Accelerated Computational Discovery of High-Performance Materials for Organic Photovoltaics by Means of Cheminformatics

In this perspective we explore the use of strategies from drug discovery, pattern recognition, and machine learning in the context of computational materials science. We focus our discussion on the development of donor materials for organic photovoltaics by means of a cheminformatics approach. These methods enable the development of models based on molecular descriptors that can be correlated to the important characteristics of the materials. Particularly, we formulate empirical models, parametrized using a training set of donor polymers with available experimental data, for the important current–voltage and efficiency characteristics of candidate molecules. The descriptors are readily computed which allows us to rapidly assess key quantities related to the performance of organic photovoltaics for many candidate molecules. As part of the Harvard Clean Energy Project, we use this approach to quickly obtain an initial ranking of its molecular library with 2.6 million candidate compounds. Our method reveals molecular motifs of particular interest, such as the benzothiadiazole and thienopyrrole moieties, which are present in the most promising set of molecules.Chemistry and Chemical Biolog

The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid

This Perspective introduces the Harvard Clean Energy Project (CEP), a theory-driven search for the next generation of organic solar cell materials. We give a broad overview of its setup and infrastructure, present first results, and outline upcoming developments. CEP has established an automated, high-throughput, in silico framework to study potential candidate structures for organic photovoltaics. The current project phase is concerned with the characterization of millions of molecular motifs using first-principles quantum chemistry. The scale of this study requires a correspondingly large computational resource, which is provided by distributed volunteer computing on IBM’s World Community Grid. The results are compiled and analyzed in a reference database and will be made available for public use. In addition to finding specific candidates with certain properties, it is the goal of CEP to illuminate and understand the structure–property relations in the domain of organic electronics. Such insights can open the door to a rational and systematic design of future high-performance materials. The computational work in CEP is tightly embedded in a collaboration with experimentalists, who provide valuable input and feedback to the project.Chemistry and Chemical Biolog

Lead candidates for high-performance organic photovoltaics from high-throughput quantum chemistry – the Harvard Clean Energy Project

The virtual high-throughput screening framework of the Harvard Clean Energy Project allows for the computational assessment of candidate structures for organic electronic materials – in particular photovoltaics – at an unprecedented scale. We report the most promising compounds that have emerged after studying 2.3 million molecular motifs by means of 150 million density functional theory calculations. Our top candidates are analyzed with respect to their structural makeup in order to identify important building blocks and extract design rules for efficient materials. An online database of the results is made available to the community.Engineering and Applied Science

Effects of Odd–Even Side Chain Length of Alkyl-Substituted Diphenylbithiophenes on First Monolayer Thin Film Packing Structure

Because of their preferential two-dimensional layer-by-layer growth in thin films, 5,5′bis(4-alkylphenyl)-2,2′-bithiophenes (P2TPs) are model compounds for studying the effects of systematic chemical structure variations on thin-film structure and morphology, which in turn, impact the charge transport in organic field-effect transistors. For the first time, we observed, by grazing incidence X-ray diffraction (GIXD), a strong change in molecular tilt angle in a monolayer of P2TP, depending on whether the alkyl chain on the P2TP molecules was of odd or even length. The monolayers were deposited on densely packed ultrasmooth self-assembled alkane silane modified $SiO_2$ surfaces. Our work shows that a subtle change in molecular structure can have a significant impact on the molecular packing structure in thin film, which in turn, will have a strong impact on charge transport of organic semiconductors. This was verified by quantum-chemical calculations that predict a corresponding odd–even effect in the strength of the intermolecular electronic coupling.Chemistry and Chemical BiologyEngineering and Applied Science

Confined organization of fullerene units along high polymer chains

Conductive fullerene (C_60) units were designed to be arranged in one dimensional close contact by locally organizing them with covalent bonds in a spatially constrained manner. Combined molecular dynamics and quantum chemical calculations predicted that the intramolecular electronic interactions (i.e. charge transport) between the pendant C_60 units could be controlled by the length of the spacers linking the C_60 units and the polymer main chain. In this context, C_60 side-chain polymers with high relative degrees of polymerization up to 1220 and fullerene compositions up to 53% were synthesized by ruthenium catalyzed ring-opening metathesis polymerization of the corresponding norbornene-functionalized monomers. UV/vis absorption and photothermal deflection spectra corroborated the enhanced inter-fullerene interactions along the polymer chains. The electron mobility measured for the thin film field-effect transistor devices from the polymers was more than an order of magnitude higher than that from the monomers, as a result of the stronger electronic coupling between the adjacent fullerene units within the long polymer chains. This molecular design strategy represents a general approach to the enhancement of charge transport properties of organic materials via covalent bond-based organization

Computational investigation of intramolecular reorganization energy in diketopyrrolopyrrole (DPP) derivatives

Intramolecular reorganization energy (RE) of molecules derived from the diketopyrrolopyrrole (DPP) unit has been studied using B3LYP/6-31G(d,p) theory. It was found that the replacement of the oxygen atoms with sulfur in the DPP unit led to a smaller RE for both the hole and electron transfer processes. One disadvantage of the sulfur replacement is the twist of the conjugated backbone, which might impair the π − π interactions in the solid state. The RE calculated from the adiabatic potential energy surfaces and that derived from the normal mode analysis agreed well for both systems. Electronic structure data showed that the replacement of oxygen atoms with sulfur in the DPP unit might lead to the development of ambipolar compounds with low RE

A quantitative structure-property study of reorganization energy for known p-type organic semiconductors

Intramolecular reorganization energy (RE), which quantifies the electron-phonon coupling strength, is an important charge transport parameter for the theoretical characterization of molecular organic semiconductors (OSCs). On a small scale, the accurate calculation of the RE is trivial; however, for large-scale screening, faster approaches are desirable. We investigate the structure-property relations and present a quantitative structure-property relationship study to facilitate the computation of RE from molecular structure. To this end, we generated a compound set of 171, which was derived from known p-type OSCs built from moieties such as acenes, thiophenes, and pentalenes. We show that simple structural descriptors such as the number of atoms, rings or rotatable bonds only weakly correlate with the RE. On the other hand, we show that regression models based on a more comprehensive representation of the molecules such as SMILES-based molecular signatures and geometry-based molecular transforms can predict the RE with a coefficient of determination of 0.7 and a mean absolute error of 40 meV in the library, in which the RE ranges from 76 to 480 meV. Our analysis indicates that a more extensive compound set for training is necessary for more predictive models

A theoretical study of the structure and binding energies of dimers of Zn(II)-Porphyrin derivatives

Zinc complexed porphyrin and chlorophyll derivatives form functional aggregates with remarkable photophysical and optoelectronic properties. Understanding the type and strength of intermolecular interactions between these molecules is essential for designing new materials with desired morphology and functionality. The dimer interactions of a molecular set comprised of porphyrin derivatives obtained by substitutional changes starting from free-base porphyrin is studied. It is found that B97M-rV/def2-TZVP level of theory provides a good compromise between the accuracy and cost to get the dimer geometries and interaction energies. The neglect of the relaxation energy due to the change in the monomer configurations upon complex formation, causes a more significant error than the basis set superposition error. The metal complexation increases the binding energy by about -6 to -8 kcal/mol, and the introduction of keto and hydroxy groups further stabilizes the dimers by -10 to -15 kcal/mol. Although the saturation of one of the pyrrol double bonds does not change the interaction energy, the addition of R groups increases it