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Abstract Turbo codes play a crucial role in wireless communication systems, and their compiled code structures are key factors affecting the performance of the entire communication system. As a result, the study of turbo compiled code structures has been a focal point for researchers. The iterative decoding of turbo code structures has multiple limitations and large storage resource consumption, leading to poor system anti‐interference ability and a rapid increase in BER. To address these issues, this paper proposes the mimic turbo compiled code structure (MTCCS) for wireless communication systems. MTCCS is based on the DHR idea, incorporating dynamic, heterogeneous, and redundancy characteristics. Dynamicity is achieved through a dynamic scheduling algorithm based on abnormal feedback information. Heterogeneity is achieved through a codec component collection design method based on intrinsic and extrinsic heterogeneity. Redundancy is achieved through a majority voting algorithm. At the beginning of information transmission, MTCCS randomly selects heterogeneous codecs from the heterogeneous codec collection to enter the runtime pool. After the information transmission is complete, the majority voting algorithm is used to adjudicate the multi‐mode output of the codecs, resulting in a relatively accurate decoding outcome. Meanwhile, the dynamic scheduling module calculates the abnormal feedback information of each codec and accordingly dynamically schedules the mimic turbo codecs to replace the abnormal ones. Through the above process, MTCCS realizes the adaptive compilation code and improves the anti‐interference ability of turbo code. Simulation experiments are conducted on MTCCS in both non‐interference and interference scenarios. Simulation experiments show that MTCCS introducing the DHR idea achieves a balance between anti‐interference and decoding performance. It effectively addresses the issue of poor anti‐interference ability in turbo codes, and the decoding performance of MTCCS is superior to that of the previous single conventional turbo codes.

Abstract Reducing interface nonradiative recombination is important for realizing highly efficient perovskite solar cells. In this work, we develop a synergistic bimolecular interlayer (SBI) strategy via 4-methoxyphenylphosphonic acid (MPA) and 2-phenylethylammonium iodide (PEAI) to functionalize the perovskite interface. MPA induces an in-situ chemical reaction at the perovskite surface via forming strong P-O-Pb covalent bonds that diminish the surface defect density and upshift the surface Fermi level. PEAI further creates an additional negative surface dipole so that a more n-type perovskite surface is constructed, which enhances electron extraction at the top interface. With this cooperative surface treatment, we greatly minimize interface nonradiative recombination through both enhanced defect passivation and improved energetics. The resulting p-i-n device achieves a stabilized power conversion efficiency of 25.53% and one of the smallest nonradiative recombination induced V oc loss of only 59 mV reported to date. We also obtain a certified efficiency of 25.05%. This work sheds light on the synergistic interface engineering for further improvement of perovskite solar cells.

Abstract Understanding the evolution mechanism of cracks helps to evaluate the behavior and performance of rock masses and provides a theoretical basis for the mechanism of crack propagation and instability. For this purpose, a rock mechanics testing system and an acoustic emission monitoring system were used to conduct acoustic emission positioning experiments on coal samples under uniaxial compression. According to clustering theory, the distribution pattern of microcracks and the dynamic evolution process of multiple cracks were studied. Subsequently, the reasons for the change in the spatio-temporal entropy (H) and fractal dimension (D) of a single crack were revealed. The research results show that microcracks present a statistical equilibrium distribution, the Gaussian distribution model is applicable to cluster crack distribution patterns, and a machine learning method can effectively identify cracks. The fractal dimension reflects the spatial characteristics of three-dimensional elliptical cracks, and low-dimensional cluster cracks are more likely to develop into macroscopic cracks. The change of H is related to the formation process of cracks, and an abnormal H (sudden increase and sudden decrease) could provide precursor information for the instability of coal samples. This research provides a new method to study crack distributions and formations and shows the competitiveness of the method in evaluating the damage state of coal.

Microseismic (MS) monitoring is an effective method for tracking the development of rock fractures. However, the utilization of existing data is severely limited by current visualization techniques. In this study, the evolution characteristics of MS parameters during the rock fracture process were investigated using MS localization techniques and spatial clustering methods. Machine learning methods were applied to cluster acoustic emission events, enabling the automatic identification of hazardous regions and the construction of crack propagation trajectories. The applicability of clustering methods was assessed using MS monitoring data collected during an in situ rock fracture process. The research results show that the spatial clustering method can effectively delineate hazardous areas, and the changes in these regions reflect the progressive development of rock mass fractures. Regions with a higher proportion of high-energy MS events pose greater risks. Additionally, the propagation trajectory of MS events can effectively characterize the concentration and development direction of fractures. This study provides valuable insights into the characterization of crack evolution and seepage channels.

Workpiece surface defect detection is an indispensable part of intelligent production. The surface information obtained by traditional 2D image detection has some limitations due to the influence of environmental light factors and part complexity. However, the digital twin model has the characteristics of high fidelity and scalability, and the digital twin surface can be obtained by a device with a scanning accuracy of 0.02mm to achieve the representation of the real surface of the workpiece. The surface defect detection system for digital twin models is proposed based on the improved YOLOv5 model in this paper. Firstly, the digital twin model of the workpiece is reconstructed by the point cloud data obtained by the scanning device, and the surface features with defects are captured. Subsequently, the training dataset is calibrated based on the defect surface, where the defect types include Inclusion, Perforation, pitting surface and Rolled-in scale. Finally, the improved YOLOv5 model with CBAM mechanism and BiFPN module was used to identify the surface defects of the digital twin model and compare it with the original YOLOv5 model and other common models. The results show that the improved YOLOv5 model can realize the identification and classification of surface defects. Compared with the original YOLOv5 model, the mAP value of the improved YOLOv5 model has increased by 0.2%, and the model has high precision. On the basis of the same data set, the improved YOLOv5 model has higher recognition accuracy than other models, improving 11.7%, 3.4%, 6.2%, 33.5%, respectively. As a result, this study provides a practical and systematic detection method for digital twin model surface during the intelligent production process, and realizes the rapid screening of the workpiece with defects.

Reducing energy loss of sub-cells is critical for high performance tandem organic solar cells. Here, the authors design and synthesize an ultra-narrow bandgap acceptor through replacement of terminal thiophene by selenophene in the central fused ring, achieving efficiency of 19% for tandem cells.

The plant-derived enzyme induced calcium carbonate precipitation (EICP) can significantly improve the engineering mechanical properties of sand. However, there is no specification for choosing the parameter value in the specific operation, and the solidification effect needs to be improved. Based on soybean urease, the effects of temperature, urease concentration, urea concentration, calcium concentration, pH value, calcium source type and other variables on urease activity and calcium carbonate precipitation were studied, and the SEM and XRD tests on precipitated calcium carbonate crystals were carried out. On this basis, the unconfined compressive strength and solidification effect of soybean urease-solidified sand were tested. The results showed that the urease activity increased linearly with the increase of urease concentration, but there was a temperature threshold. When the temperature exceeded the threshold, urease activity was completely inactivated, and the threshold decreased with the increase of urease concentration. Urea concentration and pH value affected urease activity together, and there was an optimum combination, i.e. the optimum pH value is 7 when urea concentration is 0.1–1 mol/L, and 8 when urea concentration is 1.0–1.5 mol/L. Urease is the catalyst of a precipitation reaction. The higher the urease concentration was, the more complete the reaction was, and the higher the precipitation rate of calcium carbonate was. For urea and calcium solutions, the dosage mainly affected the precipitation of calcium carbonate, and the dosage ratio should be 1:1. The concentration and pH value of urea and calcium solutions can affect the precipitation of calcium carbonate by affecting urease activity. Different calcium sources had little influence on the amount of precipitated calcium carbonate. The composition and density of precipitated calcium carbonate crystals from different calcium sources were basically the same, but the crystal structure was different. The calcium carbonate crystals with calcium chloride as calcium source are mainly massive, with spherical and spheroidal crystals on the surface and large cementation surface, which can be used as an ideal calcium source in EICP technology. The unconfined compressive strength of the sand solidified with urease from soybean and calcium chloride as calcium source was about 6 times that of the sand mixed with coal fly ash. SEM images show that the precipitated calcium carbonate crystals wrap and bond the sand into a whole, and the solidification effect is ideal.

High-performance organic solar cells call for novel designs of acceptor molecules. Here, He et al. design and synthesize a non-fullerene acceptor with an asymmetric structure for diverse donor:acceptor interfacial conformations and report a certificated power conversion efficiency of 18.2%.

Understanding the characteristics and evolution of crack propagation in rock masses is crucial for evaluating their stability. By applying clustering theory to analyze recorded microseismic events, we differentiate the development positions of individual cracks amidst multiple crack formations. Three distinct crack cluster distribution patterns are identified, allowing for the evaluation of regional stability through microseismic event density and ellipsoidal model parameters. The process of crack propagation involves independent development at nucleation positions, mutual influence between adjacent locations, and subsequent crack growth and propagation. Additionally, we examine crack evolution prior to roof collapse and establish a connectivity model between surface and goaf roof cracks. When microseismic events are identified as developing along a plane, it indicates a higher risk of damage in that area. Through the analysis of crack propagation location and angle, our study provides a theoretical foundation for predicting crack direction. Notably, our model’s findings align with onsite observations, demonstrating its practical effectiveness. The results of this research offer valuable insights for collapse prediction and early warning systems for mine roofs, contributing to advancements in mining safety and operations.

BackgroundAccording to epidemiological evidence, people with type 2 diabetes mellitus have a higher risk of developing colorectal cancer.ObjectiveTo examine the relationship between colorectal cancer (CRC) and serum levels of IGF-1, IGF-1R, AGEs,RAGE and sRAGE in patients with type 2 diabetes.MethodsBy using RNA−Seq data of CRC patients from The Cancer Genome Atlas (TCGA) database, we divided the patients into normal group(58 patients)and tumor group(446 patients), and analyzed the expression and prognostic value analysis of IGF-1,IGF1R and RAGE. Cox regression and the Kaplan-Meier method were used to determine the predictive value of target gene on clinical outcomes in CRC patients. In order to further combine CRC with diabetes research,one hundred forty-eight patients hospitalized in the Second Hospital of Harbin Medical University from July 2021 to July 2022 were enrolled and divided into CA and control groups. There were 106 patients in the CA group, including 75 patients with CRC and 31 patients with CRC+T2DM; the control group comprised 42 patients with T2DM. Circulating levels of IGF-1, IGF-1R, AGEs, RAGE, and sRAGE in the serum of the patients were measured using Enzyme-Linked Immunosorbnent Assay (ELISA) kits, and other clinical parameters were also measured during hospitalization. Statistical methods used were χ² test, independent samples t-test and Pearson correlation analysis were. Finally, we controlled for confounding factors and used logistic multi-factor regression analysis.ResultsBioinformatics analysis showed that IGF-1, IGF1R and RAGE were highly expressed in CRC patients, and the patients with high expression also showed significantly lower overall survival rate. Through Cox regression analysis, IGF-1 can be used as an independent influencing factor of CRC. In the ELISA experiment, serum AGE, RAGE, IGF-1, and IGF-1R levels were higher in the CRC and CRC+T2DM groups than in the T2DM group, but the serum sRAGE concentrations in these groups were lower than those in the T2DM group (P < 0.05). Serum AGE, RAGE, sRAGE, IGF1, and IGF1R levels were higher in the CRC+T2DM group than in the CRC group (P < 0.05). In CRC+T2DM patients, serum AGEs were correlated with age (p = 0.027), and the serum AGE levels in these groups were positively correlated with RAGE and IGF-1 levels (p < 0.001) and negatively correlated with sRAGE and IGF-1R levels (p < 0.001). After correcting for confounding factors based on logistic multiple regression analysis, the effects of age, serum IGF-1 and IGF-1R on the development of CRC in patients with T2DM were statistically significant (p

Morphology of organic thin film, including the in-plane and out-of-plane directions, plays a crucial role in determining the performance of organic solar cells, yet the characterisation is challenging for the out-of-plane direction. Here, the authors use GTSAXS to uncover the nanomorphology in this dimension, and show how it affects exciton dissociation and charge transfer.

Understanding correlations between molecular structures and macroscopic properties is critical in realising highly efficient organic photovoltaics. Here, the authors conduct a comprehensive study based on four non-fullerene acceptors revealing how the extended conjugation, asymmetric terminals and alkyl chain length can affect device performance.

Cross-platform binary code similarity detection is determining whether a pair of binary functions coming from different platforms are similar, and plays an important role in many areas. Traditional methods focus on using platform-independent characteristic strands intersecting or control flow graph (CFG) matching to compute the similarity and have shortages in terms of efficiency and scalability. The existing deep-learning-based methods improve the efficiency but have a low accuracy and still using manually constructed features. Aiming at these problems, a cross-platform binary code similarity detection method based on neural machine translation (NMT) and graph embedding is proposed in this manuscript. We train an NMT model and a graph embedding model to automatically extract two parts of semantics of the binary code and represent it as a high-dimension vector, named an embedding. Then the similarity of two binary functions can be measured by the distance between their corresponding embeddings. We implement a prototype named SimInspector. Our comparative experiment result shows that SimInspector outperforms the state-of-the-art approach, Gemini, by about 6% with respect to similarity detection accuracy, and maintains a good efficiency.

Non-fullerene acceptors have contributed hugely to the best-performing organic solar cells, yet the photo-degradation remains a hurdle preventing the practical application. In this work, research group from Zhejiang University discovers non-fused acceptors with excellent photochemical tolerance in aerobic condition, and identify the main degradation pathway.

Microseismic monitoring is a common monitoring tool in the mining production process; for supervising a huge amount of microseismic data, effective analysis tools are necessary. In this study, the monitoring results of microseismic events at the Maoping lead-zinc mine in Yiliang County, Yunnan Province, and the spatiotemporal distribution characteristics of microseismic events are analyzed. We analyze the temporal characteristics of microseismic events using fractal theory, combining the change in fractal dimension with the rock burst incubation process. We also construct an observation area model for event anomalies based on the spatial distribution characteristics of microseismic events. The results show that the growth of the fractal dimension is consistent with the trend of the incubation process before rock burst, and the larger the fractal dimension, the higher the rock burst risk. The observation model, based on the density of microseismic events, can effectively refine the rock burst discrimination range and facilitate subsequent observations. An effective and feasible method of microseismic analysis is provided.

To further understand the changing pattern of the bottom structure’s ground pressure activity under the influence of faults, predicting the potential occurrence of geological hazards and rock blast problems to reduce the loss of resources is important. A new microseismic monitoring system was established based on the original Pulang copper mine microseismic monitoring system. This paper analyzed the change law of the microseismic events on the fault in the first mining area of the Pulang copper mine, calculated the cumulative apparent volume and energy index changes of the microseismic events near the fault base, and quantitatively analyzed the microseismic event anomalies under the influence of the fault. The results show that rupture of the rock makes the cumulative apparent volume and energy index change significantly, while the timeliness of both makes the cumulative apparent volume predictive of the occurrence of rock fracture and rockburst, and the number of microseismic events corresponds to the intensity of the fault activation, which plays a predictive and guiding role in the subsequent study of fault activation, stability monitoring, and safe production in the mine area of Pulang copper mine.

Abstract The tuning of vertical morphology is critical and challenging for organic solar cells (OSCs). In this work, a high open‐circuit voltage (VOC) binary D18‐Cl/L8‐BO system is attained while maintaining the high short‐circuit current (JSC) and fill factor (FF) by employing 1,4‐diiodobenzene (DIB), a volatile solid additive. It is suggested that DIB can act as a linker between donor or/and acceptor molecules, which significantly modifies the active layer morphology. The overall crystalline packing of the donor and acceptor is enhanced, and the vertical domain sizes of phase separation are significantly decreased. All these morphological changes contribute to exciton dissociation, charge transport, and collection. Therefore, the best‐performing device exhibits an efficiency of 18.7% with a VOC of 0.922 V, a JSC of 26.6 mA cm−2, and an FF of 75.6%. As far as it is known, the VOC achieved here is by far the highest among the reported OSCs with efficiencies over 17%. This work demonstrates the high competence of solid additives with two iodine atoms to tune the morphology, particularly in the vertical direction, which can become a promising direction for future optimization of OSCs.

Abstract Two new fused‐ring electron acceptor (FREA) isomers with nonlinear and linear molecular conformation, m‐BAIDIC and p‐BAIDIC, are designed and synthesized. Despite the similar light absorption range and energy levels, the two isomers exhibit distinct electron reorganization energies and molecular packing motifs, which are directly related to the molecular conformation. Compared with the nonlinear acceptor, the linear p‐BAIDIC shows more ordered molecular packing and higher crystallinity. Furthermore, p‐BAIDIC‐based devices exhibit reduced nonradiative energy loss and improved charge transport mobilities. It is beneficial to enhance the open‐circuit voltage (VOC) and short‐current current density (JSC) of the devices. Therefore, the linear FREA, p‐BAIDIC yields a relatively higher efficiency of 7.71% in the binary device with PM6, in comparison with the nonlinear m‐BAIDIC. When p‐BAIDIC is incorporated into the binary PM6/BO‐4Cl system to form a ternary system, synergistic enhancements in VOC, JSC, fill factor (FF), and ultimately a high efficiency of 17.6% are achieved.

Near-infrared light-emitting diodes (NIR-LEDs) are widely used in various applications such as night-vision devices, optical communication, biological imaging and optical diagnosis. The current solution-processed high-efficiency perovskite NIR-LEDs are typically based on CsPbI3 and FAPbI3 with emission peaks being limited in the range of 700–800 nm. NIR-LEDs with longer emission wavelengths near to 900 nm can be prepared by replacing Pb with Sn. However, Sn-based perovskite LEDs usually exhibit a low efficiency owing to the high concentration of Sn-related defects and the rapid oxidation of Sn2+ to Sn4+, which further induces the device degradation. These problems can be solved by rationally adjusting the ratio between Pb content with Sn. Mixed Sn-Pb halide perovskites with a smaller bandgap and superior stability than pure Sn-based perovskites are promising candidates for manufacturing next-generation NIR emitters. In this study, we systematically investigated the optical properties of a family of hybrid Sn and Pb iodide compounds. The emission spectra of the mixed Sn-Pb halide perovskites were tuned by changing the Sn:Pb ratio. Consequently, the peak emission wavelength red-shifted from 710 nm to longer than 950 nm. The absorption and photoluminescence emission properties associated with different compositions were compared, and the results demonstrated the potential of MA- and FA-based mixed Sn-Pb halide perovskites for preparing low-cost and efficient NIR-LEDs. In addition, we clarified the influence of cations on the bandgap bowing effect and electronic properties of mixed Sn-Pb halide perovskites.

Abstract The heterointerface between the contacted organic and inorganic semiconductors critically affects the charge extraction, hence overall performance of organic optoelectronics, especially for organic solar cells (OSCs). Herein, we develop an effective interfacial strategy that simultaneously boosts the chemical, electric, and electronic properties of the organic–inorganic heterointerface of the derived OSCs, through implanting conjugated molecules as self‐assemble monolayers (SAMs) to metal oxide nanoparticles (MO NPs). As results, SAM passivated zinc oxide nanoparticles (ZnO NPs) as electron transport layers (ETLs) not only enable the best performed OSCs containing MO ETLs, but also exhibit the most desirable thickness insensitive features (up to 300 nm). In addition, SAM‐ZnO ETLs help also substantially improving the photostability of the derived OSCs. Overall, this work can be beneficial to the further development of high‐performance and cost‐effective OSCs.

Abstract All‐inorganic perovskite quantum dots (QDs) CsPbX3 (X = Cl, Br, and I) have recently emerged as a new promising class of X‐ray scintillators. However, the instability of perovskite QDs and the strong optical scattering of the thick opaque QD scintillator film imped it to realize high‐quality and robust X‐ray image. Herein, the europium (Eu) doped CsPbBr3 QDs are in situ grown inside transparent amorphous matrix to form glass‐ceramic (GC) scintillator with glass phase serving as both matrix and encapsulation for the perovskite QD scintillators. The small amount of Eu dopant optimizes the crystallization of CsPbBr3 QDs and makes their distribution more uniform in the glass matrix, which can significantly reduce the light scattering and also enhance the photoluminescence emission of CsPbBr3 QDs. As a result, a remarkably high spatial resolution of 15.0 lp mm−1 is realized thanks to the reduced light scattering, which is so far a record resolution for perovskite scintillator based X‐ray imaging, and the scintillation stability is also significantly improved compared to the bare perovskite QD scintillators. Those results provide an effective platform particularly for the emerging perovskite nanocrystal scintillators to reduce light scattering and improve radiation hardness.

Antimony trisulfide has a proper bandgap of 1.7 eV for making solar cells but the devices suffer from severe voltage loss. Here Yang et al. propose that the photoexcited carriers are self-trapped by lattice deformation, which places a thermodynamic limit of only 0.8 V for the open circuit voltage.

Background Tumor mutation burden (TMB) is an important determinant and biomarker for response of targeted therapy and prognosis in patients with lung cancer. The present study aimed to determine whether radiomics signature could non‐invasively predict the TMB status and driver mutations in patients with resectable early stage lung adenocarcinoma (LUAD). Methods A total of 61pulmonary nodules (PNs) from 51 patients post‐operatively diagnosed LUAD were enrolled for analysis. Two datasets were divided according to two‐thirds of patients from different commercial Comprehensive Genomic Profiling (CGP) panels: a training cohort including 41 PNs and a testing cohort including rest 20PNs. We sequenced all tumor specimens and paired blood cells using next generation sequencing (NGS), so as to detect TMB status and somatic mutations. We collected 718 quantitative 3D radiomics features extracted from segmented volumes of each PNs and 78 clinical and pathological features retrieved from medical records as well. Support vector machine methods were performed to establish the predictive model. Results We established an efficient fusion‐positive tumor prediction model that predicts TMB status and EGFR/TP53 mutations of early stage LUAD. The radiomics signature yielded a median AUC value of 0.606, 0.604, and 0.586 respectively. Combining radiomics with the clinical information can further improve the prediction performance, which the median AUC values are 0.671 for TMB, 0.697 and 0.656 for EGFR/TP53 respectively. Conclusion It is feasible and effective to facilitate TMB and somatic driver mutations prediction by using the radiomics signature and NGS data in early stage LUAD.

Cancer patients who initially benefit from Erlotinib, a drug targeting EGFR path, eventually develop resistance to the drug. The underlying mechanism is largely unknown. This study investigated the role of ARL4C in Erlotinib resistance development of NSCLC. qRT-PCR and Western blotting were performed to analyze the expression of mRNA and protein of ARL4C in two NSCLC cell lines (HCC827 and PC-9). Several assays (MTS, colony formation, transwell migration, luciferase reporter, and chromatin-immunoprecipitation) were used to explore the role of ARL4C in biofunctional changes of Erlotinib-resistant cells and their associations with Jak2/Stat 5/β-catenin signaling. Results demonstrated that (1) long-term use of Erlotinib resulted in downregulation of ARL4C; (2) overexpression of ARL4C could regain the sensitivity to Erlotinib in the drug-resistant HCC827/ER cells, while downregulation of ARL4C increased HCC827, and PC-9 cells' resistance to the drug; (3) Erlotinib-induced downregulation of ARL4C resulted in phosphorylation of Jak2/Stat5 and upregulation of β-catenin and their related molecules Axin2, CD44, Ccnd1, Lgr-5, and MMP7, which promoted the malignant behaviors of Erlotinib-resistant cells; (4) chromatin immunoprecipitation and luciferase reporter assay revealed that Stat5 could bind to β-catenin promoter to upregulate molecules to maintain the malignant behaviors, which might count for how Erlotinib-resistant cell survived while EGFR path was blocked; (5) the expression of ARL4C was not associated with known EGFR gene mutations in both Erlotinib-resistant cells and NSCLC tissues. Our data suggest that Erlotinib resistance of NSCLCs is associated with downregulation of ARL4C via affecting Jak/Stat/β-catenin signaling. ARL4C could serve as a biomarker to predict the effectiveness of TKI targeting therapy and a potential therapeutic target for overcoming Erlotinib resistance in NSCLC.

The right to be forgotten is a new trending right that originated from the European Union and is transferring to China. To break down the Bentham’s panopticon of comprehensive digital memory, it is necessary for China to adopt the right to be forgotten. While the Chinese legal framework of personal information has not been completed yet, the Draft of Personal Information Law implies a focus on duties of controllers and interests of minors. By analysing possible legal attributes of the right to be forgotten, it can be noted that typifying the right to be forgotten is essential, but the problem of exercising limitation and of the asymmetric information market have not been solved. To tackle these problems, one solution is to specify the requirements of the government, the organization and the information subject with balance; the other is to perfect the right to be forgotten referring to the Informed Consent Principle and complement other principles to support the entire personal information protection system.

Abstract In this study, a uniform nanoporous NiO film, with a thickness of up to 2.6 μm, was prepared using polyethylene glycol (PEG). The addition of PEG significantly decreased the cracks in the NiO film and prevented the peeling of the NiO film from a fluorine-doped tin oxide substrate. The NiO cathode was prepared using CdSeS quantum dots (QDs) as the sensitizer, with an optimized photoelectric conversion of 0.80%. The optimized QD-sensitized NiO films were first assembled with the TiO2 anode to prepared QD-sensitized p–n-type tandem solar cells. The open circuit voltage was greater than that obtained using the separated NiO cathode or TiO2 anode.

Diamond-like carbon(DLC) films had many unique and outstanding properties such as high thermal conductivity, high hardness, excellent chemical inertness, low friction coefficients and wear coefficients. The properties and combinations were very promising for heat sink, micro-electromechanical devices, radiation hardening, biomedical devices, automotive industry and other technical applications, more research and a lot of attention were attracted in recent years. The research progress of diamond-like films and the nucleation mechanism of film were summarized, and application prospect of DLC films were demonstrated. The aim of this paper is to provide insights on the research trend of DLC films and the industry applications.

In order to improve the transmission performance and efficiency,the mathematical model is established based on the main design parameters of multi- axis micro- cultivator gearbox. Then the optimization program of the key design parameters is programmed combining the SGA,the NSGA- Ⅱ with MATLAB language. Finally,the mathematical model are optimized using this program and the optimization results are compared. The optimization results show that volume decreased respectively by 14. 13% and 15. 96% and coincidence degree are improved respectively by 4. 07% and 4. 60% by using the SGA and the NSGA- Ⅱalgorithm optimization. A good optimization effect is got and the NSGA- Ⅱ algorithm is better.

Al doped SnO2 microspheres were prepared through hydrothermal method. As-prepared SnO2 microspheres were applied as photoanode materials in dye-sensitized solar cells (DSCs). The properties of the assembled DSCs were significantly improved, especially the open-circuit voltage. The reason for the enhancement was explored through the investigation of dark current curves and electrochemistry impedance spectra. These results showed that the Al doping significantly increased the reaction resistance of recombination reactions and restrained the dark current. The efficient lifetime of photoexcited electrons was also obviously lengthened.

The electrochemical behaviors of Al(III) deposits on Ni substrates were investigated in LiCl-KCl-AlCl3 (2 wt.%) molten salts. Various electrochemical methods, including cyclic voltammetry (CV), square wave voltammetry (SWV), and open circuit chronopotentiometry (OCP) were used to explore the deposition processes of Al(III) on Ni substrates. Five kinds of Al-Ni alloys phase were firstly electrodeposited by the regulation of deposition potential form LiCl-KCl-AlCl3 (2 wt.%) molten salts at 753 K. The formation of Al-Ni alloys, such as AlNi3, Ni5Al3, AlNi, Al3Ni2, and Al3Ni were confirmed by X-ray diffractometer (XRD) and the cross-section morphologies were investigated by scanning electron microscope (SEM). Meanwhile, it was found that the temperature of molten salt was another key parameter for the controlling of alloys phase. No Al-Ni alloys phase other than AlNi3 and Ni5Al3 could be deposited at 703 K.