Faceting and lateral overgrowth have been investigated for Ge selectively grown on Si(001) substrates in trench regions bound by ${\text{SiO}}_2$ sidewalls. In wet-etched large trenches with sloped sidewalls, Ge faceting behavior was similar to Si and ${\text{Si}}_x{\text{Ge}}_{1-x}$ faceting: slow-growing $\left\{113\right\}$ facets dominate, with $\left\{111\right\}$ facets expanding as the layer became thicker. However, the $\left\{111\right\}$ facet length for Ge was much smaller than that of Si; this can be explained in terms of mass transport and accumulation, as well as energy minimization and the higher surface diffusivity of Ge. In dry-etched small trenches with vertical sidewalls, minimization of the high-energy interface area between Ge and ${\text{SiO}}_2$ appears to be most critical in determining faceting morphology. Overgrowth of Ge led to void formation at the oxide interface, presumably to avoid the high-energy $\text{Ge}/{\text{SiO}}_2$ interface. Upon coalescence of lateral-growth regions, fast-growing (001) forms and dominates subsequent growth. Thus, the total thickness of the overgrown Ge layer was closely related to the width of the ${\text{SiO}}_2$ region between trenches.

Growth of Ge thick layers with and without a low temperature Ge buffer has been investigated using reduced pressure chemical vapor deposition with emphasis on the evolution of surface morphology and its roughness. Growth at 400 °C exhibited a 200 s incubation period for which about 1 equivalent monolayer of Ge was deposited with a surface roughness of around 0.1 nm followed by an abrupt increase due to an island growth. Higher growth temperature resulted in shorter or no observed incubation period and led to rougher surface due to larger size of islands. Ge layers grown at 600 °C on at low temperature Ge buffer first grown at 400 °C exhibited around 1 nm surface roughness independent of the layer thickness, which is much lower than those at 400–600 °C without the low temperature buffer. The Ge thick layer with the low temperature Ge buffer had thinner defective interface of Ge/Si than that without the buffer.

Game playing is an accessible leisure activity. Recently, the World Health Organization officially included gaming disorder in the ICD-11, and studies using several bio-signals were conducted to quantitatively determine this. However, most EEG studies regarding internet gaming disorder (IGD) were conducted in the resting state, and the outcomes appeared to be too inconsistent to identify a general trend. Therefore, this study aimed to use a series of statistical processes with all the existing EEG parameters until the most effective ones to identify the difference between IGD subjects IGD and healthy subjects was determined. Thirty subjects were grouped into IGD (n = 15) and healthy (n = 15) subjects by using the Young’s internet addition test (IAT) and the compulsive internet use scale (CIUS). EEG data for 16 channels were collected while the subjects played League of Legends. For the exhaustive search of parameters, 240 parameters were tested in terms of t-test, factor analysis, Pearson correlation, and finally logistic regression analysis. After a series of statistical processes, the parameters from Alpha, sensory motor rhythm (SMR), and MidBeta ranging from the Fp1, C3, C4, and O1 channels were found to be best indicators of IGD symptoms. The accuracy of diagnosis was computed as 63.5–73.1% before cross-validation. The most interesting finding of the study was the dynamics of EEG relative power in the 10–20 Hz band. This EEG crossing phenomenon between IGD and healthy subjects may explain why previous research showed inconsistent outcomes. The outcome of this study could be the referential guide for further investigation to quantitatively assess IGD symptoms.