前驱体法制备氮氧化硅纳米线及其光学性能研究

在Ni催化剂的存在下,通过SiCl4的水解氨解反应并在1300℃氨气气氛中进行热氮化处理制得了无定形氮氧化硅纳米线.产物经X射线衍射(XRD)、热重-差示扫描量热(TG-DSC)、扫描电镜(SEM)、透射电镜(TEM)、能量色散谱(EDS)和选区电子衍射(SAED)等表征手段进行分析,结果表明纳米线为无定形结构,直径为100～150nm.在波长为220nm的光激发下,产物的光致发光光谱(PL)在563nm和289nm处分别出现了一个强的绿光发光峰和一个弱的紫光发光峰.对纳米线的生长机理进行分析,表明纳米线的生长遵循气-液-固(VLS)机制控制模式.     

碘化铅单晶体生长新方法探索

本文分析了用布里奇曼法生长碘化铅单晶体的结晶过程。发现坩埚下降法生长碘化铅单晶体过程中,碘的蒸发与凝结、铅的分凝与沉淀是影响晶体质量的两个重要因素。提出了采用U型安瓿提拉方式生长碘化铅单晶体的新方法,有效抑制了碘的蒸发并排除了分凝的铅,获得了桔红色半透明的碘化铅晶体。经测试,晶体的结晶性好,红外透过率达45%,电阻率为1.7×1012Ω.cm,为制备性能优异的碘化铅室温核辐射探测器奠定了基础。     

燃烧剂对低温燃烧合成Pr-CeO2粉体结构与性能的影响

以乙酸铵和柠檬酸为燃烧剂,Ce(NO3)3·6H2O和Pr6O11为主要原料,采用低温燃烧法(LCS)制备了Ce0.95Pr0.5O2纳米晶粉体.用DSC、XRD、SEM及色度测试等手段研究了Ce0.95Pr0.5O2纳米晶微粒前驱体的着火温度、产物晶体结构、晶体形貌及色度.结果表明:乙酸铵和柠檬酸作为燃烧剂的反应前驱体着火温度分别在250℃和300℃左右.两种燃烧产物均为单一的萤石型固溶体.与柠檬酸相比,乙酸铵作为燃烧剂得到的燃烧产物结晶程度更完善、Pr离子进入CeO2晶格的含量更多、呈色更好,且颗粒的团聚程度变小.根据Scherrer公式计算,用两种燃烧剂制备产物的平均晶粒尺寸分别为20～30 nm和10～15 nm,为纳米晶颗粒.最后得到Ce0.95Pr0.5O2粉体的颗粒尺寸则在200～300 nm之间.乙酸铵与硝酸铈的最佳摩尔配比为2:1,柠檬酸与硝酸铈的最佳摩尔配比为3:1.     

溶剂热法合成CoS2纳米粉体

本文采用溶剂热法,以CoCl2·6H2O 、Na2S·9H2O为原料,乙二醇和无水乙醇为溶剂,在180 ℃恒温下制备出CoS2纳米粉体.用XRD和SEM、TEM对其组成、粒径大小、表面形貌进行表征,用VSM对其铁磁性进行测量.结果表明, 制得的CoS2为粒度均匀、粒径分布在10～50nm之间的球形铁磁性纳米材料.     

Er3+:NaY(Wo.9Moo.1O4)2晶体的生长及光谱性能

采用提拉法(CZ法),生长出质量良好的Er3+:NaY(W0.9Mo0.1O4)2晶体.通过X射线粉末衍射,红外光谱分析,并与NaY(WO4)2相比较,得到Er3+:NaY(W0.9Mo0.1O4)2晶体的结构与NYW类似,仍为四方晶系的白钨矿结构,I4(1)/α空间群.测定了晶体的实际组成,得到晶体中各元素均按理论值进行掺杂,计算了掺杂离子的分凝系数约为1.15.在光谱性质上,测试了晶体的吸收光谱,及晶体在50～1000cm-1波数范围内的拉曼光谱,并计算了各吸收峰的半峰宽及吸收系数A.     

硫缺陷型In2S3光催化剂高效分解水制氢研究

缺陷工程被认为是提高光催化剂分解水制氢性能的关键策略之一,然而有关缺陷诱导半导体材料电子结构演变并增强光生载流子传输机制尚不明确。在本研究中,我们通过简单的一步水热合成法成功构建了富含S缺陷的In2S3半导体光催化剂（VS-In2S3）,在模拟太阳光辐照下其光催化分解水产氢性能相比传统的In2S3（P-In2S3）提升了近一个数量级（达到221.18 μmol/g/h）。此外,利用自主研发的原位X射线光电子能谱（SI-XPS）结合相关密度泛函理论计算证实：S缺陷可诱导强还原性的低价态In（In(3-x)+）暴露,进而增强In位点对H2O的吸附和活化能力,因此,S缺陷型In2S3表现出显著增强的光催化析氢活性。此外,可视化观测到H2O分子在原位光照下脱质子转化为OH的分解水制氢过程。该研究为缺陷型光催化剂设计及光催化分解水反应机制和过程研究提供了一定的见解。     

Rapid Identification for the Pterocarpus Bracelet by Three-Step Infrared Spectrum Method

In order to explore a rapid identification method for the anti-counterfeit of commercial high value collections, a three-step infrared spectrum method was used for the pterocarpus collection identification to confirm whether a commercial pterocarpus bracelet (PB) was made from the precious species of Pterocarpus santalinus (P. santalinus). In the first step, undertaken by Fourier transform infrared spectroscopy (FTIR) spectrum, the absorption peaks intensity of PB was slightly higher than that of P. santalinus only at 1594 cm⁻¹, 1205 cm⁻¹, 1155 cm⁻¹ and 836 cm⁻¹. In the next step of second derivative IR spectra (SDIR), the FTIR features of the tested samples were further amplified, and the peaks at 1600 cm⁻¹, 1171 cm⁻¹ and 1152 cm⁻¹ become clearly defined in PB. Finally, by means of two-dimensional correlation infrared (2DIR) spectrum, it revealed that the response of holocellulose to thermal perturbation was stronger in P. santalinus than that in PB mainly at 977 cm⁻¹, 1008 cm⁻¹, 1100 cm⁻¹, 1057 cm⁻¹, 1190 cm⁻¹ and 1214 cm⁻¹, while the aromatic functional groups of PB were much more sensitive to the thermal perturbation than those of P. santalinus mainly at 1456 cm⁻¹, 1467 cm⁻¹, 1518 cm⁻¹, 1558 cm⁻¹, 1576 cm⁻¹ and 1605 cm⁻¹. In addition, fluorescence microscopy was used to verify the effectiveness of the above method for wood identification and the results showed good consistency. This study demonstrated that the three-step IR method could provide a rapid and effective way for the anti-counterfeit of pterocarpus collections.     

Forecasting COVID-19 Epidemic Trends by Combining a Neural Network with Rt Estimation

On 31 December 2019, a cluster of pneumonia cases of unknown etiology was reported in Wuhan (China). The cases were declared to be Coronavirus Disease 2019 (COVID-19) by the World Health Organization (WHO). COVID-19 has been defined as SARS Coronavirus 2 (SARS-CoV-2). Some countries, e.g., Italy, France, and the United Kingdom (UK), have been subjected to frequent restrictions for preventing the spread of infection, contrary to other ones, e.g., the United States of America (USA) and Sweden. The restrictions afflicted the evolution of trends with several perturbations that destabilized its normal evolution. Globally, Rt has been used to estimate time-varying reproduction numbers during epidemics. Methods: This paper presents a solution based on Deep Learning (DL) for the analysis and forecasting of epidemic trends in new positive cases of SARS-CoV-2 (COVID-19). It combined a neural network (NN) and an Rt estimation by adjusting the data produced by the output layer of the NN on the related Rt estimation. Results: Tests were performed on datasets related to the following countries: Italy, the USA, France, the UK, and Sweden. Positive case registration was retrieved between 24 February 2020 and 11 January 2022. Tests performed on the Italian dataset showed that our solution reduced the Mean Absolute Percentage Error (MAPE) by 28.44%, 39.36%, 22.96%, 17.93%, 28.10%, and 24.50% compared to other ones with the same configuration but that were based on the LSTM, GRU, RNN, ARIMA (1,0,3), and ARIMA (7,2,4) models, or an NN without applying the Rt as a corrective index. It also reduced MAPE by 17.93%, the Mean Absolute Error (MAE) by 34.37%, and the Root Mean Square Error (RMSE) by 43.76% compared to the same model without the adjustment performed by the Rt. Furthermore, it allowed an average MAPE reduction of 5.37%, 63.10%, 17.84%, and 14.91% on the datasets related to the USA, France, the UK, and Sweden, respectively.     

Optimized Green Extraction of Polyphenols from Cassia javanica L. Petals for Their Application in Sunflower Oil: Anticancer and Antioxidant Properties

The total phenolic content (TPC) from Cassia javanica L. petals were extracted using ethanolic solvent extraction at concentrations ranging from 0 to 90% and an SCF-CO₂ co-solvent at various pressures. Ultrasound-assisted extraction parameters were optimized using response surface methodology (RSM). Antioxidant and anticancer properties of total phenols were assessed. An SCF-CO₂ co-solvent extract was nano-encapsulated and applied to sunflower oil without the addition of an antioxidant. The results indicated that the best treatment for retaining TPC and total flavonoids content (TFC) was SCF-CO₂ co-solvent followed by the ultrasound and ethanolic extraction procedures. Additionally, the best antioxidant activity by β-carotene/linoleic acid and DPPH free radical-scavenging test systems was observed by SCF-CO₂ co-solvent then ultrasound and ethanolic extraction methods. SCF-CO₂ co-solvent recorded the highest inhibition % for PC3 (76.20%) and MCF7 (98.70%) and the lowest IC₅₀ value for PC3 (145 µ/mL) and MCF7 (96 µ/mL). It was discovered that fortifying sunflower oil with SCF-CO₂ co-solvent nanoparticles had a beneficial effect on free fatty acids and peroxide levels. The SCF-CO₂ method was finally found to be superior and could be used in large-scale processing.