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A novel BINOL-like chiral nanographene was prepared with good yield. Unlike most helicity-based nanographenes, this chirality of the nanographene purely stems from an axial chirality.

Two novel nitrogen-doped, hexa-peri-hexabenzocoronene (HBC)-based nanographenes (NGs) 1 and 2 bearing an azepine and an azocine at the fjord region, respectively, were synthesized and characterized. Notably, structure 1 was synthesized by Diels-Alder reaction of cyclic alkene and tetrachlorothiophene-S,S-dioxide, followed by Suzuki-Miyaura cross-coupling and Scholl-type reactions, which represents a modified strategy to construct NGs. The azo-heptagon-embedded NG 1 leads to a saddle shape, and the azo-octagon-embedded NG 2 exhibits a distorted saddle-helix conformation with the largest torsion angle recorded so far in [5]helicenes. As a result, the different structural topographies for NGs 1 and 2 lead to significant changes in the optical properties including UV absorption and fluorescent emission. Additionally, the 8π-heterocycles azepine and azocine in the NGs 1 and 2 exhibited obvious antiaromatic properties.

The pyrazoline fluorophore, generated by photoinduced tetrazole-ene cycloaddition, shows faint fluorescence in protic solvents. To suppress this fluorescence-quenching, we rationally designed a series of substituted diaryl tetrazoles at the N-side phenyl ring to produce a tetrazole-ene based photoactivatable fluorophore. Spectroscopic and cellular imaging studies demonstrated that the version of the fluorophore with a bis(trifluoromethyl)benzene substituent exhibited significantly enhanced brightness and photostability.

Aryl azide and diaryl tetrazole are both photoactive molecules, which can form nitrene and nitrile imine intermediates respectively by photolysis. Depending on the new finding that the azide can suppress the photolysis of tetrazole in the azide-tetrazole conjugated system, we developed aryl azide-tetrazole probes for the photoactivatable fluorogenic azide alkyne click (PFAAC) reaction, in which the aryl azide-tetrazole probes were not phoroactivatable fluorogenic itself, but the triazole products after click reaction were prefluorophore that can be activated by light. Therefore, in PFAAC chemistry, the fluorescent probes can be activated by two orthogonal events: azide-alkyne click reaction and light, which leads to spatiotemporal resolution and high signal-to-noise ratio. This PFAAC process was proved in vitro by copper-catalyzed or strain-promoted azide-alkyne reactions and in live cells by spatiotemporally controlled organelle imaging. By incorporation a linker to the azide-tetrazole conjugate, this PFAAC chemistry could covalently label extra probes to the biomolecules and spatiotemporally detecting this process by photoinduced fluorescence.

The azepine- and oxepine-embedded polycyclic aromatic hydrocarbons (PAH) 1-3, as the hexa-peri-hexabenzocoronene (HBC)-based nanographenes (NG) were designed and synthesized by Diels-Alder reaction of cyclic alkene with tetrachlorothiophene-S,S-dioxide, followed by Suzuki-Miyaura cross-coupling and Scholl-type cyclodehydrogenation. Due to the strained seven-membered ring and the inherent structural pattern, heteroatom-doped NGs 1-3 show C

Oracle character is one kind of the earliest hieroglyphics, which can be dated back to Shang Dynasty in China. Oracle character recognition is important for modern archaeology, ancient text understanding, and historical chronology, etc. To overcome the limitation and class imbalance of training data in oracle character recognition, we propose a classification method based on deep metric learning. We use a convolutional neural network (CNN) to map the character images to an Euclidean space where the distance between different samples can measure their similarities such that classification can be performed by the Nearest Neighbor (NN) rule. Because new categories are still being discovered in reality, our model enables the rejection of unseen categories and the configuration of new categories. To accelerate NN classification, we also propose a prototype pruning method with little loss of accuracy. The proposed method exceeds the state of the art on the public dataset Oracle-20K and outperforms CNN with softmax layer on a new dataset Oracle-AYNU.