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The influence of the stacking of three atoms thick islands of Co on Ru(0001) is studied by spin-polarized low-energy electron microscopy (SPLEEM). It decreases by two orders of magnitude by changing the stacking sequence from fcc to hcp.
We present a method for the additive fabrication of planar magnetic nanoarrays with minimal surface roughness. Synthesis is accomplished by combining electron-beam lithography, used to generate nanometric patterned masks, with ion implantation in thin films. By implanting 56 Fe + ions, we are able to introduce magnetic functionality in a controlled manner into continuous Pd thin films, achieving 3D spatial resolution down to a few tens of nanometers. Our results demonstrate the application of this technique in fabricating square artificial spin ice lattices, which exhibit well-defined magnetization textures and interactions among the patterned magnetic elements.
Recent current density measurements with a low-beta electron beam (β=0.5-0.75) are strongly affected by electron scatter and Cherenkov limits. These invasive measurements are heavily influenced by the electron energy and the intercepting material properties: density, index of refraction, and atomic number. We evaluate various measurement methods, including x-ray scintillation and Cherenkov emission. To optimize the x-ray scintillation technique for this energy regime, metal foils of differing atomic number (Z) and thickness were placed upstream of a scintillation screen. We have selected Cherenkov emitters, based on a material refractive index, in order to differentiate the contributions from electron scatter and produced fluorescence, Cherenkov emission, and total internal reflection. The observed distributions for both approaches are verified through MCNP6®. Additionally, the simulations provide insight as to what physical processes dominate the measured distribution. We conclude by determining the limits and optimal measurement range for each measurement technique.
Mn-rich disordered rocksalt (DRX) cathode materials exhibit a phase transformation from a disordered to a partially disordered spinel-like structure (δ-phase) during electrochemical cycling. Here, in this computational study, we use charge-informed molecular dynamics with a fine-tuned CHGNet foundation potential to investigate the phase transformation in LixMn 0.8 Ti 0.1 O 1.9 F 0.1 . Our results indicate that transition metal migration occurs and reorders to form the spinel-like ordering in an FCC anion framework. The transformed structure contains a higher concentration of nontransition metal (0-TM) face-sharing channels, which are known to improve Li transport kinetics. Analysis of the Mn valence distribution suggests that the appearance of tetrahedral Mn 2+ is a consequence of spinel-like ordering, rather than the trigger for cation migration as previously suggested. Calculated equilibrium intercalation voltage profiles demonstrate that the δ-phase, unlike the ordered spinel, exhibits solid-solution signatures at low voltage. A higher Li capacity is obtained than in the DRX phase. This study provides atomic insights into solid-state phase transformation and its relation to experimental electrochemistry, highlighting the potential of machine-learning interatomic potentials for understanding complex oxide materials.
Using single-crystal neutron diffraction, we present a systematic investigation of the crystal structure and magnetism of the van der Waals topological insulators MnBi 2 Te 4 and MnBi 4 Te 7 , where rich topological quantum states have been recently predicted and observed. Structural refinements reveal that considerable Bi atoms occupied on the Mn sites in both materials, distinct from the previously reported antisite disorder. We show unambiguously that MnBi 2 Te 4 orders antiferromagnetically below 24 K, featured by a magnetic symmetry R I - 3 c , while MnBi 4 Te 7 is antiferromagnetic below 13 K with a magnetic space group P c - 3 c 1 . They both present antiferromagnetically coupled ferromagnetic layers with spins along the c axis. We put forward a stacking rule for the crystal structure of an infinitely adaptive series MnBi 2 n Te 3 n + 1 ( n ≥ 1 ) with a building unit of [ Bi 2 Te 3 ] . Overall, by comparing the magnetic properties between MnBi 2 Te 4 and MnBi 4 Te 7 , together with recent density-functional theory calculations, we concluded that a two-dimensional magnetism limit might be realized in the derivatives. Our work may promote theoretical studies of topological magnetic states in the series of MnBi 2 n Te 3 n + 1 .
The pursuit of efficient spin polarization in quaternary Heusler alloys with the general formula XX'YZ (where X, X', and Y are transition metals and Z is a p-block element) has been a subject of significant scientific interest. While previous studies showed that isoelectronic substitution of a 4d element in place of a 3d element in quaternary Heusler alloys improves the half-metallic ferromagnetic characteristics, our research here, on the quaternary Heusler alloy NiRuMnSn, reveals a strikingly different scenario. In this study, we present a detailed structural analysis of the material using x-ray absorption fine structure and neutron diffraction techniques which confirms the formation of a single-phase compound with 50:50 site disorder between Ni and Ru atoms at 4c and 4d sites. Contrary to expectations, our density functional theory calculations suggest a considerable decrease in spin polarization even in the ordered structure. Additionally, we report on the compound's exceptional behavior, displaying a rare reentrant spin-glass property below ~ 60 K, a unique and intriguing feature for quaternary Heusler-type compounds.
Here, we present a five-phase equation of state (EOS) for elemental gallium (Ga) that is developed using both experimental data and new theoretical predictions. Four experimentally observed solid phases (Ga-I, Ga-II, Ga-III, and Ga-IV) and one liquid phase are included. To improve our understanding of the thermal behavior of Ga and its phase boundaries under compression, we have performed ab initio density functional theory (DFT) free-energy calculations for the Ga-III and liquid phases, which enables us to determine the melt temperature to be 2214 ± 100 K at 110 GPa, extending significantly beyond the existing experimental melt data, which are limited to 25 GPa. In order to best describe the electron-thermal contribution, which dominates the liquid free energy at high temperatures, we have carried out averaged-atom-in-jellium DFT calculations to cover the entire temperature and density range of the EOS. The resulting multiphase Ga EOS is able to accurately reproduce a diverse variety of data, including known phase boundaries, the principal Hugoniot, low-pressure liquid isobars, and diamond-anvil-cell isotherm measurements at high pressures. It agrees more closely with key experimentally measured properties than other Ga EOS models targeted for high-pressure applications.
SF-22-156 Machine learning (ML) models and applications in materials design and discovery typically involve the use of feature representations or descriptors followed by a learning algorithm that maps them to user desired properties of interest. Most popular mathematical formulation-based descriptors are not unique across atomic environments and suffer from transferability issues across different application domains and/or material classes. The CEGANN code provides a unified interface to facilitate material characterization across materials across multiple scales (from atomic to mesoscale) and diverse classes of materials ranging from metals oxides, non-metals, and even hierarchical materials such as zeolites and semi ordered materials such as mesophases. CEGANN implements a Graph Attention Network (GAT) type convolution architecture. The details of network architecture can be found in the paper https://doi.org/10.48550/arXiv.2207.10168. The software comes with pretrained examples and dataset for the classification of the following representative systems: (1) Structure-level representation such as space group (2) Structural dimensionality (e.g., bulk, 2D, clusters etc.) (3) Grain boundary identification (4) Nucleation and growth of a zeolite polymorph (5) Characterization of binary mesophases and their phase transitions (6) Growth of ice. The code is written in python programming language.
The theory of the g tensor in one-electron systems is briefly reviewed and calculations are performed in several ways for the hydrogen molecular ion in order to test approximations which must be made for larger systems. Approximate ground state wavefunctions are determined variationally. The first-order wavefunction with respect to the orbit-field perturbation is calculated, and the second-order g tensor is determined. The results of the various approximate calculations are compared and discussed. It is found that the linear combination of atomic orbitals method is rather poor and that two center integrals cannot be neglected.
A biased random walk, Monte Carlo procedure is used to study the melting transition in small clusters of N atoms. Results show an abrupt change in physical properties near melting, but there is no evidence that the transition is either first or second order; rather the transition is more gradual.
Recent experiments using scanning tunneling microscopy show evidence for the formation of surface alloys of otherwise immiscible metals. Such is the case for Au deposited in Ni(11), where experiments by Pleth Nielsen et al. indicate that at low Au coverage (less than 0.5 ML), Au atoms replace Ni atoms in the surface layer forming a surface alloy while the Ni atoms form islands on the surface. In this work, we present results of a theoretical modeling of this phenomenon using the recently developed BFS method for alloys. We provide results of an extensive analysis of the growth process which strongly support the conclusions drawn from the experiment; at very low coverages, there is tendency for dimer formation on the overlayer, which later exchange positions with Ni atoms in the surface layer, thus accounting for the large number of substituted dimers. Ni island formations as well as other alternative short range order patterns are discussed.
We present wavelengths and absolute intensities for 243 emission lines from a single active region observed by the Solar Extreme Ultraviolet (EUV) Rocket Telescope and Spectrograph (SERTS) on 1989 May 5. For this catalog, the imaged spectra have been spatially averaged over a field of view 7 sec x 276 sec cutting through the center of AR5464 at S18 W45. Wavelength coverage is 170-450 A with a spectral resolution approaching 10,000. Most of the line positions are determined to 5 mA or better, representing the highest accuracy yet obtained for solar wavelengths throughout this spectral interval. The relative photometric calibration of the instrument is good to +/- 20% over its first-order range, and has been placed onto an absolute scale that should be correct to within a factor less than 2. Where known, identifications, atomic transitions and formation temperatures are also given. The identified lines arise from temperatures that cover the range log T greater than or equal to 4.7 and less than or equal to 6.8, providing information about the Sun's corona and upper transition region. Upper limits to the intensity of any emission line not included here can be estimated from the measured instrumental sensitivity. This averaged EUV spectrum should prove useful as a source of accurate wavelengths and intensities for emission characteristic of the high-temperature plasma associated with a solar active region and small subflare.
Understanding and controlling the formation kinetics of varieties of crystal imperfections such as point defects, non uniform distribution of doping atoms, and impurity atoms in growing crystals are very important. Theoretical (numerical) modeling of the crystal growth process is an essential step to achieving these objectives. In order to obtain reliable modeling results, input parameters, i.e. various thermophysical parameters, must be accurate. The importance of accurate thermophysical properties of semiconductors in crystal growth cannot be overly emphasized. The total hemispherical emissivity, for instance, has a dramatic impact on the thermal environment. It determines the radiative emission from the surface of the melt which determines to a large extent the profile of the solidified crystal. In order to understand the convection and the turbulence in a melt, viscosity becomes an important parameter. The liquid surface tension determines the shape of the liquid-atmosphere interface near the solid-liquid-atmosphere triple point. Currently used values for these parameters are rather inaccurate, and this program intends to provide more reliable measurements of these thermophysical properties. Thus, the objective of this program is in the accurate measurements of various thermophysical properties which can be reliably used in the modeling of various crystal growth processes. In this program, thermophysical properties of molten semiconductors, such as Si, Ge, Si-Ge, and InSb will be measured as a function of temperature using the High Temperature Electrostatic Levitator at JPL. Each material will be doped by different kinds of impurities at various doping levels. Thermophysical properties which will be measured include: density, thermal expansion coefficient, surface tension, viscosity, specific heat, hemispherical total emissivity, and perhaps electrical and thermal conductivities. Many molten semiconductors are chemically reactive with crucibles. As a result, these dispersed impurities in the melts tend to substantially modify the properties of pure semiconductors. Sample levitation done in a vacuum clearly helps maintain the sample purity. However, in the 1-g environment, all gravity caused effects such as convection, sedimentation and buoyancy are still present in the sample. In addition, large forces needed to levitate a sample in the presence of the gravity can cause additional flows in the melt. The use of the High Temperature Electrostatic Levitator (HTESL) for the present research is a recent development and little is known about the flows induced by the electrostatic forces. In this ground base program, we will define the limits of HTESL technology as various thermophysical properties of molten semiconductors are measured.
Geometrical structures and energetic properties for different tautomers of adenine are calculated in this study, using multi-configurational wave functions. Both the ground and the lowest singlet excited state potential energy surfaces are studied. Four tautomeric forms are considered, and their energetic order is found to be different on the ground and the excited state potential energy surfaces. Minimum energy reaction paths are obtained for hydrogen atom transfer (tautomerization) reactions in the ground and the lowest excited electronic states. It is found that the barrier heights and the shapes of the reaction paths are different for the ground and the excited electronic states, suggesting that the probability of such tautomerization reaction is higher on the excited state potential energy surface. This tautomerization process should become possible in the presence of water or other polar solvent molecules and should play an important role in the photochemistry of adenine.
Thanks to the mid-IR sensitivities of the ISO and IRTS orbiting spectrometers it is now possible to search the diffuse interstellar medium for heretofore inaccessible molecular emission. In view of the recent strong case for the presence of C(7-) (Kirkwood et al. 1998, Tulej et al. 1998),and the fact that carbon chains possess prominent infrared active modes in a very clean portion of the interstellar spectrum, we have analyzed the IRTS spectrum of the diffuse interstellar medium for the infrared signatures of these species. Theoretical and experimental infrared band frequencies and absolute intensities of many different carbon chain species are presented. These include cyanopolyynes, neutral and anionic linear carbon molecules, and neutral and ionized, even-numbered, hydrogenated carbon chains. We show that--as a family--these species have abundances in the diffuse ISM on the order of 10(-10) with respect to hydrogen, values consistent with their abundances in dense molecular clouds. Assuming an average length of 10 C atoms per C-chain implies that roughly a millionth of the cosmically available carbon is in the form of carbon chains and that carbon chains can account for a few percent of the visible to near-IR diffuse interstellar band (DIB) total equivalent width (not DIB number).
Absolute rate data and product branching ratios for the reactions Cl + HO2 to HCl + O2 (k1a) and Cl + HO2 to OH + ClO (k1b) have been measured from 226 to 336 K at a total pressure of 1 Torr of helium using the discharge flow resonance fluorescence technique coupled with infrared diode laser spectroscopy. For kinetic measurements, pseudo-first-order conditions were used with both reagents in excess in separate experiments. HO2 was produced by two methods: through the termolecular reaction of H atoms with O2 and also by the reaction of F atoms with H2O2. Cl atoms were produced by a microwave discharge of Cl2 in He. HO2 radicals were converted to OH radicals prior to detection by resonance fluorescence at 308 nm. Cl atoms were detected directly at 138 nm also by resonance fluorescence. Measurement of the consumption of HO2 in excess Cl yielded k1a and measurement of the consumption of Cl in excess HO2 yielded the total rate coefficient, k1. Values of k1a and k1 derived from kinetic experiments expressed in Arrhenius form are (1.6 +/- 0.2) x 10-11 exp[(249 +/- 34)/T] and (2.8 +/- 0.1) x 10-11 exp[(123 +/- 15)/T] cm3 molecule-1 s-1, respectively. As the expression for k1 is only weakly temperature dependent, we report a temperature-independent value of k1 = (4.5 +/- 0.4) x 10-11 cm3 molecule-1 s-1. Additionally, an Arrhenius expression for k1b can also be derived: k1b = (7.7 +/- 0.8) x 10-11 exp[-(708 +/- 29)/T] cm3 molecule-1 s-1. These expressions for k1a and k1b are valid for 226 K T 336 and 256 K T 296 K, respectively. The cited errors are at the level of a single standard deviation. For the product measurements, an excess of Cl was added to known concentrations of HO2 and the reaction was allowed to reach completion. HCl product concentrations were determined by IR absorption yielding the ratio k1a/k1 over the temperature range 236 K T 296 K. OH product concentrations were determined by resonance fluorescence giving rise to the ratio k1b/k1 over the temperature range 226 K T 336 K. Both of these ratios were subsequently converted to absolute numbers. Values of k1a and k1b from the product experiments expressed in Arrhenius form are (1.5 +/- 0.1) x 10-11 exp[(222 +/- 17)/T] and (10.6 +/- 1.5) x 10-11 exp[-(733 +/- 41)/T] cm3 molecule-1 s-1, respectively. These expressions for k1a and k1b are valid for 256 K T 296 and 226 K T 336 K, respectively. A combination of the kinetic and product data results in the following Arrhenius expressions for k1a and k1b of (1.4 +/- 0.3) x 10-11 exp[(269 +/- 58)/T] and (12.7 +/- 4.1) x 10-11 exp[-(801 +/- 94)/T] cm3 molecule-1 s-1, respectively. Numerical simulations were used to check for interferences from secondary chemistry in both the kinetic and product experiments and also to quantify the losses incurred during the conversion process HO2 to OH for detection purposes.
Forward modeling of optical spectra with absolute radiometric intensities requires knowledge of the individual transition probabilities for every transition in the spectrum. In many cases, these transition probabilities, or Einstein A-coefficients, quickly become practically impossible to obtain through either theoretical or experimental methods. Complicated electronic orbitals with higher order effects will reduce the accuracy of theoretical models. Experimental measurements can be prohibitively expensive and are rarely comprehensive due to physical constraints and sheer volume of required measurements. Due to these limitations, spectral predictions for many element transitions are not attainable. In this work, we investigate the efficacy of using machine learning models, specifically fully connected neural networks (FCNN), to predict Einstein A-coefficients using data from the NIST Atomic Spectra Database. For simple elements where closed form quantum calculations are possible, the data-driven modeling workflow performs well but can still have lower precision than theoretical calculations. For more complicated nuclei, deep learning emerged more comparable to theoretical predictions, such as Hartree–Fock. Unlike experiment or theory, the deep learning approach scales favorably with the number of transitions in a spectrum, especially if the transition probabilities are distributed across a wide range of values. It is also capable of being trained on both theoretical and experimental values simultaneously. In addition, the model performance improves when training on multiple elements prior to testing. The scalability of the machine learning approach makes it a potentially promising technique for estimating transition probabilities in previously inaccessible regions of the spectral and thermal domains on a significantly reduced timeline.
A widespread belief persists that the Boys–Bernardi function counterpoise (CP) procedure “overcorrects” supramolecular interaction energies for the effects of basis-set superposition error. To the extent that this is true for correlated wave function methods, it is usually an artifact of low-quality basis sets. The question has not been considered systematically in the context of density functional theory, however, where basis-set convergence is generally less problematic. We present a systematic assessment of the CP procedure for a representative set of functionals and basis sets, considering both benchmark data sets of small dimers and larger supramolecular complexes. The latter include layered composite polymers with ~150 atoms and ligand–protein models with ~300 atoms. Provided that CP correction is used, we find that intermolecular interaction energies of nearly complete-basis quality can be obtained using only double-ζ basis sets. Furthermore, this is less expensive as compared to triple-ζ basis sets without CP correction. CP-corrected interaction energies are less sensitive to the presence of diffuse basis functions as compared to uncorrected energies, which is important because diffuse functions are expensive and often numerically problematic for large systems. Our results upend the conventional wisdom that CP “overcorrects” for basis-set incompleteness. In small basis sets, CP correction is mandatory in order to demonstrate that the results do not rest on error cancellation.