Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “extreme value”

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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The High-energy Spectrum of the Nearby Planet-hosting Inactive Mid-M Dwarf LHS 3844

To fully characterize the atmospheres, or lack thereof, of terrestrial exoplanets, we must include the high-energy environments provided by their host stars. The nearby mid-M dwarf LHS 3844 hosts a terrestrial world that lacks a substantial atmosphere. We present a time-series UV spectrum of LHS 3844 from 1131 to 3215 Å captured by HST/COS. We detect one flare in the FUV that has an absolute energy of 8.96 ± 0.77 × 10{sup 28} erg and an equivalent duration of 355 ± 31 s. We extract the flare and quiescent UV spectra separately. For each spectrum, we estimate the Lyα flux using correlations between UV line strengths. We use Swift-XRT to place an upper limit on the soft X-ray flux and construct a differential emission model to estimate flux that is obscured by the interstellar medium. We compare the differential emission model flux estimates in the XUV to other methods that rely on scaling from the Lyα, Si iv, and N v lines in the UV. The XUV, FUV, and NUV flux of LHS 3844 relative to its bolometric luminosity is log{sub 10}(L {sub band}/L {sub Bol}) =−3.65, −4.16, and −4.48, respectively, for the quiescent state. These values agree with trends in high-energy flux as a function of stellar effective temperature found by the MUSCLES survey for a sample of early-M dwarfs. Many of the most spectroscopically accessible terrestrial exoplanets orbit inactive mid-to-late M dwarfs like LHS 3844. Measurements of M dwarf high-energy spectra are preferable for exoplanet characterization but are not always possible. The spectrum of LHS 3844 is a useful proxy for the current radiation environment for these worlds.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Coupled nuclear–electronic decay dynamics of O2 inner valence excited states revealed by attosecond XUV wave-mixing spectroscopy

Multiple Rydberg series converging to the $O_2^+$ c $^{4}Σ^{-}_{u}$ state, accessed by 20-25 eV extreme ultraviolet (XUV) light, serve as important model systems for the competition between nuclear dissociation and electronic autoionization. The dynamics of the lowest member of these series, the $3sσ_g $ state around 21 eV, has been challenging to study owing to its ultra-short lifetime (<10 fs). Here, we apply transient wave-mixing spectroscopy with an attosecond XUV pulse to investigate the decay dynamics of this electronic state. Lifetimes of 5.8 ± 0.5 fs and 4.5 ± 0.7 fs at 95% confidence intervals are obtained for v = 0 and v = 1 vibrational levels of the 3s Rydberg state, respectively. A theoretical treatment of predissociation and electronic autoionization finds that these lifetimes are dominated by electronic autoionization. The strong dependence of the electronic autoionization rate on the internuclear distance because of two ionic decay channels that cross the 3s Rydberg state results in the different lifetimes of the two vibrational levels. The calculated lifetimes are highly sensitive to the location of the 3s potential with respect to the decay channels; by slight adjustment of the location, values of 6.2 and 5.0 fs are obtained computationally for the v = 0 and v = 1 levels, respectively, in good agreement with experiment. Overall, an intriguing picture of the coupled nuclear-electronic dynamics is revealed by attosecond XUV wave-mixing spectroscopy, indicating that the decay dynamics are not a simple competition between isolated autoionization and predissociation processes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Simulation, Structural, Thermal and Mechanical Properties of the FeTiTaVW High Entropy Alloy

Developing new materials to be applied in extreme environments is an opportunity and a challenge for the future. High entropy alloys are new materials that seem promising approaches to work in nuclear fusion reactors. In this work, FeTaTiVW high entropy alloys were developed and characterized with Molecular Dynamic and Hybrid Molecular Dynamic Monte Carlo simulations. The simulation results show that phase separation originates a lower potential energy per atom and a high level of segregation compared to those of a uniform solid solution. Moreover, the experimental diffractogram of the milled powder shows the formation of a body-centred cubic-type structure and the presence of TiO2. In addition, the microstructure of the consolidated material evidenced three phases: W-rich, Ti-rich, and a phase with all the elements. This phase separation observed in the microstructure agrees with the Hybrid Molecular Dynamic Monte Carlo simulation. Moreover, the consolidated material’s thermal conductivity and specific heat are almost constant from 25 °C to 1000 °C, and linear expansion increases with increasing temperature. On the other hand, specific heat and thermal expansion values are in between CuCrZr and W values (materials chosen for the reactor walls). The FeTaTiVW high entropy alloy evidences a ductile behaviour at 1000 °C. Therefore, the promising thermal properties of this system can be attributed to the multiple phases and systems with different compositions of the same elements, which is exciting for future developments.

Martins, Ricardo (ORCID:0000000177685704)↗
DOE OSTI2025

Enhancing Streamflow Reanalysis Across the Conterminous US Leveraging Multiple Gridded Precipitation Data Sets

Streamflow observations, essential for various water resource applications, are often unavailable at critical locations in need. Although different models have been proposed to enhance streamflow predictability at ungauged locations, the challenge extends beyond model fidelity. Differences in meteorologic forcing data sets, precipitation in particular, can significantly affect the accuracy of hydrologic predictions. This challenge intensifies across regions characterized by diverse hydro-climatological and geographical conditions, such as in the conterminous US (CONUS) where a single precipitation product struggles to consistently replicate observed hydrographs, particularly peak flow dynamics. To enhance streamflow predictions, we utilize a VIC-RAPID hydrologic modeling framework driven by multiple commonly used meteorological forcing data sets, such as Daymet, PRISM, ST4, AORC, and their hybrids and create multiple sets of 40-year (1980–2019) hourly, daily, and monthly streamflow reanalysis, Dayflow Version 2, for 2.7 million river reaches across the CONUS. Most forcings lead to skillful streamflow performance, except for ST4 in the mountainous west, where severe radar blockage adversely affects the accuracy. The evaluation using over 6,000 hourly stream gauges shows that hourly AORC and ST4 lead to improved annual peak flow performance over Daymet—driven streamflow (Dayflow V1), particularly in smaller basins, highlighting the value of high temporal resolution forcings in hydrologic predictions. Compared with other benchmark data sets like National Water Model V3.0, AORC-driven VIC-RAPID exhibits improved regional streamflow performance, with comparable peak flow representation. We envision that multi-forcing streamflow reanalysis data can inform regions in need of forcing data enhancement, diagnose hydrologic model performance, and benefit diverse water resource applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

First Measurement of 𝐴 = 4 Hypernuclei and Antihypernuclei at the LHC

In this Letter, the first evidence of the $^4_{\bar{Λ}}$$\overline{He}$ antihypernucleus is presented, along with the first measurement at the LHC of the production of (anti)hypernuclei with mass number 𝐴 = 4, specifically (anti)⁢$^4_Λ$H and (anti)⁢$^4_Λ$He. In addition, the antiparticle-to-particle ratios for both hypernuclei ($^4_{\bar{Λ}}$$\bar{H}$⁡/$^4_Λ$H and $^4_{\bar{Λ}}$$\overline{He}$/$^4_Λ$He) are shown, which are sensitive to the baryochemical potential of the strongly interacting matter created in heavy-ion collisions. The results are obtained from a data sample of central Pb-Pb collisions, collected during the 2018 LHC data taking at a center-of-mass energy per nucleon pair of $\sqrt{𝑠_{NN}}$ = 5.02 TeV. The yields measured for the average of the charge-conjugated states are found to be [0.78 ± 0.19⁢(stat) ± 0.17⁢(syst)] × 10 −6 for the (anti)⁢$^4_Λ$H and [1.08 ± 0.34⁢(stat)± 0.20⁢(syst)] × 10 −6 for the (anti)⁢$^4_Λ$He, and the measured antiparticle-to-particle ratios are in agreement with unity. The presence of (anti)⁢$^4_Λ$H and (anti)⁢$^4_Λ$He excited states is expected to strongly enhance the production yield of these hypernuclei. The yield values exhibit a combined deviation of 3.3⁢𝜎 from the theoretical ground-state-only expectation, while the inclusion of the excited states in the calculations leads to an agreement within 0.6⁢𝜎 with the present measurements. Additionally, the measured (anti)$^4_Λ$H and (anti)⁢$^4_Λ$He masses are compatible with the world-average values within the uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Surface-based observations of cold-air outbreak clouds during the COMBLE field campaign

Abstract. Cold-air outbreaks (CAOs) are characterized by extreme air–sea energy exchanges and low-level convective clouds over large areas in the high-latitude oceans. As such, CAOs are an important component of the Earth's climate system. The CAOs in the Marine Boundary Layer Experiment (COMBLE) deployment of the US Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) provided the first comprehensive view of CAOs using a suite of ground-based observations at the northern coast of Norway. Here, cloud and precipitation observations from 13 CAO cases during COMBLE are analyzed. A vertical air motion retrieval technique is applied to the Ka-band ARM Zenith-pointing Radar (KAZR) observations. The CAO cumulus clouds are characterized by strong updrafts with magnitudes between 2–8 m s−1, vertical extents of 1–3 km, and horizontal scales of 0.25–3 km. A strong relationship between our vertical air velocity retrievals and liquid water path (LWP) measurements is found. The LWP measurements exceed 1 kg m−2 in strong updraft areas, and the vertical extent of the updraft correlates well with the LWP values. The CAO cumulus clouds exhibit eddy dissipation rate values between 10−3 and 10−2 m2 s−3 in the lowest 10 km of the atmosphere, and using a radar Doppler spectra technique, evidence of secondary ice production is found during one of the cases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Development of Ti 3 SiC 2 MAX phase tubular structures for solar receiver applications

Solar receiver tubes are key components of concentrating solar-thermal power (CSP) systems that harvest solar energy. For better efficiency, the Gen3 CSP receivers, which collect heat into a heat transfer fluid, require a temperature exceeding 700 °C during operation and need to perform under extreme conditions of high temperature and high thermal stress. Operators are seeking CSP designs using new high-temperature structural materials with high thermal conductivity and high creep resistance to achieve a design life of 30 years and thus help recover the plant capital cost sooner. MAX phase materials, which consist of an early transition metal element, an A-group element, and carbon or nitrogen, are expected to exhibit high creep resistance as well as high fracture toughness. Here, in this paper, we describe fabricating both (1) dense Ti 3 SiC 2 MAX phase disks and (2) short-length tubes using field-assisted sintering technology (FAST). First, the disk samples that we fabricated are fully dense and contain ≈90 % Ti 3 SiC 2 MAX phase materials and ≈10 % TiC phase materials. We determined a flexure strength of 519 ± 32 MPa by conducting a four-point bending test at room temperature with rectangular bar samples of ≈100 % density. The thermal conductivity of the Ti 3 SiC 2 MAX phase samples, measured by light flashing analysis, decreases linearly from a value of 41 W . m -1 . K -1 at room temperature to a value of 36 W . m -1 . K -1 at 650 °C. A solar reflectance measurement of the Ti 3 SiC 2 MAX phase revealed that, temperature increases from 400 to 1400 °C, thermal emittance increases from 0.39 to 0.49, while selectivity decreases from 1.8 to 1.4, respectively. Whereas the surface oxidized MAX phase samples after 100 h exposure to air at 1000 °C exhibit that of SiC. Next, we discuss fabrication of the crack-free Ti 3 SiC 2 MAX phase tubular structures accomplished by using FAST processing in graphite bedding. A Ti 3 SiC 2 MAX phase content of > 95 % with traceable ≈3% remaining TiC phase and ≈15 % porosity were demonstrated after high-temperature annealing. An average fracture strength of ≈250 MPa was determined with Ti 3 SiC 2 MAX phase tubes of ≈85 % density by diametral compression testing at room temperature. Our work demonstrated that using FAST processing to produce Ti 3 SiC 2 MAX phase tubular structures for CSP receiver applications is a viable approach.

14 SOLAR ENERGY↗
DOE OSTI2024

The effect of plasma shaping on high density H-mode SOL profiles and fluctuations in TCV

Abstract The impact of plasma shaping on the properties of high density H-mode scrape-off layer (SOL) profiles and transport at the outer midplane has been investigated on Tokamakà configuration variable. The experimental dataset has been acquired by evolving the upper triangularity while keeping the other parameters constant. The scan comprises δ u p values between 0.0 and 0.6, excluding negative triangularity scenarios. Within this study, a transition from type-I edge localised modes to the quasi-continuous exhaust regime takes place from low to high δ u p . The modification of the upstream SOL profiles has been assessed, in terms of separatrix quantities, within the α t turbulence control parameter theoretical framework (Eich et al 2020 Nucl. Fusion 60 056016). The target parallel heat load and the upstream near-SOL density profiles have been shown to broaden significantly for increasing α t . Correspondingly, in the far SOL a density shoulder formation is observed when moving from low to high δ u p . These behaviours have been correlated with an enhancement of the SOL fluctuation level, as registered by wall-mounted Langmuir probes as well as the thermal helium beam diagnostic. Specifically, both the background and the filamentary-induced fluctuating parts of the first wall ion saturation current signal are larger at higher δ u p , with filaments being ejected more frequently into the SOL. Comparison of two pulses at the extremes of the δ u p scan range, but with otherwise same input parameters, shows that the midplane neutral pressure does not change much during the H-mode phase of the discharge. This indicates that indirect effects of the change in geometry, linked to first wall recycling sources, should not play a significant role. The total core radiation increases at high δ u p , on account of a stronger plasma–wall interaction and resulting larger carbon impurity intake from the first wall. This is likely associated to the enhanced first wall fluctuations, as well as a smaller outer gap and the close-to-double-null magnetic topology at high shaping.

Stagni, A. (ORCID:0000000180841544)↗
DOE OSTI2021

Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operationson Spatial Accelerators

To meet the extreme compute demands for deep learning across commercial and scientific applications, dataflow accelerators are becoming increasingly popular. While these“domain-specific” accelerators are not fully programmable like CPUs and GPUs, they retain varying levels of flexibility with respect to data orchestration, i.e., dataflow and tiling optimizations to enhance efficiency. There are several challenges when designing new algorithms and mapping approaches to execute the algorithms for a target problem on new hardware. Previous works have addressed these challenges individually. To address this challenge as a whole, in this work, we present an HW-SW co-design ecosystem for spatial accelerators called Union within the popular MLIR compiler infrastructure. Our framework allows exploring different algorithms and their mappings on several accelerator cost models. Union also includes a plug-and-play library of accelerator cost models and mappers which can easily be extended. The algorithms and accelerator cost models are connected via a novel mapping abstraction that captures the map space of spatial accelerators which can be systematically pruned based on constraints from the hardware, workload, and mapper. We demonstrate the value of Union for the community with several case studies which examine offloading different tensor operations (CONV/GEMM/Tensor Contraction) on diverse accelerator architectures using different mapping schemes.

Jeong, Geonhwa↗
DOE OSTI2022

A combined theoretical-experimental investigation of thermal transport in low-dose irradiated thorium dioxide

During reactor operation, nuclear fuels are subject to extreme temperature and irradiation conditions which can significantly degrade the fuel's thermal transport properties. The reduction in thermal conductivity of the fuel as a result of irradiation-induced lattice defects is arguably the most important fuel performance metric in regard to reactor efficiency and safety. Because thorium dioxide (ThO2) is suitable as a model system for more complex materials such as UO2 and its mixed oxides, we present a theoretical investigation of thermal conductivity reduction seen in defect-bearing thorium dioxide and compare directly to experimental measurements. Phonon-mediated thermal transport of the fuel is modeled by a solution to the Boltzmann transport equation (BTE) for phonons. A cluster dynamics (CD) model for lattice defect evolution during irradiation predicts defect densities which are used as input to the BTE for modeling phonon-defect scatterings. Phonon scatterings by lattice defects include those from point defects and vacancy clusters and interstitial clusters of various sizes. The CD model is benchmarked against structural defect characterization of irradiated thorium dioxide using electron microscopy. Thermal conductivity predicted by the BTE model is compared to measured values for irradiated thorium dioxide specimens below room temperature to isolate effects of phonon-defect scattering from intrinsic 3-phonon processes, which dominate at higher temperatures. The computed conductivity values are in partial agreement at temperatures close to room temperature while slight deviations are observed at the lowest measured temperatures, suggesting that implemented phonon-defect scattering cross-section expressions may not be adequate for low temperatures. The presented work provides a necessary investigation of the influence of irradiation induced defects on fuel performance and represents a first step toward a full characterization of phonon mediated thermal transport in irradiated materials with complex defect microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Weak scale as a trigger

Does the value of the Higgs mass parameter affect the expectation value of local operators in the Standard Model? For essentially all local operators the answer to this question is "no", and this is one of the avatars of the hierarchy problem: nothing is "triggered" when the Higgs mass parameter crosses zero. In this letter, we explore settings in which Higgs mass parameters $can$ act as a "trigger" for some local operators ${\cal O}_T$. In the Standard Model, this happens for ${\cal O}_T = {\rm Tr} (G \tilde G)$. We also introduce a "type-0" two Higgs doublet model, with a $Z_4$ symmetry, for which ${\cal O}_T = H_1 H_2$ is triggered by the Higgs masses, demanding the existence of new Higgs states necessarily comparable to or lighter than the weak scale, with no wiggle room to decouple them whatsoever. Surprisingly, this model is not yet entirely excluded by collider searches, and will be incisively probed by the high-luminosity run of the LHC, as well as future Higgs factories. We also discuss a possibility for using this trigger to explain the origin of the weak scale, invoking a landscape of extremely light, weakly interacting scalars $\phi_i$, with a coupling to ${\cal O}_T$ needed to make it possible to find vacua with small enough cosmological constant. The weak scale trigger links the tuning of the Higgs mass to that of the cosmological constant, while coherent oscillations of the $\phi_i$ can constitute dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

An Extreme-precision Radial-velocity Pipeline: First Radial Velocities from EXPRES

The EXtreme-PREcision Spectrograph (EXPRES) is an environmentally stabilized, fiber-fed, R = 137,500, optical spectrograph. It was recently commissioned at the 4.3 m Lowell Discovery Telescope near Flagstaff, Arizona. The spectrograph was designed with a target radial-velocity (RV) precision of 30 cm s{sup −1}. In addition to instrumental innovations, the EXPRES pipeline, presented here, is the first on-sky, optical, fiber-fed spectrograph to employ many novel techniques—including an “extended flat” fiber used for wavelength-dependent quantum efficiency characterization of the CCD, a flat-relative optimal extraction algorithm, chromatic barycentric corrections, chromatic calibration offsets, and an ultra-precise laser frequency comb for wavelength calibration. We describe the reduction, calibration, and RV analysis pipeline used for EXPRES and present an example of our current sub-meter-per-second RV measurement precision, which reaches a formal, single-measurement error of 0.3 m s{sup −1} for an observation with a per-pixel signal-to-noise ratio of 250. These velocities yield an orbital solution on the known exoplanet host 51 Peg that matches literature values with a residual rms of 0.895 m s{sup −1}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Lithium-Ion Battery Diagnostics Using Electrochemical Impedance via Machine-Learning

Diagnosing battery states such as health, state-of-charge, or temperature is crucial for ensuring the safety and reliability of electrochemical energy storage systems. While some states, such as temperature, may be measured using cheap sensors, accurate diagnosis of battery health metrics usually requires time-consuming performance measurements, making them infeasible for use in real-world operation. These health metrics can be measured during lab-testing and then estimated on-line using predictive life models or via state observer algorithms such as Kalman filters, but these predictive methods should be supplemented by actual measurement of battery health whenever possible to ensure reliability. Rapid measurement of battery health may be done by various types of fast diagnostic techniques such as electrochemical impedance spectroscopy (EIS), which can be performed in only a few minutes and require only a fraction of the energy and power needed for a full charge and discharge measurement. But there is a substantial challenge for estimating battery health using EIS data, as EIS is sensitive to cell temperature, state-of-charge, current, and resting time in addition to health. Thus, utilizing EIS data to predict battery capacity requires correcting for all these additional variables, a task that is extremely difficult to handle analytically. This talk utilizes machine-learning methods to estimate the effectiveness of battery capacity prediction from EIS data, leveraging a data set of hundreds of EIS measurements recorded at varying temperature and state-of-charge throughout a 500-day aging study of 32 commercial, large-format NMC-Graphite lithium-ion batteries. Using EIS as input to machine-learning models is complicated by the nonlinear response of impedance to battery health, temperature, and state-of-charge, as well as the collinearity between the impedance response at neighboring frequencies, which can easily lead to overfit models. To train robust models, features from EIS data need to be extracted from the data or some subset of critical frequencies selected. Many approaches for extracting and selecting features from EIS data from electrochemical analysis and machine-learning fields were identified for analysis: using the entire raw spectra; selection of one, two, or many frequencies from the entire spectra; selecting interesting points from the EIS measurement using domain knowledge; fitting EIS with an equivalent-circuit model; calculating statistics on the raw impedance values; and reducing the dimensionality of the data using unsupervised linear (principal component analysis) and non-linear (uniform manifold approximation and projection) methods. These approaches were rigorously compared using a machine-learning pipeline approach, training linear, Gaussian process, and random forest regression models and quantifying performance using cross-validation as well as a held-out test set. An artificial neural network model trained on the raw spectra was also tested. Promising pipelines were fine-tuned via Bayesian hyperparameter optimization using cross-validation loss and training with class-specific weights to counter data set imbalance. The most reliable method for utilizing impedance in this work was the selection of two optimal frequencies through an exhaustive search, resulting in about 2% mean absolute error on test data for both Gaussian process and random forest model architectures. Interrogation of a variety of models reveals critical frequencies of 100 Hz and 103 Hz for this data set, though the optimal set of frequencies is not necessarily intuitive, i.e., the best performing models are not simply those that use impedance at frequencies that have the highest correlation to the relative discharge capacity. The best performing model is an ensemble model, which is able to predict battery capacity with 1.9% mean absolute error for unseen cells using impedance recorded at a variety of temperatures and states-of-charge.

battery↗
DOE OSTI2024

Effects of irradiation damage on the elastic properties and hardness of complex transition metal diborides

Multi-principal component transition metal (TM) diborides represent a class of high-entropy ceramics (HECs) that have received considerable interest in recent years owing to their promising properties for extreme environment applications that include thermal/ environmental barriers, hypersonic vehicles, turbine engines, and next-generation nuclear reactors. While the addition of chemical disorder through the random distribution of TM elements on the cation sublattice has offered opportunities to tailor elastic stiffness and hardness, the effects of irradiationinduced structural damage on the physical properties of these complex materials have remained largely unexplored. To this end, changes in the hardness and elastic moduli of a high-entropy TM diboride (Hf0.2Nb0.2Ta0.2Ti0.2Zr0.2)B2 and three of its quaternary subsets following irradiation with 10 MeV gold (Au) ions to fluences of up to 6 × 10^15 Au cm-2 are investigated at the micrometer and sub-micrometer length-scales via the dispersion of laser-generated surface acoustic waves (SAW) and nanoindentation, respectively. The nanoindentation measurements show that the TM diborides exhibit an initial increase in hardness following irradiation with energetic Au ions, with a subsequent decrease in hardness following further irradiation. One quaternary composition, (Hf1/3Ta1/3Ti1/3)B2, exhibits a notable exception to the trend and continues to exhibit an increase in hardness with ion irradiation fluence. Although differences in the absolute values of the effective elastic moduli obtained from the measured SAW dispersion and nanoindentation are observed (and attributed to microstructural variations at the measurement length-scale), both techniques yield similar trends in the form of an initial reduction and subsequent saturation in the elastic modulus with increasing ion irradiation fluence. The quaternary TM diboride (Hf1/3Ta1/3Ti1/3)B2 again exhibits a departure from this trend. The high-entropy TM diboride (Hf0.2Nb0.2Ta0.2Ti0.2Zr0.2)B2 exhibits the greatest recovery in hardness and modulus when irradiated to high ion fluences following initial changes at low fluence, indicating superior resistance to radiation-induced damage over its quaternary counterparts. Opportunities for designing HECs with superior hardness and modulus for enhanced radiation resistance (compared to their single constituent counterparts) by tailoring chemical disorder and bond character in the lattice are discussed.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Healable Coatings as a Mechanism to Repair Leading Edge Erosion in Wind Energy

Wind turbine blades are highly engineered structures designed to face temperature extremes and high winds. However, erosion of the blade's leading edge and subsequent repair remains a significant and costly challenge for the wind energy industry. Repair of these leading edges can lead to large amounts of downtime for the turbine and significant operational inefficiencies. In this work, the strength of adhesion and healing ability of a commercially available vitrimer (Mallinda's VITRIMAX) was compared to that of a thermoplastic resin, which has previously been demonstrated in wind energy applications (Arkema's Elium) to evaluate their efficacy as surface coatings for wind turbine blades, particularly their leading edges. Vitrimers are a class of inherently reprocessable thermosets, and it was theorized that vitrimer-based leading edge coatings could enable more robust and efficient wind turbine blades with decreased operational downtime and safer maintenance practices. It was found that the VITRIMAX adhered better to the wind blades' surfaces than both the manufacturer's paint and Elium, with increases in pull-off strength of adhesion ranging from 24% to 83% above that of the original paint. Furthermore, the VITRIMAX adhered strongly to the underlying composite of each blade with strength of adhesion values increasing in ranges from 42% to 97% above that of the original paint. Finally, the vitrimer coating showed an 88% decrease in surface roughness compared to end-of-life blade materials, and initial healing demonstrations in which coatings were manually scratched and subsequently healed exhibited an ~84.5% decrease in scratch depths.

Hubbard, Amber [ORNL]↗
DOE OSTI2021

Twisted bilayer graphene. I. Matrix elements, approximations, perturbation theory, and a k · p two-band model

We investigate the twisted bilayer graphene (TBG) model of Bistritzer and MacDonald (BM) [Bistritzer and MacDonald, Proc. Natl. Acad. Sci. 108, 12233 (2011)] to obtain an analytic understanding of its energetics and wave functions needed for many-body calculations. We provide an approximation scheme for the wave functions of the BM model, which first elucidates why the BM K M -point centered original calculation containing only four plane waves provides a good analytical value for the first magic angle (θ M ≈ 1°). The approximation scheme also elucidates why most of the many-body matrix elements in the Coulomb Hamiltonian projected to the active bands can be neglected. By applying our approximation scheme at the first magic angle to a Γ M -point centered model of six plane waves, we analytically understand the reason for the small Γ M -point gap between the active and passive bands in the isotropic limit w 0 = w 1 . Furthermore, we analytically calculate the group velocities of the passive bands in the isotropic limit, and show that they are almost doubly degenerate, even away from the Γ M point, where no symmetry forces them to be. Furthermore, moving away from the Γ M and K M points, we provide an explicit analytical perturbative understanding as to why the TBG bands are flat at the first magic angle, despite the first magic angle is defined by only requiring a vanishing K M -point Dirac velocity. We derive analytically a connected “magic manifold” w 1 = $2\sqrt{1 + w^{2}_{0}}$ $-\sqrt{2 + 3w^2_0}$, on which the bands remain extremely flat as w 0 is tuned between the isotropic (w 0 = w 1 ) and chiral (w 0 = 0) limits. We analytically show why going away from the isotropic limit by making w 0 less (but not larger) than w 1 increases the Γ M -point gap between the active and the passive bands. Finally, by perturbation theory, we provide an analytic Γ M point k ∙ p two-band model that reproduces the TBG band structure and eigenstates within a certain w 0 , w 1 parameter range. Further refinement of this model are discussed, which suggest a possible faithful representation of the TBG bands by a two-band Γ M point k ∙ p model in the full w 0 , w 1 parameter range.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Wave-packet manipulation of He Rydberg states by a seeded free-electron laser

We report a two-dimensional pump-control-probe spectroscopic study of the dynamics of singly excited He Rydberg-state wave packets with a seeded extreme ultraviolet (XUV) free-electron laser (FEL) source. A pair of coherent XUV pulses, defined by their coarse time separation and relative phase, created and manipulated the wave packets. The He atoms were postionized by infrared (IR) pulses, and the ion yield was measured as a function of XUV phase and IR arrival time. We tagged and sorted the relative phase of the XUV pulse pair on a single-shot basis by fitting each FEL spectrum with a suitable function that accounts for nonidealities of the XUV pulse pairs, associated with the seeding process; more generally, the fit returns the time-dependent electric field of the FEL spectra. The experimental two-dimensional maps of ion yields, measured as a function of IR (probe) delay and of XUV (pump-control) phase, were compared with the solution of the first-order time-dependent Schrödinger equation for this field. Despite the fact that the experimental conditions imply strong excitation, beyond the approximations of first-order perturbation theory, the simulated map satisfactorily reproduces the experimental one for temporally well-separated pulses. We show that by selecting data at appropriate values of pump-control phase, we enhance or suppress the amplitude of chosen wave-packet components consisting of two or more Rydberg states. When the temporal overlap of the pulse pair cannot be neglected, the phase reconstruction is underdetermined, and we provide a simplified comparison between data and simulations. Published by the American Physical Society 2024

Dumergue, Mathieu (ORCID:0000000236984406)↗
DOE OSTI2023

Laboratory-Scale Coal-Derived Graphene Process (Final Report)

The Energy & Environmental Research Center (EERC) conducted a laboratory-scale coal-derived graphene (CDG) project focused on developing a technological process for making graphene from four U.S. domestic coal or coal wastes, including lignite from North Dakota, subbituminous coal from Wyoming, bituminous coal from Utah, and anthracite from Pennsylvania. The project was divided into two performance or budget periods (BPs), with BP1 comprising the up-front laboratory experiments to make graphene materials from coal beginning on May 1, 2020, to April 30, 2022. BP2 was conducted from May 1, 2022, to April 30, 2023, and was focused on analyzing the CDG process economic feasibility and the technical gaps for technological scale-up and commercialization. During this project, a few different coal-derived high-value products have been demonstrated, including graphite, graphene oxide (GO), reduced graphene oxide (rGO), and graphene quantum dots (GQDs). A new graphite microstructure was discovered and named “croissant graphite” because of the exterior morphological and textural resemblance to croissant food items sold in commercial groceries stores. The new graphite structure and the associated preparation from coal or coal waste feedstocks has been the subject of a U.S. patent application. The systematic experimental processes involving coal cleaning, upgrading, and conversion to high-value carbon products culminated into a developed upgraded coal-to-products (UCP) technology that is being pursued for potential fast-track commercialization, if funding is available. It is envisioned that commercialization of the UCP technology would increase consumption of U.S. domestic coals or coal wastes to make environmentally sustainable high-value products for the electronics industry, high-energy-storage applications, and clean energy technologies such as electric vehicle (EV) lithium-ion batteries (LIBs), for which graphite has become a critical mineral commodity. Croissant graphite microstructures, when observed by field emission scanning electron microscopy (FESEM), display wavy surface morphology and often grow from a base that is made of graphitized particles with honeycomb-like layers, which are believed to be graphene layers. While more studies are needed to fully ascertain the mechanisms of the croissant graphite microstructure formation, it is postulated that their growth may begin from curling of the graphene sheets into ribbon-like structures, and continuous growth and densification of the ribbon-like structures forms croissant microstructures. Additional studies are ongoing to evaluate the electrochemical performance of croissant graphite for LIB applications and to determine the experimental conditions necessary to tune on/off croissant formation so that it can be either optimized or suppressed depending on performance evaluation results. In addition to the discovery of croissant graphite, the graphitization process from the four coal ranks in general was successful. X-ray diffraction (XRD) analysis showed that the degree of graphitization (DoG) ranged from 12% to 80% in an early sample set, and further optimization on lignite coal produces a DoG of about 92%, which was spectacular to see as lignite is the lowest-rank coal. Thus, it is expected that the graphitization performance for higher-rank coals will be similar or better when optimized as well. The coal-derived graphite was used to make GO and rGO. Analytical characterization, e.g., by methods such as Raman spectroscopy, XRD, Fourier transform infrared (FTIR) spectroscopy and FESEM, showed that the sequence of converting the coal to graphite, exfoliating it to GO, and then chemically reducing the GO to rGO was successful. Although coal naturally contains aromatic compounds and some relatively small-sized condensed aromatic units, it does not contain graphene sheets. In the UCP process, the aromatic domains in the coals, particularly low-rank coals, are concentrated and condensed further into graphene sheets, which are ordered into a 3D stack during graphitization. The synthesized graphite is then unpacked by methods such as exfoliation to various graphene products. GQDs were synthesized from all four coal types, and their optical properties were demonstrated to be tunable by the coal precursor preprocessing treatments. In all four coal types, enhanced optical properties were observed for the produced GDQs with incremental improvements made to the coal precursors. GQDs produced from raw coal samples displayed lower ultraviolet–visible (UV–Vis) spectroscopy absorbance intensity compared to those obtained from cleaned and upgraded coal residues. The photoluminescence (PL) intensities also varied with pretreatment conditions and with the concentration of GQDs in aqueous solutions. GQDs obtained from anthracite show longer emission wavelengths and can be excited by visible light as opposed to GQDs derived from the other coal ranks. UV fluorescence 3D maps and spectra revealed that the emission wavelength at which the GQDs solutions display the highest intensity was slightly redshifted based on the coal precursor pretreatments. In low-rank coal (lignite and subbituminous) samples, two clusters were observed in the maps for GQDs, which may suggest that there are potentially two types of fluorophores in solution or two main size populations. The ability to tune the properties of GQDs based on processing methods can be exploited to make GQDs for various optical display or optoelectronics applications. The results also highlight the importance of removing coal-borne impurities to improve the quality of the coal precursor for preparation of graphene products. Coal and/or coal wastes preprocessing methods were developed and applied to clean and upgrade the coal precursors prior to graphitization and subsequent conversion to graphene products. The preprocessing methods involve high specific-gravity separations, mineral acid cleaning (no hydrofluoric acid), and subsequent upgrading by reducing the coal-borne heteroatom (nitrogen, sulfur, and oxygen) content using proprietary chemical agents. Analytical characterization revealed that the preprocessing steps were successful, with ash reductions that range from 38% to 80% and residual ash content that was below the 5 wt% initial target. Based on proximate and ultimate analysis, the heteroatom reduction reactions produced upgraded coal residues with the oxygen content reduced by 8% to 24%, with additional reductions in the nitrogen and sulfur contents. An initial assessment of the waste streams from the UCP process shows very small to negligible environmental impact due to CO 2 , NO x , and SO x because most process steps are performed under inert atmosphere with argon. Consequently, reactive oxygen environments that tend to create these species are avoided. The inorganic and potentially hazardous species are released into aqueous waste streams that are easy to handle for proper disposal. The liquid waste streams were found to contain low-level concentrations of rare-earth elements (REEs), which could be concentrated and recovered as value-added by-products. Additionally, the volatile and gaseous fractions from carbonization and heat treatment contain useful organic compounds that can also be recovered as potential valuable by-products. Thus, the UCP technology is considered an environmentally sustainable and promising emerging technology for making high-value products from coal and coal wastes, with potential additional value-added by-products. Analysis of potential markets for the coal-derived carbon products shows a strong demand in both niche market sectors and across a wide variety of other industrial sectors. Graphite is currently considered a critical mineral commodity that has a large and growing demand in the LIB industry for EV applications. Based on data from Fortune Business Insights (2022) and Marketwatch (2023) reports, the average global graphite market is projected to reach about 33 billion by 2028, growing at a compound annual growth rate (CAGR) of about 7%, with much of this growth expected to be in the LIB industry. GO and rGO have strong market potentials in various application areas, such as coatings for anticorrosion, anti-icing, and antimicrobial protection, thermal barriers, wear resistance, sensors, additive manufacturing such as 3D inks, and others. GQDs are the emerging key player in the bioimaging, photovoltaics, and light-emitting diodes (LEDs) applications, with the potential to replace traditional semiconductor quantum dots (SQDs), which are based on metallic systems that are more toxic and more expensive. Biomedical applications of GQDs are becoming more attractive because of low to no toxicity and extremely low cost compared to SQDs. The major challenges for scale-up and commercialization of coal-derived carbon products such as graphene vary from the inherent attributes of graphene itself to reluctance to accept graphene in new manufacturing processes because of the uncertainty of the unknown. The 2D nature of graphene materials with a thickness of one atom presents significant challenges to proper handling/processing, and process scale-up becomes difficult because it requires high-end, expensive equipment, even for routine handling and analysis for quality assurance and control. Pristine graphene can also be extremely difficult to work into other matrices, thus hindering downstream processibility, especially at large scale. Currently, the cost of graphene and graphene products is still high and presents an economic risk that tends to slow down investment in scaling up emerging technologies. The lack of a standard for graphene materials for quality assurance and quality control poses a great challenge not only for the markets but also for commercialization efforts. A first-look economic feasibility analysis of the UCP technology provided valuable information that suggests the UCP process would be feasible, especially when it is scaled to a pilot scale and could be more competitive at the full scale. Graphitization was found to be the most energy-consuming and most capital-intensive step in the overall process. In small laboratory- and bench-scale experiments, labor is a significant contributor to the total process costs. Although these energy, capital, and labor constraints contribute to a higher selling price for the product, a preliminary economic model suggests that the process would be feasible at large scale when the process is fully integrated, optimized, and automated.

01 COAL, LIGNITE, AND PEAT↗