A computational exploration of the crystal energy and charge-carrier mobility landscapes of the chiral [6]helicene molecule

Rational Design of New Conjugated Polymers with Main Chain Chirality for Efficient Optoelectronic Devices: Carbo[6]Helicene and Indacenodithiophene Copolymers as Model Compounds

The unique properties of conjugated polymers (CPs) in various optoelectronic applications are mainly attributed to their different self-assembly processes and superstructures. Various methods are utilized to tune and control CP structure and properties with less attention paid to the use of chirality. CPs with main chain chirality are rare and their microscopic and macroscopic properties are still unknown. In this work, the first experimental results are provided along these lines by synthesizing a series of racemic and enantiopure CPs containing statistical and alternating carbo[6]helicene and indacenodithiophene moieties and evaluating their microscopic (optical, energy levels) and macroscopic properties (hole mobilities, photovoltaic performance). It is demonstrated that a small statistical insertion of either the racemic or enantiopure helicene into the polymer backbone finely tunes the microscopic and macroscopic properties as a function of the statistical content. The microscopic properties of the enantiopure versus the racemic polymers with the same helicene loading remain similar. On the contrary, the macroscopic properties, and more interestingly those between the two enantiomeric forms, are altered as a function of the statistical content. Once incorporated into a solar cell device, these chiral CPs display better performance in their enantiopure versus racemic forms.

Mechanochemical Scholl Reaction on Phenylated Cyclopentadiene Core: One-Step Synthesis of Fluoreno[5]helicenes

In this study, we explore feasibility of the mechanochemical approach in the synthesis of tetrabenzofluorenes (fluoreno[5]helicenes). For this, commercially available phenylated cyclopentadiene precursors are subjected to the Scholl reaction in the solid state using FeCl3 as an oxidant and sodium chloride as the solid reaction medium. This ball milling process gave access to the 5-membered ring containing-helicenes in one synthetic step in high (95-96 %) isolated yields. The solution-phase reactions, however, were found to be moderate to low yielding in this regard (10-40 %).

Frontiers of molecular crystal structure prediction for pharmaceuticals and functional organic materials

The reliability of organic molecular crystal structure prediction has improved tremendously in recent years. Crystal structure predictions for small, mostly rigid molecules are quickly becoming routine. Structure predictions for larger, highly flexible molecules are more challenging, but their crystal structures can also now be predicted with increasing rates of success. These advances are ushering in a new era where crystal structure prediction drives the experimental discovery of new solid forms. After briefly discussing the computational methods that enable successful crystal structure prediction, this perspective presents case studies from the literature that demonstrate how state-of-the-art crystal structure prediction can transform how scientists approach problems involving the organic solid state. Applications to pharmaceuticals, porous organic materials, photomechanical crystals, organic semi-conductors, and nuclear magnetic resonance crystallography are included. Finally, efforts to improve our understanding of which predicted crystal structures can actually be produced experimentally and other outstanding challenges are discussed.

Remarkable Enhancement of Hole Mobility of Novel DA-D'-AD Small Molecules by Thermal Annealing: Effect of the D'-Bridge Block

Conjugated small molecules are advanced semiconductor materials with attractive physicochemical and optoelectronic properties enabling the development of next-generation electronic devices. The charge carrier mobility of small molecules strongly influences the efficiency of organic and hybrid electronics based on them. Herein, we report the synthesis of four novel small molecules and their investigation with regard to the impact of molecular structure and thermal treatment of films on charge carriers' mobility. The benzodithiophene-containing compounds (BDT) were shown to be more promising in terms of tuning the morphology upon thermal treatment. Impressive enhancement of hole mobilities by more than 50 times was found for annealed films based on a compound M4 comprising triisopropylsilyl-functionalized BDT core. The results provide a favorable experience and strategy for the rational design of state-of-the-art organic semiconductor materials (OSMs) and for improving their charge-transport characteristics.

XDM-corrected hybrid DFT with numerical atomic orbitals predicts molecular crystal lattice energies with unprecedented accuracy

Molecular crystals are important for many applications, including energetic materials, organic semiconductors, and the development and commercialization of pharmaceuticals. The exchange-hole dipole moment (XDM) dispersion model has shown good performance in the calculation of relative and absolute lattice energies of molecular crystals, although it has traditionally been applied in combination with plane-wave/pseudopotential approaches. This has limited XDM to use with semilocal functional approximations, which suffer from delocalization error and poor quality conformational energies, and to systems with a few hundreds of atoms at most due to unfavorable scaling. In this work, we combine XDM with numerical atomic orbitals, which enable the efficient use of XDM-corrected hybrid functionals for molecular crystals. We test the new XDM-corrected functionals for their ability to predict the lattice energies of molecular crystals for the X23 set and 13 ice phases, the latter being a particularly stringent test. A composite approach using a XDM-corrected, 25% hybrid functional based on B86bPBE achieves a mean absolute error of 0.48 kcal mol^-1 per molecule for the X23 set and 0.19 kcal mol^-1 for the total lattice energies of the ice phases, compared to recent diffusion Monte-Carlo data. These results make the new XDM-corrected hybrids not only far more computationally efficient than previous XDM implementations, but also the most accurate density-functional methods for molecular crystal lattice energies to date.

Controlling anisotropic properties by manipulating the orientation of chiral small molecules

Chiral π-conjugated molecules bring new functionality to technological applications and represent an exciting, rapidly expanding area of research. Their functional properties, such as the absorption and emission of circularly polarized light or the transport of spin-polarized electrons, are highly anisotropic. As a result, the orientation of chiral molecules critically determines the functionality and efficiency of chiral devices. Here we present a strategy to control the orientation of a small chiral molecule (2,2'-dicyano[6]helicene) by the use of organic and inorganic templating layers. Such templating layers can either force 2,2'-dicyano[6]helicene to adopt a face-on orientation and self-assemble into upright supramolecular columns oriented with their helical axis perpendicular to the substrate, or an edge-on orientation with parallel-lying supramolecular columns. Through such control, we show that low- and high-energy chiroptical responses can be independently 'turned on' or 'turned off'. The templating methodologies described here provide a simple way to engineer orientational control and, by association, anisotropic functional properties of chiral molecular systems for a range of emerging technologies.

Computational modeling to assist in the discovery of supramolecular materials

Computational modeling is increasingly used to assist in the discovery of supramolecular materials. Supramolecular materials are typically primarily built from organic components that are self-assembled through noncovalent bonding and have potential applications, including in selective binding, sorption, molecular separations, catalysis, optoelectronics, sensing, and as molecular machines. In this review, the key areas where computational prediction can assist in the discovery of supramolecular materials, including in structure prediction, property prediction, and the prediction of how to synthesize a hypothetical material are discussed, before exploring the potential impact of artificial intelligence techniques on the field. Throughout, the importance of close integration with experimental materials discovery programs will be highlighted. A series of case studies from the author's work across some different supramolecular material classes will be discussed, before finishing with a discussion of the outlook for the field.

Minimal Basis Set Hartree-Fock Corrected with Atom-Centered Potentials for Molecular Crystal Modeling and Crystal Structure Prediction

Crystal structure prediction (CSP), determining the experimentally observable structure of a molecular crystal from the molecular diagram, is an important challenge with technologically relevant applications in materials manufacturing and drug design. For the purpose of screening the randomly generated candidate crystal structures, CSP protocols require energy ranking methods that are fast and can accurately capture the small energy differences between molecular crystals. In addition, a good ranking method should also produce accurate equilibrium geometries, both intramolecular and intermolecular. In this article, we explore the combination of minimal-basis-set Hartree-Fock (HF) with atom-centered potentials (ACPs) as a method for modeling the structure and energetics of molecular crystals. The ACPs are developed for the H, C, N, and O atoms and fitted to a set of reference data at the B86bPBE-XDM level in order to mitigate basis-set incompleteness and missing correlation. In particular, ACPs are developed in combination with two methods: HF-D3/MINIs and HF-3c. The application of ACPs greatly improves the performance of HF-D3/MINIs for lattice energies, crystal energy differences, energy-volume and energy-strain relations, and crystal geometries. In the case of HF-3c, the improvement in the crystal energy differences is much smaller than in HF-D3/MINIs, but lattice energies and particularly crystal geometries are considerably better when ACPs are used. The resulting methods may be useful for CSP but also for quick calculation of molecular crystal lattice energies and geometries.

Global analysis of the energy landscapes of molecular crystal structures by applying the threshold algorithm

Polymorphism in molecular crystals has important consequences for the control of materials properties and our understanding of crystallization. Computational methods, including crystal structure prediction, have provided important insight into polymorphism, but have usually been limited to assessing the relative energies of structures. We describe the implementation of the Monte Carlo threshold algorithm as a method to provide an estimate of the energy barriers separating crystal structures. By sampling the local energy minima accessible from multiple starting structures, the simulations yield a global picture of the crystal energy landscapes and provide valuable information on the depth of the energy minima associated with crystal structures. We present results from applying the threshold algorithm to four polymorphic organic molecular crystals, examine the influence of applying space group symmetry constraints during the simulations, and discuss the relationship between the structure of the energy landscape and the intermolecular interactions present in the crystals.

A density-functional benchmark of vibrational free-energy corrections for molecular crystal polymorphism

Many crystal structure prediction protocols only concern themselves with the electronic energy of molecular crystals. However, vibrational contributions to the free energy ( Fvib) can be significant in determining accurate stability rankings for crystal candidates. While force-field studies have been conducted to gauge the magnitude of these free-energy corrections, highly accurate results from quantum mechanical methods, such as density-functional theory (DFT), are desirable. Here, we introduce the PV17 set of 17 polymorphic pairs of organic molecular crystals, for which plane wave DFT is used to calculate the vibrational free energies and free-energy differences (Δ Fvib) between each pair. Our DFT results confirm that the vibrational free-energy corrections are small, having a mean value of 1.0 kJ/mol and a maximum value of 2.3 kJ/mol for the PV17 set. Furthermore, we assess the accuracy of a series of lower-cost DFT, semi-empirical, and force-field models for computing Δ Fvib that have been proposed in the literature. It is found that calculating Fvib using the Γ-point frequencies does not provide Δ Fvib values of sufficiently high quality. In addition, Δ Fvib values calculated using various approximate methods have mean absolute errors relative to our converged DFT results of equivalent or larger magnitude than the vibrational free-energy corrections themselves. Thus, we conclude that, in a crystal structure prediction protocol, it is preferable to forego the inclusion of vibrational free-energy corrections than to estimate them with any of the approximate methods considered here.

Packing Preferences of Chalcones: A Model Conjugated Pharmaceutical Scaffold

We sought the crystal packing preferences of the chalcone scaffold by analyzing 232 single-component crystal structures of chalcones with a small (six or fewer non-hydrogen atoms) substituent on either or both rings, including the unsubstituted molecule. This covers 216 molecules, as some are polymorphic, and 277 independent molecular conformations, as 16% of the crystal structures have more than one symmetry independent molecule. Quantum mechanical conformational profiles of the unsubstituted molecule and the almost 5000 crystal structures within 20 kJ mol^-1 of the global minimum generated in a crystal structure prediction (CSP) study have been used to complement this analysis. Although π conjugation would be expected to favor a planar molecule, there are a significant number of crystal structures containing nonplanar molecules with an approximately 50° angle between the aromatic rings. The relative orientations of the molecules in the inversion-related dimers and translation-related dimers in the experimental crystal structures show the same trends as in the CSP-generated structures for the unsubstituted molecule, allowing for the substituent making the side-to-side distances larger. There is no type of dimer geometry associated with particularly favorable lattice energies for the chalcone core. Less than a third of the experimental structures show a face-to-face contact associated with π···π stacking. Analysis of the experimental crystal structures with XPac and Mercury finds various pairs of isostructural crystals, but the largest isostructural set had only 15 structures, with all substituents (mainly halogens) in the para position. The most common one-dimensional motif, found in half of the experimental crystal structures, is a translation-related side-to-side packing, which can be adopted by all the observed conformations. This close-packed motif can be adopted by chalcones with a particularly wide variety of substituents as the substituents are at the periphery. Thus, although the crystal structures of the substituted chalcones show thermodynamically plausible packings of the chalcone scaffold, there is little evidence for any crystal engineering principle of preferred chalcone scaffold packing beyond close packing of the specific molecule.

Quantum Mechanical-Based Stability Evaluation of Crystal Structures for HIV-Targeted Drug Cabotegravir

The long-acting parenteral formulation of the HIV integrase inhibitor cabotegravir (GSK744) is currently being developed to prevent HIV infections, benefiting from infrequent dosing and high efficacy. The crystal structure can affect the bioavailability and efficacy of cabotegravir. However, the stability determination of crystal structures of GSK744 have remained a challenge. Here, we introduced an ab initio protocol to determine the stability of the crystal structures of pharmaceutical molecules, which were obtained from crystal structure prediction process starting from the molecular diagram. Using GSK744 as a case study, the ab initio predicted that Gibbs free energy provides reliable further refinement of the predicted crystal structures and presents its capability for becoming a crystal stability determination approach in the future. The proposed work can assist in the comprehensive screening of pharmaceutical design and can provide structural predictions and stability evaluation for pharmaceutical crystals.

A Family of Superhelicenes: Easily Tunable, Chiral Nanographenes by Merging Helicity with Planar π Systems

We designed a straightforward synthetic route towards a full-fledged family of π-extended helicenes: superhelicenes. They have two hexa-peri-hexabenzocoronenes (HBCs) in common that are connected via a central five-membered ring. By means of structurally altering this 5-membered ring, we realized a versatile library of molecular building blocks. Not only the superhelicene structure, but also their features are tuned with ease. In-depth physico-chemical characterizations served as a proof of concept thereof. The superhelicene enantiomers were separated, their circular dichroism was measured in preliminary studies and concluded with an enantiomeric assignment. Our work was rounded-off by crystal structure analyses. Mixed stacks of M- and P-isomers led to twisted molecular wires. Using such stacks, charge-carrier mobilities were calculated, giving reason to expect outstanding hole transporting properties.

X-shaped thiadiazole-containing double [7]heterohelicene with strong chiroptical response and π-stacked homochiral assembly

An X-shaped double [7]heterohelicene 1 bearing four thiadiazole units is synthesized by regioselective cyclodehydrogenation. Enantiopure 1 exhibits excellent chiroptical properties with an impressive absorption dissymmetry factor of up to 0.027, as well as a compact π-stacked homochiral assembly which is unprecedented in the realm of double helicenes.

Examination of aggregation-induced enhanced emission in a propeller-shaped chiral nonconjugated blue emitter from restricted intramolecular rotation and J-type ππ stacking interactions

Herein, to get rid of aggregation-caused quenching (ACQ) in the solid phase, which is generally observed in π-conjugated planar molecules, a new chiral nonconjugated molecule with the propeller-shaped blue emitter property was prepared and characterized, and its photoluminescence behavior in the solid and solution phases were investigated through single crystal X-ray crystallography and photophysical studies. To further understand the aggregation-induced enhanced emission process (AIEE), concentration effect and solvent effect on the fluorescence properties of the solution phase and fluorescence quantum yield measurements in the solid and solution states were performed. In addition, thermal gravimetric analysis (TGA), cyclic voltammogram measurements (CV) and theoretical analysis of the molecule were carried out. According to the results of the experimental work done, the molecule showed aggregation-induced enhanced blue emission (AIEE) in the crystal state, which arose from the strong J-type ππ stacking interactions between the adjacent rings of the molecules, and the restricted intramolecular rotation process (RIR). The solvent polarity-dependent emission also verified the AIEE process. Therefore, combining the advantages of nonconjugation and chirality properties in the synthesis of the molecule afforded a new, unusual AIEE material and provided a new way for the design of a nonconjugated chiral fluorescent optoelectronic material.

HCGA: Highly comparative graph analysis for network phenotyping

Networks are widely used as mathematical models of complex systems across many scientific disciplines. Decades of work have produced a vast corpus of research characterizing the topological, combinatorial, statistical, and spectral properties of graphs. Each graph property can be thought of as a feature that captures important (and sometimes overlapping) characteristics of a network. In this paper, we introduce HCGA, a framework for highly comparative analysis of graph datasets that computes several thousands of graph features from any given network. HCGA also offers a suite of statistical learning and data analysis tools for automated identification and selection of important and interpretable features underpinning the characterization of graph datasets. We show that HCGA outperforms other methodologies on supervised classification tasks on benchmark datasets while retaining the interpretability of network features. We exemplify HCGA by predicting the charge transfer in organic semiconductors and clustering a dataset of neuronal morphology images.

Crystal Structure Prediction Methods for Organic Molecules: State of the Art

The prediction of the crystal structures that a given organic molecule is likely to form is an important theoretical problem of significant interest for the pharmaceutical and agrochemical industries, among others. As evidenced by a series of six blind tests organized over the past 2 decades, methodologies for crystal structure prediction (CSP) have witnessed substantial progress and have now reached a stage of development where they can begin to be applied to systems of practical significance. This article reviews the state of the art in general-purpose methodologies for CSP, placing them within a common framework that highlights both their similarities and their differences. The review discusses specific areas that constitute the main focus of current research efforts toward improving the reliability and widening applicability of these methodologies, and offers some perspectives for the evolution of this technology over the next decade.

Integrating Computational and Experimental Workflows for Accelerated Organic Materials Discovery

Organic materials find application in a range of areas, including optoelectronics, sensing, encapsulation, molecular separations, and photocatalysis. The discovery of materials is frustratingly slow however, particularly when contrasted to the vast chemical space of possibilities based on the near limitless options for organic molecular precursors. The difficulty in predicting the material assembly, and consequent properties, of any molecule is another significant roadblock to targeted materials design. There has been significant progress in the development of computational approaches to screen large numbers of materials, for both their structure and properties, helping guide synthetic researchers toward promising materials. In particular, artificial intelligence techniques have the potential to make significant impact in many elements of the discovery process. Alongside this, automation and robotics are increasing the scale and speed with which materials synthesis can be realized. Herein, the focus is on demonstrating the power of integrating computational and experimental materials discovery programmes, including both a summary of key situations where approaches can be combined and a series of case studies that demonstrate recent successes.

Crystal structure prediction of energetic materials and a twisted arene with Genarris and GAtor

A molecular crystal structure prediction workflow, based on the random structure generator, Genarris, and the genetic algorithm (GA), GAtor, is successfully applied to two energetic materials and a chiral arene.

Structure prediction of crystals, surfaces and nanoparticles

We review the current techniques used in the prediction of crystal structures and their surfaces and of the structures of nanoparticles. The main classes of search algorithm and energy function are summarized, and we discuss the growing role of methods based on machine learning. We illustrate the current status of the field with examples taken from metallic, inorganic and organic systems. This article is part of a discussion meeting issue 'Dynamic in situ microscopy relating structure and function'.

Application of XDM to ionic solids: The importance of dispersion for bulk moduli and crystal geometries

Dispersion corrections are essential in the description of intermolecular interactions; however, dispersion-corrected functionals must also be transferrable to hard solids. The exchange-hole dipole moment (XDM) model has demonstrated excellent performance for non-covalent interactions. In this article, we examine its ability to describe the relative stability, geometry, and compressibility of simple ionic solids. For the specific cases of the cesium halides, XDM-corrected functionals correctly predict the energy ranking of the B1 and B2 forms, and a dispersion contribution is required to obtain this result. Furthermore, for the lattice constants of the 20 alkali halides, the performance of XDM-corrected functionals is excellent, provided that the base functional's exchange enhancement factor properly captures non-bonded repulsion. The mean absolute errors in lattice constants obtained with B86bPBE-XDM and B86bPBE-25X-XDM are 0.060 Å and 0.039 Å, respectively, suggesting that delocalization error also plays a minor role in these systems. Finally, we considered the calculation of bulk moduli for alkali halides and alkaline-earth oxides. Previous claims in the literature that simple generalized gradient approximations, such as PBE, can reliably predict experimental bulk moduli have benefited from large error cancellations between neglecting both dispersion and vibrational effects. If vibrational effects are taken into account, dispersion-corrected functionals are quite accurate (4 GPa-5 GPa average error), again, if non-bonded repulsion is correctly represented. Careful comparisons of the calculated bulk moduli with experimental data are needed to avoid systematic biases and misleading conclusions.

Persistent Organic Room-Temperature Phosphorescence in Cyclohexane-trans-1,2-Bisphthalimide Derivatives: The Dramatic Impact of Heterochiral vs Homochiral interactions

Persistent metal-free room-temperature phosphorescence (RTP) materials attract significant interest owing to the production of long-lived triplet excited states. Although several organic designs show RTP, the impact of intermolecular interactions on the triplet excitons stabilization and migrations remains hardly understood because obtaining different ordered intermolecular interactions while conserving identical molecular electronic properties is very challenging. We propose here a new strategy to circumvent this problem by taking advantage of the distinct molecular packing that can be found between enantiomer and racemic forms of a chiral molecule. Structural, photophysical, and chiroptical investigations of chiral cyclohexane bisphthalimide derivatives showed that heterochiral and homochiral dimer interactions play a crucial role on the triplet excited state stabilization, resulting in higher RTP efficiency for enantiopure systems than for racemic one. This study paves the way to the use of molecular chirality to rationalize supramolecular properties arising from subtle intermolecular interactions.

Evolutionary chemical space exploration for functional materials: computational organic semiconductor discovery

Computational methods, including crystal structure and property prediction, have the potential to accelerate the materials discovery process by enabling structure prediction and screening of possible molecular building blocks prior to their synthesis. However, the discovery of new functional molecular materials is still limited by the need to identify promising molecules from a vast chemical space. We describe an evolutionary method which explores a user specified region of chemical space to identify promising molecules, which are subsequently evaluated using crystal structure prediction. We demonstrate the methods for the exploration of aza-substituted pentacenes with the aim of finding small molecule organic semiconductors with high charge carrier mobilities, where the space of possible substitution patterns is too large to exhaustively search using a high throughput approach. The method efficiently explores this large space, typically requiring calculations on only ∼1% of molecules during a search. The results reveal two promising structural motifs: aza-substituted naphtho[1,2-a]anthracenes with reorganisation energies as low as pentacene and a series of pyridazine-based molecules having both low reorganisation energies and high electron affinities.

Charge mobility calculation of organic semiconductors without use of experimental single-crystal data

Prediction of material properties of newly designed molecules is a long-term goal in organic electronics. In general, it is a difficult problem, because the material properties are dominated by the unknown packing structure. We present a practical method to obtain charge transport properties of organic single crystals, without use of experimental single-crystal data. As a demonstration, we employ the promising molecule C10-DNBDT. We succeeded in quantitative evaluation of charge mobility of the single crystal using our quantum wave-packet dynamical simulation method. Here, the single-crystal data is computationally obtained by searching possible packing structures from structural formula of the molecule. We increase accuracy in identifying the actual crystal structure from suggested ones by using not only crystal energy but also similarity between calculated and experimental powder X-ray diffraction patterns. The proposed methodology can be a theoretical design technique for efficiently developing new high-performance organic semiconductors, since it can estimate the charge transport properties at early stage in the process of material development.

First-Principles-Based Force Field for 2,6-Diamino-3,5-dinitropyrazine-1-oxide (LLM-105)

2,6-Diamino-3,5-dinitropyrazine-1-oxide (LLM-105) is a highly promising energetic material (EM) with high safety. Understanding its microscopic response mechanisms within the external stimulus is meaningful for the design of EMs. In order to comprehend the complicated phenomena, it is necessary to employ molecular simulation methods to investigate the response mechanisms with the force field (FF) at an atomic level. In this work, we developed a tailored FF for LLM-105 based on first-principles calculations. The validity of the FF was evaluated by molecular dynamics simulations. The structural parameters of LLM-105 predicted by FF are in good agreement with the experimental values, such as lattice constant, bond length, bond angle, dihedral angle and center of mass, and so forth. Moreover, the FF possesses good performance to describe the structural response on pressure accurately. In general, our work not only builds a balanced FF in gas and condensed phases, but also provides a useful tool to study the properties about LLM-105 at a large scale, which is helpful to improve the understanding about the balance between energy and safety in EMs.

Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. II. Smoothed intramolecular potentials

The application of crystal structure prediction (CSP) to industrially relevant molecules requires the handling of increasingly large and flexible compounds. A revised model for the effect of molecular flexibility on the lattice energy that removes the discontinuities and non-differentiabilities present in earlier models (Sugden et al., 2016), with a view to improving the performance of CSP is presented. The approach is based on the concept of computing a weighted average of local models, and has been implemented within the CrystalPredictor code. Through the comparative investigation of several compounds studied in earlier literature, it is shown that this new model results in large reductions in computational effort (of up to 65%) and in significant increases in reliability. The approach is further applied to investigate, for the first time, the computational polymorphic landscape of flufenamic acid for Z' = 1 structures, resulting in the successful identification of all three experimentally resolved polymorphs within reasonable computational time.

Impact of morphology, side-chains, and crystallinity on charge-transport properties of π-extended double helicenes

We report a computational study on the effect of side-chain substitution, heteroaromatic substitution and unique crystal packing on the charge transport and mobility of three double helicene molecules. These double helicene (DH) molecules, having curved π-conjugation, are structural hybrids of non-planar [6]helicene and planar tribenzo[b,n,pqr]perylene (TBP). We find that side-chain substitution has only a effect on intrinsic electronic properties in DHs but dramatically impacts the packing arrangement, morphologies and transport network, exhibited in calculated charge transport parameters. Interestingly, the dimensionality of the transport evolves from one dimensional to three dimensional with side-chain substitution (DH2) and heteroaromatic substitution (DH3). Using two different well-known transport models, we have established a direct link between the morphology, transport connectivity, and hole mobilities. While both unsubstituted and substituted DHs exhibit high hole mobilities in the ordered phase, the results show that with inclusion of positional disorder, the mobilities of disordered DH1 and DH3 are lower while the mobility of DH2 remain nearly unchanged. We relate this effect to the dimensionality of their unique transport networks. These DH molecules are promising organic semiconductors with high mobilities in ordered and disordered phases, with predicted values that lie in the range of ∼1 to 10 cm2 V-1 s-1.

The interplay among molecular structures, crystal symmetries and lattice energy landscapes revealed using unsupervised machine learning: a closer look at pyrrole azaphenacenes

Using unsupervised machine learning and CSPs to help crystallographers better understand how crystallizations are affected by molecular structures.

The influence of nitrogen position on charge carrier mobility in enantiopure aza[6]helicene crystals

A computational study exploring the influence of the nitrogen position on charge carrier mobility in enantiopure aza[6]helicene crystals

New Helicene-Type Hole-Transporting Molecules for High-Performance and Durable Perovskite Solar Cells

Three azahelicene derivatives with electron-rich bis(4-methoxyphenyl)amino or bis( p-methoxyphenyl)aminophenyl groups at the terminals were deliberately designed, synthesized, and characterized as hole-transporting materials (HTMs) for perovskite solar cells (PSCs). Optical and thermal properties, energy level alignments, film morphologies, hole extraction ability, and hole mobility were studied in detail. PSCs using the newly synthesized molecules as HTMs were fabricated. A maximum power conversion efficiency (PCE) of 17.34% was observed for the bis( p-methoxyphenyl)amino-substituted derivative (SY1) and 16.10% for the bis( p-methoxyphenyl)aminophenyl-substituted derivative (SY2). Longer-chain substituent such as hexyloxy group greatly diminishes the efficiency. In addition, the dopant-free devices fabricated with SY1 as the HTM shows an average PCE of 12.13%, which is significantly higher than that of spiro-OMeTAD (7.61%). The ambient long-term stability test revealed that after 500 h, the devices prepared from SY1 and SY2 retained more than 96% of its initial performance, which is much improved than the reference device with standard spiro-OMeTAD as the HTM under the same conditions. Detailed material cost analysis reveals that the material cost for SY1 is less than 8% of that for spiro-OMeTAD. These results provide a useful direction for designing a new class of HTMs to prepare highly efficient and more durable PSCs.

Read between the Molecules: Computational Insights into Organic Semiconductors

The performance and key electronic properties of molecular organic semiconductors are dictated by the interplay between the chemistry of the molecular core and the intermolecular factors of which manipulation has inspired both experimentalists and theorists. This Perspective presents major computational challenges and modern methodological strategies to advance the field. The discussion ranges from insights and design principles at the quantum chemical level, in-depth atomistic modeling based on multiscale protocols, morphological prediction and characterization as well as energy-property maps involving data-driven analysis. A personal overview of the past achievements and future direction is also provided.

Is zeroth order crystal structure prediction (CSP_0) coming to maturity? What should we aim for in an ideal crystal structure prediction code?

Crystal structure prediction based on searching for the global minimum in the lattice energy (CSP_0) is growing in use for guiding the discovery of new materials, for example, new functional materials, new phases of interest to planetary scientists and new polymorphs relevant to pharmaceutical development. This Faraday Discussion can assess the progress of CSP_0 over the range of types of materials to which CSP is currently and could be applied, which depends on our ability to model the variety of interatomic forces in crystals. The basic hypothesis, that the outcome of crystallisation is determined by thermodynamics, needs examining by considering methods of modelling relative thermodynamic stability not only as a function of pressure and temperature, but also of size, solvent and the presence of heterogeneous templates or impurities (CSP_thd). Given that many important materials persist, and indeed may be formed, when they are not the most thermodynamically stable structure, we need to define what would be required of an ideal CSP code (CSP_aim).