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Recently, there has been a huge increase in the different ways to manufacture polymer-based sensors. Methods like additive manufacturing, microfluidic preparation, and brush painting are just a few examples of new approaches designed to improve sensor features like self-healing, higher sensitivity, reduced drift over time, and lower hysteresis. That being said, we believe there is still a lot of potential to boost the performance of current sensors by applying modeling, classification, and machine learning techniques. With this approach, final sensor users may benefit from inexpensive computational methods instead of dealing with the already mentioned manufacturing routes. In this study, a total of 96 specimens of two commercial brands of Force Sensing Resistors (FSRs) were characterized under the error metrics of drift and hysteresis; the characterization was performed at multiple input voltages in a tailored test bench. It was found that the output voltage at null force ( V o_null ) of a given specimen is inversely correlated with its drift error, and, consequently, it is possible to predict the sensor's performance by performing inexpensive electrical measurements on the sensor before deploying it to the final application. Hysteresis error was also studied in regard to V o_null readings; nonetheless, a relationship between V o_null and hysteresis was not found. However, a classification rule base on k -means clustering method was implemented; the clustering allowed us to distinguish in advance between sensors with high and low hysteresis by relying solely on V o_null readings; the method was successfully implemented on Peratech SP200 sensors, but it could be applied to Interlink FSR402 sensors. With the aim of providing a comprehensive insight of the experimental data, the theoretical foundations of FSRs are also presented and correlated with the introduced modeling/classification techniques. more...

Polymer nanocomposites have found wide acceptance in research applications as pressure sensors under the designation of force-sensing resistors (FSRs). However, given the random dispersion of conductive nanoparticles in the polymer matrix, the sensitivity of FSRs notably differs from one specimen to another; this condition has precluded the use of FSRs in industrial applications that require large part-to-part repeatability. Six Sigma methodology provides a standard framework to reduce the process variability regarding a critical variable. The Six Sigma core is the DMAIC cycle (Define, Measure, Analyze, Improve, and Control). In this study, we have deployed the DMAIC cycle to reduce the process variability of sensor sensitivity, where sensitivity was defined by the rate of change in the output voltage in response to the applied force. It was found that sensor sensitivity could be trimmed by changing their input (driving) voltage. The whole process comprised: characterization of FSR sensitivity, followed by physical modeling that let us identify the underlying physics of FSR variability, and ultimately, a mechanism to reduce it; this process let us enhance the sensors' part-to-part repeatability from an industrial standpoint. Two mechanisms were explored to reduce the variability in FSR sensitivity. (i) It was found that the output voltage at null force can be used to discard noncompliant sensors that exhibit either too high or too low sensitivity; this observation is a novel contribution from this research. (ii) An alternative method was also proposed and validated that let us trim the sensitivity of FSRs by means of changing the input voltage. This study was carried out from 64 specimens of Interlink FSR402 sensors. more...

Polyaniline (PANI) has recently gained great attention due to its outstanding electrical properties and ease of processability; these characteristics make it ideal for the manufacturing of polymer blends. In this study, the processing and piezoresistive characterization of polymer composites resulting from the blend of PANI with ultra-high molecular weight polyethylene (UHMWPE) in different weight percentages (wt %) is reported. The PANI/UHMWPE composites were uniformly homogenized by mechanical mixing and the pellets were manufactured by compression molding. A total of four pellets were manufactured, with PANI percentages of 20, 25, 30 and 35 wt %. Fourier-transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), differential thermal analysis (DTA), scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) were used to confirm the effective distribution of PANI and UHMWPE particles in the pellets. A piezoresistive characterization was performed on the basis of compressive forces at different voltages; it was found that the error metrics of hysteresis and drift were influenced by the operating voltage. In general, larger voltages lowered the error metrics, but a reduction in sensor sensitivity came along with voltage increments. In an attempt to explain such a phenomenon, the authors developed a microscopic model for the piezoresistive response of PANI composites, aiming towards a broader usage of PANI composites in strain/stress sensing applications as an alternative to carbonaceous materials. more...

Force Sensing Resistors (FSRs) are manufactured by sandwiching a Conductive Polymer Composite (CPC) between metal electrodes. The piezoresistive property of FSRs has been exploited to perform stress and strain measurements, but the rheological property of polymers has undermined the repeatability of measurements causing creep in the electrical resistance of FSRs. With the aim of understanding the creep phenomenon, the drift response of thirty two specimens of FSRs was studied using a statistical approach. Similarly, a theoretical model for the creep response was developed by combining the Burger's rheological model with the equations for the quantum tunneling conduction through thin insulating films. The proposed model and the experimental observations showed that the sourcing voltage has a strong influence on the creep response; this observation-and the corresponding model-is an important contribution that has not been previously accounted. The phenomenon of sensitivity degradation was also studied. It was found that sensitivity degradation is a voltage-related phenomenon that can be avoided by choosing an appropriate sourcing voltage in the driving circuit. The models and experimental observations from this study are key aspects to enhance the repeatability of measurements and the accuracy of FSRs., Competing Interests: The authors declare no conflict of interest. more...

Conductive polymer composites are manufactured by randomly dispersing conductive particles along an insulating polymer matrix. Several authors have attempted to model the piezoresistive response of conductive polymer composites. However, all the proposed models rely upon experimental measurements of the electrical resistance at rest state. Similarly, the models available in literature assume a voltage-independent resistance and a stress-independent area for tunneling conduction. With the aim of developing and validating a more comprehensive model, a test bench capable of exerting controlled forces has been developed. Commercially available sensors-which are manufactured from conductive polymer composites-have been tested at different voltages and stresses, and a model has been derived on the basis of equations for the quantum tunneling conduction through thin insulating film layers. The resistance contribution from the contact resistance has been included in the model together with the resistance contribution from the conductive particles. The proposed model embraces a voltage-dependent behavior for the composite resistance, and a stress-dependent behavior for the tunneling conduction area. The proposed model is capable of predicting sensor current based upon information from the sourcing voltage and the applied stress. This study uses a physical (non-phenomenological) approach for all the phenomena discussed here., Competing Interests: The authors declare no conflicts of interest. more...

This article upgrades the RC linear model presented for piezoresistive force sensors. Amplitude nonlinearity is found in sensor conductance, and a characteristic equation is formulated for modeling its response under DC-driving voltages below 1 V. The feasibility of such equation is tested on four FlexiForce model A201-100 piezoresistive sensors by varying the sourcing voltage and the applied forces. Since the characteristic equation proves to be valid, a method is presented for obtaining a specific sensitivity in sensor response by calculating the appropriate sourcing voltage and feedback resistor in the driving circuit; this provides plug-and-play capabilities to the device and reduces the start-up time of new applications where piezoresistive devices are to be used. Finally, a method for bypassing the amplitude nonlinearity is presented with the aim of reading sensor capacitance. more...