Direct Counting of Tritium-Tagged Solid and Liquid Samples

satisfactory. The alternative method requires less stand- ard hydrochloric acid and sodium hydroxide, and it is better adapted to samples of completel...
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V O L U M E 2 8 , N O . 11, N O V E M B E R 1 9 5 6 Results for total hydrochloric acid in Table I1 averaged 0.5 mg. high. This is equivalent to 0.05 ml. of 0.3X hydrochloric acid. The standard deviation was 0.1 mg. This was good accuracy and excellent precision. Results for total sulfuric acid in Table I11 averaged 0.7 mg. or 0.05 ml. high, and the standard deviation was 0.5 mg. The accuracy was good, and precision was acceptable. The sodium carbonate results shown in Table IV averaged 2.5 mg. high and had standard deviations of 0.4 and 1.5 mg. The sodium hydroxide results averaged 1.3 mg. low, and the standard deviations were 0.4 and 0.9 mg. The greatest error was in carbonate, which averaged about 0.9% high, corresponding to 0.12 ml. of 0.4N hydrochloric acid. As can be seen from the recommended procedures, error in the total soda or hydroxidebicarbonate titrations Rill be doubled in the carbonate and hydroxide values. However, these results were considerably better than those from former procedures (1, 6 ) , in which the carbonate is precipitated as barium carbonate, filtered off, and analyzed. I n such methods significant errors are caused by adsorption by barium carbonate and the reaction of sodium hydroxide with atmospheric carbon dioxide during filtration. Therefore, though the accuracy and precision for carbonate and hydroxide were not as good as was desired, the results were an improvement over those by previous procedures. Average biases for aluminum oxide by the recommended method were +0.1, $0.5, +0.1, and -0.6 mg. (Tables 11, 111, and IV). The standard deviation estimates were all about 0.1 mg. This is good accuracy and excellent precision. The recommended method was unaffected by aluminum oxide concentration. I n contrast, the alternative method (Table 11) gave a +0.4-mg. bias a t the 0.025 gram of aluminum oxide concentration, and the biases progressed to -0.9 mg. a t the 0.2 gram of aluminum oxide concentration. However, results in the 0.05 to 0.15 gram of aluminum oxide concentration range were satisfactory. The alternative method requires less standard hydrochloric acid and sodium hydroxide, and it is better adapted to samples of completely unknown aluminum oxide concentration. Results for aluminum oxide in the presence of nitric and perchloric acids had accuracy and precision corresponding to that shown in Tables I1 and 111.

1735 EFFECT O F IMPURITIES ON ALUMINUM OXIDE R E S U L T S

Aliquots of several aluminum chloride solutions containing about 0.2 gram of aluminum oxide were titrated by the recommended method. Samples containing no impurity were interspersed a t random among samples to which a solution containing a known amount of impurity had been added. A pooled value for standard deviation was obtained for samples to which no impurity had been added. Control limits were arbitrarily established as the average without impurity &3 times the pooled standard deviation estimate ( X ~ k 3 . s ) . Each impurity was tested to find the amount, if less than 0.2 gram as the anhydrous oxide, that would cause an aluminum oxide bias equal to the control limit. Titration curves were prepared on the impurities in amounts equivalent to 0.2 gram of anhydrous oxide. These tests were limited, and the data are recommended only as a guide. The results of the tests are shown in Table V. The 16 impurities that produced the strongest interferences had positive biases in aluminum oxide. The titration curves showed that the greatest cause of interference was the release of hydroxide under the conditions of the method. Intermediate interference was caused by a combination of hydroxide release and buffering, and buffering was the principal cause of minor interference. CONCLUSION

The methods presented provide for accurate, precise, and rapid determination of aluminum oxide or aluminum, total acid, hydroxide, and carbonate. LITERATURE CITED

Bushey, A. H., AXAL.CHEM.20, 169 (1948). Hale, hf. x., IND. ENG.CHEM., ANAL.ED. 18, 568 (1946). Prescott, F. J., Shaw, J. K., Biiello, J. P. Cragwall, G. O., Ind. Eng. Chem. 45, 338 (1953). (4) Snyder, L. J., ISD.ENG.CHEM.,ANAL.ED. 17, 37 (1945). (5) Viebock, F., Brecher, C., Arch. Pharm. 270, 114 (1932). (6) Watts. H. L.. Utlev. D. W.. ~ X A L CHEM. . 25. 864 (1953). - for good counting operation. KO explanation is known for the dip in the counting plateau of the 60--, tritium-tagged cottonseed oil (CSO) sample.

18

13

V O L U M E 28, NO. 1 1 , N O V E M B E R 1 9 5 6

1737

order t o obtain acceptable accuracv and reproducibility. This f:ict is brought out clearly by the data given in Table I, in which tlie counts of liquid samples are compared with those of solid winples. Although the parent material used is identical in TLLble I, the solid samples have an average count over tm-ice as great as that of the liquid phase. This is thought to be a result oi the much greater surface area of the crystalline solid samples. Stability of count data with time was not taken for an infinitely thick cottonseed oil soap sample, because soaps do not melt at practical counting temperatures, and it is considered to be of little value to count a solid infinitely thick sample in view of the very large variability in the count,s of this type of sample. Drifting of the count rate Tvas sometimes observed for infinitely thick solid, but not for liquid-type samples. Standard Deviation of Counts of Liquid and Infinitely Thin Tritium-Tagged Samples. The standard deviations of several variables involved in preparing and counting tritium-tagged liciuid samples are summarized in Table 11. All the variables are roughly t,he same in magnitude, when lens paper is used to spread tlie samples, averaging about 4yo standard deviation for samples m i n t e d in t,he standard 1 X 5/16 inch planchets. The data of Tnble I1 bring out two other important points-that elimination of the use of lens paper to spread the liquid samples increases the stzndard deviation from 3.5 to 1Syoand the use of ll/g X iiich aluminum planchets (with lens paper) leads to a higher standard deviation than thxt foiind with the 1 X L / 1 6 inch nickel-iron planchets.

Table 111. Standard Deviation of Counts of Infinitely Thin Tritium Samples"

w

I3

z -

.. I

(12 y per sr4. cm. sample thickness)

Type of Material F a t t y Acid

C

1

Mean

9000 9280 9170

2

9800 9490 9730

5410

1

10,580 10,710 10,090

10.315

L 9,990 9,850 10,670

Standard Deviation, 7% Between duplicates, saine operator Between operators a

5 2

1.0 ml. of sample solution cvaporaied in 1 X

6 4 6/16

inch planchets.

The over-all preciiion of infinitely thin tritium-tagged cottonseed nil, fatty acid, and soap samples is about 67, standard deviation. Representative data are given in Table 111. Infinitely thin samples can be .-atiqfactorilr counted nt temperatures below their melting point DISCUSSIOY 4 \ D COYCLUSIONS

The direct counting radioassay of tritium-tagged cottonseed oil triglyceride and fattv acid as infinitely thick or infinitelv thin samples is satisfactory, using a windowless gas-fioiT- counter. Cottonseed oil soap samples may be counted only as infinitely thin samples, in view of the large st'andard deviat.ion of the counts of solid infinitely thick samples. Based on this work it would seem possible to count accurately any nonvolatile tritiumtagged samples as infinitely thin samples or liquid infinitely thick samples. The precision of sample preparation and of counting shows about 4yo standard deviat,ion for liquid 100-mg. samples spread with lens paper and about (3% for infinitely thin samples. The counting efficiency for infinitely thin tritium-tagged samples counted in the window! 570. Based on less gas-flow counter is 50 == this figure, the counting efficiency for 20 mg. per sq. em. tritium-tagged samples is within about 0.257. Decreasing the infinitely thick sample size would increase counting efficiency. LITERATURE CITED

m !5-

z 3 0 u

10 -

-4

f

5-

50 SAMPLE

4 5

IO

SAMPLE

Figure 2.

Saniple Counts

;

t-

00

Soap

Operator

15

20

THICKNESS.

25

100 THICKNESS,

I50 ~g / c m

30

kg / c m

Self-absorption of tritium-tagged cottonseed oil triglyceride samples l l / a X 1/16 inch aluminum planchets Solution volume constant at 1 ml.

(1) Biggs, 11. W., Kritchevsky, D., Kirk, XI. K., .&SAL. CHEM.24, 223 (19.52). (2) Eidinoff, 31. L., Knoll, J. E., Science 112, 250 (1950). ( 3 ) Glasc-ock, It. F., .\7aatzue 168, 121 (1951); Sucleonics 9, 25 (1951). (4) Hayes, F. N., Goiild. R. G., Science 117, 480 (1953). (5) Jenkins, W , A , , - ~ X A T ,C.H E M . 26, 1477 (1953). (6) Lihby, W. F.. ISD. Esc;. CHFX., A kED. ~ 19, 2 (1947). (7) Melander, L., Aria Chem. Scand. 2, 440 (1948).

(8) Robinson, C. V., R e r . Sci. I n s t r . 22, 353

(1951). (9) White, D. F., Campbell, I. G., Payne, P. It., Saticre 166, 628 (1950). (10) Wilzhach, K. E., Kaplan, L., Brown, W. G., Science 118, 522 (1953). REcE1vr.n for review -4pril 9, 1956.

1956.

Accepted July 13.

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