Study of Pb-based and Pb-free perovskite solar cells using Cu-doped Ni1-xO thin films as hole transport material

SCAPS solar cell simulation program was applied to model an inverted structure of perovskite solar cells using Cu-doped Ni_1-xO thin films as hole transport layer. The Cu-doped Ni_1-xO film were made by co-sputtering deposition under different deposition conditions. By increasing the amount of the Cu-dopant, the film crystallinity enhanced whereas the bandgap energy decreased. The transmittance of the thin films decreased significantly by increasing the sputtering power of copper. High quality, uniform, compact, and pin-hole free films with low surface roughness were achieved. The structural, chemical, surface morphology, optical, electrical, and electronic properties of the Cu doped Ni_1-xO films were used as input parameters in the simulation of Pb-based (MAPbI_3-xCl_x) and Pb-free (MAGeI₃) perovskite solar cells. Simulation results showed that the performance of both Pb-based and Pb-free perovskite solar cell devices significantly enhanced with Cu-doped Ni_1-xO film. The highest power conversion efficiency (PCE) for the Pb-free perovskite solar cell is 8.9% which is lower than the highest PCE of 17.5% for the Pb-based perovskite solar cell.     

Machine learning algorithm selection for windage alteration fault diagnosis of mine ventilation system

Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation.     

Diluted chemical bath deposition of CdZnS as prospective buffer layer in CIGS solar cell

In this study, dilute chemical bath deposition technique has been used to deposit CdZnS thin films on soda-lime glass substrates. The structural, morphological, optoelectronic properties of as-grown films have been investigated as a function of different Zn²⁺ precursor concentrations. The X-ray diffractogram of CdS thin-film reveals a peak corresponding to (002) plane with wurtzite structure, and the peak shift has been observed with the increase of the Zn²⁺ concentration upon formation of CdZnS thin film. From morphological studies, it has been revealed that the diluted chemical bath deposition technique provides homogeneous distribution of film on the substrate even at a lower concentration of Zn²⁺. Optical characterization has shown that the transparency of the film is influenced by Zn²⁺ concentration and when the Zn²⁺ concentration is varied from 0 M to 0.0256 M, bandgap values of resulting films range from 2.42 eV to 3.90 eV while. Furthermore, electrical properties have shown that with increasing zinc concentration the resistivity of the film increases. Finally, numerical simulation validates and suggests that CdZnS buffer layer with composition of 0.0032 M Zn²⁺ concentration would be a promising candidate in CIGS solar cell.     

Surface Reconstruction Engineering with Synergistic Effect of Mixed-Salt Passivation Treatment toward Efficient and Stable Perovskite Solar Cells

Surface passivation treatment is a widely used strategy to resolve trap-mediated nonradiative recombination toward high-efficiency metal-halide perovskite photovoltaics. However, a lack of passivation with mixture treatment has been investigated, as well as an in-depth understanding of its passivation mechanism. Here, a systematic study on a mixed-salt passivation strategy of formamidinium bromide (FABr) coupled with different F-substituted alkyl lengths of ammonium iodide is demonstrated. It is obtained better device performance with decreasing chain length of the F-substituted alkyl ammonium iodide in the presence of FABr. Moreover, they unraveled a synergistic passivation mechanism of the mixed-salt treatment through surface reconstruction engineering, where FABr dominates the reformation of the perovskite surface via reacting with the excess PbI₂. Meanwhile, ammonium iodide passivates the perovskite grain boundaries both on the surface and top perovskite bulk through penetration. This synergistic passivation engineer results in a high-quality perovskite surface with fewer defects and suppressed ion migration, leading to a champion efficiency of 23.5% with mixed-salt treatment. In addition, the introduction of the moisture resisted F-substituted groups presents a more hydrophobic perovskite surface, thus enabling the decorated devices with excellent long-term stability under a high humid atmosphere as well as operational conditions.     

Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

Ablative Radiotherapy Reprograms the Tumor Microenvironment of a Pancreatic Tumor in Favoring the Immune Checkpoint Blockade Therapy

The low overall survival rate of patients with pancreatic cancer has driven research to seek a new therapeutic protocol. Radiotherapy (RT) is frequently an option in the neoadjuvant or palliative settings for pancreatic cancer treatment. This study explored the effect of RT protocols on the tumor microenvironment (TME) and their consequent impact on anti-programmed cell death ligand-1 (PD-L1) therapy. Using a murine orthotopic pancreatic tumor model, UN-KC-6141, RT-disturbed TME was examined by immunohistochemical staining. The results showed that ablative RT is more effective than fractionated RT at recruiting T cells. On the other hand, fractionated RT induces more myeloid-derived suppressor cell infiltration than ablative RT. The RT-disturbed TME presents a higher perfusion rate per vessel. The increase in vessel perfusion is associated with a higher amount of anti-PD-L1 antibody being delivered to the tumor. Animal survival is increased by anti-PD-L1 therapy after ablative RT, with 67% of treated animals surviving more than 30 days after tumor inoculation compared to a median survival time of 16.5 days for the control group. Splenocytes isolated from surviving animals were specifically cytotoxic for UN-KC-6141 cells. We conclude that the ablative RT-induced TME is more suited than conventional RT-induced TME to combination therapy with immune checkpoint blockade.     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.     

Thermal transport and chemical conversion in single reacting sorbent particles

The effects of particle size and carbon dioxide concentration on chemical conversion in engineered spherical particles undergoing calcium oxide looping are investigated. Particles are thermochemically cycled in a furnace under different carbon dioxide concentrations. Changes in composition due to chemical reactions are measured using thermogravimetric analysis. Gas composition at the furnace exit is evaluated with mass spectroscopy. A numerical model of thermal transport phenomena developed previously is adapted to match the physical system investigated in the present study. The model is used to elucidate effects of reacting medium characteristics on particle temperature and reaction extent. Experimental and numerical results show that (1) an increase in particle size results in a decrease in carbonation extent, and (2) the carbonation step consists of fast and slow reaction regimes. The reaction rates in the fast and slow carbonation regimes increase with increasing carbon dioxide concentration. The effect of carbon dioxide concentration and the distinction between the fast and slow regimes become more pronounced with increasing particle size.     

高等级生物安全实验室通风空调系统冗余设计原则探讨

对比分析了国内外标准有关高等级生物安全实验室通风空调系统冗余设计的要求。结合我国已有高等级生物安全实验室,重点分析了送风机、排风机、排风高效过滤器冗余设计的具体实施形式和存在的问题,给出了冗余设计原则建议。