Design of Pixel Terahertz Metamaterial Absorber Sensor Based on an Improved Ant Colony Algorithm

In this article, a dual-band pixel terahertz (THz) metamaterial absorber sensor has been designed based on an improved binary ant colony optimization (IBACO) algorithm incorporating competitive learning and teaching learning mechanisms, which enable transcend the constraints of metamaterial absorber sensor methods that rely on a priori knowledge and design experience, leading to significant consumption of time and computational resources. Equivalent circuit model (ECM) theory and impedance matching theory, as well as further discussion of current and field distributions, are undertaken to elucidate the underlying physical mechanisms. Notably, the sensor demonstrates exceptional frequency selectivity and polarization independence, achieving absorption rates exceeding 97% at 0.6598 and 0.9443 THz, and sensitivities of 69.6 and 146.4 GHz/RIU, respectively, corresponding to figures of merit (FOMs) of 8.81 and 31.15, which positions the sensor as a viable candidate for applications in RF stealth and detection sensing. Compared to conventional design approaches, the proposed method facilitates the rapid development of sensors tailored to specific design objectives, thereby heralding new possibilities for designing high-performance THz and other electromagnetic (EM) devices.