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.     

Theoretical prediction of structure,electronic and optical properties of VH2 hydrogen storage material

The vanadium hydrides have better hydrogen storage capacity in comparison to the other metal hydrides. Although the structure of VH₂ hydride has been reported, the structural stability, electronic and optical properties of VH₂ hydride are unclear. To solve these problems, we apply the first-principles method to study the structural stability, electronic and optical properties of VH₂ hydrides. Similar to the metal dihydrides, four possible VH₂ hydrides such as the cubic (Fm-3m), tetragonal (I4/mmm), tetragonal (P4₂/mnm) and orthorhombic (Pnma) are designed. The result shows that the cubic VH₂ hydride is a thermodynamic and dynamical stability. In particular, the tetragonal (I4/mmm) and the orthorhombic (Pnma) VH₂ hydrides are firstly predicted. It is found that these VH₂ hydrides show metallic behavior. The electronic interaction of V (d-state)-H (s-state) is beneficial to improve the hydrogen storage in VH₂ hydride. In addition, the formation of V–H bond can improve the structural stability of VH₂ hydride. Based on the analysis of optical properties, it is found that all VH₂ hydrides show the ultraviolet response. Compared to the tetragonal and orthorhombic VH₂ hydrides, the cubic VH₂ hydride has better storage optical properties. Therefore, we believe that the VH₂ hydride is a promising hydrogen storage material.     

Recent insights in synthesis and energy storage applications of porous carbon derived from biomass waste: A review

In the last few decades, global warming, environmental pollution, and an energy shortage of fossil fuel may cause a severe economic crisis and health threats. Storage, conversion, and application of regenerable and dispersive energy would be a promising solution to release this crisis. The development of porous carbon materials from regenerated biomass are competent methods to store energy with high performance and limited environmental damages. In this regard, bio-carbon with abundant surface functional groups and an easily tunable three-dimensional porous structure may be a potential candidate as a sustainable and green carbon material. Up to now, although some literature has screened the biomass source, reaction temperature, and activator dosage during thermochemical synthesis, a comprehensive evaluation and a detailed discussion of the relationship between raw materials, preparation methods, and the structural and chemical properties of carbon materials are still lacking. Hence, in this review, we first assess the recent advancements in carbonization and activation process of biomass with different compositions and the activity performance in various energy storage applications including supercapacitors, lithium-ion batteries, and hydrogen storage, highlighting the mechanisms and open questions in current energy society. After that, the connections between preparation methods and porous carbon properties including specific surface area, pore volume, and surface chemistry are reviewed in detail. Importantly, we discuss the relationship between the pore structure of prepared porous carbon with surface functional groups, and the energy storage performance in various energy storage fields for different biomass sources and thermal conversion methods. Finally, the conclusion and prospective are concluded to give an outlook for the development of biomass carbon materials, and energy storage applications technologies. This review demonstrates significant potentials for energy applications of biomass materials, and it is expected to inspire new discoveries to promote practical applications of biomass materials in more energy storage and conversion fields.     

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.     

纳米药物非临床药代动力学的研究策略及关注要点

随着纳米技术的迅速发展，纳米药物的研发已成为目前药物创新的发展方向之一。纳米药物具有基于纳米结构的尺度效应，其药代动力学特征与普通药物相比存在明显差异，其药代动力学研究与普通药物相比也有其特殊性。本文着重探讨纳米药物的非临床药代动力学的研究策略及关注要点，包括受试物、体内/外试验、生物样本分析、数据评价分析等，期望为研发者提供参考。     

Comparative analysis of inbreeding parameters and runs of homozygosity islands in 2 Italian autochthonous cattle breeds mainly raised in the Parmigiano-Reggiano cheese production region

Reggiana and Modenese are autochthonous cattle breeds, reared in the North of Italy, that can be mainly distinguished for their standard coat color (Reggiana is red, whereas Modenese is white with some pale gray shades). Almost all milk produced by these breeds is transformed into 2 mono-breed branded Parmigiano-Reggiano cheeses, from which farmers receive the economic incomes needed for the sustainable conservation of these animal genetic resources. After the setting up of their herd books in 1960s, these breeds experienced a strong reduction in the population size that was subsequently reverted starting in the 1990s (Reggiana) or more recently (Modenese) reaching at present a total of about 2,800 and 500 registered cows, respectively. Due to the small population size of these breeds, inbreeding is a very important cause of concern for their conservation programs. Inbreeding is traditionally estimated using pedigree data, which are summarized in an inbreeding coefficient calculated at the individual level (F_PED). However, incompleteness of pedigree information and registration errors can affect the effectiveness of conservation strategies. High-throughput SNP genotyping platforms allow investigation of inbreeding using genome information that can overcome the limits of pedigree data. Several approaches have been proposed to estimate genomic inbreeding, with the use of runs of homozygosity (ROH) considered to be the more appropriate. In this study, several pedigree and genomic inbreeding parameters, calculated using the whole herd book populations or considering genotyping information (GeneSeek GGP Bovine 150K) from 1,684 Reggiana cattle and 323 Modenese cattle, were compared. Average inbreeding values per year were used to calculate effective population size. Reggiana breed had generally lower genomic inbreeding values than Modenese breed. The low correlation between pedigree-based and genomic-based parameters (ranging from 0.187 to 0.195 and 0.319 to 0.323 in the Reggiana and Modenese breeds, respectively) reflected the common problems of local populations in which pedigree records are not complete. The high proportion of short ROH over the total number of ROH indicates no major recent inbreeding events in both breeds. ROH islands spread over the genome of the 2 breeds (15 in Reggiana and 14 in Modenese) identified several signatures of selection. Some of these included genes affecting milk production traits, stature, body conformation traits (with a main ROH island in both breeds on BTA6 containing the ABCG2, NCAPG, and LCORL genes) and coat color (on BTA13 in Modenese containing the ASIP gene). In conclusion, this work provides an extensive comparative analysis of pedigree and genomic inbreeding parameters and relevant genomic information that will be useful in the conservation strategies of these 2 iconic local cattle breeds.     

Microwave hybrid fast sintering of red clay ceramics

This work aimed to examine the performance of the hybrid sintering of clay ceramic in a microwave furnace, compared to the sintering process in a conventional furnace. The raw materials were subjected to X-ray fluorescence, loss on ignition (LOI), X-ray diffraction, particle size distribution, real specific mass, and thermogravimetric analyses. The red clay ceramic mass was prepared, extruded, pre-sintered in a conventional furnace at 600°C/60 min, and sintered at temperatures between 700 °C and 1100 °C. The sintering conventional (resistive oven) was carried out for 60 min with a heating rate of 10°C/min. In the microwave furnace, the sintering times were 5, 10, and 15 min, with a heating rate of 50°C/min, with a sintering chamber coated with silicon carbide (susceptor). The sintered specimens were characterized according to linear shrinkage, water absorption, apparent porosity, apparent specific mass, X-ray diffraction, Raman spectroscopy analysis, spectroscopy analysis in the ultraviolet and visible regions, microhardness, and scanning electron microscopy. The results showed that microwave sintering promoted an increase in the microhardness and apparent specific mass, and reduction in water absorption and apparent porosity values, due to greater densification in the microstructure. The best results occurred for specimens sintered at 1100°C.     

Feature selection methods for root-cause analysis among top-level product attributes

Manufacturing companies not only strive to deliver flawless products but also monitor product failures in the field to identify potential quality issues. When product failures occur, quality engineers must identify the root cause to improve any affected product and process. This root-cause analysis can be supported by feature selection methods that identify relevant product attributes, such as manufacturing dates with an increased number of product failures. In this paper, we present different methods for feature selection and evaluate their ability to identify relevant product attributes in a root-cause analysis. First, we compile a list of feature selection methods. Then, we summarize the properties of product attributes in warranty case data and discuss these properties regarding the challenges they pose for machine learning algorithms. Next, we simulate datasets of warranty cases, which emulate these product properties. Finally, we compare the feature selection methods based on these simulated datasets. In the end, the univariate filter information gain is determined to be a suitable method for a wide range of applications. The comparison based on simulated data provides a more general result than other publications, which only focus on a single use case. Due to the generic nature of the simulated datasets, the results can be applied to various root-cause analysis processes in different quality management applications and provide a guideline for readers who wish to explore machine learning methods for their analysis of quality data.     

Agronomic performance of high oleic,low linolenic soybean in Tennessee

Soybean oil hydrogenation alters the linolenic acid molecule to prevent the oil from becoming rancid, however, health reports have indicated trans-fat caused by hydrogenation, is not generally regarded as safe. Typical soybeans contain approximately 80 g kg⁻¹ to 120 g kg⁻¹ linolenic acid and 240 g kg⁻¹ of oleic acid. In an effort to accommodate the need for high-quality oil, the United Soybean Board introduced an industry standard for a high oleic acid greater than 750 g kg⁻¹ and linolenic acid less than 30 g kg⁻¹ oil. By combing mutations in the soybean plant at four loci, FAD2-1A and FAD2-1B, oleate desaturase genes and FAD3A and FAD3C, linoleate desaturase genes, and seed oil will not require hydrogenation to prevent oxidation and produce high-quality oil. In 2017 and 2018, a study comparing four near-isogenic lines across multiple Tennessee locations was performed to identify agronomic traits associated with mutations in FAD3A and FAD3C loci, while holding FAD2-1A and FAD2-1B constant in the mutant (high oleic) state. Soybean lines were assessed for yield and oil quality based on mutations at FAD2-1 and FAD3 loci. Variations of wild-type and mutant genotypes were compared at FAD3A and FAD3C loci. Analysis using a generalized linear mixed model in SAS 9.4, indicated no yield drag or other negative agronomic traits associated with the high oleic and low linolenic acid genotype. All four mutations of fad2-1A, fad2-1B, fad3A, and fad3C were determined as necessary to produce a soybean with the new industry standard (>750 g kg⁻¹ oleic and <30 g kg⁻¹ linolenic acid) in a maturity group-IV-Late cultivar for Tennessee growers.