Received: 17 August 2014 Revised: 19 September 2014 Accepted: 21 October 2014 Published online in Wiley Online Library: 2 December 2014
(wileyonlinelibrary.com) DOI 10.1002/xrs.2572
16
Graphene oxide-based solid phase extraction ofvitamin B12 from pharmaceutical formulationsand its determination by X-ray fluorescenceMorteza Moradi,* Soraya Zenouzi, Kamran Ahmadi and Ali Aghakhani
Correspondence to: Morteza Moradi, Department of Semiconductors, Materialsand Energy Research Center, Karaj, Iran. E-mail: [email protected]
Department of Semiconductors, Materials and Energy Research Center, Karaj, Iran
Introduction
Vitamin B12 (cobalamin) is an organic complex that contains a co-balt ion in its structure.[1] This vitamin is an important coenzymefor cell development and growth, and its deficiency leads to weak-ness, fatigue, nausea, constipation, weight loss, pernicious anemiaand nerve degeneration.[2] Peculiarly, vitamin B12 is essential forthe human diet, but cannot be synthesized by the body. This vita-min has to be obtained from natural sources such as fish, dairyproducts, egg, meat and poultry. However, compared to other vita-mins, the daily requirement of vitamin B12 is relatively low.[3] Thedetermination of vitamin B12 in human serum at picogram level be-comes necessary for the detection of its deficiency.[4] Hence, sensi-tive analytical detection devices are required. To counter thedeficiency of vitamin B12, many supplements are available in the formof tablets, capsules and injections. Methods for determination of vita-min B12 remain limited due to their low sensitivity and poor selectivity.Several methods have been so far applied for determination of
vitamin B12 including microbiological assay that uses Lactobacillusleichmannii (ATCC 7830) as the test organism,[5] radioisotopic dilu-tion assay,[6,7] high-performance liquid chromatography (HPLC)with different detection methods including UV detection,[8,9] elec-trochemical detection,[8] flame atomic absorption spectrometry(FAAS),[10] fluorometry,[11,12] inductively coupled plasmamass spec-trometry (ICP-MS)[13–15] and biosensor assay based on surface plas-mon resonance (SPR).[16] These conventional methods have theirown advantages, but at the same time, they have certain draw-backs such as being laborious, time consuming, tedious, less safe,too expensive and showing low sensitivity and selectivity. Otherdisadvantages of these methods have been mentioned in theliterature.[17] But there is no report about determination of vitaminB12 by using X-ray fluorescence (XRF).XRF analysis is a powerful analytical tool for the spectrochemical
determination of almost all the elements present in a sample. XRF
X-Ray Spectrom. 2015, 44, 16–23
radiation is inducedwhen photons of sufficiently high energy, emit-ted from an X-ray source, impinge on a material. These primaryX-rays undergo interaction processes with the analyte atoms. Thisallows the identification of the elements present in the analyteand the determination of their mass or concentration. Measure-ment of the spectrum of the emitted characteristic fluorescence ra-diation is performed using wavelength dispersive (WD) and energydispersive (ED) spectrometers. In principle, XRF analysis is a multiel-ement analytical technique and in particular, the simultaneous de-termination of all the detectable elements present in the sample isinherently possible with EDXRF. In WDXRF both the sequential andthe simultaneous detection modes are possible.[18]
New idea for analysis of organic compounds by XRFmethods ex-tends the applicability of this methodology in further studies. So far,only a few paper presented an indirect method for the determina-tion XRF determination of organic compound. Themethod is basedon the precipitation of an ion-associate complex formed betweenterazosin (as target analyte) and [Zn(SCN)4]
2� and the formationof a thin film on amembrane filter.[19] To the best of our knowledge,this is the first report about the application of the XRF for the deter-mination of vitamin B12 which have one cobalt atom in its structure.
XRF possesses a number of limitations when dealing with aque-ous samples, such as short linear range, the requirement of closelymatching standards to overcome matrix effects, bubbles releasedfrom solutions due to inadequate sample holder filling and heatingof the solution.[20] The extraction of analytes from a liquid onto asolid (SPE) is an important field in sample handling of elements
for their detection by XRF. The basic principle of such procedure isbased on transfer of analytes from the aqueous phase to the activesites of the adjacent solid phase. One of the clear trends in scienceand technology of the future is nanotechnology. Several sorbentshave been reported in the literature to preconcentrate metals priorto their determination by XRF techniques, such as ion-exchangematerials,[21] polyurethane foam (PUF),[22] filter discs,[23] activatedcarbon[24] and membrane filters.[25] Yamini et al.[26] reported deter-mining the nanogram per milliliter level of V, Cr, Mn, Fe, Co, Ni, Cuand Zn in water by XRF after using a silica gel powder. In anotherwork, the preconcentration of Co, Ni, Cu, Zn and Pb using grapheneoxide (GO) as solid sorbent without using chelating agent is pro-posed by Zawisza et al..[27] The proposed procedure is based on dis-persive solid-phase microextraction (DSPME). Some new efficientvariations of these methods and new techniques extending thepossibilities of XRF for liquid solutions analysis have been proposedin recent years. In 2010, Marguí et al. reviewed practical aspects re-lated to the use of extractive and non-extractive sample preparationof elements before their detection by XRF.[28] However, the interest inpreconcentration methods for XRF has increasingly turned towardsthe refinement of its modes for use in practical sample preparations.
In this research, GO are dispersed in aqueous samples, which pro-motes the immediate interaction between the vitamin B12 and GOand shortens the time of sample preparation in comparison with aclassical SPE. After the adsorption process, the GOwith adsorbed vi-tamin were collected onto a filter and measured directly using XRFspectrometry without the necessity of analyte elution.
17
Experimental
Chemicals and reagents
All reagents used were of analytical grade. Vitamin B12 and metha-nol were obtained from Sigma-Aldrich (St. Louis, MO, USA). Sulfuricacid (99.8%), hydrogen peroxide (H2O2, 30%), hydrochloric acid(HCl, 37%), acetonitrile (ACN), sodium chloride (NaCl), sodium hy-droxide and potassium permanganate (KMnO4) with the purityhigher than 99.9% were obtained from Merck Chemicals(Darmstadt, Germany). (Graphite powder was purchased fromSamchun Pure Chemical Co Ltd (Pyeongtaek, Korea). Ultra-pure wa-ter was prepared by use of an AquaMax-Ultra Youngling ultra-purewater-purification system (Dongan-gu, South Korea). Stock solu-tions (1000mg l�1) of the analyte were prepared by dissolving ap-propriate amounts of the compounds in deionized water. Theywere stored under refrigeration at 4 °C and were stable for at least3months. Working standard solutions were prepared daily by dilut-ing the stock standard solutions to the required concentrationswith ultra-pure water. The samples of multivitamin tablet, efferves-cent tablet and injection sample were purchased from local markets.
Apparatus
A wavelength-dispersive sequential X-ray spectrometer (8410, ARL,Australia) equipped by super-Q soft-ware for quantitative analysiswas used for measuring the Kα line of all elements. The measure-ment parameter was 2θ=52.80 for Co. Rh tube, 60 kV 50mA; LiF(200) crystal; 150-μmcollimator; 25%–75%windowwidth; countingtime f or peak andbackground, a duplex (flow+Xe-sealed) detectorfor the determination of Co. Prepared samples were characterizedusing X-ray powder diffraction (XRD, Philips X’pert diffractometerwith Cu Kα radiation (λ =0.154 nm) generated at 40 kV and 30mAwith a step size of 0.04° s�1) and Raman spectroscopy (Bruker,
Germany). The morphology of the GO was characterized bytransmission electron microscopy (TEM, Philips EM 208, TheNetherlands).
The pH values were measured using a WTW Inolab 720 pHmeter(Weilheim, Germany). During the extraction, the sample containingGO was stirred with a stirring speed of 1000 rpm by a heater-magnetic stirrer model 301 from Heidolph (Kelheim, Germany)using a 10.0mm×5.0mm magnetic bar.
Synthesis of graphene oxide
Graphene oxide (GO) synthesis was carried out via the modifiedHummer’s method.[29] Graphite (5.0 g) and NaNO3 (2.5 g) weremixed with 120ml of H2SO4 (95%) in a 500-ml flask. The mixturewas stirred for 30min within an ice bath. While maintaining vigor-ous stirring, KMnO4 (15 g) was added to the suspension. The rateof addition was carefully controlled to keep the reaction tempera-ture lower than 20 °C. The ice bath was then removed, and themix-ture was stirred at room temperature overnight. As the reactionprogresses, the mixture gradually became pasty, and the colorturned into light brownish. At the end, 150ml of H2O was slowlyadded to the pasty with vigorous agitation. The reaction tempera-ture was rapidly increased to 98 °C with effervescence, and thecolor changed to yellow. The diluted suspension was stirred at98 °C for one day. Then, 50ml of 30% H2O2 was added to the mix-ture. For purification, themixture was washed by rinsing and centri-fugation with 5% HCl and then deionized water for several times.After filtration and dried under vacuum, the GO was obtained as agray powder.
Sample preparation
For extraction and determination of vitamin B12 from multivitamintablet sample, one tablet was finely powdered and dissolved in50ml of deionized water. After filtering the solution, the superna-tant was transferred into a 100-ml volumetric flask and diluted tothe mark with deionized water. Finally, the extraction procedurewas followed under the optimum conditions for 80ml of this solu-tion. For extraction of vitamin B12 from effervescent tablet sample,each tablet was dissolved in 100ml of deionized water and after fil-tering and pH adjustment, extraction was accomplished under theoptimum conditions.
Extraction procedure
2.3ml of 1.0mgml-1 suspension of GO was added to 77.7ml ofaqueous sample. The pH of the solution was adjusted to 2. Next,the mixture was stirred by amagnetic stirrer for 10.5min. After that,the sample was collected onto the Millipore filter (cellulose esters,0.2-mmpore size) using a vacuum filtration assembly. Loaded filterswere placed between two 6.0-mm-thick Mylar X-ray foils (suppliedby Chemplex Industries, Inc., New Cork, USA) mounted in specialliquid sample holders which incorporate a snap-on ring at theend of the cell for attachment of thin-film supports. Afterwards,samples were sealed in the sample holder of the equipment forWDXRF analysis. The blank samplewas prepared using the describedprocedure and high purity water instead of the analyzed solution.
Optimization strategy
There are several factors like pH, sample volume, sorbent amountand extraction time that affect the extraction process. In order toobtain the optimum conditions for extraction of vitamin B12, effects
of sample pH on the extraction of analyte by the proposed methodwere optimized using one-variable-at-a-time (OVAT) process. InOVAT strategy we can only control one variable at a time and otherfactors are fixed. Optimization of the three other parameters on theextraction efficiency was performed using a multivariate optimiza-tion. The software package Design-Expert 8.0.6 trial version(Stat-Ease Inc., MN, USA) was used for experimental design, dataanalysis and response surfaces.The extraction recovery for solid phase extraction was expressed
as the percentage of total analyte amount, ns, initial (number ofmoles of the analyte amoun toriginally present in the sample) trans-ferred into the extraction phase at the end of the extraction, na, final(number of moles finally collected in the extraction phase) was cal-culated by the following equation:
R %ð Þ ¼ 100� na;final=na;initial� �
(1)
Results and discussion
Characterization of GO
Figure 1 shows the XRD patterns of natural graphite, and GO.Graphite exhibits a strong and sharp peak at 26.40 in Fig. 1(a), indi-cating a higher ordered structure, that corresponds to a basal spac-ing d (002) = 3.3Å. The pattern of GO, on the other hand, exhibits a001 reflection at 9.07°. The interlayer spacing of GO was calculatedto be 9.6Å. This value is higher than interlayer spacing of graphite(d-spacing=3.3 Å, 2Theta= 26.4°), due to the presence of oxygen-ated functional groups and intercalated water molecules.Raman spectroscopy, as a non-destructive technique, plays a crit-
ical role in characterization of graphene materials[30] and has beenemployed here to gain information about structure and defects ofthe GO sheets in the composite and the precursor phase. The Ra-man spectrum for the graphite and GO is presented in Fig. 1B.Two intense bands are clearly seen in GO sample at 1355 (D-band)and 1581 cm�1 (G-band), respectively. The former peak is called Dband, which is activated once the defects are introduced into sp2
hybridized carbon networks, and the intensity of D band is pro-portional to the defects concentration. Thus the strong D bandintensity indicates the existence of large amount of defects insp2-carbon-based materials. The D-band is associated with in-plane bond stretching motion of the pairs of C sp2 atoms (theE2g phonons) and shows defects of the sp2 domain, while theG-band is related to breathing modes of rings or κ-point pho-nons of A1g symmetry.[31]
Figure 1C displays the typical TEM image of the synthesized GOthat represent a layered and sheet-like structure with the large sur-face and wrinkled edge. These results indicate a good exfoliation ofgraphite during the oxidation process.
Optimization
Influence of the sample pH
It is well known that pH of sample solution is one of the importantfactors affecting the extraction efficiency of ionizable compounds;thus, pH of sample solution was optimized separately using OVATmethod. According to the literature, GO can be considered as a ma-terial with a negative surface charge due to its acidic groups,[32] so acationic analyte can be adsorbed onto it. The ionization plot (Fig. 2)shows the relationship between pH and the relative quantities ofeach species of the compound.[33] Thus, vitamin B12 can be consid-ered as a three-cationic at pH=1.0 to 5.0, theoretically. In fact, vita-min B12 has different forms, and the percentage of each form isaffected by pH (some cationic and anionic forms). Therefore, atlow acidic pH, vitamin B12 molecules can be adsorbed onto thenegative surface of the GO whereas they cannot be adsorbed onto the GO at higher pHs due to the repulsion between negativecharge of phosphate group onto vitamin B12 molecule and adsor-bent surface. The influence o f acidic pHs (1.0 – 5.0) on the extrac-tion efficiency was investigated. It was thus deduced that pH=2is suitable for extraction (Fig. 3).
Multivariate optimization
In the next step, a multivariate optimization was applied tooptimize the three factors (sample volume, sorbent amountand extraction time). Multivariate optimization procedures in-volve simultaneous alteration of all experimental factors studiedaccording to an experimental design. Experimental designs areused to plan the experiments in such a way that a maximum ex-traction recovery is gained from a minimum number of experi-ments. The best experimental designs for the purpose ofmodeling and optimization are the response surface designs.Having a careful design and experiments analysis, it seeks to re-late a response (or output) variable to the levels of a number ofpredictor (or input) variables. The input variables are some-times called independent variables, and the performance mea-sure or quality characteristic is the response. Basically, thisoptimization process involves three major steps: performingthe statistically designed experiments, estimating the coeffi-cients in a mathematical model and consequently predicting
Figure 2. Ioniziation plot of vitamin B12. Purple circle is positive charge and green circle is negative.
Figure 3. The effect of pH on the extraction efficiency of vitamin B12.
Sample preparation
19
the response and checking the adequacy of the model. Usingthe mathematical model, the levels of the variables giving max-imum response can then be calculated. In the present work, inorder to investigate the interaction between variables a Box–Behnken design (BBD) was performed which is a response sur-face methodology (RSM) based on a highly fractionalizedthree-level factorial design. The number of experiments sug-gested by this is calculated according to the equation 2 K(K� 1) + Co, where K is the number of variables and Co is thenumber of center points.[34] In this study, K and Co were set at3 and 4, respectively, which meant 16 experiments had to bedone. The results of the BBD are presented in Table 1. This de-sign is suitable for exploration of quadratic response surface
and construction of a second-order polynomial model whichcan be expressed as the following equation:
Y ¼ b0 þ ∑biXi þ ∑biiX2i þ ∑bijXiXj (2)
where, Y is the response variable (cps), bo is an intercept, bi, biiand bij are constant regression coefficients of the model and Xi,Xj (i = 1,3; j = 1,3 and i ≠ j) represent the coded level of an inde-pendent variable. The values of the coefficients Xi and Xj are re-lated to the effect of these variables on the response.Coefficients with more than 1 factor term and those withhigher order terms represent interaction terms and quadraticrelationship, respectively. It is worthy to note that the re-sponses in Table 1 were count per second (cps). As usual inBBD optimization, each factor has three levels in: upper (+1),central (0) and lower points (�1). For simplicity the three levelshave shown in coded number. For example in sorbent volumein Table 1: �1 is 1.0 mg, 0 is 2.0 mg and +1 is 3.0mg. As shownin Table 1, both of coded and un-coded value of each men-tioned parameters in 16 experiment runs have shown. Also inlast column of Table 1, cps of each run is represented.
Analysis of variance (ANOVA) is the most efficient parametricmethod available for the analysis of data from experiments. It wasdevised originally to test the differences between several differentgroups of treatments thus circumventing the problem of makingmultiple comparisons between the group means using t-tests.The F value can be used to determine the significance of individualparameters in a model. The ANOVA result showed that the F valueof 27.70 is significant, and there is only 0.03% likelihood that largemodel F value could occur by chance. Values of p (Prob> F) less
Table 1. Box–Behnken response surface design and responses value
Run X1 X2 X3 Sorbent amount (mg) Sample volume (ml) Extraction time (min) cps
1 �1 �1 0 1.0 50.0 10.0 1.84
2 1 �1 0 3.0 50.0 10.0 3.32
3(C) 0 0 0 2.0 75.0 10.0 4.02
4 1 0 1 3.0 75.0 15.0 3.50
5(C) 0 0 0 2.0 75.0 10.0 3.95
6 0 1 1 2.0 100.0 15.0 3.21
7 1 0 �1 3.0 75.0 5.0 2.88
8 0 �1 1 2.0 50.0 15.0 2.03
9(C) 0 0 0 2.0 75.0 10.0 3.91
10 �1 0 1 1.0 75.0 15.0 1.96
11 �1 0 �1 1.0 75.0 5.0 2.07
12 0 �1 �1 2.0 50.0 5.0 2.11
13 1 1 0 3.0 100.0 10.0 3.02
14(C) 0 0 0 2.0 75.0 10.0 4.10
15 0 1 �1 2.0 100.0 5.0 2.55
16 �1 1 0 1.0 100.0 10.0 2.51
(C)Center point
Figure 4. Goodness-of-fit of empirical model.
M. Moradi et al.
20
than 0.0500 indicate model terms are significant. It was also shownthat GO amount (p=0.0002), sample volume (p=0.0117) and theinteractions between GO amount and sample volume (p=0.0485)have a significant effect upon the extraction.As can be seen, all of the quadratic components of have the sig-
nificant effect (p< 0.0001) on the extraction efficiency and the re-lated RSM behavior agrees with the literature.[35] Quadraticcomponent is a non-linear relation between factors and response.The effect of quadratic components is very complicated, and upto now the reasons of their effect are not clear.The response equation fitted the experimental data with R2 of
0.9765, indicating 97.65% of the variability in the response. Thegoodness-of-fit of the model to the experimental data shown inFig. 4 has an adjusted R2-value of 0.9412. According to Joglekarand May,[36] R2 should be at least 0.80 for a good fit of a model.As is observed, the coefficient of determination, R2, was more than0.80 whichmeans that the obtained equation is adequate for corre-lating the experimental results. In this figure, red color is related tohigher cps and blue is related to lower cps. Plotting predicted
values versus experimental values in Fig. 4 also shows that all ofthe predicted values of RSM model are located in close proximityto the experimental values. In other words, the relation betweenthe actual responses of each 16 design runs and predicted response(using Eqn (2)) is presented. It can be seen actual data in each pointis near to predicted one. This supports the hypothesis that themodel equation, Eqn (2), is sufficient to describe the response.
Three-dimensional response surface curves were plotted tostudy the interaction between the two factors selected and to de-termine the optimum conditions for the maximum cps (Fig. 5).The codedmodel was used to generate 3-D diagram and a contourplot of calculated response surface from the interaction betweenvolume of sorbent amount–sample volume, sorbent amount–extraction time and sample volume–extraction time (Fig. 5A–C, re-spectively) as a function of the three variables with the other pa-rameter being at its constant level. The optimal values of variablesare obtained when moving along the major and minor axis of theellipse and the response at the center point results in maximum re-covery. According to Fig. 5A, the recovery increases first and thenslightly decreases by increasing the amount of sorbent. Comparedto traditional SPE sorbents, nanoparticle sorbents have large sur-face area and high adsorption efficiency; therefore, satisfactory re-sults can be achieved by using lower amount of GO sorbents. Forinvestigating the optimum amount of the adsorbent, differentamounts of the adsorbent (1.0–3.0mg) were applied to extract ofvitamin B12 from the sample, and 2.3mg of the GO was sufficientf or extraction of the vitamin B12.
The effect of sample volume on the extraction efficiency wasstudied by extraction of the analyte from 50 to 100ml of water sam-ples. The most extraction efficiency of the target analyte was ob-tained when sample volume was 80ml (Fig. 5A, B). Highervolumes could not be processed as the amount of the sorbent involume unit of the sample decreased due to the high dispersionof the sorbent in the aqueous media. Therefore, access of analyteto the sorbent surface became more difficult. Hence, sample vol-ume of 80ml was selected for subsequent experiments.
The extraction time profiles were studied by varying the extrac-tion time in the range of 5–15min. Due to the shorter diffusionroute for GO, extraction of target analyte can be achieved in shorter
time even for larger volumes of samples. The results are presentedin Fig. 5B, C. It is found that the extraction of elements is maximizedwhen the stirring time is more than 11min. So stirring of the solu-tion was done for 11min at subsequent analysis.
Quantitative analysis
According to the overall results of the optimization study, the fol-lowing experimental conditions were chosen: sorbent amount,2.3mg; sample volume, 80ml and extraction time, 11min. In orderto proceed with the current evaluation of the proposed extractiontechnique, linearity, LOD, enhancement factor (EF) and repeatabilitywere investigated under optimized conditions with the standardsolutions of the analyte. The performance of the developed proce-dure is summarized in Table 2. Calibration curve was plotted using10 spiking levels of vitamin B12 over a range between 10 and1000μg l�1 and analyzing each level in triplicates. Good linearityof response (LDR) was observed in the range of 25–1000μg l�1 witha correlation of determination more than 0.998. Figure 6 showsthese calibration curves with their equation. It can be seen that itis linear. The LOD was obtained from the formula CLOD=3Sb/m,where Sb is the standard deviation of ten replicates of blank mea-surements and m is the slope of the calibration curve. Also, EF, cal-culated as the ratio of slopes of the calibration curve afterpreconcentration of the analyte and direct calibration equation,was obtained 46. Precision of the method (RSD%) was found tobe less than 8.1% based on four-replicate analysis during 1day ata concentration of 100μg l�1.
A comparison between the figures of merit of the proposedmethod and some published methods for extraction and
Table 2. Figures of merit of the proposed extraction method forvitamin B12
determination of vitamin B12 is summarized in Table 3. Clearly,the proposed method has a good sensitivity and precision with asuitable dynamic linear range. Also, the obtained LODs for the ana-lyte by the present method with sample volume of 80ml are com-parable with those obtained by other methods. All of the resultsreveal that the new developed method is not only a good samplepreconcentration technique, but also an excellent sample clean-up procedure that can be used for trace analysis of vitamin B12 withXRF. Also, the proposed GO-based SPE has some advantages incomparison with other applied extraction methods such as SPE, in-cluding lower consumption of adsorbent and organic solvents andshorter extraction times.
Analysis of real samples
In order to evaluate the applicability of the developed extractionmethod to analysis of the vitamin B12 in the real samples with com-plex matrices, three selected pharmaceutical formulations were ex-tracted and analyzed using the proposed method under theoptimum conditions. Sample preparation for the real samples wasperformed according to Section 2.4. The results of extraction of vi-tamin B12 from multivitamin tablet, effervescent tablet and injec-tion samples are tabulated in Table 4. Results showed thatvitamin B12 was present in the analyzed multivitamin and
effervescent tablets with concentration of 6.6 and 4.9μg per eachtablet, respectively. Also, themethodwas tested for extraction of vi-tamin from an injection sample containing mixture of three vita-mins of B1, B6 and B12 (containing 333mg l�1 of vitamin B12). Forthis purpose, 200μl of the injection sample was diluted to 80mlwith deionized water. According to Table 4, the results obtainedby the current method agreed well with the labeled values of vita-min B12 for multivitamin tablet, effervescent tablet and injectionsample. The RSD (%) were in the ranges of 3.8–7.5%. As we know,recovery (R%) in extraction methods represents the amount ofextracted analyte from sample to extraction phase. To determina-tion of R%, we can use add-foundmanner, so that a known concen-tration of analyte was added into sample and after extraction usingproposed technique, the amount of extracted analyte wasdetermined. If the recovery of added amount is in the range of90–110%, the proposed method is validated. As can be seen inTable 4, recovery values of real samples are in the range of 93 to106%; thus, proposed extraction method prior to XRF analysis issuitable method for vitamin B12 determination.
Conclusions
Liquid samples usually provide a high X-ray scatter backgroundresulting in poor signal-to-noise ratio. To overcome this prob-lem, many different chemical and physical preconcentrationtechniques have been proposed prior to XRF analysis. Theextraction of vitamin B12, which contains a cobalt atom in themolecule, from a liquid onto a graphene oxide is a new idea
for in sample handling of metal-organic compounds for their de-tection by XRF. The results further demonstrated that the pro-posed GO-based extraction method has good precision,linearity, and accuracy over the investigated concentrationrange. Also, the proposed method offers a simple, fast, sensitiveand selective method for extraction and determination of vita-min B12. Furthermore, there is a possibility of extraction of vita-min B12 from large volumes of sample and therefore samplediluting and decrease of matrix effects are possible.
Acknowledgements
The authors are grateful for the financial support of this work fromthe Iran National Science Foundation (INSF) (Tehran, Iran).
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