Revision as of 00:56, 26 October 2017

PAA_Selenium/Soil_Experiments#Selenium_Sample_Analysis

Sample Description

The sample was placed in an aluminum cylinder that was to be irradiated. The target components consisted of a nickel foil on the front of the cylinder with 2 pure selenium pellets under the foil, but still outside the cylinder. Inside the target there was burnt sagebrush ash, which was burned with a blowtorch, and selenium. Below are the masses of the components

Nickel Foil: 0.2783g

Outer Se Pellets: 0.0971g

Sage Ash: 0.5111g

Inner Se Pellets: 0.0523g

Energy

LB May Calibration 2017

The Calibration for Detector A was done on the morning of 5/23/17 with the MPA software using the thorium rods (as the calibration was fairly close already) and the correction values were found to be Det A Intercept = -12.208800 slope =1.021270

Efficiency

LB May 2017 Det A Efficiency

Nickel Information

Se170063 Nickel Investigation

Activity and Half Life

Se170063 Activity And Half Life

Alternative Method

Se170063 Activity and HL Alternate

Corrected Alternative method

The files used for this analysis are in the directory /data/IAC/Se/May2017/5_25_17/Se_Activity_SysOffset_Mix

To begin, I have corrected the mixture to have a factor of 0.62, which is the mystery factor throwing of all of these analyses. The histogram is also weighted by the mass. The weight added to the histogram is

So the true number of counts has indeed been weighted here. Now I want to try to test every different method that was suggested. So first I am going to weight the mixture by the mystery factor of 0.62, and leave my Gaussian fits as wide as they were previously. The gaussians will probably be made more compact if the mystery factor does not alleviate the problem. The first step is to find the number of counts within the window of interest. Below is the process I used to determine the number of counts and the error associated with it. First begin by plotting the histogram using the ROOT program Eff.C, which is shown below.

Now take the integral given in the stats box and subtract the background to get the number of counts. Here the number of counts would be

Now I can convert this error into an activity by dividing by the time, which is 300 seconds in this case. After that take the natural log of the quotient.

Now to find the error we can notice that the standard deviation here is 0.6238. The procedure is to expand the window by one or two standard deviations and find the difference in the number of counts in the original window. Due to the binning here I have decided to expand the window by 1 channel on each side, which is roughly 2 standard deviations. A picture is given below.

Now we do a similar method to find the number of counts within this window.

Now take the difference between the original window's number of counts and the expanded window's number of counts.

Now to propagate this error we must divide this number by the original number of counts.

This method was repeated for the next set of runs that make the data file. The numbers are in a table below.

	0 <t< 300 sec	730 < t < 1020 sec	1480 < t < 1775	2250 < t < 2550 sec	3050 < t < 3300 sec	3775 < t < 4050 sec	4480 < t < 4770 sec
Original Window Counts	880200	716200	617100	545800
Original Window Background (Integrated)	381379	267608	215260	189665
Original Window Difference	498821	448592	401850	356135
Expanded Window Counts	970900	782600	671300
Expanded Window Background	468138	333633	269025
Expanded Window Difference	502762	448967	402275
Error in counts	3941	375	425
.dat file entry	7.416220118 +/- 0.0079006297	7.343988145 +/- 0.0008359489264	7.216858801 +/- 0.0010576086

Below are the related pages for this sample using this method of window expansion:

Runlist

Table with dates and filename and locations on daq1

LB_May_2017_Irradiation_Day#10.25_Se_Soil_Mix