A. Matynia

Phosphates (V) recovery from phosphorus mineral fertilizers industry wastewater by continuous struvite reaction crystallization process.

Continuous DT MSMPR (Draft Tube Mixed Suspension Mixed Product Removal) crystallizer was provided with typical wastewater from phosphorus mineral fertilizers industry (pH < 4, 0.445 mass % of PO4(3-), inorganic impurities presence), dissolved substrates (magnesium and ammonium chlorides) and solution alkalising the environment of struvite MgNH4PO4·6H2O reaction crystallization process. Research ran in constant temperature 298 K assuming stoichiometric proportions of substrates or 20% excess of magnesium ions. Influence of pH (8.5-10) and mean residence time (900-3600 s) on product size distribution, its chemical composition, crystals shape, size-homogeneity and process kinetics was identified. Crystals of mean size ca. 25-37 μm and homogeneity CV 70-83% were produced. The largest crystals, of acceptable homogeneity, were produced using 20% excess of magnesium ions, pH 9 and mean residence time 3600 s. Under these conditions nucleation rate did not exceed 9 × 10(7) 1/(s m(3)) according to SIG (Size Independent Growth) MSMPR kinetic model. Linear crystal growth rate was 4.27 × 10(-9) m/s. Excess of magnesium ions influenced struvite reaction crystallization process yield advantageously. Concentration of phosphate(V) ions decreased from 0.445 to 9.2 × 10(-4) mass %. This can be regarded as a very good process result. In product crystals, besides main component - struvite, all impurities from wastewater were detected analytically.

Kinetics of Reaction-Crystallization of Struvite in the Continuous Draft Tube Magma Type Crystallizers—Influence of Different Internal Hydrodynamics

Abstract A laboratory-scale reaction-crystallization process of struvite synthesis from diluted water solution of Mg 2+ , NH 4 + and PO 4 3− ions was studied. The research covered the tests of two original constructions of continuous jet-pump Draft Tube Magma (DTM)-type crystallizers with internal circulation of suspension (upward/downward). Interactions between constructional, hydrodynamic and kinetic factors were established and discussed. Nucleation and linear growth rates of struvite crystals were calculated on the basis of population density distribution. Kinetic model of idealized Mixed Suspension Mixed Product Removal (MSMPR) crystallizer considering the size-dependent growth mechanism was applied (Rojkowski hyperbolic equation). For comparison purposes the kinetic data corresponded to a simpler, continuous draft tube-type crystallizer equipped with propeller agitator were analyzed. It was concluded that crystal product of larger size was withdrawn from the jet-pump DTM crystallizer of the descending flow of suspension in a mixing chamber.

THE INFLUENCE OF PROCESS PARAMETERS ON STRUVITE CONTINUOUS CRYSTALLIZATION KINETICS

ABSTRACT Experimental data concerning the kinetics of mass crystallization of struvite during the process of magnesium ion removal from water with the use of ammonium dihydrogenphosphate, NH4H2PO4, addition under alkaline conditions are presented. The tests were carried out in a continuous laboratory DTM MSMPR crystallizer with internal circulation of suspension (T = 298 K). The influence of concentration of Mg2 + ions in the raw material, pH of the process environment, and residence time of suspension on the nucleation and growth rates of struvite crystals was established. Kinetic parameters were evaluated from the crystal size distributions using selected size-dependent growth (SDG) models.

Size-dependent growth kinetics of vitamin C crystals in water solutions of L(+)-ascorbic acid with the addition of methanol and ethanol

Size-dependent growth kinetics of vitamin C crystals in water solutions of L(+)-ascorbic acid with the addition of methanol and ethanol Growth kinetics of vitamin C crystals during the batch mass crystallization process in L(+)-ascorbic acid - methanol - ethanol - water system was determined. The linear growth rate values were estimated on the basis of the product crystal size distributions. The kinetic model of the continuous process in a MSMPR crystallizer was adopted for the batch mode description according to Nyvlts conception, taking the sizedependent growth (SDG) rate effects into consideration. The kinetic parameter values were determined with a Rojkowski hyperbolic SDG model. A good compatibility between the experimental product crystal population density distributions and the SDG model predictions was observed. The interpretation of the kinetic data was presented and discussed.

Multilayer perceptron as the tool for modeling of reaction crystallization of barium sulphate in MSMPR crystallizer

One of the most ecologically harmful industrial wastes are the post-processed, used quenching salts, especially rich in BaCl2. Original method of their neutralization is based on their dissolution in water followed by a complex reaction crystallization process (after solid (NH4)2SO4 addition) effecting in production of barium sulphate. The process regime, which determines the crystalline product quality, depends on many technological parameters which individually influence various partial processes in micro- and macroscale. Facing this intrinsic complexity of the process its reliable analytical model has not been elaborated up till now. Application of artificial neural networks (e.g. multilayer perceptrons) for thorough description of such complex systems is substantiated since these need only the scattered information incorporated within the raw experimental data. An alternative model of the system behavior - numerical but free of any simplifying assumptions - is thus possible. Neural network simulation effects concerning reaction crystallization of barium sulphate in a DT MSMPR crystallizer are presented and discussed.

Reaction crystallization of struvite in a continuous DTM type crystallizer with a compressed air driven jet pump

Reaction crystallization of struvite in a continuous DTM type crystallizer with a compressed air driven jet pump Experimental tests covering the production of struvite MgNH4PO4·6H2O from water solutions containing 1.0 mass % of phosphate(V) ions using magnesium and ammonium ions in stoichiometric proportions were carried out in a crystallizer of 1.2 dm3 working volume. The process temperature was 298 K. Struvite crystals of mean size Lm from ca. 14 to ca. 38 μm were produced depending on the process environments pH (9-11) and the mean residence time of suspension in a crystallizer, τ (900-3600 s). In such defined process conditions the linear growth rate of struvite crystals changed from 1.45·10-8 m/s (pH 9, τ 900 s) to 2.06·10-9 m/s (pH 11, τ 3600 s) while the nucleation rate from 5.1·107 to 3.2·109 1/(sm3). Crystal product of the most advantageous granular characteristics was produced at pH 9 and the mean residence time 3600 s. Within this product population the largest sizes reached above 200 μm while the number of crystals smaller than 3 mm was kept below 6%.

Struvite recovery from solution containing phosphate(V) and sulphate(VI) ions

Abstract The research results concerning the application of magnesium and ammonium ions for continuous removal of phosphate(V) ions from solution containing 1.0 or 0.20 mass% of PO43– and from 0.10 to 0.50 mass% of SO42– are presented. A continuous struvite MgNH4PO4 × 6H2O reaction crystallization process was carried out both under stoichiometric conditions and using 20% excess of magnesium ions. The research was conducted in a DT MSMPR type crystallizer with internal circulation of suspension driven by a propeller stirrer, in constant temperature 298 K. The pH varied from 9 to 11 and mean residence time of suspension in a crystallizer τ varied from 900 to 3600 s. It was concluded, that sulphate(VI) ions influenced product quality disadvantageously. Depending on process parameter combinations struvite crystals of mean size from ca. 18 to ca. 44 μm and of moderate homogeneity: CV 7–95% were produced. Presence of sulphate(VI) ions favored crystallization of struvite as prismatic crystals, but tubular forms were also identified. The best shaped struvite crystals were produced at relatively low concentration of sulphate(VI) ions, pH 9 and for mean residence time of suspension in a crystallizer elongated up to 3600 s.

Kinetics of the continuous reaction crystallization of barium sulphate in BaCl2 - (NH4)2 SO4 - NaCl - H2O system - neural network model

Kinetics of the continuous reaction crystallization of barium sulphate in BaCl2 - (NH4)2 SO4 - NaCl - H2O system - neural network model One of the main toxic components of post quenching salts formed in large quantities during steel hardening processes is BaCl2. This dangerous ingredient can be chemically neutralized after dissolution in water by means of reaction crystallization with solid ammonium sulphate (NH4)2 SO4. The resulting size distribution of the ecologically harmless crystalline product - BaSO4 - is an important criteria deciding about its further applicability. Presence of a second component of binary quenching salt mixture (BaCl2-NaCl) in water solution, NaCl, influences the reaction-crystallization process kinetics affecting the resulting product properties. The experimental 39 input-output data vectors containing the information about the continuous reaction crystallization in BaCl2 - (NH4)2 SO4 - NaCl - H2 O system ([BaCl2]RM = 10-24 mass %, [NaCl]RM = 0-12 mass %, T = 305-348 K and τ = 900-9000 s) created the database for the neural network training and validation. The applicability of diversified network configurations, neuron types and training strategies were verified. An optimal network structure was used for the process modeling.

Modeling of MSMPR crystallizer dynamics – time series prediction by neural network

Abstract Mass crystallization process usually produces difficult for modeling oscillations of process parameters of diversified amplitude and period. For the simulation of dynamic behavior of MSMPR crystallizer in various technological conditions an artificial neural network specialized in time series prediction was originally used. The Monte Carlo simulations provided numerical data matrixes corresponded to stable and unstable process behavior, which were directly used for the neural network training and testing. Artificial neural network structures designed for both cumulative and individual parameter predictions were tested and verified in respect of their prediction ability in one-step, medium-term and long-term prognosis of the mass crystallization process dynamics.