Machine-Learning-Assisted Understanding of Polymer Nanocomposites Composition-Property Relationship: A Case Study of NanoMine Database.

The NanoMine database, one of two nodes in the MaterialsMine database, is a new materials data resource that collects annotated data on polymer nanocomposites (PNCs). This work showcases the potential of NanoMine and other materials data resources to assist fundamental materials understanding and therefore rational materials design. This specific case study is built around studying the relationship between the change in the glass transition temperature () and key descriptors of the nanofillers and the polymer matrix in PNCs.

[Quantitative determination of cutoff perturbation factor pdelta in the DIN 6800-2 (2008) by means of Monte Carlo simulations].

The new German DIN 6800-2 (2008) dosimetry protocol introduces a perturbation factor pdelta which accounts for the ionization chamber specific cutoff energy delta in the calculation of the Spencer-Attix stopping-power ratios. Quantitative values are not included in the protocol. In this study the perturbation factor was calculated for different types of ionization chambers using Monte Carlo simulations.