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An in-depth insight into the chemistry and nature of the individual chemical bonds is essential for understanding materials. Bonding analysis is thus expected to provide important features for large-scale data analysis and machine learning of material properties. Such chemical bonding information can be computed using the LOBSTER software package, which post-processes modern density functional theory data by projecting the plane wave-based wave functions onto an atomic orbital basis. With the help of a fully automatic workflow, the VASP and LOBSTER software packages are used to generate the data. We then perform bonding analyses on 1520 compounds (insulators and semiconductors) and provide the results as a database. The projected densities of states and bonding indicators are benchmarked on standard density-functional theory computations and available heuristics, respectively. Lastly, we illustrate the predictive power of bonding descriptors by constructing a machine learning model for phononic properties, which shows an increase in prediction accuracies by 27% (mean absolute errors) compared to a benchmark model differing only by not relying on any quantum-chemical bonding features.
The friction and wear behaviour of thin hard coatings, such as TiN and the promising class of C-based coatings (a-C, a-C:H, and diamond for example), are compared under oscillating and reciprocating sliding conditions. The typical effects of test parameters, such as stroke, frequency, normal force, relative humidity and test duration, are described as a basis for the proper selection of test conditions or, conversely, for the selection of suitable coatings for particular practical applications.
Friction and wear data from over 1000 vibrating tests using thin hard coatings against 100Cr6 and against Al2O3 have been compiled in a database. This allows easy manipulation and comparison of test results. Using selection criteria and filter procedures (e. g., lifetime of coatings, friction limits, and critical wear rate), suitable coating systems for different test conditions can be chosen from the database. The effects of test parameters on friction and wear behaviour and changes have anyway to be known for meaningful tribotesting, as well as for the selection of coatings.
This paper describes the COMAR database for certified reference materials (CRMs). The Web-based version of COMAR is freely accessible via the Internet. COMAR was established to assist laboratories in finding the CRMs needed. The database is maintained in a collaboration of the worlds major CRM producers. The planned changes in the database as agreed at the last COMAR council meeting in Prague in May 2006 are indicated.