Kinetic Energy Dose as a Unified Metric for Comparing Ball Mills in the Mechanocatalytic Depolymerization of Lignocellulose

Mechanochemistry utilizes mechanical forces to activate chemical bonds. It offers environmentally benign routes for both (bio) organic and inorganic syntheses. However, direct comparison of mechanochemistry results is often very challenging. In mechanochemical synthetic protocols, ball mill setup (mechanical design and grinding vessel geometry) in addition to experimental parameters (milling frequency, duration, ball count and size) vary broadly. This fact poses a severe issue to further progress in this exciting research area because ball mill setup and experimental parameters govern how much kinetic energy is transferred to a chemical reaction. In this work, we address the challenge of comparing mechanochemical reaction results by taking the energy dose provided by ball mills as a unified metric into account. In this quest, we applied kinematic modeling to two ball mills functioning under distinct working principles to express the energy dose as a mathematical function of the experimental parameters. By examining the effect of energy dose on the extent of the mechanocatalytic depolymerization (MCD) of lignocellulosic biomass (beechwood), we found linear correlations between yield of water-soluble products (WSP) and energy dose for both ball mills. Interestingly, when a substrate layer is formed on the grinding jar wall and/or grinding medium, a weak non-linear correlation between water-soluble products yield and energy dose is identified. We demonstrate that the chemical reaction’s best utilization of kinetic energy is achieved in the linear regime, which presents improved WSP yields for given energy doses. In the broader context, the current analysis outlines the usefulness of the energy dose as a unified metric in mechanochemistry to further the understanding of reaction results obtained from different ball mills operating under varied experimental conditions.

Spark Plasma Sintering of Aluminum Nanocomposite Powders: Recent Strategy to Translate from Lab-Scale to Mass Production

The aim of this paper focuses on presenting a recent study that describes the fundamental steps needed to effectively scale-up from lab to mass production parts produced from Al powders reinforced with 0.5 wt% of industrial multiwalled carbon nanotubes (MWCNTs), with mechanical and electrical conductivity properties higher that those measured at the lab scale. The produced material samples were produced via a Spark Plasma Sintering (SPS) process using nanocomposite aluminum powders elaborated with a planetary ball-mill at the lab scale, and high-volume attrition milling equipment in combination with controlled atmosphere sinter hardening furnace equipment, which were used to consolidate the material at the industrial level. Surprisingly, the electrical conductivity and mechanical properties of the samples produced with the reinforced nanocomposite Al powders were made with mass production equipment and were similar or higher than those samples fabricated using metallic powders prepared with ball-mill lab equipment. Experimental measurements show that the hardness and the electrical conductivity properties of the samples fabricated with the mass production Al powders are 48% and 7.5% higher than those of the produced lab samples. This paper elucidates the steps that one needs to follow during the mass production process of reinforced aluminum powders to improve the physical properties of metallic samples consolidated via the SPS process.

Efficacy of Selenourea Organocatalysts in Asymmetric Michael Reactions under Standard and Solvent-Free Conditions

By varying the steric and electronic surroundings of the hydrogen-bonding motif, the novel chiral Cinchona-alkaloid based selenoureas were developed. Acting as bifunctional catalysts, they were applied in the Michael reactions of dithiomalonate and nitrostyrene providing chiral adducts with up to 96% ee. The asymmetric Michael–-hemiacetalization reaction of benzylidene pyruvate and dimedone, performed with the assistance of 5 mol% of selenoureas, furnished the product with up to 93% ee and excellent yields. The effectiveness of the new hydrogen-bond donors was also proved in solvent-free reactions under ball mill conditions, supporting the sustainability of the devised catalytic protocol.

The structure and phase composition of the cermet charge in the Al‒Al2O3 system obtained using mechanical processing of aluminum powder in a planetary ball mill

The cermet charge in the Al‒Al2O3 system was obtained by mechanical processing (MP) in a planetary ball mill of aluminum powder of the industrial grade PAP-2 (GOST 5494‒95), consisting of flake particles of submicron thickness with a coating of stearin. Depending on the MP modes used, 4 types of charge were obtained, the bulk density of which varied from 0,33 to 1,1 g/cm3. For all types of charge, the synthesis of the α-Al2O3 phase was observed as a result of the exothermic reaction of the interaction of air oxygen with the surface of aluminum particles during the MP. It is also possible to form boehmite and gibbsite when the activated surface of Al particles interacts with atmospheric water vapor. The local X-ray spectral analysis (EDX) was used to detect X-ray amorphous carbon in the composition of the charge, the appearance of which is associated with the impact- shearing effect of grinding bodies, leading to the nucleation of X-ray amorphous carbon inclusions due to the termal destruction of stearin. The maximum bending strength of the sintered cermet was 550 MPa. This cermet is characterized by a discrete fracture: the formation of dimples as a result of the shear of layered packets under the action of tangential stresses. The revealed mechanisms cermet’s fractures allow us to establish the optimal modes of MP of powder compositions for obtaining various constructional elements from them.

Applied Machine Learning for Geometallurgical Throughput Prediction—A Case Study Using Production Data at the Tropicana Gold Mining Complex

With the increased use of digital technologies in the mining industry, the amount of centrally stored production data is continuously growing. However, datasets in mines and processing plants are not fully utilized to build links between extracted materials and metallurgical plant performances. This article shows a case study at the Tropicana Gold mining complex that utilizes penetration rates from blasthole drilling and measurements of the comminution circuit to construct a data-driven, geometallurgical throughput prediction model of the ball mill. Several improvements over a previous publication are shown. First, the recorded power draw, feed particle and product particle size are newly considered. Second, a machine learning model in the form of a neural network is used and compared to a linear model. The article also shows that hardness proportions perform 6.3% better than averages of penetration rates for throughput prediction, underlining the importance of compositional approaches for non-additive geometallurgical variables. When adding ball mill power and product particle size, the prediction error (RMSE) decreases by another 10.6%. This result can only be achieved with the neural network, whereas the linear regression shows improvements of 4.2%. Finally, it is discussed how the throughput prediction model can be integrated into production scheduling.

Production Capacity Requirements Planning Using The Capacity Method Requirement Planning

PT. ABC is a company engaged in the manufacture of Dolomite Fertilizer. The number of requests is greater than the amount of production. Due to fluctuations in the number of requests that tend to increase, this occurs due to a lack of capacity at the workstation. Therefore, it is necessary to calculate the capacity requirements planning analysis for each work station to know the company's capacity needs. The research aims to identify the shortage/excess production capacity and provide proposals for the balance of production capacity at PT. A B C. Production capacity research was conducted using the Capacity Requirement Planning (CRP) method. Results and Discussion, comparison of available capacity and required capacity (load) are as follows, work station jaw crusher available capacity 36.74 hours/week while required capacity (load) 36 hours/week, work station bucket elevator available capacity 36, 74 hours/week while the required capacity (load) is 14.4 hours/week, work station ball mill available capacity is 36.74 hours/week while the required capacity (load) is 45.6 hours/week, and work station silo flour the available capacity is 36.74 hours/week while the required capacity (load) is 51.59 hours/week. In conclusion, two stations experience excess capacity, namely the jaw crusher work station with an excess capacity of 0.74 hours/week and the bucket elevator work station with an excess capacity of 22.34 hours/week. The other two work stations experienced a lack of capacity, namely the ball mill work station with a capacity shortage of 22.34 hours/week and the silo flour work station with a capacity shortage of 14.85 hours/week. Efforts to balance capacity by scheduling overtime and adding equipment (machinery) to work centers that lack capacity, so that the company's production targets are achieved.