Low-Cost Open-Source Biosensing System Prototype Based on a Love Wave Surface Acoustic Wave Resonator

Abstract

Love wave surface acoustic wave (LSAW) sensors are crystal resonators known for their high potential for biosensing applications due to their high sensitivity, real-time detection, and compatibility with microfluidic systems. Commercial LSAW devices are costly, and manufacturing them is even more expensive, making accessibility a significant challenge. Additionally, their use requires specialized systems, and with only a few manufacturers dominating the market, most available solutions are proprietary, limiting customization and adaptability for specific research needs. In this work, a low-cost open-source LSAW biosensing system prototype was developed based on a commercially acquired resonator. The development integrates microfluidics through a polydimethylsiloxane (PDMS) chip, low-cost electronics, and both 3D printed ultraviolet (UV) resin and polylactic acid (PLA) parts. The instrument used for measurements was a vector network analyzer (VNA) that features open-source software. The code was customized for this study to enable real-time, label-free biosensing. Experimental validation consisted of evaluating the sensitivity and repeatability of the system, from the setup to its use with different fluids. Results demonstrated that the development is able to advance to more complex applications.

1. Introduction

Surface acoustic wave (SAW) sensors have gained significant attention in the field of biosensing due to their high sensitivity, label-free detection capabilities, and real-time monitoring potential [1,2]. Biosensing refers to the detection of biomolecules using a sensor that converts a biochemical interaction into a measurable signal [3]. Among the various types of surface acoustic wave devices, Love surface acoustic wave (LSAW) sensors stand out for their ability to confine acoustic energy within a guiding layer, enhancing sensitivity to surface interactions [4]. These devices are crystal resonators that operate based on the propagation of shear horizontal acoustic waves along a piezoelectric substrate, where changes in mass loading, viscosity, or mechanical properties at the surface result in measurable variations in wave velocity and attenuation [5]. Using a vector network analyzer (VNA), the phase and insertion loss (IL) of the S21 parameter can be analyzed, both of which are useful for studying the sensor behavior [6,7]. Changes in phase velocity caused by interactions at the sensor surface can be detected as either a phase shift at a fixed frequency or a frequency shift at a fixed phase. Both reflect modifications in the wave propagation conditions due to surface events [8,9,10].

One of the key advantages of selecting LSAW technology is its high sensitivity and compatibility with microfluidic systems, enabling precise handling of liquid samples in biosensing applications like specific antigen detection [11]. This ability to manipulate and analyze fluids in real time makes them ideal for applications involving biological samples, diagnostics, and chemical sensing. Integrating microfluidic techniques onto the sensor surface, small sample volumes can be efficiently guided over the active sensing area, improving detection sensitivity and reducing reagent consumption [12]. In this context, Polydimethylsiloxane (PDMS) based microfluidic channels provide a cost-effective and adaptable platform for precise fluid handling, ensuring controlled sample delivery and minimizing external disturbances [13].

Despite the advantages of LSAW sensors within the broader family of surface SAW devices, their widespread adoption has been limited by factors such as high fabrication costs, the need for specialized instrumentation, and proprietary technologies that restrict accessibility [14]. A few companies manufacture both commercial SAW sensors and sensing systems based on this technology, and the available options are typically expensive and require sophisticated laboratory setups, limiting their accessibility for researchers with limited resources or for deployment in decentralized settings. To overcome these limitations, researchers often develop their own low-cost and open-source SAW-based systems, aiming to create accessible and customizable solutions [15,16,17]. Open-source hardware and software approaches have revolutionized various scientific fields by promoting transparency, collaboration, and cost-effectiveness. In biosensing, such initiatives can accelerate innovation, enable reproducibility, and facilitate technology adoption in diverse research and clinical environments.

To address the challenges explained, this work presents an original low-cost and open-source LSAW biosensing system prototype that integrates easily accessible components and customizable software. The development has been designed to maintain high sensitivity while ensuring affordability and ease of fabrication. Detailed schematics, assembly procedures, and software codes are shared to enable replication and further development by the scientific community. The system has been tested to validate its performance on real-time monitoring of fluid circulation to demonstrate that it provides reliable and repeatable measurements.

2. Design

2.1. Sensing System

The system design is based on a Love surface acoustic wave sensor with an approximate resonance frequency of 120 MHz (Figure 1a). A module was designed to position the sensor and connect it to a NanoVNA-type H running a customized open-source software for real-time experiments. The module also integrates a PDMS chip that enables fluid circulation over the sensing area of the sensor, and the fluid flow rate is controlled using a Mindray BeneFusion 5 infusion pump. Figure 1b presents a schematic representation of the system.

2.2. Module and PDMS Chip

The module consists of a base and a top module. The base features guides for precise positioning of the sensor and the PDMS chip. The top module incorporates two printed circuit boards (PCBs) with two gold-plated pogo pins to establish electrical contact with the sensor, as well as two SMA connectors for interfacing with the NanoVNA. The PDMS chip is adjusted on the sensor surface by applying pressure [18,19] to both ends and the center of the microfluidic device. This adjustment, which can be manually controlled using three screws or automatically with an accessory added to the top module, was experimentally calculated to ensure proper PDMS chip alignment and sealing without significantly attenuating the sensor signal. Finally, the top module is secured to the base with four inserts and screws. Figure 2 shows an exploded view of the module design, including the sensor, the PDMS chip, and the SMA connectors.

The design of the PDMS chip (Figure 3) is based on the geometry of the LSAW sensing area. A custom rectangular seal (3.8 mm in length, 2.6 mm in width, and 0.75 mm in wall thickness) controls the fluid leak and defines a custom sensing area of 2.3 mm in length and 1.1 mm in width. Fluid transport and expulsion are facilitated by two 0.5 mm diameter channels that form a U-shaped passage alongside the seal, creating a contact volume of approximately 1.7 µL. The chip is connected to the infusion pump and ejects fluid through two microfluidic hoses that are press-fitted into the chip. When switching the syringe, reverse flow was controlled with a three-way stopcock in the inlet hose.

2.3. Housings and Mounting Base

The sensor was protected from temperature fluctuations, air currents, and particle deposition by employing a two-layer enclosure. Studying the sensor structure and constituent materials, it was determined that an active temperature control was not necessary, as temperature variations were not expected to significantly affect the measurements [20]. Moreover, such control would primarily serve to acclimate the module enclosure, since direct temperature regulation at the sensor level could potentially introduce substantial signal variations.

The first enclosure (housing A, Figure 4a) surrounds and protects the lateral sides of the sensing module while permitting access for NanoVNA cables and microfluidic tubing. The second enclosure (housing B, Figure 4b) completely encapsulates housing A and the module, creating a closed box-like environment that further isolates the sensor from external interference. Both housings include dedicated openings for routing cables and tubing. Additionally, a mounting base (Figure 4c) was designed to precisely align and stabilize the infusion pump, sensor module, and VNA in terms of height and relative positioning.

2.4. Custom NanoVNA Software

The NanoVNA-type H was used to study the sensor response using its open-source software (available at: https://github.com/NanoVNA-Saver/nanovna-saver (accessed on 5 September 2022) written in Python. The VNA is a device used for various radiofrequency applications, and this led to the modification of the Python code to better suit biosensing needs. The changes include removing non-essential tools, improving the interface design, and implementing real-time signal analysis algorithms, along with a continuous frequency sweep tool to assess the sensor response over a defined period. This tool sets a working frequency at the point of maximum IL amplitude and performs multiple scans over time. This approach was adopted based on the satisfactory results obtained in previous studies. For the sensor used in this work, prior research has typically selected a point near the maximum insertion loss (IL), where the phase response is expected to exhibit an approximately linear behavior [8,20,21]. In addition, various SAW-based sensing strategies in the literature analyze surface changes either by fixing a single frequency point or by comparing entire sweep curves [7,9,21,22]. Additionally, sweeps data can be exported in Touchstone format for in-depth analysis, or an Excel file based on the working frequency. Figure 5 shows the customized software in operation, displaying its configuration section along with real-time graphs and data.

3. Build Instructions

3.1. Bill of Materials

Table 1. Bill of materials.

Item	Brand/Model	Source	Cost [US$]	Quantity	Total [US$]
Insert	M3	Amazon	0.06	7	0.4
Nut	M3	Amazon	0.04	6	0.24
Screw	M3 × 12	Amazon	0.14	6	0.84
Screw	M4 × 25	Amazon	0.34	4	1.36
Screw	M3 × 20	Amazon	0.4	2	0.80
Screw	M3 × 15	Amazon	0.4	4	1.60
Pogo Pin	Mill-Max 0913	DigiKey	0.86	4	3.44
Shipping Estimation	-	JLC3DP	39.11	1	39.11
UV Resin Base Module	-	JLC3DP	0.66	1	0.66
UV Resin Top Module	-	JLC3DP	0.55	1	0.55
PLA PDMS Mold	-	JLC3DP	1.00	1	1.00
PLA Pressure Accessory	-	JLC3DP	1.00	1	1.00
PLA Housing A Part 1	-	JLC3DP	1.00	1	1.00
PLA Housing A Part 2	-	JLC3DP	1.64	1	1.64
PLA Housing B Part 1	-	JLC3DP	3.58	1	3.58
PLA Housing B Part 2	-	JLC3DP	3.53	1	3.53
PLA Mounting Base Part 1	-	JLC3DP	26.72	1	26.72
PLA Mounting Base Part 2	-	JLC3DP	19.95	1	19.95
PLA Mounting Base Part 3	-	JLC3DP	11.73	1	11.73
PDMS Kit	Sylgard 184™	Amazon	180.00	1	180.00
Microfluidic Hose	0.51 × 1.52 mm × 1 m	Amazon	34.44	1	34.44
Three-way Stopcock	QWORK	Amazon	0.85	1	0.85
NanoVNA	Type H	Amazon	60.00	1	60.00
LSAW Sensor × 10	AWS SNS000069A	AWSensors	275.00	1	275
SMA Connector	Female 90° Solder PCB	Amazon	2.00	2	4.00
-	-	-	-	Total	673.44

PLA and UV resin parts cost was calculated using a printing simulator on the JLC3DP website. The total cost of the PDMS kit and the sensor pack was included, as they are necessary, even though they were not used in their entirety. The cost of the infusion pump was not included, as it is not essential for the system’s operation and can be replaced according to the user’s preference. Additionally, the shipping estimation can be disregarded.

presents the bill of materials corresponding to the costs of the system components and supplementary materials. The design file summary can be found in the Supplementary Materials section.

3.2. Module and NanoVNA Software

The construction of the module starts using adhesive to fix four inserts to the base (Figure 6a) and two (three if manual adjustment of the PDMS chip is desired) to the top module (Figure 6b). Then, both PCBs are attached to the top module (using a hot glue gun or by securing them with screws and nuts through the extra holes), and after that, the SMA connectors and the pogo pins are soldered on the PCBs (Figure 6c). Next, in case the adjustment accessory was selected, it is secured to the top module with two screws. After that, the module should be connected to the NanoVNA to verify that the pogo pins make precise contact with the crystal, checking that the sensor frequency response is correct. The software, written in Python 3.9, must be used for this. It can be run in environments such as PyCharm, Visual Studio, and others. If the user prefers, the code can be compiled into an executable. For both cases, a line in the SweepWorker file of the code must be modified by changing the path of the folder where the Touchstone files from the continuous sweep are saved.

3.3. PDMS Chip

A 1:10 mixture of Sylgard 184™ elastomer and curing agent is prepared and placed in a vacuum pump for one hour to remove air bubbles. Next, using the PLA mold, two metal rods, similar to those used for electronic component pins, are inserted until they reach the vertical section of the U-shaped passage (Figure 7). The mixture is then poured into the mold and placed in an oven at 52 °C for at least two hours. This temperature is chosen because PLA starts to deform at temperatures above 60 °C [23]. Once the PDMS is cured, the rods are removed, forming the horizontal inlet and outlet fluid channels. Finally, the chip is carefully demolded, and the microfluidic device is checked for leaks by connecting hoses and circulating a simple fluid, such as water. For a simple final test, fluid circulation is performed while monitoring the insertion loss of the S21 parameter to check for potential leaks. The pressure applied to the PDMS chip involves a trade-off between ensuring proper sealing to prevent leakage and avoiding excessive attenuation that could distort the IL curve.

3.4. Housings and Mounting Base

The mounting base consists of two parts secured with two screws and nuts (Figure 8). Part A provides height to the module and the VNA, and part B positions them and is composed of two sections joined with two screws and two nuts. On the other hand, the module is protected by housings A and B (both composed of two parts), which require no assembly instructions as they are placed during the system setup.

4. Operating Instructions

4.1. Sensor Cleaning and System Setup

The sensor is manually cleaned before use following this protocol:

• Soak for 10 min in a 2% SDS and distilled water solution.
• Rinse with distilled water.
• Dry with nitrogen gas.

The system setup protocol is described as follows:

• Attach the module to the system.
• Place the LSAW sensor on the module base.
• Mount the PDMS chip (with its hoses inserted) using module base guides.
• Place the lower part of housing A and housing B.
• Close the module, securing it with four screws.
• Connect the VNA to the SMA connectors on the top module.
• Close both housings with their upper parts and position the drain hose.
• Connect the inlet hose and the syringe to the 3-way stopcock.
• Place the syringe in the infusion pump and select the desired flow rate.

After completing the instructions, the system is ready for fluid circulation and frequency response measurement. Figure 9 shows the assembled system in operation.

4.2. Custom Software

After completing the system setup, with the NanoVNA connected to the PC, turn it on and open the software. The program should detect the instrument and its port. The method for performing a continuous sweep is carried out as follows:

• Press the Connect button to automatically perform a simple sweep.
• While performing simple sweeps, adjust the sweep parameters until achieving the desired resolution and time characteristics.
• In the sweep configuration, click Find Resonance to set a working frequency and perform a simple sweep.
• Select the Continuous Sweep function and, based on the time required for a single sweep, choose the number of sweeps to perform (integer value).
• The Touchstone files will be stored in the selected directory.
• Once completed, data can be exported in Excel format by clicking Save Data.

5. Validation

5.1. PDMS Chip Effect and Fluid Leakage

The correct operation of the system was evaluated by analyzing the baseline response of the sensor, the effect of the PDMS chip, and both fluid circulation and leakage (Figure 10). First, the frequency response of the sensor was obtained in air, without the PDMS chip, confirming that the circuit connecting the sensor to the VNA was functioning properly. Second, the PDMS chip was incorporated, and its impact on the sensor response was analyzed by varying the pressure applied to the sensor surface. Finally, distilled water was circulated with the PDMS chip tightly and loosely adjusted to observe the difference in response when fluid leakage occurred. Fluid circulation was performed with a flow rate of 0.425 µL/s, and from this initial experiment onward, all measurements were conducted at room temperature.

The frequency response of phase and insertion loss, starting from the response in air, exhibits different behaviors for each case. A similar behavior is observed for PDMS A and fluid leakage, while it was inverse for PDMS B. It can be observed that an increase in phase is accompanied by a frequency shift to the right. The curves show irregularities due to noise, which is present in all cases. The behavior in air is distinguished by a higher amplitude compared to the other cases and a cleaner curve. On the other hand, over-tightening the PDMS chip not only causes an inverse behavior in phase and IL but also leads to greater deformation of the curves. In addition, increased pressure can deform the rectangular seal, applying force on the IDTs, which would have a greater impact on the frequency response, making precise pressure control and placement of the rectangular seal critical. Finally, fluid leakage results in deformation and attenuation of the curves, drastically altering the phase and IL response compared to the other cases.

5.2. System Stabilization

Stabilization was analyzed by monitoring changes in phase and IL while circulating distilled water. For the continuous sweep, the working point was set at the maximum IL of the first sweep. At the beginning of the experiment, both parameters did not stabilize. The changes were constant and small, and there was no indication that the response would stabilize. If a leakage had occurred, the change would have been similar to what was observed in the previous section. After assembling the system and immediately circulating the fluid, particles may have continued depositing onto the sensor surface. Additionally, the pressure exerted by the PDMS chip on the sensor deforms the rectangular seal during system setup, and it is reasonable to assume that allowing the system to rest also contributes to stabilization. Therefore, it was decided to let the system settle with stagnant distilled water until the following day. After the relaxation period, distilled water was circulated again, and stability was reached. Figure 11 shows the temporal evolution of insertion loss and phase during the circulation of distilled water, highlighting the point at which signal stability is achieved after the relaxation period.

The experiment started with stagnant distilled water and an attenuation of IL compared to the previous day. Starting at minute 11.7, considering the phase shift in the signal, a constant behavior was observed, which also attempts to resemble the IL, despite their distinct behaviors. From the beginning until the point of stability, the difference between having stagnant and circulating distilled water was 0.2 degrees.

5.3. Sensitivity and Repeatability

The sensitivity and repeatability of the system were evaluated upon reaching stability, focusing on analyzing the phase shift, as it reflects changes in mass, viscosity, and density. Alternate cycles of phosphate-buffered saline (PBS) pH 7.4 10 mM solution (Sigma, St. Louis, USA) and distilled water were performed, giving a total of three circulations each. When frequency response stability was reached, the system was left for at least 20 min before proceeding to the next fluid. Time duration was chosen based on the experiments observed in various experiments using LSAW technology [21,22,24]. This approach ensures that the sensor can distinguish between two fluids with different physical properties and that the phase returns to a previous value upon recirculation. Figure 12 depicts the phase shift temporal curve of the experiment, and

Table 2. Sensitivity and repeatability results. Phase mean and std for each fluid circulation stage are shown for distilled water and the PBS solution. Additionally, each circulation stage includes a syringe change and a stability time, both presented in minutes. Final PBS circulation does not include a syringe change, and the time, in this case, corresponds to the completion of the experiment. Finally, the first stability value, corresponding to distilled water, is set to zero.

Fluid (Stage)	Phase (Degree)	Syringe Change (Minute)	Stabilization (Minute)
Water [1]	−40.293 +/−0.016	20.872	0.000
PBS [1]	−41.076 +/−0.028	48.963	27.385
Water [2]	−40.334 +/−0.028	89.978	73.612
PBS [2]	−40.865 +/−0.031	120.129	99.006
Water [3]	−40.366 +/−0.030	155.847	131.396
PBS [3]	−40.951 +/−0.029	186.222	168.949

shows the phase mean and standard deviation (std) for each stable period of distilled water and PBS solution.

The first distilled water circulation, corresponding to the initial stability, yielded a standard deviation of 0.016°, while the subsequent circulations ranged between 0.028° and 0.031°. On the other hand, the distilled water circulation results varied by 0.073° when subtracting the maximum and minimum values. For PBS, this difference was 0.211°, indicating that the interaction between this fluid and the surface generated variability in the response. Averaging the means, distilled water had a value of 40.331 and PBS 40.964, differing by 0.663°. Considering the maximum standard deviation obtained, 0.031°, it can be stated that the noise present in the system during the stability period is within acceptable limits [22].

The limit of detection (LOD), defined as the smallest detectable change in signal, was estimated using the maximum phase noise (Δφ_n) of the standard deviation measured in the stable regime of the phase response. First of all, the phase variation can be combined with the theoretical phase-to-mass sensitivity of the sensor to estimate the surface mass density change (Δσ) [20]. Following established approaches [25,26], the LOD was calculated as a function Δσ, as shown in Equation (1):

$$LOD={\displaystyle \frac{3\times \Delta {\phi }_{\mathrm{n}}}{\Delta \sigma }}$$

(1)

During system characterization, the maximum standard deviation of 0.031° results in a LOD of 0.153 $\mathrm{n}\mathrm{g}/{\mathrm{m}\mathrm{m}}^2$. The magnitude is acceptable in comparison with values reported where phase shift measurements are used to obtain the limit of detection in terms of surface mass density [26,27,28,29].

The analysis was finished with a t-test to support the observed differentiation between fluids. A clear distinction was observed between the responses to distilled water and PBS, which was further confirmed by a statistical test yielding a p-value < 0.001, a t-statistic of 38.690, and a 95% confidence interval for the difference in means ranging from 0.607 to 0.674. These parameters demonstrate that the sensor was able to reliably differentiate between the two fluids across three repeated cycles each, resulting in two clearly distinguishable response groups.

5.4. Sensor Reutilization and Measurement Technique

The tests did not involve surface functionalization or the use of aggressive reagents; a single sensor was used throughout all the experiments to assess how it was altered with constant use and evaluate its reutilization. It was observed that the gold layer covering the four electrical contacts showed signs of degradation, with some particles detaching from the surface. This damage is likely caused by the repeated mechanical interaction between the pogo pins and the thin gold coating, combined with the pressure applied during each connection cycle. Over time, this may compromise the electrical reliability and long-term reproducibility of the measurements. To mitigate this issue, alternative contact methods with reduced mechanical stress—such as using softer contact materials or optimized pin designs—could be explored to extend sensor lifespan and maintain consistent performance. Additionally, sensor robustness could be improved by increasing the thickness of the gold layer by extending sputtering time or employing complementary gold deposition techniques such as electroplating. On the other hand, while the measurement technique used for the continuous sweep involves setting a working frequency at the maximum IL of the first sweep, other approaches can be used to explore the sensor response. One could seek the maximum IL or a specific phase value, leading to frequency shifts. Alternatively, a fixed frequency point could be chosen where IL is not necessarily at its maximum but close to zero phase, where the phase curve also exhibits linear behavior.

5.5. System Comparative Overview

A comparative overview is provided to contextualize the relevance and novelty of the proposed system. This comparison highlights key differences between the developed platform and those typically reported in the literature for sensing systems based on SAW technology, as well as other commonly used acoustic platforms such as Quartz Crystal Microbalance (QCM) [8,18,20,21,22,24,30,31,32,33,34,35,36,37]. The system developed in this work is based on a commercial LSAW sensor, similar to some reported platforms that use either commercial or custom-fabricated devices. Despite many previous works relying on proprietary setups or only partially described designs, this system is fully open-source, promoting reproducibility and accessibility. In terms of cost, the use of affordable components and materials results in a low-cost solution, contrasting with the costly materials and instruments typically employed in other studies.

The mechanical housing is fabricated using 3D printing techniques, employing PLA and UV resin, whereas reported systems often use metal, plastic, or 3D-printed enclosures without detailing their composition or accessibility. The microfluidic interface incorporates a removable PDMS chip, which simplifies cleaning and sensor replacement. This contrasts with other configurations in the literature, where the microfluidic component is either permanently bonded or derived from commercial microfluidics kits. In the proposed setup, fluid circulation is performed in flow mode, and some works report batch operation or a combination of both. The sensor is removable and reusable, in contrast to platforms where the sensor is permanently bonded to a microfluidic chip, limiting its lifetime.

Electrical connection is achieved through a PCB interface with gold-plated pogo pins, providing a robust and solder-free solution, while alternative approaches include wire bonding or soldering, which are less practical for repeated use. The measurement instrument is a low-cost NanoVNA-H, whereas most reported systems rely on high-end, costly instrumentation. While some characteristics of the presented work overlap with existing approaches, the integration of affordability, reusability, and open-source accessibility results in a platform that offers several advantages.

6. Conclusions

A sensing system prototype based on a commercial LSAW sensor was developed. The core of the design is a dedicated module that allows precise sensor positioning and seamless integration of a PDMS-based microfluidic chip. The system was built using low-cost and open-source components, making it an accessible and adaptable platform. Furthermore, when evaluating the developed prototype from an economic perspective—excluding the costs of sensors—it proves to be cost-effective, with an approximate cost of $400. For instance, OpenQCM offers commercial systems that employ technologies similar to the one adopted (such as Quartz Crystal Microbalance), with prices ranging from €1000 to €4000.

The validation experiments involved evaluating the IL and phase of the sensor under different conditions. The integration of the PDMS chip and fluid circulation causes attenuation on both parameters, while a fluid leak can be distinguished by the change it induces in the curves. The system stability while circulating liquid is not immediately achieved upon assembling the system, and a waiting period is required. Finally, focusing on phase changes, distilled water and a PBS solution, fluids with distinct physical characteristics, were differentiated successfully (p-value < 0.001). Notably, the PBS solution used is a fluid commonly employed in biosensing applications, such as biodetection and surface functionalization, and the results obtained with this medium were in good agreement with its expected behavior.

Several improvements can be made to the system, such as enhancing the electrical connection with components that reduce noise and proposing changes to the design and sealing method of the PDMS chip. Based on the results obtained, it is believed that the developed prototype has met expectations and is in a position to undergo testing in biosensing applications, such as immobilizing biological elements and evaluating interactions with biofluids or targets.