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A Machine‐Learning‐Based Approach for Solving Atomic Structures of Nanomaterials Combining Pair Distribution Functions with Density Functional Theory (Adv. Mater. 13/2023). Issue 13 (29th March 2023)
Record Type:
Journal Article
Title:
A Machine‐Learning‐Based Approach for Solving Atomic Structures of Nanomaterials Combining Pair Distribution Functions with Density Functional Theory (Adv. Mater. 13/2023). Issue 13 (29th March 2023)
Main Title:
A Machine‐Learning‐Based Approach for Solving Atomic Structures of Nanomaterials Combining Pair Distribution Functions with Density Functional Theory (Adv. Mater. 13/2023)
Abstract : Atomic Structure Prediction In article number 2208220, Bo B. Iversen, Bjørk Hammer, Wilke Dononelli, and co‐workers present a new machine‐learning‐based approach, which combines pair distribution functions with density functional theory, for solving atomic structures of nanomaterials.