Quantum Chemical Study Aimed at Modeling Efficient Aza-BODIPY NIR Dyes: Molecular and Electronic Structure, Absorption, and Emission Spectra

Rational design of CT-coupled J-aggregation platform based on Aza-BODIPY for highly efficient phototherapy

Supramolecular engineering is exceptionally appealing in the design of functional materials, and J-aggregates resulting from noncovalent interactions offer intriguing features. However, building J-aggregation platforms remains a significant challenge. Herein, we report 3,5-dithienyl Aza-BODIPYs with a donor-acceptor-donor (D-A-D) architecture as the first charge transfer (CT)-coupled J-aggregation BODIPY-type platform. The core acceptor moieties in one molecule interact with donor units in neighboring molecules to generate slip-stacked packing motifs, resulting in CT-coupled J-aggregation with a redshifted wavelength up to 886 nm and an absorption tail over 1100 nm. The J-aggregates show significant photoacoustic signals and high photothermal conversion efficiency of 66%. The results obtained in vivo show that the J-aggregates have the potential to be used for tumor photothermal ablation and photoacoustic imaging. This study not only demonstrates Aza-BODIPY with D-A-D as a novel CT-coupled J-aggregation platform for NIR phototherapy materials but also motivates further study on the design of J-aggregation.

Highly crystalline and fluorescent BODIPY-labelled phenyl-triazole-coumarins as n-type semiconducting materials for OFET devices

In this work, the synthesis of BODIPY-phenyl-triazole labelled coumarins (BPhTCs) using a two-step approach is described. The influence of the BODIPY appending on the photophysical, electrochemical and thermal properties of the phenyl-triazole-coumarin precursors (PhTCs) was investigated. Band gap energies were measured by absorption spectroscopy (2.20 ± 0.02 eV in the solid and 2.35 ± 0.01 eV in solution) and cyclic voltammetry (2.10 ± 0.05 eV). The results are supported by DFT calculations confirming the presence of lowest LUMO levels that facilitate the electron injection and stabilize the electron transport. Their charge-transport parameters were measured in Organic Field-Effect Transistor (OFET) devices. BPhTCs showed an ambipolar transistor behavior with good n-type charge mobilities (10-2 cm2V-1s-1) allowing these derivatives to be employed as promising semiconducting crystalline and fluorescent materials with good thermal and air stability up to 250 °C.

XPS and quantum chemical analysis of 4Me-BODIPY derivatives

The results of a X-ray photoelectron spectroscopy (XPS) and steady-state absorption spectroscopy study of the electronic structure, and cationic and excited states of a series of 1,3,5,7-tetramethyl-substituted BODIPYs (4Me,2R-BODIPYs) are presented. The experimental data were interpreted using high-level ab initio quantum chemical computations, including the algebraic diagrammatic construction method for the polarization propagator of the second order (ADC(2)), the outer-valence Green's function (OVGF) method, the density functional (DFT) approach, and the time-dependent DFT (TD-DFT) approach. Substitution effects on the XPS and absorption spectra were determined for 2,6-positions of 4Me,2R-BODIPY pyrrole nuclei (R = H, Br, Bu, benzyl). A very satisfactory performance of the DFT Koopmans theorem analogue was demonstrated with respect to the energy intervals between the electronic levels of 4Me,2R-BODIPY above 13 eV (BHHLYP functional) and the values of the HOMO-LUMO energy gap (ωB97X functional).

Data-driven modeling of S0 → S1 excitation energy in the BODIPY chemical space: High-throughput computation, quantum machine learning, and inverse design

Derivatives of BODIPY are popular fluorophores due to their synthetic feasibility, structural rigidity, high quantum yield, and tunable spectroscopic properties. While the characteristic absorption maximum of BODIPY is at 2.5 eV, combinations of functional groups and substitution sites can shift the peak position by ±1 eV. Time-dependent long-range corrected hybrid density functional methods can model the lowest excitation energies offering a semi-quantitative precision of ±0.3 eV. Alas, the chemical space of BODIPYs stemming from combinatorial introduction of-even a few dozen-substituents is too large for brute-force high-throughput modeling. To navigate this vast space, we select 77 412 molecules and train a kernel-based quantum machine learning model providing <2% hold-out error. Further reuse of the results presented here to navigate the entire BODIPY universe comprising over 253 giga (253 × 10⁹) molecules is demonstrated by inverse-designing candidates with desired target excitation energies.