The discovery of high-performance functional materials is crucial for overcoming technical issues in modern industries. Extensive efforts have been devoted toward accelerating and facilitating this process, not only experimentally but also from the viewpoint of materials design. Recently, machine learning has attracted considerable attention, as it can provide rational guidelines for efficient material exploration without time-consuming iterations or prior human knowledge. In this regard, here we develop an inverse design model based on a deep encoder-decoder architecture for targeted molecular design. Inspired by neural machine language translation, the deep neural network encoder extracts hidden features between molecular structures and their material properties, while the recurrent neural network decoder reconstructs the extracted features into new molecular structures having the target properties. In material design tasks, the proposed fully data-driven methodology successfully learned design rules from the given databases and generated promising light-absorbing molecules and host materials for a phosphorescent organic light-emitting diode by creating new ligands and combinatorial rules.

Computationally predicting reverse intersystem crossing (RISC) rates is important for designing new thermally activated delayed fluorescence (TADF) materials. We report a method that can quantitatively predict RISC rates by explicitly considering the spin–vibronic coupling mechanism. The coupling element of the spin–vibronic Hamiltonian is obtained by expanding the spin–orbit and the non-Born–Oppenheimer terms to second order and is then brought into the Golden Rule rate under the Condon approximation. The rate equation is solved directly in the time domain using a correlation function approach. The contributions of the first-order direct spin–orbit coupling and the second-order spin–vibronic coupling to an RISC rate can be quantitatively analyzed in a separate manner. We demonstrate the utility of the method by applying it to a representative TADF system, where we observe that the spin–vibronic portion is substantial but not dominant especially with a relatively small triplet–singlet energy gap. Likewise, our method may elucidate the physical background of efficient nonradiative transitions from the lowest triplet to a higher lying singlet in other purely organic TADF systems, and it will be of great utility toward designing new such molecules.

The recently developed narrow-band blue-emitting organoboron chromophores based on the multiple-resonance (MR) effect have now become one of the most important components for constructing efficient organic light emitting diodes (OLEDs). While they basically emit through fluorescence, they are also known for showing substantial thermally activated delayed fluorescence (TADF) even with a relatively large singlet–triplet gap (Δ E ST ). Indeed, understanding the reverse intersystem crossing (RISC) dynamics behind this peculiar TADF will allow judicious molecular designs toward achieving better performing OLEDs. Explaining the underlying nonadiabatic spin-flip mechanism, however, has often been equivocal, and how the sufficiently fast RISC takes place even with the sizable Δ E ST and vanishingly small spin–orbit coupling is not well understood. Here, we show that a vibronic resonance, namely the frequency matching condition between the vibration and the electronic energy gap, orchestrates three electronic states together and this effect plays a major role in enhancing RISC in a typical organoboron emitter. Interestingly, the mediating upper electronic state is quite high in energy to an extent that its thermal population is vanishingly small. Through semiclassical quantum dynamics simulations, we further show that the geometry dependent non-Condon coupling to the upper triplet state that oscillates with the frequency Δ E ST / ℏ is the main driving force behind the peculiar resonance enhancement. The existence of an array of vibrational modes with strong vibronic rate enhancements provides the ability to sustain efficient RISC over a range of Δ E ST in defiance of the energy gap law, which can render the MR-emitters peculiar in comparison with more conventional donor–acceptor type emitters. Our investigation may provide a new guide for future blue emitting molecule developments.

Finding narrow-band, ultrapure blue thermally activated delayed fluorescence (TADF) materials is extremely important for developing highly efficient organic light-emitting diodes (OLEDs). Here, spin-vibronic coupling (SVC)-assisted ultrapure blue emitters obtained by joining two carbazole-derived moieties at a para position of a phenyl unit and performing substitutions using several blocking groups are presented. Despite a relatively large singlet-triplet gap (∆E ST ) of >0.2 eV, efficient triplet-to-singlet crossover can be realized, with assistance from resonant SVC. To enhance the spin crossover, electronic energy levels are fine-tuned, thereby causing ∆E ST to be in resonance with a triplet-triplet gap (∆E TT ). A sizable population transfer between spin multiplicities (>10 3 s −1 ) is achieved, and this result agrees well with theoretical predictions. An OLED fabricated using a multiple-resonance-type SVC-TADF emitter with CIE color coordinates of (0.15, 0.05) exhibits ultrapure blue emissions, with a narrow full-width-at-half-maximum of 21 nm and a high external quantum efficiency of 23.1%.

Achieving narrow‐bandwidth emission and high external quantum efficiency (EQE) simultaneously is a challenge for next‐generation blue‐emitting organic light‐emitting diodes (OLEDs). In this study, novel multiple‐resonance thermally activated delayed fluorescence (MR‐TADF) emitters are developed by fusing an indolocarbazole unit with two carbazole skeletons using para‐oriented nitrogen atoms. The resulting rigid and planar π‐system without electron‐accepting atoms exhibits pure blue photoluminescence at 470 nm, reaching a 100% quantum yield with a full‐width‐at‐half‐maximum (FWHM) of 25 nm. Higher‐level quantum chemistry calculations confirm an MR effect within the extended π‐conjugation and an enhanced triplet‐to‐singlet crossover (104 s−1) through a reduced energy gap (ΔEST) coupled with large spin‐vibronic coupling mediated by low‐lying triplet excited states. An OLED fabricated using the MR‐TADF emitter with CIE color coordinates of (0.12, 0.16) exhibits a record high EQE of 30.9% and a small FWHM of 23 nm. With further optimization of the device structure, a high EQE of 33.8% is achieved without additional outcoupling enhancements owing to the near‐perfect horizontal alignment of the emitting dipoles.

We report the derivation and implementation of orbital optimization algorithms for the active space decomposition (ASD) model, which are extensions of complete active space self-consistent field (CASSCF) and its occupation-restricted variants in the conventional multiconfiguration electronic-structure theory. Orbital rotations between active subspaces are included in the optimization, which allows us to unambiguously partition the active space into subspaces, enabling application of ASD to electron and exciton dynamics in covalently linked chromophores. One-and two-particle reduced density matrices, which are required for evaluation of orbital gradient and approximate Hessian elements, are computed from the intermediate tensors in the ASD energy evaluation. Numerical results on 4-(2-naphthylmethyl)-benzaldehyde and [3 6 ]cyclophane and model Hamiltonian analyses of triplet energy transfer processes in the Closs systems are presented. Furthermore model Hamiltonians for hole and electron transfer processes in anti-[2.2](1,4)pentacenophane are studied using an occupation-restricted variant.

Evolutionary design has gained significant attention as a useful tool to accelerate the design process by automatically modifying molecular structures to obtain molecules with the target properties. However, its methodology presents a practical challenge—devising a way in which to rapidly evolve molecules while maintaining their chemical validity. In this study, we address this limitation by developing an evolutionary design method. The method employs deep learning models to extract the inherent knowledge from a database of materials and is used to effectively guide the evolutionary design. In the proposed method, the Morgan fingerprint vectors of seed molecules are evolved using the techniques of mutation and crossover within the genetic algorithm. Then, a recurrent neural network is used to reconstruct the final fingerprints into actual molecular structures while maintaining their chemical validity. The use of deep neural network models to predict the properties of these molecules enabled more versatile and efficient molecular evaluations to be conducted by using the proposed method repeatedly. Four design tasks were performed to modify the light-absorbing wavelengths of organic molecules from the PubChem library.

We report a new formulation for Golden Rule-based predictions of photoluminescence quantum yields (PLQY) of phosphorescent emitters containing a heavy element, and its implementation compatible with first-principles computation frameworks. The main components of PLQY (i.e., phosphorescent rate and intersystem crossing rate from the lowest triplet state to the ground singlet state) are obtained through correlation functions in time domain, and the relativistic effects are also considered using the relativistic effective core potentials. The spin–orbit coupling is treated in a perturbative manner to generate spin–orbit-corrected, two-component T1 substates within single-excitation theory, where the electronic transition dipole moments and the non-Born–Oppenheimer coupling matrix elements to the S0 state are computed. We applied this new approach to the photophysical properties of 34 Pt­(II) complexes designed for the organic light-emitting diode (OLED) applications and observed a good agreement between predictions and experiments over diverse scaffolds. For the two representative complexes, further analysis on the nonradiative characteristics was performed based on the decomposition of the non-Born–Oppenheimer coupling into contributions from the nuclear vibrations and from the excited-state electronic structures.