Singlet fission, the process of forming two triplet excitons from one singlet exciton, is a characteristic reserved for only a handful of organic molecules due to the atypical energetic requirement for low energy excited triplet states. The predominant strategy for achieving such a trait is by increasing ground state diradical character; however, this greatly reduces ambient stability. Herein, we exploit Baird's rule of excited state aromaticity to manipulate the singlet−triplet energy gap and create novel singlet fission candidates. We achieve this through the inclusion of a [4n] 5-membered heterocycle, whose electronic resonance promotes aromaticity in the triplet state, stabilizing its energy relative to the singlet excited state. Using this theory, we design a family of derivatives of indolonaphthyridine thiophene (INDT) with highly tunable excited state energies. Not only do we access novel singlet fission materials, they also exhibit excellent ambient stability, imparted due to the delocalized nature of the triplet excited state. Spin-coated films retained up to 85% activity after several weeks of exposure to oxygen and light, while analogous films of TIPS-pentacene showed full degradation after 4 days, showcasing the excellent stability of this class of singlet fission scaffold. Extension of our theoretical analysis to almost ten thousand candidates reveals an unprecedented degree of tunability and several thousand potential fission-capable candidates, while clearly demonstrating the relationship between triplet aromaticity and singlet−triplet energy gap, confirming this novel strategy for manipulating the exchange energy in organic materials.

Using a simple π-conjugated trimer, EDOT-phenylene-EDOT (where EDOT = 3,4-ethylenedioxythiophene), we evaluate the effect that fluorine substituents have upon changes in conformation, conjugation and oxidation potentials in π-conjugated structures. These variations are assessed as a function of the fluorine atom's propensity to feature in hydrogen and/or halogen bonding with other heteroatoms. The molecular motif was chosen because the EDOT unit presents the possibility of competing O•••X or S•••X non-covalent contacts (where X = H or F). Such non-bonding interactions are acknowledged to be highly influential in dictating molecular and polymer morphology and inducing changes in certain physical properties. We studied four compounds, beginning with an unsubstituted bridging phenylene ring and then adding one, two, or four fluorine units to the parent molecule. Our studies involve single crystal XRD studies, cyclic voltammetry, absorption spectroscopy and density functional theory calculations to identify the dominant non-covalent interactions and elucidate their effects on the molecules described. Experimental studies have also been carried out on the corresponding electrochemically synthesized polymers to confirm that these non-covalent interactions and their effects persist in polymers. Our findings show that hydrogen bonding and halogen bonding feature in these molecules and their corresponding polymers.

Multifidelity modeling is a technique for fusing the information from two or more datasets into one model. It is particularly advantageous when one dataset contains few accurate results and the other contains many less accurate results. Within the context of modeling potential energy surfaces, the low-fidelity dataset can be made up of a large number of inexpensive energy computations that provide adequate coverage of the N-dimensional space spanned by the molecular internal coordinates. The high-fidelity dataset can provide fewer but more accurate electronic energies for the molecule in question. Here, we compare the performance of several neural network-based approaches to multifidelity modeling. We show that the four methods (dual, Δ-learning, weight transfer, and Meng–Karniadakis neural networks) outperform a traditional implementation of a neural network, given the same amount of training data. We also show that the Δ-learning approach is the most practical and tends to provide the most accurate model.

The conformational variability of π-conjugated molecules or polymers, defined by the capacity for rotation among the connected ring moieties that comprise the structure, directly impacts properties of organic semiconductors ranging from material processability to the electronic, redox, optical, and mechanical characteristics. Thus, the shapes of the potential energy surfaces and corresponding energy barriers of inter-ring rotations as a function of the system chemistry serve as critical parameters for both molecular/polymer and material design. Here, we systematically examine the effects of various ring chemistries, ortho-positioned substituents, and oligomer length on the rotation of two rings in the center of the system. Two primary factors, as one might expect, dictate the potential energy surface (PES) for rotation: the degree of π-electron delocalization across the dihedral bond and the noncovalent interactions among ortho-substituted atoms and/or groups. Each factor can stabilize or destabilize fully planar conformations. Notably, the oligomer chain length has a little-to-no discernible impact on the rotation energetics in systems with more than six rings. We identify four distinct shapes for PES of rotation that relate to chemical composition, which enable us to develop classification models to classify a system’s dihedral potential energy surface from a two-dimensional structure. We then combine these classification models and previously reported analytical methods to quickly predict polymer chain dimensions from a monomer structure. The insights derived here are expected to help direct and accelerate the in silico design of new molecular and polymer classes with the desired optoelectronic properties and ease of processing.