The statistical modeling of surface roughness in high-speed flat end milling

Surface roughness is one of the most important requirements in machining process. The surface roughness value is a result of the tool wear. When tool wear increase, the surface roughness also increases. The determination of the sufficient cutting parameters is a very important process obtained by means of both minimum surface roughness values and long tool life. The statistical models were developed to predict the surface roughness.This paper presents the development of a statistical model for surface roughness estimation in a high-speed flat end milling process under wet cutting conditions, using machining variables such as spindle speed, feed rate, depth of cut, and step over. First- and second-order models were developed using experimental results of a rotatable central composite design, and assessed by means of various statistical tests. The highest coefficient of correlation (R_adj²) (88%) was obtained with a 10-parameter second-order model. Meanwhile, a time trend was observed in residual values between model predictions and experimental data, reflecting the probable effect of the tool wear on surface roughness. Thus, in order to enhance the estimation capability of the model, another independent variable was included into the model to account for the effect of the tool wear, and the total operating time of the tool was selected as the most suitable variable for this purpose. By inserting this new variable as a linear term into the model, R_adj² was increased to 94% and a good fit was observed between the model predictions and supplementary experimental data.In this study, it was observed that, the order of significance of the main variables is as X₅>X₃>X₄>X₁>X₂ (total machining time, depth of cut, step over, spindle speed and feed rate, respectively).     

Removal of Cd(II), Hg(II), and Pb(II) ions from aqueous solution using p(HEMA/chitosan) membranes

An interpenetration network (IPN) was synthesized from 2‐hydroxyethyl methacrylate (HEMA) and chitosan, p(HEMA/chitosan) via UV‐initiated photo‐polymerization. The selectivity to different heavy metal ions viz Cd(II), Pb(II), and Hg(II) to the IPN membrane has been investigated from aqueous solution using bare pHEMA membrane as a control system. Removal efficiency of metal ions from aqueous solution using the IPN membranes increased with increasing chitosan content and initial metal ions concentrations, and the equilibrium time was reached within 60 min. Adsorption of all the tested heavy metal ions on the IPN membranes was found to be pH dependent and maximum adsorption was obtained at pH 5.0. The maximum adsorption capacities of the IPN membrane for Cd(II), Pb(II), and Hg(II) were 0.063, 0.179, and 0.197 mmol/g membrane, respectively. The adsorption of the Cd(II), Hg(II), and Pb(II) metal ions on the bare pHEMA membrane was not significant. When the heavy metal ions were in competition, the amounts of adsorbed metal ions were found to be 0.035 mmol/g for Cd(II), 0.074 mmol/g for Hg(II), and 0.153 mmol/g for Pb(II), the IPN membrane is significantly selective for Pb(II) ions. The stability constants of IPN membrane–metal ions complexes were calculated by the method of Ruzic. The results obtained from the kinetics and isotherm studies showed that the experimental data for the removal of heavy metal ions were well described with the second‐order kinetic equations and the Langmuir isotherm model. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 2007     

Detection of sulphamethazine with an optical biosensor and anti-idiotypic antibodies

We describe the development of an assay for the detection of sulphamethazine in animal urine with a surface plasmon resonance (SPR) biosensor. In order to obtain a general assay that can easily be transferred to other veterinary drug residues, a monoclonal antibody against sulphamethazine and a corresponding anti-idiotypic antibody were used. The assay had a lower detection limit of 5 μg/l which is well below the maximum residue limits (MRL) of 100 μg/l and can be used for screening purposes in animal urine. The binding reaction between the antibodies as occurring during sensor application was characterized with respect to avidity and kinetic properties.     

Development of a multichannel fluorescence affinity sensor system

A multichannel fluorometer is proposed for analysis of biochemical reactions. The sensor is based on the luminescence generation in the evanescent field of a totally reflected laser beam. For transduction, multiple reflection elements are used. Multichannel operation is realized, including the possibility of applying different solutions to each channel at the same time. First experimental results, obtained with fluorescein or Cy5 as labels in a model hybridization assay, demonstrate the applicability and allow the detection of 3-10 fmol injected fluorescently labeled oligonucleotide.     

Preparation and characterization of comb type polymer coated poly(HEMA/EGDMA) microspheres containing surface-anchored sulfonic acid: Application in γ-globulin separation

Poly(2-hydroxyethyl methacrylate/ethylenglycol dimethacrylate), poly(HEMA/EGDMA) microspheres was prepared via suspension polymerization. After activation of the hydroxyl groups of poly(HEMA/EGDMA) by bromination, surface-initiated atom transfer radical polymerization (ATRP) of glycidylmethacrylate was conducted in dioxane/bipyridine mixture with CuBr as catalyst at 65 °C. The epoxy groups of the poly(glycidylmethacrylate) comb polymer were converted into sulfonic acid groups (as proton-exchange groups) with reaction of sodium sulfite. Synthesized microspheres were characterized by swelling studies, FT-IR spectroscopy, scanning electron microscopy (SEM) and elemental analysis. The microspheres were used as ion-exchange support for adsorption and purification of human γ-globulin (IgG). The maximum γ-globulin adsorption on the ion-exchange adsorbents was observed at between pH 5.0 and 6.0. The IgG adsorption onto the poly(HEMA/EGDMA) microspheres was negligible. The maximum amount of adsorbed γ-globulin was found to be 230.1 mg/g microspheres. The ion-exchange adsorbents allowed one-step separation of IgG from human plasma. The γ-globulin molecules could be repeatedly adsorbed and desorbed with this ion-exchange support without noticeable loss in their IgG adsorption capacity.     

Treatment of levafix orange textile dye solution by electrocoagulation

The decolorization of the levafix orange textile dye in aqueous solution by electrocoagulation using aluminum sacrificial anode has been investigated. The process performance is analyzed in terms of decolorization efficiency and the important cost-related parameters such as electrode and energy consumptions, as a function of initial pH, conductivity, current density, initial dye concentration and electrolysis time. The present study proves the effectiveness of electrochemical treatment for the textile dye solution. 95% decolorization efficiency may be obtained at suitable operating conditions such as; current density 100 A/m(2), operating time 12 min and initial pH 6.4. The corresponding electrode and energy consumptions during the electrolysis were found to be 1.8 kg Al/kg dye and 35 k Wh/kg dye.     

Preparation and characterization of strong cation exchange terpolymer resin as effective adsorbent for removal of disperse dyes

In this study, (hydroxypropylmethacrylate-co-ethyleneglycol dimethacrylate-co-glycidylmetharylate) terpolymer resin functionalized with sulfonic acid groups was prepared and used as cation exchange resin for removal of two different disperse dyes (i.e., Direct Red R [DR-R] and Disperse Violet 28 [DV-28]) from aqueous solution. The properties of the adsorbent were determined using Fourier transform infrared, dynamic light scattering, scanning electron microscopy, and Brunauer, Emmett, and Teller methods. The maximum adsorption capacity of the resin for the DR-R and DV-28 was found to be 86.1 and 179.6 mg/g, respectively. Desorption study was realized to evaluate the reusability of the resin and the percent desorption from the resin for DR-R and DV-28 dyes was found to be approximately 89.4% and 91.7%, respectively. The experimental data were evaluated using different kinetics and isotherm models. These results show that the experimental data could be designated with the second-order kinetic model and both Langmuir and Temkin isotherm models. Finally, the presented resin was able to remove large amounts of organic pollutants in a short process time with a low amount of adsorbent. Thus, it was shown that the prepared resin has high potential for use as an effective and sustainable adsorbent for the treatment of industrial wastewater. POLYM. ENG. SCI., 60:192–201, 2020. © 2019 Society of Plastics Engineers     

Adsorption of Congo Red dye by native amine and carboxyl modified biomass of <Emphasis Type="Italic">Funalia trogii</Emphasis>: Isotherms,kinetics and thermodynamics mechanisms

Native, iminodiacetic acid and triethylenetetraamine modified biomasses of Funalia trogii were used for removal of Congo Red dye (CRD) from aqueous medium. The native and modified fungal biomasses were characterized using ATR-FTIR, Zeta potential, contact angle studies and analytical methods. FTIR studies of the native and chemically modified adsorbent preparations show that amine, carboxyl and hydroxyl groups are involved in the adsorption of the model dye (i.e., Congo Red). The maximum adsorption of the CRD on the native, carboxyl and amine groups modified fungal biomasses was obtained at pH 5.0. The amount of adsorbed dye on the adsorbent samples increased as the initial concentration of CRD in the solution increased to 200mg/L. The adsorption capacities of native, carboxyl groups and amine modified fungal preparations were 90.4, 153.6 and 193.7mg/g dry adsorbents, respectively. The data was fitted well with the Langmuir isotherm model, and followed the pseudo-second-order equations. Thermodynamic parameters (ΔG ^o , ΔH ^o and ΔS ^o ) were also calculated. The results showed that triethylenetetraamine (TETA) modified biomass of F. trogii presented an excellent dye removal performance and can be used in various environmental applications such as various micro-pollutants removal from aqueous medium.     

Construction of consistent neural network empirical physical formulas for detector counts in neutron exit channel selection

Proper selection of neutron exit channels following heavy-ion reactions is important in nuclear structure physics. A knowledge of detector counts versus number of neutron interaction points per event can be useful in this selection. In this paper, we constructed layered feedforward neural networks (LFNNs) consistent empirical physical formulas (EPFs) to estimate the detector counts versus number of neutron interaction points per event. The LFNN-EPFs are of explicit mathematical functional form. Therefore, by various suitable operations of mathematical analysis, these LFNN-EPFs can be used to derivate further physical functions which might be potentially relevant to neutron exit channel selection.