Effect of order and disorder on degradation processes of copper phthalocyanine nanolayers

The impact was examined of surface ordering of 50 nm-thick copper phthalocyanine (CuPc) layers on the layer's susceptibility to ambience-induced degradation processes. The surface morphology of CuPc layers obtained by physical vapor deposition with different deposition rates, 0.01 nm/s (r1) and 0.02 nm/s (r2), was diagnosed applying atomic force and scanning electron microscopes. The images exhibited compact, ordered surface topography with crystallites of homogeneous geometry for a layer with r1 while randomly distributed bigger crystallites on a rougher and more expanded surface for a layer with r2. X-ray diffraction revealed the α-form of phthalocyanine, mostly with an orientation of the a axis perpendicular to the substrate plane. Mean grain size in bulk was slightly larger for CuPc with r2. Energy dispersive X-ray spectroscopy demonstrated an increase of C/Cu and N/Cu elemental ratios compared to the expected composition for both layers but significantly more pronounced for layer with r2. Morphological features and traces of CuPc-air interaction were mirrored also in the Raman spectra. Samples with r2 exhibited an increased peak width, and their peaks were shifted compared to samples with r1, which was attributed to surface disorder. The Raman spectra exhibited the appearance of additional peaks of oxidation products indicating Csingle bondOsingle bondC, Cdouble bond; length as m-dashO and Nsingle bondO bonds, with intensities coinciding to an increased carbon and nitrogen content. More intensive peaks were recorded for layers obtained with higher deposition rate, proving their stronger susceptibility to environment-induced degradation processes

In silico assessment of the dosimetric quality of a novel, automated radiation treatment planning strategy for linac-based radiosurgery of multiple brain metastases and a comparison with robotic methods

To appraise the dosimetric features and the quality of the treatment plan for radiosurgery of multiple brain metastases optimized with a novel automated engine and to compare with plans optimized for robotic-based delivery