SCA is a multi-sensor microsystem (MSM) to monitor for the presence of toxic chemicals (TICs), pollutants, masterarbeit schreiben lassen, volatile organic compounds (VOCs) and flammable gases in air.
The SCA integrates temperature, relative humidity, ionic compounds and ghostwriter beauftragen. It exploits Temperature and Voltage Cycled operation combined with Electrical Impedance Spectrometer (EIS) to achieve improved ghostwriter bachelorarbeit. Alternate Current (AC) readout is less sensitive to drifts plus EIS allows to derive the sensor’ R/C equivalent circuit to decouple components that drift from the ones that represent the response to the gas, in support of drift masterarbeit ghostwriter. Thanks to its versatile analytical instruments and availability of on-board Interdigitated Electrodes, SCA is also an excellent experimental board for new sensitive materials. Several SCAs can be installed onto long cables for large area continuous monitoring.
Specifications
ELECTRICAL
Supply Voltage
1.5-3.6V
Max Current
1.4mA continuous when reading on-chip sensors with EIS
Size
5.5×3.9mm
Interface
I3C or SENSIBUS, single data wire multidrop sensor array cable interface, 1.5-3.6V
Unique Identifier
OTP 48bits Unique Device Identifier, 16bits User Defined
ELECTRICAL IMPEDANCE SPECTROSCOPY
Frequency
3.1mHz to 1.2MHz
Vpp output sinewave
156mV to 2.8Vpp
Coherent demodulation
1st, 2nd or 3rd harmonic
Output
Reciprocal of real or imagery component
Wide Measurement Range
From ohms to 100MΩ
TEMPERATURE
Range
-40°C to 125°C
Accuracy
±0.1°C
POLYMMIDE
Detects
Relative Humidity, Vapors
Range
0% to 100%
Accuracy
±0.5%
ALUMINUM OXIDE
Detects
Ionized Particles and Vapors, i.e. Acids, Ammonia dissolved in water
Limit of detection
1ppm Ammonium
HEATED TIN OXIDE
Detects
Air contaminants, Flammables, Cigarette smoke
Limit of detection
100ppb H2
Measurements
Open Data
The following data is made available to data scientists, AI developers and it is free to use. The datasets have been acquired with the SCA air sensor and the SLM-Studio software, these are the same data we use to train our own machine learning models.
Please, feel free to share with us results of your investigations.