The cometabolic biodegradation of 4-Chlorophenol (4-CP) by the Stenotrophomonas maltophilia KB2 strain in the presence of phenol (P) was studied. In order to determine the kinetics of biodegradation of both substrates, present alone and in cometabolic systems, a series of tests was carried out in a batch reactor changing, in a wide range, the initial concentration of both substrates. The growth of the tested strain on phenol alone was described by Haldane kinetic model (mm = 0:9 1/h, Ksg = 48:97 gg/m3, KIg = 256:12 gg/m3, Yxg = 0:5715). The rate of 4-CP transformation by resting cells of KB2 strain was also described by Haldane equation and the estimated parameters of the model were: kc = 0:229 gc=gxh, Ksc = 0:696 gc=m3, KIc = 43:82 gc=m3. Cometabolic degradation of 4-CP in the presence of phenol was investigated for a wide range of initial 4-CP and phenol concentrations (22–66 gc/m3 and 67–280 gg/m3 respectively). The experimental database was exploited to verify the two kinetic models: CIModel taking only the competitive inhibition into consideration and a more universal CNIModel considering both competitive and non-competitive inhibition. CNIModel approximated experimental data better than CIModel.
In the foundry industry, many harmful compounds can be found, which as a result of gradual but long-term exposure to employees bring negative results. One of such compounds is phenol (aromatic organic compound), which its vapours are corrosive to the eyes, the skin, and the respiratory tract. Exposition to this compound also may cause harmful effects on the central nervous system and heart, resulting in dysrhythmia, seizures, and coma. Phenol is a component of many foundry resins, especially used in shell moulds in the form of resincoated sands. In order to identify it, the pyrolysis gas chromatography-mass spectrometry method (Py-GC/MS) was used. The tests were carried out in conditions close to real (shell mould process – temperature 300°C). During the measurement, attention was focused on the appropriate selection of chromatographic analysis conditions in order to best separate the compounds, as it is difficult to separate the phenol and its derivatives. The identification of compounds was based on own standards.
The paper presents the impact of biodegradable material - polycaprolactone (PCL) on selected properties of moulding sands. A self-hardening moulding sands with phenol-furfuryl resin, which is widely used in foundry practice, and an environmentally friendly self-hardening moulding sand with hydrated sodium silicate where chosen for testing. The purpose of the new additive in the case of synthetic resin moulding sands is to reduce their harmfulness to the environment and to increase their “elasticity” at ambient temperature. In the case of moulding sands with environmentally friendly hydrated sodium silicate binder, the task of the new additive is to increase the elasticity of the tested samples while preserving their ecological character. Studies have shown that the use of 5% PCL in moulding sand increases their flexibility at ambient temperature, both with organic and inorganic binders. The influence of the new additive on the deformation of the moulding sands at elevated temperatures has also been demonstrated.
Chemical bonded resin sand mould system has high dimensional accuracy, surface finish and sand mould properties compared to green sand mould system. The mould cavity prepared under chemical bonded sand mould system must produce sufficient permeability and hardness to withstand sand drop while pouring molten metal through ladle. The demand for improved values of permeability and mould hardness depends on systematic study and analysis of influencing variables namely grain fineness number, setting time, percent of resin and hardener. Try-error experiment methods and analysis were considered impractical in actual foundry practice due to the associated cost. Experimental matrices of central composite design allow conducting minimum experiments that provide complete insight of the process. Statistical significance of influencing variables and their interaction were determined to control the process. Analysis of variance (ANOVA) test was conducted to validate the model statistically. Mathematical equation was derived separately for mould hardness and permeability, which are expressed as a non-linear function of input variables based on the collected experimental input-output data. The developed model prediction accuracy for practical usefulness was tested with 10 random experimental conditions. The decision variables for higher mould hardness and permeability were determined using desirability function approach. The prediction results were found to be consistent with experimental values.