Neighbor Configurations Research Articles

A two-dimensional cellular automaton-finite difference (CA-FD) model for lithium dendrite simulation

The non-uniform lithium deposition behavior on the negative electrode during the charging process in lithium metal batteries leads to serious safety hazards in practical applications. The phase field (PF) method is the most commonly used to simulate the evolution of the microscopic morphology of lithium dendrite, which is computationally expensive due to the coupled partial differential equations (PDEs). Compared to PF, cellular automaton (CA) can efficiently process the evolution of solid-liquid interface with the neighbor configuration and interaction rules. In this paper, a two-dimensional cellular automaton-finite difference (CA-FD) model based on the decentered square algorithm (DSCA) is established. In this model, the growth of the moving solid-phase interface is described by CA, and the distribution of concentration and electric potential is solved by FD, therefore achieving a higher computation efficiency. During the modeling process, it has been verified that DSCA is more favorable to simulate the preferential growth of lithium dendrite tips than Neumann neighbors and Moore neighbors. Based on this model, the effect of different operating conditions of the lithium metal battery on the growth of lithium dendrites is investigated. The simulation results indicate that an increase in either the interfacial overpotential or the exchange current density accelerates the growth of lithium dendrites, in addition, more side branches are generated under higher overpotential. Therefore, low-rate charging mode is recommended in lithium metal battery to inhibit the growth of lithium dendrite.

Defect Structures of Rare Earth-Doped Lutetium Oxide and Impacts of Li Co-Dopant

Defect complexes consisting of point defects induced by the doping of rare earth elements (Nd, Er) into lutetium oxide (Lu2O3) host were investigated with respect to defect formation energies and defect configurations using atomistic simulations with General Utility Lattice Program (GULP). The site preferences of the substitutional point defects of the dopants and the occupation between the two available cationic sites, the 8b and 24d sites, were analyzed. Additionally, the impacts of Li on the doping of rare earth elements into Lu2O3 were revealed from the viewpoints of energy and structure. Dopant pairs in the nearest neighbor configurations (8b + 8b), (8b + 24d), and (24d + 24d) were considered. The results contribute to the understanding of structures of defects in rare earth-doped Lu2O3.

Atom counting based on Voronoi averaged STEM intensities using a crosstalk correction scheme

If quantitative scanning transmission electron microscopy is used for very precise thickness measurements with atomic resolution, it is commonly referred to as »atom counting«. Due to scattering and the finite probe extent the signal recorded in one atomic column is dependent not only on its own height but also on the height of its neighbours. Especially for thicker specimens this crosstalk effect can have significant impact on the measured intensity. If it is not appropriately accounted for in the evaluation, it can result in a deterioration of accuracy that impedes the possibility of actual atom counting. However, as the number of possible neighbour configurations can be excessively large, a comprehensive consideration of all in the evaluation reference is neigh impossible. This work proposes a method that allows for the a-posteriori reduction of crosstalk during the evaluation by algebraic means. Based on a parametric model, which is described in detail in the article, the crosstalk is expressed by an invertible matrix. Applying the inverted matrix to the measurement yields crosstalk corrected intensity values with very little computational effort. These can subsequently be evaluated by direct comparison to simple reference data. The working principle of the method is presented on the example of crystalline gold. The crosstalk parametrisation is found by fitting a model to sets of specifically created multislice simulations. The parameters are given for both aberration corrected and uncorrected STEM. Subsequently the abilities and potential of the technique are assessed in simulative studies on multiple model systems including gold nanoparticles. Overall a significant and robust improvement of the attainable precision can be demonstrated making the proposed method a promising tool for reference-based atom counting.

Effect of chemical disorder on the magnetic anisotropy in L10 FeNi from first-principles calculations

We use first-principles calculations to investigate how deviations from perfect chemical order affect the magnetocrystalline anisotropy energy (MAE) in $L{1}_{0}$ FeNi. We first analyze the local chemical environment of the Fe atoms in various partially ordered configurations, using the orbital magnetic moment anisotropy (OMA) as proxy for a local contribution to the MAE. We are able to identify a specific nearest neighbor configuration and use this ``favorable environment'' to successfully design various structures with MAE higher than the perfectly ordered system. However, a systematic analysis of the correlation between local environment and OMA using smooth overlap of atomic positions indicates only a partial correlation, which exists only if the deviation from full chemical order is not too large, whereas in general no such correlation can be identified even using up to third nearest neighbors. Guided by the observation that the identified favorable environment implies an Fe-rich composition, we investigate the effect of randomly inserting additional Fe into the nominal Ni planes of the perfectly ordered structure. We find that the MAE increases with Fe content, at least up to 62.5% Fe. Thus, our paper shows that the perfectly ordered case is not the one with highest MAE and that an increased MAE can be obtained for slightly Fe-rich compositions.

Optoelectrical analysis of TCO+Silicon oxide double layers at the front and rear side of silicon heterojunction solar cells

Silicon Heterojunction has become a promising technology to substitute passivated emitter and rear contact (PERC) solar cells in pursuance of lower levelized cost of electricity through high efficiency devices. While high open circuit voltages and fill factors are reached, current loss related to the front and rear contacts, such as the transparent conductive oxide (TCO) layers is still a limiting factor to come closer to the efficiency limit of silicon based solar cells. Furthermore, reducing indium consumption for the TCO has become mandatory to push silicon heterojunction technology towards a terawatt scale production due to material scarcity and costs. To address these issues dielectric layers, such as silicon dioxide or nitride cappings are implemented to reduce TCO thicknesses both diminishing parasitic absorption and material consumption. However, reducing the TCO thickness comes in cost of resistive losses. Furthermore, the TCO properties do vary with thickness and neighboring layer configuration altering the optimization frame of the device. In this paper we present a detailed analysis to quantify the optoelectrical losses trade-off associated to the TCO thickness reduction in such layer stacks. Through the analysis we show and explain why experimental bifacial cells with 20 nm front and rear TCO perform at a similar level to reference cells with 75 nm under front and rear illumination reaching efficiency close to 24% at 92% bifaciality. We present as well a simple interconnection method via screen printing metallization to implement a thin TCO/silicon dioxide/silver reflector enhancing current density from 39.6 to 40.4 mA/cm 2 without compromising resistive losses resulting in a 0.2% absolute solar cell efficiency increase from a bifacial design (23.5–23.7%). Finally, following this approach we present a certified champion cell with an efficiency of 24.6%. • Analysis of TCO variations on electron and hole contact for Si heterojunction solar cells by simulations and experiments. • Both sides 20 nm TCO + SiO 2 layer stack SHJ solar cells with 23.9% efficiency. • Champion solar cell with rear 20 nm TCO + SiO 2 layer stack and silver rear reflector with 24.6% efficiency.

Kinetic Equations of Physicochemical Processes with Allowance for Multi-Particle Effects in the Lattice Gas Model

A way of deriving kinetic equations of physicochemical processes in dense phases is developed on the basis of the discrete–continuous description of the spatial distribution of components in the lattice gas model (LGM), with allowance for multi-particle effects. The emergence of multi-particle effects is associated with the simultaneous influence of all neighbors on the rate of the elementary stage with the participation of a given particle. They include multi-particle potentials of interaction, including quantum–chemical energy calculations, the effect the configurations of neighboring molecules have on the internal motion of the central particle, and the effects of the indirect correlation of interacting particles that occurs for any potential of pair interaction, assuming the internal motions of particles do not depend on the local configurations of neighbors. Multi-particle effects take models beyond the quasi-chemical approximation, which reflects direct correlations of interacting particles through pair distribution functions, and require the use of correlation functions for a larger number of particles in describing their kinetics. The rates of elementary one- and two-node stages are calculated within the theory of absolute rates of reactions in non-ideal reaction systems. Ways of calculating approximate rates of the elementary stages of mono- and bimolecular processes are discussed, along with the possibilities of generalizing the derived equations.

A DFT+U study of site dependent Fe-doped TiO2 diluted magnetic semiconductor material: Room-temperature ferromagnetism and improved semiconducting properties

This article reports the crystal structure, impurity formation energy, electronic property, magnetic property, and dopant configuration site dependence of ferromagnetic temperature Tc of anatase (Ti15FeO32, Ti14Fe2O32, and Ti13Fe3O32) by first-principles calculations based on density functional theory (DFT) with Hubbard onsite correction (DFT+U). The estimated formation energy validated the structural stability of the Fe-doped TiO2 with 2.08% (Ti15FeO32), 4.17% (Ti14Fe2O32), and 6.25% (Ti13Fe3O32) concentrations at the Ti sites. The electronic structure analysis reveals that the bandgap in the doped system changed from a wide bandgap of 3.23 eV (pristine TiO2) to slightly lower bandgaps of 3.13, 3.08, and 3.04 eV with Fe concentrations of 2.08%, 4.17%, and 6.25%, respectively. The calculated partial density of states also show the hybridization of O with 2p- and Fe 3d-orbitals near the conduction band minimum and generate the impurity energy level reducing the bandgap. Furthermore, the estimated Curie temperature (Tc) varied depending on the Fe–Fe interactions, the concentration of the Fe dopants, and doping sites. For instance, Tc is calculated to be 343.57 K for 2.08% Fe at the symmetric point of the crystal while estimated to be 323.84 and 393.297 K for 4.17% at the nearest neighbor and the next-nearest neighbor configurations. Due to the increase of the Fe concentration to 6.25%, the calculated Tc monotonically improved to 342.5 and 513.174 K at the nearest neighbor and the next-nearest neighbor of the Fe-site, respectively. These indicate that all the calculated findings estimate the ferromagnetic transition temperature Tc to above room temperature. Moreover, the system’s total magnetization reveals the augmentation of a number of unpaired electrons as a result of rise in oxygen vacancies and, hence, there could be more holes when the Fe content gets higher, perhaps generating more bound magnetic polarons that favor the critical temperature, Tc.

Effect of the number of defect particles on the structure and dispersion relation of a two-dimensional dust lattice system

The effect of the number of defect particles on the structure and dispersion relations of a two-dimensional (2D) dust lattice is studied by molecular dynamics (MD) simulation. The dust lattice structures are characterized by particle distribution, nearest neighbor configuration and pair correlation function. The current autocorrelation function, the dispersion relation and sound speed are used to represent the wave properties. The wave propagation of the dust lattice closely relates to the lattice structure. It shows that the number of defect particles can affect the dust lattice local structure and then affect the dispersion relations of waves propagating in it. The presence of defect particles has a greater effect on the transverse waves than on the longitudinal waves of the dust lattice. The appropriate number of defect particles can weaken the anisotropy property of the lattice.

Determination of Vacancy Formation Energies in Binary UZr Alloys Using Special Quasirandom Structure Methods

The use of predictive models to examine defect production and migration in metallic systems requires a thorough understanding of the energetics of defect formation and migration. In fully miscible alloys, atomistic properties will all have a range of values that are heavily dependent on local atomic configurations. In this work we have used the atomistic simulation tool Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) to investigate the impact of first nearest neighbor configuration on vacancy formation energies at 0 K in γ-U-Zr alloys of varying Zr concentrations. The properties of randomly generated alloy microstructures were also compared with those produced as special quasi-random structures (SQS) using the “mcsqs” code within the Alloy Theoretic Automated Toolkit. Results have confirmed that local configuration can have a significant impact on measured properties and must be considered when characterizing miscible alloy systems. Results also indicated that the generation method of the random structure (i.e., via random species assignment or a method of enforced randomness) does not result in a measurable difference in average vacancy formation energies in miscible U-Zr systems.

A novel stochastic optimization method to efficiently synthesize large‐scale nonsharp distillation systems

AbstractThis study presents a novel stochastic optimization method for the efficient synthesis of large‐scale nonsharp distillation systems, where heat integration and thermal coupling can be involved simultaneously. A new binary tree encoding method was developed to represent distillation sequences with no limits on the number of middle components in nonsharp splits to ensure a complete solution space. Thermally coupled structures were defined by 0–1 binary variables. Evolutionary rules were developed to generate neighboring distillation configurations randomly. Finally, an optimization framework was proposed, where simulated annealing (SA) algorithm was used to optimize distillation configurations; for a certain distillation configuration randomly generated by SA, its continuous variables were optimized using particle swarm optimization algorithm. Four cases—including the synthesis of six‐ and seven‐component nonsharp heat integrated and thermally coupled distillation sequences—were studied to demonstrate that the proposed method was efficient and could obtain optimal and valuable suboptimal solutions with high probabilities.

Effect of germanium auto-diffusion on the bond lengths of Ga and P atoms in GaP/Ge(111) investigated by using X-ray absorption spectroscopy.

The germanium auto-diffusion effects on the inter-atomic distance between the nearest neighbors of the Ga atom in GaP epilayers are investigated using high-resolution X-ray diffraction (HRXRD) and X-ray absorption spectroscopy. The GaP layers grown on Ge (111) are structurally coherent and relaxed but they show the presence of residual strain which is attributed to the auto-diffusion of Ge from the results of secondary ion mass spectrometry and electrochemical capacitance voltage measurements. Subsequently, the inter-atomic distances between the nearest neighbors of Ga atom in GaP are determined from X-ray absorption fine-structure spectra performed at the Ga K-edge. The estimated local bond lengths of Ga with its first and second nearest neighbors show asymmetric variation for the in-plane and out-of-plane direction of GaP/Ge(111). The magnitude and direction of in-plane and out-of-plane microscopic residual strain present in the GaP/Ge are calculated from the difference in bond lengths which explains the presence of macroscopic residual tensile strain estimated from HRXRD. Modified nearest neighbor configurations of Ga in the auto-diffused GaP epilayer are proposed for new possibilities within the GaP/Ge hetero-structure, such as the conversion from indirect to direct band structures and engineering the tensile strain quantum dot structures on (111) surfaces.

Design of solute clustering during thermomechanical processing of AA6016 Al–Mg–Si alloy

Solute clustering is a technologically important microstructural process in Al alloys. Exerting control over this process to enhance the alloy properties and reduce the energy costs of production is a major scientific and technological focus, with automotive sheet applications serving as a key driver. In this work, we detail changes in the state of clustering arising from the insertion of a thermomechanical pre-ageing process, via a coil-cooling step in a commercial production line, immediately after solution treatment. This pre-ageing step effectively mitigates the negative effects of the natural ageing on the mechanical properties that would otherwise occur after solution treatment and ahead of the final paint-bake step. Our work was focussed on a short duration/low temperature single-step pre-ageing process on a Cu-lean grade of AA6016. Using a combination of atom probe tomography and first principles density functional theory simulations, we are able to reveal and explain the atomic-scale microstructure arising from this thermomechanical process. Mg–Si co-clusters ≥ 20 solute atoms were found responsible for the excellent properties in the material exposed to the pre-ageing plus paint-baking process. Our simulations revealed that vacancies can effectively stabilise single-species Si clusters enabling them to attract further solute and serving as a pathway to formation of the larger Mg–Si co-clusters that are so beneficial to alloy properties. Our simulations also revealed that the nearest neighbour configurations are a critical aspect to the stability of the clusters.

Distributions of Hyper-Local Configuration Elements to Characterize, Compare, and Assess Landscape-Level Spatial Patterns.

Even with considerable attention in recent decades, measuring and working with patterns remains a complex task due to the underlying dynamic processes that form these patterns, the influence of scales, and the many further implications stemming from their representation. This work scrutinizes binary classes mapped onto regular grids and counts the relative frequencies of all first-order configuration components and then converts these measurements into empirical probabilities of occurrence for either of the two landscape classes. The approach takes into consideration configuration explicitly and composition implicitly (in a common framework), while the construction of a frequency distribution provides a generic model of landscape structure that can be used to simulate structurally similar landscapes or to compare divergence from other landscapes. The technique is first tested on simulated data to characterize a continuum of landscapes across a range of spatial autocorrelations and relative compositions. Subsequent assessments of boundary prominence are explored, where outcomes are known a priori, to demonstrate the utility of this novel method. For a binary map on a regular grid, there are 32 possible configurations of first-order orthogonal neighbours. The goal is to develop a workflow that permits patterns to be characterized in this way and to offer an approach that identifies how relatively divergent observed patterns are, using the well-known Kullback–Leibler divergence.

Using non-homogeneous point process statistics to find multi-species event clusters in an implanted semiconductor

The Poisson distribution of event-to--nearest-event radial distances is well known for homogeneous processes that do not depend on location or time. Here we investigate the case of a non-homogeneous point process where the event probability (and hence the neighbour configuration) depends on location within the event space. The particular non-homogeneous scenario of interest to us is ion implantation into a semiconductor for the purposes of studying interactions between the implanted impurities. We calculate the probability of a simple cluster based on nearest neighbour distances, and specialise to a particular two-species cluster of interest for qubit gates. We show that if the two species are implanted at different depths there is a maximum in the cluster probability and an optimum density profile.

Re effects in model Ni-based superalloys investigated with first-principles calculations and atom probe tomography**Project supported by the National Key Research and Development Program of China (Grant No. 2017YFB0701503).

The phase partition and site preference of Re atoms in a ternary Ni–Al–Re model alloy, including the electronic structure of different Re configurations, are investigated with first-principles calculations and atom probe tomography. The Re distribution of single, nearest neighbor (NN), next-nearest neighbor (NNN), and cluster configurations are respectively designed in the models with γ and γ′ phases. The results show that the Re atoms tend to entering γ′ phase and the Re atoms prefer to occupy the Al sites in γ′ phase. The Re cluster with a combination of NN and NNN Re–Re pair configuration is not preferred than the isolated Re atom in the Ni-based superalloys, and the configuration with isolated Re atom is more preferred in the system. Especially, the electronic states are analyzed and the energetic parameters are calculated. The electronic structure analyses show there exists strong Ni–Re electronic interaction and it is mainly contributed by the d–d hybridization. The characteristic features of the electronic states of the Re doping effects are also given. It is also found that Re atoms prefer the Al sites in γ′ side at the interface. The density of states at or near the Fermi level and the d–d hybridizations of NN Ni–Re are found to be important in the systems.

Oxygen Reduction Reactions on Single‐ or Few‐Atom Discrete Active Sites for Heterogeneous Catalysis

AbstractThe oxygen reduction reaction (ORR) is of great importance in energy‐converting processes such as fuel cells and in metal–air batteries and is vital to facilitate the transition toward a nonfossil dependent society. The ORR has been associated with expensive noble metal catalysts that facilitate the O2 adsorption, dissociation, and subsequent electron transfer. Single‐ or few‐atom motifs based on earth‐abundant transition metals, such as Fe, Co, and Mo, combined with nonmetallic elements, such as P, S, and N, embedded in a carbon‐based matrix represent one of the most promising alternatives. Often these are referred to as single atom catalysts; however, the coordination number of the metal atom as well as the type and nearest neighbor configuration has a strong influence on the function of the active sites, and a more adequate term to describe them is metal‐coordinated motifs. Despite intense research, their function and catalytic mechanism still puzzle researchers. They are not molecular systems with discrete energy states; neither can they fully be described by theories that are adapted for heterogeneous bulk catalysts. Here, recent results on single‐ and few‐atom electrocatalyst motifs are reviewed with an emphasis on reports discussing the function and the mechanism of the active sites.

Grain Boundaries and Phases Identification of Metallographic Images by a Normalized Sobel Operation and the Edge Thinning Process for Further Numerical Simulation

The recognitions of phases and precise grain boundaries based on metallographic images are useful for conducting micromechanical simulations, such as finite element analysis and peridynamics. In this work, those processes are automatized by using a Sobel operator for identifying edges, which is normalized by different proposed Gaussian filters (on intensity, rugosity, or both). After that, a threshold is used to discretize the edges. Different neighboring pixel configurations, sensitive to edge intensity, are proposed for thinning and cleaning the discretized edges, and hence, grain boundaries with a one-pixel thickness are obtained. Then, the phase is selected by averaging color of each delimited grain. Finally, the precision on the phase recognition was found to increase from 75.61 to 83.6% for the unmodified and the normalized Sobel operator, respectively.

Reverse-nearest neighborhood based oversampling for imbalanced, multi-label datasets

In this article, we present a novel reverse-nearest neighborhood based oversampling scheme for the imbalanced labels of a multi-label dataset. Reverse nearest neighborhood of a query point includes all those points which contain the query point as one of their neighbor. It facilitates us to identify an adaptive number of neighbors (according to the density and distribution of points) instead of a fixed number of neighbors. We add label-specific synthetic minority instances in the reverse nearest neighborhood of the minority points of each label. Reverse nearest neighbor configuration also detects the singular minority points, which we avoid as seed points in the oversampling phase. On the oversampled data of each label, we train and invoke a Linear Support Vector Machine to complete the learning and testing. Results of the proposed method against comparing methods on class-imbalance focused metrics indicates its competence in handling differently imbalanced multi-label datasets.

Strong Interplay between Sodium and Oxygen in Kesterite Absorbers: Complex Formation, Incorporation, and Tailoring Depth Distributions

AbstractSodium and oxygen are prevalent impurities in kesterite solar cells. Both elements are known to strongly impact performance of the kesterite devices and can be connected to efficiency improvements seen after heat treatments. The sodium distribution in the kesterite absorber is commonly reported, whereas the oxygen distribution has received less attention. Here, a direct relationship between sodium and oxygen in kesterite absorbers is established using secondary ion mass spectrometry and explained by defect analyses within the density functional theory. The calculations reveal a binding energy of 0.76 eV between the substitutional defects NaCu and OS in the nearest neighbor configuration, indicating an abundance of NaO complexes in kesterite absorbers at relevant temperatures. Oxygen incorporation is studied by introducing isotopic 18O at different stages of the Cu2ZnSnS4/Mo/soda‐lime glass baseline processing. It is observed that oxygen from the Mo back contact and contaminations during the sulfurization are primary contributors to the oxygen distribution. Indeed, unintentional oxygen incorporation leads to immobilization of sodium. This results in a strong correlation between sodium and oxygen, in excellent agreement with the theoretical calculations. Consequently, oxygen availability should be monitored to optimize postdeposition heat treatments to control impurities in kesterite absorbers and ultimately, the solar cell efficiency.

On Ontological Alternatives to Bohmian Mechanics.

The article describes an interpretation of the mathematical formalism of standard quantum mechanics in terms of relations. In particular, the wave function is interpreted as a complex-valued relation between an entity (often called “particle”) and a second entity x (often called “spatial point”). Such complex-valued relations can also be formulated for classical physical systems. Entanglement is interpreted as a relation between two entities (particles or properties of particles). Such relations define the concept of “being next to each other”, which implies that entangled entities are close to each other, even though they might appear to be far away with respect to a classical background space. However, when space is also considered to be a network of relations (of which the classical background space is a large-scale continuum limit), such nearest neighbor configurations are possible. The measurement problem is discussed from the perspective of this interpretation. It should be emphasized that this interpretation is not meant to be a serious attempt to describe the ontology of our world, but its purpose is to make it obvious that, besides Bohmian mechanics, presumably many other ontological interpretations of quantum theory exist.