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Machine learning-guided accelerated discovery of structure-property correlations in lean magnesium alloys for biomedical applications

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Journal of Magnesium and Alloys 2024年第6期12卷 2267-2283页

作者： Sreenivas Raguraman Maitreyee Sharma Priyadarshini Tram Nguyen Ryan McGovern Andrew Kim Adam J.Griebel paulette clancy Timothy P.Weihs Department of Materials Science and Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Hopkins Extreme Materials Institute Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Department of Chemical and Biomolecular Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Translational Tissue Engineering Center Johns Hopkins School of Medicine400 N BroadwayBaltimore21231MDU.S.A Department of Biomedical Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Research and Development Fort Wayne Metals Research ProductsLLC9609 Ardmore AveFort Wayne46809INU.S.A Department of Mechanical Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A

Magnesium alloys are emerging as promising alternatives to traditional orthopedic implant materials thanks to their biodegradability,biocompatibility,and impressive mechanical ***,their rapid in-vivo degradation presents challenges,notably in upholding mechanical integrity over *** study investigates the impact of high-temperature thermal processing on the mechanical and degradation attributes of a lean Mg-Zn-Ca-Mn alloy,*** rapid,cost-efficient characterization methods like X-ray diffraction and optical microscopy,we swiftly examine microstructural changes post-thermal *** Pearson correlation coefficient analysis,we unveil the relationship between microstructural properties and critical targets(properties):hardness and corrosion ***,leveraging the least absolute shrinkage and selection operator(LASSO),we pinpoint the dominant microstructural factors among closely correlated *** findings underscore the significant role of grain size refinement in strengthening and the predominance of the ternary Ca_(2)Mg_(6)Zn_(3)phase in corrosion *** suggests that achieving an optimal blend of strength and corrosion resistance is attainable through fine grains and reduced concentration of ternary *** thorough investigation furnishes valuable insights into the intricate interplay of processing,structure,and properties in magnesium alloys,thereby advancing the development of superior biodegradable implant materials.

关键词： Magnesium alloys Machine learning Corrosion Mechanical properties Rapid characterization

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Efficient search of compositional space for hybrid organic-inorganic perovskites via Bayesian optimization

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npj Computational Materials 2018年第1期4卷 232-238页

作者： Henry C.Herbol Weici Hu Peter Frazier paulette clancy Matthias Poloczek Department of Materials Science and Engineering Cornell UniversityIthacaNYUSA School of Operations Research and Information Engineering Cornell UniversityIthacaNYUSA Robert F.Smith School of Chemical and Biomolecular Engineering Cornell UniversityIthacaNYUSA Department of Systems and Industrial Engineering University of ArizonaTucsonAZUSA

Accelerated searches,made possible by machine learning techniques,are of growing interest in materials discovery.A suitable case involves the solution processing of components that ultimately form thin films of solar cell materials known as hybrid organic–inorganic perovskites(HOIPs).The number of molecular species that combine in solution to form these films constitutes an overwhelmingly large“compositional”space(at times,exceeding 500,000 possible combinations).Selecting a HOIP with desirable characteristics involves choosing different cations,halides,and solvent blends from a diverse palette of *** unguided search by experimental investigations or molecular simulations is prohibitively *** this work,we propose a Bayesian optimization method that uses an application-specific kernel to overcome challenges where data is scarce,and in which the search space is given by binary variables indicating whether a constituent is present or *** demonstrate that the proposed approach identifies HOIPs with the targeted maximum intermolecular binding energy between HOIP salt and solvent at considerably lower cost than previous state-of-the-art Bayesian optimization methodology and at a fraction of the time(less than 10%)needed to complete an exhaustive *** find an optimal composition within 15±10 iterations in a HOIP compositional space containing 72 combinations,and within 31±9 iterations when considering mixed halides(240 combinations).Exhaustive quantum mechanical simulations of all possible combinations were used to validate the optimal prediction from a Bayesian optimization *** paper demonstrates the potential of the Bayesian optimization methodology reported here for new materials discovery.

关键词： optimization inorganic perovskite

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Pentacene-based nanorods on Au（111） single crystals： Charge transfer, diffusion, and step-edge barriers

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Nano Research 2013年第6期6卷 449-459页

作者： Sabine-Antonia Savu Sabine Abb Simon Schundelmeier Jonathan D. Saathoff James M. Stevenson Christina Tonshoff Holger F. Bettinger paulette clancy M. Benedetta Casu Thomas Chasse Institute of Physical and Theoretical Chemistry University of Tuebingen Aufder Morgenstelle 18 72076 Tuebingen Germany School of Chemical and Biomolecular Engineering Cornel/University Ithaca New York 14853 USA Institute of Organic Chemistry University of Tuebingen Auf der Morgenstelle 18 72076 Tuebingen Germany

We investigate nanorod assemblies of two 64-substituted pentacenes, namely （2,3-X2-9,10-Y2）-substituted pentacenes with X -- Y = OCH3 （MOP） and with X = F, Y-- OCH3 （MOPF）, grown on Au（111） single crystals. By using a multi-technique approach based on ultraviolet photoelectron spectroscopy X-ray photoelectron spectroscopy; and X-ray absorption, we find evidence for charge transfer screening at the interface with gold. Furthermore, the MOP and MOPF nanorods show a rough surface morphology, which was investigated with atomic force microscopy. We use molecular simulation techniques to investigate the energetic barriers to diffusion and to traverse step-edges to estimate their influence on the nanorod roughness. We find that barriers to surface diffusion on a terrace are anisotropic and that their direction favors the formation of nanorods in these materials.

关键词： nanorod assembly substituted pentacene electronic structures/ processes/mechanisms organic electronics charge transfer diffusion and step-edge barrier

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