Bioleaching of marmatite flotation concentrate by Acidithiobacillus ferrooxidans and Leptospirillum ferrooxidans

Bioleaching of marmatite flotation concentrate by Acidithiobacillus ferrooxidans and Leptospirillum ferrooxidans was investigated at 35 ℃, the initial pH value of 2.0 on an orbital shaker with 160 min-1 over a period of 10 days. Experimental results indicate that the adapted strains increase markedly the dissolution rate and the leaching ratio of marmatite. Pulp density also affects the bioleaching of marmatite. Massive elemental sulfur and jarosite form during the leaching process in the systems inoculating the adapted strains in pure and mixed cultures; and acid product is enhanced, which decreases the pH below to 2.0 in latter leaching period. Marmatite preferentially dissolves during the bacterial leaching of complex sulfides. Compared with the pure cultures of original and adapted strains, the adapted strains of Acidithiobacillus ferrooxidans and Leptospirillum ferrooxidans in mixed cultures are more efficient in the oxidation of marmatite.

Marmatite bioleaching with moderately thermoacidophilic bacterial strain and mineral analyses of solid residues

The bioleaching of a marmatite flotation concentrate with a moderately thermoacidophilic iron-oxidizing bacterial strain (MLY) is influenced significantly by temperature, pH, particle size, pulp density of ores and bacterial strains. Under such leaching conditions as the initial pH value of 1.5, temperature of 50℃, pulp density of 5%, particle size less than 35.5μm (over 90%) and inoculating the adapted strains of MLY, the leached Zn is over 95% after 10d of bioleaching. SEM observations show the cell attachment and the surface features of solid residues under different leaching conditions. XRD and EDX analyses show that a mass of elemental sulfur form during the bioleaching process. The technological feasibility of a microbiological process using MLY for extracting zinc from the marmatite concentrate is demonstrated.

A novel 3-layer mixed cultural evolutionary optimization framework for optimal operation of syngas production in a Texaco coal-water slurry gasifier

Optimizing operational parameters for syngas production of Texaco coal-water slurry gasifier studied in this paper is a complicated nonlinear constrained problem concerning 3 BP(Error Back Propagation) neural networks. To solve this model, a new 3-layer cultural evolving algorithm framework which has a population space, a medium space and a belief space is firstly conceived. Standard differential evolution algorithm(DE), genetic algorithm(GA), and particle swarm optimization algorithm(PSO) are embedded in this framework to build 3-layer mixed cultural DE/GA/PSO(3LM-CDE, 3LM-CGA, and 3LM-CPSO) algorithms. The accuracy and efficiency of the proposed hybrid algorithms are firstly tested in 20 benchmark nonlinear constrained functions. Then, the operational optimization model for syngas production in a Texaco coal-water slurry gasifier of a real-world chemical plant is solved effectively. The simulation results are encouraging that the 3-layer cultural algorithm evolving framework suggests ways in which the performance of DE, GA, PSO and other population-based evolutionary algorithms(EAs) can be improved,and the optimal operational parameters based on 3LM-CDE algorithm of the syngas production in the Texaco coalwater slurry gasifier shows outstanding computing results than actual industry use and other algorithms.

CFD simulation for reduction of pyrolusite in fluidized beds

In this study,a CFD model coupled with heterogeneous flow structure,mass transfer equations,and chemical reaction kinetics is established to forecast the pyrolusite reduction reaction behavior.Compared with the previous studies which ignore the volume change of solids phase,the influence of volume shrinkage on reaction and flow behavior is explored in this research.Volume shrinkage of pyrolusite is proved to be non-negligible in predicting the conversion rate.The negligence of volume shrinkage leads to the overestimation of conversion rate for its inaccurate estimation of surface area for reaction.Besides,the influence of volume shrinkage on the reaction is found smaller in the scaled-up reactor.

Analysis of the energy-minimization multiscale model with multiobjective optimization

Gas-solid two-phase flow is ubiquitous in nature and many engineering fields,such as chemical engineering,energy,and mining.The closure of its hydrodynamic model is difficult owing to the complex multiscale structure of such flow.To address this problem,the energy-minimization multi-scale(EMMS)model introduces a stability condition that presents a compromise of the different dominant mechanisms involved in the systems,each expressed as an extremum tendency.However,in the physical system,each dominant mechanism should be expressed to a certain extent,and this has been formulated as a multiobjective optimization problem according to the EMMS principle generalized from the EMMS model.The mathematical properties and physical meanings of this multiobjective optimization problem have not yet been explored.This paper presents a numerical solution of this multiobjective optimization problem and discusses the correspondence between the solution characteristics and flow regimes in gas-solid fluidization.This suggests that,while the most probable flow structures may correspond to the stable states predicted by the EMMS model,the noninferior solutions are in qualitative agreement with the observable flow structures under corresponding conditions.This demonstrates that both the dominant mechanisms and stability condition proposed for the EMMS model are physically reasonable and consistent,suggesting a general approach of describing complex systems with multiple dominant mechanisms.

Pattern formation in particle systems driven by color field

The structural evolution of systems with two kinds of particles driven in opposite directions, i.e., driven by a color field, is investigated by molecular dynamics simulations. Gaussian thermostat, a common treatment to restrict the thermal velocity of the particles in the systems, has been used so as to account for the dissipation of heat and allow the system to reach a steady state. It has been found that with the increase of the strength of driving force （F）, the system undergoes an obvious structural transition from an initially random mixing state to a state characterized by separate lanes and in each lane only one kind of particles exists. The analysis shows that the reason for the formation of lane structure is not only the increase of F but also the variation of particle friction coefficient. While using Gaussian thermostat the particle friction coefficient becomes a function of F. Increasing F leads to high particle friction coefficient and inevitably results in lane formation for strong enough driving force. When lifting the effect of F on friction coefficient and choosing a constant friction coefficient, our results show that for a given F there always exists a critical value of friction coefficient higher than which the system will develop into lane structure.