Detecting Spatial Defects in Colored Patterns with Coupled Self-Oscillating Gels

With the growing demand for wearable computers, there is a need for materials systems that can perform computational tasks without relying on external electrical power. Using theory and simulation, we design a materials system that “computes” by integrating the inherent behavior of self-oscillating gels undergoing the Belousov–Zhabotinsky (BZ) reaction and piezoelectric (PZ) plates. These “BZ-PZ” units are connected electrically to form a coupled oscillator network, which displays specific modes of synchronization. We exploit this attribute in employing multiple BZ-PZ networks to perform pattern matching on complex multi-dimensional data, such as colored images. By decomposing a colored image into sets of binary vectors, we use each BZ-PZ network, or “channel”, to store distinct information about the color and the shape of the image and perform the pattern matching operation. Our simulation results indicate that the multi-channel BZ-PZ device can detect subtle differences between the input and stored patterns, such as the color variation of one pixel or a small change in the shape of an object. To demonstrate a practical application, we utilize our system to process a colored QR code and show its potential in cryptography and steganography.