# Electrochemical Detection of Penicillin G Using Molecularly Imprinted Conductive Co-Polymer Sensor
## 3 Results and Discussion
### Sensor's Performances
#### 3.2.2 Reproducibility and Selectivity  
To quantify the efficiency of the detection, we characterize the evolution of the slope of the curve before and after the detection. In practice, measurements are conducted at 15 min intervals until stability is observed (characterized by at least three overlapping curves, especially on Bode diagrams). PenG is added to reach a solution concentration of 15 ppb. This addition is made just after obtaining the last stability curve. The following measurements are made 15 min later and every 15 min as well, until at least three measurements are obtained. To quantify the efficiency of the detection, the most relevant method is to characterize the evolution of the slope of the response curve (as Figure 7, for example) before and after the detection. In other words, the greater the angle between the two, the better the detection. In the example presented in Figure 8, we can conclude that the MIP exhibits a better detection efficiency than the NIP since we measure:  
Hereafter, for these experiments, the results will be expressed in this way. Since we are dealing with the slopes of lines characterizing a response in percent as a function of time, we will qualify the importance of this efficiency by arbitrary units (noted \"a.u.\", thereafter). The signal variation measured for these different sensors in module and phase is presented in Figure 9a. This graph shows data from five MIP samples and four NIP samples. As expected, and as often observed, the sensitivity measured when observing the modulus is bigger than when observing the phase. It clearly appears that, for the phase as for the modulus, the sensitivity of the sensors is better for the MIPs than for the corresponding NIPs and this seems reproducible. This kind of sensor analysis also allows to observe the reliability of the obtained measurements. In module, the average of the sensitivities is approximately 0.27 with a standard deviation of 0.05. This represents a variation of almost 20%, which is quite high. In phase, on the other hand, the results are less good. Indeed, in Figure 9a, it can be observed that the phase variation is much lower than the Modulus variation. Moreover, some phase results obtained for MIPs are close to the ones obtained for NIPs. This highlights the fact that it is preferable to work in modules and not in phases to obtain the most accurate measurements possible. Demonstrating the selectivity of a MIP sensor is a necessary step to demonstrate the primary value of a MIP. This verification is therefore crucial to be able to affirm that this sensor is relevant. In the case of interference measurements, only MIPs are used to conduct the tests. To verify this selectivity, the added molecule for the detection tests is generally close to the target molecule, in terms of size, functional groups, and shape. But it can also be a molecule often present in the medium interfering with the other measurement methods. Figure 8: Example of how to quantify the sensors’ efficiency (with a, b, c, and d, the slope of the curves). Other interfererents were also used to verify the selectivity of PenG. In particular, molecules strongly similar to PenG and from the same family will be used: the \(\beta\)-lactams. The focus here is on Cefacetrile (cf. Figure 10b) and Ceftiofur (cf. Figure 10c). For the interference measurements, the 15 ppb of PenG are replaced by 15 ppb of the tested interferent. The results obtained for these measurements can be observed in the Figure 9b. From left to right, the measurements are compared for CAP, Cefacetrile, and Ceftiofur for the modulus measurement. The sensitivity value is compared, for each interferent, for the addition of 15 ppb. Finally, all these values are compared with one of the sensors in contact with a solution of 15 ppb of PenG (in green).