| Image | Part Number | Description / PDF | Quantity | Rfq |
|---|---|---|---|---|
 |
Maxim Integrated |
EVAL KIT MAX8606 (USB/AC ADAPTER |
8 |
|
|
Maxim Integrated |
EVAL MAX17311 MODELGAUGE |
219 |
|
|
Maxim Integrated |
EVAL KIT DS8007 (MULTIPROTOCOL D |
7 |
|
|
Maxim Integrated |
EVAL KIT MAX8713 (SIMPLIFIED MUL |
15 |
|
|
Maxim Integrated |
EVALUATION KIT/TWO-CHANNEL, I2C, |
10 |
|
|
Maxim Integrated |
EVKIT FOR 5KV ISOLATED CAN |
21 |
|
|
Maxim Integrated |
EVAL KIT FOR MAX77829 |
9 |
|
|
Maxim Integrated |
EVAL KIT MAX5391 (DUAL 256-TAP, |
25 |
|
|
Maxim Integrated |
EVAL KIT MAX6951 (SERIALLY INTER |
11 |
|
|
Maxim Integrated |
KIT EVALUATION FOR DS2745 |
20 |
|
|
Maxim Integrated |
LOW-POWER, TINY, DUAL IO-LINK DE |
510 |
|
|
Maxim Integrated |
LOOP POWERED 4-20MA CURRENT LOOP |
15 |
|
|
Maxim Integrated |
EVKIT FOR ULTRA-SMALL, LOW-RON, |
320 |
|
|
Maxim Integrated |
EVAL KIT MAX5392 (DUAL, 256-TAP, |
10 |
|
|
Maxim Integrated |
EVKIT FOR HOMEBUS TRANSCEIVER |
318 |
|
|
Maxim Integrated |
EV KIT FOR HIGH-ACCURACY 12-/16- |
311 |
|
|
Maxim Integrated |
EVKIT FOR TDFN STAND-ALONE MODEL |
34 |
|
|
Maxim Integrated |
EVKIT FOR PMIC WITH ULTRA LOW IQ |
13 |
|
|
Maxim Integrated |
EVAL KIT MAX17048(MODELGAUGE 1-C |
7 |
|
|
Maxim Integrated |
EVKIT OF MAX33040E, 3.3V, 2MBPS |
318 |
|
Evaluation and Demonstration Boards and Kits are hardware platforms designed to facilitate the development, testing, and demonstration of electronic systems. They serve as critical tools for engineers and developers to prototype applications, validate designs, and accelerate time-to-market. These boards integrate processors, sensors, communication interfaces, and software ecosystems, enabling rapid experimentation across diverse industries such as IoT, automotive, and industrial automation.
| Type | Functional Features | Application Examples |
|---|---|---|
| Microcontroller Development Boards | Embedded CPUs, GPIOs, integrated peripherals | IoT devices, robotics |
| FPGA Evaluation Boards | Reconfigurable logic, high-speed interfaces | Communication systems, AI accelerators |
| Sensor Expansion Kits | Multi-sensor integration (temperature, motion, etc.) | Smart agriculture, environmental monitoring |
| Wireless Communication Modules | Bluetooth/Wi-Fi/LoRa protocols, antenna interfaces | Connected healthcare, smart cities |
Typical architecture includes: - Processing Units: Microcontrollers, FPGAs, or SoCs - Memory: RAM, Flash, EEPROM - Interfaces: USB, UART, SPI, I2C, Ethernet - Power Management: Regulators, battery connectors - Software Stack: SDKs, device drivers, IDEs Physical designs often feature standardized form factors (e.g., Arduino Uno, Raspberry Pi HATs) for modular expansion.
| Parameter | Description |
|---|---|
| Processor Performance (MHz/GHz) | Determines computational capability |
| Memory Capacity (RAM/Flash) | Affects program complexity and data storage |
| Interface Types | Dictates peripheral compatibility |
| Power Consumption (mW/MHz) | Critical for battery-operated devices |
| Operating Temperature (-40 C to +85 C) | Defines environmental durability |
- Internet of Things (IoT): Smart home controllers, edge AI nodes - Automotive: ADAS sensor fusion platforms - Industrial Automation: PLC controllers, predictive maintenance systems - Consumer Electronics: Wearables, AR/VR prototypes
| Manufacturer | Representative Products |
|---|---|
| STMicroelectronics | STM32 Nucleo Series, SensorTile Kit |
| Intel | Intel Edison, Movidius Neural Compute Stick |
| Xilinx | Zynq UltraScale+ MPSoC Evaluation Kit |
| Arduino | Arduino MKR Series, Nano 33 IoT |
Key considerations: 1. Match processor capabilities to application complexity 2. Verify interface compatibility with target peripherals 3. Assess software ecosystem maturity (e.g., ROS support) 4. Evaluate power budget requirements 5. Consider long-term availability and community support
- Growing adoption of RISC-V-based evaluation platforms - Integration of AI/ML accelerators in edge computing boards - Expansion of open-source hardware ecosystems - Increased focus on energy-efficient architectures for IoT - Standardization of form factors (e.g., SparkFun's Qwiic system)