In an effort to understand the reaction mechanisms involved in the adsorption of organic aromatic molecules on high-index Si surfaces, the reactions of pyrrole molecules adsorbed onto Si(5 5 12)À2 Â 1 surfaces were studied using scanning tunneling microscopy and first principle calculations. The dissociation of one or two H atom(s) bonded to N (or N and C) from the pyrrole molecules was favored, and adsorption at adatom, tetramer, dimer, or honeycomb Si(5 5 12)À2 Â 1 sites occurred to produce several distinct configurations. Pyrrole was most reactive toward the dimer site, yielding two dissociated hydrogen atoms and a vertical configuration. Pyrrole also adsorbed onto the tetramer and honeycomb sites, yielding two dissociated hydrogen atoms. On the adatom row, however, pyrrole bound to an adatom via a σ bond between the adatom and N to yield one dissociated H atom adsorbed onto a nearby adatom. No other hydrogen dissociation reactions were observed. In all configurations, the aromaticity of pyrrole was retained.

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We show that the resonance energy and dispersion interactions (DIs) are critical factors in determining the selectivity and configuration in the reaction of pyrimidine molecules with a silicon surface. The atomic structures of the pyrimidine molecules after they reacted with a Si(5 5 12)−2 × 1 surface were studied. Binding configurations of the pyrimidines were distinct from those of other molecules with N lone-pair electrons and aromaticity. The pyrimidine molecules were adsorbed to produce two σ bonds to silicon with N 2 and C 5 on the adatom row (Adr) and honeycomb chain (Hnc) sites and with C 1 and C 4 on the dimer row (Dmr) and the tetramer row (Ttr) sites. The reactions occurred via a [4 + 2]-type cycloaddition to produce planar-type configurations with loss of aromaticity. That is, the atoms of the aromatic ring of pyrimidine form chemical bonds with silicon atoms, which is in contrast to the adsorption behaviors reported for other N-containing aromatic molecules. When pyrimidine is adsorbed, its molecular orbitals are distorted because the N−Si bond axis does not coincide with the molecular orbital symmetric axis. Therefore, the vertical geometry is relatively unstable. DIs contribute a range of 0.4−0.6 eV for all stable adsorption structures and are essential for producing planar-type configurations on the Dmr and Ttr sites. In the absence of DIs, the vertical structure is stable; however, when DIs are included, the planar-type configuration becomes more stable. Moreover, even though the aromaticity is stabilized in the vertical structure, the greater adsorption energy for the flat structure of pyrimidine is mainly attributed to the lower energy cost involved in breaking the aromaticity.

The covalent binding of thiophene molecules to a Si(5 5 12)−2 × 1 surface was investigated using scanning tunneling microscopy and density functional theory calculations. The molecular attachment occurred exclusively between the bonding of the 2,5 carbon atoms and the two silicon adatoms without the involvement of the sulfur atom (over 90%). The binding structure formed a di−σ bond with a planar butterfly-like configuration. Adsorption at other sites, including at the dimer, tetramer, or honeycomb rows, occurred much less frequently. Our calculations predicted that the adsorption energies of the thiophene molecules were 1.02− 1.56 eV at the adatom, dimer, and tetramer sites. The molecules adsorbed on the honeycomb rows with a low adsorption energy (below 1 eV). The binding modes of the simple aromatic molecules onto the Si(5 5 12)−2 × 1 surface are compared and discussed.

AI based design for OLED materials are being tried in a variety of ways. An exemplary system is being developed to predict optical characteristics through machine learning (ML) with existing data. Once the performance descriptor is well defined and the quantum chemical calculation method is established, AI‐reverse design is expected to be possible. However, not all OLED emitting materials are equally capable of it. Different approaches are needed because the luminescence mechanism and its complexity of calculation are different depending on the material types. For pure fluorescence or even high efficiency phosphorescence, their luminescence mechanisms are relatively well defined and nearly irreversible and so the correlation between the calculation and performance could be better. If so, the reverse design is becoming possible and already it has begun to be tried a lot. However, in the case of TADF, the radiation and non‐radiation paths vary, ISC‐RISC is more reversible, and the controversy over luminescence mechanism remains. As a result, the calculating method of luminous efficiency has not yet been fully established. In this study, we want to report the consistency level of predicting characteristics of OLED materials using AI, and also discuss the difference between each emitting material types for reverse design. In particular, we also want to share the issues of calculating methods for TADF performance.