Gas Sensors

Image Part Number Description / PDF Quantity Rfq
SGX-4H2S

SGX-4H2S

Amphenol

4 SERIES H2S SENSOR - 100PPM

93

VQ31MB

VQ31MB

Amphenol

PELLISTOR PR 3.5V/90MA TC C CAN

14

VQ641TS/1

VQ641TS/1

Amphenol

VQ41 PELLISTOR VQ600 HEAD, METRI

23

VQ635M/1

VQ635M/1

Amphenol

VQ35 PELLISTOR VQ600 HEAD, METRI

0

IR12GJ

IR12GJ

Amphenol

19MM, HYDROCARBON INFRARED GAS S

10

VQ21TB

VQ21TB

Amphenol

PR PELLISTOR PR, 2V/300MA OC SOL

180

VQ631M/3

VQ631M/3

Amphenol

VQ31 PELLISTOR, VQ600 HEAD, 0.75

0

VQ635M/2

VQ635M/2

Amphenol

VQ35 PELLISTOR, VQ600 HEAD, 0.5"

0

VQ601/3

VQ601/3

Amphenol

VQ1 PELLISTOR, VQ600 HEAD, 0.75"

0

IR11GM_1

IR11GM_1

Amphenol

16MM,0-5% VOLUME CO2 INFRARED GA

4

VQ631M/2

VQ631M/2

Amphenol

VQ31 PELLISTOR, VQ600 HEAD, 0.5"

0

VQ606M/3

VQ606M/3

Amphenol

VQ6 PELLISTOR, VQ600 HEAD, 0.75"

0

VQ547TS

VQ547TS

Amphenol

VQ47 AMMONIA SENSOR, VQ500 HEAD

45

EC4-20-SO2

EC4-20-SO2

Amphenol

4 SERIES SO2 GAS SENSOR 20PPM

11

VQ621T/2

VQ621T/2

Amphenol

VQ21 PELLISTOR, VQ600 HEAD, 0.5"

0

INIR-RF-R290

INIR-RF-R290

Amphenol

INTEGRATED GAS SENSOR -R290

25

VQ546MR

VQ546MR

Amphenol

VQ46 PELLISTOR, VQ500 HEAD, +VE

34

IR11EM

IR11EM

Amphenol

16MM, 0-5% VOLUME CO2 INFRARED G

23

VQ621T/1

VQ621T/1

Amphenol

VQ21 PELLISTOR VQ600 HEAD, METRI

21

VQ641TS/3

VQ641TS/3

Amphenol

VQ41 PELLISTOR, VQ600 HEAD, 0.75

0

Gas Sensors

1. Overview

Gas sensors are detection devices that identify and measure gas concentrations in the environment. They convert chemical interactions with gas molecules into electrical signals for quantitative analysis. These sensors play a critical role in industrial safety, environmental monitoring, healthcare, and smart home systems by preventing gas leaks, ensuring air quality, and enabling process control.

2. Major Types and Functional Classification

TypeFunctional FeaturesApplication Examples
ElectrochemicalHigh accuracy, stable baseline, requires oxygenCO detectors, O2 monitors
SemiconductorLow cost, broad detection range, temperature-dependentIndoor air quality sensors
Catalytic CombustionExplosive gas detection, requires periodic calibrationIndustrial methane detectors
Infrared (IR)Non-contact measurement, high selectivityCO2 HVAC monitoring
Photoionization (PID)VOC detection at ppm levels, UV lamp requiredEnvironmental pollution monitoring

3. Structure and Components

A typical gas sensor consists of: - Sensing element (metal oxide/electrolyte membrane) - Signal conditioning circuit (amplifier, ADC) - Housing with gas inlet ports - Temperature/humidity compensation module - Communication interface (UART/I2C)

4. Key Technical Specifications

ParameterDescription
Detection RangeMeasurable gas concentration span (ppm to %LEL)
SensitivitySignal change per gas concentration unit (mV/ppm)
Response TimeT90 response speed (3-300 seconds)
AccuracyMeasurement error margin ( 2-10%)
Operating TemperatureFunctional range (-20 C to +50 C typical)
Long-term StabilityDrift specification (5-15% per year)

5. Application Fields

  • Industrial safety: Fixed gas detection systems
  • Environmental monitoring: Urban air quality stations
  • Healthcare: Medical breath analyzers
  • Smart homes: Combustible gas alarms
  • Automotive: Cabin air quality management

6. Leading Manufacturers and Products

ManufacturerProduct SeriesKey Features
HoneywellXNX Universal TransmitterDual-sensor redundancy
Figaro EngineeringTGS2600Low-power VOC detection
MembraporToxic Gas SensorsEletrochemical cells for Cl2
SenseairK-30 CO2 ModuleNDIR technology, 30ppm accuracy
AMS (Austria)ENS160 MOX SensorAI-based gas discrimination

7. Selection Guidelines

Key consideration factors:

  1. Target gas chemical properties
  2. Environmental conditions (temperature/humidity range)
  3. Required detection threshold and repeatability
  4. Power consumption budget
  5. Maintenance accessibility for calibration
  6. Cost vs. lifetime trade-offs

Industry Trends Analysis

Emerging development trends include: - Miniaturization through MEMS technology - Multi-gas detection using AI pattern recognition - Wireless self-powered IoT sensor nodes - Enhanced selectivity via nanomaterial coatings - Reduced cross-sensitivity through hybrid sensing methods

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