Testing GaN for the Next Generation of Power Electronics

Gallium nitride (GaN) power devices are rapidly transitioning from an emerging technology to a critical component enabling high-efficiency power conversion. As applications such as AI infrastructure, data centers, robotics and electrification demand higher efficiency, higher power density and faster switching, how GaN devices are tested is becoming more and more important.

To learn how semiconductor testing is changing with GaN technology, Accotest’s Global Marketing Director Huipeng Liu was interviewed. Accotest is a leading automated test equipment (ATE) manufacturer with extensive experience in semiconductor production testing.

From silicon-based testing to GaN-specific test architectures

The evolution of GaN testing parallels the evolution of the technology itself.

Initially, when GaN power devices were produced, they were frequently treated as conventional silicon discrete devices. But this soon proved to be not enough. Because GaN devices can switch at much higher speeds and combine low conduction losses with very fast transient behavior, their test requirements are fundamentally different from those of conventional silicon power semiconductors.

This is why the test platforms have evolved in the last decade to architectures that are specific to wide-bandgap devices.

One of the big developments is the ability to combine conventional static parametric measurements with dynamic measurements in the same production test environment (Figure 1). This is especially important for GaN, where parameters like on-resistance alone are not sufficient to fully describe device behavior under switching conditions.

Figure 1: Test challenges include dynamic R_DS(ON) test capability. (Source: AccoTest)

Modern test solutions can combine static testing with dynamic R_DS(ON) measurements and support multi-site configurations. This enables testing of several devices in parallel while maintaining the accuracy and repeatability of the measurements as in the production environments.

This evolution also reflects the diversity of GaN architectures entering the market today. The testing requirements can be quite different depending on the type of device (GaN FET, monolithic GaN IC, co-packaged device, bridge configuration, or other integrated implementations).

The message is clear: GaN testing needs an open, flexible test architecture, not the traditional discrete-device approaches.

Dynamic R_DS(ON) becomes a critical measurement

One of the most important challenges in GaN testing is accurately measuring R_DS(ON), particularly as device resistance continues to decrease.

For low-voltage and high-current applications, even a small increase in on-resistance can translate into significant conduction losses. At the same time, GaN's fast switching characteristics make dynamic measurements considerably more challenging than conventional static resistance measurements.

Dynamic R_DS(ON) testing therefore needs to account for the device's behavior under realistic switching conditions. The measurement system must capture the relevant voltage and current characteristics without introducing excessive parasitic effects or measurement errors.

This is especially important as GaN technology moves toward increasingly low microOhm-level on-resistance. At these resistance levels, the measurement environment itself can become a significant part of the measurement problem.

Test fixtures, interconnects, switching loops, instrumentation bandwidth, timing, and measurement algorithms all influence the result.

For production testing, this creates a demanding combination of requirements: high measurement accuracy, high throughput, repeatability, and the ability to perform dynamic measurements without compromising device integrity.

Reliability starts with the test method

Reliability is another critical dimension of GaN testing, particularly in applications where power devices operate continuously and at high switching frequencies.

AI data centers provide a good example. Power conversion systems supporting AI computing must operate efficiently while handling demanding electrical and thermal conditions. Any weakness in the power semiconductor can ultimately affect system availability and operating cost.

Testing therefore has two objectives. The first is to identify devices that do not meet the required electrical and performance specifications. The second is to ensure that the testing process itself does not introduce additional electrical or thermal stress that could compromise device reliability.

This distinction is particularly important for GaN because its fast-switching behavior can generate high dv/dt and di/dt. A poorly designed test environment can introduce overshoot, ringing, excessive transient stress, or other conditions that are not representative of normal device operation.

A production test system must therefore be designed not only to measure the device accurately, but also to control the electrical environment in which that measurement takes place.

This makes the test platform part of the overall reliability strategy.

Wafer-level testing and yield optimization

Testing is also moving earlier in the semiconductor manufacturing process.

Wafer-level testing can provide valuable information about device performance and process variation before devices proceed through subsequent manufacturing stages. For GaN, this is particularly useful because parameters such as leakage current and on-resistance can provide important indicators of device quality.

Leakage current is especially relevant when devices are evaluated at elevated voltage and temperature. Small variations in leakage can become more significant as operating voltage increases, making accurate high-voltage measurements essential.

R_DS(ON) is another critical parameter. As the target resistance moves into the microOhm range, measurement accuracy becomes increasingly challenging. The test system must distinguish the actual device characteristics from resistance introduced by probes, interconnects, contacts, and the measurement setup.

Accurate wafer-level measurements can therefore contribute directly to yield optimization by helping identify process variations and defective devices earlier in the manufacturing flow.

Testing as a competitive advantage

As GaN becomes more widely adopted, semiconductor testing is no longer simply a final manufacturing step. It is becoming an important element of the competitive equation.

Higher device performance creates more demanding test requirements. Faster switching, lower R_DS(ON), higher operating voltages, and increasingly sophisticated integration all require more capable measurement systems.

At the same time, production volumes are increasing. Test equipment must therefore deliver both technical performance and economic efficiency.

Multi-site testing is one way to address this challenge. By testing several devices simultaneously, manufacturers can increase throughput without proportionally increasing the test footprint.

However, multi-site testing introduces its own challenges. Measurement channels must be highly synchronized, parasitic effects must be controlled, and the system must maintain consistent performance across all sites.

The objective is not simply to test more devices simultaneously, but to do so while maintaining the same level of measurement confidence.

Figure 2: Example of dynamic R_DS(ON) waveforms soft switching and hard switching. (Source: AccoTest)

From better devices to better applications

The future development of GaN will depend on more than improvements to the semiconductor itself.

Device technology, packaging, gate-drive techniques, magnetics, thermal management, testing, and system architecture are increasingly interconnected. Improvements in one area can enable advances in another.

For GaN, this interaction is particularly visible in high-frequency and high-power applications. The ability to switch faster and reduce losses creates new opportunities, but realizing those benefits at system level requires the entire power-conversion architecture to evolve accordingly.

This is especially relevant for emerging applications such as AI infrastructure and humanoid robotics. These systems require compact, efficient, reliable power conversion and can benefit significantly from the combination of GaN's high switching performance and low conduction losses.

Ultimately, the most important question is not simply how to manufacture a better GaN device, but how to use GaN more effectively within the complete power system.

EPC and AccoTest join forces to build A GaN testing ecosystem

The collaboration between EPC and AccoTest focuses on a practical challenge in GaN manufacturing: accurately testing devices whose electrical characteristics and switching behavior increasingly exceed the capabilities of conventional discrete-device test methods.

As EPC continues to develop GaN devices for high-frequency and high-power-conversion applications, the test methodology must evolve with the device technology. In particular, low R_DS(ON), fast switching transients, and the need for reliable measurements at elevated voltage and temperature place specific requirements on the test system.

AccoTest's experience with GaN production testing provides a test architecture capable of addressing these requirements. The approach combines static parametric measurements with dynamic measurements, including dynamic R_DS(ON), and supports multi-site configurations for production environments.

This is relevant to EPC because measurements at very low resistance levels are increasingly sensitive to the complete electrical path used during the test. Contact resistance, interconnect parasitics, measurement timing, current levels, and voltage-sensing techniques can all influence the measured value. A suitable test architecture must therefore minimize these effects and provide repeatable results across devices and test sites.

The collaboration also extends to the characterization of GaN devices during production. Measurements such as leakage current and R_DS(ON), particularly under higher-voltage and higher-temperature conditions, provide important information for evaluating device performance and identifying process variation.

For EPC, the objective is not simply to increase test throughput. The test system must provide data that can be correlated with actual device performance while maintaining the electrical conditions required to avoid introducing unwanted stress during measurement.

This becomes increasingly important as GaN devices move toward higher levels of integration and more demanding operating conditions. The testing environment must accommodate different device configurations while maintaining measurement accuracy, repeatability, and production efficiency.

By working together on these test requirements, EPC and AccoTest are addressing the testing challenges that arise directly from the electrical characteristics of GaN technology. The focus is on developing a production test approach that can support accurate device characterization as GaN performance continues to advance.