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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Characterization of polymer networks presents unique challenges due to the insolubility of the materials, but this also enables characterization by new techniques that take advantage of the bulk network structure.
Measurements on samples of calcined uranyl fluoride (UO 2 F 2 ) using Raman spectroscopy, electron microscopy with elemental analysis, and secondary ion mass spectrometry (SIMS) indicate four facts. First, UO 2 F 2 undergoes a previously unreported oxidation reaction beginning around 350 °C in air. The resulting oxidation compound is likely similar to U 3 O 8 /UO 3 , but presently represents a novel chemical species. Second, variations in F/U ratio across samples as measured by electron microscopy with x-ray spectroscopy correlate with variations in F/U ratio as measured with the NanoSIMS 50L instrument. Third, simple mixed powders of LaF 3 +U 3 O 8 are not sufficiently homogeneous to act as a high F+U content standard material. Fourth, additional method development for determining the bulk F/U ratio using an alternative technique is necessary to further develop analytical standards.
Fine powders of (Hf1-xZrx)B2 solid solution were synthesized by two methods. In the first one, solution-based processing of HfCl4, ZrCl4, sucrose and H3BO3 was carried out followed by heat treatment (e.g., at 1500 °C for 1 h) in Argon to achieve the carbothermal reduction (CTR) reaction to form the boride solid solution. In the second one, called boron hydride reduction (BHR) method, HfCl4, ZrCl4 and NaBH4 were directly mixed in a glove box followed by heat treatment in Argon at elevated temperatures from 700 to 1500 °C. In addition, the powders synthesized via both methods were flash sintered without sample preheating in a homemade setup. The synthesized powders as well as the flash sintered bulk ceramics were characterized using different techniques including XRD, SEM, EDS, TEM, TGA-DSC, and Vickers hardness test to reveal the inter-relationships between starting materials composition, processing conditions, and the resulting materials microstructure and physical/chemical properties.
This document reports on the considerations and development of an initial computational model based on the first principles for predicting acoustic propagation in a wellbore based on a logging-while-drilling (LWD) tool. This tool could be used to create a large database of simulated signals mimicking gas-influx-while-drilling events (so-called “kicks”). While other logging techniques, such as electrical resistivity and bulk density, are available in LWD tools, the acoustic logging method was identified in a complementary experimental endeavor as the most appropriate for early kick detection due to its high sensitivity to the presence of gas in liquids.
This paper describes the measurement of convective heat transfer coefficients and friction factors for sCO2 flowing in pin-fin patterned pipes in the Heat Exchange and Experimental Testing (HEET) facility at the US DoE’s National Energy Technology Laboratory (NETL) in Morgantown, WV. The measurement procedures in the HEET rig were validated by conducting benchmark tests with smooth stainless-steel tube and comparing the results with published correlations for Nusselt number (Nu) and friction factor. Over typical Reynolds number range in sCO2, the measured Nu and friction factors were within 7% of classical correlations for smooth tube flow.The candidate pin fin patterned pipes were additively manufactured (AM) at the Oak Ridge National Laboratory. The pins were circular or elliptical in cross-section. Pin length to diameter aspect ratios were 1.33 and 2, while the pin diameter to tube diameter ratio was 0.188 and 0.125. Tests were performed for ReD varying from 6.9×104 to 2.2×105 and at conditions equivalent to the low pressure outlet (8.69 MPa, 361 K) of the low temperature recuperator (LTR) in an indirect sCO2 power cycle. The Wilson plot technique was utilized to measure the bulk heat transfer coefficients.For the better performing design (tube A, pin length to tube diameter ratio: 1.33, pin diameter to tube diameter ratio: 0.188), the local heat transfer coefficient increased by 112% relative to the Dittus-Boelter correlation at the LTR low pressure outlet. This corresponded to a 282% increase in the product of the heat transfer coefficient and the surface area. Large pressure drops across the test articles were observed.
We present a laboratory experiment, developed around a pair of instrumental analysis techniques, Raman spectroscopy and ambient ionization mass spectrometry (MS), conducted by senior chemistry undergraduate students for bulk analysis of over-the-counter drugs using benchtop versions of the two instruments, as well as trace analysis of illicit drugs utilizing the corresponding portable instruments. The identification and confirmation of seized drugs is a routine operation in forensic laboratories that can be simplified using these two instrumental techniques in tandem. Bulk samples are readily analyzed using conventional Raman spectroscopy followed by paper cone spray ionization (PCSI) MS, while trace analysis is allowed by a simple single-substrate dual-analyzer method using surface enhanced Raman spectroscopy (SERS) from paper followed by paper spray ionization (PSI) MS. The introduction of these novel strategies to the students exposed them to potential career paths in forensic science by means of a hands-on experience that provided fundamental knowledge about this set of analytical methods, including intercomparisons of their performance, as well as practical issues like costs, regulations and databases. The use of portable instrumentation represents an additional learning experience for the students, considering that it is cutting-edge technology that is just now being transferred from academic to industrial labs and that it allows a valuable discussion of the advantages and disadvantages of bringing the laboratory to the field.
In this work, we present a data-driven technique for measuring the time-of-flight through material sealed within a container. Time-of-flight measurement provides a noninvasive means of quantifying the sound speed profile within a material by transmitting an acoustic burst and then measuring the time required for the burst to arrive at an opposing receiver. In a hermetically-sealed cylindrical container, a portion of the acoustic energy propagates through the material as a bulk wave, while the remainder of the acoustic energy propagates around the container walls as guided waves. As a result, interference from the guided waves obscures the bulk arrival, inhibiting measurement of the sound speed. The technique uses a Convolutional Neural Network (CNN) to identify critical features in the measured waveforms and identify bulk wave arrivals. We demonstrate this time-of-flight measurement technique on high explosive-filled containers as they are heated from room temperature to detonation. This is a particularly challenging application for acoustic time-of-flight measurements as the high explosives have significant sound speed gradients as they undergo heating, and they lead to significant attenuation of the bulk wave, as opposed to the guided waves, which do not suffer significant attenuation. We characterize the performance of the CNN as a function of the high explosive temperature and as a function of the CNN hyperparameters. We then provide physical insight into the error trends.
We detail scientific and engineering advances which enable the controlled spalling and layer transfer of single crystal 4H silicon carbide (4H-SiC) from bulk substrates. 4HSiC’s properties, including high thermal conductivity and a wide bandgap, make it an ideal semiconductor for power electronics. Moreover, 4H-SiC is an excellent host of solid-state atomic defect qubits for quantum computing and quantum networking. Because 4H-SiC substrates are expensive (due to long growth times and limited yield), techniques for removal and transfer of bulk-quality films are desirable for substrate reuse and integration of the separated films. In this work, we utilize updated approaches for stressor layer thickness control and spalling crack initiation to demonstrate controlled spalling of 4H-SiC, the highest fracture toughness crystal spalled to date. We achieve coherent spin control of neutral divacancy (VV 0 ) qubit ensembles and measure a quasi-bulk spin T 2 of 79.7 μs in the spalled films.
Abstract In concentrated solar power (CSP) applications, fluidized bed is a promising approach for high heat transfer coefficient (HTC) solar receivers and heat exchangers. However, the complexity of multiphase mixing has made it difficult to characterize and analyze the heat transfer mechanism. This paper presents an experimental study on simultaneously characterizing heat transfer in both the near-wall and the bulk regions of a fluidized bed using modulated photothermal radiometry (MPR). The MPR is a non-contact frequency-domain technique using an intensity-modulated laser as the heat source and surface infrared emission as thermometry. The thermal penetration depth of the laser heating is varied by controlling its modulation frequency, and thus the measurement can resolve the near-wall and the bulk thermal resistances. With the MPR technique, we measured fluidized silica sands with a mean size of 164 μm in a vertical channel of 6 mm depth. Our results show that the near-wall thermal resistance is substantially increased with increasing gas velocity, which partially offsets the benefit of higher HTC brought by stronger particle mixing during the fluidization. We also used the MPR to quantify the improvement in particle-wall heat transfer in an inclined channel. We found that an 8° inclination towards the heat exchanging side led to a lower near-wall thermal resistance and a higher HTC at high gas velocities. This work demonstrates that the MPR technique is a useful tool to quantify the important near-wall thermal resistance from a bulk particle bed, which not only advances our understanding of heat transfer in fluidized beds, but may also contribute to the design of fluidized bed heat exchangers with higher HTC.
Herein, a novel solid-phase gradient alloying technique was developed for a high throughput composition-microstructure-mechanical property assessment. Friction extrusion of a two-piece billet setup facilitated the formation of a seamless compositionally graded aluminum (Al)-silicon (Si) extrudate rod, with Si concentration in Al matrix gradually increasing from ~1 at% at one end to ~7 at% at the other end of the rod. We observed a strong dependence of the Al grain size, morphology, and texture on the Si concentration. The Si particles pinned the recrystallized grain boundaries resulting in refined (< 10 µm) and textured grains in the high Si content region, while the Al grains in the low Si region are equiaxed, randomly textured, and with a larger average size (~50 µm). The hardness of Al-Si gradient extrudate increases by ~50% percent with a 6 at% increase in Si content due to Hall Petch and particle strengthening effects. Our approach demonstrates the use of a solid phase processing technique to successfully produce a defect-free continuously compositionally graded bulk components thus overcoming the limitations of porosity and material heterogeneities commonly observed in other techniques such as by additive laser deposition.
This Tutorial provides an overview of the techniques that are most commonly utilized to grow bulk van der Waals crystals. The materials discussed were selected to highlight various challenges that are often encountered during crystal growth. Additionally, in relatively equal parts, the text covers melt-based techniques, vapor transport growths, and the characterization of crystal quality with an emphasis on structural and chemical homogeneities. Furthermore, pertinent details are given regarding the growth and characterization of many specific compounds, with examples mostly drawn from our own research, and an effort is made to highlight cases where the growths offer a particular lesson or the conditions have a significant impact on the crystal’s physical properties. A primary goal is to motivate more researchers to grow crystals by providing general descriptions and considerations for different growth techniques and equipment while sharing some of our own lessons learned and best practices for the growth and characterization of layered van der Waals crystals. The Tutorial is not written solely for aspiring crystal growers, however, because any researcher who collaborates with a crystal grower can benefit from having a greater understanding and appreciation of the processes of crystal growth and materials development.
HfO 2 , a simple binary oxide, exhibits ultra-scalable ferroelectricity integrable into silicon technology. This material has a polymorphic nature, with the polar orthorhombic (Pbc2 1 ) form in ultrathin films regarded as the plausible cause of ferroelectricity but thought not to be attainable in bulk crystals. In this work, using a state-of-the-art laser-diode-heated floating zone technique, we report the Pbc2 1 phase and ferroelectricity in bulk single-crystalline HfO 2 :Y as well as the presence of the antipolar Pbca phase at different Y concentrations. Neutron diffraction and atomic imaging demonstrate (anti)polar crystallographic signatures and abundant 90°/180° ferroelectric domains in addition to switchable polarization with negligible wake-up effects. Density-functional-theory calculations indicate that the yttrium doping and rapid cooling are the key factors for stabilization of the desired phase in bulk. Our observations provide insights into the polymorphic nature and phase control of HfO 2 , remove the upper size limit for ferroelectricity and suggest directions towards next-generation ferroelectric devices.
This study presents the application of X-ray diffraction computed tomography for the first time to analyze the crystal dimensions of LiNi 0.33 Mn 0.33 Co 0.33 O 2 electrodes cycled to 4.2 and 4.7 V in full cells with graphite as negative electrodes at 1 μm spatial resolution to determine the change in unit cell dimensions as a result of electrochemical cycling. The nature of the technique permits the spatial localization of the diffraction information in 3D and mapping of heterogeneities from the electrode to the particle level. An overall decrease of 0.4% and 0.6% was observed for the unit cell volume after 100 cycles for the electrodes cycled to 4.2 and 4.7 V. Additionally, focused ion beam-scanning electron microscope cross-sections indicate extensive particle cracking as a function of upper cut-off voltage, further confirming that severe cycling stresses exacerbate degradation. Finally, the technique facilitates the detection of parts of the electrode that have inhomogeneous lattice parameters that deviate from the bulk of the sample, further highlighting the effectiveness of the technique as a diagnostic tool, bridging the gap between crystal structure and electrochemical performance.
Complex concentrated alloys (CCAs) are a system of alloys composition of nearly equiatomic elements, creating a state of high configurational entropy in the material. These alloys are of interest for various industrial applications due to their high strength and hardness, wide operational temperature range, creep and diffusion resistance, and radiation resistance. In the current work CoCrFeNi-base CCAs are synthesize by combining three commonly industrial alloys: IN718, SS316L, and 70Co30Cr (commercially known as Stellite 21), in-situ utilizing directed energy deposition (DED) additive manufacturing (AM). One bulk specimen is fabricated with a 1:1:1 ratio of IN718, SS316L, and 70Co30Cr where IN718 is a source of nickel and chrome, SS316 is a source of iron and chrome, and 70Co30Cr is a source of cobalt and supplemental chrome. Additionally, a functionally graded material (FGM) of the identified CCA system from SS316 was fabricated with 10 layers, where the initial five layers are the base material of SS316L and graded by steps of 20% to transition to the CCA system. Overall build quality, microstructure, compositional distribution, phases analysis, and microhardness were studied by laser optical microscopy, scanning election microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction analysis (XRD), and Vickers microhardness techniques. Overall build quality showed a successful bulk build with acceptable density, however unmelted particles are observed in the as-built alloy. Compositional results show that the system meets the Boltzmann’s hypothesis definition of an HEA, and that an FCC CCA was produced with increased hardness, small grain size, and superior hardness properties to the SS316L substrate. While initial XRD results show predominately FCC structure, EDS analysis of interdendritic regions show the existence of Laves phases in the material. The fabrication of an FGM CCA allowed for potential screening of additional alloy mixes which may be of interest to explore in future research, and the resulting composition is compared to predicted values. This novel method of CCA fabrication results in substantial cost savings of these CCA systems over traditional methods.
Heavy-fermion metals are prototype systems for observing emergent quantum phases driven by electronic interactions. A long-standing aspiration is the dimensional reduction of these materials to exert control over their quantum phases, which remains a significant challenge because traditional intermetallic heavy-fermion compounds have three-dimensional atomic and electronic structures. Here we report comprehensive thermodynamic and spectroscopic evidence of an antiferromagnetically ordered heavy-fermion ground state in CeSiI, an intermetallic comprising two-dimensional (2D) metallic sheets held together by weak interlayer van der Waals (vdW) interactions. Owing to its vdW nature, CeSiI has a quasi-2D electronic structure, and we can control its physical dimension through exfoliation. The emergence of coherent hybridization of f and conduction electrons at low temperature is supported by the temperature evolution of angle-resolved photoemission and scanning tunnelling spectra near the Fermi level and by heat capacity measurements. Electrical transport measurements on few-layer fakes reveal heavy-fermion behaviour and magnetic order down to the ultra-thin regime. Importantly, our work establishes CeSiI and related materials as a unique platform for studying dimensionally confined heavy fermions in bulk crystals and employing 2D device fabrication techniques and vdW heterostructures to manipulate the interplay between Kondo screening, magnetic order and proximity effects.
Sm2Fe17C3 phase (2:17) is metastable and exhibits excellent intrinsic hard magnetic properties. Doping elements such as Ga facilitate the formation of a single-phase 2:17 structure in arc-melted Sm2Fe17Cx alloys, which opens a promising route for fabricating fully dense bulk Sm2Fe17Cx magnets via high-temperature techniques such as melting and sintering. First-principles electronic structure calculation indicates that Ga prefers to partially replace Fe at the 9d and 18h crystallographic sites in Sm2Fe17C3 and Sm2Fe17, respectively. This difference in site preference is attributed to the distinct chemical environments surrounding the Fe atoms in the two compounds. Ga substitution favors the Sm–Ga bonding formation while avoiding Ga–C interactions. Doped Ga atoms result in more negative formation energy in Sm2(Fe, Ga)17C3, indicating improved structural stability. Crystal Orbital Hamilton Population analysis reveals that carbon insertion weakens the bonding of Sm-Fe (18h) and Sm-Fe (18f) in Sm2Fe17C3. Ga doping facilitates electron redistribution across chemical bonds, thereby reinforcing Fe(18h)–Sm and Fe(18f)–Sm interactions and stabilizing the carbon-centered octahedral local structure. This synergistic effect contributes significantly to the observed enhancement in phase stability of Sm2(Fe, Ga)17Cx. These findings suggest that chemical bond engineering through the selective doping of Ga can enhance phase stability and facilitate the synthesis of Sm2Fe17C3, providing a viable strategy for developing advanced magnets.
Motivated by recent reports of ambient-pressure superconductivity in La 3 Ni 2 O 7 films grown on LaSrAlO 4 , we investigate the superconducting instability in a one-unit-cell (1UC) thin film using ab initio and random-phase approximation techniques. Compared to the high-pressure bulk system, the ratio of interlayer 𝑑 3𝑧 2 −𝑟 2 hopping to intralayer 𝑑 𝑥 2 −𝑦 2 hopping is suppressed in the 1UC thin film, and the crystal-field splitting of the 𝑒 𝑔 orbitals is increased. Here, our calculation indicates that spin-fluctuation-driven pairing correlations are weak for the stoichiometric case at ambient pressure, but increase significantly under hole doping. The leading pairing symmetry is also found to change by hole doping. Specifically, we obtain a leading 𝑑 𝑥 2 −𝑦 2 pairing state at moderate hole doping, followed by a 𝑑 𝑥𝑦 state at higher doping. These states are driven by intraband spin-fluctuation scattering within the 𝛾 hole pocket centered around the 𝑀 point, and arise primarily from states in the Ni layer farther from the substrate. These results strongly suggest that the thin-film superconducting samples are hole-doped and that pairing in this system predominantly arises in the layer, as opposed to the interlayer pairing in the pressurized bulk system.
Microorganisms colonizing natural habits such as soils co-evolve to form specific spatial patterns through interspecies interactions. These self-organized patterns are a key ecological phenotype, which provides critical information on their interaction mechanisms. However, conventional network inference techniques that analyze species population data in bulk have yet to be extended to account for such spatial heterogeneity. Here we proposed supervised deep learning as a new network inference tool for predicting interspecies interactions from spatiotemporal patterns of microbial evolution. Due to lack of biological imaging data that can be used for training deep learning networks, we used in silico data generated from high-fidelity agent-based models to determine model structure and parameters. Even though networks were trained under simple configurations where interaction coefficients are assumed to be spatially invariant, we demonstrated that the resulting model can be utilized to successfully predict spatial variation of interactions in more complex domains (i.e., configured with a context-dependent mixture of interaction coefficients) as well as in simple domains without further training. In the further test against real biological data obtained through imaging experiments of a binary consortium (Pseudomonas fluorescens and a mutant of Escherichia coli), our model also predicted the dramatic shifts in interactions of the two organisms across different environmental contexts. Through various successful demonstrations in this work, the combined use of the agent-based model and machine learning algorithm provides a means to use new type of data - microscopic images - for extracting microbial interactions, therefore presenting itself as a useful tool for the analysis of more complex microbial community interactions.