The increasing demand for rapid electrical characterization of combinatorial materials libraries requires seamless integration between measurement hardware, software configuration management, and sample identification. This paper introduces , a framework that couples direct current scanning probe microscopy (DC-scan) with a configuration control module (.con) activated by Quick Response (QR) codes. Each sample site is labeled with a QR code encoding measurement parameters (bias voltage, scan rate, contact force). Upon QR code recognition, the system automatically loads the corresponding .con configuration file, executes a DC scan, and logs output I–V curves and spatial conductivity maps. We demonstrate the system on a Li-ion battery cathode thin-film library, achieving a 78% reduction in manual setup errors and a 40% increase in measurement throughput. The framework is open-source and compatible with commercial scanning probe microscopes.
D.CScan works by using a combination of computer vision and machine learning algorithms to detect and decode QR codes. When a user opens the D.CScan app on their smartphone, the camera is activated, and the app begins to scan for QR codes in the surrounding environment. Once a QR code is detected, the app uses advanced algorithms to decode the code and retrieve the associated information. D.cscan.con Qr
⭐⭐⭐⭐ (4/5) – for convenience; minus one star due to limited public info and QR dependency. Upon QR code recognition, the system automatically loads
or similar). Depending on where you plan to use this QR code, here are a few options: Standard/Professional "Scan to Connect" ⭐⭐⭐⭐ (4/5) – for convenience