Triplet fusion upconversion using sterically protected 9,10-diphenylanthracene as the emitter.

Improving the efficiency of triplet fusion upconversion (TF-UC) in the solid-state is still challenging due to the aggregation and phase separation of chromophores. In this work, two 9,10-diphenylanthracene (DPA) derivatives based on the modification of the 9,10-phenyl rings with bulky isopropyl groups (bDPA-1 and bDPA-2) were used as emitters. By using platinum octaethylporphyrin (PtOEP) as the sensitizer, TF-UC performance was comprehensively investigated in 3 media: toluene solution, polyurethane thin film and nano/micro-crystals in a polyvinyl alcohol matrix. Only a small difference in upconversion efficiency between the bulky DPAs and the DPA reference was observed in toluene solution and polyurethane thin film. However, a large improvement of TF-UC quantum yield was achieved in bDPA-2/PtOEP crystals (ΦUC = (0.92 ± 0.05)%) with a low excitation intensity threshold (52 mW cm-2) compared to that of DPA/PtOEP crystals (ΦUC = (0.09 ± 0.03)%). This difference was largely attributed to improved dispersibility of the PtOEP sensitizer in the bDPA-2 emitter crystals. The bulky DPAs also show excellent stability under UV irradiation with exposure to oxygen compared to DPA. These results provide a strategy for developing efficient solid-state TF-UC systems based on nano/micro-particles of emitter-sensitizer mixtures.

Fabrication of microchannels by space-selective control of phase separation in glass.

Microchannels have important scientific applications in many fields, because they enable precise control, manipulation, and analysis of fluid on a micrometer scale. Herein, we demonstrate an effective strategy for fabrication of microchannels, based on the space-selective phase separation in glass induced by a femtosecond laser. The proposed method shows its abilities in fabrication of three-dimensional microchannels with ∼5 mm length scale and a uniform cross section. Moreover, we also achieve the modulation of the morphology on the inner surface of microchannels by using objective lenses with various numerical-apertures. The physical mechanism of the phase separation and microstructure evolution is discussed. Our method provides new opportunities to fabricate microchannels with complex structures and multifunctional integration.

Funneling and Enhancing Upconversion Emission by Light-Harvesting Molecular Wires.

Triplet-triplet annihilation (TTA) upconversion has shown promising potentials in the augmentation of solar energy conversion. However, challenging issues exist in improving TTA upconversion efficiencies in solid-states, one of which is the back energy transfer from upconverted singlet annihilators to sensitizers, resulting in decreasing upconversion emission. Here we present a light-harvesting molecular wire consisting of dendrons with 9,10-diphenylanthracene derivatives (DPAEH) at the periphery and p-phenylene ethynylene oligomers (PPE) as the wire core. The peripheral DPAEH antenna funnels singlet excitonic energy to the wire on a 12 ps time scale. Incorporating the molecular wire into the TTA upconversion solid consisting of the DPAEH annihilator and the porphyrin sensitizer evidently improves the upconversion quantum yield from 1.5% to 2.7% upon 532 nm excitation by suppressing the back energy transfer from the singlet annihilator to the sensitizer. This finding offers a potential route to use a singlet energy light-harvesting architecture for enhancing TTA upconversion.

Precise diagnosis of three top cancers using dbGaP data.

The challenge of decoding information about complex diseases hidden in huge number of single nucleotide polymorphism (SNP) genotypes is undertaken based on five dbGaP studies. Current genome-wide association studies have successfully identified many high-risk SNPs associated with diseases, but precise diagnostic models for complex diseases by these or more other SNP genotypes are still unavailable in the literature. We report that lung cancer, breast cancer and prostate cancer as the first three top cancers worldwide can be predicted precisely via 240-370 SNPs with accuracy up to 99% according to leave-one-out and 10-fold cross-validation. Our findings (1) confirm an early guess of Dr. Mitchell H. Gail that about 300 SNPs are needed to improve risk forecasts for breast cancer, (2) reveal an incredible fact that SNP genotypes may contain almost all information that one wants to know, and (3) show a hopeful possibility that complex diseases can be precisely diagnosed by means of SNP genotypes without using phenotypical features. In short words, information hidden in SNP genotypes can be extracted in efficient ways to make precise diagnoses for complex diseases.