged as a promising tool for downscaling coarse-resolution climate data to high-resolution outputs, enabling improved regional climate predictions. A critical aspect of DL-based downscaling is the incorporation of uncertainty quantification (UQ), which enhances the interpretability and reliability of predictions—key factors for climate risk assessment and decision-making. This study develops a DL model to downscale 2 m temperature across the contiguous United States using reanalysis datasets. We systematically evaluate three epistemic UQ methods—deep ensembles (DEns), Monte Carlo dropout (MCD), and Flipout—based on their probabilistic accuracy, downscaling performance, sensitivity to geographical features, and computational efficiency. Results indicate that MCD generally outperforms Flipout and DEns in terms of calibration and downscaling accuracy. However, DEns demonstrate lower calibration errors in coastal regions, indicating its higher confidence within these areas. Flipout, in contrast, is more sensitive to elevation gradients and exhibits higher calibration errors in mountainous regions. Hence, the choice of UQ method for this task depends on the specific requirements of the application. For applications that prioritize overall calibration, downscaling accuracy, and computational efficiency, MCD is a strong candidate. These findings highlight the importance of selecting UQ methods based on application-specific requirements, such as geographical context and computational constraints. By addressing the trade-offs between UQ methods, this study provides actionable insights for improving the reliability, scalability, and utility of DL-based downscaling in climate science.

Environmental sciences↗
DOE OSTI2025

Estimating the Impacts of Increasing Temperatures and the Efficacy of Climate Adaptation Strategies in Urban Microclimates with Deep Learning

As urbanization and climate change progress, understanding and addressing urban heat becomes a priority for climate adaptation efforts. High temperatures concentrated in the urban core can drive increased risk of heat-related death and illness as well as increased energy demand for cooling. However, modeling the urban microclimate is an ongoing field of research typically burdened by an imprecise description of the built environment, incomplete observational records, significant computational cost, and a lack of high-resolution estimates of the impacts of increasing temperatures. Here, we present computationally efficient machine learning methods that can improve the accuracy of urban temperature estimates when compared to historical reanalysis data. These models are applied to a neighborhood in Los Angeles, and we compare the energy benefits of heat mitigation strategies to the impacts of climate change. We find that cooling demand is likely to increase substantially through midcentury, but engineered high-albedo surfaces could lessen this increase by more than 50 %. The corresponding increase in winter gas heating offsets the summer cooling benefit in the current climate, but total annual energy use from combined heating and cooling with electric heat pumps benefits from the engineered heat mitigation strategies under both current and future climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High-temperature thermal imaging to inform the arc-melt synthesis of nuclear materials

The advancement of nuclear energy technology necessitates the development of novel materials and synthesis methods to produce materials which enable new fuel cycles. Alongside the maturation of R&D scale technologies to produce these materials, there is an ongoing effort to develop in situ monitoring capabilities to reduce the time to the discovery and development of these fuels. Monitoring data can be leveraged in artificial intelligence platforms to detect phenomena which lead to varied macro- and microstructural features which impact the application and performance of samples synthesized. The present study presents early-stage findings of the implementation of high-temperature, high-frame-rate infrared thermal imaging to monitor the arc-melt synthesis of novel fuels and compounds relevant to advanced nuclear reactors. The study illustrates both the challenges and opportunities of this methodology, highlighting the importance of internal standards while determining emissivity and transmission values as well as visualizing volatilization during melt synthesis.

Stone, Jordan↗
DOE OSTI2020

Performance of Public Film Cooling Geometries Produced Through Additive Manufacturing

Abstract Film cooling is an essential cooling technology to allow modern gas turbines to operate at high temperatures. For years, researchers in this community have worked to improve the effectiveness of film cooling configurations by maximizing the coolant coverage and minimizing the heat flux from the hot gas into the part. Working toward this goal has generated many promising film cooling concepts with unique shapes and configurations. However, until recently, many of these designs were challenging to manufacture in actual turbine hardware due to limitations with legacy manufacturing methods. Now, with the advances in additive manufacturing, it is possible to create turbine parts using high-temperature nickel alloys that feature detailed and unique geometry features. Armed with this new manufacturing power, this study aims to build and test the promising designs from the public literature that were previously difficult or impossible to implement. In this study, different cooling hole designs were manufactured in test coupons using a laser powder bed fusion process. Each nickel alloy coupon featured a single row of engine scale cooling holes, fed by a microchannel. To evaluate performance, the overall cooling effectiveness of each coupon was measured using a matched Biot test at engine relevant conditions. The results showed that certain hole shapes are better suited for additive manufacturing than others and that the manufacturing process can cause significant deviations from the performance reported in the literature.

Engineering↗
DOE OSTI2021

Acoustic MEMS Sensor Array for Quench Detection of CICC Superconducting Cables

A novel quench detection method using microelectro- mechanical system (MEMS) sensor technology has been investigated in use for high temperature superconducting (HTS) conductors such REBCO tape cables. The sensor array along a superconducting cable, such as a cable-in-conduit-conductor (CICC), is installed in a cooling channel. It will allow sensitive and quick detection for a local quench of a superconducting cable. This work has confirmed that a quench of a single REBCO tape can be detected in liquid nitrogen by a MEMS piezoelectric microphone sensor. The quench detection design utilizing a MEMS sensor array method is discussed for the case of a toroidal field (TF) magnets of a fusion Tokamak device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

A quantitative phase-field model for gas bubble evolution in UO2

Due to the large formation energy of vacancies and noble gas atoms in the form of interstitials or substitutional atoms in nuclear fuel (UO2), the thermodynamic equilibrium concentrations of these species are very low in the nuclear fuel matrix even at very high temperatures, which imposes difficulties upon the quantitative study of bubble evolution via the phase-field method. In this study, a quantitative phase-field model is proposed to deal with this problem. The system’s free energy density is derived according to the principles of thermodynamics, with consideration of the elastic effect and with the use of real material parameters from experiments. The model is useful for the study of the kinetics of gas bubble growth with very dilute concentrations of vacancy and gas atoms in the matrix. This model is applied to study single bubble growth and multiple bubble growth under various concentrations of vacancy and gas atoms and at various temperatures. The elastic effect and the effects of the generation rate of vacancies and gas atoms on bubble growth are analyzed.

low defect concentration, nuclear fuel, gas bubble↗
DOE OSTI2020

High-Quality SnSe 2 Single Crystals: Electronic and Thermoelectric Properties

In this work, high-quality SnSe 2 single crystals were successfully synthesized using a temperature gradient method. N-type characteristics and strong anisotropic transport properties of SnSe 2 single crystals were exhibited between the ab plane and the c-axis. At 673 K, the power factor (PF) value along the ab plane is 3.43 μW cm -1 K -2 , while it is 0.92 μW cm -1 K -2 along the c-axis. The ratio between thermal conductivities along the ab plane (κ ab ) and c-axis (κ c ) is on the order of 7.6 at 300 K, while this value is about 5.6 at 673 K. The thermoelectric figure of merit (ZT) in the c-axis (0.15) is higher than that (0.1) along the ab plane, according to the ultralow out-of-plane thermal conductivity. The electronic band structure results, which were examined by angle-resolved photoemission spectroscopy (ARPES) predicted the potential of improving the thermoelectric performance of SnSe 2 single crystals by electron doping.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Synthesis of Fluorine-Doped Lithium Argyrodite Solid Electrolytes for Solid-State Lithium Metal Batteries

Solid-state lithium metal batteries (SSLMBs) that utilize novel solid electrolytes (SEs) have garnered much attention because of their potential to yield safe and high-energy-density batteries. Sulfide-based argyrodite-class SEs are an attractive option because of their impressive ionic conductivity. Recent studies have shown that LiF at the interface between Li and SE enhances electrochemical stability. However, the synthesis of F-doped argyrodites has remained challenging because of the high temperatures used in the state-of-the-art solid-state synthesis methods. In this work, for the f irst time, we report F-doped Li 5+y PS 5 F y argyrodites with a tunable doping content and dual dopants (F-/Cl- and F-/Br-) that were synthesized through a solvent-based approach. Among all compositions, Li 6 PS 5 F 0.5 C l0.5 exhibits the highest Li-ion conductivity of 3.5 x 10 -4 S cm -1 at room temperature (RT). Furthermore, Li symmetric cells using Li 6 PS 5 F 0.5 Cl 0.5 show the best cycling performance among the tested cells. X-ray photoelectron spectroscopy and ab initio molecular dynamics simulations revealed that the enhanced interfacial stability of Li 6 PS 5 F 0.5 C l0.5 SE against Li metal can be attributed to the formation of a stable solid electrolyte interphase (SEI)-containing conductive species (Li 3 P), alongside LiCl and LiF. These findings open new opportunities to develop high-performance SSLMBs using a novel class of F-doped argyrodite electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2026

Hyperspectral radiance mapping and chromatic correction for temperature measurement in laser-heated diamond anvil cells

In laser-heated diamond anvil cell (DAC) experiments, the effective heated region typically decreases in size with increasing pressure, leading to steeper thermal gradients. Under these conditions, chromatic aberration in the optical path from sample to detector can significantly create bias in spectro-radiometric temperature measurement. We present a radiance-mapping approach using a hyperspectral camera that records 25 spectral channels spanning 605–875 nm at each pixel in a single exposure, providing spatially and spectrally resolved radiance in each frame. This enables chromatic effects to be recorded and corrected in data processing. We developed a procedure for hyperspectral mapping, involving per-camera calibration, crosstalk removal, measured spectral throughput functions, and optional sub-pixel co-registration to minimize chromatic distortion. The calibrated radiance maps are then used to derive temperature maps of the laser-heated hotspots. For smaller heating spots, the radiance mapping approach reveals chromatic shifts that conventional spectro-radiometric methods cannot quantify. Ambient-pressure heating experiments confirm accurate temperature retrieval. At high pressure, application of the hyperspectral system to a platinum-heating experiment at 12 GPa demonstrates stable temperature reconstruction under steep thermal gradients. Beyond mitigating chromatic aberrations, the ability to diagnose optical artifacts separately from emissivity variations during controlled test experiments or in situ suggests a path toward more rigorous spectral emissivity analysis and improved modeling of thermal transport in laser-heated DAC experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Quasiparticle Scattering in a Superconductor near a Nematic Critical Point: Resonance Mode and Multiple Attractive Channels

We analyze the scattering rate for 2D fermions interacting via soft nematic fluctuations. The ground state is an s-wave superconductor, but other pairing channels are almost equally attractive. This strongly alters the scattering rate: At energies beyond the pairing gap Δ, it is renormalized by contributions from all pairing channels. At energies of order Δ, it is determined by the competition between scattering into a gapped continuum and dispersing nematic resonance. The outcome is a “peak-peak-dip-hump” spectrum, similar, but not identical, to the “peak-dip-hump” structure in the cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Prediction of s ± -Wave Superconductivity Enhanced by Electronic Doping in Trilayer Nickelates La 4 Ni 3 O 10 under Pressure

Motivated by the recently reported signatures of superconductivity in trilayer La 4 ⁢Ni 3 ⁢O 10 under pressure, here we comprehensively study this system using ab initio and random-phase approximation techniques. Without electronic interactions, the Ni d 3z 2 –r 2 orbitals show a bonding-antibonding and nonbonding splitting behavior via the O p z orbitals inducing a “trimer” lattice in La 4⁢ Ni 3 ⁢O 10 , analogous to the dimers of La 3 ⁢Ni 2 ⁢O 7 . The Fermi surface consists of three electron sheets with mixed e g orbitals, and a hole and an electron pocket made up of the d 3⁢z 2 –r 2 orbital, suggesting a Ni two-orbital minimum model. In addition, we find that superconducting pairing is induced in the s ± -wave channel due to partial nesting between the M = (π,π) centered pockets and portions of the Fermi surface centered at the Γ = (0,0) point. With changing electronic density n, the s ± instability remains leading and its pairing strength shows a domelike behavior with a maximum around n = 4.2 ( ~6.7% electron doping). The superconducting instability disappears at the same electronic density as that in the new 1313 stacking La 3 ⁢Ni 2 ⁢O 7 , correlated with the vanishing of the hole pocket that arises from the trilayer sublattice, suggesting that the high-T c superconductivity of La 3⁢ Ni 2 ⁢O 7 does not originate from a trilayer and monolayer structure. Furthermore, we confirm the experimentally proposed spin state in La 4 ⁢Ni 3 ⁢O 10 with an in-plane (π, π) order and antiferromagnetic coupling between the top and bottom Ni layers, and spin zero in the middle layer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗