Atomic steps, a defect common to all crystal surfaces, can play an important role in many physical and chemical processes. However, attempts to predict surface dynamics under nonequilibrium conditions are usually frustrated by poor knowledge of the atomic processes of surface motion arising from mass transport from/to surface steps. Using low-energy electron microscopy that spatially and temporally resolves oxide film growth during the oxidation of NiAl(100) we demonstrate that surface steps are impermeable to oxide film growth. The advancement of the oxide occurs exclusively on the same terrace and requires the coordinated migration of surface steps. The resulting piling up of surface steps ahead of the oxide growth front progressively impedes the oxide growth. This process is reversed during oxide decomposition. The migration of the substrate steps is found to be a surface-step version of the well-known Hele-Shaw problem, governed by detachment (attachment) of Al atoms at step edges induced by the oxide growth (decomposition). By comparing with the oxidation of NiAl(110) that exhibits unimpeded oxide film growth over substrate steps we suggest that whenever steps are the source of atoms used for oxide growth they limit the oxidation process; when atoms are supplied from the bulk, the oxidation rate is not limited by the motion of surface steps.
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http://dx.doi.org/10.1073/pnas.1420690112 | DOI Listing |
Prev Sci
January 2025
Faculty of Nursing, Physiotherapy, and Podiatry, Department of Nursing, Universidad de Sevilla, Avenzoar Street, 6, 41009, Seville, Spain.
Adolescence is a critical period for developing risk behaviors such as substance use, which can impact health in adulthood. Culturally adapted evidence-based programs (EBPs) are promising for prevention. This review explores the processes for culturally adapting EBPs targeting alcohol, tobacco, or cannabis use, and/or anxiety or depression in adolescents.
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State Key Laboratory of Coordination Chemistry, Key Laboratory of Mesoscopic Chemistry of Ministry of Education, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China.
The applications of machine learning (ML) in complex interfacial interactions are hindered by the time-consuming process of manual feature selection and model construction. An automated ML program was implemented with four subsequent steps: data distribution analysis, dimensionality reduction and clustering, feature selection, and model optimization. Without the need of manual intervention, the descriptors of metal charge variance (Δ) and electronegativity of substrate (χ) and metal (δχ) were raised up with good performance in predicting electrochemical reaction energies for both nitrogen reduction reaction (NRR) and CO reduction reaction (CORR) on metal-zeolites and MoS surfaces.
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Center for Nanoscience and Nanotechnology, Tel Aviv University, Tel Aviv-Yafo, Israel.
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View Article and Find Full Text PDFJ Phys Chem Lett
January 2025
Graduate School of Science and Engineering, Kindai University, 3-4-1 Kowakae, Higashiosaka, Osaka 577-8502, Japan.
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