Relation of Certain Quantum Chemical Parameters to Lubrication Behavior of Solid Oxides

Insight into the Mechanisms of Nitride Films with Excellent Hardness and Lubricating Performance: A Review

Transition metal nitride (TMN) films with excellent hardness and lubricating performance are versatile low dimension materials, which are widely used in various fields including industries, transportation, aerospace, and so on. This paper introduces one film design strategy and provides a review of the mechanisms for strengthening and lubricating nitride films. The design strategy refers to two aspects which determine the structures, the performance, the components, and the chemical constitutions of nitride films The strengthening mechanisms of nitride films are then illuminated in detail, including the solid solution effect, the grain size effect, the secondary phase effect, the stress or stress field effect, the template effect, and the valence electron concentration effect. Five lubricating mechanisms are next summarized, including the easy-shear nature, the tribo-chemical reactions, the lubricious fluorides, the textured contact surface, and the synergistic effect. This paper aims to give a comprehensive introduction for understanding the mechanisms of strengthening and lubrication of nitride films for students and researchers, as well as to understand the current research progress in nitride films for exploring research gaps.

Predicting toxic potencies of metal oxide nanoparticles by means of nano-QSARs

BACKGROUND

The enormous physicochemical and structural diversity of metal oxide nanoparticles (MeONPs) poses significant challenges to the testing of their biological uptake, biodistribution, and effects that can be used to develop understanding of key nano-bio modes of action. This has generated considerable uncertainties in the assessment of their human health and environmental risks and has raised concerns about the adequacy of their regulation. In order to surpass the extremely resource intensive case-by-case testing, intelligent strategies combining testing methods and non-testing predictive modeling should be developed.

METHODS

The quantitative structure-activity relationship (QSARs) in silico tools can be instrumental in understanding properties that affect the potencies of MeONPs and in predicting toxic responses and thresholds of effects.

RESULTS

The present study proposes a predictive nano-QSAR model for predicting the cytotoxicity of MeONPs. The model was applied to test the relationships between 26 physicochemical properties of 51 MeONPs and their cytotoxic effects in Escherichia coli. The two parameters, enthalpy of formation of a gaseous cation (▵Hme+) and polarization force (Z/r), were elucidated to make a significant contribution for the toxic effect of these MeONPs. The study also proposed the mechanisms of toxic potency in E. coli through the model, which indicated that the MeONPs as well as their released metal ions could collectively induce DNA damage and cell apoptosis.

SIGNIFICANCE

These findings may provide an alternative method for prioritizing current and future MeONPs for potential in vivo testing, virtual prescreening and for designing environmentally benign nanomaterials.

Using experimental data of Escherichia coli to develop a QSAR model for predicting the photo-induced cytotoxicity of metal oxide nanoparticles

A quantitative structure-activity relationship (QSAR) study of seventeen metal oxide nanoparticles (MNPs), in regard to their photo-induced toxicity to bacteria Escherichia coli, was developed by using quantum chemical methods. A simple and statistically significant QSAR model (F=33.83, R(2)=0.87) was successfully developed for the dark group based on two descriptors, absolute electronegativity of the metal and the metal oxide. Similarly, a best correlation (F=20.51, R(2)=0.804) was obtained to predict the photo-induced toxicity of MNPs by using two descriptors, molar heat capacity and average of the alpha and beta LUMO (lowest unoccupied molecular orbital) energies of the metal oxide. Revelation of these influential molecular descriptors may be useful in elucidating the mechanisms of nanotoxicity and for predicting the environmental risk associated with release of the MNPs. In addition, the developed model may have a role in the future design and manufacture of safe nanomaterials.