Related Experiment Video
Updated: May 24, 2026

07:04
High Precision Zinc Isotopic Measurements Applied to Mouse Organs
Published on: May 22, 2015
Standardization of 65Zn by sum-peak method.
E M Oliveira1, A Iwahara, R Poledna
1Laboratório Nacional de Metrologia das Radiacões Ionizantes (LNMRI/IRD/CNEN), Av. Salvador Allende, s/n, Recreio, CEP 22780-160 Rio de Janeiro, Brazil. estela@ird.gov.br
Summary
The sum peak method offers a simpler and more practical approach for standardizing Zinc-65 (65Zn) radioactivity. This method provides accurate results comparable to traditional ionization chambers.
Area of Science:
- Nuclear Physics
- Metrology
- Radiochemistry
Background:
- Accurate standardization of radioactive sources is crucial for various applications.
- Existing methods for Zinc-65 (65Zn) standardization can be complex and time-consuming.
Purpose of the Study:
- To evaluate the efficacy of the sum peak method for standardizing a commercial Zinc-65 (65Zn) solution.
- To compare the results obtained by the sum peak method with those from a traceable ionization chamber.
Main Methods:
- Standardization of a (65)Zn solution using the sum peak method with a planar high-purity germanium (HPGe) detector.
- Comparison of activity measurements with a well-type 4πγ ionization chamber traceable to BIPM standards.
Main Results:
- The sum peak method yielded an activity of 42.79 kBq/g.
- The ionization chamber provided a comparable activity of 42.74 kBq/g at the reference date.
- The sum peak method achieved a lower uncertainty (0.25%, k=1) compared to the ionization chamber (0.85%, k=1).
Conclusions:
- The sum peak method is a viable and accurate technique for (65)Zn standardization.
- This method presents advantages in terms of ease of use, simplicity, and practicality over other techniques.
Related Concept Videos
Introduction to z Scores
A z score (or standardized value) is measured in units of the standard deviation. It indicates how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
z scores help...
z scores help...
Introduction to z Scores
A z score (or standardized value) is measured in units of the standard deviation. It tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a zero z score. It is important to note that the mean of the z scores is zero, and the standard deviation is one.
z scores help...
z scores help...
z Scores and Unusual Values
The z score is one of the three measures of relative standing. It describes the location of a value in a dataset relative to the mean. z scores are obtained after the standardization of the values in a dataset. The z score for the mean is 0.
This score indicates how far a value is from the mean in terms of standard deviation. For example, if a data value has a z score of +1, the researcher can infer that the particular data value is one standard deviation above the mean. If another data value...
This score indicates how far a value is from the mean in terms of standard deviation. For example, if a data value has a z score of +1, the researcher can infer that the particular data value is one standard deviation above the mean. If another data value...
Testing a Claim about Standard Deviation
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
z Scores and Area Under the Curve
z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of zero.

