The increasing availability of portable analysis tools is democratizing science, allowing for cost-effective and convenient laboratory-based testing. Smartphone-based platforms are particularly attractive due to their global ubiquity and built-in computational capabilities. However, many smartphone-based analytical methods require additional hardware, limiting their widespread adoption. This research explores the potential of using the smartphone's built-in magnetometer for analyte sensing, offering advantages for optically challenging samples. Current smartphone-based diagnostic tools predominantly rely on optical methods, using the camera as the primary sensing interface. This approach has limitations when dealing with samples that are opaque, highly scattering, or exhibit autofluorescence. Magnetic-based methods, leveraging the smartphone's magnetometer, remain largely unexplored, despite their potential to overcome these limitations. This study aims to bridge this gap by developing a novel sensing platform that integrates the smartphone's existing magnetometer with analyte-responsive magnetic-hydrogel composites.

Existing literature showcases the successful development of various portable diagnostic tools, including paper-based diagnostics, wearable sensors, and lab-on-a-chip devices. Smartphone-based platforms have gained significant traction due to their accessibility and computational power, enabling quantitative measurements. However, many current smartphone-based analytical platforms rely on additional hardware like electrochemical sensors or external power sources, increasing their cost and complexity. Significant progress has been made in camera-based optical techniques using the smartphone's built-in camera, enabling various types of measurements. Conversely, the application of the built-in magnetometer for analyte sensing has remained under-explored, despite its advantages in handling optically challenging samples. This study aims to leverage the potential of magnetometer-based sensing for the development of a cost-effective and widely accessible platform.

The researchers designed a smartphone-based sensor platform using a bilayer smart hydrogel actuator with embedded magnetized particles. The actuator, in a T-shape, consists of an inert hydrogel segment for clamping and an analyte-responsive bilayer segment that curls upon analyte exposure, displacing the magnetic particles relative to the smartphone's magnetometer. The magnetic particles are silica-coated Nd2Fe14B microparticles to prevent corrosion. Two types of hydrogel actuators were developed: a glucose-responsive hydrogel and a pH-responsive hydrogel. The glucose-responsive hydrogel utilizes a boronic acid-based formulation, optimized for selectivity over fructose and lactic acid. The inert hydrogel layers were composed of the same monomers without the sugar-binding boronic acid. The amount of N-(3-dimethylaminopropyl acrylamide) (DMA) in the inert formulation was adjusted to match the initial swelling of both layers, ensuring a flat hydrogel composite without analyte. For pH sensing, an acrylic acid-based smart hydrogel was paired with an inert layer, designed to curl upward with increasing pH. The platform was characterized using two smartphone models: Motorola Moto E (2020) and Google Pixel 2. The response time, sensitivity, and repeatability of the sensors were evaluated. Real-world sample testing included the analysis of sugar content in wine and champagne and pH sensing of various beverages. The researchers also investigated methods to improve the platform's sensitivity and response time by optimizing the hydrogel chemistry and geometry and increasing the amount of magnetic material.

The study demonstrated the successful development of a smartphone-based sensor platform using a bilayer smart hydrogel actuator for quantitative liquid analyte measurements. The platform uses the smartphone's magnetometer, avoiding the need for additional electronics or power sources beyond the phone itself. The glucose-responsive hydrogel actuator exhibited a dynamic range covering typical physiological and pathological glucose levels, extending up to 50 mM and down to single-digit micromolar concentrations. The platform's response is repeatable across multiple cycles, with minimal variability in the endpoint magnetometer readings (less than half a percent for glucose). The response to glucose concentration changes was dynamic and approximately linear over two orders of magnitude (R² = 0.985). Similarly, the pH-responsive platform showed a linear response (R² = 0.989) over a significant portion of its range. Testing of real-world samples (wine and beverages) validated the platform's ability to provide accurate and quantitative measurements. Analysis of the system noise revealed that the magnetometer's inherent noise, rather than the hydrogel actuator, primarily limits the detection limit. The researchers demonstrated that increasing the magnetic material loading and reducing the distance between the actuator and magnetometer significantly improved the sensor sensitivity. The detection limit for glucose reached single-digit micromolar concentrations, exceeding the sensitivity of many optical and electrochemical glucose sensors. Experiments suggest that improving sensor sensitivity could potentially reach the nanomolar range. The cost of the hydrogel actuator is estimated to be only a few cents, making the platform highly accessible.

The key innovation of this platform lies in amplifying the small motion of a magnet attached to a uniformly composed hydrogel by using a bilayer hydrogel design. This amplification allows for sensitive measurements even with the less sensitive magnetometer within a smartphone. A mathematical model describing the relationship between hydrogel dilation and the change in magnetic field was developed and validated experimentally. The sensor's linearity was confirmed experimentally over a significant range, and further analysis suggests that further linear range can be achieved by tailoring the hydrogel's initial configuration. The platform's sensitivity is primarily limited by the smartphone magnetometer's inherent noise, not the hydrogel actuator itself. Optimization strategies were explored, focusing on enhancing sensitivity through increased magnetic material, reduced distance to the magnetometer, improved hydrogel chemistry and geometry. The potential to reduce response time by altering hydrogel properties (porosity, thickness) was also shown.

This study successfully demonstrates a novel smartphone-based sensing platform that utilizes the built-in magnetometer and a bilayer hydrogel actuator to perform quantitative, high-sensitivity measurements of liquid analytes. The platform's simplicity, low cost, and adaptability suggest significant potential for diverse applications. Future research directions include optimizing hydrogel properties for faster response times and exploring additional analyte targets beyond glucose and pH.

While the study demonstrates impressive sensitivity and dynamic range, some limitations exist. The current hydrogel formulations may exhibit some cross-reactivity with other analytes, requiring further optimization for improved selectivity. The response time of the current prototype is relatively slow (on the order of minutes), though strategies to reduce this are explored in the study. The platform's sensitivity is currently limited by the built-in smartphone magnetometer's noise floor; further improvements might require more sensitive magnetometer technology. The accuracy and reliability of the measurements may be affected by environmental factors like ambient magnetic fields.