Algorithms of Chemicals Detection Using Raman Spectra: Raman spectrometers are devices which enable fast and non-contact identification of examined chemicals. These devices utilize the Raman phenomenon to identify unknown and often illicit chemicals (e.g.drugs, explosives) without the necessity of their preparation. Now, Raman devices can be portable and therefore can be more widely used to improve security at public places. Unfortunately, Raman spectra measurements is a challenge due to noise and interferences present outside the laboratories. The design of a portable Raman spectrometer developed at the Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology is presented. The paper outlines sources of interferences present in Raman spectra measurements and signal processing techniques required to reduce their influence (e.g.background removal, spectra smoothing). Finally, the selected algorithms for automated chemicals classification are presented. The algorithms compare the measured Raman spectra with a reference spectra library to identify the sample. Detection efficiency of these algorithms is discussed and directions of further research are outlined.

Portable Raman spectrometer - design rules and applications: Raman spectroscopy has become more popular due to its new prospective field applications in forensic sciences, war against terrorism, environment protection and other field chemical analysis. Raman spectrometers can be miniaturised to portable devices and their price is decreasing due to development of optoelectronics components. Unfortunately, this technology has still numerous limitations that influence their design and limit the scope of possible applications. The conception and design of the portable Raman spectrometer is described, including discussion of performance and limitations of representative components of such device available on the market. An enhanced portable Raman spectrometer using two lasers, one emitting at 355 nm and the other at 785 nm, and employing advanced signal acquisition and data processing methods is presenented. Advantages of such system are outlined and example measurement results acquired using equivalent hardware are presented. Data processing flow for identification of chemicals is also described.

We discuss the implementation challenges of gas sensing systems based on low-frequency noise measurements on chemoresistive sensors. Resistance fluctuations in various gas sensing materials, in a frequency range typically up to a few kHz, can enhance gas sensing by considering its intensity and the slope of power spectral density. The issues of low-frequency noise measurements in resistive gas sensors, specifically in two-dimensional materials exhibiting gas-sensing properties, are considered. We present measurement setups and noise-processing methods for gas detection. The chemoresistive sensors show various DC resistances requiring different flicker noise measurement approaches. Separate noise measurement setups are used for resistances up to a few hundred kΩ and for resistances with much higher values. Noise measurements in highly resistive materials (e.g., MoS₂, WS₂, and ZrS₃) are prone to external interferences but can be modulated using temperature or light irradiation for enhanced sensing. Therefore, such materials are of considerable interest for gas sensing.

This paper describes a measurement setup (eNose) designed to analyze air samples containing various volatile organic compounds (VOCs). The setup utilizes a set of resistive gas sensors of divergent gas selectivity and sensitivity. Some of the applied sensors are commercially available and were proposed recently to reduce their consumed energy. The sensors detect various VOCs at sensitivities determined by metal oxide sensors’ technology and operating conditions. The setup can utilize prototype gas sensors, made of resistive layers of different compositions, as well. Their properties can be modulated by selecting operating temperature or using UV light irradiation. The unit is controlled by an embedded system M5Stack Core2 ESP32 IoT. We used this development kit to program the measurement procedure and data recording fastly. The setup utilizes an aluminum gas chamber of a volume of 220 ml, a set of electrical valves to introduce there an air sample with the help of an electrical micropump. The handling of the setup was simplified to a selection of a few operations by touch screen only without a necessity of extra training. The recorded data are saved in a memory card for further processing. The evolved setup can be upgraded to apply more advanced data processing by utilizing WiFi or Bluetooth connection. The control program was prepared using the Arduino IDE software environment and can be further advanced with ease. The applied materials and the established measurement procedure can use various air samples, including exhaled breath samples for patients’ screening check-ups. We applied the same time of 10 min for response and recovery, acceptable for practical use.