Results for “Temperature boosting” — Page 14

NASA NTRS1998

Performance of the Spacecraft Propulsion Research Facility During Altitude Firing Tests of the Delta 3 Upper Stage

The Spacecraft Propulsion Research Facility at the NASA Lewis Research Center's Plum Brook Station was reactivated in order to conduct flight simulation ground tests of the Delta 3 cryogenic upper stage. The tests were a cooperative effort between The Boeing Company, Pratt and Whitney, and NASA. They included demonstration of tanking and detanking of liquid hydrogen, liquid oxygen and helium pressurant gas as well as 12 engine firings simulating first, second, and third burns at altitude conditions. A key to the success of these tests was the performance of the primary facility systems and their interfaces with the vehicle. These systems included the structural support of the vehicle, propellant supplies, data acquisition, facility control systems, and the altitude exhaust system. While the facility connections to the vehicle umbilical panel simulated the performance of the launch pad systems, additional purge and electrical connections were also required which were unique to ground testing of the vehicle. The altitude exhaust system permitted an approximate simulation of the boost-phase pressure profile by rapidly pumping the test chamber from 13 psia to 0.5 psia as well as maintaining altitude conditions during extended steady-state firings. The performance of the steam driven ejector exhaust system has been correlated with variations in cooling water temperature during these tests. This correlation and comparisons to limited data available from Centaur tests conducted in the facility from 1969-1971 provided insight into optimizing the operation of the exhaust system for future tests. Overall, the facility proved to be robust and flexible for vehicle space simulation engine firings and enabled all test objectives to be successfully completed within the planned schedule.

Meyer, Michael L.↗

NASA NTRS2003

Accretion Disk Spectra of the Ultra-luminous X-ray Sources in Nearby Spiral Galaxies and Galactic Superluminal Jet Sources

Ultra-luminous Compact X-ray Sources (ULXs) in nearby spiral galaxies and Galactic superluminal jet sources share the common spectral characteristic that they have unusually high disk temperatures which cannot be explained in the framework of the standard optically thick accretion disk in the Schwarzschild metric. On the other hand, the standard accretion disk around the Kerr black hole might explain the observed high disk temperature, as the inner radius of the Kerr disk gets smaller and the disk temperature can be consequently higher. However, we point out that the observable Kerr disk spectra becomes significantly harder than Schwarzschild disk spectra only when the disk is highly inclined. This is because the emission from the innermost part of the accretion disk is Doppler-boosted for an edge-on Kerr disk, while hardly seen for a face-on disk. The Galactic superluminal jet sources are known to be highly inclined systems, thus their energy spectra may be explained with the standard Kerr disk with known black hole masses. For ULXs, on the other hand, the standard Kerr disk model seems implausible, since it is highly unlikely that their accretion disks are preferentially inclined, and, if edge-on Kerr disk model is applied, the black hole mass becomes unreasonably large (greater than or approximately equal to 300 Solar Mass). Instead, the slim disk (advection dominated optically thick disk) model is likely to explain the observed super- Eddington luminosities, hard energy spectra, and spectral variations of ULXs. We suggest that ULXs are accreting black holes with a few tens of solar mass, which is not unexpected from the standard stellar evolution scenario, and their X-ray emission is from the slim disk shining at super-Eddington luminosities.

White, Nicholas E.↗

DOE OSTI2025

Data‐Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data

Understanding rare‐earth element (REE) mineralization mechanisms is essential for developing efficient separation strategies. Although the geochemical pathways that generate REE deposits are qualitatively known, quantitative links between specific conditions and mineralization outcomes remain limited. Herein, the repurpose laboratory REE hydrothermal synthesis data—originally collected for functional‐materials fabrication—as a surrogate for studying mineralization with data‐driven methods. The compiled 1,200+ hydrothermal reaction records and trained three machine‐learning models—K‐nearest neighbors (KNN), random forest (RF), and extreme gradient boosting (XGB)—to predict product elements and phases from precursors, additives, reaction conditions, and engineered features. Validation shows XGB achieves the highest accuracy. Feature importance indicates thermodynamic properties of cations and anions dominate model decisions. Correlations reveal positive relationships among precursor concentration, reaction time, pH, and temperature, consistent with classical crystallization behavior. XGB‐based regressors are built to predict crystallization temperature and pH from precursor/product attributes. Performance is strongest when similar training examples exist, while accuracy declines for underrepresented reactions, notably REE carbonates and heavy‐REE systems. Overall, the study shows that functional‐materials datasets can illuminate REE mineralization and provide priors for exploration and processing. Expanding datasets with less‐studied chemistries and conditions will improve generality and support deposit discovery and more efficient REE recovery.

feature importance analysis↗

DOE OSTI2020

Coupling High-Throughput Experiments and Regression Algorithms to Optimize PGM-Free ORR Electrocatalyst Synthesis

Over the past decades, significant improvement has been achieved in the performance of platinum group metal-free (PGM-free) materials as an alternative to Pt-based electrocatalysts for oxygen reduction reaction (ORR). However, further progress in ORR activity requires evaluation of precursors and synthesis approaches. In response to this challenge, we generated a first of its kind experimental data set of 36 samples using high-throughput synthesis and activity measurements. Several control parameters (e.g., Fe precursor identity, the precursor content, and pyrolysis temperature) were varied. We then developed several state-of-the-art machine learning (ML) based regression models to predict ORR activity, dependent on selected synthesis variables. Through an iterative algorithm, higher prediction accuracy (smaller root-mean-square error) was achieved. We identified that gradient boosting regression (GBR) and support vector regression (SVR), among several methods, work best for this data set. Aided by our ML-based surrogate models, we decided to alter catalyst synthesis conditions, which resulted in a 36% increase in measured ORR activity in comparison to the maximum ORR mass activity value of 21.9 A/g catalyst in the original data set. Overall, this combined experiment and machine learning approach represents a promising path forward toward developing highly efficient next-generation ORR electrocatalysts and, more generally, functional materials.

25 ENERGY STORAGE↗

DOE OSTI2025

Aligning thermal and current quenches with a high density low-Z injection

The conventional approach for thermal quench (TQ) mitigation in a tokamak disruption is through a high- Z impurity injection that radiates away the plasma’s thermal energy before it reaches the wall. The downside is a robust Ohmic-to-runaway current conversion due to the radiatively clamped low post-thermal-quench electron temperature. An alternative approach is to deploy a low- Z (either deuterium or hydrogen) injection that aims to slow down the TQ, and ideally aligns it with the current quench (CQ). This approach has been investigated here via 3D MHD simulations using the PIXIE3D code. By boosting the hydrogen density, a fusion-grade plasma is dilutionally cooled at approximately the original pressure. Energy loss to the wall is controlled by a Bohm outflow condition at the boundary where the magnetic field intercepts a thin plasma sheath at the wall, in addition to Bremsstrahlung bulk losses. Robust MHD instabilities proceed as usual, while the collisionality of the plasma has been greatly increased and parallel transport is now in the Braginskii regime. The main conclusion of this study is that the decreased transport loss along open field lines due to a sufficient low- Z injection slows down the TQ rate to the order of 20 ms, aligned with the CQ timescale for a 15 MA ITER plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Sulfur-Doped Carbon Support Boosts CO2RR Activity of Ag Electrocatalysts

For presentation at the 70th AVS International Symposium and Exhibition. In this work, we show that the activity of Ag electrocatalysts for electrochemical CO2 to CO conversion is improved when supported on sulfur-doped (S-doped) carbon materials. S-doped carbon support was created by treating the heavily sputtered, highly oriented pyrolytic graphite (HOPG) in H2S at elevated temperatures, as confirmed by the S 2p X-ray photoelectron spectroscopy (XPS) peak. Scanning tunneling microscopy (STM) images indicated that Ag nanoparticles supported on S-doped HOPG had similar size distributions as those supported on sulfur-free (S-free) HOPG. While both catalysts reached > 90% CO Faradaic efficiency (FECO) at E = -1.3 V vs. the reversible hydrogen electrode (RHE) in the CO2 reduction reaction (CO2RR), Ag catalysts supported on S-doped HOPG demonstrated 70% higher CO turnover frequency (TOFCO = 3.4 CO/atomAg/s) than those supported on S-free HOPG (TOFCO = 2.0 CO/atomAg/s). Preliminary calculations based on density functional theory (DFT) indicated a more favorable energetic pathway of CO2-to-CO at the C-S-Ag interface, tentatively consistent with experiments. These results hint at a new approach to design active and selective electrocatalysts for CO2 conversion.

Deng, Xingyi↗

DOE OSTI2026

Evapotranspiration partitioning estimates from 8 methods from 47 NEON sites, 2019-2021

This dataset provides daily estimates of evapotranspiration (ET) and the transpiration-to-evapotranspiration ratio (T/ET) across 47 terrestrial National Ecological Observatory Network (NEON) sites spanning diverse environmental and biome conditions in the United States across three years of data (2019-2021). Daily ET is reported in both energy units (MJ m⁻² day⁻¹) and equivalent water depth (mm day⁻¹), assuming a constant latent heat of vaporization of 2.45 MJ/kg. The primary method uses a hybrid recurrent neural network–Penman–Monteith framework (RNN-PM), which integrates physically based surface energy balance constraints with data-driven learning to partition ET into transpiration and evaporation components. Model inputs include in situ meteorological observations (air temperature, vapor pressure deficit, wind speed, and radiation) combined with satellite-derived land surface temperature, leaf area index, and soil moisture. For benchmarking and uncertainty assessment, T/ET estimates from seven additional models are included: Priestley-Taylor Jet Propulsion Laboratory (PT-JPL), Penman-Monteith (P-M), Two-Source Energy Balance (TSEB), Support Vector Regression (SVR), and Categorical Boosting (CatBoost), among others—spanning empirical, machine-learning, and process-based approaches (see methods section or linked publication for detailed descriptions). Data Package Contents: The dataset a csv files containing daily ET and T/ET estimates for each site and model, along with associated metadata files these variables. Data can be accessed using common spreadsheet software (e.g., Microsoft Excel, LibreOffice) or programming environments such as R or Python. Together, these data support cross-site comparisons of ecosystem water use, evaluation of ET partitioning methods, and development of improved land–atmosphere exchange models.

EARTH SCIENCE > ATMOSPHERE↗

DOE OSTI2026

Tailorable multiferroic tunnel junctions from all-van der Waals multilayer stacking

Multiferroic tunnel junctions (MFTJs) represent a class of multistate, non-volatile spintronic devices, in which electron tunnelling can be manipulated by switching long-range lattice and spin orders. In contrast to conventional oxide-based MFTJs, MFTJs constructed from two-dimensional van der Waals (vdW) crystals promise minimal defect concentration in the constituents and at interfaces, which may allow for probing intrinsic tunnelling physics and the development of high-performance devices. Here, in this study, we construct Fe 3 GeTe 2 /CuInP 2 S 6 /Fe 3 GeTe 2 all-vdW MFTJs by assembling multilayer flakes of ferromagnetic Fe 3 GeTe 2 electrodes and a ferroelectric CuInP 2 S 6 spacer. These MFTJs exhibit four non-volatile resistance states featuring sizable tunnelling magnetoresistance of ∼10 2 % and tunnelling electroresistance of ∼10 4 %. To tune the properties of the vdW MFTJ, we make use of the flexibility in material choice offered by vdW heterostructure devices; we use Fe 3 GeTe 2 /Fe 5 GeTe 2 asymmetric electrodes to boost the tunnelling electroresistance by 10 3 %, we integrate In 2 Se 3 as a ferroelectric with a smaller bandgap to enhance the ON-state current density by 10 4 % to 10 4 A cm −2 and we use Fe 3 GaTe 2 electrodes to demonstrate room temperature operation. Furthermore, when we combine the asymmetric ferromagnetic electrodes with the small-bandgap ferroelectric spacer to construct Fe 3 GeTe 2 /In 2 Se 3 /Fe 5 GeTe 2 MFTJs, we simultaneously realized tunnelling electroresistance of 10 6 % and an ON-state current density of 10 4 A cm −2 , both two orders of magnitude higher than the highest values achieved with conventional oxide-based MFTJs. In the future, our all-vdW MFTJs with the tailorability of all functional layers may make it possible to investigate fundamental aspects of interlayer tunnelling and enable the design of functional magnetoelectric nanodevices.

Xie, Ti [University of Maryland, College Park, MD ↗

DOE OSTI2025

Machine-learning and first-principles investigation of lightweight medium-entropy alloys for hydrogen-storage applications

The transition to a low-carbon economy demands efficient and sustainable energy-storage solutions, with hydrogen emerging as a promising clean-energy carrier and with metal hydrides recognized for their hydrogen-storage capacity. Here, we leverage machine learning (ML) to predict hydrogen-to-metal (H/M) ratios and solution energy by incorporating thermodynamic parameters and local lattice distortion (LLD) as key features. Our best-performing ML model provides improvements to H/M ratios and solution energies over a broad class of medium-entripy alloys (easily extendable to multi-principal-element alloys), such as Ti–Nb-X (X = Mo, Cr, Hf, Ta, V, Zr) and Co–Ni-X (X = Al, Mg, V). Ti–Nb–Mo alloys reveal compositional effects in H-storage behavior, in particular Ti, Nb, and V enhance H-storage capacity, while Mo reduces H/M and hydrogen weight percent by 40–50 %. We attributed results in molybdenum-rich alloys to slow hydrogen kinetics, as validated by our pressure-composition-temperature (PCT) isotherm experiments on pure Ti and Ti 5 Mo 95 alloys. Density functional theory (DFT) and molecular dynamics (MD) simulations also confirm that Ti and Nb promote H diffusion, whereas Mo hinders it, highlighting the interplay between electronic structure, lattice distortions, and hydrogen uptake. Notably, our Gradient Boosting Regression model identifies LLD as a critical factor in H/M predictions. Here, to aid material selection, we present two periodic tables illustrating elemental effects on (a) H 2 wt% and (b) solution energy, derived from ML, and provide a reference for identifying alloying elements that enhance hydrogen solubility and storage.

08 HYDROGEN↗

NASA NTRS1990

The performance of multilayer insulation in a rapidly depressurizing environment

The performance of multilayer insulation in a rapidly depressurizing environment is determined by the variation of heat transfer with internal pressure and the pressure history of the interstitial gas. Measurements of thermal performance were made on three multilayer insulation configurations at room temperature and steady state pressures from 10(exp -6) to 10(exp -1) torr. The heat transfer due to gas conduction alone correlated with the kinetic theory of gases in the molecular flow regime. Pressure histories were measured in a unique apparatus which simulated the depressurization rate of a boost vehicle. The pressure histories on both sides of two of the configurations were measured to bound the actual interstitial pressure. The results of the two types of measurements agreed with earlier work and were combined to make performance predictions using an actual ascent pressure history.

Efromson, Ronald A.↗

NASA NTRS1938

Engine Performance and Knock Rating of Fuels for High-output Aircraft Engines

Data are presented to show the effects of inlet-air pressure, inlet-air temperature, and compression ratio on the maximum permissible performance obtained on a single-cylinder test engine with aircraft-engine fuels varying from a fuel of 87 octane number to one 100 octane number plus 1 ml of tetraethyl lead per gallon. The data were obtained on a 5-inch by 5.75-inch liquid-cooled engine operating at 2,500 r.p.m. The compression ratio was varied from 6.50 to 8.75. The inlet-air temperature was varied from 120 to 280 F. and the inlet-air pressure from 30 inches of mercury absolute to the highest permissible. The limiting factors for the increase in compression ratio and in inlet-air pressure was the occurrence of either audible or incipient knock. The data are correlated to show that, for any one fuel,there is a definite relationship between the limiting conditions of inlet-air temperature and density at any compression ratio. This relationship is dependent on the combustion-gas temperature and density relationship that causes knock. The report presents a suggested method of rating aircraft-engine fuels based on this relationship. It is concluded that aircraft-engine fuels cannot be satisfactorily rated by any single factor, such as octane number, highest useful compression ratio, or allowable boost pressure. The fuels should be rated by a curve that expresses the limitations of the fuel over a variety of engine conditions.

Rothbrock, A M↗

DOE OSTI2025

Optimizing the critical temperature and superfluid density of a metal-superconductor bilayer

A promising path to realizing higher superconducting transition temperatures 𝑇 c is the strategic engineering of artificial heterostructures. For example, quantum materials could, in principle, be coupled with other materials to produce a more robust superconducting state. Here, in this work, we add numerical support to the hypothesis that a strongly interacting superconductor weakened by phase fluctuations can boost its 𝑇 c by hybridizing the system with a metal. Using determinant quantum Monte Carlo, we simulate a two-dimensional bilayer composed of an attractive Hubbard model and a metallic layer in two regimes of the interaction strength −|𝑈|. In the strongly interacting regime, we find that increasing the interlayer hybridization 𝑡 ⊥ results in a nonmonotonic enhancement of 𝑇 c , with an optimal value comparable to the maximum 𝑇 c observed in the single-layer attractive Hubbard model, confirming trends inferred from other approaches. In the intermediate coupling regime, when −|𝑈| is close to the value associated with the maximum 𝑇 c of the single-layer model, increasing 𝑡 ⊥ tends to decrease 𝑇 c , implying that the correlated layer was already optimally tuned. Importantly, we demonstrate that the mechanism behind these trends is related to enhancement in the superfluid stiffness, as was initially proposed by Kivelson [Phys. B: Condens. Matter 318, 61 (2002)].

Zhang, Yutan [Univ. of California, Davis, CA (Unit↗

DOE OSTI2020

Effect of water vapor on high-temperature oxidation of NiAl alloy

The high-temperature oxidation of NiAl is studied with dry oxygen and water vapor. The oxidation in H 2 O results in a thicker Al 2 O 3 oxide scale than that in O 2 . The oxide scale formed initially is a single layer of γ-Al 2 O 3 that subsequently transforms into a α-Al 2 O 3 /γ-Al 2 O 3 bilayer structure, in which the inner α-Al2O3 layer formed in H2O has a higher porosity than that in O 2 . Finally, further density functional theory calculations show that H protons derived from H 2 O molecules penetrate into the oxide lattice and boost the formation of lattice vacancies in both α-Al 2 O 3 and γ-Al 2 O 3 , thus enhancing the oxide scale growth.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Design of a Cryogenic Assembly for Comparing Qubit Infrared Packaging Inefficiencies

It is well known that everything emits infrared (IR) light in the form of thermal radiation. IR radiation on superconducting qubits carries enough energy to cause decoherence and so-called “quasiparticle poisoning.” Therefore, proper IR shielding is needed to keep the qubit in a high-coherence state. However, trying to extract IR-specific information from a qubit is difficult, so a microwave kinetic inductance detector (MKID) can be used instead. We show that the IR shielding inefficiencies of MKID packages can only be compared with other packaging inefficiencies. We create a cryogenic assembly CAD design, consisting of magnetic shield cans, a copper mounting plate and mounts, and an MKID enclosure, which thermalizes the assembly to dilution refrigerator temperatures. Phase 1 of this design involves using a narrowband IR laser source to test the IR shielding of packaging at the laser’s wavelength. When the best IR shielding packaging is determined, the superconducting qubit can replace the MKID, allowing the qubit to avoid decoherence due to IR radiation and boost its performance and coherence lifetime.

Mailliard, Robert J. [Fermilab] (ORCID:00090000277↗

DOE OSTI2026

Design of a Cryogenic Assembly for Comparing Qubit Infrared Packaging Inefficiencies

It is well known that everything emits infrared (IR) light in the form of thermal radiation. IR radiation on superconducting qubits carries enough energy to cause decoherence and so-called “quasiparticle poisoning.” Therefore, proper IR shielding is needed to keep the qubit in a high-coherence state. However, trying to extract IR-specific information from a qubit is difficult, so a microwave kinetic inductance detector (MKID) can be used instead. We show that the IR shielding inefficiencies of MKID packages can only be compared with other packaging inefficiencies. We create a cryogenic assembly CAD design, consisting of magnetic shield cans, a copper mounting plate and mounts, and an MKID enclosure, which thermalizes the assembly to dilution refrigerator temperatures. Phase 1 of this design involves using a narrowband IR laser source to test the IR shielding of packaging at the laser’s wavelength. When the best IR shielding packaging is determined, the superconducting qubit can replace the MKID, allowing the qubit to avoid decoherence due to IR radiation and boost its performance and coherence lifetime.

Mailliard, Robert J. [Fermilab] (ORCID:00090000277↗

DOE OSTI2026

Design of a Cryogenic Assembly for Comparing Qubit Infrared Packaging Inefficiencies

It is well known that everything emits infrared (IR) light in the form of thermal radiation. IR radiation on superconducting qubits carries enough energy to cause decoherence and so-called “quasiparticle poisoning.” Therefore, proper IR shielding is needed to keep the qubit in a high coherence state. However, trying to extract IR-specific information from a qubit is difficult, so a microwave kinetic inductance detector (MKID) can be used instead. We show that the IR shielding inefficiencies of MKID packages can only be compared with other packaging inefficiencies. We create a cryogenic assembly CAD design, consisting of magnetic shield cans, a copper mounting plate and mounts, and an MKID enclosure, which thermalizes the assembly to dilution refrigerator temperatures. Phase 1 of this design involves using a narrowband IR laser source to test the IR shielding of packaging at the laser’s wavelength. When the best IR shielding packaging is determined, the superconducting qubit can replace the MKID, allowing the qubit to avoid decoherence due to IR radiation and boost its performance and coherence lifetime.

Mailliard, Robert J. [Fermilab] (ORCID:00090000277↗

DOE OSTI2026

Design of a Cryogenic Assembly for Comparing Qubit Infrared Packaging Inefficiencies

It is well known that everything emits infrared (IR) light in the form of thermal radiation. IR radiation on superconducting qubits carries enough energy to cause decoherence and so-called “quasiparticle poisoning.” Therefore, proper IR shielding is needed to keep the qubit in a high-coherence state. However, trying to extract IR-specific information from a qubit is difficult, so a microwave kinetic inductance detector (MKID) can be used instead. We show that the IR shielding inefficiencies of MKID packages can only be compared with other packaging inefficiencies. We create a cryogenic assembly CAD design, consisting of magnetic shield cans, a copper mounting plate and mounts, and an MKID enclosure, which thermalizes the assembly to dilution refrigerator temperatures. Phase 1 of this design involves using a narrowband IR laser source to test the IR shielding of packaging at the laser’s wavelength. When the best IR shielding packaging is determined, the superconducting qubit can replace the MKID, allowing the qubit to avoid decoherence due to IR radiation and boost its performance and coherence lifetime.

Mailliard, Robert J. [Fermilab] (ORCID:00090000277↗

DOE OSTI2026

CMS Outer Tracker Module QA

It is well known that everything emits infrared (IR) light in the form of thermal radiation. IR radiation on superconducting qubits carries enough energy to cause decoherence and so-called “quasiparticle poisoning.” Therefore, proper IR shielding is needed to keep the qubit in a high-coherence state. However, trying to extract IR-specific information from a qubit is difficult, so a microwave kinetic inductance detector (MKID) can be used instead. We show that the IR shielding inefficiencies of MKID packages can only be compared with other packaging inefficiencies. We create a cryogenic assembly CAD design, consisting of magnetic shield cans, a copper mounting plate and mounts, and an MKID enclosure, which thermalizes the assembly to dilution refrigerator temperatures. Phase 1 of this design involves using a narrowband IR laser source to test the IR shielding of packaging at the laser’s wavelength. When the best IR shielding packaging is determined, the superconducting qubit can replace the MKID, allowing the qubit to avoid decoherence due to IR radiation and boost its performance and coherence lifetime.

Hobbeheydar, Samuel [Carnegie Mellon U. (main); Fe↗