Size selectivity curves

FIGURE 4.15 Types of size selectivity curves. Taken from Klumpar et al. [25, pp. 17-19]. 

The effects of bypass on size selectivity are shown in Figure 4.15. Bypass reporting to the fine stream changes curve b to curve c. Bj ass reporting to the coarse stream moves from curve b to curve c. Comminution of the particles in a classifier will give rise to a size selectivity curve such as d. 

FIGURE 4.18 (Continued) (c) Predicted particle volume fraction for 35% weight CaCOs powder in a 75-mm hydrocyclone, (d) Experimental and predicted size selectivity curves for 35% weight CaCOg powder in a 75-mm hydrocyclone (the interactions correspond to viscosity corrections made for the particle volume fraction distribuiuBi within the hydrocyclone). From Rcgamani and Mifai [48]. 

FIGURE 2.2 Selectivity curve of Superdex 7S, HR 10/30, as compared to a hypothetical single pore-size support. , experimental data from dextran fractions calculated for a SEC medium having a single pore radius of 60 A. [Reproduced from Hagel (1996), with permission.]... 

Figure 5. The influence of the Ru particles size on the hydrocarbon selectivities Curve 1, distribution for a mean-particle size of 1.5 nm Curve 2, distribution for a mean-particle size of 10 nm initial pressure, 20 bar HJCO = 4/1 reaction temperature,200°C...

Fig. 5. Library size and diversity can be explored in a single run using the MoSELECT program. The family of solutions found is shown by the solid squares and is superimposed on the SELECT curve repeated from Fig. 4.

Figure 4.18 Upper right figure shows a forced-draft or blowthrough tower, which has a fan at the bottom for driving air through the fill above, Tower selection for smaller units can be made from the accompanying curves and table for a cold water temperature of 85°F (this is generally the water basin discharge temperature for small towers). As an example, enter at 104°F hot water temperature to a wet bulb value of 75°F, then drop vertically to the water flow selected (580 gpm). This falls between curves that designate the manufacturer s distinct model size. Select the next larger size, i,e., the curve immediately below, and follow across to the recommended tower model).

Selectivity of a typical classifier is plotted as a function of size in Figure 4.15. Selectivity monotonically increases from 0 to 1 as size increases (Curve 6-6 ). Even thou size selectivity is a complete measure of classifier performance, the user is often required to take a shortcut method of expressing performance on a specific feed material. A practical measurement of overall classification performance for a given application can be obtained by calculating recovery and 3rield. Recovery is the relative amount of material in the feed that is finer than size d that is recovered in the product. Recovery, R(d expressed... 

Discrete data point, extracted irom the log file, can be viewed. The data can also be viewed in tabular form and as a size distribution curve. Data can also be integrated over any selected range. A Statistical Process Control (SPC) option enables the file data to be viewed in standard control chart format either as an X or R chart. 

Malvern (Insitec) ECPS2 is designed to monitor and control particle size distributions from 0.5 to 1,500 pm, at concentrations up to 10,000 ppm, directly in pneumatic powder flow streams. Up to one thousand size distribution measurements per second are carried out at flow velocities from static to ultrasonic. Discrete data point, extracted from the log file, can be viewed. The data can also be viewed in tabular form and as a size distribution curve. Data can also be integrated over any selected range. A Statistical Process Control (SPC) option enables the file data to be viewed in standard control chart format either as an X or R chart. Various interface arrangements have been described, [203] ... 

Cs+ selectivity can be controlled by varying the density of sites within catalyst pellets and the diameter of these pellets. The density of sites determines the reactant requirements and the pellet size controls the required path length of diffusing molecules. Such modifications affect the value of x, causing the performance of these catalysts to move along the curve in Fig. 20. The shape of the selectivity curve, however, depends only on the intrinsic readsorption rate constant (/Sr) and on the kinetic dependence of chain growth pathways on reactant pressure. 

Fig. 8 Determination of the size selectivity, m, from the calibration curve of a polyelectrolyte with different peak masses MP. m corresponds to the slope of the tangent at the inflection point...

Fig. 15 Trend in the size selectivity, m, (1st derivative of the calibration curve) for different dextrans. The numerical values represent the molecular mass with the highest size selectivity...

Figure 14.4. Selectivity curve from SEC of DNA ( ) and protein ( ) molecular weight standards on a 106 x 10 mm Superose 6 gel filtration column with 0.02 M Tris-HCl pH 7.6 containing 0.15 M NaCl as the eluent.4 [Reprinted, with permission, from H. Ellegren and T. Laas, Journal of Chromatography 467, 1989, 217-226. Size - Exclusion Chromatography of DNA Restriction Fragments. Fragment Length Determinations and a Comparison with the Behaviour of Proteins in Size-Exclusion Chromatography . 1989 Elsevier Science Publishers B.V.]...

The adsorption of gas mixtures has been extensively studied. For example, Wendland et al. [64] applied the Bom—Green—Yvon approach using a coarse grained density to study the adsorption of subcritical Lennard-Jones fluids. In a subsequent paper, they tested their equations with simulated adsorption isotherms of several model mixtures [65]. They compared the adsorption of model gases with an equal molecular size but different adsorption potentials. They discussed the stmcture of the adsorbed phase, adsorption isotherms, and selectivity curves. Based on the vacancy solution theory [66], Nguyen and Do [67] developed a new technique for predicting the multicomponent adsorption equihbria of supercritical fluids in microporous carbons. They concluded that the degree of adsorption enhancement, due to the proximity of the pore... 

To operate EQPS on an EQ6 calculated reaction path, the user selects the boundary constraints affecting a process (open vs. closed system, isotopic equilibrium or disequilibrium between redox subsets, and precipitation pathway accompanying redox reactions), inputs initial solution or system reactant(s) composition(s), and specifies an input file generated from an EQ6 run. The EQ6 data consists of solution composition and mineral amounts at discrete points on a reaction pathway. EQPS can either be set to calculate at the points produced by EQ6, or use a curve crawler technique to produce pseudo-continuous isotopic pathways at user definable granularity. Accuracy of either computational procedure depends most on the step size executed by EQ6 and only slightly on the step size selected during the... 

The calculated A. and < ) for the selected curves are sumarized in Table 12. The index n in (t indicates the length of the chain (or the size of the D/D matrix). We see that as n increases, (]) decreases, as expected. A comparison of different curves again gives plausible results. Among the fractals considered the Koch curve appears the least... 

Figure 22.6. PL spectra of a non-size-selected sample after different successive treatments after passivation in air for two months (thick solid curve), after exposure to HF vapor for 40 min (grey thin and dotted curves), after reexposure to air for 1 h (black thin and dashed curves), and after continued exposure to air for 2 d (dash-dotted curve). The sketch in the upper part of the figure illustrates the effect of the various treatments on the core and oxide shell of the nanoparticles (schematic).

The selection of any NDT method for a particular inspection will be due to some extent on the probability of detection (POD) for that method. The POD is a measure of the reliability of the method to detect a particular type of flaw size [13,14]. POD curves are created from empirical studies to show the reliability of a method for detection of features or defects. A useful curve for PODs is a 90% POD with 95% confidence, referred to as a 90/95 POD. Figure 15.8 is a notional POD curve that shows how one method may perform more reliably than another for the detection of particular flaw sizes. POD curves can be expensive to develop experimentally because they require test samples with known defect sizes and numerous inspection tests by different operators to develop credible statistics. Model-assisted-based methods are being developed to reduce this burden [15]. 

The responses were selected among the physical variables used to monitor the porosity of the materials, i.e., maximum of the pore size distribution curve (Z>p mode), mean pore diameter (Dp mean), total pore volume ( Fp), specific surface area (Sp). The slope of the backpressure vs. flow rate curve was also chosen in order to monitor the chromatographic performance of the materials. 

For the following study we prepared a size-selected sample with an average size of d) = 3.6 nm and a rather narrow size distribution with a full width at half maximum (FWHM) of Ad = 0.6 nm. The freshly prepared sample was transferred under vacuum into the analysis chamber, where we tried to measure a PL spectmm. However, no PL could be detected unless we exposed the sample for some time to air (under normal conditions). After 20 min, some rather weak photoluminescence could be observed. The maximum position of the corresponding PL curve was at 1.72 eV. This PL curve and the following results are displayed in Fig. 3. With increasing time of exposure to air, the PL became more intense and the PL peak position further shifted to the blue. After one day, the maximum position had already experienced a shift to 1.85 eV. At later times, the effect became smaller and seemed to go into saturation. Finally, after 25 days, the maximum position was found at 1.87 eV. 

---