We report on the synthesis of 5-nm thick-Ag embedded−SnS (Ag/SnS) films by the radio frequency (RF) sputtering method as an absorbent layer to detect NO2 gas. Structure, morphology, elements, and optical properties of the Ag/SnS films were studied by X − ray diffraction, scanning electron microscopy, energy−dispersive spectroscopy, Raman and photoluminescence techniques, respectively. We firstly investigated the sensitivity of 5 – 20 ppm concentration of the Ag/SnS films to NO2 gas at an operating temperature ranging 30 – 100 °C. It was indicated that the Ag/SnS film–based sensor got good response and recovery at an operating temperature of 80 °C for NO2 gas. The 100 nm thick SnS film−based sensor made a faster response time (40 s) and recovery time (1320 s) to 20 ppm NO2 gas at 30 °C than those of other SnS films−based sensors. The result shows that the Ag/SnS film might be suitable for improving NO2 sensor properties due to the enhanced hole mobility, and more defectiveness of the SnS monolayer (Sn–vacancy). Based on these findings, we propose the fabrication of nanometals on SnS film for the high sensitive and selective NO2 gas−sensing a lower detection limit and at room temperature.

Structural, electronic, and magnetic properties of two-dimensional Cr2N MXene under strain were studied. The uniaxial and biaxial strain was considered from −5 to 5%. Phonon dispersion was calculated; imaginary frequency was not found for both kinds of strain. Phonon density of states displays an interesting relation between strain and optical phonon gaps (OPGs), that it implies tunable thermal conductivity. When we apply biaxial tensile strain, the OPG increases; however, this is not appreciable under uniaxial strain. The electronic properties of the dynamically stable systems were investigated by calculating the band structure and electron localization function (ELF) along the (110) plane. The band structure showed a metallic behavior under compressive strain; nevertheless, under tensile strain, the system has a little indirect band gap of 0.16 eV. By analyzing, the ELF interactions between Cr–N are determined to be a weaker covalent bonding Cr2N under tensile strain. On the other hand, if the Cr atoms reduce or increase their self-distance, the magnetization alignment changes, also the magnetic anisotropy energy displays out-of-plane spin alignment. These properties extend the potential applications of Cr2N in the spintronic area as long as they can be grown on substrates with high lattice mismatch, conserving their magnetic properties.

This study applies the idea of computing with words to develop an advanced genetic method to design the Linguistic Rule Base Systems (LRBSs) from a given dataset to solve the dataset regression problem, whose rules can be considered human knowledge. It has two primary specific features. The first is its ability to ensure the uncertain equality of two dataset contents assigned to each of its designed rules: the dataset content the users capture when reading it and the one the proposed method computes and assigns to it. Then, Tarski et al.’s interpretability concept in the math logics field does require the designed fuzzy sets to be isomorphic images of their assigned words. It implies their soundness in representing their words. The second is its ability to ensure the LRBs’ scalability, an essential feature of human knowledge stating that it can grow while maintaining its existing one. Then, the proposed method can utilize the existing LRBSs optimality to design a new optimized LRBSs generation to increase the regression precision by allowing the existing L-attributes’ word sets to grow. Compared to existing methods, the conducted experimental study can justify its performance and benefits in solving the regression problems using benchmark datasets in this area.