Optimization procedure of gradient separations in ion-exchange chromatography using simplex optimization method in combination with the computer simulation program for ion-exchange chromatography is presented. The optimization of parameters describing gradient profile for the separation in ion chromatography is based on the optimization criterion obtained from calculated chromatograms. The optimization criterion depends on the parameters used for calculations and thus exhibits the quality of gradient conditions for the separation of the analytes. Simplex method is used to calculate new gradient profiles in order to reach optimum separations for the selected set of analytes. The Simplex algorithm works stepwise, for each new combination of parameters that describe the gradient profile a new calculation is performed and from the calculated chromatogram the optimization criterion is determined. The proposed method is efficient and may reduce the time and cost of analyses of complex samples with ion-exchange chromatography.
COBISS.SI-ID: 4729626
Process optimization involves the minimization (or maximization) of an objective function, that can be established from a technical and (or) economic viewpoint taking into account safety of process. The basic idea of the optimization method using neural network (NN) is to replace the model equations (which traditionally obtained using, for example, the surface response design or others methods) by an equivalent NN. The feed-forward bottleneck neural network (FFBN) as a mapping technique is described and evaluated. From the 2D maps the optimal parameters of pigment dyeing of high performance fibers on the bases of poly-amide benzimidazole (PABI) and polyimide (arimid) are discussed. The studied fibers were treated in 32 experiments under the conditions as proposed by the Design of Experiment (DOE), varying five influencing factors. Neural network mapping method enables visualization of process and shows the influence of different factors on different output responses. Optimum parameters were selected upon compromise decision.
COBISS.SI-ID: 4713754
The applicability domain (AD) of models developed for regulatory use has attracted great attention recently. The AD of quantitative structure-activity relationship (QSAR) models is the response and chemical structure space in which the model makes predictions with a given reliability. The evaluation of AD of regressions QSAR models for congeneric sets of chemicals can be find in many papers and books while the issue about metrics for the evaluation of an AD for the non-linear models (like neural networks) for the diverse set of chemicals represents the new field of investigations in QSAR studies. The scientific society is standing before the challenge to find out reliable way for the evaluation of an AD of non linear models. The new metrics for the evaluation of the AD of the counter propagation artificial neural network (CP ANN) models are discussed in the article: the Euclidean distances between an object (molecule) and the corresponding excited neuron of the neural network and between an object (molecule) and the representative object (vector of average values of descriptors). The investigation of the training and test sets chemicals coverage in the descriptors space was made with the respect to false predicted chemicals. The leverage approach was used to compare non linear (CP ANN) models with linear ones
COBISS.SI-ID: 4861978
Waste composite poly-methyl methacrylate filled with a fine dispersion aluminium trihydrate (PMMA/ATH) and Fischer-Tropsch wax were used as modifying agents for a 70/100 paving grade bitumen employed for road paving. The effect of modifying agent content, primary ageing and long-term oxidative ageing on rheological and mechanical properties of base and modified bitumen were studied. The rutting resistance at high service temperatures was analyzed with oscillatory shear tests and multiple stress creep recovery measurements. Waste PMMA/ATH powder proved suitable for bitumen modification, particularly in combination with wax. Moreover, aluminium trihydrate is a flame retardant material. PMMA/ATH is less susceptible to heat and oxygen, therefore modified bitumen samples show improved viscoelastic and physical characteristics compared to base bitumen at handling and in-service temperatures.
COBISS.SI-ID: 5069338
The subject invention is bitumen with the addition of PMMA/ATH composite dust. PMMA/ATH composite powder is, according to the invention, added to the bitumen, which is used in asphalt mixtures, in order to improve properties of asphalt mixtures. The invention belongs to the field of asphalt. Modified bitumen, according to the invention contains the following ingredients in percentage by weight: from 50% to 99.9% (w/w) binder, which is mostly bitumen, and from 0.1 to 50% (w/ ) PMMA / ATH composite powder. Bitumen properties were tested with standard tests, such as softening point test method ring&ball (EN 1427), penetration test (EN 1426) and Fraass breaking point (EN 12593). Tests at 25% (w/w) content of PMMA/ATH composite dust in the bitumen showed a 7.4 ° C increase in temperature softening point (EN 1427) and a 4 ° C decrease in temperature of Fraass breaking point (EN 12593) with respect to the base bitumen. Rheological tests at 60 ° C showed an increase in rut formation parameter of G*/sin (). Basic bitumen has rut formation parameter 1330 Pa, at 25% (w/w) content of PMMA/ATH composite dust in the bitumen measured value of rut formation parameter 3650 Pa, which is almost three times greater resistance to the formation of ruts as base bitumen.
COBISS.SI-ID: 5121818