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SOLUTION
IV/CV DC Testing
1. Test Platform Setup: Centered around a high-precision probe station, the setup is complemented by measurement instruments such as a DC power supply/source meter, an LCR meter (for CV testing), and a low-noise oscilloscope, with system integration achieved via interfaces like GPIB/LAN.
(1) Core equipment: High-precision probe station (equipped with sub-micron positioning system and vacuum-chuck stage), DC source meter (accuracy ≥ 0.1%), LCR meter (frequency range: 1 kHz – 1 MHz), and temperature control module (optional, -55°C to 125°C).
2. Key Component Matching: Select appropriate probes (such as beryllium-copper or tungsten probes) based on the test object, and pair them with either a vacuum- or electrostatically actuated stage to securely hold the sample in place. Optionally, incorporate a temperature-control module to simulate various operating temperatures.
3. Test Process Design: Implement automated testing through software programming (e.g., LabVIEW), covering the entire workflow from probe contact and parameter setup to data acquisition, curve plotting (such as I-V and C-V characteristic curves), and final report generation.
Core pain points addressed and key technical highlights
- Contact reliability: Employs a high-precision probe positioning system (sub-micron level) and carefully controls probe pressure (typically 1–50 g) to prevent sample damage or poor contact.
Photoelectrical performance testing typically includes tests in the following areas:
1. Photoelectric Response Characterization: By providing a light source to the optoelectronic device, we measure its ability to respond to optical signals, including tests of parameters such as photocurrent, photovoltage, and photoelectric conversion efficiency.
2. Spectral Characterization Testing: Measures the response of optoelectronic devices across different wavelength ranges to assess their sensitivity and selectivity toward various wavelengths of light signals.
3. Device parameter testing: This includes measuring electrical parameters such as resistance, capacitance, and inductance of optoelectronic devices to evaluate their electrical performance.
4. Response Time Testing: Measures the speed at which optoelectronic devices respond to light signals, including tests of parameters such as rise time and fall time.
Currently, a major challenge widely encountered is how to efficiently perform testing at the optical chip level. During optical chip testing, its coupling Low efficiency, significant coupling losses, and an insufficient level of test automation have become widespread concerns. In particular, stress tests conducted under non-operational conditions require maintaining prolonged exposure to extreme high- and low-temperature environments. For instance, a high-density integrated LED array like Micro-LED, where pixel pitches are on the order of 10 micrometers, requires a high-pixel, high-magnification microscope—and demands precise alignment and positioning of probes and probe holders.
- Process Navigation: Use parameters to quantify process outcomes, quickly identify deviations in steps like lithography and doping, and accelerate process optimization.
- Performance verification: Measured the switching, on-state, and other performance characteristics, as well as interface quality, of the new device to validate design rationale and reduce trial-and-error costs.
- Reliable early warning: Combining environmental simulation tests, we predict failure risks under extreme conditions by analyzing parameter variations, thereby supporting robust reliability design.
II. Production Side: Testing and Quality Control
- Batch Sorting: Automated wafer-by-wafer testing ensures efficient screening of qualified devices, perfectly aligned with mass production timelines.
- Process Monitoring: Statistically analyze batch parameter variations, continuously track process stability in real time, and prevent mass defects.
- Cost reduction: Eliminate defects before encapsulation to minimize wasteful investments; support device grading to enhance added value.
III. Analysis Endpoint: Characterizing the Localization Problem
- Failure Analysis: Identify fault types by analyzing abnormal curves, delving into root causes such as oxide layer breakdown and interface defects.
- Feature溯源: Restore the extent of device performance degradation, compare device quality across different suppliers, and support selection decisions.
- Mechanism Insights: Extract key microscopic physical information—such as fixed charge density and interface-state effects—from the parameters, enabling deeper mechanistic studies.