Embedded Files
The black box with transparent top render and a table that lists the parts.
Background:
Solubility is a concept prevalent throughout many areas of chemistry and fluid dynamics. Solvent, solute, and saturation point are important components of the solubility measurement. Solvent is the chemical doing the dissolving, and the solute is the chemical being dissolved. Solutions have a saturation point that depends on the temperature and the compound(s) being dissolved. This saturation point is a critical state where the solvent has dissolved the maximum possible solute (compound); any additional solute will settle as a solid and not dissolve. In this automated solubility measurement system, solubility data are obtained mainly using a light scattering technique and changing the status of the solution with solvent and solute delivery.
Objective:
The objective of this project is to find the saturation point of novel combinations of salts and solvents using two RGB color sensors to record RGB light data emitted from an LED in the range of 0 to 255. The system is designed to scope a range for the solution's solubility and reduce human burden on solubility measurement.
Requirements:
Automated solubility recognition process using a controller with feedback.
Liquid delivery system that can be computer controlled.
Stirring mechanism that can be computer controlled.
Data acquisition system that is easy to use and has minimal human interaction.
Inclusion of a temperature sensor and conductivity sensor.
Built enclosure to run experiment and remove ambient light.
Deliverables:
CAD design of the entire experimental setup.
Enclosed black box to encase experiment and hide from outside light.
Pump control system.
Solid solute delivery system.
Data acquisition system that collects values of temperature, RGB, conductivity.
Circuit board and micro-board controller incorporating all sensors together with mechanical components.
Python code that exports experimental data into Excel file, and sends the file through an email. Alert email also sets up if the experiment fails due to the reason of beaker is full.
Description of Final Design:
Features:
Black box (enclosed system):
The design of the black box avoids extra light seeping into the interface, meanwhile it contains three inlets on the top for the delivery of solvent and solute and the conductivity probe. RGB color sensors and temperature sensor are able to mount inside the black box.
Acrylics design of the black box, with the lid (left) and without the lid (right).
PCB:
PCB:
PCB design used in the system, circuit for RGB color sensors, temperature sensor, and the solid delivery system.
LED Assembly - Beaker Testing 3.MOVVideo showing how to control the green, red, and blue LEDs.
LED Assembly:
LED Assembly:
Three different color LEDs mounted together and used for light scattering in the system.
RGB Color Sensors, Temperature Sensor, and Conductivity Probe:
RGB color sensors detect RGB components of the LED to obtain the data of light intensity. Temperature sensor monitors the change of temperature in the experiment. The conductivity probe connects to the Arduino Uno with the Arduino interface shield to determine the conductivity of the solution.
Testing of the TCS34725 RGB color sensor (top) and DS18B20 temperature sensor (bottom).
Vernier conductivity probe (top) and the Arduino interface shield (bottom).
IKA magnetic stirrer in use with python code.
Magnetic Stirrer:
Magnetic stirrer employs a magnetic field and causes the magnetic stirrer bar to spin in the solute in order to stir the solvent with the solute.
Masterflex Digital Drive 07551-20 peristaltic pump.
Peristaltic pump:
The peristaltic pump delivers solvent (liquid) to the solution to reach the saturation point.
Team 25 Hardware Tutorial Video FINAL 2021-06-12 1304.movHardware Tutorial Video
Hardware Tutorial Video
Video with detailed instructions on how to use each component in the system, and the explanation of the Python and Arduino codes in the system.
Analysis Results:
The system is tested with the solubility measurement of sodium sulfate and water. The following results exhibit the RGB values of the LEDs, which are the important values utilized to obtain the saturation point. The difference between the data outputs of the RGB color sensors is compared with a tolerance in order to find the saturation point, so calibration is needed.
The RGB values detected by the RGB color sensors without calibration (left) and with calibration (right).
Temperature sensor data
Temperature sensor data
Temperature data for water and salt solution in Fahrenheit that collected by the DS18B20 temperature sensor and exported to the Excel file. MATLAB is used to import Excel file and plotted the data.
Conductivity sensor data
Conductivity sensor data
Conductivity data shows the turbid point of the solution (where solvent does not dissolve anymore), which it helps evaluated the solubility data and located the saturation point.
Pump Data
Pump Data
Since the Python codes only allow users to control the RPM, the team test the pump multiple times to find out the linear relationship between RPM and flow rate, revolution and volume.
Example of how the data from each sensors and the pump exported to the Excel file.
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