Sorption data analysis

Sorption data analysis
In the following notes,
a. AC = activated carbon, whether alone as GAC (all black)
or in mixture with an Ammonium sorbent (black / white mix)
b. You entered ABS 610nm readings in the table. ABS 610nm is numerically
equivalent to an empirical concentration T-units/ml. Use T-units just like mg. I’ll
show you the conversion later.
Step 1. Check the data set for the following items
Row 11 should contain the sorbent masses, in the range of 2.4 to 7.6 grams.
 Did the data manager forget the decimal?
 Are all in the correct units?
Some list the correct magnitude, but wrong units, such as 2.4 mg.
 Are they in consistent units?
Row 22 should contain FILTERED measurements from the three reaction tubes.
Filtering drops the ABS 610 nm reading by about 0.3 .
 Does the final reading show a large drop from the previous reading, evidence
of filtering the sample?
 If not, mark the final reading “possible unfiltered” or similar wording.
Step 2.
Calculate q for each reaction tube
q = (C(start) – C(end)) * Vol
mass of AC
C(start) is the concentration in T-units/ml at time 0
C(end) is the final filtered concentration
Volume is the liquid volume (25 ml for all tubes in this study)
mass of AC is listed at the top of each column of data.
For example, from the first table of data on the GAC sheet, for tube #1
q = (2.018 – 0.02)Tunits/ml * 25 ml
2.4 g = 20.81 T-units/g
 Use only filtered measurements for the end value. Do not calculate q if the tube
did not have a filtered end value.
 Ignore any tubes that were dropped. The liquid to sorbent ratio must remain the
same throughout the experiment for valid isotherm calculations.
 Calculate q for reaction tubes (having AC and dye);
NOT the RO control tube, NOT the dye control tube.
 This should result in nearly 36 q values.
……..
Step 3. Create a new table in Excel for the GAC data (both regular and “hi”)
with the paired C(end) and q value for each tube, like this:

If last few readings of the unfiltered sample are similar, assume equilibrium.
You may want to correct for the sorbent dust, which artificially raises the
abs610 reading. An appropriate correction would be to subtract the
appropriate RO control value at that time period – an RO+sorbent tube of
the same sorbent in approximately the same mass.
This table should have approximately 24 rows, a few less if tubes were dropped
or did not have a filtered final reading.
Create a separate, similar table for the GAC+Ammonia sorbent mix readings.
This table should have approximately 12 rows.
Use Excel’s slope and intercept functions to find 1/n and log K, respectively.
Complete the final conversion of log K to K.
When reporting K and 1/n values, you must also report the units you used for q and for
C. These fitting parameters are dependent on the units of the data.
Step 4. Compare rates of dye uptake between the two different sorbents.
This will be evaluated as one type of second level analysis for this report.
 Use the GAC and mix worksheets, which have sets of similar dye concentrations.
 You could consider using the “GAC hi” data in comparison to the GAC data. Do
not compare “GAC hi” rates to the” mix” data
Rate comparisons can use the unfiltered ABS 610 values.
Rates refer to the change in ABS610 with respect to time, for the initial few
measurements showing rapid change between time points.
Calculate an initial rate for each tube separately.
Complete all reporting tasks according to the Lab Report Guidelines.
Major items expected
 Compare K and 1/n for the two sorbents
 Do the two sorbents act similarly or have differences?
 What issues are raised by the RO(no dye) / GAC controls?
 What issues are raised by the Dye / no GAC controls?
 Was the system at equilibrium? What effect would this have on q, K, 1/n if not?
 How do you recommend the client use this information?
Other possible considerations:
 The second sorbent claims to target ammonia. Can you hypothesize what other
compounds it might be beneficial for?
 Compare rates
 Provide recommendations for a next experiment in this study (additional
information the client might need, evaluation of artifact data as possible
experimental error or a different mechanism, etc)