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At least 793 records · Page 44

A comprehensive numerical investigation on spray models for Direct-Injection Spark-Ignition engines

Gasoline direct-injection spark-ignition (DISI) engines generate a large portion of their unburned hydrocarbon (UHC) and soot emissions during the cold-start phase. A predictive computational fluid dynamics (CFD) modeling framework can be used to understand the physical processes that characterize fuel spray evolution and fuel-film formation at cold start conditions, which can help to reduce engine-out particulate emissions. This study systematically evaluated spray submodels and developed a set of simulation best practices for physical-numerical submodels with the goal of enabling accurate simulations of liquid spray behavior in a DISI engine. Three comprehensive experimental datasets containing free-spray projected liquid volume (PLV), liquid volume fraction (LVF), and near-field X-ray radiography data were used to validate the simulation results and evaluate the spray submodels. Systematic analysis delved into injected parcel distribution, droplet collision, spray breakup, and evaporation via a detailed assessment of the relevant spray submodels. Moreover, the effects of turbulence models and the initial turbulent flow properties on the liquid spray evolution were examined. Based on extensive calibration efforts, a set of simulation best practices for the free spray was developed and validated against the PLV/LVF data. Simulation results indicated that the uniform distribution for parcel initialization, coupled with appropriate droplet collision submodels, provides an improved spray morphology compared to the cluster distribution. The findings also underscored the importance of calibrating the Kelvin-Helmholtz Rayleigh-Taylor (KH-RT) breakup model constants and droplet heat transfer coefficient scaling factor to achieve favorable agreement regarding measured liquid penetration and spray widths. In conclusion, this study marks a substantial stride towards accurately predicting fuel film evolution and soot formation within DISI engine performance.

ECN Spray G↗

Radiation-Induced Effects on the Extraction Properties of Hexa-n-octylnitrilo-triacetamide (HONTA) Complexes of Americium and Europium

The candidate An(III)/Ln(III) separation ligand hexa-n-octylnitrilo-triacetamide (HONTA) was irradiated under envisioned SELECT (Solvent Extraction from Liquid waste using Extractants of CHON-type for Transmutation) process conditions (n-dodecane/0.1 M HNO 3 ) using a solvent test loop in conjunction with cobalt-60 gamma irradiation. The extent of HONTA radiolysis and complimentary degradation product formation was quantified by HPLC-ESI-MS/MS. Further, the impact of HONTA radiolysis on process performance was evaluated by measuring the change in 243 Am and 154 Eu distribution ratios as a function of absorbed gamma dose. HONTA was found to decay exponentially with increasing dose, affording a dose coefficient of d = (4.48 ± 0.19) × 10 –3 kGy –1 . Multiple degradation products were detected by HPLC-ESI-MS/MS with dioctylamine being the dominant quantifiable species. Both 243 Am and 154 Eu distribution ratios exhibited an induction period of ~70 kGy for extraction (0.1 M HNO 3 ) and back-extraction (4.0 M HNO 3 ) conditions, after which both values decreased with absorbed dose. The decrease in distribution ratios was attributed to a combination of the destruction of HONTA and ingrowth of dioctylamine, which is capable of interfering in metal ion complexation. Furthermore, the loss of HONTA with absorbed gamma dose was predominantly attributed to its reaction with the n-dodecane radical cation (R˙ + ). These R˙ + reaction kinetics were measured for HONTA and its 241 Am and 154 Eu complexes using picosecond pulsed electron radiolysis techniques. All three second-order rate coefficients (k) were essentially diffusion limited in n-dodecane indicating a significant reaction pathway: k(HONTA + R˙ + ) = (7.6 ± 0.8) × 10 9 M –1 s –1 , k(Am(HONTA) 2 + R˙ + ) = (7.1 ± 0.7) × 10 10 M –1 s –1 , and k(Eu(HONTA) 2 + R˙ + ) = (9.5 ± 0.5) × 10 10 M –1 s –1 . HONTA-metal ion complexation afforded an order-of-magnitude increase in rate coefficient. Additional nanosecond time-resolved measurements showed that both direct and indirect HONTA radiolysis yielded the short-lived (< 100 ns) HONTA radical cation and a second long-lived (µs) species identified as the HONTA triplet excited state. The latter was confirmed by a series of oxygen quenching picosecond pulsed electron measurements, affording a quenching rate coefficient of k( 3 [HONTA]* + O 2 ) = 2.2 × 10 8 M –1 s –1 . Overall, both the HONTA radical cation and triplet excited state are important precursors to the suite of measured HONTA degradation products.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Proton surface exchange kinetics of perovskite triple conducting thin films for protonic ceramic electrolysis cells: BaPr 0.9 Y 0.1 O 3–δ (BPY) vs. Ba 1–x Co 0.4 Fe 0.4 Zr 0.1 Y 0.1 O 3–δ (BCFZY)

Protonic ceramic electrolysis cells (PCECs) are an attractive green H 2 production technology, given their intermediate-temperature operating range and ability to produce dry H 2 . However, PCECs will benefit from development of more efficient and durable “triple conducting” anodes where steam is split, H incorporated, and oxygen evolved. In this work, we evaluated the kinetics of the steam-splitting/H incorporation reaction on BaPr 0.9 Y 0.1 O 3–δ (BPY) in comparison to the benchmark Ba 1–x Co 0.4 Fe 0.4 Z r0.1 Y 0.1 O 3–δ (BCFZY) composition, replacing most of the transition metal elements (Co, Fe, Zr) with the lanthanide Pr. We prepared geometrically well-defined perovskite BPY and BCFZY thin films by pulsed laser deposition and performed simultaneous optical transmission relaxation and electrical conductivity relaxation measurements at 400–500 °C in 0.21 atm O 2 during switching of the steam partial pressure to isolate and compare their proton surface exchange coefficients (k). The k values of BPY were comparable to those of BCFZY and more stable over time. According to angle-resolved XPS and STEM-EDS mapping of FIB cross-sections, the surface of BPY exhibited Ba enrichment, Pr deficiency, and Si contamination. In contrast, BCFZY exhibited Ba deficiency throughout, no obvious surface segregation, and less Si contamination. The Ba segregation on the BPY film appears to have promoted steam splitting/H incorporation kinetics even though the more basic surface reacted with the acidic environmental SiO x H y . Faster kinetics observed on stoichiometric BCFZY vs. Ba-deficient BCFZY confirmed the benefit of a high A-site Ba concentration. This result contrasts with most work on perovskites applied in solid oxide electrolysis cell anodes, in which A-site segregation is considered deleterious for surface reaction kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SCALE Modeling of the Sodium Cooled Fast-Spectrum Advanced Burner Test Reactor

This report documents the modeling and simulation of a sodium-cooled fast reactor (SFR) as part of a U.S. Nuclear Regulatory Commission–sponsored project to assess the modeling and simulation capabilities for accident progression, source term, and consequence analysis for advanced reactor technologies with the Oak Ridge National Laboratory code SCALE and the Sandia National Laboratories (SNL) code MELCOR. Based on publicly available benchmark specifications, a fully heterogeneous 3D SCALE model of the 250 MWth Advanced Burner Test Reactor (ABTR) was developed to demonstrate SCALE’s capabilities for full-core reactivity analysis, fuel inventory prediction, and decay heat analysis of an SFR. The benchmark specifications contain modeling details for the ABTR core at the beginning of equilibrium cycle (BOEC) at operating conditions; they were derived from a 2006 preconceptual design report produced by Argonne National Laboratory. The ABTR was designed to demonstrate reactor-based transmutation of transuranics, that is, to “burn” transuranics recovered from light-water reactor (LWR) spent fuel. The ABTR’s fuel is designed to operate in 4 month cycles using uranium/transuranic (U/TRU) metallic fuel, with a TRU content of approximately 20%, at a conversion ratio of approximately 0.6. Various reactivity calculations were performed with SCALE for the ABTR and, where possible, compared with results available in the open literature. Additionally, SCALE was used to perform a full-core depletion calculation over the 4 month cycle to obtain the nuclide inventory at the end of equilibrium cycle (EOEC). These nuclide inventories, decay heat, power profiles, and reactivity feedback coefficients at EOEC represent the initial conditions for analyzing severe accident scenarios with MELCOR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development of Decay Heat Sensitivity Analysis Capability in SCALE/ORIGEN

In this work, a decay heat sensitivity analysis capability was developed and implemented in the ORIGEN code of the SCALE nuclear modeling and simulation suite. This capability introduces improved numerical integration schemes, which overcome the challenges associated with accurately modeling the behavior of adjoint nuclide amounts during coarse time steps for both nuclide amount and decay heat sensitivity calculations. This capability significantly improves the accuracy of calculations without compromising computational efficiency compared to the existing method. Extensive verification was conducted for various benchmark problems, including a 238 Pu decay and an irradiation problem involving 135 Xe, evaluated with both coarse and fine time grids. The results show excellent agreement with reference direct perturbation solutions, reaffirming the computational accuracy of the newly proposed numerical integration methods. Furthermore, sensitivity analyses were performed for fission product inventories ( 147 Sm, 150 Sm, 155 Gd) in pressurized water reactor UO 2 and MOX fuel assemblies. These analyses demonstrated that the ORIGEN sensitivity analysis capability can capture detailed sensitivity coefficients and underlying physics in real applications. Additionally, a decay heat sensitivity analysis for high-assay low-enriched uranium fuel, including various initial 235 U enrichment and burnup points, highlights the extended capabilities of SCALE/ORIGEN in comprehensively assessing the factors influencing total decay heat. These advancements in ORIGEN offer valuable insights for reactor analysis, fuel design, and safety assessments, especially in the context of advanced nuclear fuel development and design changes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Influence of Microstructure on TCR for Inkjet-Printed Resistive Temperature Detectors Fabricated Using AgNO 3 /Ethylene-Glycol-Based Inks

This study investigated the influence of microstructure on the performance of Ag inkjet-printed, resistive temperature detectors (RTDs) fabricated using particle-free inks based on a silver nitrate (AgNO 3 ) precursor and ethylene glycol as the ink solvent. Specifically, the temperature coefficient of resistance (TCR) and sensitivity for sensors printed using inks that use monoethylene glycol (mono-EG), diethylene glycol (di-EG), and triethylene glycol (tri-EG) and subjected to a low-pressure argon (Ar) plasma after printing were investigated. Scanning electron microscopy (SEM) confirmed previous findings that microstructure is strongly influenced by the ink solvent, with mono-EG inks producing dense structures, while di- and tri-EG inks produce porous structures, with tri-EG inks yielding the most porous structures. RTD testing revealed that sensors printed using mono-EG ink exhibited the highest TCR (1.7 × 10 -3 /°C), followed by di-EG ink (8.2 × 10 -4 /°C) and tri-EG ink (7.2 × 10 -4 /°C). These findings indicate that porosity exhibits a strong negative influence on TCR. Sensitivity was not strongly influenced by microstructure but rather by the resistance of RTD. The highest sensitivity (0.84 Ω/°C) was observed for an RTD printed using mono-EG ink but not under plasma exposure conditions that yield the highest TCR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

AlGaN High Electron Mobility Transistor for High-Temperature Logic

Here we report on AlGaN high electron mobility transistor (HEMT)-based logic development, using combined enhancement- and depletion-mode transistors to fabricate inverters with operation from room temperature up to 500°C. Our development approach included: (a) characterizing temperature-dependent carrier transport for different AlGaN HEMT heterostructures, (b) developing a suitable gate metal scheme for use in high temperatures, and (c) over-temperature testing of discrete devices and inverters. Hall mobility data (from 30°C to 500°C) revealed the reference GaN-channel HEMT experienced a 6.9x reduction in mobility, whereas the AlGaN channel HEMTs experienced about a 3.1x reduction. Furthermore, a greater aluminum contrast between the barrier and channel enabled higher carrier densities in the two-dimensional electron gas for all temperatures. The combination of reduced variation in mobility with temperature and high sheet carrier concentration showed that an Al-rich AlGaN-channel HEMT with a high barrier-to-channel aluminum contrast is the best option for an extreme temperature HEMT design. Three gate metal stacks were selected for low resistivity, high melting point, low thermal expansion coefficient, and high expected barrier height. The impact of thermal cycling was examined through electrical characterization of samples measured before and after rapid thermal anneal. The 200-nm tungsten gate metallization was the top performer with minimal reduction in drain current, a slightly positive threshold voltage shift, and about an order of magnitude advantage over the other gates in on-to-off current ratio. After incorporating the tungsten gate metal stack in device fabrication, characterization of transistors and inverters from room temperature up to 500°C was performed. The enhancement-mode (e-mode) devices’ resistance started increasing at about 200°C, resulting in drain current degradation. This phenomenon was not observed in depletion-mode (d-mode) devices but highlights a challenge for inverters in an e-mode driver and d-mode load configuration.

42 ENGINEERING↗

Outdoor Deployment Data for a Four-Terminal GaAs//Si Tandem Solar Mini-Module

This dataset contains the complete outdoor measurement and analysis data for a mechanically stacked, four-terminal (4T) gallium arsenide (GaAs)//silicon (Si) tandem solar mini-module deployed from October 2019 to January 2021 at the Solar Radiation Research Laboratory (SRRL) in Golden, Colorado, USA. The data support a performance modeling and degradation analysis framework for tandem photovoltaic devices, as described in the accompanying publication. The dataset includes: (1) current–voltage (J–V) characteristics of each sub-cell measured approximately every five minutes, with extracted performance parameters; (2) spectral irradiance from an EKO MS-710 WISER spectroradiometer, along with derived spectral mismatch ratios (SMR) and average photon energy (APE); (3) one-minute resolution meteorological data from the co-located SRRL weather station and GPS-derived precipitable water vapor (PWV); (4) pre-deployment laboratory characterization (external quantum efficiency, J–V curves, standard test conditions parameters); (5) outdoor-extracted temperature and PWV correction coefficients; and (6) PVcircuit equivalent-circuit simulation outputs used for model validation. Degradation rates of −4.1 ± 0.2 %/year (GaAs) and −2.5 ± 0.9 %/year (Si) were determined using a filtering and normalization methodology adapted for fixed-tilt tandem modules. All data are provided in open, portable formats (Apache Parquet, CSV, JSON) to enable full reproducibility of the published analysis.

14 SOLAR ENERGY↗

MODELLING FIBER ORIENTATION DURING ADDITIVE MANUFACTURING COMPRESSION MOLDING PROCESSES

The production of high-performance thermoplastic composites reinforced with short carbon fibers can be achieved by a novel “additive manufacturing-compression molding” technique. An advantage of such combination is two-fold: controlled fiber orientation in additive manufacturing and less void content by compression molding. In this study, a computational fluid dynamics model has been developed to predict the behavior of printed layers during fiber-reinforced thermoplastic extrusion and subsequent compression molding. The fiber orientation was modelled with a simple quadratic closure model. The interaction between the fibers is included using a rotary diffusion coefficient which becomes significant in concentrated regimes. Finally, the second order orientation tensor is coupled with the momentum equation as an anisotropic part of the stress term. The effect of processing parameters on the behavior of printed layers was investigated to determine the favorable printing scenarios. The developed numerical model enables design of high-performance composites with tunable mechanical properties.

Seta, Berin↗

Enhancement of operational Flexibility of Power Plants Using IN740

Headers are crucial components within diverse industries, especially in the energy sector, as they enable the efficient transfer of fluids. The selection of materials for headers is determined by their specific applications; for example, Grade 91 and Grade 92 steels are commonly utilized. In our research, we recommend the adoption of INCONEL alloy 740 due to its exceptional robustness and heat-resistant characteristics. One critical parameter in header systems is the heat transfer coefficient, which directly influences the efficiency of heat exchange processes and can thereby impact the structural integrity of the headers. This coefficient is closely linked with factors such as the Nusselt number, which is influenced by fluid flow characteristics and thermal properties. The flow direction within headers, whether unidirectional or multidirectional—significantly affects the overall dynamics of heat transfer. This research focuses on exploring the behavior of headers, a specific pipeline system component, using ANSYS simulation software. The study aims to predict heat transfer and mechanical behavior within headers under various conditions through steady-state and transient simulations (parts 1 and 2 of the report). Key parameters such as heat transfer coefficient, velocity, and temperature are examined with the goal of optimizing header design. Part 3 of the report addresses the critical yet underexplored relationship between pressure drop and heat transfer coefficients in the transient flow regime within headers, specifically focusing on smooth horizontal circular tubes. Limited experimental work has been conducted in this area, prompting the need for comprehensive analysis. By leveraging machine learning techniques, this research aims to establish a correlation between pressure drop and heat transfer across various flow conditions, including laminar, transient, quasi-turbulent, and turbulent regimes. The data utilized for this analysis were meticulously gathered from existing literature, capturing simultaneous measurements of pressure drops and heat transfer. Part 4: In the context of power plants, header pipes are essential components that significantly influence system performance by facilitating the collection and distribution of steam. This report highlights the critical role of header pipes in enhancing reliability, efficiency, and overall power plant performance. A key aspect of this investigation is shape optimization, which aims to maximize performance while minimizing material usage. By focusing on shape optimization, this research contributes to improved efficiency and a reduced environmental footprint for power plant installations. The methodology developed in this study emphasizes optimizing header shapes to decrease reliance on expensive alloy materials and lower maintenance costs. Furthermore, a case study was conducted using a header from an operational power plant to validate the proposed optimization techniques. Finally, part 5 addresses the challenges associated with flexible operations in boiler systems, the study outlines several strategies for enhancing the durability and reliability of steam headers. Key approaches include material selection, which involves utilizing advanced materials with superior high-temperature properties and enhanced fatigue resistance to extend the lifespan of steam headers. Design modifications are also recommended, focusing on implementing changes that mitigate thermal stress and cyclic loading to reduce the likelihood of failures under varying operating conditions. Additionally, the study emphasizes the importance of regular inspection and monitoring by establishing rigorous protocols to detect early signs of damage, allowing for timely maintenance and minimizing the risks of catastrophic failures. Furthermore, operational guidelines are developed to minimize the frequency and severity of thermal transients, ensuring stable and efficient operations. Collectively, these strategies provide a robust framework for overcoming the unique challenges posed by flexible operation in boiler systems, ultimately contributing to improved reliability and performance in power plant operations. Through this comprehensive approach, the study not only enhances the understanding of pressure drop and heat transfer relationships but also promotes advancements in design and operation that will benefit the entire power generation industry.

01 COAL, LIGNITE, AND PEAT↗

Surface Roughness Effects on Heat Transfer in Additively Manufactured sCO 2 Cycle Heat Exchangers

An experimental study was performed to consider the impact of surface roughness on heat transfer and pressure drop to supercritical carbon dioxide (sCO 2 ) in additively manufactured channels. All tests were performed in the Heat Exchange and Experimental Testing (HEET) rig at the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) in Morgantown, West Virginia. Four test articles were considered. The first was a hydrodynamically smooth, drawn tube. The other three were additively manufactured channels with square and rectangular cross sections, which were characterized by sand-grain roughness to hydraulic diameter ratios spanning 0.0029 to 0.0073. Friction factors were determined by measuring the tube mass flow rate and pressure drop. The tube side heat transfer coefficient was measured using the Wilson plot technique. It was found that the friction factor results were 8% greater than the Colebrook correlation. Greater deviation was observed between the heat transfer results and the correlations. The Gnielinski correlation overpredicted the experimental points by nominally 30% and the Norris correlation overpredicting the experimental points by nominally 25%. A thermal performance factor was formed from the friction factor augmentation and Nusselt number augmentation results. These results indicated a 10% improvement in heat duty for a heat exchanger constructed utilizing a tube with ϵ/D_h =0.0073 relative to a heat exchanger utilizing a smooth, conventional tube.

36 MATERIALS SCIENCE↗

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗

Comparative Evaluation of Control-Oriented Heavy Duty Vehicle Air Drag Coefficient Models

Heavy-duty vehicles (HDVs) are a significant source of fuel consumption and greenhouse gas emissions, prompting solutions such as HDV platooning to mitigate these negative impacts through air drag reduction. The intervehicle distance in an HDV platoon needs to be carefully selected, such that the platoon-level energy efficiency and safety considerations can be well balanced. Underlying this problem lies in accurately modeling the relationship between HDV air drag coefficient and intervehicle distance. Through comprehensive evaluation and comparison, we analyze five control-oriented HDV air drag coefficient models, including the polynomial model, rational polynomial model, rational model, semi-quadratic model, and ridge model. Leveraging Scipy Curve-Fit toolbox and our previously compiled air drag coefficient datasets, we optimally identify the parameters inside each model. The calibrated models are then thoroughly evaluated via five complementary metrics. The comparison results reveal that the semi-quadratic model has the highest overall performance, while the widely adopted rational model only exhibits suboptimal performance.

Best, Micah↗

High-Temperature Thermodynamics of Cerium Silicates, A-Ce 2 Si 2 O 7 , and Ce 4.67 (SiO 4 ) 3 O

Lanthanide disilicates and oxyapatites have potential roles in high temperature applications as thermal (TBC) and environmental barrier coatings (EBC), or possible alteration phases in geological nuclear waste repositories. However, those Ce 3+ -bearing silicates have only been limitedly studied. In this work, we performed detailed structural and thermodynamic investigations on A-Ce 2 Si 2 O 7 (tetragonal, P4 1 ) and Ce 4.67 (SiO 4 ) 3 O (hexagonal, P6 3 /m). The high temperature structural behaviors and coefficients of thermal expansion were determined by in situ high temperature synchrotron X-ray diffraction (HT-XRD) implemented with Rietveld analysis and thermogravimetric analysis coupled with differential scanning calorimetry (TGA-DSC). A-Ce 2 Si 2 O 7 was found to be stable in N 2 and air up to ~1483 K with anisotropic thermal expansion along the a and c axes (α a = 12.3 × 10 -6 K -1 and α c = 12.4 × 10 -6 K -1 ). Ce 4.67 (SiO 4 ) 3 O had a slow partial oxidation between 533 K and 873 K to a new nonstoichiometric phase Ce 3+ 1.67- xCe4 + x Ce 3+ 3 (SiO 4 ) 3 O 1+0.5x , followed by a thermal decomposition to CeO 2 and SiO 2 at ~1000 K in air. By using high temperature oxide melt solution calorimetry at 973 K with lead borate as the solvent, the standard enthalpy of formation was determined for A-Ce 2 Si 2 O 7 (-3825.1 ± 6.0 kJ/mol) and Ce 4.67 (SiO 4 ) 3 O (-7391.3 ± 9.5 kJ/mol). Finally, these thermodynamic parameters were compared with those of CeO 2 , CeSiO 4 , and other silicate oxyapatites for examining their chemical stability in high temperature environments relevant for aeronautical applications, mineral formation, and nuclear fuel cycle.

36 MATERIALS SCIENCE↗

Enhanced thermoelectric performance via quantum confinement in a metal oxide semiconductor field effect transistor for thermal management

Abstract The performance of thermoelectric devices is gauged by the dimensionless figure of merit $${{{{{\boldsymbol{ZT}}}}}}$$ ZT . Improving $${{{{{\boldsymbol{ZT}}}}}}$$ ZT has proven to be a formidable challenge given the interdependence of its constitutive quantities, namely Seebeck coefficient, electrical conductivity, thermal conductivity, and temperature. Here, we use quantum confinement to decouple Seebeck coefficient and electrical conductivity to demonstrate an order of magnitude quantum-based enhancement to the thermoelectric figure of merit $${{{{{\boldsymbol{ZT}}}}}}$$ ZT in complimentary metal-oxide-semiconductor field-effect transistors. While most quantum-based enhancement is done through physical confinement using two-dimensional materials, our approach uses electrical confinement. Because of this, our device is more robust than the two-dimensional materials currently used. We further articulate that improvement by as much as a factor of 50 could be achieved in a practical setting. Our approach further provides a path for monolithic integration of on-chip coolers and energy scavengers with virtually no deviation from the fabrication flow of standard electronics.

Oxandale, Samuel W. (ORCID:0000000207484066)↗

OrbNet Denali: A machine learning potential for biological and organic chemistry with semi-empirical cost and DFT accuracy

We present OrbNet Denali, a machine learning model for an electronic structure that is designed as a drop-in replacement for groundstate density functional theory (DFT) energy calculations. The model is a message-passing graph neural network that uses symmetryadapted atomic orbital features from a low-cost quantum calculation to predict the energy of a molecule. OrbNet Denali is trained on a vast dataset of 2.3 × 10 6 DFT calculations on molecules and geometries. This dataset covers the most common elements in biochemistry and organic chemistry (H, Li, B, C, N, O, F, Na, Mg, Si, P, S, Cl, K, Ca, Br, and I) and charged molecules. OrbNet Denali is demonstrated on several well-established benchmark datasets, and we find that it provides accuracy that is on par with modern DFT methods while offering a speedup of up to three orders of magnitude. For the GMTKN55 benchmark set, OrbNet Denali achieves WTMAD-1 and WTMAD-2 scores of 7.19 and 9.84, on par with modern DFT functionals. For several GMTKN55 subsets, which contain chemical problems that are not present in the training set, OrbNet Denali produces a mean absolute error comparable to those of DFT methods. For the Hutchison conformer benchmark set, OrbNet Denali has a median correlation coefficient of R 2 = 0.90 compared to the reference DLPNO-CCSD(T) calculation and R 2 = 0.97 compared to the method used to generate the training data (ωB97X-D3/def2- TZVP), exceeding the performance of any other method with a similar cost. Similarly, the model reaches chemical accuracy for noncovalent interactions in the S66x10 dataset. For torsional profiles, OrbNet Denali reproduces the torsion profiles of ωB97X-D3/def2-TZVP with an average mean absolute error of 0.12 kcal/mol for the potential energy surfaces of the diverse fragments in the TorsionNet500 dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diffusion-mediated passing of molecular species in linear nanopores constrained by orientational alignment

For diffusion-mediated catalytic conversion reactions in materials with narrow linear nanopores, e.g., mesoporous silica MCM-41, a key parameter is the propensity for product species to be able to pass reactant species and thus to efficiently exit the pore. For elongated species, this can require orientational alignment with the pore axis. In this work, we perform benchmark analyses for such solution-phase systems where one of these species is elongated in order to quantify the dependence of this passing propensity, P, on pore diameter and on the rotational diffusion coefficient, Dr, of the elongated species. In particular, we consider the passing of a spherical and an elongated spherocylindrical shaped species in a cylindrical pore in an implicit solvent, where these species cannot overlap. Passing is mediated by diffusive Brownian motion of these species as described by strongly damped Langevin dynamics. We quantify scaling of P for pore width just above the threshold where passing is sterically blocked, and also reveal a significant decrease in P for lower Dr. We also consider the dependence of P on the aspect ratio of the elongated species and obtain an exact result in the limiting regime of large aspect ratio.

Brownian motion↗

First use of an InSb crystal for x-ray imaging spectroscopy of highly ionized tungsten in the Wendelstein 7-X stellarator

Advances in time and space resolved measurements of highly charged states of tungsten (W) through x-ray imaging spectroscopy have enabled investigation of impurity transport in the Wendelstein 7-X (W7-X) stellarator. The high-resolution x-ray imaging spectrometer (HR-XIS) system on W7-X utilizes the Bragg diffraction properties of a set of multiple crystals to measure a range of impurity emission lines within sections of the 1–7 Å wavelength range, including transitions of W. A new indium–antimonide crystal has been installed on the HR-XIS system to allow viewing of the 5.5–6.2 Å region focusing on emissions of W. Consequently, many bright W emission lines from W 40+ to W 47+ were observed in this wavelength range, both in plasmas with injected W and in those with only intrinsic W impurity sources, showing the high sensitivity of the diagnostic. Three W 46+ emissions correspond in wavelength and intensity with calculated photon emissivity coefficients and can be exploited for W transport and concentration applications in plasmas with T e ≳ 2.1 keV. Here, an estimate of the core W density behavior in two separate turbulence-reduced ‘high-performance’ (HP) discharges on W7-X is done using the 5.6893 Å W 46+ line. The n W behavior in HP scenarios can be explained by previous experimental results and neoclassical predictions.

XICS↗