Structural characterization of γ-terpinene thin films using mass spectroscopy and X-Ray photoelectron spectroscopy

Understanding the polymerization mechanism of a precursor is indispensable to enhance the requisite material properties. In situ mass spectroscopy and X-ray photoelectron spectroscopy is used in this study to understand the RF plasma polymerization of γ-terpinene. High-resolution mass spectra positive ion mass spectrometry data of the plasma phase demonstrates the presence of oligomeric species of the type [M+H]+ and [2M+H]+, where M represents a unit of the starting material. In addition, there is abundant fragmented species, with most dominant being [M+] (136 m/z), C10H13+ (133 m/z), C9H11+ (119 m/z), and C7H9+ (93 m/z). The results reported in this manuscript enables to comprehend the relationship between the degree of incorporation of oxygen and the rate of deposition with the input RF power.

Reproducibility of scratch assays is affected by the initial degree of confluence: Experiments, modelling and model selection

Scratch assays are difficult to reproduce. Here we identify a previously overlooked source of variability which could partially explain this difficulty. We analyse a suite of scratch assays in which we vary the initial degree of confluence (initial cell density). Our results indicate that the rate of re-colonisation is very sensitive to the initial density. To quantify the relative roles of cell migration and proliferation, we calibrate the solution of the Fisher–Kolmogorov model to cell density profiles to provide estimates of the cell diffusivity, D, and the cell proliferation rate, λ. This procedure indicates that the estimates of D and λ are very sensitive to the initial density. This dependence suggests that the Fisher–Kolmogorov model does not accurately represent the details of the collective cell spreading process, since this model assumes that D and λ are constants that ought to be independent of the initial density. Since higher initial cell density leads to enhanced spreading, we also calibrate the solution of the Porous–Fisher model to the data as this model assumes that the cell flux is an increasing function of the cell density. Estimates of D and λ associated with the Porous–Fisher model are less sensitive to the initial density, suggesting that the Porous–Fisher model provides a better description of the experiments.