Relativistic DFT Calculations of Cadmium and Selenium Solid-State NMR Spectra of CdSe Nanocrystal Surfaces
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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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Significance In this multidisciplinary study, we investigated local and global structural responses upon carbon monoxide (CO) dissociation from the heme iron(II) in myoglobin in solution using ultrafast X-ray absorption and scattering. CO dissociation was optically triggered and pulsed X-rays probed structural and electronic changes as a function of time, revealing an iron(II) spin state transition and nuclear motions propagating from the active site throughout the entire protein. Quantum mechanical computational results were used to assign the iron K-edge absorption features, and to map out electronic and nuclear trajectories during Fe–CO bond elongation and heme macrocycle doming. The study has important implications for heme–protein function and the interaction of small molecule substrates with the metal active centers in enzymes.
We apply correlation matrix renormalization theory (CMRT) to cerium nitride (CeN) under pressure. For 𝐵1 (NaCl-type) phase, CMRT gives an equation of state consistent with ambient pressure experiments. It produces electronic density-of-state (DOS) characterized by a sharp 4𝑓 quasiparticle resonance peak pinned at the Fermi level and two subbands formed by strong hybridization between the localized Ce-4𝑓 electrons and the itinerant Ce-5𝑑 and N-2𝑝 electrons below the Fermi level, consistent with x-ray photoemission spectroscopy experiments. Upon compression, CMRT predicts a first-order 𝐵1 → 𝐵2 (CsCl-type) transition with ∼11% volume collapse in agreement with experiments. Across the transition, the 4𝑓 spectrum broadens, the 4𝑓 orbital occupancy increases, and the hybridization with conduction states enhances, signaling a crossover from partially localized to more itinerant 4𝑓 behavior. Furthermore, these features are in excellent agreement with experimental observations, demonstrating that CMRT provides a parameter-free description and prediction of correlation-driven structural and electronic transitions in rare-earth compounds.
The stability of low-index platinum surfaces and their electronic properties is investigated with density functional theory, toward the goal of understanding the surface structure and electron emission, and identifying precursors to electrical breakdown, on nonideal platinum surfaces. Propensity for electron emission can be related to a local work function, which, in turn, is intimately dependent on the local surface structure. The (1×N) missing row reconstruction of the Pt(110) surface is systematically examined. The (1×3) missing row reconstruction is found to be the lowest in energy, with the (1×2) and (1×4) slightly less stable. In the limit of large (1×N) with wider (111) nanoterraces, the energy accurately approaches the asymptotic limit of the infinite Pt(111) surface. Furthermore, this suggests a local energetic stability of narrow (111) nanoterraces on free Pt surfaces that could be a common structural feature in the complex surface morphologies, leading to work functions consistent with those on thermally grown Pt substrates.
Dynamic and static crystal lattice properties of SrCu 2 (BO 3 ) 2 are studied by means of Raman scattering, magnetostriction, and thermal expansion measurements in magnetic fields to 45 T. Raman experiments versus temperature reveal that some phonon modes show an unusual behavior: their frequencies soften (modes at 200 and 450 cm –1 ) while others harden (modes at 385 and 478 cm –1 ) when decreasing the temperature below 15 K. Magneto-Raman experiments show that their field dependence correlates with their respective temperature dependencies; e.g., modes that are hardened with increasing temperature also harden with applied magnetic fields and modes that become softer with temperature also soften with applied fields. We use density functional theory to successfully model and compute the energies of these modes, classifying them into two types: pantograph (modes that soften when decreasing the temperature) and nonpantograph. We conclude that the former involves the modification of the intradimer exchange interaction J and the latter the interdimer J'. Lastly, dilatometry is used to correlate field-dependent Raman modes to the closing of the spin gap as well as fractional-magnetization stripe states M = 1/4 M s and M = 1/3 M s , where M s is the saturation magnetization.
In this work we study ordinary muon capture (OMC) on 24 Mg from a first-principles perspective. Starting from a particular two- and three-nucleon interaction derived from chiral effective field theory, we use the valence-space in-medium similarity renormalization group (VS-IMSRG) framework to construct effective Hamiltonians and muon-capture operators, which nonperturbatively account for many-body physics outside the valence space. Here, the obtained nuclear matrix elements are compared against those from the phenomenological shell model. The impact of including the correlations from the nuclear shell model (NSM) as well as including the induced twobody part is studied in detail. Furthermore, the effects of realistic bound-muon wave function on the operators is studied. Finally, predictions for capture rates to the lowest excited states in 24 Na are given and compared with available data. It is found that the spectroscopic properties of 24 Mg and its OMC daughter 24 Na are fairly well described by both the NSM and VS-IMSRG, and that the effect of the hadronic two-body currents significantly reduces the OMC rates. Both models have some difficulties in matching the measured OMC rates, especially for the 2 + final states. This calls for further studies in other light nuclei with available OMC data.
Starting from chiral nuclear interactions, we evaluate the contribution of the leading-order contact transition operator to the nuclear matrix element (NME) of neutrinoless double-beta decay, assuming a light Majorana neutrino-exchange mechanism. The corresponding low-energy constant (LEC) is determined by fitting the transition amplitude of the nn → ppe – e – process to a recently proposed synthetic datum. We examine the dependence of the amplitude on similarity renormalization group (SRG) scale and chiral expansion order of the nuclear interaction, finding that both dependences can be compensated to a large extent by readjusting the LEC. We evaluate the contribution of both the leading-order contact operator and standard long-range operator to the neutrinoless double-beta decays in the light nuclei 6,8 He and the candidate nucleus 48 Ca. Furthermore, our results provide the first clear demonstration that the contact term enhances the NME by 43(7)% in 48 Ca, where the uncertainty is propagated from the synthetic datum.
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The H-Canyon Facility plans on processing bundles from Non-Aluminum Spent Nuclear Fuel (NASNF) Risk Group 1 (UO 2 core fuels). Uranium-zirconium (UZr) alloys and zirconium clad UO 2 fuel containing UZr intermetallic compound have the potential to cause explosions during dissolution. UZr intermetallic typically only forms when uranium and zirconium (or zirconium alloy) cladding are in contact at high temperatures. Thermal modeling was performed to determine the maximum cladding temperature for Campaign 1 Zircoloy cladded fuel assembles during reactor operation to help determine if the UZr intermetallic compound could have formed during reactor operations. The temperature of 350°C was chosen as a conservative minimum value for the possible formation of intermetallic UZr compound. The modeling approach, inputs, and results are outlined in this document.
Dynamic catalysis—the forced oscillation of catalytic reaction coordinate potential energy surfaces (PES)—has recently emerged as a promising method for the acceleration of heterogeneously-catalyzed reactions. Theoretical study of enhancement of rates and supra-equilibrium product yield via dynamic catalysis has, to-date, been severely limited by onerous computational demands of forward integration of stiff, coupled ordinary differential equations (ODEs) that are necessary to quantitatively describe periodic cycling between PESs. Here, we establish a new approach that reduces, by ≳108×, the computational cost of finding the time-averaged rate at dynamic steady state (i.e. the limit cycle for linear and nonlinear systems of kinetic equations). Our developments are motivated by and conceived from physical and mathematical insight drawn from examination of a simple, didactic case study for which closed-form solutions of rate enhancement are derived in explicit terms of periods of oscillation and elementary step rate constants. Generalization of such closed-form solutions to more complex catalytic systems is achieved by introducing a periodic boundary condition requiring the dynamic steady state solution to have the same periodicity as the kinetic oscillations and solving the corresponding differential equations by linear algebra or Newton-Raphson-based approaches. The methodology is well-suited to extension to non-linear systems for which we detail the potential for multiple solutions or solutions with different periodicities. For linear and non-linear systems alike, the acute decrement in computational expense enables rapid optimization of oscillation waveforms and, consequently, accelerates understanding of the key catalyst properties that enable maximization of reaction rates, conversions, and selectivities during dynamic catalysis.
In recent years, theoretical simulations using computational physics and chemistry models have been used widely to predict the physical, chemical, and structural properties of nanomaterials. To reflect such rapid progress, two Special Issues on the theoretical study of nanomaterials were published. The 36 articles collected cover broad re-search fields and applications. In this Editorial, we provide an overview of these pub-lications and summarize the main findings. Based on these research outcomes, we lay out some future research directions.
This report details the steps taken to review a dose assessment performed by the National Institute of Science and Technology following a release at their reactor in Gaithersburg, MD in Feb. 2021.
The optical, thermal, and chemical properties of glass make it an ideal material for use in a wide range of applications, from optics and chemistry reactionware to consumer products. Tomographic volumetric additive manufacturing (tVAM) creates 3D objects by selectively gelling material within a rotating vial of photo-sensitive material by exposure to a series of tomographically-determined images. Here, in this study, tVAM is investigated for fabrication of complex, centimeter-scale, 3D silica glass parts. By optimizing the post-processing procedure, fully-dense glass parts with up to 2 cm 2 cross sectional area are achieved. The changes in optical properties during printing are leveraged for in situ metrology during printing, and the non-Newtonian nature of the glass-filled photoresin system to facilitate larger fabrication volumes via tiled projections. Printed structures are finally demonstrated for applications as MEMS components, optics, fluidics, and consumer products.
Abstract Long‐term in situ soil moisture monitoring inevitably requires sensors to be replaced. Ensuing discontinuities in the data record can be mitigated by intercalibration, however it is unclear how long the existing sensor needs to remain alongside the newly installed before there is enough overlapping data to generate a robust intercalibration. We used 154 pairs of established and newly installed sensors within the Marena, Oklahoma, In Situ Sensor Testbed to determine if there is a minimum overlap time that should be considered when planning upcoming replacements. Hourly observations of the existing sensor were linearly calibrated to those of the newly installed sensor with coefficients determined from overlap periods incremented by 30 days until a reference period of 2 years was reached. The resulting bias, root‐mean‐square error, and correlation coefficient for sensor pairs indicate that a minimum of 6 to 9 months of overlapping data are required to generate a successful intercalibration. Extending that to a full year before decommissioning the old sensor results in a stable intercalibration with higher confidence.
It is well known that both complex and dual numbers can be employed to obtain machine precision first-order derivatives; however, neither, on their own, can compute machine precision 2nd order derivatives. To address this limitation, it is demonstrated in this paper that combined dual-complex numbers can be used to compute machine precision 1st and 2nd order derivatives. The dual-complex approach is simpler than utilizing multicomplex or hyper-dual numbers as existing dual libraries can be used as is or easily augmented to accept complex numbers, and the complexity of developing, integrating, and deploying multicomplex or hyper-dual libraries is avoided. The efficacy of this approach is demonstrated for both univariate and multivariate functions. Finally, source code examples using the Python, Julia, and Mathematica languages are provided as supplemental material.
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