ZnO纳米钉的制备和光学性质研究

通过化学气相沉积(CVD)方法在Si(100)衬底上制备出新型的ZnO纳米钉结构.X射线衍射(XRD)结果表明纳米钉是六角纤锌矿结构.纳米钉顶部对角线在450～750 nm之间,纳米钉长度为几个微米.研究了不同气氛下退火样品的可见发光性质,认为绿光发射来自于导带电子和反位氧中空穴的辐射复合.     

Improved Stretchable and Sensitive Fe Nanowire-Based Strain Sensor by Optimizing Areal Density of Nanowire Network

Flexible strain sensors, when considering high sensitivity and a large strain range, have become a key requirement for current robotic applications. However, it is still a thorny issue to take both factors into consideration at the same time. Here, we report a sandwich-structured strain sensor based on Fe nanowires (Fe NWs) that has a high GF (37–53) while taking into account a large strain range (15–57.5%), low hysteresis (2.45%), stability, and low cost with an areal density of Fe NWs of 4.4 mg/cm². Additionally, the relationship between the contact point of the conductive network, the output resistance, and the areal density of the sensing unit is analyzed. Microscopically, the contact points of the conductive network directly affect the sensor output resistance distribution, thereby affecting the gauge factor (GF) of the sensor. Macroscopically, the areal density and the output resistivity of the strain sensor have the opposite percolation theory, which affects its linearity performance. At the same time, there is a positive correlation between the areal density and the contact point: when the stretching amount is constant, it theoretically shows that the areal density affects the GF. When the areal density reaches this percolation threshold range, the sensing performance is the best. This will lay the foundation for rapid applications in wearable robots.     

Deep Multilabel Multilingual Document Learning for Cross-Lingual Document Retrieval

Cross-lingual document retrieval, which aims to take a query in one language to retrieve relevant documents in another, has attracted strong research interest in the last decades. Most studies on this task start with cross-lingual comparisons at the word level and then represent documents via word embeddings, which leads to insufficient structure information. In this work, the cross-lingual comparison at the document level is achieved through the cross-lingual semantic space. Our method, MDL (deep multilabel multilingual document learning), leverages a six-layer fully connected network to project cross-lingual documents into a shared semantic space. The semantic distances can be calculated when the cross-lingual documents are transformed into embeddings in semantic space. The supervision signals are automatically extracted from the data and then used to construct the semantic space via a linear classifier. The ambiguity of manual labels could be avoided and the multilabel supervision signals can be acquired instead of a single label. The representation of the semantic space is enriched by multilabel supervision signals, which improves the discriminative ability of the embeddings. The MDL is easy to extend to other fields since it does not depend on specific data. Furthermore, MDL is more efficient than the models training all languages jointly, since each language is trained individually. Experiments on Wikipedia data showed that the proposed method outperforms the state-of-the-art cross-lingual document retrieval methods.     

Harnessing Protein-Ligand Interaction Fingerprints to Predict New Scaffolds of RIPK1 Inhibitors

Necroptosis has emerged as an exciting target in oncological, inflammatory, neurodegenerative, and autoimmune diseases, in addition to acute ischemic injuries. It is known to play a role in innate immune response, as well as in antiviral cellular response. Here we devised a concerted in silico and experimental framework to identify novel RIPK1 inhibitors, a key necroptosis factor. We propose the first in silico model for the prediction of new RIPK1 inhibitor scaffolds by combining docking and machine learning methodologies. Through the data analysis of patterns in docking results, we derived two rules, where rule #1 consisted of a four-residue signature filter, and rule #2 consisted of a six-residue similarity filter based on docking calculations. These were used in consensus with a machine learning QSAR model from data collated from ChEMBL, the literature, in patents, and from PubChem data. The models allowed for good prediction of actives of >90, 92, and 96.4% precision, respectively. As a proof-of-concept, we selected 50 compounds from the ChemBridge database, using a consensus of both molecular docking and machine learning methods, and tested them in a phenotypic necroptosis assay and a biochemical RIPK1 inhibition assay. A total of 7 of the 47 tested compounds demonstrated around 20–25% inhibition of RIPK1’s kinase activity but, more importantly, these compounds were discovered to occupy new areas of chemical space. Although no strong actives were found, they could be candidates for further optimization, particularly because they have new scaffolds. In conclusion, this screening method may prove valuable for future screening efforts as it allows for the exploration of new areas of the chemical space in a very fast and inexpensive manner, therefore providing efficient starting points amenable to further hit-optimization campaigns.     

一种超高耐久混凝土——梯度结构混凝土

分析超高耐久混凝土的研究现状,提出了一种高耐久、低成本的超高耐久混凝土--梯度结构混凝土(Gradient Structural Concrete,简称GSC),采用电量法和氯离子扩散系数法来评价梯度结构混凝土的抗氯离子渗透性能,最后进行梯度结构混凝土的寿命预测与成本分析.结果表明,高性能混凝土(High Performance Concrete,简称HPC)、无细观界面过渡区水泥基复合材料(Meso-interfacial transition zone-free cement-based materials,简称 MIF)和梯度结构混凝土MIF-HPC的6 h导电量和氯离子扩散系数的排列顺序均为:HPC>MIF-HPC>MIF,其抗氯离子渗透性能排列顺序为:MIF>MIF-HPC>HPC.梯度结构混凝土的成本会有所增加,但由于其氯离子渗透性能大幅降低,其使用寿命得到大幅延长,使得其年损耗费用大幅下降.     

Polyoxometalate/Cellulose Nanofibrils Aerogels for Highly Efficient Oxidative Desulfurization

Polyoxometalate (POM) presents great potential in oxidative desulfurization (ODS) reaction. However, the high dissolubility of POM in common solvents makes it difficult to recycle. Besides, the small specific surface area of POM also limits the interaction between them and the substrate. Depositing polyoxometalates onto three-dimensional (3D) network structured materials could largely expand the application of POM. Here, the surfaces of cellulose nanofibrils (CNFs) were modified with very few (3-Aminopropyl) trimethoxysilane (APTS) to endow positive charges on the surfaces of CNFs, and then phosphotungstic acid (PTA) was loaded to obtain the aerogel A-CNF/PTA as the ODS catalyst. FT-IR indicated the successful deposition of PTA onto aminosilane modified CNF surfaces. UV-VIS further suggested the stability of PTA in the aerogels. BET and SEM results suggested the increased specific surface area and the relatively uniform 3D network structure of the prepared aerogels. TGA analysis indicated that the thermal stability of the aerogel A-CNF/PTA50% was a little higher than that of the pure CNF aerogel. Most importantly, the aerogel A-CNF/PTA50% showed good catalytic performance for ODS. Catalysis results showed that the substrate conversion rate of the aerogel A-CNF/PTA50% reached 100% within 120 min at room temperature. Even after five cycles, the substrate conversion rate of the aerogel A-CNF/PTA50% still reached 91.2% during the dynamic catalytic process. This work provides a scalable and facile way to stably deposit POM onto 3D structured materials.     

Surface-anchoring zwitterionic antioxidant enables efficient,stable,and scalable all-perovskite tandem solar cells

Lead-halide perovskite photovoltaics(PVs)have achieved impressive progress in power conversion efficiencies(PCEs)over the past ten years,accelerating their step forward to next-generation commercial PV technologies[1].As a leading candidate for perovskite PVs,monolithic all-perovskite tandem solar cells(PTSCs)have achieved the best24.8%for small-area devices(0.049 cm^2)in 2019。     

激光激发水中产生超声波的实验研究

采用压电陶瓷水听器研究了Nd：YAG脉冲激光激发水中产生瞬态超声波的特性,给出了声压信号随距离的变化关系。研究结果表明：用激光产生水下声波是完全可行的。当观测点与光击穿区的距离r远大于柱体长度时,垂直于光传播方向的激光瞬态超声波幅值与r成反比;当观测点与光击穿区的距离r很小时,垂直于光传播方向的声压幅值与产成反比。此外,当激光入射角度发生变化,超声脉冲的幅值也随之发生变化,其幅值在激光束垂直入射的时候最大。     

Poly(lactic acid) composites with poly(lactic acid)‐modified carbon nanotubes

This work reports the study of the effect of chemical functionalization of carbon nanotubes on their dispersion in poly(lactic acid). The nanotubes were functionalized by the 1,3‐dipolar cycloaddition reaction, generating pyrrolidine groups at the nanotube surface. Further reaction of the pyrrolidine groups with poly(lactic acid) was studied in solution and in the polymer melt. The former involved refluxing the nanotubes in a dimethylformamide/polymer solution; the latter was carried out by direct melt mixing in a microcompounder. The carbon nanotubes collected after each process were characterized by thermogravimetry and by X‐ray photoelectron spectroscopy, showing evidence of polymer bonded to the nanotube surface only when the reaction was carried out in the polymer melt. The composites with polymer modified nanotubes present smaller average agglomerate area and a narrower agglomerate area distribution. In addition, they show improved tensile properties at low CNT concentration and present lower electrical resistivity. © 2013 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2013, 51, 3740–3750     

高效液相色谱法同时测定生物质乳酸发酵液中有机酸及糖类化合物

建立了高效液相色谱(HPLC)同时测定生物质乳酸发酵液中有机酸及糖类的分析方法。使用Bio-Rad Aminex HPX-87H色谱柱,以5 mmol/L的H2SO4为流动相,在柱温55 ℃,流速0.6 mL/min条件下,采用示差折光检测器进行检测。结果表明,该方法可在17 min内实现发酵液中各种有机酸和糖类化合物等的完全分离与定量,6种有机酸和3种糖类化合物在0.15～5.19 g/L范围内的线性关系良好,回归方程的线性相关系数在0.9998以上。将该法用于米根霉发酵液的检测,两个水平的加标回收率为96.91%～103.11%,相对标准偏差(n=6)为0.81%～4.61%。该法适用于微生物发酵液中多种有机酸和糖类的快速、高效分离和定量测定。