Kionix Productdetail
KXR94-7050
Tri-Axis, 1.0g - 4g, Multiplexed Analog and Digital (SPI), 5x5x1.2mm DFN - KXR94-7050
The KXR94 is a high-performance, ultra-low noise, tri-axis accelerometer offering multiplexed analog or SPI digital communications, an integrated 4-channel multiplexer and a factory-programmable low-pass filter. The KXR94 offers a g-range of ±1g to ±4g and operates from a 2.5 V to 5.25 V DC supply, both factory-programmable. It is in a 5 x 5 x 1.2 mm, 14-pin, DFN package with an operating temperature range of -40°C to +85°C.
Highlights
- Our best-selling high performance part
- Extremely low noise
- Excellent performance over temperature
- Successfully Utilized in Multiple Automotive and Consumer Applications
Product Specifications
| Axis | G Range | Sensitivity | Noise (µg/√Hz) | Resolution | Package Size | Pins | Package Type | Interface Output | Wakeup | Operating Temperature (Min.)[°C] | Operating Temperature (Max.)[°C] | Supply Voltage [V] | Current Consumption |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 3 | 2g | 660, (mV/g) | - | 8-bit, 12-bit | 5x5x1.2mm | 14-pin | DFN | Multiplexed Analog | No | -40 | 125 | 3.3 | 0.82 - 1.15 mA |
EVALUATION BOARDS
| PART NUMBER | BUY NOW | DESCRIPTION | DOCUMENTATION |
|---|---|---|---|
| EVAL-KXR94-7050 |  |
KXR94-7050 Evaluation Board (Legacy) |
KAMMDM001R32 Schematic (KX_94) (Legacy) KAMMDM001R32 Board Layout (KX_94) (Legacy) |
Developer Tools
| Buy Now | Description | |
|---|---|---|
| IoT Evaluation and Development Kit | |
Kionix's IoT evaluation kit utilizes hardware platform based on Nordic Semiconductor's Bluetooth LE SoC. The compact (27/32mm x 4.2mm), highly integrated modular sensor system integrates Kionix's accelerometer (KX122-1037), combo accel-mag (KMX62-1031), and combo accel-gyro (KXG07) sensors along with ROHM's barometric pressure sensor (BM1383AGLV). Additional sensors can be evaluated using the add-on board that can fit inside the kit. This enables measurement of 3D acceleration, 3D magnetism, 3D rotation, air pressure, and temperature, making it ideal for training, prototyping, and initial set development of IoT and wearable applications. |
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