TY - JOUR
T1 - Data Mining for Parameters Affecting Polymorph Selection in Contorted Hexabenzocoronene Derivatives
AU - Hiszpanski, Anna M.
AU - Dsilva, Carmeline J.
AU - Kevrekidis, Ioannis G.
AU - Loo, Yueh Lin
N1 - Funding Information:
We thank Dr. Arthur Woll (Cornell High Energy Synchrotron Source) for his assistance with GIXD experiments and Dr. Matthew Bruzek and Prof. John Anthony (University of Kentucky, Lexington) for providing the fluorinated pentacene quinone precursor used in the synthesis of fluorinated cHBC derivatives (NSF DMR-1035217). This work was supported by the NSF MRSEC program through the Princeton Center for Complex Materials (DMR-1420451) and the DMREF Program (DMR-DMR-1627453). GIXD experiments were conducted at CHESS, which is supported by NSF and NIH/NIGMS under award DMR-1332208. A.M.H. acknowledges support through the National Defense Science and Engineering Graduate (NDSEG) Fellowship (Air Force Office of Scientific Research 32 CFR 168a). Lawrence Livermore National Laboratory is operated by Lawrence Livermore National Security, LLC, for the U.S. Department of Energy, National Nuclear Security Administration under Contract DE-AC52-07NA27344. LLNL-JRNL-739547.
Publisher Copyright:
Copyright © 2018 American Chemical Society.
PY - 2018/5/22
Y1 - 2018/5/22
N2 - The macroscopic properties of molecular materials can be drastically influenced by their solid-state packing arrangements, of which there can be many (e.g., polymorphism). Strategies to controllably and predictively access select polymorphs are thus highly desired, but computationally predicting the conditions necessary to access a given polymorph is challenging with the current state of the art. Using derivatives of contorted hexabenzocoronene, cHBC, we employed data mining, rather than first-principles approaches, to find relationships between the crystallizing molecule, postdeposition solvent-vapor annealing conditions that induce polymorphic transformation, and the resulting polymorphs. This analysis yields a correlative function that can be used to successfully predict the appearance of either one of two polymorphs in thin films of cHBC derivatives. Within the postdeposition processing phase space of cHBC derivatives, we have demonstrated an approach to generate guidelines to select crystallization conditions to bias polymorph access. We believe this approach can be applied more broadly to accelerate the predictions of processing conditions to access desired molecular polymorphs, making progress toward one of the grand challenges identified by the Materials Genome Initiative.
AB - The macroscopic properties of molecular materials can be drastically influenced by their solid-state packing arrangements, of which there can be many (e.g., polymorphism). Strategies to controllably and predictively access select polymorphs are thus highly desired, but computationally predicting the conditions necessary to access a given polymorph is challenging with the current state of the art. Using derivatives of contorted hexabenzocoronene, cHBC, we employed data mining, rather than first-principles approaches, to find relationships between the crystallizing molecule, postdeposition solvent-vapor annealing conditions that induce polymorphic transformation, and the resulting polymorphs. This analysis yields a correlative function that can be used to successfully predict the appearance of either one of two polymorphs in thin films of cHBC derivatives. Within the postdeposition processing phase space of cHBC derivatives, we have demonstrated an approach to generate guidelines to select crystallization conditions to bias polymorph access. We believe this approach can be applied more broadly to accelerate the predictions of processing conditions to access desired molecular polymorphs, making progress toward one of the grand challenges identified by the Materials Genome Initiative.
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U2 - 10.1021/acs.chemmater.8b00679
DO - 10.1021/acs.chemmater.8b00679
M3 - Article
C2 - 31178626
AN - SCOPUS:85047510640
SN - 0897-4756
VL - 30
SP - 3330
EP - 3337
JO - Chemistry of Materials
JF - Chemistry of Materials
IS - 10
ER -