A microwave microfluidic sensor for detecting binary liquid mixtures with a dielectric method at RF/microwave frequencies is presented in this article. The sensor is based on a split-ring resonator (SRR) that is implemented in a microstrip transmission line, with interdigitated electrodes (IDEs) being integrated into the ring for liquid detection. Based on the equivalent circuit of the IDE-SRR device and with a series of finite element simulations, the detection theory is developed, and the device design optimization is investigated. The validation measurements on water-isopropanol liquid mixtures with various concentrations show that the proposed IDE-SRR sensor has higher sensitivity than the previous standard SRR sensor. The IDE-SRR sensor is then used to detect two binary liquids, i.e., water-methanol mixtures and water-tetrahydrofuran mixtures. The measured effective permittivity results of the binary mixtures at RF/microwave frequency range are compared with the existing mixing models for binary dielectric mixtures at zero frequency.

Broadband dielectric spectroscopy measurements of biological materials within RF/microwave range can reveal cellular information, which is of important value in biological and medical researches. Here, we present a platform that combines a miniaturized coplanar waveguide (CPW) transmission line (TL) sensor and a special CPW-fed interdigitated capacitor (IDC), which allows us to measure the complex permittivity of cell cultures from 300 kHz to 50 GHz. The CPW-TL and CPW-IDC sensors are integrated with an SU-8 microfluidic channel, enabling measurements of microliter or even nanoliter volumes of liquids and suspensions. Due to the accurate alignment of the SU-8 polymer and the reliable liftoff fabrication procedure, we are able to minimize the measurement errors caused by the sensors' dimension tolerance. To ensure accurate complex permittivity extraction of the tested material, related calibrations and deembedding processes are explained. With the measurement of deionized water as a validation, the platform is used to measure the complex permittivity of both a yeast cell culture and a mammalian cell culture. We elaborate on the interesting findings and discuss future possibilities.

This paper describes the design, fabrication, and assessment of an on-wafer measurement platform for non-invasive quantitative characterization of small volumes of liquids over the frequency range from 500 kHz to 1 GHz. The platform, integrated with a micrometer scale SU-8 microfluidic channel, allows accurate placement of very small liquid volumes at a well-defined location. For the first time, a miniaturized one-port interdigital capacitor (IDC) sensor is used for dielectric spectroscopy (DS) measurements at RF/lower microwave frequency range. 3D simulation on the IDC sensor with the finite element method (FEM) verifies the complex permittivity extraction model. A validation of this platform is performed using water-isopropanol mixtures, and then it is utilized for liquid temperature measurement and baker's yeast cell concentration detection. An observation over 5 minutes is also carried out on a cell suspension, which has shown the capability of this platform in monitoring dynamic process in chemical or biological fields.

Due to its noninvasive property, the interdigital capacitor (IDC) has been applied in dielectric liquid detection and characterization. In order to integrate the IDC sensor on a lab-on-chip, it is often required to minimize and optimize the sensor for sensitive and efficient performance. However, the conventional numerical simulation approach is quite time-consuming. Therefore, an efficient analytical method is proposed herein, leading to accurate capacitance and conductance expressions of an arbitrary multilayer-structured IDC. The model is validated with practical measurements of a series of coplanar waveguide (CPW) structure-based IDCs. In addition, an accurate characterization function, which relates the IDC capacitance and conductance to the complex permittivity of a material loaded on the top of the IDC sensing area, is obtained. The characterization function shows good agreement with the finite-element method (FEM) simulation results, which demonstrates the capability of the IDC sensor in dielectric spectroscopy measurements of μL and even nL liquids.

The 2024 Nobel Prizes in Physics and Chemistry were awarded for foundational discoveries and inventions enabling machine learning through artificial neural networks. Artificial intelligence (AI) and artificial metamaterials are two cutting-edge technologies that have shown significant advancements and applications in various fields. AI, with its roots tracing back to Alan Turing’s seminal work, has undergone remarkable evolution over decades, with key advancements including the Turing Test, expert systems, deep learning, and the emergence of multimodal AI models. Electromagnetic wave control, critical for scientific research and industrial applications, has been significantly broadened by artificial metamaterials. This review explores the synergistic integration of AI and artificial metamaterials, emphasizing how AI accelerates the design and functionality of artificial materials, while novel physical neural networks constructed from artificial metamaterials significantly enhance AI’s computational speed and its ability to solve complex physical problems. This paper provides a detailed discussion of AI-based forward prediction and inverse design principles and applications in metamaterial design. It also examines the potential of big-data-driven AI methods in addressing challenges in metamaterial design. In addition, this review delves into the role of artificial metamaterials in advancing AI, focusing on the progress of electromagnetic physical neural networks in optics, terahertz, and microwaves. Emphasizing the transformative impact of the intersection between AI and artificial metamaterials, this review underscores significant improvements in efficiency, accuracy, and applicability. The collaborative development of AI and artificial metamaterials accelerates the metamaterial design process and opens new possibilities for innovations in photonics, communications, radars, and sensing.

The dielectric spectroscopy (DS) measurement is an attractive noninvasive method to reveal the intrinsic information of biological materials and cell cultures. However, the presence of a double layer due to electrode polarization within the lower RF and microwave range significantly affects the accurate analysis of dielectric properties of ionic liquids. In this paper, we measure the broadband DS of five saline solutions with a microfluidic coplanar waveguide (CPW) transmission line sensor across the frequency range from 40 kHz to 110 GHz. Derived from a parallel-plate structure that is transformed from the quasi-TEM CPW sensor through a conformal mapping technique, a broadband spectroscopy modeling method is proposed, where a Cole-Cole function or a constant phase element formula is used depending on the ionic concentrations and the measurement window. Validation analysis on the five saline solutions demonstrates the capability of the modeling method in separating relaxation properties of the bulk sample from the double-layer effects.