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At least 559 records · Page 31

Nuclear techniques in studies of condensed matter

Nuclear techniques have played an important role in the studies of materials over the past several decades. For example, X-ray diffraction, neutron diffraction, neutron activation, and particle- or photon-induced X-ray emission techniques have been used extensively for the elucidation of structural and compositional details of materials. Several new techniques have been developed recently. Four such techniques are briefly reviewed which have great potential in the study and development of new materials. Of these four, Mossbauer spectroscopy, muon spin rotation, and positron annihilation spectroscopy techniques exploit their great sensitivity to the local atomic environments in the test materials. Interest in synchrotron radiation, on the other hand, stems from its special properties, such as high intensity, high degree of polarization, and high monochromaticity. It is hoped that this brief review will stimulate interest in the exploitation of these newer techniques for the development of improved materials.

Singh, Jag J.↗

Modeling scale-up of particle coating by atomic layer deposition

Atomic layer deposition (ALD) is a promising technique to functionalize particle surfaces for energy applications including energy storage, catalysis, and decarbonization. In this work, we present a set of models of ALD particle coating to explore the transition from lab scale to manufacturing. Our models encompass the main particle coating manufacturing approaches including rotary bed, fluidized bed, and continuously vibrating reactors. These models provide key metrics, such as throughput and precursor utilization, required to evaluate the scalability of ALD manufacturing approaches and their feasibility in the context of energy applications. Our results show that designs that force the precursor to flow through fluidized particles transition faster to a transport-limited regime where throughput is maximized. They also exhibit higher precursor utilization. In the context of continuous processes, our models indicate that it is possible to achieve self-extinguishing processes with almost 100% precursor utilization. A comparison with past experimental results of ALD in fluidized bed reactors shows excellent qualitative and quantitative agreement.

25 ENERGY STORAGE↗

Effect of Co/SiO 2 Single-Site Heterogeneity on Small Alkane Dehydrogenation Kinetics

Atomically dispersed, high-spin Co(II) atoms in distorted tetrahedral coordination to an amorphous silica (am-SiO 2 ) support, and more recently in zeolite frameworks, are active and selective for light alkane dehydrogenation. This paper investigates how variations in the geometry of the active sites affect the ethane dehydrogenation activity of atomically dispersed Co(II) on an am-SiO 2 support. We generate a distribution of sites and determine the geometric parameters that exhibit the strongest correlation with the coordination geometry and activity of the metal atom by means of linear dimensionality reduction techniques. We perform electronic structure calculations and microkinetic modeling and deduce the mechanism and kinetics for a representative sample of sites. Irrespective of the active site geometry, the rate of ethane dehydrogenation is governed by the β-hydride elimination, which involves quartet-doublet spin-crossing and proceeds adiabatically due to strong spin-orbit coupling. Informed by the complete microkinetic analysis of the sites, we derive the reduced rate expression as a function of three site-dependent quantities. We show that these site-dependent quantities correlate with the energy of formation of the ethyl intermediate that forms via C-H bond activation. This correlation allows us to derive the site-averaged rate for the entire distribution of sites. Among various sites, the tri-coordinate and planar tetra-coordinate Co sites exhibit higher Lewis acidity than the tetrahedral sites, and consequently, higher initial rates. Finally, we discuss the implications for more active catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding Formation of Irradiation-Induced Defects through 4D-STEM, Electron Tomography, and WBDF-STEM

A major challenge in advancing nuclear materials for next-generation fission and proposed fusion reactors is to comprehensively understand the formation of irradiation-induced defects. Here it is essential to correlate the evolution of irradiation-induced defects and the degradation of mechanical properties, as they collectively dictate the material's lifespan and ensure nuclear safety. Scanning transmission electron microscopy (STEM) based techniques have emerged as indispensable tools for irradiation-induced defect characterization, offering high spatial resolution imaging and chemical analysis, such as electron energy loss spectroscopy (EELS) and energy dispersive X-ray spectroscopy (EDXS). These techniques have been effectively used to obtain an atomic-scale view of the defect structure. Recent advances in electron microscopy, particularly in 4D-STEM, offer detailed insight into microstructural evolution by capturing full 2D diffraction patterns at every pixel position. Using high-speed direct electron detectors, this technology generates a four-dimensional dataset, overcoming the limitations of traditional STEM imaging.

36 MATERIALS SCIENCE↗

Preliminary results of neutron and X-ray diffraction data collection on a lytic polysaccharide monooxygenase under reduced and acidic conditions

Lytic polysaccharide monooxygenases (LPMOs) are copper-center enzymes that are involved in the oxidative cleavage of the glycosidic bond in crystalline cellulose and other polysaccharides. The LPMO reaction is initiated by the addition of a reductant and oxygen to ultimately form an unknown activated copper–oxygen species that is responsible for polysaccharide-substrate H-atom abstraction. Given the sensitivity of metalloproteins to radiation damage, neutron protein crystallo­graphy provides a nondestructive technique for structural characterization while also informing on the positions of H atoms. Neutron cryo-crystallography permits the trapping of catalytic intermediates, thereby providing insight into the protonation states and chemical nature of otherwise short-lived species in the reaction mechanism. Here, to characterize the reaction-mechanism intermediates of LPMO9D from Neurospora crassa, a cryo-neutron diffraction data set was collected from an ascorbate-reduced crystal. A second neutron diffraction data set was collected at room temperature from an LPMO9D crystal exposed to low-pH conditions to probe the protonation states of ionizable groups involved in catalysis under acidic conditions.

Neurospora crassa↗

Modeling diffusion and depletion in high-aspect-ratio atomic layer deposition processes: Process parameters and manufacturing impacts

Atomic layer deposition (ALD) is a powerful technique for modifying the surface chemistry and properties of substrates with complex and nonplanar topologies. However, achieving uniform and conformal deposition on ultrahigh-aspect-ratio substrates remains challenging, typically requiring large quantities of precursors and long exposure times. Furthermore, process optimization is often performed empirically and involves substantial trial and error. In this work, we perform a combined experimental and computational study of ALD Al 2 O 3 infiltration into silica aerogel monoliths (aspect ratio >10 5 ). A reaction-diffusion model is used to explore the effects of key processing parameters, namely, exposure time per dose, precursor source temperature, number of aerogels in the reactor, and reactor volume. The model is based on quasi-static mode ALD, where the dosed precursor is held in the chamber for a fixed period of time before purging. We analyze the trade-offs between process throughput and precursor utilization for each of these parameters. Furthermore, we investigate the co-optimization and interactions between multiple process parameters, demonstrating the potential for further improvements. Furthermore, this physics-based model can be used to identify a set of process parameters for high-aspect-ratio ALD that meet specific manufacturing objective functions, including throughput, cost, and sustainability.

Aerogel↗

Benchmarking large language models for materials synthesis: The case of atomic layer deposition

In this work, we introduce an open-ended question benchmark, ALDbench, to evaluate the performance of large language models (LLMs) in materials synthesis, and, in particular, in the field of atomic layer deposition, a thin film growth technique used in energy applications and microelectronics. Our benchmark comprises questions with a level of difficulty ranging from the graduate level to domain expert current with the state of the art in the field. Human experts reviewed the questions along the criteria of difficulty and specificity, and the model responses along four different criteria: overall quality, specificity, relevance, and accuracy. We ran this benchmark on an instance of OpenAI’s GPT-4o. The responses from the model received a composite quality score of 3.7 on a 1–5 scale, consistent with a passing grade. However, 36% of the questions received at least one below average score. An in-depth analysis of the responses identified at least five instances of suspected hallucination. Finally, we observed statistically significant correlations between the difficulty of the question and the quality of the response, the difficulty of the question and the relevance of the response, the specificity of the question, and the accuracy of the response as graded by the human experts. Furthermore, this emphasizes the need to evaluate LLMs across multiple criteria beyond difficulty or accuracy.

Artificial intelligence↗

Atomic layer deposition of nanofilms on porous polymer substrates: Strategies for success

Atomic layer deposition (ALD) is a versatile technique for engineering the surfaces of porous polymers, imbuing the flexible, high-surface-area substrates with inorganic and hybrid material properties. Previously reported enhancements include fouling resistance, electrical conductance, thermal stability, photocatalytic activity, hydrophilicity, and oleophilicity. However, there are many poorly understood phenomena that introduce challenges in applying ALD to porous polymers. In this paper, we address five common challenges and ways to overcome them: (1) entrapped precursor, (2) embrittlement, (3) film fracture, (4) deformation, and (5) pore collapse. These challenges are often interrelated and can exacerbate one another. To investigate these phenomena, we applied various ALD chemistries to porous polymers including polyethersulfone, polysulfone, polyvinylidene fluoride, and polycarbonate track-etched membranes. Reaction-diffusion modeling revealed why certain precursors and processing conditions result in embrittling subsurface material growth, entrapment of unreacted precursors, and nongrowth. We quantify the limits of ALD processing temperatures that are dictated by thermal expansion mismatch and can lead to fractured ALD films. The results herein allow us to make recommendations to avoid, mitigate, or overcome the difficulties encountered when performing ALD and plasma-enhanced ALD on porous polymers. We intend this article to serve as a “lessons learned” guide informed by previous experience to provide a better understanding of the difficulties and limitations of ALD on porous polymers and knowledge-based guidelines for successful depositions. This knowledge can accelerate future research and help experimentalists navigate and troubleshoot as they expose porous polymers to reactive precursor vapors.

36 MATERIALS SCIENCE↗

Low Earth Orbital Atomic Oxygen Interactions With Materials

Atomic oxygen is formed in the low Earth orbital environment (LEO) by photo dissociation of diatomic oxygen by short wavelength (< 243 nm) solar radiation which has sufficient energy to break the 5.12 eV O2 diatomic bond in an environment where the mean free path is sufficiently long (~ 108 meters) that the probability of reassociation or the formation of ozone (O3) is small. As a consequence, between the altitudes of 180 and 650 km, atomic oxygen is the most abundant species. Spacecraft impact the atomic oxygen resident in LEO with sufficient energy to break hydrocarbon polymer bonds, causing oxidation and thinning of the polymers due to loss of volatile oxidation products. Mitigation techniques, such as the development of materials with improved durability to atomic oxygen attack, as well as atomic oxygen protective coatings, have been employed with varying degrees of success to improve durability of polymers in the LEO environment. Atomic oxygen can also oxidize silicones and silicone contamination to produce non-volatile silica deposits. Such contaminants are present on most LEO missions and can be a threat to performance of optical surfaces. The LEO atomic oxygen environment, its interactions with materials, results of space testing, computational modeling, mitigation techniques, and ground laboratory simulation procedures and issues are presented.

Banks, Bruce A.↗

The importance of atomic and molecular correlation on the bonding in transition metal compounds

The determination of accurate spectroscopic parameters for molecular systems containing transition metal atoms is shown to require extensive data sets and a high level correlation treatment, and techniques and their limitations are considered. Extensive results reported on the transition metal atoms, hydrides, oxides, and dimers makes possible the design of a calculation to correctly describe the mixing of different atomic asymptotes, and to give a correct balance between molecular bonding and exchange interactions. Examples considered include the dipole moment of the 2Delta state of NiH, which can help determine the mixture of 3d(8)4s(2) and 3d(9)4s(1) in the NiH wavefunction, and the bonding in CrO, where an equivalent description of the relative energies associated with the Cr 3d-3d atomic exchange and the Cr-O bond is important.

Bauschlicher, Charles W., Jr.↗

Laser spectroscopy of indium Rydberg atom bunches by electric field ionization

This work reports on the application of a novel electric field-ionization setup for high-resolution laser spectroscopy measurements on bunched fast atomic beams in a collinear geometry. In combination with multi-step resonant excitation to Rydberg states using pulsed lasers, the field ionization technique demonstrates increased sensitivity for isotope separation and measurement of atomic parameters over previous non-resonant laser ionization methods. The setup was tested at the Collinear Resonance Ionization Spectroscopy experiment at ISOLDE-CERN to perform high-resolution measurements of transitions in the indium atom from the 5s 2 5d 2 D 5/2 and 5s 2 5d 2 D 3/2 states to 5s 2 np 2 P and 5s 2 nf 2 F Rydberg states, up to a principal quantum number of n=72 . The extracted Rydberg level energies were used to re-evaluate the ionization potential of the indium atom to be 46,670.107(4)cm -1 . The nuclear magnetic dipole and nuclear electric quadrupole hyperfine structure constants and level isotope shifts of the 5s 2 5d 2 D 5/2 and 5s 2 5d 2 D 3/2 states were determined for 113,115 In. The results are compared to calculations using relativistic coupled-cluster theory. A good agreement is found with the ionization potential and isotope shifts, while disagreement of hyperfine structure constants indicates an increased importance of electron correlations in these excited atomic states. With the aim of further increasing the detection sensitivity for measurements on exotic isotopes, a systematic study of the field-ionization arrangement implemented in the work was performed at the same time and an improved design was simulated and is presented. The improved design offers increased background suppression independent of the distance from field ionization to ion detection.

74 ATOMIC AND MOLECULAR PHYSICS↗

Structural Properties of Nanometer‐Sized Gold Nanoparticles on a Silicon Substrate

Properties of gold nanoparticles (Au NPs) supported on Si substrates, which have been the focus of recent attention, depend sensitively on the size, structure, and coordination of Au NPs as well as on the processes of interdiffusion and chemical bonding at the Au–Si interface. There is a great need, therefore, for developing structural techniques capable of imaging such nanosystems in atomic detail. Here, it is discussed how the atomic structure of nanometer‐sized Au NPs deposited on a silicon surface can be determined by using high‐energy X‐ray diffraction measurements in combination with an analysis based on atomic‐pair‐distribution functions and advanced reverse Monte Carlo methods. This approach delivers simple and incisive pictures of the structure of Au clusters on Si and reveals direct structural evidence for the emergence of a Au‐silicide interface following room temperature deposition of Au NPs on Si. This study will contribute to designing Au/Si nanostructures with desirable properties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Time-discretization of a plasma-neutral MHD model with a semi-implicit leapfrog algorithm

The semi-implicit leapfrog time-discretization is a workhorse algorithm for initial-value MHD codes to bridge between vastly separated time scales. Inclusion of atomic interactions with neutrals breaks the functional structure of the MHD equations that exploited by the leapfrog. In this work, we address how to best integrate atomic physics into the semi-implicit leapfrog. Following the Crank-Nicolson method, one approach is to time-center the atomic interactions in the linear solver and use a Newton method to include the nonlinear contributions. Alternatively, another family of methods are based on operator-splitting the terms associated with the atomic interactions using a Strang-splitting technique. These methods naturally break equations into constituent ODE and PDE parts and preserve the structure exploited by the semi-implicit leapfrog. We study the accuracy and efficiency of these methods through a battery of 0D and 1D cases and show that a second-order-in-time Douglas-Rachford inspired coupling between the ODE and PDE advances is effective in reducing the time-discretization error to be comparable to that of Crank-Nicolson with Newton iteration of the nonlinear terms. Splitting ODE and PDE parts results in independent matrix solves for each field which reduces the computational cost considerably and provides parallelization over species relative to Crank-Nicolson.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Disordered hydrogen adsorption at the three-fold site of W(110)

Hydrogen often forms disordered phases on metals; however, deciphering the atomic-scale behavior requires experimental and modeling techniques that directly probe the short-range order between neighboring hydrogen adsorbates. Here, to address this challenge, we applied direct recoil spectroscopy (DRS) to investigate hydrogen adsorption on the W(110) surface. We show that the recoiled hydrogen flux measured during DRS is sensitive to the short range order of the adsorbed hydrogen. Ordered hydrogen neighbors are much more efficient at dechanneling incident ions along low-index surface channels, strongly suppressing the recoiled hydrogen flux along these directions. By modeling the DRS measurements with molecular dynamics for ordered and disordered hydrogen phases, we find that at a hydrogen surface coverage of approximately Θ = 0.6, the hydrogen adsorbates are bound to three-fold sites in a disordered phase at room temperature. This finding is consistent with transfer-matrix scaling model calculations that suggest the transition to an ordered hydrogen phase occurs at a greater surface coverage of Θ = 0.83.

08 HYDROGEN↗

Identification and correction of temporal and spatial distortions in scanning transmission electron microscopy

Scanning transmission electron microscopy (STEM) has become the technique of choice for quantitative characterization of atomic structure of materials, where the minute displacements of atomic columns from high-symmetry positions can be used to map strain, polarization, octahedra tilts, and other physical and chemical order parameter fields. The latter can be used as inputs into mesoscopic and atomistic models, providing insight into the correlative relationships and generative physics of materials on the atomic level. However, these quantitative applications of STEM necessitate understanding the microscope induced image distortions and developing the pathways to compensate them both as part of a rapid calibration procedure for in situ imaging, and the post-experimental data analysis stage. Here, we explore the spatiotemporal structure of the microscopic distortions in STEM using multivariate analysis of the atomic trajectories in the image stacks. Based on the behavior of principal component analysis (PCA), we develop the Gaussian process (GP)-based regression method for quantification of the distortion function. The limitations of such an approach and possible strategies for implementation as a part of in-line data acquisition in STEM are discussed. Here, the analysis workflow is summarized in a Jupyter notebook that can be used to retrace the analysis and analyze the reader's data.

36 MATERIALS SCIENCE↗

Shape Control of Colloidal Semiconductor Nanocrystals through Thermodynamically Driven Aggregative Growth

The optoelectronic properties of colloidal semiconductor nanocrystals (NCs) can be manipulated by changing their geometric shapes. The precise synthetic control over particle morphologies, however, has remained elusive. Conventional growth techniques rely on the kinetic assembly of atomic units, where supersaturation and precipitation processes can lead to a broad distribution of particle shapes. In this paper, we demonstrate that replacing atomic precursors with small-size nanocrystals as building blocks for larger colloids offers an easier, more predictive control over nanoparticle shape evolution. The reported growth strategy is illustrated via shape-selective syntheses of CdSe and CdS NC cubes, spheres, rods, as well as unprecedented “donut” and ring-like structures. Growth of desired particle morphologies was achieved by choosing an appropriate reaction solvent that minimizes the surface free energy through a unique shape formation. This so-called "aggregative growth mechanism" is explained using a thermodynamic model for interacting viscous colloids. We expect that this novel growth strategy will offer a viable platform for shape–selective synthesis of many inorganic colloids, providing pathways to optimizable optoelectronic materials.

36 MATERIALS SCIENCE↗

Insights into the Li Diffusion Mechanism in Si/C Composite Anodes for Lithium-Ion Batteries

Recently, Si/C composite materials have attracted enormous research interest as the most promising candidates for the anodes of next-generation lithium-ion batteries, owing to their high energy density and mechanical buffering property. However, the fundamental mechanism of Li diffusion behavior in various Si/C composite materials remains unclear, with our understanding limited by experimental techniques and continuum modeling methodologies. Herein, the atomic behavior of Li diffusion in the Si/C composite material is studied within the framework of density functional theory. Two representative structural mixing formats, that is, simple mixture mode and core-shell mode, are modeled and compared. We discover that the carbon material increases Li diffusion in silicon from 7.75 x 10 -5 to 2.097 x 10 -4 cm 2 /s. The boost is about 50% more obvious in the mixture mode, while the core-shell structure shows more dependence on the atomic structures of the carbon layer. These results offer new insights into Li diffusion behavior in Si/C composites and unlock the enhancing mechanism for Li diffusion in Si/C. Furthermore, this understanding facilitates the modeling of batteries with composite anodes and will guide the corresponding structure designs for robust and high-energy-density batteries.

25 ENERGY STORAGE↗

Machine learning of 27Al NMR electric field gradient tensors for crystalline structures from DFT

NMR crystallography has emerged as a promising technique for the determination and refinement of atomic coordinates in crystal structures. The crystal structure of compounds containing quadrupolar nuclei, such as 27Al, can be improved by directly comparing solid-state NMR measurements to DFT computations of the electric field gradient (EFG) tensor. The non-negligible computational cost of these first-principles calculations limits the applicability of this method to all but the most well-defined structures. We developed a fast, low-cost machine learning model to predict EFG parameters based on local structural motifs and elemental parameters. We computed 8081 EFG tensors from 1681 27Al crystalline solids using DFT and benchmarked them against 105 experimentally measured 27Al sites. Surprisingly, simple local geometric features dominate the predictive performance of the resulting random-forest model, yielding an R2 value of 0.98 and an RMSE of 0.61 MHz for CQ, the quadrupolar coupling constant. This model accuracy should enable pre-refining future structural assignments before finally validating with first-principles calculations. Such a catalogue of 27Al NMR tensors can serve as a tool for researchers assigning complex NMR spectra influenced by the nuclear electric quadrupole interaction.

Sun, He↗