Quantitative Ultrasound-Assisted Extraction for Trace-Metal

In the Laboratory

Quantitative Ultrasound-Assisted Extraction for Trace-Metal Determination: An Experiment for Analytical Chemistry Isela Lavilla,* Marta Costas, Francisco Pena-Pereira, Sandra Gil, and Carlos Bendicho Departamento de Química Analítica y Alimentaria, Universidad de Vigo, As Lagoas-Marcosende s/n, 36310 Vigo, Spain *[email protected]

An advanced laboratory experiment with emphasis on sample preparation for a third-year analytical chemistry course is described. Upper-level analytical chemistry students are introduced to ultrasound-assisted extraction (UAE) for trace analysis by electrothermal atomic absorption spectrometry (ETAAS). This topic can be successfully accomplished by students who have experience in instrumental analysis, especially ETAAS for trace-metal determination. This experiment requires three class periods (a total of 12 h) with students working in groups of four. The structure of this experiment is flexible, allowing modifications and reductions in time by the instructor. This experiment can be used as an introduction to analytical research. Microwave-assisted digestion has conventionally been used for sample decomposition prior to trace-metal determination by ETAAS, as described by Spudich et al. (1). However, UAE has received increased attention over the past few years owing to its inherent safety, simplicity and reliability. The extraction of some trace metals was first reported by Miller-Ihli while working with ultrasonic slurry sampling combined with ETAAS (2). Since then, numerous researchers have focused their efforts toward the quantitative extraction of different metals. Two aspects are critical for obtaining quantitative extraction with UAE: (i) the analyte-matrix interaction and (ii) the ability of the ultrasonic processor to dissipate energy (3). The phenomenon of cavitation (formation, growth, and collapse of very small bubbles) is responsible for analyte extraction. Cavitational collapse on the surface of a solid particle causes a microstream of solvent to impinge on the surface. The result is particle rupture (i.e., disruption) and an increase in surface area for reaction. As a consequence, the analyte is extracted from the solid sample into the liquid media, from which the analyte concentration is determined (3). The systems used most often for extraction purposes are bath and probe-type sonicators. The power of most commercial ultrasonic baths is not always sufficient for quantitative extraction of analytes bound to a matrix. Cavitation within the extraction vessel placed inside the ultrasound bath is rarely achieved. In general, probe-type sonicators have a 100-fold greater mean power than baths, so a better performance in extraction is obtained. In addition, the probe is introduced directly into the extraction vessel, thus, ensuring that cavitation takes place (3). The introduction of liquid extract into the instrument (i.e., spectrometer), with only part of the sample matrix, permits an easy adaptation to various atomic techniques such as ETAAS (4), flame atomic absorption spectrometry (FAAS) (5), and inductively coupled plasma-optical emission spectrometry (ICPOES) (6). Hydride generation atomic absorption spectrometry 480

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Figure 1. Schematic representation of the ultrasound probe inside the autosampler cup.

(HG-AAS) (7) and inductively coupled plasma-mass spectrometry (ICP-MS) (6) can be used with more difficulty. Among these techniques, ETAAS is the most widely used. The extraction can be made with a probe directly introduced into an autosampler cup (Figure 1). The solid sample is usually weighed in the cup and a volume of a diluted acid solution is added as extractant solution. The resulting slurry is subjected to ultrasonic treatment. The cup is placed in the spectrometer autosampler (stirring is not necessary), and then a small volume, few microliters, of the supernatant is introduced into the graphite furnace. Aqueous standards are commonly used for calibration (4). To develop an UAE procedure, the characterization of variables influencing the extraction process such as sonication time, ultrasound amplitude, acid concentration, particle size, and sample mass is necessary (3, 4). Experiment Though many experiments related with UAE can be carried out in the laboratory based on an extensive list of scientific papers (8-13), we proposed the determination of nickel in biological tissues

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Vol. 88 No. 4 April 2011 pubs.acs.org/jchemeduc r 2011 American Chemical Society and Division of Chemical Education, Inc. 10.1021/ed1005147 Published on Web 01/24/2011

In the Laboratory

Figure 2. Procedure used for determination of Ni in seafood by UAE-ETAAS.

by ETAAS using a probe system (14, 15). Nickel is present in seafood and easily determined by ETAAS. In general, seafood can concentrate Ni with unfortunate effects on humans (Ni compounds are considered carcinogenic). FDA guidance documents establish Ni levels relating to safety attributes of seafood (16). A scheme describing the experimental procedure is shown in Figure 2; the values of variables were established by a previous optimization. An ultrasonic processor (VC Sonics and Materials, Dambury, CT) equipped with a titanium tip (suitable for a volume of 1.5 mL) was used for extraction purposes. The experimental variables, acid concentration, sample mass, particle size, sonication time, and sonication amplitude, were optimized by the students. A univariate optimization was carried out in this work, but a multivariate optimization can be used as an alternative (14, 15). An atomic absorption spectrometer (Unicam Solaar 939, Cambridge, U.K.) equipped with a graphite furnace and deuterium background corrector was employed for the measurements; a Ni hollow cathode lamp was used as radiation source; pyrolytically coated graphite tubes were used throughout the work. The optimization of the temperature program for atomization of nickel was made by students on the basis of the recommended conditions supplied by the manufacturer. A matrix modifier was not necessary. Aqueous standards were prepared by the students for calibration purposes. Reagents were ultrapure water, nitric acid (Merck, Darmstadt, Germany), and stock standard solution of Ni (1000 mg L-1) (Merck). All chemicals were analytical-reagent grade. Different samples of fish and shellfish were purchased from local markets.

r 2011 American Chemical Society and Division of Chemical Education, Inc.

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Only the edible part of seafood was taken for Ni determination. Certified reference materials (CRMs) were used for method validation (TORT-2, lobster hepatopancreas, and DORM-3, dogfish muscle, from the National Research Council of Canada and SRM 2977, mussel tissue, from the National Institute of Standards and Technology, USA). The use of CRMs was especially useful for students to critically assess their experimental results. Other specific details regarding the experimental procedure can be found in the supporting information. Hazards Concentrated nitric acid may be fatal if swallowed or inhaled, is extremely corrosive, and skin or eye contact may cause severe burns and permanent harm. Nickel dermatitis and respiratory effects have been reported in humans from chronic exposure to nickel. The EPA has classified nickel refinery dust and nickel subsulfide as Group A (human carcinogens) and nickel carbonyl as a Group B2 (probable human carcinogen). Laboratory coats, goggles, and gloves are mandatory for personal protection. The instrument manufacturer safety practices and recommendations should be followed carefully. Exhaust venting of gases is necessary. All compressed gases are hazardous because of high pressures inside the cylinders. Argon, an inert gas, is nontoxic and does not burn or explode. Results Students obtained ashing and atomization curves using the supernatant from the sonication of mussel tissue slurry. These

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In the Laboratory Table 1. Ni Content Found by the Students in Fish and CRMs Sample

Exp Value/(μg g-1)a

Certified Value/(μg g-1)

texp

ttabb

TORT-2

2.36 ( 0.11

2.50 ( 0.19

2.233

4.303

DORM-3

1.24 ( 0.06

1.28 ( 0.24

1.039

4.303

SRM 2977

5.95 ( 0.25

6.06 ( 0.24

0.745

4.303

Mussel

3.70 ( 0.20

Prawn

7.49 ( 0.50

Hake

4.77 ( 0.19

Sole

5.14 ( 0.31

a

Mean value ( standard deviation, n = 3. b p = 0.05, 2 tails, n = 3.

Analytical characteristics were also obtained by the students. The calibration curve was linear up to 50 μg L-1, the characteristic mass was 10 pg, and the limit of detection was 0.2 μg L-1 (calculated according to the 3σ criterion). The between-batch precision, expressed as relative standard deviation, was between 2 and 9%. The calculation of typical figures of merit provided the students with an approach to carry out a quality-control evaluation of the analytical method. More information is provided in the supporting information. The method was validated using the three CRMs (Student t test was used). Different seafood samples were also analyzed: mussels, prawns, hake and sole. The results for CRMs and samples from three replicates are show in Table 1. Evaluation The analytical results obtained were evaluated by each student (individually) then by the student group. The use of CRMs allows the results to be statistically evaluated (certificate value versus experimental results). The report made by the students was an important tool for the evaluation. The report followed a format similar to a research article (more information in supporting information). Further discussion allowed the instructor to question the students to demonstrate whether they understood their data and the applicability of UAE-ETAAS for Ni determination in biological matrices. Conclusion

Figure 3. Optimization of the variables influencing the Ni extraction from TORT-2: (A) acid concentration, (B) sample mass, (C) particle size, (D) sonication time, (E) ultrasound amplitude.

curves and the corresponding temperature programs are available in the supporting information. Optimizations of extraction variables are shown in Figure 3. The results were obtained using TORT-2 and expressed as percentage of recovery. 482


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This experiment provides students with interesting and practical experience dealing with sample preparation for tracemetal determination. UAE is a fast and easy sample preparation approach using soft conditions. This can be considered a green methodology that eliminates or reduces the quantities of reagents and solvents used, particularly for sample preparation. In addition, this combined approach (UAE-ETAAS) consumes less energy and requires less time. It is important to discuss with students the reasons for choosing greener analytical methods. Sample preparation for metal determination has traditionally been carried out using wet- or dry-ashing methods. These methods involve tedious and time-consuming treatments at high temperatures with corrosive reagents. Among these methods, microwave-assisted digestion has the greatest acceptance. However, the use of microwave ovens with pressure reactors introduces an extra factor of risk for the students in the laboratory. The combination of UAE and ETAAS allows them to carry out trace-metal determination in a safer way.


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In the Laboratory

Literature Cited 1. Spudich, T. M.; Herrmann, J. K.; Fietkau, R.; Edwards, G. A.; McCurdy, D. L. J. Chem. Educ. 2004, 81, 262–265. 2. Miller-Ihli, N. J. J. Anal. At. Spectrom. 1994, 9, 1129–1134. 3. Bendicho, C; Lavilla, I. Ultrasound Extractions. In Encyclopedia of Separation Science; Academic Press: Amsterdam, 2000; pp 1448-1454. 4. Amoedo, L.; Capelo, J. L.; Lavilla, I.; Bendicho, C. J. Anal. At. Spectrom. 1999, 14, 1221–1226. 5. Filgueiras, A. V.; Capelo, J. L.; Lavilla, I.; Bendicho, C. Talanta 2000, 53, 433–441. 6. Krishna, M. V.; Balarama, K.; Arunachalam, J. Anal. Chim. Acta 2004, 522, 179–187. 7. Capelo, J. L.; Lavilla, I.; Bendicho, C. Anal. Chem. 2001, 73, 3732– 3736. 8. Santos Junior, D.; Krug, F. J.; Pereira, M. G.; Korn, M. Appl. Spectrosc. Rev. 2006, 41, 305–321. 9. Manutsewee, N.; Aeungmaitrepirom, W.; Imyim, A. Food Chem. 2007, 101, 817–824.


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10. Afridi, H.; Kazi, T. G.; Arain, M. B.; Jamadi, M. K.; Kazi, G. H.; Jalbani, N. J. AOAC Int. 2007, 90, 470–478. 11. Ansari, R.; Kazi, T. G.; Jamali, M. K.; Arain, M. B.; Sherazi, S. T.; Jalbani, N.; Afridi, H. I. J. AOAC Int. 2008, 91, 400–407. 12. Neves, R. C. F.; Moraes, P. M.; Saleh, M. A. D.; Loureiro, V. R.; Silva, F. A.; Barros, M. M.; Padilha, C. C. F.; Jorge, S. M. A.; Padilha, P. M. Food Chem. 2009, 113, 679–683. 13. Shah, A. Q.; Kazi, T. G.; Arain, M. B.; Baig, J. A.; Afridi, H. I.; Jamali, M. K.; Jalbani, N.; Kandhro, G. A. J. AOAC Int. 2009, 92, 1580–1586. 14. Lavilla, I.; Vilas, P.; Millos, J.; Bendicho, C. Anal. Chim. Acta 2006, 577, 119–125. 15. Lavilla, I.; Vilas, P.; Bendicho, C. Food Chem. 2007, 106, 403–409. 16. U.S. Food and Drug Administration Home Page. http://www.fda. gov/ (accessed Jan 2011).

Supporting Information Available Student handout; notes for the instructor. This material is available via the Internet at http://pubs.acs.org.


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Quantitative Ultrasound-Assisted Extraction for Trace-Metal

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