Detection of volatile organic compounds (VOCs) from the breath is becoming a viable route for the early detection of diseases non-invasively. This paper presents a sensor array of 3 component metal oxides that give maximal cross-sensitivity and can successfully use machine learning methods to identify four distinct VOCs in a mixture. The metal oxide sensor array comprises NiO-Au (ohmic), CuO-Au (Schottky), and ZnO–Au (Schottky) sensors made by the DC reactive sputtering method and having a film thickness of 80–100 nm. The NiO and CuO films have ultrafine particle sizes of < 50 nm and rough surface texture, while ZnO films consist of nanoscale platelets. This array was subjected to various VOC concentrations, including ethanol, acetone, toluene, and chloroform, one by one and in a pair/mix of gases. Thus, the response values show severe interference and departure from commonly observed power law behavior. The dataset obtained from individual gases and their mixtures were analyzed using multiple machine learning algorithms, such as Random Forest (RF), K-Nearest Neighbor (KNN), Decision Tree, Linear Regression, Logistic Regression, Naive Bayes, Linear Discriminant Analysis, Artificial Neural Network, and Support Vector Machine. KNN and RF have shown more than 99% accuracy in classifying different varying chemicals in the gas mixtures. In regression analysis, KNN has delivered the best results with an R² value of more than 0.99 and LOD of 0.012 ppm, 0.015 ppm, 0.014 ppm, and 0.025 ppm for predicting the concentrations of acetone, toluene, ethanol, and chloroform, respectively, in complex mixtures. Therefore, it is demonstrated that the array utilizing the provided algorithms can classify and predict the concentrations of the four gases simultaneously for disease diagnosis and treatment monitoring. Graphical Abstract

The effect of Radio Frequency (RF) power on the properties of magnetron sputtered Al doped ZnO thin films and the related sensor properties are investigated. A series of 2 wt% Al doped ZnO; Zn_0.98Al_0.02O (AZO) thin films prepared with magnetron sputtering at different RF powers, are examined. The structural results reveal a good adhesive nature of thin films with quartz substrates as well as increasing thickness of the films with increasing RF power. Besides, the increasing RF power is found to improve the crystallinity and grain growth as confirmed by X-ray diffraction. On the other hand, the optical transmittance is significantly influenced by the RF power, where the transparency values achieved are higher than 82% for all the AZO thin films and the estimated optical band gap energy is found to decrease with RF power due to an increase in the crystallite size as well as the film thickness. In addition, the defect induced luminescence at low temperature (77 K) and room temperature (300 K) was studied through photoluminescence spectroscopy, it is found that the defect density of electronic states of the Al³⁺ ion increases with an increase of RF power due to the increase in the thickness of the film and the crystallite size. The gas sensing behavior of AZO films was studied for NO₂ at 350 °C. The AZO film shows a good response towards NO₂ gas and also a good relationship between the response and the NO₂ concentration, which is modeled using an empirical formula. The sensing mechanism of NO₂ is discussed.

The effect of annealing on structural defects and d0 ferromagnetism in SnO2 nanoparticles prepared by solution combustion method is investigated. The as-synthesized SnO2 nanoparticles were annealed at 400–800 °C for 2 h, in ambient conditions. The crystallinity, size, and morphology of the samples were studied using x-ray diffraction and transmission electron microscopy studies. The annealing results in grain growth due to coarsening as well as reduction in oxygen vacancies as confirmed by Raman spectroscopy, photoluminescence spectroscopy, and x-ray photoelectron spectroscopy. All the as synthesized and annealed samples exhibit room temperature ferromagnetism (RTFM) with distinct hysteresis loops and the saturation magnetization as high as ∼0.02 emu/g in as-synthesized samples. However, the saturation magnetization is drastically reduced with increasing annealing temperature. Further the presence of singly charged oxygen vacancies (Vo− signal at g-value 1.99) is confirmed by electron paramagnetic resonance studies, which also diminish with increasing annealing temperature. The observed diminishing RTFM and simultaneous evidences of diminishing O vacancies clearly indicate that RTFM is driven by defects in oxide lattice and confirms primary role of oxygen vacancies in inducing ferromagnetic ordering in metal oxide semiconductors. The study also provides improved fundamental understanding regarding the ambiguity in the origin of intrinsic RTFM in semiconducting metal oxides and projects their technological application in the field of spintronics.

Unusual optical bandgap narrowing is observed in undoped SnO₂ nanoparticles synthesized by the solution combustion method. The estimated crystallite size is nearly 7 nm. Though the quantum confinement effect predicts a larger optical bandgap for materials with small crystallite size than the bulk, the optical bandgap in the as synthesized materials is found to be 2.9 eV compared to the reported value of 3.6 eV for bulk SnO₂ particles. The yellow-green photoluminescence emissions and the observed narrowing of the bandgap can be attributed to the deep donor levels of oxygen vacancies, owing to the high exothermicity of the combustion reaction and the faster cooling rates involved in the process.