With the growing demand for wearable computers, there is a need for material systems that can perform computational tasks without relying on external electrical power. Using theory and simulation, we… Click to show full abstract
With the growing demand for wearable computers, there is a need for material systems that can perform computational tasks without relying on external electrical power. Using theory and simulation, we design a material 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 Quick Response code and show its potential in cryptography and steganography.With the growing demand for wearable computers, there is a need for material systems that can perform computational tasks without relying on external electrical power. Using theory and simulation, we design a material 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 patter...
               
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