Olfactory Atlases with an Array of Porphyrinoids Coated ZnO Nanoparticle
Authors: Muduganti Mounika , Magna Gabriele , Paolesse Roberto , Di Natale Corrado 
Published: May 2020

Introduction

The processes of recognition of odors in natural olfaction are still largely unknown; however, a practical method to compare stimuli with the past experience is to arrange all the signals in a map where the identification of unknown samples can be based on a measure of distance. The formation of odor maps can be easily obtained with electronic noses where data collected related to either pure or mixed volatile compounds can be arranged in maps using simple and available algorithms. The projection of unknown samples onto these map is expected to provide a tentative identification of the composition of samples. This concept is here explored with a minimal sensor array made of four resistive sensors based on porphyrinoids coated ZnO nanoparticles. The scope of the paper is to explore the capability of a gas sensor array to associate stimulus coming from real samples to an odor map created with reference volatile compounds. The association between memorized odor and unknown samples is intriguing since it allows to utilize e-nose platform even in unfamiliar scenarios.

Experimental

Four hybrid materials have been prepared functionalizing ZnO nanoparticles with four organic dyes: two corroles (H3TPC, CuTPC) and two porphyrins (H2TPP, CuTPP) bearing a carboxylic group for anchoring. One pot method was used to synthesize and coat nanoparticles with organic dyes at the same time [2]. Both UV and SEM characterization evidence the presence of dye and the formation of nanoparticles. EDX characterization shows that the presence of central metal seems to rule the amount, and so thickness, of dyes present in the layer. The four sensors were fabricated by drop casting hybrid nanoparticles onto interdigitated electrodes. Sensor array was accommodated in a sealed chamber provided by transparent glass window allowing for illumination to photo-activate hybrid material with visible light at room temperature shown in figure 1. Actually both porphyrin and corrole can drive the conductivity of the underlying metal oxides once in the excited state; which in turn is obtained by visible irradiation. In this condition the gas sensitivity is strongly affect by the dye chemical structure. A mass flow controller system allows to deliver different concentrations of vapor samples to the chamber. Seven volatile compounds (VC) as well four types of real samples at room temperature have been used to train the e-nose, namely Butanol, Ethanol, Hexane, Styrene, Triethylamine, Toluene and water. Sensor response was measured as the relative change of resistance (before and at the end of vapor exposure). Preparation of real samples. Finally, unknown real samples are used to test the capability of array to associated first-time experienced odors to the ones previously memorized. Real samples comprise vapors obtained by wine, fish, sliced meat and rotten meat (obtained by storing samples into a fridge for days). In case of sliced meat, the effect of time over the spoiling was investigated.

Results

As expected, all sensors showed a remarkable sensitivity towards triethylamine, here taken as chemical probe of electron donor species. Secondly, in the case of free-base dye coating, hybrid materials show an enhanced sensitivity to alcohols and water thanks to the interaction by hydrogen bonding. Data were analyzed by using both Principal Component Analysis (PCA) and Self Organizing Map (SOM). Pure volatile compounds were utilized to create model and used as references to assign odour/off-odour similarities in real samples. It is worth to note that both of this algorithm are unsupervised and so models are produced by the intrinsic similarities occurring between samples. Principal Component analysis (PCA) was trained using only the pure VC samples and showed a good discrimination of the all VCs (alcohols, hydrocarbons and amines). Figure 2. shows PCA projections when real sample data are projected on the model (unknown samples not used to train the model), it is observed that fish is close to water (the frozen fish are usually chilled quick to avoid that microbiological spoilage happens), wine sample lies between ethanol and water, the sliced meat initially was near to alcohol (fresh) and along the time it drifts towards amines. Grinded meat, which spoils quickly, lies always in proximity of the amine. In the second approach, VC responses were used to train a 12x12 SOM shown in figure 3. A labeled map can be obtained by assigning each neuron to the class which activated itself more often. Not stimulated neurons are assigned by k-NN using the already labeled elements. Even if SOM is 2-D limited projection, results show similarities to the ones obtained in case of PCA. Also in this case the unknown sample are located close to the pure compounds to which are more close. In case of meat, spoiling process can be monitored and detected by the path of sample into the olfactory map. Results obtained utilizing both PCA and SOM show the possibility to utilize a common database to build an artificial olfactory model able to qualitatively recognize unknown samples and associate them to odors or off-odors.

References

[1] Y. Sivalingam, E. Martinelli, A. Catini, G. Magna, G. Pomarico, F. Basoli, R. Paolesse, C. Di Natale. Gas-sensitive photoconductivity of porphyrin-functionalized ZnO nanorods. J Phys Chem C 116 (2012) 9151-9157
[2] G. Magna, S. Dinc-Zor, A. Catini, R. Capuano, F. Basoli, E. Martinelli, R. Paolesse, C. Di Natale. Surface arrangement dependent selectivity of porphyrins gas sensors. Sensors and Actuators B, 251 (2017) 524-532

Figure 1