Bi‐Functional On‐Surface Molecular Assemblies Predicted From a Multifaceted Computational Approach
Abstract Molecular self‐assembly will not become a routine method for building nanomaterials unless our ability to predict the outcome of this process is dramatically improved. Even then, reliable strategies for realizing molecular assemblies with novel functionality are required for building nanoma...
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| Format: | Article |
| Language: | English |
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Wiley-VCH
2022-12-01
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| Series: | Advanced Physics Research |
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| Online Access: | https://doi.org/10.1002/apxr.202200019 |
| _version_ | 1797775053882916864 |
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| author | Daniel M. Packwood |
| author_facet | Daniel M. Packwood |
| author_sort | Daniel M. Packwood |
| collection | DOAJ |
| description | Abstract Molecular self‐assembly will not become a routine method for building nanomaterials unless our ability to predict the outcome of this process is dramatically improved. Even then, reliable strategies for realizing molecular assemblies with novel functionality are required for building nanomaterials for specific device applications. On the basis of a multifaceted computational approach that integrates several state‐of‐the‐art methods, this paper predicts that bi‐functional on‐surface assemblies of metal phthalocyanine molecules can be realized through the simple strategy of introducing asymmetry into the phthalocyanine ligands. This bi‐functionality arises from a combination of antiferromagnetic ordering within the assembly and presence of locally fluctuating magnetic moments, and has potential applications as non‐Gaussian noise sources in nanodevices. |
| first_indexed | 2024-03-12T22:29:26Z |
| format | Article |
| id | doaj.art-4125dfa7022d4916b79ba7e1e4945649 |
| institution | Directory Open Access Journal |
| issn | 2751-1200 |
| language | English |
| last_indexed | 2024-03-12T22:29:26Z |
| publishDate | 2022-12-01 |
| publisher | Wiley-VCH |
| record_format | Article |
| series | Advanced Physics Research |
| spelling | doaj.art-4125dfa7022d4916b79ba7e1e49456492023-07-21T15:30:35ZengWiley-VCHAdvanced Physics Research2751-12002022-12-0111n/an/a10.1002/apxr.202200019Bi‐Functional On‐Surface Molecular Assemblies Predicted From a Multifaceted Computational ApproachDaniel M. Packwood0Institute for Integrated Cell‐Material Sciences (iCeMS) Kyoto University Kyoto 606‐8502 JapanAbstract Molecular self‐assembly will not become a routine method for building nanomaterials unless our ability to predict the outcome of this process is dramatically improved. Even then, reliable strategies for realizing molecular assemblies with novel functionality are required for building nanomaterials for specific device applications. On the basis of a multifaceted computational approach that integrates several state‐of‐the‐art methods, this paper predicts that bi‐functional on‐surface assemblies of metal phthalocyanine molecules can be realized through the simple strategy of introducing asymmetry into the phthalocyanine ligands. This bi‐functionality arises from a combination of antiferromagnetic ordering within the assembly and presence of locally fluctuating magnetic moments, and has potential applications as non‐Gaussian noise sources in nanodevices.https://doi.org/10.1002/apxr.202200019density functional theorymachine learningself‐assemblysimulationssurfaces |
| spellingShingle | Daniel M. Packwood Bi‐Functional On‐Surface Molecular Assemblies Predicted From a Multifaceted Computational Approach Advanced Physics Research density functional theory machine learning self‐assembly simulations surfaces |
| title | Bi‐Functional On‐Surface Molecular Assemblies Predicted From a Multifaceted Computational Approach |
| title_full | Bi‐Functional On‐Surface Molecular Assemblies Predicted From a Multifaceted Computational Approach |
| title_fullStr | Bi‐Functional On‐Surface Molecular Assemblies Predicted From a Multifaceted Computational Approach |
| title_full_unstemmed | Bi‐Functional On‐Surface Molecular Assemblies Predicted From a Multifaceted Computational Approach |
| title_short | Bi‐Functional On‐Surface Molecular Assemblies Predicted From a Multifaceted Computational Approach |
| title_sort | bi functional on surface molecular assemblies predicted from a multifaceted computational approach |
| topic | density functional theory machine learning self‐assembly simulations surfaces |
| url | https://doi.org/10.1002/apxr.202200019 |
| work_keys_str_mv | AT danielmpackwood bifunctionalonsurfacemolecularassembliespredictedfromamultifacetedcomputationalapproach |