Effect of Substituent Location on the Relationship between the Transition Dipole Moments, Difference Static Dipole, and Hydrophobicity in Squaraine Dyes for Quantum Information Devices.

Aggregates of organic dyes that exhibit excitonic coupling have a wide array of applications, including medical imaging, organic photovoltaics, and quantum information devices. The optical properties of a dye monomer, as a basis of dye aggregate, can be modified to strengthen excitonic coupling. Squaraine (SQ) dyes are attractive for those applications due to their strong absorbance peak in the visible range. While the effects of substituent types on the optical properties of SQ dyes have been previously examined, the effects of various substituent locations have not yet been investigated. In this study, density functional theory (DFT) and time-dependent density functional theory (TD-DFT) were used to investigate the relationships between SQ substituent location and several key properties of the performance of dye aggregate systems, namely, difference static dipole (Δd), transition dipole moment (µ), hydrophobicity, and the angle (θ) between Δd and µ. We found that attaching substituents along the long axis of the dye could increase µ while placement off the long axis was shown to increase Δd and reduce θ. The reduction in θ is largely due to a change in the direction of Δd as the direction of µ is not significantly affected by substituent position. Hydrophobicity decreases when electron-donating substituents are located close to the nitrogen of the indolenine ring. These results provide insight into the structure-property relationships of SQ dyes and guide the design of dye monomers for aggregate systems with desired properties and performance.

Intramolecular Charge Transfer and Ultrafast Nonradiative Decay in DNA-Tethered Asymmetric Nitro- and Dimethylamino-Substituted Squaraines.

Molecular (dye) aggregates are a materials platform of interest in light harvesting, organic optoelectronics, and nanoscale computing, including quantum information science (QIS). Strong excitonic interactions between dyes are key to their use in QIS; critically, properties of the individual dyes govern the extent of these interactions. In this work, the electronic structure and excited-state dynamics of a series of indolenine-based squaraine dyes incorporating dimethylamino (electron donating) and/or nitro (electron withdrawing) substituents, so-called asymmetric dyes, were characterized. The dyes were covalently tethered to DNA Holliday junctions to suppress aggregation and permit characterization of their monomer photophysics. A combination of density functional theory and steady-state absorption spectroscopy shows that the difference static dipole moment (Δd) successively increases with the addition of these substituents while simultaneously maintaining a large transition dipole moment (µ). Steady-state fluorescence and time-resolved absorption and fluorescence spectroscopies uncover a significant nonradiative decay pathway in the asymmetrically substituted dyes that drastically reduces their excited-state lifetime (τ). This work indicates that Δd can indeed be increased by functionalizing dyes with electron donating and withdrawing substituents and that, in certain classes of dyes such as these asymmetric squaraines, strategies may be needed to ensure long τ, e.g., by rigidifying the π-conjugated network.

Data-Driven and Multiscale Modeling of DNA-Templated Dye Aggregates.

Dye aggregates are of interest for excitonic applications, including biomedical imaging, organic photovoltaics, and quantum information systems. Dyes with large transition dipole moments (µ) are necessary to optimize coupling within dye aggregates. Extinction coefficients (ε) can be used to determine the µ of dyes, and so dyes with a large ε (>150,000 M−1cm−1) should be engineered or identified. However, dye properties leading to a large ε are not fully understood, and low-throughput methods of dye screening, such as experimental measurements or density functional theory (DFT) calculations, can be time-consuming. In order to screen large datasets of molecules for desirable properties (i.e., large ε and µ), a computational workflow was established using machine learning (ML), DFT, time-dependent (TD-) DFT, and molecular dynamics (MD). ML models were developed through training and validation on a dataset of 8802 dyes using structural features. A Classifier was developed with an accuracy of 97% and a Regressor was constructed with an R2 of above 0.9, comparing between experiment and ML prediction. Using the Regressor, the ε values of over 18,000 dyes were predicted. The top 100 dyes were further screened using DFT and TD-DFT to identify 15 dyes with a µ relative to a reference dye, pentamethine indocyanine dye Cy5. Two benchmark MD simulations were performed on Cy5 and Cy5.5 dimers, and it was found that MD could accurately capture experimental results. The results of this study exhibit that our computational workflow for identifying dyes with a large µ for excitonic applications is effective and can be used as a tool to develop new dyes for excitonic applications.