Development and Optimization of Terahertz Detection Systems

Abstract

Terahertz (THz) technology, occupying the spectral range between microwaves and infrared radiation (0.1–10 THz), has rapidly emerged as a compelling focus of scientific and engineering research. Characterized by its non-ionizing nature, strong penetration through non-metallic materials, and high sensitivity to molecular composition and water content, THz radiation offers significant potential across a broad spectrum of applications.

THz detection systems form the foundational core of THz technology platforms, serving the critical function of converting incident terahertz radiation into quantifiable electrical signals. The effectiveness and applicability of THz technology depend heavily on the performance of these detection systems. However, current THz detection technologies remain limited in several critical aspects, including sensitivity, accuracy, temporal resolution, and scalability. Specifically, weak interaction between THz waves and detectors often restricts signal detection, while environmental noise and material inconsistencies reduce measurement fidelity. Furthermore, the relatively slow response times hinder the real-time capture of dynamic biological and communicational processes. These challenges pose substantial barriers to the development of high-performance THz systems, constraining the practical implementation of THz technology's immense potential across various fields.

In response to these challenges, this research presents a comprehensive exploration of advanced THz detection strategies, introducing multiple technological innovations aimed at achieving accurate, sensitive, fast, compact, and cost-effective THz detection solutions. Central to this work is the design of a novel graphene-integrated microbolometer, forming the core of a THz Microbolometer Array Imaging System (MAIS). This microbolometer features an optimized structural design and tailored material composition, significantly improving responsivity, detectivity, and response time. This innovative microbolometer design not only sigfinicantly enhances the THz detection performance, but also establishes a solid foundation for advancing THz imaging applications. Complementing detection methodology development, a Micro Circular Log-Periodic Antenna (MCLPA) was designed and optimized using a custom-developed Evolutionary Neural Network (ENN). This algorithm-driven approach enables efficient optimization of the sophisticated antenna design, resulting in a compact structure with broad bandwidth, high gain, and optimal impedance matching. This ENN-driven MCLPA represents a significant breakthrough in THz antenna engineering, introducing a transformative design paradigm that synergistically integrates algorithmic intelligence with structural innovation.

In conclusion, this work significantly contributes to overcoming key limitations in THz detection by integrating advancements in novel device architecture, advanced material engineering, and innovative algorithm-driven design methodology. These innovations collectively enhance sensitivity, accuracy, response speed, system compactness and cost-effectiveness, representing a considerable step forward in the performance of THz detection systems. Beyond technical improvements, the results provide a solid foundation for practical implementation in biomedical and other high-impact applications. Overall, the contributions made herein substantially advance the development of THz technology and offer promising pathways for its transformative application across scientific, industrial and clinical fields.