Precise determination of Young's modulus of amorphous CuZr/nanocrystalline Cu multilayer via nanoindentation.

Extracting mechanical data of thin films on rigid substrates using nanoindentation is compromised by the mechanical properties of underlying substrates, which may falsify the obtained results. With ongoing miniaturization, the substrate influence becomes more pronounced. In this study we present an experimental approach to extract the true Young's modulus of crystalline-amorphous multilayers by means of nanoindentation. We used 1 µm thick multilayers comprised of amorphous CuZr and nanocrystalline Cu. All films were deposited onto two rigid substrate types with Young's moduli below and above the ones expected for the deposits (film-to-substrate hardness and elastic moduli ratios between 0.3 to 1.1 and 0.6 to 1.5, respectively). Linear extrapolation of indentation data to zero indentation depth allows to precisely determine the real film's Young's modulus. Same investigations were performed on monolithic Cu and CuZr films of same thickness. While the hardness values change with the variation of the bilayer thickness of the multilayer structures, the Young's modulus is not affected by the interfaces.

Bridging Fidelities to Predict Nanoindentation Tip Radii Using Interpretable Deep Learning Models.

As the need for miniaturized structural and functional materials has increased, the need for precise materials characterizaton has also expanded. Nanoindentation is a popular method that can be used to measure material mechanical behavior which enables high-throughput experiments and, in some cases, can also provide images of the indented area through scanning. Both indenting and scanning can cause tip wear that can influence the measurements. Therefore, precise characterization of tip radii is needed to improve data evaluation. A data fusion method is introduced which uses finite element simulations and experimental data to estimate the tip radius in situ in a meaningful way using an interpretable multi-fidelity deep learning approach. By interpreting the machine learning models, it is shown that the approaches are able to accurately capture physical indentation phenomena.

Determination of residual solvents in isobutylboronic acid: Masking derivatization improves stability of GC column.

Masking derivatization was introduced for the determination of residual solvents in samples containing a volatile reactive matrix component(s). Isobutylboronic acid, used in the last step of Bortezomib synthesis, represents a compound passing to the gas phase and deteriorating a chromatographic column during a headspace analysis. The masking derivatization with 1,8-diaminonaphthalene allowed a simple and straightforward conversion of isobutylboronic acid to a stable nonvolatile derivative and thus prevented gas chromatography column deterioration. The method was successfully validated according to the guidelines of International Committee for Harmonization (Q3C (R6) Guideline for Residual Solvents) and international pharmacopoeias (Ph. Eur., USP) and approved by Teva Czech Industries for routine application.

Vegetable lipids as components of functional foods.

Nutritionally beneficial compounds naturally present in vegetable lipids will be subject of this minireview. This article will discuss lipidic compounds from less known vegetable sources and potential advantages of its incorporation into human diet as a functional ingredient.