Structures and atomic charges of LaMnO3 high-index surfaces and surface energies of LaMnO3 low-index surfaces, revisited
Presentation at the Spring 2022 ACS National Meeting
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Presentation at the Spring 2022 ACS National Meeting
We have developed a single-shot mega-electronvolt ultrafast-electron-diffraction system to measure the structural dynamics of warm dense matter. The electron probe in this system is featured by a kinetic energy of 3.2 MeV and a total charge of 20 fC, with the FWHM pulse duration and spot size at sample of 350 fs and 120 μm respectively. We demonstrate its unique capability by visualizing the atomic structural changes of warm dense gold formed from a laser-excited 35-nm freestanding single-crystal gold foil. The temporal evolution of the Bragg peak intensity and of the liquid signal during solid-liquid phase transition are quantitatively determined. This experimental capability opens up an exciting opportunity to unravel the atomic dynamics of structural phase transitions in warm dense matter regime.
The atomic structures of SrTiO{sub 3} (STO)/LaNiO{sub 3} (LNO)/STO heterostructure interfaces were investigated by spherical aberration-corrected (C{sub S}) (scanning) transmission electron microscopy. Atomic displacement and lattice distortion measurements and electron energy loss spectroscopy (EELS) were used to quantitatively analyze the distortion of the interfacial octahedra and the bond length at the interfaces. Combined with high-resolution transmission electron microscopy (HRTEM) and scanning transmission electron microscopy analyses, two distinct interfacial atomic terminating layers are unambiguously determined. Ensuing quantitative HRTEM measurements revealed that the Ni-O bond length in the interfacial octahedral is elongated at the bottom interface (–NiO{sub 2}-SrO–). Atomic displacement shows structural relaxation effects when crossing the interfaces and lattice distortions across the interface is more pronounced in LNO than in STO. The Ti/O atomic ratio, La and Ti relative atomic ratio as derived by EELS quantification indicate non-stoichiometric composition at the interfaces. Distinct fine structures of Ti-L{sub 2,3} edge and O-K edge at the bottom and top interfaces are observed. By comparison, we are able to estimate Ti valency at both interfaces. Combining the structural distortions and Ti valency, the polar discontinuity and charge transfer at the interfaces are discussed.
Ni is one of the most extensively utilized metals in industrial catalysis. For example, Ni is the catalyst of choice for the steam reforming of hydrocarbons. However, pure Ni also detrimentally catalyzes the formation of graphitic carbon, which in turn leads to coking and deactivation of the catalyst. It has been shown that alloying small amounts of a less reactive metal like Au into Ni can alleviate this issue by breaking up the larger Ni ensembles that promote coke formation. We are taking the opposite of this approach by alloying very small amounts of Ni into Cu, another catalytically less active host metal to create single Ni atom sites. In this way our single-atom alloy approach has the potential to greatly enhance catalytic selectivity and reduce poisoning, analogous to other single-atom alloys such as PtCu and PdCu. Herein we report the atomic-scale surface structure and local geometry of low coverages of Ni deposited on a Cu(111) single crystal with scanning tunneling microscopy. At 433 K, low concentrations of Ni alloy in the Cu host as a single-atom alloy in Ni-rich brims along ascending step edges. To support our STM assignments of the single atom dispersion of Ni, reflection absorption infrared spectroscopy of CO on NiCu was performed. To access the binding strength of CO to isolated Ni sites, we use temperature-programmed desorption studies which reveal that CO binds more weakly to single Ni atoms in Cu compared to Ni(111), indicating that NiCu single-atom alloys are promising for catalytic applications in which CO poisoning is an issue. Altogether, these results provide a guide for the preparation of NiCu single-atom alloy model catalysts that are predicted by theory to be promising for a number of reactions.
Ptychography is a high-resolution imaging technique, which does not require lenses for image magnification and which provides phase contrast with high sensitivity. Here, we propose to use x-ray ptychography for the imaging of surface structure in crystalline samples. We show that ptychography can be used to image atomic step structures using coherent diffraction patterns recorded along the crystal truncation rod of a crystal surface. In a proof-of-concept experiment on a Pt (111) sample, we present ptychographic reconstructions showing features consistent with surface steps. Due to the penetration power of x-rays, this method could find interesting applications for the study of surface structures under buried interfaces or in harsh environments.
Glass scintillators may hold great promise for low-cost, large-volume, shapeable radiation detectors. However, the light yield and energy resolution of glass scintillators to-date have been more than an order of magnitude worse than for crystalline scintillators and far from the theoretical limits. Glass scintillators are fabricated by dissolving rare-earth dopants into a glass matrix. Their operation relies on gamma ray absorption in the glass generating electrons and holes that must migrate to a rare-earth activator atom to emit light. The transport of carriers in the glass limits the performance, particularly in glasses where the solubility limit of activator is low, since carriers may recombine non-radiatively before reaching an activator atom. In this work, we aim to use atomistic simulations to discover the nature of electron transport in specific glass materials and how it may be enhanced by tuning the composition or forming process. The analysis proceeds in two steps: generation of a computational model of a given glass’s atomic structure, then extraction of the electronic structure to correlate electronic structure with carrier transport. Here we report results for two glasses: silica (SiO 2 ) and sodium silicate (Na 2 O:SiO 2 ). Multiple compositions of the latter are studied, namely Na 2 O:SiO 2 ratios of of 1:2, 1:3, and 3:7, with most results focused on the 3:7 composition. The overall goal is to establish a computational framework that can mimic a range of experimental glass structures by tuning computational parameters in the construction of the glass model, and enable studies of the correlation between atomic structure and electronic transport properties of the glass materials. These correlations would direct synthesis parameters for a given glass to optimize its transport properties.
For oxygen reduction reaction (ORR) over alloy electrocatalysts, the understanding of how the atomic arrangement of the metal species in the nanocatalysts is responsible for the catalytic enhancement is challenging for achieving better design and tailoring of nanoalloy catalysts. This paper reports results of an investigation of the atomic structures and the electrocatalytic activities of ternary and binary nanoalloys, aiming at revealing a fundamental insight into the unique atomic-scale structure-electrocatalytic activity relationship. PtIrCo catalyst and its binary counterparts (PtCo and PtIr) are chosen as a model system for this study. The effect of thermochemical treatment temperature on the atomic-scale structure of the catalysts was examined as a useful probe to the structure-activity correlation. The structural characterization of the binary and ternary nanoalloy catalysts was performed by combining surface sensitive techniques such as XPS and 3D atomic ordering sensitive techniques such as high-energy X-ray diffraction (HE-XRD) coupled to atomic pair distribution function (PDF) analysis (HE-XRD/PDFs) and computer simulations. The results show that the thermal treatment temperature tunes the nanoalloy’s atomic and chemical ordering in a different way depending on the chemical composition, leading to differences in the nanoalloy’s mass and specific activities. A unique structural tunability of the atomic ordering in a platinum-iridium-cobalt nanoalloy has been revealed for enhancing greatly the electrocatalytic activity toward oxygen reduction reaction, which has significant implication for rational design and nanoengineering of advanced catalysts for electrochemical energy conversion and storage.
The phase behavior of grain boundaries can have a strong influence on interfacial properties. Little is known about the emergence of grain boundary phases in elemental metal systems and how they transform. Here, we observe the nanoscale patterning of a grain boundary by two alternating grain boundary phases with distinct atomic structures in elemental copper by atomic resolution imaging. The same grain boundary phases are found by computational grain boundary structure search indicating a first-order transformation. Finite temperature atomistic simulations reveal a congruent, diffusionless transition between these phases under ambient pressure. The patterning of the grain boundary at room temperature is dominated by the grain boundary phase junctions separating the phase segments. Our analysis suggests that the reduced mobility of the phase junctions at low temperatures kinetically limits the transformation, but repulsive elastic interactions between them and disconnections could additionally stabilize the pattern formation.
Pt-based electrocatalysts are the primary choice for fuel cells due to their superior oxygen reduction reaction (ORR) activity. To enhance ORR performance and durability, extensive studies have investigated transition metal alloying, doping, and shape control to optimize the three key governing factors for ORR: geometry, local chemistry, and strain of their surface and subsurface. However, systematic optimization remains incomplete, as it requires an atomic-scale understanding of these factors and their dynamics over potential cycling, as well as their relationship to ORR activity. Here, we implement neural network-assisted atomic electron tomography to measure the 3D atomic structural dynamics and their effects on the functional degradation of PtNi alloy catalysts. Our results reveal that PtNi catalysts undergo shape changes, surface alloying, and strain relaxation during cycling, which can be effectively mitigated by Ga doping. By combining geometry, local chemistry, and strain analysis, we calculated the changes in ORR activity over thousands of cycles and observed that Ga doping leads to higher initial activity and greater stability. These findings offer a pathway to understanding 3D atomic structural dynamics and their relation to ORR activity during cycling, paving the way for the systematic design of durable, high-efficiency nanocatalysts.
A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented. These features include fragmentation methods like the fragment molecular orbital, effective fragment potential and effective fragment molecular orbital methods, hybrid MPI/OpenMP approaches to Hartree-Fock and resolution of the identity second order perturbation theory. Many new coupled cluster theory methods have been implemented in GAMESS, as have multiple levels of density functional/tight binding theory. The role of accelerators, especially graphical processing units, is discussed in the context of the new features of LibCChem, as is the associated problem of power consumption as the power of computers increases dramatically. The process by which a complex program suite like GAMESS is maintained and developed is considered. Future developments are briefly summarized.
The growth of zinc oxide thin films by atomic layer deposition is believed to proceed through an embryonic step in which three-dimensional nanoislands form and then coalesce to trigger a layer-by-layer growth mode. This transient initial state is characterized by a poorly ordered atomic structure, which may be inaccessible by X-ray diffraction techniques. Here in this work, we apply X-ray absorption spectroscopy in situ to address the local structure of Zn after each atomic layer deposition cycle, using a custom-built reactor mounted at a synchrotron beamline, and we shed light on the atomistic mechanisms taking place during the first stages of the growth. We find that such mechanisms are surprisingly different for zinc oxide growth on amorphous (silica) and crystalline (sapphire) substrate. Ab initio simulations and quantitative data analysis allow the formulation of a comprehensive growth model, based on the different effects of surface atoms and grain boundaries in the nanoscale islands, and the consequent induced local disorder. From a comparison of these spectroscopy results with those from X-ray diffraction reported recently, we observe that the final structure of the zinc oxide nanolayers depends strongly on the mechanisms taking place during the initial stages of growth. Finally, the approach followed here for the case of zinc oxide will be of general interest for characterizing and optimizing the growth and properties of more complex nanostructures.
Atomistic simulations are employed to demonstrate the existence of a well-defined thermodynamic phase transformation between grain boundary (GB) phases with different atomic structures. The free energy of different interface structures for an embedded-atom-method model of the Σ5 (310) [001] symmetric tilt boundary in elemental Cu is computed using the nonequilibrium Frenkel-Ladd thermodynamic integration method through molecular dynamics simulations. It is shown that the free-energy curves predict a temperature-induced first-order interfacial phase transition in the GB structure in agreement with computational studies of the same model system. Moreover, the role of vibrational entropy in the stabilization of the high-temperature GB phase is clarified. The calculated results are able to determine the GB phase stability at homologous temperatures less than 0.5, a temperature range particularly important given the limitation of the methods available hitherto in modeling GB phase transitions at low temperatures. Lastly, the calculation of GB free energies complements currently available 0 K GB structure search methods, making feasible the characterization of GB phase diagrams.
In the field of Structural Biology, Atom Probe Tomography (APT) is in the nascent stages of development wherein coarse-grained visuals of proteins have been captured. The characterization of organic samples or biomolecules through the technique is currently limited to the detection of a few dominant signatures. The problem of indecipherable characterization can inherently be traced back to multiple forms of technique-specific responses to organic samples and consequent triggers leading to organic-sample and sample-medium interactions. While it is possible for captured manifestations of protein reconstructions to seemingly appear intact from a basic visual purview, the parameter-protein associative responses throughout the structure as a direct consequence of the inherent workings of the technique (until harmonized with organic sample complexity and behavior) and field evaporation-based factors make non-aberrative atomic associations infeasible. The work focused on identifying and theorizing the (above stated and other) fundamental mechanisms that stronghold the study of intricate atomic to higher order associations in proteins through APT. Attempts at structure elucidation of the cryogenic sample under study, through indirect associations (and methods) based on other imaging techniques, further revealed the distinct and highly distortive nature at the atomic scale deterring structural tunability and thus characterization of APT based cryogenic samples under analysis. As a direct counter to the atomic scale characterization problem, by taking the experiment-specific uncertainties, and probable APT-centric organic sample-based variabilities into account, a basic result is extracted and presented. Through mass-spectrometric and computational analysis, specific individual amino acids (Sulfur-containing protein-bound amino acids) in proteins and aspects of protein structure (probable backbone fragments, partial sequence - partial backbone portions) have been identified and characterized. Under analysis considerations, a few of the simplest known and easily inferable segments that favor structural deteriorations in the reconstructions are stated. Additionally, to overcome technique-specific deterrents to the characterization of biomolecules in cryogenic sample medium, the development of a protein-labeling strategy tailored to APT is suggested.
Understanding structural properties of materials and how they relate to its atomic structure, while extremely challenging, is a key scientific quest that has dominated the landscape of materials research for decades. Neutron and X-ray scattering is a state-of-the-art method to investigate material structure on the atomic scale. Traditional methods of processing neutron scattering data to decipher the structure of target materials have relied on computing scattering patterns using physics-based forward models and comparing them with experimentally gathered scattering profiles within a computationally expensive optimization loop. Here, we report an initial design of a data-driven machine learning pipeline for material structure prediction that is computationally faster (once trained) and potentially more accurate. We describe the architecture of the ML pipeline and a preliminary benchmarking study of shallow machine learning models in terms of their prediction accuracy and limitations. We show that material structure prediction from neutron scattering data using shallow learning models is feasible to within 90% prediction accuracy for certain classes of materials but deeper models are required for more general material structure predictions.
Atomic structure and microstructure of grain boundaries in polycrystaline ceramics
Mg{sub 60}Ni{sub 30}La{sub 10−x}Co{sub x} (x = 0, 4) amorphous alloys were prepared by rapid solidification, using a melt-spinning technique. X-ray diffraction and differential scanning calorimetry analysis were employed to measure their microstructure, thermal stability and glass-forming ability, and hydrogen storage properties were studied by means of PCTPro2000. Based on differential scanning calorimetry results, their glass-forming ability and thermal stability were investigated by Kissinger method, Lasocka curves and atomic cluster model, respectively. The results indicate that glass-forming ability, thermal properties and hydrogen storage properties in the Mg-rich corner of Mg–Ni–La–Co system alloys were enhanced by Co substitution for La. It can be found that the smaller activation energy (ΔΕ) and frequency factor (υ{sub 0}), the bigger value of B (glass transition point in Lasocka curves), and higher glass-forming ability of Mg–Ni–La–Co alloys would be followed. In addition, atomic structure parameter (λ), deduced from atomic cluster model is valuable in the design of Mg–Ni–La–Co system alloys with good glass-forming ability. With an increase of Co content from 0 to 4, the hydrogen desorption capacity within 4000 s rises from 2.25 to 2.85 wt.% at 573 K. - Highlights: • Amorphous Mg{sub 60}Ni{sub 30}La{sub 10−x}Co{sub x} (x = 0 and 4) alloys were produced by melt spinning. • The GFA and hydrogen storage properties were enhanced by Co substitution for La. • With an increase of Co content, the hydrogen desorption capacity rises at 573 K.
In this paper, carbon deposition on SnO{sub 2} layer using DC unbalanced magnetron-sputtering technique at low temperature has been systematically studied. Sputtering process were carried out at pressure of 4.6×10{sup −2} Torr by keeping the substrate temperature at 300 °C. SnO{sub 2} were growth on silicon (111) substrate using thermal evaporation and continuing with dry oxidation of Sn at 225 °C. Thermal evaporation for high purity Sn was conducted by maintain the current source as high as 40 ampere. The quality of SnO{sub 2} on Si(111) and the characteristic of carbon thin film on SnO{sub 2} were analized by mean XRD, FTIR and Raman spectra. XRD analysis shows that SnO{sub 2} film is growth uniformly on Si(111). FTIR and Raman spectra confirm the formation of thin film carbon on SnO{sub 2}. Additionally, thermal annealing for some sample series have been performed to study their structural stability. The change of atomic structure due to thermal annealing were analized by Raman and XRD spectra.