Computational Approaches for Organic Semiconductors: From Chemical and Physical Understanding to Predicting New Materials

While a complete understanding of organic semiconductor (OSC) design principles remains elusive, computational methods─ranging from techniques based in classical and quantum mechanics to more recent data-enabled models─can complement experimental observations and provide deep physicochemical insights into OSC structure-processing-property relationships, offering new capabilities for in silico OSC discovery and design. In this Review, we trace the evolution of these computational methods and their application to OSCs, beginning with early quantum-chemical methods to investigate resonance in benzene and building to recent machine-learning (ML) techniques and their application to ever more sophisticated OSC scientific and engineering challenges. Along the way, we highlight the limitations of the methods and how sophisticated physical and mathematical frameworks have been created to overcome those limitations. We illustrate applications of these methods to a range of specific challenges in OSCs derived from π-conjugated polymers and molecules, including predicting charge-carrier transport, modeling chain conformations and bulk morphology, estimating thermomechanical properties, and describing phonons and thermal transport, to name a few. Through these examples, we demonstrate how advances in computational methods accelerate the deployment of OSCsin wide-ranging technologies, such as organic photovoltaics (OPVs), organic light-emitting diodes (OLEDs), organic thermoelectrics, organic batteries, and organic (bio)sensors. We conclude by providing an outlook for the future development of computational techniques to discover and assess the properties of high-performing OSCs with greater accuracy.

Effects of solvation shell relaxation on chain association mechanisms in poly(3-hexylthiophene) solutions

Using poly(3-hexylthiophene) (P3HT) as a model conjugated polymer and atomistic molecular dynamics simulations with carefully verified force fields, we performed in-depth investigations of solvation shell properties of P3HT chains (15 repeating units per chain) in two representative groups of non-polar (or aprotic) organic solvents (better solvents: ortho-dichlorobenzene, bromobenzene, and chlorobenzene; poorer solvents: chloroform, para-xylene, and toluene). We demonstrated that solvation shell relaxation properties in P3HT solutions dictate the formation of regular π-π associations and, hence, crystallinity through the initial chain association and subsequent chain sliding. In contrast, the mean features of polymer-solvent interactions, including solvation free energy and radial distribution function, present little or no difference for all solvent media investigated. Better-solvent media were revealed to bear relatively large values of the first solvation shell relaxation time (τ1 ≫ 100 ps) as well as larger ratios of relaxation times for the first two solvation shells (τ1/τ2 > 2), and vice versa for poorer-solvent media (τ1 ≪ 100 ps and τ1/τ2 < 2). The linear hexyl side-chain unit was noted to substantially enlarge both quantities while notably reducing the solvation free energy as well. As discussed herein, these findings shed new light on the mechanistic features by which solvent quality impacts the degree of π-π association crucial for modern applications with crystalline conjugated polymers.

Transfer Learned Designer Polymers For Organic Solar Cells

Organic photovoltaic (OPV) materials have been examined extensively over the past two decades for solar cell applications because of the potential for device flexibility, low-temperature solution processability, and negligible environmental impact. However, discovery of new candidate OPV materials, especially polymer-based electron donors, that demonstrate notable power conversion efficiencies (PCEs), is nontrivial and time-intensive exercise given the extensive set of possible chemistries. Recent progress in machine learning accelerated materials discovery has facilitated to address this challenge, with molecular line representations, such as Simplified Molecular-Input Line-Entry Systems (SMILES), gaining popularity as molecular fingerprints describing the donor chemical structures. Here, we employ a transfer learning based recurrent neural (LSTM) model, which harnesses the SMILES molecular fingerprints as an input to generate novel designer chemistries for OPV devices. The generative model, perfected on a small focused OPV data set, predicts new polymer repeat units with potentially high PCE. Calculations of the similarity coefficient between the known and the generated polymers corroborate the accuracy of the model predictability as a function of the underlying chemical specificity. The data-enabled framework is sufficiently generic for use in accelerated machine learned materials discovery for various chemistries and applications, mining the hitherto available experimental and computational data.

The interplay of interfaces, supramolecular assembly, and electronics in organic semiconductors

Organic semiconductors, which include a diverse range of carbon-based small molecules and polymers with interesting optoelectronic properties, offer many advantages over conventional inorganic semiconductors such as silicon and are growing in importance in electronic applications. Although these materials are now the basis of a lucrative industry in electronic displays, many promising applications such as photovoltaics remain largely untapped. One major impediment to more rapid development and widespread adoption of organic semiconductor technologies is that device performance is not easily predicted from the chemical structure of the constituent molecules. Fundamentally, this is because organic semiconductor molecules, unlike inorganic materials, interact by weak non-covalent forces, resulting in significant structural disorder that can strongly impact electronic properties. Nevertheless, directional forces between generally anisotropic organic-semiconductor molecules, combined with translational symmetry breaking at interfaces, can be exploited to control supramolecular order and consequent electronic properties in these materials. This review surveys recent advances in understanding of supramolecular assembly at organic-semiconductor interfaces and its impact on device properties in a number of applications, including transistors, light-emitting diodes, and photovoltaics. Recent progress and challenges in computer simulations of supramolecular assembly and orientational anisotropy at these interfaces is also addressed.

Solution Processing Dependent Bulk Heterojunction Nanomorphology of P3HT/PCBM Thin Films

Mixtures of poly(3-hexyl-thiophene) (P3HT) and phenyl-C61-butyric acid methyl ester (PCBM) have been widely employed as donor and acceptor materials, respectively, for the active layer of the bulk heterojunction (BHJ) organic solar cells. Experiments are able to provide only limited insights on the dynamics of blend morphology of these organic materials because of the challenges in extracting microstructural characterization amidst the poor contrast in electron microscopy. We present results from coarse-grained molecular dynamics simulations (CGMD) describing the morphological evolution of P3HT/PCBM active layer under solution processing in chlorobenzene (CB). We examine the impact of various processing parameters such as weight ratio, degree of polymerization (DOP), thermal annealing, and preheating on the BHJ active layers using morphological characterizations from atomic trajectories. Simulated diffraction patterns are compared with experimental results of X-ray diffraction and Small Angle X-ray Scattering (SAXS). Both simulated scattering and experimental X-ray diffraction and X-ray scattering measurements reveal increase in crystallinity for P3HT upon annealing until PCBM weight fraction ∼50%. The solubility of PCBM being greater in CB than that of P3HT facilitates the phase separation of the polymer during early stages of solvent evaporation. An increase in the average size of the P3HT domain relative to the preannealed morphology, is due to phase segregation and crystallization of the polymer upon annealing. Percolation for PCBM remains unchanged until PCBM constitutes at least one-half of the composition. Although 1.0:2.0 weight ratio is predicted to be ideal for balanced charge transport, 1.0:1.0 weight ratio is the most beneficial of overall power conversion based on exciton generation and charge separation at the interface. DOP of P3HT molecules is another important design variable as larger P3HT molecules tend to entangle more often deteriorating molecular order of P3HT phase in the active layer. Preheating the ternary mixture of P3HT, PCBM, and CB modifies the structural order and morphology of the BHJ due to changes in PCBM diffusion into the P3HT phase.

Synergistic Effects of Electric-Field-Assisted Annealing and Thermal Annealing in Bulk-Heterojunction Solar Cells

We propose an optimum low-temperature-based annealing procedure for semicrystalline donor-fullerene solar cells that is well-suited for plastic and flexible substrates. This proposed alternate strategy utilizes an external electric field (EF) across the bulk heterojunction (BHJ) film during processing at a desired temperature. This processing technique is studied for different molecular weights of the donor in the BHJ blend films. The films indicate an increase in interchain interactions of the semicrystalline polymer chains and an enhancement in hole mobility with EF-assisted annealing treatment. Besides being a controlled method, this processing technique is capable of yielding solar cell devices with performance equivalent to or better than those obtained using plain thermal procedures.

Bulk Heterojunction Morphologies with Atomistic Resolution from Coarse-Grain Solvent Evaporation Simulations

Control over the morphology of the active layer of bulk heterojunction (BHJ) organic solar cells is paramount to achieve high-efficiency devices. However, no method currently available can predict morphologies for a novel donor–acceptor blend. An approach which allows reaching relevant length scales, retaining chemical specificity, and mimicking experimental fabrication conditions, and which is suited for high-throughput schemes has been proven challenging to find. Here, we propose a method to generate atom-resolved morphologies of BHJs which conforms to these requirements. Coarse-grain (CG) molecular dynamics simulations are employed to simulate the large-scale morphological organization during solution-processing. The use of CG models which retain chemical specificity translates into a direct path to the rational design of donor and acceptor compounds which differ only slightly in chemical nature. Finally, the direct retrieval of fully atomistic detail is possible through backmapping, opening the way for improved quantum mechanical calculations addressing the charge separation mechanism. The method is illustrated for the poly(3-hexyl-thiophene) (P3HT)–phenyl-C61-butyric acid methyl ester (PCBM) mixture, and found to predict morphologies in agreement with experimental data. The effect of drying rate, P3HT molecular weight, and thermal annealing are investigated extensively, resulting in trends mimicking experimental findings. The proposed methodology can help reduce the parameter space which has to be explored before obtaining optimal morphologies not only for BHJ solar cells but also for any other solution-processed soft matter device.

Simulating charge transport in organic semiconductors and devices: a review

Charge transport simulation can be a valuable tool to better understand, optimise and design organic transistors (OTFTs), photovoltaics (OPVs), and light-emitting diodes (OLEDs). This review presents an overview of common charge transport and device models; namely drift-diffusion, master equation, mesoscale kinetic Monte Carlo and quantum chemical Monte Carlo, and a discussion of the relative merits of each. This is followed by a review of the application of these models as applied to charge transport in organic semiconductors and devices, highlighting in particular the insights made possible by modelling. The review concludes with an outlook for charge transport modelling in organic electronics.

Electrostatic phenomena in organic semiconductors: fundamentals and implications for photovoltaics

This review summarizes the current understanding of electrostatic phenomena in ordered and disordered organic semiconductors, outlines numerical schemes developed for quantitative evaluation of electrostatic and induction contributions to ionization potentials and electron affinities of organic molecules in a solid state, and illustrates two applications of these techniques: interpretation of photoelectron spectroscopy of thin films and energetics of heterointerfaces in organic solar cells.

Addition of P3HT-grafted Silica nanoparticles improves bulk-heterojunction morphology in P3HT-PCBM blends

We present molecular dynamics simulations of a ternary blend of P3HT, PCBM and P3HT-grafted silica nanoparticles (SiNP) for applications in polymer-based solar cells. Using coarse-grained models, we study the effect of SiNP on the spatial arrangement of PCBM in P3HT. Our results suggest that addition of SiNP not only alters the morphology of PCBM clusters but also improves the crystallinity of P3HT. We exploit the property of grafted SiNP to self-assemble into a variety of anisotropic structures and the tendency of PCBM to preferentially adhere to SiNP surface, due to favorable interactions, to achieve morphologies with desirable characteristics for the active layer, including domain size, crystallinity of P3HT, and elimination of isolated islands of PCBM. As the concentration of SiNP increases, the number of isolated PCBM molecules decreases, which in turn improves the crystallinity of P3HT domains. We also observe that by tuning the grafting parameters of SiNP, it is possible to achieve structures ranging from cylindrical to sheets to highly interconnected network of strings. The changes brought about by addition of SiNP shows a promising potential to improve the performance of these materials when used as active layers in organic photovoltaics.

Petascale Simulations of the Morphology and the Molecular Interface of Bulk Heterojunctions

Understanding how additives interact and segregate within bulk heterojunction (BHJ) thin films is critical for exercising control over structure at multiple length scales and delivering improvements in photovoltaic performance. The morphological evolution of poly(3-hexylthiophene) (P3HT) and phenyl-C61-butyric acid methyl ester (PCBM) blends that are commensurate with the size of a BHJ thin film is examined using petascale coarse-grained molecular dynamics simulations. Comparisons between two-component and three-component systems containing short P3HT chains as additives undergoing thermal annealing demonstrate that the short chains alter the morphology in apparently useful ways: they efficiently migrate to the P3HT/PCBM interface, increasing the P3HT domain size and interfacial area. Simulation results agree with depth profiles determined from neutron reflectometry measurements that reveal PCBM enrichment near substrate and air interfaces but a decrease in that PCBM enrichment when a small amount of short P3HT chains are integrated into the BHJ blend. Atomistic simulations of the P3HT/PCBM blend interfaces show a nonmonotonic dependence of the interfacial thickness as a function of number of repeat units in the oligomeric P3HT additive, and the thiophene rings orient parallel to the interfacial plane as they approach the PCBM domain. Using the nanoscale geometries of the P3HT oligomers, LUMO and HOMO energy levels calculated by density functional theory are found to be invariant across the donor/acceptor interface. These connections between additives, processing, and morphology at all length scales are generally useful for efforts to improve device performance.

Electrode materials, thermal annealing sequences, and lateral/vertical phase separation of polymer solar cells from multiscale molecular simulations

The nanomorphologies of the bulk heterojunction (BHJ) layer of polymer solar cells are extremely sensitive to the electrode materials and thermal annealing conditions. In this work, the correlations of electrode materials, thermal annealing sequences, and resultant BHJ nanomorphological details of P3HT:PCBM BHJ polymer solar cell are studied by a series of large-scale, coarse-grained (CG) molecular simulations of system comprised of PEDOT:PSS/P3HT:PCBM/Al layers. Simulations are performed for various configurations of electrode materials as well as processing temperature. The complex CG molecular data are characterized using a novel extension of our graph-based framework to quantify morphology and establish a link between morphology and processing conditions. Our analysis indicates that vertical phase segregation of P3HT:PCBM blend strongly depends on the electrode material and thermal annealing schedule. A thin P3HT-rich film is formed on the top, regardless of bottom electrode material, when the BHJ layer is exposed to the free surface during thermal annealing. In addition, preferential segregation of P3HT chains and PCBM molecules toward PEDOT:PSS and Al electrodes, respectively, is observed. Detailed morphology analysis indicated that, surprisingly, vertical phase segregation does not affect the connectivity of donor/acceptor domains with respective electrodes. However, the formation of P3HT/PCBM depletion zones next to the P3HT/PCBM-rich zones can be a potential bottleneck for electron/hole transport due to increase in transport pathway length. Analysis in terms of fraction of intra- and interchain charge transports revealed that processing schedule affects the average vertical orientation of polymer chains, which may be crucial for enhanced charge transport, nongeminate recombination, and charge collection. The present study establishes a more detailed link between processing and morphology by combining multiscale molecular simulation framework with an extensive morphology feature analysis, providing a quantitative means for process optimization.

Frequency selectivity in pulse responses of Pt/poly(3-hexylthiophene-2,5-diyl)/polyethylene oxide +Li+/Pt hetero-junction

Pt/poly(3-hexylthiophene-2,5-diyl)/polyethylene oxide + Li+/Pt hetero junctions were fabricated, and their pulse responses were studied. The direct current characteristics were not symmetric in the sweeping range of ±2 V. Negative differential resistance appeared in the input range of 0 to 2 V because of de-doping (or reduction) in the side with the semiconductor layer. The device responded stably to a train of pulses with a fixed frequency. The inverse current after a pulse was related to the back-migrated ions. Importantly, the weight calculated based on the inverse current strength, was depressed during low-frequency stimulations but was potentiated during high-frequency stimulations when pulses were positive. Therefore, frequency selectivity was first observed in a semiconducting polymer/electrolyte hetero junction. Detailed analysis of the pulse response showed that the input frequency could modulate the timing of ion doping, de-doping, and re-doping at the semiconducting polymer/electrolyte interface, which then resulted in the frequency selectivity. Our study suggests that the simple redox process in semiconducting polymers can be modulated and used in signal handling or the simulation of bio-learning.