ABSTRACT
We report a device that monolithically integrates optically pumped (20-21) III-nitride quantum wells (QWs) with 560 nm emission on top of electrically injected QWs with 450 nm emission. The higher temperature growth of the blue light-emitting diode (LED) was performed first, which prevented thermal damage to the higher indium content InGaN of the optically pumped QWs. A tunnel junction (TJ) was incorporated between the optically pumped and electrically injected QWs; this TJ enabled current spreading in the buried LED. Metalorganic chemical vapor deposition enabled the growth of InGaN QWs with high radiative efficiency, while molecular beam epitaxy was leveraged to achieve activated buried p-type GaN and the TJ. This initial device exhibited dichromatic optically polarized emission with a polarization ratio of 0.28. Future improvements in spectral distribution should enable phosphor-free polarized white light emission.
ABSTRACT
A new set of 142 experimentally determined complexation constants between sulfobutylether-ß-cyclodextrin and diverse organic guest molecules, and 78 observations reported in literature, were used for the development of the QSPR models by the two machine learning regression methods - Cubist and Random Forest. Similar models were built for ß-cyclodextrin using the 233-compound dataset available in the literature. These results demonstrate that the machine learning regression methods can successfully describe the complex formation between organic molecules and ß-cyclodextrin or sulfobutylether-ß-cyclodextrin. In particular, the root mean square errors for the test sets predictions by the best models are low, 1.9 and 2.7kJ/mol, respectively. The developed QSPR models can be used to predict the solubilizing effect of cyclodextrins and to help prioritizing experimental work in drug discovery.
