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Modeling Organic Electronic Materials: Bridging Length and Time Scales UC Davis UC Davis Previously Published Works Title Modeling organic electronic materials: bridging length and time scales Permalink https://escholarship.org/uc/item/6jv1c5zk Journal Molecular Simulation, 43(10-11) ISSN 0892-7022 Authors Harrelson, TF Moulé, AJ Faller, R Publication Date 2017-07-03 DOI 10.1080/08927022.2016.1273526 Peer reviewed eScholarship.org Powered by the California Digital Library University of California Molecular Simulation ISSN: 0892-7022 (Print) 1029-0435 (Online) Journal homepage: http://www.tandfonline.com/loi/gmos20 Modeling organic electronic materials: bridging length and time scales Thomas F. Harrelson, Adam J. Moulé & Roland Faller To cite this article: Thomas F. Harrelson, Adam J. Moulé & Roland Faller (2017): Modeling organic electronic materials: bridging length and time scales, Molecular Simulation To link to this article: http://dx.doi.org/10.1080/08927022.2016.1273526 Published online: 02 Mar 2017. Submit your article to this journal View related articles View Crossmark data Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=gmos20 Download by: [The UC Davis Libraries] Date: 02 March 2017, At: 08:51 MOLECULAR SIMULATION, 2017 http://dx.doi.org/10.1080/08927022.2016.1273526 ENERGY APPLICATIONS Modeling organic electronic materials: bridging length and time scales Thomas F. Harrelson, Adam J. Moulé, Roland Faller Chemical Engineering, UC Davis, Davis, USA ABSTRACT ARTICLE HISTORY Organic electronics is a popular and rapidly growing field of research. The optical, electrical and mechanical Received 2 October 2016 properties of organic molecules and materials can be tailored using increasingly well controlled synthetic Accepted 10 December 2016 methods. The challenge and fascination with this field of research is derived from the fact that not only KEYWORDS the chemical identity, but also the spatial arrangement of the molecules critically affects the performance Coarse graining; organic of the material. Thus synthetic, fabrication, characterisation and computational scientists need to work electronics; molecular closely to relate a materials performance in a device to the molecular details that cause and optimise that dynamics performance. For computational scientists in particular, the need to relate macroscopic device performance to details of molecular electronic structure brings challenges in methodology due to the need to bridge many orders of time and length scales. This article provides a survey of computational methods applied to multiple-length and time scale problems in organic electronic materials. Here we seek to highlight a few particular approaches that expand the simulation toolbox. 1. Introduction Organic electronic devices and materials have become an increasingly important research and commercial area with a Organic molecules have been recognised for their potential to predicted market value of ∼$70 billion by 2026 [9–11]. Organic harvest and emit light for device applications for decades [1–3]. components are particularly valuable because molecular design Since these humble beginnings, organic light emitting diodes allows an almost infinite variety of structures and functions to be (OLED) have become commercially available for lighting and synthesised [12]. Ideally, it would be possible to conduct mod- are widely used for display applications [4,5]; organic photo- eling experiments to design organic molecules for electronic voltaics (OPV) have achieved over 10% power efficiency [6,7] applications and to characterise the function of the structures and both small molecule and polymer semiconductors have using computers. However this task is currently impossible achieved over 1 cm2/Vs mobility [8]. The progress represented because organic electronic molecules could be crystalline or by these astonishing technological achievements in the use of amorphous with molecular weight between 16 and 108 g/mol. organic materials for electronic applications has come about as They could be liquids, liquid solutions, network solids, gels, or a result of simultaneous major advances in organic materials insoluble materials that are evaporated into place. They could synthesis, capabilities in organic materials characterisation, and be pure hydrocarbons, organo-metallics, metal organic frame- the development of tools for organic materials modeling. This works, organic/inorganic nano-hybrids, biological solids, pure research effort is so vast that it alone could fill a library. In carbon solids and a variety of other forms. In other words, the this review, we will highlight a subset of the research on the variety of forms of organic molecules that must be described use of computational modeling tools used to describe the struc- − using simulations is vast. In addition, length scales from 10 11 ture, dynamics and energetics of organic electronic materials. to 100 m need to be considered to cover all relevant questions The highlighted studies focus on modeling the semiconducting from atomic arrangement to fully fabricated devices. Also time polymer poly-3-hexylthiophene (P3HT) (Figure 1(a)). While − scales from 10 15 to 109 s must be considered to cover from P3HT is not the highest performing polymer for any application, exciton formation to the lifetime of an OLED or PV device. Here it has been more studied than any other electronic polymer we consider the subset of modeling techniques that describes and so there is a wealth of verification data to test simulated structure over length scales from 0.1 to 1000 nm and dynamics results against. Therefore, P3HT is an excellent test subject for over time scales from fs to µs. organic electronic model development. Our goal is to examine One of the most important advantages of organic electronic the process of using multiple different simulation methods to materials is that they can be deposited from solution, which simulate structure and properties. In most simulation studies, potentially makes coating over large areas very inexpensive multiple modeling methods must be used in order to extract [13–16]. The drawback of solution deposition is that the or- meaningful data because a single method is not able to bridge ganic species must self-assemble into the desired molecular length and time scales. We will discuss limitations that can be configuration [17,18]. It is difficult to simulate self-assembly addressed using improved modeling and verification methods. processes because these processes often involve phase changes, This should justify the need for further research in developing reactions, complex interactions with the solvent and changing modeling tools for organic electronic materials. CONTACT Roland Faller [email protected] © 2017 Informa UK Limited, trading as Taylor & Francis Group 2 T.F. HARRELSON ET AL. concentrations and temperature changes. For organic field effect consistent way, while simultaneously producing a molecular transistor materials the desired self-assembly is large molecular picture of the system. As with experimental characterisation crystals with few defects and a particular molecular orientation techniques, there are a number of modeling tools for different [19]. For OLED materials, typically amorphous materials are length and time scales [34]. In general, molecular models can desired to prevent exciton quenching. Also mixtures with low be broken into three categories. First there are electronic or volume percentages of well spaced emitters are often desired [4]. quantum mechanical models that explicitly treat the electron For solution processed OPV active layers, a mixture of donor position or density separately from the nuclear position. Second and acceptor materials is preferred [20,21]. These materials there are molecular dynamics or classical models that calculate should phase separate on a length scale that maximises exciton the position and forces on atoms or groups of atoms using separation at donor acceptor interfaces while at the same time classical force fields. Third there are continuum models that providing charge transport for holes through the donor material do not explicitly account for atoms, but rather keep track of to the anode and for electrons through the acceptor material to densities (mass, charge etc.) and/or change in densities within the cathode [22,23]. a volume as a function of time. At all length scales, the meth- The discovery of state-of-the-art materials used for elec- ods can be used to determine a static structure or an explicit tronic devices is achieved through combined synthesis, char- time dependence can be added to determine how a change in acterisation and simulation techniques. This is necessary to conditions (temperature, pressure, electric field etc.) affects the understand the morphology of the donor–acceptor mixture molecular/electronic structure. because we need information over different length scales, time Modelling of organic electronic materials almost always re- scales, and with different contrast. For a simulation scientist, quires the use of more than one length scale because electronic validation of a molecular model using experimental data is materials properties depend sensitively on the atomic/molecular often the most difficult challenge because the real sample is structure over length scales that are not accessible using elec- almost always more disordered, larger, and less well defined tronic simulations. Alternatively, to determine structure using than the simulation sample. It is often impossible to make classical
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