MYTHOS: A Python Interface for Surface Crystal Structure Prediction of Organic Semiconductors
We introduce a new computational approach for predicting organic crystalline structures on flat surfaces, an essential step in designing and optimizing thin-film systems for electronic devices. Based on molecular mechanics and molecular dynamics simulations, and implemented in a user-friendly Python...
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| Veröffentlicht in: | Journal of chemical information and modeling Jg. 65; H. 14; S. 7619 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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United States
28.07.2025
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| ISSN: | 1549-960X, 1549-960X |
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| Abstract | We introduce a new computational approach for predicting organic crystalline structures on flat surfaces, an essential step in designing and optimizing thin-film systems for electronic devices. Based on molecular mechanics and molecular dynamics simulations, and implemented in a user-friendly Python program, this method enables a sequential layer-by-layer analysis of crystalline formation, thus allowing to identify surface-induced polymorphs (SIPs) and to study the transition between surface and bulk structures. A validation against six diverse test cases demonstrated a good match with experimental crystalline parameters and arrangements, underscoring the reliability of the method in identifying the most relevant polymorphs for a given molecule. |
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| AbstractList | We introduce a new computational approach for predicting organic crystalline structures on flat surfaces, an essential step in designing and optimizing thin-film systems for electronic devices. Based on molecular mechanics and molecular dynamics simulations, and implemented in a user-friendly Python program, this method enables a sequential layer-by-layer analysis of crystalline formation, thus allowing to identify surface-induced polymorphs (SIPs) and to study the transition between surface and bulk structures. A validation against six diverse test cases demonstrated a good match with experimental crystalline parameters and arrangements, underscoring the reliability of the method in identifying the most relevant polymorphs for a given molecule. We introduce a new computational approach for predicting organic crystalline structures on flat surfaces, an essential step in designing and optimizing thin-film systems for electronic devices. Based on molecular mechanics and molecular dynamics simulations, and implemented in a user-friendly Python program, this method enables a sequential layer-by-layer analysis of crystalline formation, thus allowing to identify surface-induced polymorphs (SIPs) and to study the transition between surface and bulk structures. A validation against six diverse test cases demonstrated a good match with experimental crystalline parameters and arrangements, underscoring the reliability of the method in identifying the most relevant polymorphs for a given molecule.We introduce a new computational approach for predicting organic crystalline structures on flat surfaces, an essential step in designing and optimizing thin-film systems for electronic devices. Based on molecular mechanics and molecular dynamics simulations, and implemented in a user-friendly Python program, this method enables a sequential layer-by-layer analysis of crystalline formation, thus allowing to identify surface-induced polymorphs (SIPs) and to study the transition between surface and bulk structures. A validation against six diverse test cases demonstrated a good match with experimental crystalline parameters and arrangements, underscoring the reliability of the method in identifying the most relevant polymorphs for a given molecule. |
| Author | Pfeiffer, Martin Lorini, Emilio Walzer, Karsten Muccioli, Luca |
| Author_xml | – sequence: 1 givenname: Emilio orcidid: 0000-0002-3405-2701 surname: Lorini fullname: Lorini, Emilio organization: Department of Industrial Chemistry, University of Bologna, Via Piero Gobetti, 85, 40129 Bologna, Italy – sequence: 2 givenname: Karsten surname: Walzer fullname: Walzer, Karsten organization: Heliatek GmbH, Treidlerstraße 3, 01139 Dresden, Germany – sequence: 3 givenname: Martin surname: Pfeiffer fullname: Pfeiffer, Martin organization: Heliatek GmbH, Treidlerstraße 3, 01139 Dresden, Germany – sequence: 4 givenname: Luca orcidid: 0000-0001-9227-1059 surname: Muccioli fullname: Muccioli, Luca organization: Department of Industrial Chemistry, University of Bologna, Via Piero Gobetti, 85, 40129 Bologna, Italy |
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| SubjectTerms | Crystallization Molecular Dynamics Simulation Organic Chemicals - chemistry Semiconductors Software Surface Properties |
| Title | MYTHOS: A Python Interface for Surface Crystal Structure Prediction of Organic Semiconductors |
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