Over the years, alternative procedures to the Bond grindability test have been proposed aiming to avoid the need for the standard mill or to reduce and simplify the grinding procedure. Some of them use the standard mill, while others are based on a non-standard mill or computation techniques. Therefore, papers targeting to propose a better alternative claim to improve validity, to reduce test duration, or to propose simpler and faster alternative methods for determining the Bond work index (w_i). In this review paper, a compilation and critical analysis of selected proposals is performed, concluding that some of the short procedures could be useful for control purposes, while the simulation-based procedures could be interesting within a process digitalisation strategy.

As water is essential to life and is an indispensable resource for ecosystems and their services and for nearly all human activities, the goal of this research was to evaluate the surface water quality of the Danube as it passes through the Romania–Serbia border in the nature reservations Djerdap and Iron Gate. The study aimed to assess the oxygen regime, nutrients and heavy metals contamination of the surface waters of the Danube on a length of about 240 km, between Bazias and Iron Gate II. Reference sampling and analytical methods (UV-VIS and AAS) were deployed to reach this goal. In addition, sediments were analyzed through back scattered SEM-EDAX for the elemental analysis of the sediment surface. Results obtained show a low environmental impact of heavy metals, while the Danube’s oxygen regime is under stress due to nutrients’ (nitrites and orthophosphates) significant concentration in the Danube surface water in the analyzed sector. Our approach can be applied to other water bodies in the area, to increase available scientific data together with societal awareness of the Danube’s environmental risks.

Flotation deinking is one of the most widely used techniques for the separation of ink particles from cellulose fibers during the process of paper recycling. It is a complex process influenced by a variety of factors, and is difficult to represent and usually results in models that are inconvenient to implement and/or interpret. In this paper, a comprehensive study of several machine learning methods for the prediction of flotation deinking performance is carried out, including support vector regression, regression tree ensembles (random forests and boosting) and Gaussian process regression. The prediction relies on the development of a limited dataset that assumes representative data samples obtained under a variety of laboratory conditions, including different reagents, pH values and flotation residence times. The results obtained in this paper confirm that the machine learning methods enable the accurate prediction of flotation deinking performance even when the dataset used for training the model is limited, thus enabling the determination of optimal conditions for the paper recycling process, with only minimal costs and effort. Considering the low complexity of the Gaussian process regression compared to the aforementioned ensemble models, it should be emphasized that the Gaussian process regression gave the best performance in estimating fiber recovery (R² = 97.77%) and a reasonable performance in estimating the toner recovery (R² = 86.31%).

Dry micronizing grinding of mineral raw materials is a very complex process and depends on a whole range of parameters such as: shape, particle size, size distribution of the starting and micronized material, hardness, moisture, density, surface properties, structural characteristics of mills, etc. In order to obtain a clear picture of dry micronizing milling process, a good knowledge of the theoretical principles of high-energy mills operation is necessary. Classical mills are not suitable for micronization to a fine and particularly very fine particles size (upper particle size limit below 5 μm), which is necessary for modern industrial application domains. The intensive fundamental and developmental research of the dry micronizing milling process for the new materials development has also enabled the development of new construction solutions for ultra-fine high-energy mills - mechanics. These mills have found application into the state-of-the-art production technologies of new very profitable materials. For the production of powders - particles of micron dimensions, the mechano-actuators are used and all micronizers - disintegrators, colloidal (perl mills), vibratory, planetary, ultra-centrifugal mill, Jet-current mills and others operate on the principle of impact, shock and friction. This paper presents the experimentally achieved results of dry micronizing grinding of zeolites in a vibrating mill with rings, as well as the improvement of its reactivity. All experimental micronization investigations were carried out on a previously prepared coarse particle size class (- 3.35 + 0) mm with different starting mass (50 g and 200 g), and carried out in different grinding time intervals (45, 120, 900 seconds), in order to examine the impact of these parameters on the micronization process. Grinding success was evaluated by the particle size measurements and content of class (- 5 + 0) μm, and particle specific surface. It was shown that for a sample of four times larger initial mass it is need longer grinding time to achieve the maximum content of the class (- 5 + 0) μm, but for a sample of the bulk class (- 3.35 + 0) mm with a lower starting mass the effects of amorphization due to prolonged micronizing grinding are very pronounced, and the zeolite minerals in crystalline form are practically in the trace and the largest part is amorphous. Generally, it can be concluded that a vibrating mill with a rings proved to be a good device for efficient ultra-fine micronizing grinding.

Determining the Bond grindability test in a ball mill is one of the most commonly used methods in the mining industry for measuring the hardness of ores. The test is an essential part of the Bond work index methodology for designing and calculating the efficiency of mineral grinding circuits. The Bond ball mill grindability test has several restrictions, including the sample’s initial particle size distribution (PSD). This paper presents a method for calculating the Bond work index when the Bond ball mill grindability test is performed on samples with non-standard PSD. The presented equation includes a correction factor (k) and is applicable only for P₁₀₀ = 75 μm. The defined method is then compared with methods proposed by other researchers, and conclusions are drawn as to which method results in less deviation. The presented model resulted in a mean square error of 0.66%.