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At least 343 records · Page 19

Validation of RANS Models for Predicting Bypass Flow in Prismatic VHTRs

In prismatic Very-High Temperature Reactors (VHTRs), gaps occur between neighboring fuel assemblies referred to as bypass gaps. This work aims to measure the flow distribution between the bypass gaps between neighboring assemblies and the coolant channels within the assemblies. Computational fluid dynamics (CFD) was done using Reynolds-Averaged Navier Stokes (RANS) modeling in STAR-CCM+ to assess the ability of RANS models to accurately capture this phenomena. The RANS results were compared to experimental worked performed by Seoul National University (SNU) and Korea Atomic Energy Research Institute (KAERI) for validation. The CFD results showed good comparison with the experimental data available from SNU and flow split was characterized for multiple configurations, inlet mass flow rates, and bypass gap sizes.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Simulations of Bypass Flow in Prismatic VHTRs

In prismatic Very-High Temperature Reactors (VHTRs), gaps occur between neighboring fuel assemblies referred to as bypass gaps. This work aims to measure the flow distribution between the bypass gaps between neighboring assemblies and the coolant channels within the assemblies. Computational fluid dynamics (CFD) was done using Reynolds-Averaged Navier Stokes (RANS) modeling in STAR-CCM+ to assess the ability of RANS models to accurately capture this phenomena. The RANS results were compared to experimental worked performed by Seoul National University (SNU) and Korea Atomic Energy Research Institute (KAERI) for validation. The CFD results showed good comparison with the experimental data available from SNU and flow split was characterized for multiple configurations, inlet mass flow rates, and bypass gap sizes.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials

Atomic disorder can strongly influence material properties such as charge transport, optical response, and catalytic activity. However, efficiently modeling these disorder effects remains challenging for first-principles methods due to the cost of sampling large configurational spaces and computing complex physical quantities. Recent advances of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. In this work, we present a general machine-learning-assisted computational framework that integrates equivariant GNNs with Monte Carlo simulations to compute the thermodynamic and ensemble-averaged functional properties of disordered materials. Using the surface-termination-disordered MXene monolayer Ti 3 C 2 T 2–x as a representative system, we find that electrical conductivity exhibits an emergent peak near the order–disorder phase transition temperature due to the interplay between electron scattering and doping. In contrast, optical conductivity remains largely insensitive to local atomic disorder and reflects the global surface chemical composition. These results highlight the role of atomic disorder in affecting material properties and demonstrate the potential of our approach for statistically modeling disorder effects in a wide range of materials such as high-entropy alloys and spin liquids.

MXene↗

Influence of Al location on formation of silver clusters in mordenite

Formation of zeolite supported Ag 0 clusters depends on a combination of thermodynamically stable atomic configurations, charge balance considerations, and mobility of species on the surface and within pores. Periodic density functional theory (DFT) calculations were performed to evaluate how the location of Al in the mordenite (MOR) framework and humidity control Ag 0 nanocluster formation. Four Al framework sites were studied (T1-T4) and the Al positions in the framework were identified by the shifts in the differential Al…Al pair distribution function (PDF). Furthermore, structural information about the Ag 0 nanoclusters, such as dangling bonds, can be identified by Ag…Ag PDF data. For Ag 0 formation in vacuum MOR structures with a Si:Al ratio of 5:1 with Al in the T1 position resulted in the most framework flexibility and the lowest Ag 0 nanocluster charge, indicating the best result for formation of charge neutral nanoclusters. When water is present, Al in the T3 and T4 positions results in the formation of the smallest average Ag 0 nanoclusters plus greater expansion of the O-T-O bond angle than in vacuum, indicating easier diffusion of the Ag 0 nanoclusters to the surface. Here, the presence of Al in 4-membered rings and in pairs indicates favorable MOR structures for formation of single Ag atoms, despite the existence of synthesis challenges. Therefore, Al in the T2 position is the least favorable for Ag 0 nanocluster formation in both vacuum and in the presence of water. Al in the T1, T3, and T4 positions provides beneficial effects through framework flexibility and changes in nanocluster size or charge that can be leveraged for design of zeolites for formation of metallic nanoclusters.

36 MATERIALS SCIENCE↗

Benchmark Data Set of Crystalline Organic Semiconductors

This work reports a Benchmark Data set of Crystalline Organic Semiconductors to test calculations of the structural and electronic properties of these materials in the solid state. The data set contains 67 crystals consisting of mostly rigid molecules with a single dominant conformer, covering the majority of known structural types. The experimental crystal structure is available for the entire data set, whereas zero-temperature unit cell volume can be reliably estimated for a subset of 28 crystals. Using this subset, we benchmark r 2 SCAN-D3 and PBE-D3 density functionals. Then, for the entire data set, we benchmark approximate density functional theory (DFT) methods, including GFN1-xTB and DFTB3(3ob-3-1), with various dispersion corrections against r 2 SCAN-D3. Our results show that r 2 SCAN-D3 geometries are accurate within a few percent, which is comparable to the statistical uncertainty of experimental data at a fixed temperature, but the unit cell volume is systematically underestimated by 2% on average. The several times faster PBE-D3 provides an unbiased estimate of the volume for all systems except for molecules with highly polar bonds, for which the volume is substantially overestimated in correlation with the underestimation of atomic charges. Considered approximate DFT methods are orders of magnitude faster and provide qualitatively correct but overcompressed crystal structures unless the dispersion corrections are fitted by unit cell volume.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mixtures of octanol and an ionic liquid: Structure and transport

Ionic liquids (ILs) with long alkyl substituents are amphiphilic, which leads to a bicontinuous liquid structure. The strongly interacting anionic and cationic head groups form a long range charge network, with the hydrocarbon tails forming a nonpolar domain. Such nonpolar domains have been shown to dissolve a variety of neutral organic solvents. In mixtures of ILs with solvents the neutral organic molecules residing in the nonpolar domains experience different environments and friction from the charged cations and anions. Thus, the neutral molecules diffuse much faster than predicted by hydrodynamic scaling using the average viscosity of the mixture. Here, we report studies on the structure and transport properties of mixtures of 1-octanol with the IL trihexyltetradecylphosphonium bis(trifluoromethylsulfonyl)imide (P 6,6,6,14 + /NTf 2 – ). The majority of the atom fraction in the P 6,6,6,14 + cation comprises four hydrocarbon substituents. The unique amphiphilic nature of ILs with the P 6,6,6,14 + cation makes 1-octanol fully miscible with the IL at ambient temperatures. X-ray scattering experiments show that the IL structure persists in the mixtures for 1-octanol mole fractions as large as x oct = 0.90. The self-diffusion coefficients of the three molecular species in the mixtures were measured by NMR experiments. The self-diffusion of the P 6,6,6,14 + cation is well described by the Stokes–Einstein equation, while the diffusivity of the NTf 2 – anion is slightly lower than the hydrodynamic prediction. The measured diffusivities of octanol in these mixtures are 1.3–4 times higher than the hydrodynamic predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computational Approach for Probing Redox Potential for Iron-Sulfur Clusters in Photosystem I

Photosystem I is a light-driven electron transfer device. Available X-ray crystal structure from Thermosynechococcus elongatus showed that electron transfer pathways consist of two nearly symmetric branches of cofactors converging at the first iron–sulfur cluster F X , which is followed by two terminal iron–sulfur clusters F A and F B . Experiments have shown that F X has lower oxidation potential than F A and F B , which facilitates the electron transfer reaction. Here, we use density functional theory and Multi-Conformer Continuum Electrostatics to explain the differences in the midpoint Em potentials of the F X , F A and F B clusters. Our calculations show that F X has the lowest oxidation potential compared to F A and F B due to strong pairwise electrostatic interactions with surrounding residues. These interactions are shown to be dominated by the bridging sulfurs and cysteine ligands, which may be attributed to the shorter average bond distances between the oxidized Fe ion and ligating sulfurs for F X compared to F A and F B . Moreover, the electrostatic repulsion between the 4Fe-4S clusters and the positive potential of the backbone atoms is lowest for F X compared to both F A and F B . These results agree with the experimental measurements from the redox titrations of low-temperature EPR signals and of room temperature recombination kinetics.

59 BASIC BIOLOGICAL SCIENCES↗

Composition dependence of atomic order in strain-relaxed, metastable GeSn alloys

Extended x-ray absorption fine structure (EXAFS) measurements of single-crystal Ge/GeSn radial heterostructure nanowires are used to examine the effects of composition on both short-range order (SRO) and longer-range disorder in GeSn alloys. GeSn has prompted significant interest because it can achieve a direct band gap for sufficient Sn concentrations beyond the equilibrium solid solubility limit in an all-group IV system. Short-range order in this material is particularly interesting as it has been predicted to affect the band gap independent of average composition or strain effects. By independently controlling the Sn composition and GeSn thickness during chemical vapor deposition of misfitting GeSn shells around ultrathin, elastically compliant, Ge core nanowires, the elastic misfit strain in the GeSn is minimized for Sn compositions over the studied range ≈Ge 0.96 Sn 0.04 to Ge 0.88 Sn 0.12 . The degree of SRO was found to decrease with increasing Sn composition. Additionally, damping of the EXAFS signal was observed as the Sn content increased, particularly for increasingly distant atomic shells about the absorbing atom, even for scattering paths not involving Sn atoms. This result is quantified as an increase in the mean-squared relative displacement parameters of the shells. These measurements reveal the accommodation of local strain due to the presence of the highly size-mismatched Sn atoms in the Ge diamond cubic lattice (≈14%), which may have effects on the band structure of the material in addition to the influence of short-range atomic order. Comparison among the nanowire samples allows for calculation of the topological rigidity parameter, a ∗∗ , for the first-neighbor bond lengths. Furthermore, these exhibit chemically distinct values for Ge-Ge, Ge-Sn, and Sn-Sn, and they are consistent with the value a ∗∗ = 0.75 ± 0.07 confirming the general applicability of the model to alloys with both large amounts of natural misfit strain and the potential for short-range order.

Crystal structure Semiconductors Transmission elec↗

Large-scale integration of artificial atoms in hybrid photonic circuits

A central challenge in developing quantum computers and long-range quantum networks is the distribution of entanglement across many individually controllable qubits. Colour centres in diamond have emerged as leading solid-state ‘artificial atom’ qubits because they enable on-demand remote entanglement, coherent control of over ten ancillae qubits with minute-long coherence times and memory-enhanced quantum communication. A critical next step is to integrate large numbers of artificial atoms with photonic architectures to enable large-scale quantum information processing systems. So far, these efforts have been stymied by qubit inhomogeneities, low device yield and complex device requirements. Here we introduce a process for the high-yield heterogeneous integration of ‘quantum microchiplets’—diamond waveguide arrays containing highly coherent colour centres—on a photonic integrated circuit (PIC). We use this process to realize a 128-channel, defect-free array of germanium-vacancy and silicon-vacancy colour centres in an aluminium nitride PIC. Photoluminescence spectroscopy reveals long-term, stable and narrow average optical linewidths of 54 megahertz (146 megahertz) for germanium-vacancy (silicon-vacancy) emitters, close to the lifetime-limited linewidth of 32 megahertz (93 megahertz). We show that inhomogeneities of individual colour centre optical transitions can be compensated in situ by integrated tuning over 50 gigahertz without linewidth degradation. The ability to assemble large numbers of nearly indistinguishable and tunable artificial atoms into phase-stable PICs marks a key step towards multiplexed quantum repeaters and general-purpose quantum processors

36 MATERIALS SCIENCE↗

Atomic Layer Deposition of Ruthenium Films Using Ruthenium Diketonates and O 2 , H 2 , or N 2 O: The Role of Ruthenium Etching

In this work, the evolution of the surface during the steps that comprise the atomic layer deposition (ALD) of ruthenium films on a nickel substrate using tris(2,2,6,6-tetramethyl-3,5-heptanedionato)ruthenium(III) (Ru(tmhd) 3 ) and molecular oxygen was characterized using a combination of X-ray photoelectron (XPS) and reflection–absorption infrared (RAIRS) spectroscopies. The uptake of the Ru metalorganic precursor was determined to be activated, involving the average loss of two out of the three ligands (and the retention of the third, in molecular form, at the surface–vacuum interface), and self-limited, as required in ALD. The reaction of the resulting layer from that first half of the ALD cycle with O 2 proved to be more complex: in addition to the desired removal of the carbon-containing material, the Ni substrate becomes oxidized, and some Ru is etched away in the form of the volatile RuO 4 gas. By testing different combinations of exposures and temperatures it was determined that Ru film growth was possible, but tuning and optimizing the ALD or atomic layer etching (ALE) process conditions for maximum film growth or removal rate per cycle proved difficult. Replacing O 2 with H 2 was shown not to be viable either, as such an agent can reduce the nickel oxide formed after O 2 treatments (in fact, Ru(tmhd) 3 can do this as well) but not remove the carbonaceous material deposited on the surface by the Ru precursor. The use of N 2 O, on the other hand, showed much promise, being capable of removing most of the surface carbon without affecting the Ru film or the Ni substrate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural Rearrangements of Subnanometer Cu Oxide Clusters Govern Catalytic Oxidation

Sub-nanometer metal oxide clusters are very important materials that are widely used, for example, in catalysis or electronic devices such as sensors. Hence, it is critical to understand the atomic structures and properties of sub-nanometer metal oxide clusters under a reactive gas environment, such as O 2 . We consider here experimentally accessible precise-size Cu clusters (Cu 4 ) supported on partially hydroxylated amorphous alumina and show that such clusters can access, in catalytic conditions at high temperature under a pressure of O 2 , a large ensemble of oxidized structures, representing a large variety of oxygen content, of geometries in link with the support, and of catalytic activities for oxidation reactions, as seen from their reducibilities. A grand canonical basin hopping method based on first-principles energy reveals an ensemble of 24 configurations for the Cu 4 O x cluster of low free energy, less than 0.8 eV above the global minimum. The low free energy ensemble consists of clusters of different stoichiometries, which are mainly Cu 4 O 3 and Cu 4 O 4 in the temperature range of 200–400 °C and under a pressure of 0.5 bar of O 2 . The presence of several competitive isomers at each composition implies that cluster fluxionality impacts the phase diagram, which should be ensemble-averaged. In terms of catalytic oxidation activity, Cu 4 O 3 isomers present highly variable O abstraction energy: the most stable isomers are inactive for alkane oxidative dehydrogenation, but isomerization to metastable isomers, that proceed with low barrier, enable to create active configurations with low O abstraction energy. O atoms with the lowest anionic character, and thus of more electrophilic nature, present the best oxidation capability. In contrast, all Cu 4 O 4 isomers show a low O abstraction energy and a high potential catalytic activity. Here, this manuscript demonstrates the unique structural and electronic properties of sub-nano Cu oxide clusters and illustrates the critical roles of configuration ensembles and rearrangement to highly reactive metastable cluster isomers in nanocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular basis for higher affinity of SARS-CoV-2 spike RBD for human ACE2 receptor

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused substantially more infections, deaths, and economic disruptions than the 2002-2003 SARSCoV. The key to understanding SARS-CoV-2's higher infectivity lies partly in its host receptor recognition mechanism. Experiments show that the human angiotensin converting enzyme 2 (ACE2) protein, which serves as the primary receptor for both CoVs, binds to the receptor binding domain (RBD) of CoV-2's spike protein stronger than SARS-CoV's spike RBD. The molecular basis for this difference in binding affinity, however, remains unexplained from X-ray structures. To go beyond insights gained from X-ray structures and investigate the role of thermal fluctuations in structure, we employ all-atom molecular dynamics simulations. Microseconds-long simulations reveal that while CoV and CoV-2 spike-ACE2 interfaces have similar conformational binding modes, CoV-2 spike interacts with ACE2 via a larger combinatorics of polar contacts, and on average, makes 45% more polar contacts. Correlation analysis and thermodynamic calculations indicate that these differences in the density and dynamics of polar contacts arise from differences in spatial arrangements of interfacial residues, and dynamical coupling between interfacial and non-interfacial residues. Furthermore, these results recommend that ongoing efforts to design spike-ACE2 peptide blockers will benefit from incorporating dynamical information as well as allosteric coupling effects.

59 BASIC BIOLOGICAL SCIENCES↗

Low-Energy Ion Scattering Intensities from Supported Nanoparticles: The Spherical Cap Model

Supported nanoparticles are of great importance to many technologies like fuel processing and chemical synthesis using catalysts and electrocatalysts, energy storage and generation using fuel cells and batteries, electrochemistry, magnetic information storage, and more. Low-energy ion scattering spectroscopy (LEIS) with noble gas ions like He+ is a powerful tool for the characterization of nanoparticles dispersed across flat support surfaces due to its ability to probe the elemental composition in the topmost atomic layer of a surface, providing quantitative information regarding the size and number density of nanoparticles. In this work, we present a derivation of the LEIS intensities expected from nanoparticles and the support material as a function of the average particle size, their number per unit area, and their contact angle with the support when modeled as spherical caps of the nanoparticle material dispersed over the surface of a flat support. The model assumes that the ion intensities are determined only by the physical blocking of linear ion trajectories and independent of the tilt angle of the local surface relative to the incident and scattered ion directions, an assumption we support by quantitative modeling of published data which tested tilt-angle effects. The model is a generalization to arbitrary contact angles of the hemispherical cap model, which assumes 90° contact angle and has been widely used to model spectroscopic signals in LEIS (and also in Auger and photoelectron spectroscopies) during nanoparticle growth. Here, this new model quantitatively reveals how LEIS signals are sensitive not only to the diameter and number density of the nanoparticle but also to their contact angle (or height/diameter ratio). With the use of additional data (e.g., from microscopy or adsorption microcalorimetry), the model presented here will enable more accurate determination of the average size, shape, and number density of supported nanoparticles based on LEIS intensity measurements.

99 GENERAL AND MISCELLANEOUS↗

Ni Nanoparticles on CeO 2 (111): Energetics, Electron Transfer, and Structure by Ni Adsorption Calorimetry, Spectroscopies, and Density Functional Theory

The morphology, interfacial bonding energetics and charge transfer of Ni clusters and nanoparticles on slightly-reduced CeO 2-x (111) surfaces at 100 to 300 K have been studied using single crystal adsorption calorimetry (SCAC), low-energy ion scattering spectroscopy (LEIS), Xray photoelectron spectroscopy (XPS), low energy electron diffraction (LEED) and density functional theory (DFT). The initial heat of adsorption of Ni vapor decreased with the extent of pre-reduction (x) of the CeO 2-x (111), showing that stoichiometric ceria adsorbs Ni more strongly than oxygen vacancies. On CeO 1.95 (111) at 300 K, the heat dropped quickly with coverage in the first 0.1 ML, attributed to nucleation of Ni clusters on stoichiometric steps, followed by the Ni particles spreading onto less favorable terrace sites. At 100 K, the clusters nucleate on terraces due to slower diffusion. Adsorbed Ni monomers are in the +2 oxidation state, and they bind by ~45 kJ/mol more strongly to step sites than terraces. The measured heat of adsorption versus average particle size on terraces is favorably compared to DFT calculations. The Ce 3d XPS lineshape showed an increase in Ce 3+ /Ce 4+ ratio with Ni coverage, providing the number of electrons donated to the ceria per Ni atom. The charge transferred per Ni is initially large but strongly decreases with increasing cluster size for both experiments and DFT, and shows large differences between clusters at steps versus terraces. This charge is localized on the interfacial Ni and Ce atoms in their atomic layers closest to the interface. This knowledge is crucial to understanding the nature of the active sites on the surface of Ni-CeO 2 catalysts for which metal-oxide interactions play a very important role in the activation of O-H and C-H bonds. In conclusion, the changes in these interactions with Ni particle size (metal loading) and the extent of reduction of the ceria help to explain how previously reported catalytic activity and selectivity change with these same structural details.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure-property relations of oP32-Ge under pressure

The unit-cell parameters, systematic absences, and atomic parameters of the germanium allotrope oP32-Ge show continuous changes up to 6 GPa as shown by single-crystal diffraction analysis. Peak shape and diffuse scattering features remain about unchanged throughout the experiment. Hence, neither the average nor the defect structure behavior offers a structure-property explanation for pressure-induced superconductivity observed at about 2 GPa [1]. Angle dispersive x-ray diffraction reveals a sluggish transformation of oP32-Ge to the Ge-II polymorph, the transition begins around 8 GPa and is complete at 12 GPa, a behavior similar to that of Ge-I. The reconstructive transition was associated with the breakdown of crystals into a powder that was compressed to 32 GPa. Synchrotron infrared absorption measurements up to 8.5 GPa indicate an increase of the band gap of the oP32-Ge prior to its collapse at 8.5 GPa. We suggest that the onset of superconductivity is not associated with a major structural change or that such a change occurs in specific stress and temperature conditions.

Lavina, Barbara↗

Neural network based analysis of multimodal bond distributions using extended x-ray absorption fine structure spectra

Knowledge of the local coordination environment around atomic species in functional materials is critical for understanding their mechanisms of operation. Heterogeneous mixtures of metal complexes are ubiquitous in catalysts, ionic liquids, molten salts, biological enzymes, and geochemical systems, among many others. Extracting information from ensemble-average measurements about the structural and compositional descriptors of each type of coordination complex comprising the mixture is not generally possible, especially when they possess multimodal bond-length distributions. Here, we developed a method that enables the mapping of an x-ray absorption spectrum on the radial distribution function describing the average environment of the metal ions. The supervised neural network based method utilizes an objective training set, for which the choice of the local structural motifs is completely agnostic to the theoretically expected structure and dynamics of the modeled system. The method was validated using first-principles modeling of structural dynamics of nickel complexation in molten salts, and it applies to a large class of heterogeneous systems, including those studied under in situ and operando conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optimization of Ag Electrocatalyst Performance for CO2 to CO Conversion: Pairing Atomic Simulations with Experiments

Density-functional theory- based calculations that complement our series of experimental efforts on optimizing Ag electrocatalyst performance for CO2 to CO conversion were presented. Three key findings are drawn out from the combined UHV surface science, STM and electrochemical measurements: (1) Using a series of Ag nanoparticles with 2-6 nm average diameters, CO2 reduction reaction (CO2RR) activity increases, with particle between 2 nm and ∼4 nm demonstrating the highest combination of activity and selectivity; (2) Electronic metal−support interactions (EMSIs) between Ag and C dramatically improve CO2RR performance as evidenced by a scaling relationship between particle size and the relative Ag−C EMSIs strength, which improves the CO2-to-CO Faradaic efficiency of sub-2 nm Ag particles from 2 to ∼100% and increases the CO turnover frequency ∼15-fold compared with similarly sized bare Ag particles; (3) The performance Ag electrocatalysts is improved when supported on S-doped C materials. Computational modeling of 1−10 nm Ag particles predicts a nearly identical size-dependent trend with maximum CO2RR activity predicted for 3.7nm particles. The calculations support the promotional effect of C materials, showing a large charge transfer of 1.02 e from Ag clusters to defective C and a 0.41 eV less endergonic step of forming COOH intermediate on Ag/defective-C compared to the Ag/C system. Calculations indicate a more favorable energetic pathway of CO2-to-CO at the C-S-Ag interface, consistent with experiments.

CO2 utilization↗

Atomic Layer Deposition of Nickel Using Ni(dmamb)2 and ZnO Adhesion Layer Without Plasma

Abstract In this study, a novel deposition technique that utilizes diethylzinc (C 4 H 10 ZnO) with H 2 O to form a ZnO adhesion layer was proposed. This technique was followed by the deposition of vaporized nickel(II) 1-dimethylamino-2-methyl-2-butoxide (Ni(dmamb) 2 ) and H 2 gas to facilitate the deposit of uniform layers of nickel on the ZnO adhesion layer using atomic layer deposition. Deposition temperatures ranged from 220 to 300 °C. Thickness, composition, and crystallographic structure results were analyzed using spectroscopic ellipsometry, scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD), respectively. An average growth rate of approximately 0.0105 angstroms per cycle at 260 °C was observed via ellipsometry. Uniform deposition of ZnO with less than 1% of Ni was displayed by utilizing the elemental analysis function via SEM, thereby providing high-quality images. XPS revealed ionizations consistent with nickel and ZnO through the kinetic and binding energies of each detected electron. XRD provided supplemental information regarding the validity of ZnO by exhibiting crystalline attributes, revealing the presence of its hexagonal wurtzite structure.

Baker, Kaiya↗