General Model for Predicting Response of Gas-Sensitive Materials to Target Gas Based on Machine Learning.

Gas sensors play a crucial role in various industries and applications. In recent years, there has been an increasing demand for gas sensors in society. However, the current method for screening gas-sensitive materials is time-, energy-, and cost-consuming. Consequently, an imperative exists to enhance the screening efficiency. In this study, we proposed a collaborative screening strategy through integration of density functional theory and machine learning. Taking zinc oxide (ZnO) as an example, the responsiveness of ZnO to the target gas was determined quickly on the basis of the changes in the electronic state and structure before and after gas adsorption. In this work, the adsorption energy and electronic and structural characteristics of ZnO after adsorbing 24 kinds of gases were calculated. These computed features served as the basis for training a machine learning model. Subsequently, various machine learning and evaluation algorithms were utilized to train the fast screening model. The importance of feature values was evaluated by the AdaBoost, Random Forest, and Extra Trees models. Specifically, charge transfer was assigned importance values of 0.160, 0.127, and 0.122, respectively, ranking as the highest among the 11 features. Following closely was the d-band center, which was presumed to exert influence on electrical conductivity and, consequently, adsorption properties. With 5-fold cross-validation using the Extra Tree accuracy, the 24-sample data set achieved an accuracy of 88%. The 72-sample data set achieved an accuracy of 78% using multilayer perceptron after 5-fold cross-validation, with both data sets exhibiting low standard deviations. This verified the accuracy and reliability of the strategy, showcasing its potential for rapidly screening a material's responsiveness to the target gas.

Multi-Functional Ethylene-vinyl Acetate Copolymer Flexible Composite Film Embedded with Indium Acetate-Passivated Perovskite Quantum Dots.

In recent years, all-inorganic cesium lead halide perovskite quantum dots have emerged as promising candidates for various optoelectronic applications, including sensors, light-emitting diodes, and solar cells, owing to their exceptional photoelectric properties. However, their commercial utilization has been limited by stability issues. In this study, we addressed this challenge by passivating the surface defects of CsPbBr3 quantum dots using indium acetate, a metal-organic compound. The resulting CsPbBr3 quantum dots exhibited not only high photoluminescence intensity, but also a remarkably narrow half-peak width of 19 nm. Furthermore, by embedding the CsPbBr3 quantum dots in ethylene-vinyl acetate, we achieved stretchability and significantly enhanced stability while preserving the original luminous intensity. The resulting composite film demonstrated the potential to improve the power conversion efficiency of crystalline silicon solar cells and enabled the creation of excellent white light-emitting diodes with coordinates of (0.33, 0.31). This co-passivation strategy, involving surface passivation and polymer packaging, provides a new idea for the practical application of CsPbBr3 quantum dots.

Machine Learning-Assisted Sensor Based on CsPbBr3@ZnO Nanocrystals for Identifying Methanol in Mixed Environments.

Methanol is a respiratory biomarker for pulmonary diseases, including COVID-19, and is a common chemical that may harm people if they are accidentally exposed to it. It is significant to effectively identify methanol in complex environments, yet few sensors can do so. In this work, the strategy of coating perovskites with metal oxides is proposed to synthesize core-shell CsPbBr3@ZnO nanocrystals. The CsPbBr3@ZnO sensor displays a response/recovery time of 3.27/3.11 s to 10 ppm methanol at room temperature, with a detection limit of 1 ppm. Using machine learning algorithms, the sensor can effectively identify methanol from an unknown gas mixture with 94% accuracy. Meanwhile, density functional theory is used to reveal the formation process of the core-shell structure and the target gas identification mechanism. The strong adsorption between CsPbBr3 and the ligand zinc acetylacetonate lays the foundation for the formation of the core-shell structure. The crystal structure, density of states, and band structure were influenced by different gases, which results in different response/recovery behaviors and makes it possible to identify methanol from mixed environments. Furthermore, due to the formation of type II band alignment, the gas response performance of the sensor is further improved under UV light irradiation.

In Situ Photodeposition of Cobalt Phosphate (CoHxPOy) on CdIn2S4 Photocatalyst for Accelerated Hole Extraction and Improved Hydrogen Evolution.

The ternary metal sulfide CdIn2S4 (CIS) has great application potential in solar-to-hydrogen conversion due to its suitable band gap, good stability and low cost. However, the photocatalytic hydrogen (H2) evolution performance of CIS is severely limited by the rapid electron-hole recombination originating from the slow photogenerated hole transfer kinetics. Herein, by simply depositing cobalt phosphate (CoHxPOy, noted as Co-Pi), a non-precious co-catalyst, an efficient pathway for accelerating the hole transfer process and subsequently promoting the H2 evolution reaction (HER) activity of CIS nanosheets is developed. X-ray photoelectron spectroscopy (XPS) reveals that the Co atoms of Co-Pi preferentially combine with the unsaturated S atoms of CIS to form Co-S bonds, which act as channels for fast hole extraction from CIS to Co-Pi. Electron paramagnetic resonance (EPR) and time-resolved photoluminescence (TRPL) showed that the introduction of Co-Pi on ultrathin CIS surface not only increases the probability of photogenerated holes arriving the catalyst surface, but also prolongs the charge carrier's lifetime by reducing the recombination of electrons and holes. Therefore, Co-Pi/CIS exhibits a satisfactory photocatalytic H2 evolution rate of 7.28 mmol g-1 h-1 under visible light, which is superior to the pristine CIS (2.62 mmol g-1 h-1) and Pt modified CIS (3.73 mmol g-1 h-1).

Hierarchical NiCo2S4/ZnIn2S4 heterostructured prisms: High-efficient photocatalysts for hydrogen production under visible-light.

Exploring low-cost co-catalyst to ameliorate the photocatalytic activity of semiconductors sets a clear direction for solving energy crisis and achieving efficient solar-chemical energy conversion. In this work, a unique hierarchical hollow heterojunction was constructed by in-situ growing ZnIn2S4 nanosheets on the porous NiCo2S4 hollow prisms through a low temperature solvothermal method, in which NiCo2S4 with semi-metal property acted as non-noble metal co-catalyst. NiCo2S4 co-catalyst was innovatively encapsulated in ZnIn2S4, which not only relieved the light shielding effect caused by the large loading amount of co-catalyst, but also supplied abundant active sites for H2 evolution. The hierarchical hollow heterostructure of NiCo2S4/ZnIn2S4 provided a highly efficient channel for charge transfer. Combining these advantages, NiCo2S4/ZnIn2S4 composite demonstrated excellent photocatalytic activity. In the absence of sacrificial agent, the NiCo2S4/ZnIn2S4 photocatalyst achieved a remarkable improved H2 yield of 0.77 mmol g-1h-1 under visible light irradiation (λ > 400 nm), which is 6.6 times greater than that of ZnIn2S4. Besides, NiCo2S4 even exhibited better performance on the H2 evolution improvement of ZnIn2S4 than precious metal Pt. This work will offer novel insights into the reasonable design of non-noble metal photocatalysts with respectable activity for water splitting.

Spatial carrier separation in cobalt phosphate deposited ZnIn2S4 nanosheets for efficient photocatalytic hydrogen evolution.

Developing photocatalyst with effective charge separation and fast surface reaction kinetics is crucial to high-efficiency photocatalytic H2 evolution. Herein we spatially separate the reductive and oxidative reaction sites of ZnIn2S4 nanosheet and accelerate the hole transfer process by simply depositing cobalt phosphate (CoHxPOy, noted as Co-Pi), a non-precious co-catalyst, on its basal plane. Theoretical calculations combined with comprehensive characterizations reveal that Zn vacancies induced deep local energy levels serve as hole trap states to pin the photogenerated holes on (001) surface of ZnIn2S4. Upon Co-Pi deposition, Co atoms preferentially bond with S atoms nearby the Zn vacancies of ZnIn2S4. Taking advantage of the formation of Co-S bonds, Co-Pi acts as a hole receptor to extract the trapped holes effectively. As the photocatalytic activity of ZnIn2S4 is caused by active S atoms on its edge side, deposition of Co-Pi on planar side of nanosheets helps electron-hole migration to different facets. As a result of inert facet activation and spatial carrier separation, Co-Pi/ZnIn2S4 exhibits a superior photocatalytic H2 evolution rate of 10.19 mmol g-1h-1 under visible light, which is superior to most of reported ZnIn2S4-based photocatalysts. This work will provide novel insights into the activation of inert basal planes of two-dimensional photocatalysts.

Surface engineering of perovskite films for efficient solar cells.

It is critical to prepare smooth and dense perovskite films for the fabrication of high efficiency perovskite solar cells. However, solution casting process often results in films with pinhole formation and incomplete surface coverage. Herein, we demonstrate a fast and efficient vacuum deposition method to optimize the surface morphology of solution-based perovskite films. The obtained planar devices exhibit an average power conversion efficiency (PCE) of 13.42% with a standard deviation of ±2.15% and best efficiency of 15.57%. Furthermore, the devices also show excellent stability of over 30 days with a slight degradation <9% when stored under ambient conditions. We also investigated the effect of vacuum deposition thickness on the electron transportation and overall performance of the devices. This work provides a versatile approach to prepare high-quality perovskite films and paves a way for high-performance and stable perovskite photovoltaic devices.

ZnO based heterojunctions and their application in environmental photocatalysis.

As an alternative to TiO2 photocatalysts, ZnO exhibits a large potential for photocatalytic (PC) applications in environmental treatments, such as degradation of wastewater, sterilization of drinking water, and air cleaning. However, the efficiency achieved with ZnO to date is far from that expected for commercialization, due to rapid charge recombination, photo-corrosion as well as poor utilization of solar energy. Fortunately, in recent years, a great number of breakthroughs have been achieved in PC performance (including activity and stability) of micro-/nano- structured ZnO by forming heterojunctions (HJs) with metal nanoparticles (NPs), carbon nanostructures and other semiconductors. In most cases, the improvement of PC performance was ascribed to the better charge separation at the interfaces between ZnO and the other components. Sometimes, the formation of hybrids is also in favor of visible light harvesting. This review summarizes recent advances in the fields of environmental photocatalysis by ZnO based HJs, and especially emphasizes their abilities in degradation of organic pollutants or harmful substances in water. We aim to reveal the mechanism underlying the enhanced PC performance by constructing HJs, and extend the potential of ZnO HJ photocatalysts for future trends, and practical, large-scale applications in environment-related fields.