Fiber-sample partition coefficient

Figure 3 Microextraction with SPME. Vf, volume of fiber coating Kfs, fiber/sample partition coefficient I4. volume of sample Co, initial concentration of analyte in the sample.

Calculate the fiber-sample partition coefficient (Afs) from the following equation ... 

Following the procedure listed in Section 29.2.8, determine fiber-sample partition coefficients (A )... 

AHjs can be calculated from the thermodynamic relationship between temperature and fiber-sample partition coefficients (Ku),... 

Hie determination of fiber-sample partition coefficients (Kis) is important to estimate the sensitivity of SPME extraction. 

The chemical mixtures composed of 32 probe compounds were prepared in aqueous solutions. The partition coefficients of chemicals were determined by PDMS membrane-coated fibers. The partition coefficient can be obtained by equilibrium or regression methods. In the equilibrium method, the absorption amount n° is determined at a predetermined equilibrium time. The partition coefficient of a chemical can be calculated from the equilibrium absorption amount n° and the initial concentration Q (Xia et al., 2003). The equilibrium absorption amount n° can also be obtained by regression of the absorption data sampled before the equilibrium with a kinetic model. The absorption experiment time can be reduced considerably with the regression method (Xia et al., 2004). 

In headspace SPME a three-phase equilibrium system—the liquid, the headspace, and the fiber coating—is present in the sampling vial. Each equilibrium is governed by a partition coefficient the coating-headspace partition coefficient [Kf, headspace-sample partition coefficient (/Tfc) and coating-sample partition coefficient (/Q. The total mass of an analyte after equilibrium is distributed among the three phases ... 

In regard to the potential effects of silicone membrane or film thickness (e.g., polydimethylsiloxane [PDMS]) on partition coefficients, Paschke and Popp (2003) have shown that that at equilibrium an SPME fiber with a 7 xm thick film of PDMS had about a 6-fold higher ATpw than a similar fiber with a 100 xm thick film. However, this could be the result of interactions with the silica core. Recent research (Smedes, 2004) has shown that silicone sheeting with PRCs can be employed for water sampling with good results. 

SPME is a sample-preparation technique based on absorption that is useful for extraction and concentration of analytes either by submersion in a liquid phase or exposure to a gaseous phase (Belardi and Pawliszyn, 1989 Arthur et al., 1992). Following exposure of the fiber to the sample, absorbed analytes can be thermally desorbed in a conventional GC injection port. The fiber behaves as a liquid solvent that selectively extracts analytes, with more polar fibers having a greater affinity for polar analytes. Headspace extraction from equilibrium is based on partition coefficients of individual compounds between the food and headspace and between the headspace and the fiber coat-... 

The sample volume also has an effect on both the rate and recovery in SPME extractions, as determined by extraction kinetics and by analyte partition coefficients. The sensitivity of a SPME method is proportional to n, the number of moles of analyte recovered from the sample. As the sample volume (Vs) increases, analyte recovery increases until Vs becomes much larger than the product of K, the distribution constant of the analyte, and Vf, the volume of the fiber coating (i.e., analyte recovery stops increasing when KfeVf Vs) [41]. For this reason, in very dilute samples, larger sample volume results in slower kinetics and higher analyte recovery. 

Solid phase micro-extraction (SPME) allows isolation and concentration of volatile components rapidly and easily without the use of a solvent. These techniques are independent of the form of the matrix liquids, solids and gases can be sampled quite readily. SPME is an equilibrium technique and accurate quantification requires that the extraction conditions be controlled carefully. Each chemical component will behave differently depending on its polarity, volatility, organic/water partition coefficient, volume of the sample and headspace, speed of agitation, pH of the solution and temperature of the sample (Harmon, 2002). The techniques involve the use of an inert fiber coated with an absorbant, which govern its properties. Volatile components are adsorbed onto a suitable SPME fiber (which are usually discriminative for a range of volatile components), desorbed in the injection chamber and separated by a suitable GC column. To use this method effectively, it is important to be familiar with the factors that influence recovery of the volatiles (Reineccius, 2002). 

The method is different from conventional SPE in that SPE isolates the majority of the analyte from a sample (> 90%) but only injects about 1 to 2% of the sample onto the GC. Solid-phase microextraction isolates a much smaller quantity of analyte (2-20%), but all of that sample is injected into the GC. The extraction efficiency of the fiber is a combination of extraction time, the thickness of the stationary phase, and the magnitude of the partition coefficient for the stationary phase. 

SPME is a multiphase equilibrium technique and, therefore, the analytes are not completely extracted from the matrix. Nevertheless, the method is useful for quantitative work and excellent precision and Unearity have been demonstrated. An extraction is complete when the concentration of analytes has reached distribution equilibrium between the sample and coating. This means that once the equihbrium is achieved, the amount extracted is independent of further increase in extraction time. If extraction is terminated before the equihbrium is reached, good precision and reproducibihty is still obtained if incubation temperature, sample agitation, sample pH and ionic strength, sample and headspace volume, extraction and desorption time are kept constant. The theory of the thermodynamic, kinetic and mass transfer processes underlying direct immersion and HS-SPME has been extensively discussed by Pawhszyn [2]. The sensitivity and time required to reach adsorption equilibriiun depends on the partition coefficients between the fiber and the analytes, and the thickness of the phase. Limits of detection and quantitation are often below 1 ppb. 

SPE dominates in extraction of pesticides from water samples and it represents presumably the most flexible technique for clean-up of food extracts. SPME and SBSE use a fused-silica fiber or a stir bar, respectively, coated by a sorptive material (usually polydimethylsiloxane, PDMS, or its modifications) for partition (i.e., not complete isolation) of analytes. These techniques are convenient and fast however, their application in quantitative MMRMs for analysis of pesticides in complex food samples is rather limited. The main disadvantages relate to strong matrix effects (matrix-dependent partition of analytes and deterioration of the coating by irreversible adsorbed matrix components), insufficiently wide polarity range to extract diverse pesticide residues, and variability of method sensitivity for different analytes depending on their partition coefficients. 

Deterniination of Fiber-Headspace (Aa) and Fiber-Sample (A/, Partition Coefficient and Extraction Efficiency (%)... 

Pawliszyn, 1995). In SPME, a phase-coated fiber housed within a syringe is exposed to the sample medium (water or air), allowing the analytes to be adsorbed on the fiber coating. For organic compounds having high partition coefficients, adsorption equilibrium can be attained within minutes. After sample adsorption, the fiber is withdrawn into the needle, which is then inserted into the heated injection port of the GC. The adsorbed analytes are thermally desorbed and analysis proceeds in the same manner as in normal GC/MS analysis. 

In SPME, the sample volume is chosen on the basis of the analyte partition coefficient between the sample matrix and the fiber coating. PawUszyn has described this in detail (73). The limiting sample volume can be estimated on the basis of the error of measurement E by... 

---