Advanced Materials, volume 36, issue 44

Machine Learning‐Enabled Tomographic Imaging of Chemical Short‐Range Atomic Ordering (Adv. Mater. 44/2024)

Yue Li ¹

Timoteo Colnaghi ²

Yilun Gong ^{1, 3}

Huaide Zhang ⁴

Yu Yuan ⁴

Ye Wei ⁵

Bin Gan ⁶

Min Song ⁷

Andreas Marek ²

Markus Rampp ²

Siyuan Zhang ¹

Zongrui Pei ⁸

Matthias Wuttig ⁴

Sheuly Ghosh ¹

Fritz Körmann ^{1, 9}

Jörg Neugebauer ¹

Zhangwei Wang ⁷

Baptiste Gault ^{1, 10}

Show full list: 18 authors

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Max‐Planck‐Institut für Eisenforschung GmbH Max‐Planck‐Straße 1 40237 Düsseldorf Germany |

Max Planck Computing and Data Facility Gießenbachstraße 2 85748 Garching Germany |

Department of Materials University of Oxford Parks Road Oxford OX1 3PH UK |

⁴

Institute of Physics (IA) RWTH Aachen University 52056 Aachen Germany |

⁵

Ecole Polytechnique Fédérale de Lausanne School of Engineering Rte Cantonale Lausanne 1015 Switzerland |

⁶

Suzhou Laboratory No.388, Ruoshui Street, SIP Jiangsu 215123 China |

⁷

State Key Laboratory of Powder Metallurgy Central South University Changsha 410083 China |

⁸

New York University New York NY 10012 USA |

⁹

Materials Informatics BAM Federal Institute for Materials Research and Testing Richard‐Willstätter‐Str. 11 12489 Berlin Germany |

¹⁰

Department of Materials Imperial College South Kensington London SW7 2AZ UK |

Publication type: Journal Article

Publication date: 2024-11-01

Wiley

Journal: Advanced Materials

scimago Q1

SJR: 9.191

CiteScore: 43.0

Impact factor: 27.4

ISSN: 09359648, 15214095

DOI: 10.1002/adma.202470347

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Publisher

Wiley

Journal

Advanced Materials

scimago Q1

SJR

9.191

CiteScore

43.0

Impact factor

27.4

ISSN

09359648 (Print)

15214095 (Electronic)