Dual effect synergistically triggered Ce:(Y,Tb)3(Al,Mn)5O12 transparent ceramics enabling a high color-rendering index and excellent thermal stability for white LEDs

Ce:Y₃Al₅O₁₂ transparent ceramics (TCs) with appropriate emission light proportion and high thermal stability are significant to construct white light emitting diode devices with excellent chromaticity parameters. In this work, strategies of controlling crystal-field splitting around Ce³⁺ ion and doping orange-red emitting ion, were adopted to fabricate Ce:(Y,Tb)₃(Al,Mn)₅O₁₂ TCs via vacuum sintering technique. Notably, 85.4 % of the room-temperature luminescence intensity of the TC was retained at 150 °C, and the color rendering index was as high as 79.8. Furthermore, a 12 nm red shift and a 16.2 % increase of full width at half maximum were achieved owing to the synergistic effects of Tb³⁺ and Mn²⁺ ions. By combining TCs with a 460 nm blue chip, a warm white light with a low correlated color temperature of 4155 K was acquired. Meanwhile, the action mechanism of Tb³⁺ ion and the energy transfer between Ce³⁺ and Mn²⁺ ions were verified in prepared TCs.     

基于MF-DCCA 的呼吸道疾病与大气污染物相关性分析

针对呼吸道系统疾病与大气 PM2:5、 SO2 浓度序列的相关性特征, 应用多重分形消除趋势波动分析法 (MF-DCCA), 对张家界市永定区呼吸道系统疾病患病人数与大气 PM2:5、 SO2 浓度序列进行了研究。结果发现该地区 呼吸道系统疾病患病人数与大气 PM2:5、 SO2 浓度的相关性具有长期持续特征和多重分形特征。随后对它们相关性 多重分形特征的动力来源进行了分析, 通过随机重排和相位随机处理, 结果表明在不同时间尺度上的长期持续性影响 是其主要动力来源。进一步研究发现该地区呼吸道系统疾病与大气 PM2:5、 SO2 浓度序列的相关性在四个季节均具 有长期持续性的多重分形特征, 且夏季多重分形特征相对强于其他季节。     

Nanolayer CrAlN/TiSiN coating designed for tribological applications

With the goal to produce a hard and tough coating intended for tribological applications, CrAlN/TiSiN nanolayer coating was prepared by alternative deposition of CrAlN and TiSiN layers. In the first part of the article, a detailed study of phase composition, microstructure, and layer structure of CrAlN/TiSiN coating is presented. In the second part, its mechanical properties, fracture and tribological behavior are compared to the nanocomposite TiSiN coating. An industrial magnetron sputtering unit was used for coating deposition. X-ray photoelectron spectroscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, scanning electron microscopy, and transmission electron microscopy were used for compositional and microstructural analysis. Mechanical properties and fracture behavior were studied by instrumented indentation and focused ion beam techniques. Tribological properties were evaluated by ball-on-disk test in a linear reciprocal mode. A complex layer structure was found in the nanolayer coating. The TiSiN layers were epitaxially stabilized inside the coating which led to formation of dislocations at interfaces, to introduction of disturbances in the coating growth, and as a result, to development of fine-grained columnar microstructure. Indentation load required for the onset of fracture was twice lower for the nanolayer CrAlN/TiSiN, compared to the nanocomposite TiSiN coating. This agrees very well with their mechanical properties, with H³/E² being twice higher for the TiSiN coating. However, the nanolayer coating experienced less severe damage, which had a strong impact on tribological behavior. A magnitude of order lower wear rate and four times lower steady state friction coefficient were found for the nanolayer coating.     

Freeze-drying and mechanical redispersion of aqueous PEDOT:PSS

Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) films are attracting famous applications in antistatic coating, energy storage and conversion, printed electronics, and biomedical fields due to their conductivity, optical transparency and flexibility. However, PEDOT:PSS has poor dispersion stability during long-term storage and transport. Moreover, the dried PEDOT:PSS films are insoluble in any solvent and cannot be redispersed again. In comparison to bake drying, here, a feasible strategy to achieve mechanically redispersed PEDOT:PSS with the help of freeze-drying process was reported. The redispersed PEDOT:PSS can recover not only the initial characters such as pH, chemical composition, viscosity, and particle size under similar solid contents, but also conductivity and surface morphology of treated films. In addition, the treated film exhibits self-healing properties similar to pristine film in terms of mechanical and electrical properties. This technology enables reuse and overcomes the technical problems of PEDOT:PSS dispersion, realizing real-time processing to meet variable applications.     

基于设计事理学的儿童情感陪伴玩具研究

目的 从设计事理学视角，探讨儿童情感陪伴玩具的设计方法。方法 通过社会调研结合理论分析，提炼7～12岁城市留守儿童情感陪伴玩具中“事”的各外部因素与内部因素，建立合理的儿童情感陪伴玩具设计模型及评价体系。运用案例分析法，结合儿童情感陪伴玩具设计案例与实践，验证设计事理学在实际儿童情感陪伴玩具设计中的应用价值。结论 探索儿童情感陪伴玩具的设计路径，以Combot——具有情感陪伴与寓教于乐功能的儿童情感陪伴玩具为实践案例，证明了基于设计事理学的儿童情感陪伴玩具设计方法是有效可行的，可有效指导儿童玩具设计，满足父母与孩子的情感需求，促进儿童健康成长。     

A computational approach to nutrition science reveals the dynamics of the protein content of human milk

To study the computational aspects of collecting available data in a systematically organized database is becoming a matter of urgency in Nutrition & Food Science. Indeed, major projects on developing big datasets have attempted to fill this gap, but so far with limitations on important facets of food composition such as its temporal variation and uncertainty quantification. The need for methodological data processing, from data acquisition, digital storage, statistics and visualization, via pattern recognition and modelling to prediction and optimization is key to make objective and knowledge-based decisions on scientific and technological issues for food industry, academy and regulation. This study aims to demonstrate the use of a recently developed database on the composition of human milk, the first and easily the most complex food in one's life. We show that the purpose-built ontology of the database, with novelties like considering the food composition as a temporal and stochastic response, can help to recognize patterns in the variation of its protein content.Industrial relevance textThis study highlights the need (i) for introducing ISO-like standards how to digitize food composition data; (ii) for computational methods to explore and utilize such databases to their full potentials.     

Rapid preparation of Palygorskite/Al2O3 composite aerogels with superhydrophobicity,high-temperature thermal insulation and improved mechanical properties

Al₂O₃ aerogels are widely employed in heat insulation and flame retardancy because of their unique combination of low thermal conductivity and exceptional high-temperature stability. However, the mechanical properties of Al₂O₃ aerogel are poor, and the preparation time is considerably long. In this study, we present a simple and scalable approach to construct monolithic Pal/Al₂O₃ composite aerogels using solvothermal treatment instead of traditional solvent replacement, which remarkably shortened the preparation time. Subsequently, to obtain stable superhydrophobicity (θ > 152°), the Pal/Al₂O₃ aerogel was modified by gas-phase modification method. The obtained Pal/Al₂O₃ composite aerogels demonstrate the integrated properties of low density (0.078–0.106 g/cm³), low thermal conductivity (1000 °C, 0.143 W/(m·K)), good mechanical properties (Young's modulus, 1.6 MPa), and good heat resistance. The monolithic Pal/Al₂O₃ composite aerogels with improved mechanical performance and improved thermal stability can show great potential in the field of thermal insulation.     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.     

Adenine-functionalized conjugated polymer as an efficient photocatalyst for hydrogen evolution from water

Conjugated polymers have emerged as a promising class of organic photocatalysts for photocatalytic hydrogen evolution from water splitting due to their adjustable chemical structures and electronic properties. However, developing highly efficient organic polymer photocatalysts with high photocatalytic activity for hydrogen evolution remains a significant challenge. Herein, we present an efficient approach to enhance the photocatalytic performance of linear conjugated polymers by modifying the surface chemistry via introducing a hydrophilic adenine group into the side chain. The adenine unit with five nitrogen atoms could enhance the interaction between the surface of polymer photocatalyst and water molecules through the formation of hydrogen bonding, which improves the hydrophilicity and dispersity of the resulting polymer photocatalyst in the photocatalytic reaction solution. In addition, the strong electron-donating ability of adenine group with plentiful nitrogen atoms could promote the separation of light-induced electrons and holes. As a result, the adenine-functionalized conjugated polymer PF6A-DBTO2 shows a high photocatalytic activity with a hydrogen evolution rate (HER) of 25.21 mmol g^?1 h^?1 under UV-Vis light irradiation, which is much higher than that of its counterpart polymer PF6-DBTO2 without the adenine group (6.53 mmol g^?1 h^?1). More importantly, PF6A-DBTO2 without addition of a Pt co-catalyst also exhibits an impressive HER of 21.93 mmol g^?1 h^?1 under visible light (λ > 420 nm). This work highlights that it is an efficient strategy to improve the photocatalytic activity of conjugated polymer photocatalysts by the modification of surface chemistry.     

Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.