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The basic problem in the operation of automotive brakes is the unpredictable nature of the tribological processes that occur at the contact of the friction pair. The stochastic nature of the tribological contact of the disc brake is affected differently by the complex interaction between the brake disc and the friction material under different conditions because of the influences of the applied pressure, the speed and the brake interface temperature. Owing to the highly dynamic non-linear change in the braking torque induced by the complex situation at the contact of the disc brake, the braking torque could not be modelled, predicted and controlled using classical mathematical methods. This is related, in particular, to the dynamic change in the braking torque in a braking cycle. Dynamic modelling and prediction of the braking torque is very important for further improvement in the performance of the brakes of motor vehicles through more precise control of their performance with respect to the driver demands and the change in the adhesion between the tyre and the road. Recurrent dynamic neural networks were employed in this paper for modelling, prediction and control of the dynamic change in the braking torque during a braking cycle. The dynamic functional relationship between the changes in the applied pressure, the sliding speed, the brake interface temperature and the braking torque of the disc brake was established. The dynamic model developed was used to predict and control the braking torque during a braking cycle under different disc brake operation conditions.

Bimetallic cobalt (Co)-based coatings were prepared by a facile, fast, and low-cost electroless deposition on a copper substrate (CoFe, CoMn, CoMo) and characterized by scanning electron microscopy with energy dispersive X-ray spectroscopy and X-ray diffraction analysis. Prepared coatings were thoroughly examined for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in alkaline solution (1 M potassium hydroxide, KOH) and their activity compared to that of Co and Ni coatings. All five coatings showed activity for both reactions, where CoMo and Co showed the highest activity for HER and OER, respectively. Namely, the highest HER current density was recorded at CoMo coating with low overpotential (61 mV) to reach a current density of 10 mA·cm−2. The highest OER current density was recorded at Co coating with a low Tafel slope of 60 mV·dec−1. Furthermore, these coatings proved to be stable under HER and OER polarization conditions.

Polyoxometalates (POMs) are polyatomic ions with closed three-dimensional frameworks. Their unique structure contains a large number of redox active sites, making them promising electrocatalysts for electrochemical energy conversion and storage applications. Thus, this paper presents an overview of the use of POMs as electrocatalysts for electrochemical energy conversion and storage devices, such as batteries, supercapacitors, fuel cells, or water electrolyzers. A discussion of the viability of these materials as alternatives to noble metal-based electrocatalysts is made. The current status of these materials to respond to the challenges of converting modern energy systems into more sustainable ones is also envisaged.