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    <title language="eng">Machine learning‐enabled tomographic imaging of chemical short‐range atomic ordering</title>
    <abstract language="eng">In solids, chemical short‐range order (CSRO) refers to the self‐organization of atoms of certain species occupying specific crystal sites. CSRO is increasingly being envisaged as a lever to tailor the mechanical and functional properties of materials. Yet quantitative relationships between properties and the morphology, number density, and atomic configurations of CSRO domains remain elusive. Herein, it is showcased how machine learning‐enhanced atom probe tomography (APT) can mine the near‐atomically resolved APT data and jointly exploit the technique's high elemental sensitivity to provide a 3D quantitative analysis of CSRO in a CoCrNi medium‐entropy alloy. Multiple CSRO configurations are revealed, with their formation supported by state‐of‐the‐art Monte‐Carlo simulations. Quantitative analysis of these CSROs allows establishing relationships between processing parameters and physical properties. The unambiguous characterization of CSRO will help refine strategies for designing advanced materials by manipulating atomic‐scale architectures.</abstract>
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    <abstract language="eng">AbstractThe impact of magnetism on chemical ordering in face-centered cubic CrCoNi medium entropy alloy is studied by a combination of ab initio simulations, machine learning potentials, and Monte Carlo simulations. Large magnetic energies are revealed for some mixed L12/L10 type ordered configurations, which are rooted in strong nearest-neighbor magnetic exchange interactions and chemical bonding among the constituent elements. There is a delicate interplay between magnetism and stability of MoPt2 and L12/L10 type of order, which may explain opposing experimental and theoretical findings.</abstract>
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    <abstract language="eng">The impact of magnetism on chemical ordering in face-centered cubic CrCoNi medium entropy alloy is studied by a combination of ab initio simulations, machine learning potentials, and Monte Carlo simulations. Large magnetic energies are revealed for some mixed L12 /L10 type ordered configurations, which are rooted in strong nearest-neighbor magnetic exchange interactions and chemical bonding among the constituent elements. There is a delicate interplay between magnetism and stability of MoPt2 and L12 /L10 type of ordering which may explain opposing experimental and theoretical findings.</abstract>
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    <author>Sheuly Ghosh</author>
    <author>Katharina Ueltzen</author>
    <author>Janine George</author>
    <author>Jörg Neugebauer</author>
    <author>Fritz Körmann</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Bonding analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Alloys</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Magnetism</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Material design</value>
    </subject>
    <collection role="ddc" number="620">Ingenieurwissenschaften und zugeordnete Tätigkeiten</collection>
    <collection role="institutes" number="">6 Materialchemie</collection>
    <collection role="themenfelder" number="">Material</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
    <collection role="unnumberedseries" number="">Arbeitspapiere der BAM</collection>
    <collection role="institutes" number="">6.0 Abteilungsleitung und andere</collection>
    <collection role="themenfelder" number="">Materialdesign</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
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