Self-organizing maps as a data-driven approach to elucidate the packing motifs of perylene diimide derivatives-Reference-Cited by-同舟云学术

Self-organizing maps as a data-driven approach to elucidate the packing motifs of perylene diimide derivatives

Published:2023 Issue:4 Volume:8 Page:500-515
ISSN:2058-9689
Container-title:Molecular Systems Design & Engineering
language:en
Short-container-title:Mol. Syst. Des. Eng.

Author:

Marin Francesco¹,Zappi Alessandro¹^ORCID,Melucci Dora¹,Maini Lucia¹^ORCID

Affiliation:

1. Dipartimento di Chimica ‘G. Ciamician’, Università di Bologna, via Selmi 2, 40126 Bologna, Italy

Abstract

The efficient classification or prediction of crystal structures into a small number of families of related structures can be extremely important in the design of materials with specific packing and properties.

Publisher

Royal Society of Chemistry (RSC)

Subject

Materials Chemistry,Industrial and Manufacturing Engineering,Process Chemistry and Technology,Energy Engineering and Power Technology,Biomedical Engineering,Chemical Engineering (miscellaneous),Chemistry (miscellaneous)

Link

http://pubs.rsc.org/en/content/articlepdf/2023/ME/D2ME00240J

Reference65 articles.

1. Charge Transport in Organic Semiconductors

2. n-Type Organic Semiconductors in Organic Electronics

3. Enhancing the Charge Transport in Solution-Processed Perylene Di-imide Transistors via Thermal Annealing of Metastable Disordered Films

4. Organic Optoelectronic Materials: Mechanisms and Applications

5. Organic semiconductor crystals

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