EFM32LG230F256G-E-QFN64 - 48MHz 32-bit ARM Cortex-M3 MCU | Silicon Labs
MPN: EFM32LG230F256G-E-QFN64 ✓ Active| Qty | Unit Price | Extended |
|---|---|---|
| 1 | $9.14 | $9.14 |
| 10 | $8.41 | $84.10 |
| 100 | $7.05 | $705.00 |
| 500 | $6.12 | $3,060.00 |
| 1,000 | $5.28 | $5,280.00 |
EFM32LG230F256G-E-QFN64 Overview
A microcontroller (MCU) is a single integrated semiconductor device that contains a CPU core, program memory (Flash), working memory (RAM), and a rich set of on-chip peripherals such as timers, ADC/DAC blocks, communication interfaces, and GPIO. Within the broader embedded computing taxonomy, MCUs belong to the system-on-chip hyperplane - integrating compute (control, timing), analog/mem (memory hierarchy), energy efficiency (low-power modes), and connectivity (UART, SPI, I2C, USB) on a single die. The Cortex-M3 core implements the Thumb/Thumb-2 instruction set, features hardware integer divide, jitter, and includes a Nested Vectored Interrupt Controller (NVIC) for deterministic interrupt response. EFM32 Leopard Gecko devices add energy-aware peripherals that can operate autonomously while the CPU is asleep.
Key features of the EFM32LG230F256G-E-QFN64 include 256 KB Flash program memory, 32 KB SRAM, low-energy autonomous peripherals, fast wake-up from sleep modes, brown-out detector, and on-chip temperature sensor. Peripheral highlights include four 16-bit timers, multiple USART/SPI/I2C peripherals, a 12-bit ADC, and a hardware AES accelerator. The wide operating voltage range and low-power architecture allow direct battery operation with years of battery life in duty-cycled applications.
Typical use cases are wireless sensor nodes, smart meters, home and building automation, asset tracking, fitness and medical wearables, industrial IoT edge nodes, and battery-powered HMI controllers. Selection guidance: choose this part when you need ARM Cortex-M3 ecosystem maturity combined with Silicon Labs' energy-friendly architecture in a moderate-pin-count QFN package.
Drop-in alternatives for EFM32LG230F256G-E-QFN64 — same package, pin-to-pin compatible. Different-package parts requiring PCB rework are excluded.
Quick Comparison Tool — Select alternative parts for side-by-side comparison:
EFM32LG230F256G-F-QFN64R
✅ Drop-In📋 Reference alternative (not in catalog)
EFM32GG230F1024-QFN64T
✅ Drop-In📋 Reference alternative (not in catalog)
EFM32LG330F256G-F-QFN64R
✅ Drop-In ⚠️ Specs Unverified📋 Reference alternative (not in catalog)
EFM32LG230F128G-E-QFN64
✅ Drop-In ⚠️ Specs Unverified📋 Reference alternative (not in catalog)
EFM32LG230F64G-E-QFN64
✅ Drop-In ⚠️ Specs Unverified📋 Reference alternative (not in catalog)
EFM32LG230F256G-E-QFN64 Maximum Ratings & Electrical Characteristics
| Core | ARM Cortex-M3 |
| Core Architecture | 32-bit RISC |
| Maximum CPU Frequency | 48 MHz |
| Program Memory (Flash) | 256 KB (256K x 8) |
| RAM | 32 KB |
| Active Mode Current | 211 microA/MHz |
| Stop Mode Current | 0.65 microA (per datasheet) |
| GPIO Pins | 56 (digital I/O) |
| Package | 64-QFN (9x9 mm) |
| Mounting Type | Surface Mount |
| Timers | 4x 16-bit (per product brief) |
| Debug Interface | 2-pin Serial Wire Debug + Embedded Trace Module (ETM) |
| ADC | On-die 12-bit ADC |
| RoHS Status | Compliant |
EFM32LG230F256G-E-QFN64 64-qfn (9x9 mm) Pin Configuration Guide
Pin configuration for EFM32LG230F256G-E-QFN64 (64-qfn (9x9 mm) package). This digital IC includes GPIO, communication interfaces (UART, SPI, I2C), and power pins. Refer to the manufacturer datasheet for alternate pin functions and configuration options. Essential for embedded system design and PCB layout.
No detailed pinout data available for EFM32LG230F256G-E-QFN64.
Refer to the datasheet for full pin configuration.
Typical Applications
EFM32LG230F256G-E-QFN64 is suitable for 7 applications: Battery-Powered Wireless Sensor Nodes, Smart Meter Data Concentrators, Home and Building Automation Hubs, Industrial IoT Edge Gateways, Fitness and Medical Wearables, Asset Tracking and Logistics Devices, Battery-Powered HMI Controllers.
Battery-Powered Wireless Sensor Nodes
The EFM32LG230F256G-E-QFN64 fits battery-powered wireless sensor nodes because of 0.65 microA Stop-mode consumption and 211 microA/MHz active consumption per the Silicon Labs EFM32LG datasheet. Autonomous low-energy peripherals run while the CPU sleeps, allowing sensor sampling and radio duty cycling without CPU intervention. Fast wake-up time of a few microseconds keeps energy overhead low. Choose this part when 256 KB Flash is enough for the application stack and years of coin-cell battery life are required.
Recommended
Smart Meter Data Concentrators
The EFM32LG230F256G-E-QFN64 supports smart meter data concentrators with 256 KB Flash for communication stacks (modbus, DLMS/COSEM) and 32 KB RAM for buffering consumption data. 56 GPIO pins support metering pulse counters, tamper switches, and LCD segment drivers. The Cortex-M3 core plus on-die 12-bit ADC enables accurate measurement of consumption waveforms. Industrial temperature grade and brown-out detector suit harsh meter-cabinet environments.
Recommended
Home and Building Automation Hubs
The EFM32LG230F256G-E-QFN64 fits home and building automation hubs because of 256 KB Flash for Zigbee/Thread/BLE stacks, multiple USART/SPI/I2C peripherals for sensor interfaces, and 56 GPIO for user-interface buttons and displays. Low-energy modes allow always-on listening while the CPU sleeps, drawing under 1 microA. The QFN-64 footprint integrates cleanly into compact wall-switch and thermostat form factors with minimal external components.
Recommended
Industrial IoT Edge Gateways
The EFM32LG230F256G-E-QFN64 supports industrial IoT edge nodes that aggregate sensor data and forward to cloud services via Ethernet or cellular modems. 256 KB Flash holds TLS stacks and MQTT/HTTP clients, while 32 KB RAM buffers messages during network outages. Cortex-M3 deterministic interrupts handle time-critical sensor sampling. The -40C to +85C industrial temperature grade suits factory environments.
Recommended
Fitness and Medical Wearables
The EFM32LG230F256G-E-QFN64 supports fitness and medical wearables because of 0.65 microA Stop-mode current and autonomous low-energy peripherals that sample heart-rate and motion sensors without waking the CPU. The 256 KB Flash holds BLE stacks and sensor-fusion algorithms, while 32 KB RAM buffers motion data. The compact QFN-12 footprint fits into wrist-watch form factors with multi-day battery life.
Recommended
Asset Tracking and Logistics Devices
The EFM32LG230F256G-E-QFN64 fits asset-tracking devices that combine GPS, BLE, and accelerometer data because of 256 KB Flash for location-fusion firmware and 32 KB RAM for movement buffers. Low-energy modes enable always-on geo-fence monitoring while the CPU sleeps. The 56 GPIO pins support e-paper displays, buttons, and battery gauges. Long-life silicon revisions extend fleet longevity beyond standard EOL.
Recommended
Battery-Powered HMI Controllers
The EFM32LG230F256G-E-QFN64 supports battery-powered human-machine interface controllers with segment-LCD or small TFT displays. 256 KB Flash holds graphics libraries and menu logic; 32 KB RAM buffers display frames. 56 GPIO support touch-panel sensing, encoders, and LED indicators. Low-energy modes allow always-on touch sensing while the CPU sleeps, extending battery life in remote-control and thermostat applications.
Recommended
Recommended Products Summary
Engineering reference data for EFM32LG230F256G-E-QFN64 — comparison, design guidance, and compliance information.
Selection Guide
Comparison with Alternatives
| Parameter | This Product | EFM32LG230F256G-F-QFN64R | EFM32GG230F1024-QFN64T | EFM32LG330F256G-F-QFN64R | EFM32LG230F128G-E-QFN64 |
|---|---|---|---|---|---|
| Package | QFN-64 (9x9 mm) | QFN-64 (9x9 mm) - same | QFN-64 (9x9 mm) - same | QFN-64 (9x9 mm) - same | QFN-64 (9x9 mm) - same |
| Brand | Silicon Labs | Silicon Labs | Silicon Labs | Silicon Labs | Silicon Labs |
| Core | ARM Cortex-M3 | ARM Cortex-M3 | ARM Cortex-M3 | ARM Cortex-M3 | ARM Cortex-M3 |
| Maximum CPU Frequency | 48 MHz | 48 MHz | 48 MHz | 48 MHz | 48 MHz |
| Flash Memory | 256 KB | 256 KB | 1 MB | 256 KB | 128 KB |
| RAM | 32 KB | 32 KB | 128 KB | 32 KB | 32 KB |
| Stop Mode Current | 0.65 microA | 0.65 microA | 0.65 microA | 0.65 microA | 0.65 microA |
| GPIO Pins | 56 | 56 | 56 | 56 | 56 |
| Silicon Revision | E (standard) | F (long-life) | T (tape) | F (long-life) | E (standard) |
Key Differentiators
- Industry-leading 0.65 microA Stop-mode current for multi-year battery life (vs EFM32GG230F1024-QFN64T)
- Mature Cortex-M3 ecosystem with extensive middleware availability (vs EFM32LG230F128G-E-QFN64)
- Long-life silicon revision (F suffix) available in same footprint (vs EFM32LG230F256G-F-QFN64R)
Design Notes
Use the EFM32LG230F256G-E-QFN64's low-energy peripherals (LETIMER, LESENSE, LEUART) to keep the CPU asleep as much as possible. Per the Silicon Labs EFM32LG datasheet, Stop mode draws 0.65 microA; deeper EM4 (Shutoff) modes draw nanampere-level attenuation but require specific wake-up pin configuration. Always define energy-mode entry/exit sequences in firmware to avoid unintended current spikes during transitions.
At 48 MHz CPU, the device dissipates only a few milliwatts; thermal management is not a primary concern at typical ambient. However, in enclosed industrial enclosures with no airflow, the QFN-64 exposed pad must be soldered to a copper pour for thermal spreading. Estimated theta_JA for QFN-64 9x9 mm with 4-layer 1-oz copper is approximately 25 C/W per JEDEC EIA/JESD51 - acceptable for industrial use.
Place the 1 microF and 100 nF decoupling capacitors as close as possible to the VDD and VSS pins of the EFM32LG230F256G-E-QFN64. Per Silicon Labs reference designs, the QFN-64 exposed thermal pad must be soldered to a continuous ground plane via 9 thermal vias in a 3x3 array. Keep the SWDIO/SWCLK traces short and away from switching nodes to preserve signal integrity.
Estimated: the EFM32LG230F256G-E-QFN64's QFN-64 9x9 mm package has 56 GPIO pins - the discrepancy from 64 is because of dedicated VDD/VSS/RESET pins. Do not assume all 64 pads are GPIO; check the datasheet pinout table. Also, the Cortex-M3 MPU requires aligned memory regions - use the CMSIS pack definitions for proper alignment of interrupt vector tables and stack regions.
Compliance Information
RoHS compliant per Silicon Labs product page. Not AEC-Q100 qualified - choose AEC-Q100 qualified EFR32 variants for automotive applications. Conflict-minerals compliant per Silicon Labs CMRT filings.
