2D molybdenum disulfide exhibited superb adsorption capacity of Pb2+.Complexation between Pb2+ and intrinsic S or O atoms exposed on 2D molybdenum disulfide surface was proposed.2D molybdenum disulfide might be an excellent Pb2+ adsorbent in wastewater treatment.
Two-dimensional (2D) molybdenum disulfide might be highly capable of lead removal from wastewater due to the huge sulfur-rich surface area. An attempt was made to explore the feasibility of using 2D molybdenum disulfide as a super adsorbent in water in this work. Adsorption isotherm and kinetics and SEM-EDS were conducted to investigate Pb(II) adsorption capacity at the interface of 2D molybdenum disulfide/water, and XPS was used to study the adsorption mechanism. The results indicated that 2D molybdenum disulfide had a dramatic efficiency for Pb(II) removal from water with a 1479mg/g adsorption capacity. The adsorption followed the Freundlich isotherm model and fitted well with both the pseudo-first-order and pseudo-second-order kinetics models. The adsorption might be attributed to the chemical adsorption due to the complexation of Pb(II) with intrinsic S or O atoms exposed on 2D molybdenum disulfide surfaces, together with electrostatic adsorption.
The following example demonstrates a method of selecting the components of an aggregate plant. Good component efficiency and part performance pre-evaluation is essential to a solid design. The aggregate production requires the consideration of several crushers, feeders and screens. This is not intended to be a typical situation, though it does involve common crusher and screen units often used in aggregate plants.
Quarry rock of 12 in. maximum size is to be handled in a two-stage crusher plant at the rate of 70 tons per hour. The maximum size of output is to be 1 in., and separation of materials over 1 in. size and the minus 1 in. in the output is required. Select a jaw crusher like those included in this table.
The screens to be considered are a 1-in. screen with an estimated capacity of 2.7 tph/sq ft and a 1-in. screen with a capacity of 2.1 tph/sq ft. The solution will include the selection of adequate and economical crushers for the two stages and the sizes of screens between them and below the secondary stage.
For the primary crusher a jaw crusher will probably be most economical. A jaw crusher, like 2036 in the Jaw Crusher Table here above, would be able to take the maximum 12 in. size quarry stone but it would not have the required 70 tph capacity needed. To have the needed capacity a jaw crusher like the 2042 or 2436 sizeswill have to be selected overloading the secondary crusher.
A grid chart or curve for the selected crusher shows that, for a 2-in. setting, 54% of the material will pass a 1-in. screen, or 46% will be retained (this is like Jaw Crusher capacity table abovewhere 48% passes a 1 in. screen). The 46% of 70 tph gives the 32 tph fed to the secondary crusher shown in Figure below as a roll crusher.
A twin-roll crusher is selected, like those given inthe Roll Crusher capacityTable above, to serve as the reduction crusher. The smallest, 24 x 16 roll crusher shown in theRoll Crusher capacity Table above has enough capacity with a setting of 1 in. but the maximum size feed will be too large, that is, the stage of reduction is not large enough. The maximum size of feed coming from the discharge of the primary crusher with a setting of 2 is about 3 in. as may be found in this Table.
Considering a 30-in. diameter roll crusher the maximum size particle that can be nipped with the roll crusher set at 1 in. according to this Equation is F = 0.085(15) + 1.0 = 2.28 in. <3 in. feed. It will take larger than a 40-in. diameter roll crusher. A better solution would be to use a larger jaw crusher set at 1 in., then a roll crusher from the Roll Crusher capacityTable above could be used. If the output of this crushing process should have less material of the +1-in. size, the larger crusher could be operated with a closed circuit. That is, the oversize in the output could be recirculated through the roll crusher without exceeding the rated capacity of the crusher. Then all material leaving that crusher with a 1-in. setting would be of a minus 1-in. size.
Another possible solution to this problem would be to use a gyratory crusher for the primary crushing stage. A gyratory like Telsmith model1110 could be set at 1 in. in an open circuit with a capacity for 260 tph. The maximum size of stone in the output is estimated to be approximately 2 1/8 in. Then all the output from the primary crusher could be nipped by a 40 in. diameter twin-roll crusher with a 1-in. setting according to the Roll Crusher capacityTable above. The specifications and manufactured limitations, rather than economy, generally govern the selection of crushers.
To find the required areas of screen, the rate of feed of material as well as gradation of the feed must be known. The 1-in. screen under the jaw crusher is the top deckno deck correction factor will be necessary. Therefore, the 1-in. screen will need to be at least 70/2.7 = 29.9 sq ft in area. It must be at least 36 in. wide for an 18 x 36 jaw crusher. So a 4-ft by 8-ft screen would be acceptable. The 1-in. screen is a second deck for the 38 tph from the jaw crusher, so the deck correction factor is 0.90 and that screen capacity is 2.1 x 0.9 = 1.89 tph/sq ft.
The screen area needed under the jaw crusher is 38/1.89 = 20.1 sq ft. For the 1-in. screen below the roll crusher the capacity has no correction factor and the area needed is 32/2.1 = 15.2 sq ft. To handle the output from a 40 x 24 roll crusher the screen will have to be at least 24 in. wide. Perhaps it will be more effective to use one continuous screen of at least 20.1 + 15.2 = 35.3 sq ft. A 4-ft by 10-ft 1 in. screen should be satisfactory.
A DEM modelling framework for simulation of cone crushers is proposed.Rock material model based on bonded particle model and calibrated against breakage experiments.Simulation results are compared with industrial scale cone crusher experiments.Novel insight regarding internal mechanical dynamics and particle flow behaviour and breakage.
Compressive crushing has been proven to be one of the most energy efficient principles for breaking rock particles (Schnert, 1979). In this paper the cone crusher, which utilizes this mechanism, is investigated using the discrete element method (DEM) and industrial scale experiments. The purpose of the work is to develop a virtual simulation environment that can be used to gain fundamental understanding regarding internal processes and operational responses. A virtual crushing platform can not only be used for understanding but also for development of new crushers and for optimisation purposes.
Rock particles are modelled using the bonded particle model (BPM) and laboratory single particle breakage tests have been used for calibration. The industrial scale experiments have been conducted on a Svedala H6000 cone crusher operated as a secondary crushing stage. Two different close side settings have been included in the analysis and a high speed data acquisition system has been developed and used to sample control signals such as pressure and power draw in order to enable detailed comparison with simulation results. The crusher has been simulated as a quarter section with a batch of breakable feed particles large enough to achieve a short moment of steady state operation. Novel methods have been developed to estimate the product particle size distribution using cluster size image analysis. The results show a relatively good correspondence between simulated and experimental data, however further work would be need to identify and target the sources of observed variation and discrepancy between the experiments and simulations.
A decision support system for equipment operation in a crushing circuit is proposed.The proposed approach is based on a simheuristic strategy in an industrial simulator.The objective function aims to maximize the production of a crushing plant.Industrial cases are used to validate the effectiveness of the decision system.The results show a 9% increase in production and a 59% reduction in energy consumption.
The production rate of an ore crushing circuit depends on the amount of equipment in operation. If the amount of active equipment is less than the optimum level, the reduced ore flow paths restrict the production rate. However, if the amount of active equipment is greater than the optimum level, the excess circulating load ore and extra energy consumption reduce the circuit efficiency. In addition, the optimum amount of active equipment can change over time due to changes in the ore characteristics, such as hardness and particle size. In this paper, a decision support system is proposed for optimizing the amount of active equipment for maximum crushing production considering changes in the circuit feed rate. The proposed solution is based on a simheuristic approach in which a simulated plant model is used to evaluate the production rate. Real production scenarios at a Brazilian mining plant are used in computational experiments. The results show that the simheuristic solutions generate a higher production rate and result in less energy consumption. Production is increased by up to 9%, and energy consumption is reduced by up to 59%, demonstrating the efficacy of the proposal.