Method for a liquid chemical concentration analysis system
View Patent ↗An apparatus utilizes optical reflectivity (REF) to measure concentrations in liquids. The REF optical system is packaged in a compact and cost-effective form factor. An electronic circuit drives the optical system. The miniaturized REF sensor is situated in an optical-fluidic cell or an optical-fluidic manifold with an optical window in contact with the liquid. Changes in a total internal reflection (TIR) signal are sensitive to temperature and concentration of the liquid. These changes in the TIR signal are used to accurately determine the concentration in the liquid. The liquids may be either static or dynamic.
1. A method of measuring a concentration in a liquid using an optical sensor comprising:
calibrating an Index of Refraction to a pixel number by generating at least one calibration curve of a known sample under test;
acquiring raw data sets by reading out pixel data from an optical detector in the optical sensor in contact with the known sample under test;
acquiring background data sets from the optical detector;
acquiring air reference data sets from the optical detector;
averaging the raw data sets, the background noise data sets, and the air reference data sets to form an averaged raw data set, an averaged background noise data set, and an averaged air reference data set;
calculating at least one reflectivity data set;
calculating a pixel number correlating to an Index of Refraction at which total internal reflection (TIR) occurs;
converting the calculated pixel number to the Index of Refraction using the at least one calibration curve;
calculating a temperature compensated Index of Refraction; and
converting the temperature compensated Index of Refraction to a concentration for the known sample under test.
2. A method according to claim 1 , wherein the at least one calibration curve of the known sample under test is generated as a function of a liquid temperature and a liquid concentration.
3. A method according to claim 1 , wherein the at least one calibration curve of the known sample under test is generated as a function of an optical sensor temperature and a liquid concentration.
4. A method according to claim 1 , wherein generating the at least one calibration curve includes using a polynomial least squares fit to a plurality of calibration points.
5. A method according to claim 1 , wherein acquiring background noise data sets from the optical detector includes turning off a light source in the optical sensor and reading out the pixel data.
6. A method according to claim 1 , wherein acquiring air reference data sets from the optical detector includes making measurements with air as a sample in contact with the optical sensor and reading out the pixel data.
7. A method according to claim 1 , wherein calculating the at least one reflectivity data set includes subtracting the averaged background noise data set from the averaged raw data set and subtracting the averaged background noise data set from the averaged air reference data set, dividing a result of subtraction of the averaged background noise data set from the averaged raw data set by a result of a subtraction of the averaged background noise data set from the averaged air reference data set.
8. A method according to claim 1 , wherein calculating the at least one reflectivity data set includes normalizing the at least one reflectivity data set.
9. A method according to claim 8 , wherein normalizing the at least one reflectivity data set includes dividing the at least one reflectivity data set by an average value of an intensity of a set of pixels located in a middle portion of a peak area of the at least one reflectivity data set.
10. A method according to claim 8 , wherein normalizing the at least one reflectivity data set includes adjusting the intensity of a light source.
11. A method according to claim 1 , wherein calculating the pixel number correlating to the Index of Refraction at which total internal reflection (TIR) occurs includes applying a Mass Moment Algorithm to the at least one reflectivity data set.
12. A method according to claim 11 , wherein calculating the pixel number includes averaging the results of applying the Mass Moment Algorithm to a plurality of reflectivity data sets.
13. A method according to claim 1 , wherein calculating the pixel number correlating to the Index of Refraction at which total internal reflection (TIR) occurs includes using an nth degree polynomial approximation of the shadow line, intersected with a threshold value.
14. A method according to claim 1 , wherein calibrating an Index of Refraction to a pixel number includes using known concentrations of the known sample under test.
15. A method according to claim 1 , wherein calculating the temperature compensated Index of Refraction includes using a sensor temperature measured by a temperature sensor in the optical sensor, a liquid temperature measured by a second temperature sensor in close proximity to the liquid, and the measured Index of Refraction as a function of time.
16. A method according to claim 1 , wherein calculating the temperature compensated Index of Refraction includes using a sensor temperature measured by a temperature sensor in the optical sensor, a liquid temperature measured by a second temperature sensor in an optical fluidic cell (OFC) or optical fluidic manifold (OFM), and the measured Index of Refraction as a function of time.
17. A method according to claim 1 , wherein the temperature compensated Index of Refraction is calculated by an algorithm that utilizes the sensor temperature measured by the temperature sensor in the optical sensor, the liquid temperature measured by the second temperature sensor, and the measured Index of Refraction as a function of time.
18. A method according to claim 1 , wherein the temperature compensated Index of Refraction is determined utilizing a sensor temperature measured by a temperature sensor in the optical sensor, a liquid temperature measured by a second temperature sensor, the measured Index of Refraction as a function of time, and calibration lookup tables of data previously obtained characterizing the known sample under test.
19. A method according to claim 1 , wherein converting the temperature compensated Index of Refraction to the concentration for the known sample under test includes using calibration lookup tables of data previously obtained characterizing the known sample under test.
20. A method according to claim 1 , wherein the calculated concentration is displayed using a graphical user interface (GUI) or an LCD display.
21. A method of measuring a concentration in a liquid using an optical sensor comprising:
calibrating an Index of Refraction to a pixel number by generating at least one calibration curve of a known sample under test;
acquiring raw data sets by reading out pixel data from an optical detector in the optical sensor in contact with the known sample under test;
acquiring background noise data sets from the optical detector;
acquiring air reference data sets from the optical detector;
calculating at least one reflectivity data set;
normalizing the at least one reflectivity data set;
calculating a pixel number correlating to an Index of Refraction at which total internal reflection (TIR) occurs;
converting the calculated pixel number to the Index of Refraction using the at least one calibration curve;
calculating a temperature compensated Index of Refraction using a sensor temperature measured by a temperature sensor in the optical sensor, a liquid temperature measured by a second temperature sensor in close proximity to the liquid, and the measured Index of Refraction;
converting the temperature compensated Index of Refraction to a concentration for the known sample under test; and
displaying the calculated concentration using a display.
22. A method according to claim 21 , wherein the at least one calibration curve of the known sample under test is generated as a function of a liquid temperature and a liquid concentration.
23. A method according to claim 21 , wherein the at least one calibration curve of the known sample under test is generated as a function of an optical sensor temperature and a liquid concentration.
24. A method according to claim 21 , wherein generating the at least one calibration curve includes using a polynomial least squares fit to a plurality of calibration points.
25. A method according to claim 21 , wherein acquiring background noise data sets from the optical detector includes turning off a light source in the optical sensor and reading out the pixel data.
26. A method according to claim 21 , wherein acquiring air reference data sets from the optical detector includes making measurements with air as a sample in contact with the optical sensor and reading out the pixel data.
27. A method according to claim 21 , wherein calculating the at least one reflectivity data set includes averaging the raw data sets, the background noise data sets, and the air reference data sets to form an averaged raw data set, an averaged background noise data set, and an averaged air reference data set, subtracting the averaged background noise data set from the averaged raw data set and subtracting the averaged background noise data set from the averaged air reference data set, dividing a result of subtraction of the averaged background noise data set from the averaged raw data set by a result of a subtraction of the averaged background noise data set from the averaged air reference data set.
28. A method according to claim 21 , wherein calculating the at least one reflectivity data set includes normalizing the at least one reflectivity data set.
29. A method according to claim 28 , wherein normalizing the at least one reflectivity data set includes dividing the at least one reflectivity data set by an average value of an intensity of a set of pixels located in a middle portion of a peak area of the at least one reflectivity data set.
30. A method according to claim 28 , wherein normalizing the at least one reflectivity data set includes adjusting the intensity of a light source.
31. A method according to claim 21 , wherein calculating the pixel number correlating to the Index of Refraction at which total internal reflection (TIR) occurs includes applying a Mass Moment Algorithm to the at least one reflectivity data set.
32. A method according to claim 21 , wherein calculating the pixel number includes averaging the results of applying the Mass Moment Algorithm to a plurality of reflectivity data set.
33. A method according to claim 21 , wherein calculating the pixel number correlating to the Index of Refraction at which total internal reflection (TIR) occurs includes using an nth degree polynomial approximation of the shadow line, intersected with a threshold value.
34. A method according to claim 21 , wherein calibrating an Index of Refraction to a pixel number includes using known concentrations of the known sample under test.
35. A method according to claim 21 , wherein the second temperature sensor is located in an optical fluidic cell (OFC) or optical fluidic manifold (OFM).
36. A method according to claim 21 , wherein the temperature compensated Index of Refraction is calculated by an algorithm that utilizes the sensor temperature measured by the temperature sensor in the optical sensor, the liquid temperature measured by the second temperature sensor, and the Index of Refraction.
37. A method according to claim 21 , wherein the temperature compensated Index of Refraction is determined utilizing a sensor temperature measured by a temperature sensor in the optical sensor, a liquid temperature measured by a second temperature sensor, the measured Index of Refraction as a function of time, and calibration lookup tables of data previously obtained characterizing the known sample under test.
38. A method according to claim 21 , wherein converting the temperature compensated Index of Refraction to the concentration for the known sample under test includes using calibration lookup tables of data previously obtained characterizing the known sample under test.
39. A method according to claim 21 , wherein displaying the calculated concentration using the display includes using a graphical user interface (GUI) or an LCD display.