Concentration sensor for precursor delivery system

A method, comprising:

• receiving first sensor data indicative of a first mass flow rate of a first gas flowing to a vaporization chamber, the vaporization chamber comprising a compound to be transitioned into a gaseous state;
• receiving second sensor data indicative of a second mass flow rate of a second gas flowing out of the vaporization chamber, wherein the second gas comprises the compound and the first gas;
• receiving third sensor data indicative of a third mass flow rate of the compound into the vaporization chamber;
• and
• training an untrained machine learning model to produce a trained machine learning model, wherein the untrained machine learning model is trained using the first sensor data, the second sensor data, and the third sensor data, and wherein the trained machine learning model is trained to determine an estimated concentration of the compound within the second gas.

A non-transitory machine-readable storage medium comprising instructions that, when executed by a processing device, cause the processing device to:

• receive first sensor data indicative of a first mass flow rate of a first gas flowing to a vaporization chamber, the vaporization chamber comprising a compound to be transitioned into a gaseous state;
• receive second sensor data indicative of a second mass flow rate of a second gas flowing out of the vaporization chamber, wherein the second gas comprises the compound and the first gas;
• receive third sensor data indicative of a third mass flow rate of the compound into the vaporization chamber;
• determine an estimated concentration of the compound within the second gas based on processing the first sensor data, the second sensor data, and the third sensor data;
• and
• modify a flow rate of the first gas based on the estimated concentration of the compound within the second gas.