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At least 37 records · Page 2

Stabilization of magnetic bubbles in [Ni/Co]n multilayers on an oxygen-reconstructed Nb(110) surface via an ultra-thin Cu interlayer

Magnetic thin films hosting topological spin textures, such as magnetic skyrmions, hold high potential for breakthroughs in the field of spintronics, due to good scalability and energy efficiency. Novel computational architectures such as memory-in-logic devices rely on material platforms able to host those topological spin textures. Furthermore, recently proposed designs of novel quantum information technologies are based on heterostructures where topological spin textures are in direct proximity to a superconducting layer. Here, we demonstrate the stabilization of out-of-plane magnetic bubbles in highly ordered [Ni/Co]n multilayers on a Nb(110) single crystal. This is achieved without the need for the removal of the well-known Nb(110)-oxide surface reconstruction, due to the introduction of an ultra-thin Cu interlayer in between the Nb substrate and the magnetic multilayer. The Cu interlayer generates a well-ordered hexagonal surface, which is key for the epitaxial growth of the [Ni/Co]n multilayers hosting the desired out-of-plane anisotropy. The magnetic ground state of the prepared material stacks is directly imaged via spin-polarized low-energy electron microscopy, revealing the presence of magnetic bubble domains with lateral sizes as small as 450 nm.

Dibajeh, Ahmad

Unveiling the Electrocatalytic Hydrogen Evolution Reaction Pathway on RuP 2 through Ab Initio Grand Canonical Monte Carlo

In this study, the high catalytic reactivity of ruthenium phosphide (RuP 2 ) has been identified by first-principles density functional theory (DFT) calculations for the electrocatalytic hydrogen evolution reaction (HER). Complex surface reconstructions are considered by applying the ab initio grand canonical Monte Carlo (ai-GCMC) algorithm, efficiently providing a sufficient phase-space exploration of possible surfaces. Combined with surface-phase Pourbaix diagrams, we are able to identify the actual surfaces that obtained under specific experimental environments, thus leading to a more accurate understanding of the nature of the active sites and the binding strength of adsorbates. Specifically, through hundreds of surface reconstructions and hydrogenation states generated with ai-GCMC, we identify the most favorable surface phases of RuP 2 under aqueous acidic conditions. We discover that the HER activity is determined by multiple surfaces with different stoichiometries within a narrow electrode potential window. Low HER overpotential (η) has been found for each of the identified surfaces, as low as 0.04 V. High H-coverage reconstructed surfaces have been discovered under acidic conditions, and the surface Ru sites introduced by additional Ru adatoms or exposed by P-vacancies serve as the active sites for HER based on their nearly reversible H binding. Furthermore, this work provides atomistic insights into the origin of high HER activity on RuP 2 by exploring the dynamic surface phases of electrocatalysts and features a generalizable method to explore the reconstructed/hydrogenated surface space as a function of experimental conditions.

25 ENERGY STORAGE

Off-Equilibrium Reactivity of Boron-Enriched Metal Diboride Surfaces in Electroreduction Conditions

Boron-based materials, featuring B-dependent reactivity and diverse phases, are emerging as promising catalyst systems. However, the catalytic mechanism on many borides remains poorly understood due to complex surface reconstructions under reaction conditions. Here, we investigate the MoB 2 surface in conditions of hydrogen evolution reaction in acidic media, using grand canonical global optimization, grand canonical density functional theory, ab initio molecular dynamics, free energy surface sampling, and an analytical model for electrochemical barrier evaluation. We propose a boron-enrichment strategy to tune the surface reactivity of the hexagonal face of MoB 2 . We reveal the dynamic nature of the B-enriched surface under H coverage and kinetic trapping of the system in the metastable regime with an extensive examination of the deactivation pathways. The metastable center B site on B-enriched surfaces, featuring buckled-up configuration and a usual relaxation effect, is found to be highly active toward HER via the Volmer–Heyrovsky mechanism. In conclusion, this work demonstrates how off-equilibrium behaviors can arise from the interplay between adsorbate coverage and surface reconstruction on a seemingly simple surface, and we present a theoretical framework and computational workflows to address these behaviors, along with other realistic complexities, in kinetics simulations.

Adsorption

4D-STEM Coupled with Unsupervised Machine Learning to Reveal at Large-Scale the Microstructural Evolution in Li- and Mn-Rich Cathodes

Li- and Mn-rich (LMR) layered oxides are known to exhibit a thin surface reconstruction layer, which grows during electrochemical cycling in a manner that depends on exposed crystallographic facets, cycling conditions, and electrolyte chemistry. Direct characterization of this layer has traditionally relied on high-resolution electron microscopy, which is inherently limited to small fields of view. Here, we employ four-dimensional scanning transmission electron microscopy (4D-STEM) combined with unsupervised machine-learning clustering to quantitatively map phase distributions over large areas and track their evolution in LMR cathodes during electrochemical aging. Our results show that the surface reconstruction layer consists predominantly of a rocksalt phase, whose thickness varies across different facets following activation cycling and becomes substantially thicker and more uniform during calendar aging. In contrast, a spinel-like phase is observed within the particle bulk. Large-area phase mapping and correlative high-resolution imaging reveal that this spinel-like phase preferentially nucleates at bulk crystallographic defects, including boundaries between 60°-rotated layered domains and associated mixed-phase regions, rather than exclusively at the particle surface. Our findings establish a mechanistic distinction between surface-driven rocksalt formation and bulk-defect-mediated spinel nucleation while demonstrating the unique capability of 4D-STEM to provide statistically robust, mesoscale insight into complex phase-evolution processes in LMR cathodes.

4D-STEM

Atomic‐Scale Surface Imaging of Bulk Epitaxial CsPbBr 3 Perovskite Single Crystals on Mica Using Light Assisted Scanning Tunneling Microscopy at Low‐Temperature (80 K)

Epitaxial single-crystalline CsPbBr 3 perovskite films on mica, prepared ex situ, are explored using a low-temperature scanning tunneling microscope (STM) by probing the unoccupied electronic states of their surface in ultra-high vacuum (UHV) at 80 K. Light-assisted STM measurements under a broadband illumination with visible light were employed to enhance and stabilize surface conductivity. STM imaging across the surface of macroscopic bulk CsPbBr 3 films reveals large flat terraces characterized by a specific type of surface reconstruction, consisting of parallel rows of U-shaped atomic nanostructures. These structures are spaced by 12 Å and exhibit an internal feature size of 5.1 Å. Density functional theory (DFT) calculations reproduce the experimental observations and reveal a competition between different orthorhombic CsPbBr 3 (110) surface reconstructions: a Cs-rich structure, identified as the most energetically stable, and three alternative Pb–Br-rich reconstructions, which are slightly higher in energy yet remain consistent with the STM data. Additional analyses that explicitly account for the mica substrate exclude the cubic CsPbBr 3 phase and other orthorhombic surface orientations, while showing that variations in the mica surface termination do not alter the preferred CsPbBr 3 (110) reconstruction. In conclusion, this combined approach thereby confirms our assignment and resolves previous STM interpretations of CsPbBr 3 .

36 MATERIALS SCIENCE

Temperature Field Reconstruction of Surfaces Heated Through Radiative Heat Transfer Using Convolutional Neural Networks

Microreactors could play a crucial role in decarbonizing our energy portfolio. However, their development and implementation come with specific challenges, particularly regarding cost. Due to their compact size and the harsh operational environment, collecting real-time data on reactor operation can be challenging. Many probe designs are unable to withstand extreme conditions (e.g., temperature, radiation) in the reactor. In this context, using convolutional neural networks (CNNs) can pave the way for developing a nonintrusive approach that relies solely on ex-core sensors. A well-trained physics-informed CNN can reconstruct the distribution of a given physical quantity over a domain using only a few sensors, allowing us to reconstruct the desired field distribution even in a limited space or complex geometries where a large array of sensors is impractical. In this work, we present the initial steps toward developing a real-time tool for monitoring the thermal behavior of nuclear reactor pressure vessels. Based on an experimental setup, a computational model using the Multiphysics Object-Oriented Simulation Environment (moose) framework was built, where the Ray Tracing and Heat Conduction modules were used to evaluate the temperature distribution over a convex metal surface heated through radiative heat transfer. This metal surface represents a section of a heated nuclear reactor vessel wall. The model also accounts for solid mechanics physics through the moose Solid Mechanics module. In situ experimental data, acquired from a Texas A&M facility, were used to validate the computational model. Part of the data generated by the moose model was used to train the convolutional neural network to reconstruct the vessel wall's outer surface temperature. The CNN generalization was then compared against the experimental and computational data.

Aldeia Machado, Luiz Carlos

Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

Schenker, Paul S.

Predicting Pulsed-Laser Deposition SrTiO 3 Homoepitaxy Growth Dynamics Using High-Speed Reflection High-Energy Electron Diffraction

Pulsed-laser deposition (PLD) is a powerful technique for growing complex oxides with controlled stoichiometry. To understand growth dynamics therein, it is common to leverage in situ spectroscopies, such as reflection high-energy electron diffraction (RHEED), to monitor surface crystallinity. Most commercial systems rely on video-rate cameras operating at 60-120 Hz that lack sufficient temporal resolution to capture growth dynamics at practical deposition frequencies. Here, a high-speed platform to record in situ dynamics via RHEED at >500 Hz is implemented. An open-source analysis package is designed to fit diffraction spots to 2D Gaussians, allowing single-pulse surface reconstruction kinetics extraction. Using homoepitaxially deposited (001)-oriented SrTiO 3 as a model system, we demonstrate how high-speed RHEED can provide real-time insight into growth processes obscured by slower acquisition systems. By fitting the single-pulse intensity to a set of exponential functions, we observe changes in the characteristic decay time and mechanism correlated to the substrate step width and surface termination. We observe distinct surface effects, with diffraction intensity decaying on lower-energy TiO 2 -terminated surfaces and stabilizing on SrO- or mixed-terminated surfaces. Similarly, using an exponential model, the extracted characteristic time of adatom deposition decreases with increased density of bonding sites associated with mixed termination and narrower step widths. Ultimately, this work shows how increasing RHEED temporal resolution can uncover new insights into growth processes, with practical implications for the design and control of PLD processes. This experimental platform provides new capabilities to enable data-driven machine learning analysis and autonomous control systems to enhance the complexity and fecundity of PLD.

(SrO)

The surface structure of titanium and its interaction with bromine and chlorine

The surface structure and composition of titanium have been studied by electron diffraction and Auger electron spectroscopy in the temperature range 25 to 850 C. Atomically clean, well-defined Ti surfaces were obtained by a combination of argon ion sputtering and thermal treatment at 700 to 800 C. A series of surface superstructures was observed as the crystal temperature was gradually decreased. The development of the superstructures is best explained as due to surface reconstruction as a result of surface relaxation. The interaction of bromine and chlorine vapors with clean Ti surfaces was investigated in the temperature range 25 to 500 C. Bromine exposure at room temperature gave rise to an amorphous surface layer, which on annealing transformed into an epitaxial TiBr2 structure. Chlorine interaction resulted in the formation of an epitaxial TiCl3 on both cold and hot Ti surfaces. Surface impurities inhibited the chemical interaction process on the Ti surface.

Khan, I. H.

A Reduced-Temperature Process for Preparing Atomically Clean Si(100) and SiGe(100) Surfaces with Vapor HF

Silicon processing techniques such as atomic precision advanced manufacturing (APAM) and epitaxial growth require surface preparations that activate oxide desorption (typically >1000 °C) and promote surface reconstruction toward atomically clean, flat, and ordered Si(100)-2 × 1. Here, in this study, we compare the aqueous and vapor phase cleaning of Si and Si/SiGe surfaces to prepare APAM-ready and epitaxy-ready surfaces at lower temperatures. Angle resolved X-ray photoelectron spectroscopy (ARXPS) and Fourier transform infrared (FTIR) spectroscopy indicate that vapor hydrogen fluoride (VHF) cleans dramatically reduce carbon surface contamination and allow the chemically prepared surface to reconstruct at lower temperatures, 600 °C for Si and 580 °C for a Si/Si 0.7 Ge 0.3 heterostructure, into an ordered atomic terrace structure indicated by scanning tunneling microscopy (STM). After thermal treatment and vacuum hydrogen termination, we demonstrate STM hydrogen desorption lithography (HDL) on VHF-treated Si samples, creating reactive zones that enable area-selective chemistry by using a thermal budget similar to CMOS process flows. We anticipate that these results will establish new pathways to integrate APAM with Si foundry processing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Surface structure of Sn doped β-Ga 2 O 3 (010) p(1×1) studied by quantitative low energy electron diffraction

Here, we have studied the surface structure of a single crystal β-Ga 2 O 3 (010) using quantitative Low Energy Electron Diffraction (LEED) and X-ray photoelectron spectroscopy (XPS). The XPS measurements show spectra typical of stoichiometric Ga 2 O 3 with a clean surface. LEED consistently shows a p(1x1) pattern, free of surface reconstruction. Quantitative LEED I(V) curves are acquired for 41 distinct diffraction spots. The experimental I(V) curves are compared to simulations over the first five layers. The best fits to the experimental LEED I(V) curves acquired at all diffraction spots are then used to calculate the interplanar relaxation and atomic rumpling. Significant atomic rumpling and interplanar relaxation are found over the first 5 atomic layers. As a result of rumpling a polarization of ~ 2 μC/cm 2 develops in the topmost surface layer. The structural results are in good agreement with previous density functional theory calculations and experimental X-ray photoelectron diffraction.

36 MATERIALS SCIENCE

Cu–Ni Oxidation Mechanism Unveiled: A Machine Learning-Accelerated First-Principles and in Situ TEM Study

Here, the development of accurate methods for determining how alloy surfaces spontaneously restructure under reactive and corrosive environments is a key, long-standing, grand challenge in materials science. Using machine learning-accelerated density functional theory and rare-event methods, in conjunction with in situ environmental transmission electron microscopy (ETEM), we examine the interplay between surface reconstructions and preferential segregation tendencies of CuNi(100) surfaces under oxidation conditions. Our modeling approach predicts that oxygen-induced Ni segregation in CuNi alloys favors Cu(100)-O c(2 × 2) reconstruction and destabilizes the Cu(100)-O (2√2 × √2)R45° missing row reconstruction (MRR). In situ ETEM experiments validate these predictions and show Ni segregation followed by NiO nucleation and growth in regions without MRR, with secondary nucleation and growth of Cu 2 O in MRR regions. Our approach based on combining disparate computational components and in situ ETEM provides a holistic description of the oxidation mechanism in CuNi, which applies to other alloy systems.

36 MATERIALS SCIENCE

Catalyst Deactivation Modes of PdO/γ-Al 2 O 3 Catalysts for Lean Methane Oxidation

PdO/γ-Al 2 O 3 catalysts are one of the most active catalytic components for the complete oxidation of methane. Under reaction conditions, especially in a wet feed, the catalysts suffer severe performance degradation. This study establishes a series of testing protocols to systematically investigate the causes of catalyst deactivation under methane oxidation reaction conditions. Four distinct catalyst deactivation modes are identified. Two of the deactivation modes are directly related to H 2 O, either from the feed gas or as a part of the reaction products, with one (Mode 2) being attributed to the formation of surface hydroxyl groups and the other (Mode 3) to the competitive adsorption of H 2 O on the catalysts. The impact of the two deactivation modes is acute and severe but reversible. In contrast, the other two deactivation modes are gradual and persistent but irreversible. Both modes are induced by CH 4 oxidation reaction, with the impact of a wet feed (Mode 4) being substantially more severe than that of a dry feed (Mode 1). The major cause of the irreversible catalyst deactivation is attributed to surface reconstruction of PdO nanoparticles, which behaves as a passivation layer lowering the number of coordinately unsaturated Pd sites for CH 4 activation. Although the passivation layer is relatively stable against thermal or hydrothermal treatment, it is not completely inert. Formation and partial regeneration of the passivation layer is a highly dynamic process and heavily depends on the reaction temperature: a lower reaction temperature (≤ 450 ℃) can lead to quicker catalyst deactivation; but a higher reaction temperature (between 500 – 550 ℃) can result in a greater extent of catalyst deactivation.

PdO/γ-Al2O3

Unraveling the Surface Termination and Evolution of Surface States for Electrocatalyst PtSn 4 in Alkaline HER

Semimetal PtSn 4 has been experimentally demonstrated as a promising topological electrocatalyst for the hydrogen evolution reaction (HER) under both acidic and alkaline conditions. While two possible mechanisms have been proposed to explain its activity, the role of its surface states in HER remains unclear. It is indeed in question how the surface states of this alloy evolve as HER proceeds. In this study, we investigate the surface termination that sustains conducting surface states on PtSn 4 , and we track their evolution during HER catalysis. We show that a reconstructed surface with a Sn-poor termination reproduces the scanning tunneling microscopy pattern observed in experiments and sustains a conducting surface. Through phase diagram and geometric structure analysis, we outline the HER profile following the Volmer–Heyrovsky mechanism. As hydrogen atoms adsorb onto the surface, the structure undergoes further reconstruction to an equilibrium phase with a coverage of two hydrides per unit cell. Meanwhile, the surface electronic bands evolve in response to interactions with the adsorbed hydrogen atoms. A hybridization diagram is further proposed for understanding the surface state evolution based on wave function and chemical bonding analyses. While the Pt atoms serve as conventional sites for hydrogen binding, the surface states of PtSn 4 are essential for stabilizing the hydrogen antibonding states via in-phase electronic interactions with the Sn components. This stabilization results in frontier surface bands that are responsible for driving the HER catalysis. Here, our findings provide a detailed description for the direct involvement of surface states on PtSn4 when employed as a catalyst for HER.

catalysts

Dual roles of stepped surfaces: Catalytic initiators and stabilizers of oxygen-induced reconstructions

Understanding surface restructuring under reactive conditions is crucial for designing next-generation catalysts with enhanced activity and selectivity. Here, we employ in situ transmission electron microscopy to directly observe the dynamic behavior of Cu(100) and Cu(410) surfaces under both oxidizing and vacuum annealing conditions, revealing a complex interplay among surface crystallography, local oxygen coverage, Cu atom mobility, and step-edge reactivity. The stepped Cu(410) surface acts as an active site for O 2 dissociation, triggering the oscillatory transformation of the c(2 × 2)–O phase into the more stable (2$\sqrt2$ ×$\sqrt2$)R45°–O missing-row (MR) structure on the adjacent flat Cu(100) terrace. Under subsequent vacuum annealing, this same Cu(410) facet exhibits remarkable structural resilience, preserving the MR reconstruction and chemisorbed oxygen. In contrast, the Cu(100) surface undergoes reversible transitions from the MR structure back to the c(2 × 2)–O phase. These results highlight the critical role of surface morphology in directing both the formation and stability of oxygen-induced reconstructions, demonstrating that stepped surfaces serve dual roles as both catalytic initiators and structural stabilizers. Furthermore, this work offers atomic-level insights into the environment-responsive behavior of copper surfaces, establishing a mechanistic basis for designing Cu-based catalysts through facet-specific control of surface reactivity.

36 MATERIALS SCIENCE

Facile synthesis of Co(OH)2 nanoneedle arrays grown on stainless steel for industrial electrochemical oxygen evolution reaction

The electrochemical oxygen evolution reaction (OER) is a critical half-reaction in a variety of energy conversion and storage applications, however, OER suffers from sluggish kinetics due to the four proton-electron transfer processes. To remedy this, interfacial engineering proves an effective strategy to design high active OER catalysts. Herein, we report a facile synthesis of Co(OH)2 nanoneedle (Co-NN) arrays grown on stainless steel (SS) via a one-step hydrothermal reaction, and the resultant impressive OER performance. Particularly, the Co-NN/SS needs 267, 307, and 576 mV overpotentials to reach 10, 100, and 1000 mA cm−2 in 1 M KOH & room temperature, and the overpotentials drop to 199, 257, and 283 mV to achieve the same current densities in 30 wt% KOH & 80 °C. Additionally, an alkaline water electrolysis (AWE) cell coupled with Co-NN/SS anode and PtRu/NiMo cathode only requires 1.65 and 1.73 V iR-free cell voltage to reach 1.0 and 2.0 A cm−2, respectively. The sterling OER performance could be attributed to four possible reasons, the Fe in SS surface tailoring the electronic properties of Co(OH)2, the mixed metal oxides on SS surface accelerating surface reconstruction of Co(OH)2 nanoneedles into CoOOH active species, a Ni-rich surface layer formation cooperatively boosting the OER activity, and a local electric field effect concentrating reactants on the tip surface and accelerating the mass transfer. This work provides a facile approach for synthesizing highly efficient OER catalysts for industrial applications by interfacial engineering.

Lyu, Xiang [ORNL] (ORCID:0000000208673248)

Multiple image SAR shape-from-shading

A technique for combining radar image shape-from-shading with stereo radargrammetry to produce terrain surface models using multiple SAR images is described. This technique is expected to be of use to reconstruct surface shape from Magellan images of planet Venus, and to refine the results of terrestrial radar measurements. Local variation in pixel shading is an indicator of terrain slope changes. This variation in pixel shading offers an opportunity for increasing the detail of terrain mapping over that which is available from stereo radargrammetry alone. Shape-from-shading can potentially provide a relative change in height at each pixel. This leads to a dense set of height measurements and a more faithful rendition of the local terrain shapes. However, shape-from-shading needs some type of boundary values or external terrain low-frequency information to succeed. These can be obtained from stereo or from altimeter measurements.

Thomas, J.