Vibronic coupling density analysis for the chain-length dependence of reorganization energies in oligofluorenes: a comparative study with oligothiophenes

Machine-learning-assisted performance improvements for multi-resonance thermally activated delayed fluorescence molecules

With favorable colour purity, multi-resonance thermally activated delayed fluorescence (MR-TADF) molecules exhibit enormous potential in high-definition displays. Due to the relatively small chemical space of MR-TADF molecules, it is challenging to improve molecular performance through domain-specific expertise alone. To address this problem, we focused on optimizing the classic molecule, DABNA-1, using machine learning (ML). Molecular morphing operations were initially employed to generate the adjacent chemical space of DABNA-1. Subsequently, a machine learning model was trained with a limited database and used to predict the properties throughout the generated chemical space. It was confirmed that the top 100 molecules suggested by machine learning present excellent electronic structures, characterized by small reorganization energy and singlet-triplet energy gaps. Our results indicate that the improvement in electronic structures can be elucidated through the view of the molecular orbital (MO). The results also reveal that the top 5 molecules present weaker vibronic peaks of the emission spectrum, demonstrating higher colour purity when compared to DABNA-1. Notably, the M2 molecule presents a high RISC rate, indicating its promising future as a high-efficiency MR-TADF molecule. Our machine-learning-assisted approach facilitates the rapid optimization of classical molecules, addressing a crucial requirement within the organic optoelectronic materials community.

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.

Rational design of organic semiconductors with low internal reorganization energies for hole and electron transport: position effect of aza-substitution in phenalenyl derivatives

Amphoteric-redox phenalenyl radical (PLY) is a suitable candidate used to design ambipolar organic materials. Because the singly occupied nonbonding molecular orbital (NBMO) of PLY has a perfect local nonbonding character, its internal reorganization energy (λ) for transporting holes (λ⁺) or electrons (λ^-) is known to be small. Herein, PLY is employed to study the position effect of the aza group on the λ. By adding or extracting an electron from the NBMO, the bond length alterations can be minute. Therefore, the PLY derivatives are also an excellent candidate to study the contributions from the bond angle alterations to the λ. Substituting the aza groups at the β- or α-positions of PLY shows two different trends. When consecutively substituting the aza group at the three β-positions of PLY, the λs are consistently decreased. Contrarily, a series of double functionalization of aza groups at the four α-positions of PLY, the λs are increased. It is because the local bonding or antibonding character in frontier orbitals (FMO) is observed in α2N-PLY and α4N-PLY. As the FMOs of the three β-substituted PLYs and α6N-PLY have perfect local nonbonding character, we found the bond angle alterations are the main contributors of λ. The λs for most aza-PLYs were smaller than 100 meV. Thus, we propose a design rule for substituting aza groups on the parent molecules with strong local nonbonding character in their FMOs. Based on the adiabatic ionization potential and electron affinity, two π-extended PLY derivatives with small λ were recommended for fabricating air-stable ambipolar OFET.

Active discovery of organic semiconductors

The versatility of organic molecules generates a rich design space for organic semiconductors (OSCs) considered for electronics applications. Offering unparalleled promise for materials discovery, the vastness of this design space also dictates efficient search strategies. Here, we present an active machine learning (AML) approach that explores an unlimited search space through consecutive application of molecular morphing operations. Evaluating the suitability of OSC candidates on the basis of charge injection and mobility descriptors, the approach successively queries predictive-quality first-principles calculations to build a refining surrogate model. The AML approach is optimized in a truncated test space, providing deep methodological insight by visualizing it as a chemical space network. Significantly outperforming a conventional computational funnel, the optimized AML approach rapidly identifies well-known and hitherto unknown molecular OSC candidates with superior charge conduction properties. Most importantly, it constantly finds further candidates with highest efficiency while continuing its exploration of the endless design space.

FB-REDA: fragment-based decomposition analysis of the reorganization energy for organic semiconductors

We present a fragment-based decomposition analysis tool (FB-REDA) for the reorganisation energy (λ). This tool delivers insights on how to rationally design low-λ organic semiconductors. The contribution of the fragment vibrational modes to the reorganization energy is exploited to identity the individual contributions of the molecular building blocks. The usefulness of the approach is demonstrated by offering three strategies to reduce the reorganization energy of a promising dopant-free hole transport material (TPA1PM, λ = 213 meV). A reduction of nearly 50% (TPD3PM, λ = 108 meV) is achieved. The proposed design principles are likely transferable to other organic semiconductors exploiting common molecular building blocks.

Applying strong external electric field to thiophene-based oligomers: A promising approach to upgrade semiconducting performance

A key parameter dictating the rate of charge transfer (CT) is reorganization energy (λ), an energy associated with geometry changes during hole/electron transfer. We show that "ironing" the inter-ring dihedral angles of oligothiophenes via proper substitutions or insertions (e.g., -OR, -F or -C≡C-), decreases the λ and thus promotes CT according to Marcus equation. Our results demonstrate, to attain a smaller λ, extending oligomer length is only significant if the flattened backbone structure is realized. Of great interest is that external electric fields, which are ubiquitous in electronic devices yet commonly overlooked in the computation of λ, can have a significantly greater impact than conventional substitutions. It is important to emphasize, the responses of λ to external fields is system-dependent. Compared to fused-ring conjugated systems, single-bond connected thiophenes are more sensitive to external fields. F_x lowers the λ (552 meV) of quaterthiophene by almost 80% at the intensity of 1 V/Å, down to a value (125 meV) which is even lower than that of pentacene (154 meV) and rubrene (219 meV) at the same level of theory. © 2016 Wiley Periodicals, Inc.