Adsorption of NO2, SO2, H2S, and NH3 on Os-Doped WSe2 Monolayers: A First-Principles Study

Accelerated Screening of Highly Sensitive Gas Sensor Materials for Greenhouse Gases Based on DFT and Machine Learning Methods

Greenhouse gases (GHGs) have caused great harm to the ecological environment, so it is necessary to screen gas sensor materials for detecting GHGs. In this study, we propose an ideal gas sensor design strategy with high screening efficiency and low cost targeting four typical GHGs (CO2, CH4, N2O, SF6). This strategy introduces machine learning (ML) methods based on density functional theory (DFT) to achieve accurate and rapid screening from a large number of candidate gas sensor materials. Specifically, the candidate materials include 28 different transition metal-doped WSe2 monolayers (TM-WSe2), and four gas molecules and their optimal adsorption structures on TM-WSe2 are constructed. Ten fine-tuned ML models are implemented to train and predict the adsorption energy (Eads) and adsorption distance (D) of target gases on TM-WSe2, thereby selecting the optimal ML model and identifying these promising gas sensor materials. In addition, the gas-sensing properties of these materials are verified by band structure, work function, and recovery time. This research provides a reasonable and low-cost new way for rapid screening of ideal gas sensor materials with the help of artificial intelligence and proves its effectiveness through experiments.

Adsorption of LIBs Thermal Runaway Gases on TM-Decorated HfS2 Surface: A DFT Study

With the wide application of lithium-ion batteries (LIBs) in different fields, safety accidents occur frequently. Therefore, it is necessary to monitor the thermal runaway gas for an early warning. In this article, the adsorption properties of the characteristic gases of LIBs thermal runaway gases are studied by density functional theory (DFT). The adsorption structure of TM (Co/Rh/Ir)-decorated HfS2 (TM@HfS2) is established, and its adsorption properties for C2H4, CH4, and CO are studied. The adsorption energy, charge transfer, band, DOS, charge difference density, work function, and recovery time are discussed in detail. The results show that Ir@HfS2 has the strongest adsorption performance for C2H4 and CO, so C2H4 and CO can be stably adsorbed on the surface of the Ir@HfS2 monolayer. The adsorption energy of CH4 on Co@HfS2 is stronger than those of Rh@HfS2 and Ir@HfS2, but the adsorption energy is still very small. By applying biaxial strain to Co@HfS2, we found that the adsorption energy increases with the increase in negative strain. This study provides a theoretical basis for the regulation of the adsorption properties of HfS2 by different transition metals.

Adsorption of NO2, NO, NH3, and CO on Noble Metal (Rh, Pd, Ag, Ir, Pt, Au)-Modified Hexagonal Boron Nitride Monolayers: A First-Principles Study

To investigate the application of modified hexagonal boron nitride (h-BN) in the detection and monitoring of harmful gases (NO2, NO, NH3, and CO), first-principles calculations are applied to study the geometric structure and electronic behavior of the adsorption system. In this paper, the four adsorption sites, namely, B, N, bridge, and hollow sites, are considered to explore the stable adsorption structure of metals (M = Rh, Pd, Ag, Ir, Pt, and Au) on the BN surface. The calculation results demonstrate that the geometric structures of metal at the N-site are relatively stable. Subsequently, the different adsorption structures of NO2, NO, NH3, and CO on M-BN are researched. The electron transfer, charge difference density, and work function of the stable adsorption structure are calculated. The results show that NO2, NO, and CO have the strongest adsorption capacity in the Ir-BN system, with adsorption energies of -2.705, -5.064, and -3.757 eV, respectively. The Pt-BN system has an excellent adsorption performance (-2.251 eV) for NH3. Compared with the M-BN system, the work function of the adsorption system increases after adsorbing NO2, while it decreases after adsorbing NH3. This work shows that h-BN with metal modification is a potential material for online monitoring of harmful gases.