Data_Sheet_1_Recent Applications of Interfacial Exciplex as Ideal Host of Power-Efficient OLEDs.pdf

Currently, exploring the applications of intermolecular donor-acceptor exciplex couple as host of OLEDs with phosphorescence, thermally activated delayed fluorescence (TADF) or fluorescence emitter as dopant is a hot topic. Compared to other host strategies, interfacial exciplex has the advantage in various aspects, such as barrier-free charge injection, unimpeded charge transport, and the energy-saving direct exciton formation process at the “Well”-like heterojunction interface region. Most importantly, due to a very fast and efficient reverse intersystem-crossing (RISC) process, such a host is capable of regulating singlet/triplet exciton populations in itself as well as in the dopant emitters both under photoluminescent (PL) and electroluminescent (EL) driving conditions. In this mini-review, we briefly summarize and comment on recent applications of this ideal host in OLEDs (including both thermal-evaporation OLEDs and solution-processed OLEDs) with diverse emitters, e.g., fluorescence, phosphorescence, delayed fluorescence, or others. Special attention is given to illustrate the peculiar achievement of high overall EL performance with superiorities of low driving voltages, slow roll-off rate, high power efficiencies and satisfied device lifetime using this host strategy, which is then concluded by personal perspectives on the relevant next-step in this field.</p

CuBr₂ mediated synthesis of 2-Aminothiazoles from dithiocarbamic acid salts and ketones

In a one-pot procedure, CuBr2 has been used as a efficient desulfurizing agent in the synthesis of 2-aminothiazoles by the condensation of in situ-generated 1-substituted thioureas from their dithiocarbamic acid salts, with in situ-generated α-bromoketones from ketones. All reactions were carried out under optimized reaction conditions and gave the target products in 61–95% yield.</p

Subsample analysis.

This paper introduces the market framing bias (MFB): a framing effect that affects the return-risk tradeoff under different frameworks of aggregate market losses and profits, which is measured by the absolute difference between betas in the rising and falling markets. The paper finds that the MFB can predict lower future stock return on the cross-section. Specifically, after controlling for various firm-specific characteristics, this predictive power of the FMB declines over time. Furthermore, the predictive power of the FMB is stable in the short term even after controlling for various pricing factors and firm-specific characteristics.</div

Out-of-sample predictability.

This paper introduces the market framing bias (MFB): a framing effect that affects the return-risk tradeoff under different frameworks of aggregate market losses and profits, which is measured by the absolute difference between betas in the rising and falling markets. The paper finds that the MFB can predict lower future stock return on the cross-section. Specifically, after controlling for various firm-specific characteristics, this predictive power of the FMB declines over time. Furthermore, the predictive power of the FMB is stable in the short term even after controlling for various pricing factors and firm-specific characteristics.</div

Univariate and multi-term portfolio analysis.

This paper introduces the market framing bias (MFB): a framing effect that affects the return-risk tradeoff under different frameworks of aggregate market losses and profits, which is measured by the absolute difference between betas in the rising and falling markets. The paper finds that the MFB can predict lower future stock return on the cross-section. Specifically, after controlling for various firm-specific characteristics, this predictive power of the FMB declines over time. Furthermore, the predictive power of the FMB is stable in the short term even after controlling for various pricing factors and firm-specific characteristics.</div

Descriptive statistics and correlation matrix of firm-specific variables.

Descriptive statistics and correlation matrix of firm-specific variables.</p

Additional statistical description.

This paper introduces the market framing bias (MFB): a framing effect that affects the return-risk tradeoff under different frameworks of aggregate market losses and profits, which is measured by the absolute difference between betas in the rising and falling markets. The paper finds that the MFB can predict lower future stock return on the cross-section. Specifically, after controlling for various firm-specific characteristics, this predictive power of the FMB declines over time. Furthermore, the predictive power of the FMB is stable in the short term even after controlling for various pricing factors and firm-specific characteristics.</div

Modular Monomers with Tunable Solubility: Synthesis of Highly Incompatible Block Copolymer Nano-Objects via RAFT Aqueous Dispersion Polymerization

The high incompatibility of block copolymers consisting of a neutral stabilizer block and a polyelectrolyte core-forming block is exploited to drive phase segregation during polymerization-induced self-assembly (PISA). A modular approach to systematically tune the solubility of ionic monomers/polymers is developed to efficiently identify monomers suitable for aqueous dispersion polymerizations. The strong phase segregation ability of the neutral-polyelectrolyte block copolymers favors the formation of worms over a relatively broad composition range and even at very low solids. These findings suggest that the degree of incompatibility between the stabilizer block and the core-forming block should be considered as one of the key parameters when studying morphological transitions in PISA

Stationary tests and correlation matrix of pricing factors.

Stationary tests and correlation matrix of pricing factors.</p

Bivariate portfolio analysis.

This paper introduces the market framing bias (MFB): a framing effect that affects the return-risk tradeoff under different frameworks of aggregate market losses and profits, which is measured by the absolute difference between betas in the rising and falling markets. The paper finds that the MFB can predict lower future stock return on the cross-section. Specifically, after controlling for various firm-specific characteristics, this predictive power of the FMB declines over time. Furthermore, the predictive power of the FMB is stable in the short term even after controlling for various pricing factors and firm-specific characteristics.</div