A novel growth technique, called atomic partial layer deposition (APLD), has been proposed to expand the applications of, and the research in, atomic layer deposition (ALD). This technique allows the possibility for the fabrication of well-controlled alloys on a single atomic layer scale. To demonstrate the capabilities of this technique, samples of HfO₂ and TiO₂ were prepared as conventional ALD nanolaminates through the repeated exposure of the separated metal-precursor and reactant. Subsequently, HfO₂-TiO₂ APLD growth mode samples were obtained by varying the precursor doses and exposure times to obtain a fractional coverage in the monolayer of Hf and Ti. The thickness and structure of the samples were studied by X-ray reflectivity. The surface topography was studied using atomic force microscopy along with Kelvin probe force microscopy for surface potential mapping. Clear differences on the surface, compared with the conventional HfO₂/TiO₂ ALD nanolaminates, were observed, which confirmed the HfO₂-TiO₂ APLD growth. The films were analyzed using X-ray photoelectron spectroscopy (XPS) depth profile scans and angle resolved XPS, where well-defined HfO₂ and TiO₂ contributions were found for both the conventional and APLD mode samples, and an additional contribution, assigned to a ternary phase Hf-Ti-O, in the APLD grown films was observed. This result confirms that Hf and Ti form an alloy in a monolayer by APLD mode growth.

The optical energy gap of ${\mathrm{Ge}}_{1-x}{\mathrm{Sn}}_x$ alloys $(x⩽0.14)$ grown on Ge substrates has been determined by performing transmittance measurements at $4\mathrm{K}$ using a fast fourier transform infrared interferometer. The direct energy gap transitions in ${\mathrm{Ge}}_{1-x}{\mathrm{Sn}}_x$ alloys behave following a nonlinear dependence on the Sn concentration, expressed by a quadratic equation, with a so called bowing parameter $b_0$ that describes the deviation from a simple linear dependence. Our observations resulted in $b_0^{\mathrm{RT}}=2.30\pm 0.10\mathrm{eV}$ and $b_0^{4\mathrm{K}}=2.84\pm 0.15\mathrm{eV}$ , at room temperature and $4\mathrm{K}$ , respectively. The validity of our fit is limited for Sn concentrations lower than 15%.

Bacterial canker of tomato is caused by Clavibacter michiganensis subsp. michiganensis (Cmm). The disease is highly destructive, because it produces latent asymptomatic infections that favor contagion rates. The present research aims consisted on the implementation of Raman spectroscopy (RS) and machine-learning spectral analysis as a method for the early disease detection. Raman spectra were obtained from infected asymptomatic tomato plants (BCTo) and healthy controls (HTo) with 785 nm excitation laser micro-Raman spectrometer. Spectral data were normalized and processed by principal component analysis (PCA), then the classifiers algorithms multilayer perceptron (PCA + MLP) and linear discriminant analysis (PCA + LDA) were implemented. Bacterial isolation and identification (16S rRNA gene sequencing) were realized of each plant studied. The Raman spectra obtained from tomato leaf samples of HTo and BCTo exhibited peaks associated to cellular components, and the most prominent vibrational bands were assigned to carbohydrates, carotenoids, chlorophyll, and phenolic compounds. Biochemical changes were also detectable in the Raman spectral patterns. Raman bands associated with triterpenoids and flavonoids compounds can be considered as indicators of Cmm infection during the asymptomatic stage. RS is an efficient, fast and reliable technology to differentiate the tomato health condition (BCTo or HTo). The analytical method showed high performance values of sensitivity, specificity and accuracy, among others.