Understanding Magnetic Exchange Interactions by the Pressure Dependent Curie Temperature in FeCoNiCu
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Soot production (including formation and oxidation) is studied in the transient, high-pressure and turbulent n-dodecane Spray A flames from the Engine Combustion Network (ECN) using computational fluid dynamics (CFD) simulations. A two-equation soot-in-flamelet modeling approach is applied within the framework of the Unsteady Flamelet Progress Variable (UFPV) model and results are validated against experimental data. Equations for soot mass fraction and soot number density derived in the mixture fraction space are solved in the context of detailed flamelet calculations. Source terms for the different steps in the soot chemistry are tabulated and incorporated in the flamelet manifold. For the reference condition, the modeling approach based on the tabulated flamelet manifold reduces the computational cost of a CFD calculation by approximately 40 times compared to a non-tabulated well-mixed (WM) modeling approach. The soot-in-flamelet approach is then extended to study the effect of ambient oxygen concentration, ambient mixture composition and ambient temperature on soot production. Results show that the modeling approach is able to capture the experimental trends for the soot volume fraction (SVF) with good quantitative agreement, especially in the soot ramp-up region.
Core-collapse supernovae are intense sources of tens-of-MeV neutrinos. Each explosion releases about 1058 neutrinos in a burst lasting tens of seconds. As neutrinos are weakly interacting, they escape more easily compared to photons, allowing them to be observed before the light signal. Understanding low-energy neutrino interactions with argon will be critical for future supernova measurements with the Deep Underground Neutrino Experiment (DUNE). Interpreting future DUNE supernova neutrino data will require a high-quality model of O(10 MeV) neutrino interactions, but the dominant charged-current cross section has never been measured at these low energies for an argon target. We exploit the theoretical similarities between muon capture, which has been measured, and antineutrino scattering to test MARLEY (Model of Argon Reaction Low Energy Yields), the simulation code used by DUNE to model supernova neutrino reactions. I implemented C++ code to add a muon capture mode to MARLEY and compared the predictions of the new simulation to measured isotope branching ratios of the residual nuclei. The preliminary branching ratios predicted by MARLEY running in muon capture mode demonstrate promising baseline performance when compared to experimental data and are expected to improve with further model adjustments.
A series of batch experiments were performed to assess the uranium sorption capacity of four mineralogically distinct lithologies from the Negev Desert, Israel, to evaluate the suitability of a potential site for subsurface radioactive waste disposal. The rock specimens consisted of an organic-rich phosphorite, a bituminous marl, a chalk, and a sandstone. The sorption data for each lithology were fitted using a general composite surface complexation model (GC SCM) implemented in PHREEQC. Sorption data were also fitted by a non-mechanistic Langmuir sorption isotherm, which can be used as an alternative to the GC SCM to provide a more computationally efficient method for uranium sorption. This is because all the rocks tested have high pH/alkalinity/calcium buffering capacities that restrict groundwater chemistry variations, so that the use of a GC SCM is not advantageous. The mineralogy of the rocks points to several dominant sorption phases for uranyl (UO 2 2+ ), including apatite, organic carbon, clays, and iron-bearing phases. The surface complexation parameters based on literature values for the minerals identified overestimate the uranium sorption capacities, so that for our application, an empirical approach that makes direct use of the experimental data to estimate mineral-specific sorption parameters appears to be more practical for predicting uranium sorption.
Pion production on nuclei constitutes a significant part of the total cross section in experiments involving few-GeV neutrinos. Combined analyses of data on deuterium and heavier nuclei points to tensions between the bubble chamber data and the data of the MINER$\nu$A experiment, which are often ascribed to unspecified nuclear effects. To understand the origin of these tensions, a microscopic quantum mechanical framework is needed to compute nuclear matrix elements. We use the local approximation to the relativistic distorted wave impulse approximation (RDWIA) to assess the role of final-state nucleon distortion. To perform this comparison under conditions relevant to neutrino experiments, we compute cross sections for the MINER$\nu$A and T2K charged pion production datasets. The inclusion of nucleon distortion leads to a reduction of the cross section up to 10%, but to no significant change in shape of the flux-averaged cross sections. Results with and without distortion compare favorably to experimental data, with the exception of the low-$Q^2$ MINER$\nu$A $\pi^+$ data. We point out that hydrogen target data from BEBC is also overpredicted at low-$Q^2$, and that the discrepancy is similar in shape and magnitude to what is found in comparison to MINER$\nu$A data. Including nucleon distortion alone cannot explain the overprediction of low-$Q^2$ cross sections measured by MINER$\nu$A. The similar overprediction of BEBC data on hydrogen means that it is impossible to ascribe this discrepancy solely to a nuclear effect. Axial couplings and their $Q^2$ dependence should ideally be derived from more precise data on hydrogen and deuterium.
Here, cylindrical implosion experiments are used to directly measure instability growth in a convergent geometry, providing a wealth of data for model validation. Double cylinders are a natural extension of the platform and enable measurements at a classically unstable interface, the outer surface of the inner cylinder, which experiences no ablative stabilization from the laser drive. However, the utility of this platform relies upon maintaining adequate axial uniformity of the inner cylinder during the implosion. Although previous smaller-scale double cylinder experiments exhibited acceptable levels of axial uniformity, radiation-hydrodynamics simulations of larger-scale double cylinders predict more axial non-uniformity induced by the impedance mismatch as the shock wraps around the axial ends of the inner cylinder. A mechanism to reduce axial non-uniformity in these larger double cylinder implosions is presented, and preliminary experimental data confirms the efficacy of the selected mitigation approach.
The fate of thymine upon excitation by ultraviolet radiation has been the subject of intense debate. Today, it is widely believed that its ultrafast excited state gas phase decay stems from a radiationless transition from the bright ππ* state to a dark nπ* state. However, conflicting theoretical predictions have made the experimental data difficult to interpret. Here we simulate the early gas phase ultrafast dynamics in thymine at the highest level of theory to date. This is made possible by performing wavepacket dynamics with a recently developed coupled cluster method. Our simulation confirms an ultrafast ππ* to nπ* transition (τ = 41 ± 14 fs). Furthermore, the predicted oxygen-edge X-ray absorption spectra agree quantitatively with experiment. We also predict an as-yet uncharacterized πσ* channel that leads to hydrogen dissociation at one of the two N-H bonds. Similar behavior has been identified in other heteroaromatic compounds, including adenine, and several authors have speculated that a similar pathway may exist in thymine. However, this was never confirmed theoretically or experimentally. This prediction calls for renewed efforts to experimentally identify or exclude the presence of this channel.
In recent years, the U.S. Nuclear Regulatory Commission (USNRC) and the International Atomic Energy Agency (IAEA) have developed methodologies to assess the vulnerabilities of nuclear plants against site specific extreme hazards. In many cases, advanced simulation tools are being considered to simulate multi-physics, multi-scale phenomena and to evaluate vulnerability of nuclear facilities. The credibility of advanced simulation tools is assessed based on a formal verification, validation, and uncertainty quantification procedure. One of the key limitations in validation is the lack of relevant experimental data at system-level. This limitation leads to a decrease in the confidence of system-level risk predictions. Therefore, a robust validation framework is needed to formalize the confidence in predictive capability of advanced simulation results. Additionally, this study enhances the existing risk informed validation methodology, originally proposed by Kwag et al. [1] and Bodda et al. [2], by developing additional attributes and a new set of validation indicies for a complete and wider applicability of the framework. In this manuscript, the methodology to identify the critical path that leads to the system-level failure is illustrated. The overall validation is checked for completeness and consistency by comparing the critical path for both the system-level simulation and experimental models. The applicability of the code for an intended application is represented in terms of various maturity levels and helps in the process of decision making.
Plant cell walls are complex systems that exhibit the characteristics of both rigid and soft material depending on their external perturbations. The three main polymeric components in a plant primary cell wall are cellulose fibrils, hemicellulose, and pectins. These components interact in a hierarchical fashion giving rise to mesoscale structural features such as cellulose bundles, lamella stacking, and so on. Although several studies have focused on understanding these unique structural features, a clear picture linking them to cell wall mechanics is still lacking. As a first step toward this goal, a phenomenological model of plant cell wall has been developed in this work by using available experimental data to investigate the underlying connections between mesoscale structural features and the motions of fibrils during deformation. In this model cellulose fibrils exhibit motions such as angular reorientations and kinking upon forced stretching. Furthermore, these motions are dependent on the orientation of fibrils with respect to the stretch direction, i.e., fibrils that are at an angle to the stretch direction exhibit predominant angular reorientations, while fibrils transverse to the stretch direction undergo kinking as a result of transverse compression. Varying the chain length of pectin had negligible effects on these motions. One of the main contributions from this work is the development of a simple model that can be easily fine-tuned to test other hypotheses and extended to include additional experimental knowledge about the structural aspects of cell walls in the future.
Thin film deposition from the vapor phase is a complex process involving adatom adsorption, movement, and incorporation into the growing film. While simulations have been able to capture key aspects of these processes to reproduce film morphology, these models typically ignore any subsurface diffusion that occurs. The results of these diffusion and intermixing processes are often observed experimentally, but cannot be explained by invoking bulk lattice diffusion at the deposition temperature. In this work, we present quantitative experimental data that reveals anion and cation intermixing over long length scales during the deposition of epitaxial Fe 2 O 3 and Cr 2 O 3 films and heterostructures by oxygen-plasma-assisted molecular beam epitaxy. We track this diffusion by incorporating well-defined tracer layers containing 18 O and/or 57 Fe, and measure their redistribution on the nanometer scale with atom probe tomography. Molecular dynamics simulations suggest potential intermixing events, which are then examined via nudged elastic band calculations. These reveal that adatoms on the film surface act to “pull up” subsurface O and Fe. Subsequent ring-like rotation mechanisms involving both adatom and subsurface anions then facilitate their mixing. A simple model incorporating these events qualitatively agrees with the experimental intermixing results. In addition to film deposition, these intermixing mechanisms may to be operant during other surface-mediated processes such as heterogeneous catalysis and corrosion.
The new LOGKPREDICT program integrates HostDesigner molecular design software with the machine learning (ML) program Chemprop. By supplying HostDesigner with predicted log K values, LOGKPREDICT enhances the computer-aided molecular design process by ranking ligands directly by metal–ligand binding strength. Harnessing reliable experimental data from a historic National Institute of Standards and Technology (NIST) database and data from the International Union of Pure and Applied Chemistry (IUPAC), we train message passing neural net algorithms. The multi-metal NIST-based ML model has a root mean square error (RMSE) of 0.629 ± 0.044 (R 2 of 0.960 ± 0.006), while two versions of lanthanide-only IUPAC-based ML models have, respectively, RMSE of 0.764 ± 0.073 (R 2 of 0.976 ± 0.005) and 0.757 ± 0.071 (R 2 of 0.959 ± 0.007). For relative log K predictions on an out-of-sample set of six ligands, demonstrating metal ion selectivity, the RMSE value reaches a commendably low 0.25. Here we showcase the use of LOGKPREDICT in identifying ligands with high selectivity for lanthanides in aqueous solutions, a finding supported by recent experimental evidence. We also predict new ligands yet to be verified experimentally. Therefore, our ML models implemented through LOGKPREDICT and interfaced with the ligand design software HostDesigner pave the way for designing new ligands with predetermined selectivity for competing metal ions in an aqueous solution.
Here, this paper introduces the use of statistical distributions based on transport differential equations for clear distinction of transport modes within transient kinetic experiments. More specifically, novel techniques are developed for the transient data obtained through the Temporal Analysis of Products (TAP) reactor and are applicable to experiments where pulse response into a gas flow is used. The methodology allows distinguishing between two domains of diffusion transport in heterogeneous catalytic systems, i.e., Knudsen and non-Knudsen diffusion, using statistical fingerprints, and finding the transition domain. Two distribution parameters were obtained that directly result in coefficients that correspond to the concentration and the rate of transport. Using a linear relationship between the rate and concentration coefficients, Knudsen diffusion is revealed when the rate of transport is constant and non-Knudsen diffusion is confirmed when the rate of transport coefficient is a function of the concentration coefficient. As a result, accurate transport information can be extracted from experimental data even in the presence of comprising instrument drift or noise particularly when analyzing higher pressure pulse responses with complex transport. This enables more direct investigation of experiments influenced by gas-phase reactions.
Abstract Internal features of varying scale and geometry are always present in explosives systems. Below a critical length, dependent on the explosive, these features can operate as a driving force for energy concentration and reaction, known as hotspots. At larger length scales, internal features result in jetting and detonation wave shaping, allowing for bulk work to be done by the explosive as is seen in shape charges. To date, a large volume of work has been performed to simulate hotspot ignition and large‐scale wave shaping. However, little experimental data exists on the effects of features in intermediate length scales, 0.1 to 1 millimeter. It has been observed in many tests that these small‐scale features can influence the high explosive (HE) performance and in some cases cause substantial damage to adjacent systems. This work provides quantitative data on the effects of machined voids moderately above more typical hotspot lengths, 0.3–0.8 mm in diameter, in PBX 9501 pressed to 1.785 g cm −3 ±2.5 mg cm −3 . Streak imaging was used to visualize void collapse, jet velocity, re‐initiation time, and wave shape evolution. Delay in detonation front propagation time was found to be linearly dependent on the void diameter and jet velocity was found to be independent within the tested range and resolution. Cut‐back experiments were used to investigate wave shape distortion and evolution downstream of the void, showing consistent growth and decay shapes across all void sizes. Simulations using CTH, a hydrocode by Sandia National Laboratory, were used to investigate void collapse showing agreement with the trends of experimental results but yielded inaccurate wave shape development delay values. Both simulation and experimental results identified several re‐initiation mechanisms with jetting and subsequent double shocking of localized HE being the dominant mechanisms for the void sizes that were studied.
Abstract This paper analyzes the dynamics of unstable azimuthal thermoacoustic modes in a lean premixed combustor. Azimuthal modes can be decomposed into two counter rotating waves where they can either compete and potentially suppress one of them (spinning) or coexist (standing), depending on the operating conditions. This paper describes experimental results of the dynamical behaviors of these two waves. The experimental data were taken at different mass flow rates as well as different azimuthal fuel staging in a multi-nozzle can combustor. It is shown that at a low flow rate with uniform fuel distribution, the two waves have similar amplitudes, giving rise to a standing wave. However, the two amplitudes are slowly oscillating out of phase to each other, and the phase difference between the two waves also shows oscillatory behavior. For an intermediate flow rate, the dynamics show intermittency between standing and spinning waves, indicating that the system is bistable. In addition, the phase difference dramatically shifts when the mode switches between standing and spinning waves. For a high flow rate, the system stabilizes at a spinning wave most of the time. These experimental observations demonstrate that not only the amplitudes of two waves but also the phase difference plays an important role in the dynamics of azimuthal mode. For non-uniform azimuthal fuel staging, the modal dynamics exhibit only an oscillatory standing wave behavior regardless of the mass flow rate. Compared to the uniform fuel staging, however, the pressure magnitude is considerably reduced, which provides a potential strategy to mitigate and/or suppress the instabilities.
We report high-throughput, ultra-fast laser sintering of alumina sample array and characterization of sample units’ microstructure and hardness, as a fast exploration of laser processing parameters, microstructure, and property. These experimental data were used to train machine-learning (ML) models. Accurate ML predictions were demonstrated for the processing-microstructure-property relationship, specifically in (1) prediction of the microstructure of alumina under arbitrary laser power and (2) prediction of the expected microstructure from the desired hardness. An independent neural network was developed and showed that ML-predicted microstructure had less than 10% error from real ones, in terms of projected hardness. To monitor the microstructure during laser sintering, we demonstrated an ML model that can instantaneously predict ceramic’s microstructure at the laser spot, based on the laser spot brightness. The ML model can generate more than 10 predictions per second, and the error in average grain size was less than 5% from the experimental observations.
Molten salts play a crucial role in advancing Generation IV nuclear energy technology, with chloride-based salts like NaCl-UCl 3 garnering significant attention due to their distinctive properties. However, the corrosive nature of molten salts causes the dissolution of chromium (Cr), leading to the formation of CrCl 2 and CrCl 3 species in molten chlorides. Moreover, the radioactive decay of nuclear fuel gives rise to fission products, including Cs, Sr, and I chlorides. The first part of this report presents a comprehensive study utilizing ab initio molecular dynamics (AIMD) simulations to investigate the properties of eutectic NaCl-UCl 3 molten salt in the presence of corrosion products (CrCl 2 and CrCl 3 ) and fission product (CsCl). The study focuses on essential structural and thermophysical properties such as density, mixing energy, coordination numbers (CN), and Radial Distribution Functions (RDF) of the salts with varying compositions of corrosion products and fission product, covering a range from 0% to 13.5%. The results offer valuable insights into the behavior of corrosion and fission products in uranium-based molten salts, providing essential data that can be used as input to the MTDB-TC and MSTDB-TP property databases being developed by the NEAMS program. Due to their favorable characteristics such as low melting points, high boiling points, and low costs, MgCl 2 +NaCl+KCl (MNK) eutectic salts have recently attracted attention as high-temperature heat transfer fluids. The incorporation of LiCl into MNK salts can further reduce their melting points and increase their specific heat capacities, which is de- sirable for high-temperature heat transfer applications. The second part of this report presents the development and validation of a new shell-model potential for the MgCl 2 +NaCl+KCl+LiCl system, which captures the polarization of Cl anions. The extensive comparison with experimental data and AIMD simulations demonstrates the accuracy and reliability of the potential. Furthermore, using this potential, we elucidate the intricate network structure in MNK eutectic salts that is formed through polyhedron sharing. This research contributes to a fundamental understanding of the atomic structures and thermophysical properties of multi-component molten salts, which is crucial for future development of heat transfer fluids for applications in molten salt reactors.
Numerous areas of nuclear processing, such as radioisotope production, nuclear waste remediation, and separations, depend upon the speciation of f-elements in the solution state. However, fundamental knowledge of the actinides─particularly Np─lags behind most of the elements on the periodic table. Despite the importance of Np(VI) chemistry in separations and nuclear processing, its speciation in HNO 3 remains uncertain. This work addresses some of these gaps by investigating the effect of HNO 3 concentration and temperature on the spectra and speciation of the Np(VI) nitrate system. Six samples of Np in 1 to 10 M HNO 3 were prepared and treated with (NH 4 ) 2 [Ce(NO 3 ) 6 ] to stabilize the hexavalent oxidation state. The absorbance spectrum of the 10 M HNO 3 is drastically different from the spectra of the other samples; the 10 M spectrum indicates coordination of nitrate ligands to the Np(VI)O 2 2+ ion to form a complex with high symmetry. Additionally, absorbance spectra were recorded over the temperature range of 15 to 40 °C, and systematic increases and decreases in certain spectral features of the ultraviolet–visible (UV–vis)–near-infrared (NIR) spectra are present in the spectra. The difference in spectral features suggests that Np(VI) nitrate speciation depends on temperature. Dilution studies of this sample were monitored with UV–vis–NIR and Raman spectroscopies. Spectral data indicate the presence of multiple complexes with different symmetries, including a high-symmetry complex with an inversion center. As samples are diluted and aquo ligands replace nitrate ligands bound to the Np(VI) neptunyl cation, changes in spectroscopic signals indicate a decrease in the high-symmetry nitrate complex and an increase in the lower-symmetry aquo complex. Additionally, the Raman band associated with the Np(VI)O 2 2+ symmetric stretch broadens with dilution and is fitted with two peaks. These peaks are assigned to Np(VI) aquo and nitrato complexes, indicating that this vibrational mode is sensitive to the coordination environment of the Np(VI) neptunyl cation and that contributions from these two Np(VI) complexes can be distinguished. This unique experimental data could be used to advance computational models describing the electronic transitions of complex actinyl ions.
The neutron evaluation of the isotopes that comprise natural lead were undertaken as a part of DOE-NEUP Project #19-16739. The goal of the project was to update the neutron cross sections to account for new differential measurements and incorporate the most up-to-date physics. Shortcomings in the lead cross sections was made known by several independent reports. The work performed here repeated the simulation of all the “benchmark” validation systems and concluded that the major issue is the scattering cross sections in the major lead isotopes above 100 keV. Re-evaluation of 206,207,208 Pb included both the resolved resonance region and fast region evaluations of the cross sections. Combined these regions cover energies from thermal to 20 MeV. The most drastic improvement is the resolved resonance region evaluation of 208 Pb which is now extended from 1.0 to 1.5 MeV. Parameterization of these resonances in the R-matrix provides a superior reconstruction of not only the experimental cross section but also the scattering distributions via the Blatt-Biedenharn formalism. Fast region evaluations of the three major isotopes were done to include new inelastic experimental data from the neutron Time-of-Flight facility at CERN. The culmination of all the changes to the cross section is a drastic improvement in the scattering kernel as shown in Rensselaer Polytechnic Institute (RPI) Quasi-Differential scattering measurements and improved prediction of keff for fast integral experiments. Alongside the new cross sections, new nuclear data covariance (uncertainties) have been computed and are included in the evaluation. Little is changed in the magnitude of the uncertainties but the correlations within the covariance display non-trivial changes. The new evaluations of 206,207,208 Pb have been submitted to the National Nuclear Data Center to be included in the ENDF/B-VIII.1 library. While the cross sections have been updated extensively, knowledge and modeling of the cross sections between 1.0 and 3.0 MeV for the isotopes remain a challenge. Most notably is the double differential elastic cross section for 208 Pb and 206 Pb. New quasi-differential measurements for pure samples of these two nuclei would go a long way in reducing compensating errors in the evaluations. Qualitatively, the project has produced a prosperous collaboration between the nuclear data group at RPI with staff scientists at Brookhaven National Laboratory, Naval Nuclear Laboratory, Oak Ridge National Laboratory, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Sandia National Laboratories. Quantitatively this is reflected in seven conference presentations, at least one journal submission, and one doctoral thesis.