DNA Nanoribbon-Templated Self-Assembly of Ultrasmall Fluorescent Copper Nanoclusters with Enhanced Luminescence

Fluorescent copper nanoclusters (CuNCs) have been widely used in chemical sensors, biological imaging, and light-emitting devices. However, individual fluorescent CuNCs have limitations in their capabilities arising from poor photostability and weak emission intensities. As one kind of aggregation-induced emission luminogen (AIEgen), the formation of aggregates with high compactness and good order can efficiently improve the emission intensity, stability, and tunability of CuNCs. Here, DNA nanoribbons, containing multiple specific binding sites, serve as a template for in situ synthesis and assembly of ultrasmall CuNCs (0.6 nm). These CuNC self-assemblies exhibit enhanced luminescence and excellent fluorescence stability because of tight and ordered arrangement through DNA nanoribbons templating. Furthermore, the stable and bright CuNC assemblies are demonstrated in the high-sensitivity detection and intracellular fluorescence imaging of biothiols.     

Water-Soluble Polymers with Appending Porphyrins as Bioinspired Catalysts for the Hydrogen Evolution Reaction

Molecular design to improve catalyst performance is significant but challenging. In enzymes, residue groups that are close to reaction centers play critical roles in regulating activities. Using this bioinspired strategy, three water-soluble polymers were designed with appending Co porphyrins and different side-chain groups to mimic enzyme reaction centers and activity-controlling residue groups, respectively. With these polymers, high hydrogen evolution efficiency was achieved in neutral aqueous media for electro- (turnover frequency >2.3×10⁴ s⁻¹) and photocatalysis (turnover number >2.7×10⁴). Porphyrin units are surrounded and protected by polymer chains, and more importantly, the activity can be tuned with different side-chain groups. Therefore, instead of revising molecular structures that is difficult from both design and synthesis points of view, polymers can be used to improve molecular solubility and stability and simultaneously regulate activity by using side-chain groups.     

Optimization of SIMS analytical parameters for water content measurement of olivine

Secondary ion mass spectrometry (SIMS) has a wide range of applications in Earth Science research, thanks to its high precision and sensitivity, and its capacity in direct insitu micromeasurement. The technique is operated in ultra-high vacuum (UHV) conditions, especially for the measurement of volatiles such as hydrogen, or the water content in nominally anhydrous minerals (NAMs). To minimize the water background and obtain accurate and precise water contents in NAMs (eg, olivine) critical parameters such as presputtering time, field aperture (FA), dynamic transfer on/off, and primary beam current intensity were investigated for a CAMECA IMS 1280-HR system. When the chamber vacuum reaches approximately 2 × 10⁻⁹ mbar, we set the DTOS OFF, raster size to 50 μm and primary beam current to 5 nA, and used 2000 μm FA and 170-second presputtering time. Consequently, an approximately 1.2 ppmw water background and 3.6 ppmw limit of detection (LOD) were yielded, from analyzing the San Carlos olivine. Meanwhile, the water content and homogeneity of a range of olivine minerals were characterized for potential use as reference materials for SIMS water content measurement. Olivine water content calibration curve was also established by comparing the Fourier transform infrared (FTIR) results with the SIMS-measured ¹⁶O¹H⁻/¹⁶O⁻ ratios. Accuracy and precision of water content measurement were estimated to be better than approximately 10% in this study.     

手性环丙烯构建策略用于对映选择性合成偕二氟亚甲基三元环化合物

作为最小的不饱和环状分子,环丙烯独特的刚性结构和多变的反应活性吸引了化学家的研究兴趣.自1922年Demjanov[1]报道了环丙烯化合物的首例合成以来,现已发展了一系列环丙烯的合成方法.手性环丙烯的合成是通过炔烃和重氮化合物的[2+1]不对称环加成反应.根据底物的不同,这些不对称环加成反应可以分为四类:(a)末端炔烃和单取代重氮化合物的反应,(b)末端炔烃和双取代重氮化合物的反应,(c)非末端炔烃和双取代重氮化合物的反应,(d)非末端炔烃和单取代重氮化合物的反应.在这四类反应中,末端炔烃和单取代重氮化合物的不对称反应相对容易进行.1992年,Doyle和Müller等[2]报道了手性铑催化剂[Rh2(5R-MEPY)4]促进的末端炔烃和重氮醋酸酯之间的不对称环丙烯基化反应(Scheme 1a).随后各种手性催化剂包括[Rh2(OAc)-(DPTI)3][3]、Ir(salen)衍生物[4]和[Co(3,5-diMes-Chen-Phyrin)][5]等被先后报道用于末端炔烃和单取代重氮化合物的不对称[2+1]环加成反应.     

Unpaired 3d Electrons on Atomically Dispersed Cobalt Centres in Coordination Polymers Regulate both Oxygen Reduction Reaction (ORR) Activity and Selectivity for Use in Zinc–Air Batteries

Reversible oxygen conversion is important for various green energy technologies. Herein we synthesize a series of bimetallic coordination polymers by varying the Ni/Co ratio and using HITP (HITP=2,3,6,7,10,11‐hexaiminotriphenylene) as the ligand, to interrogate the role of metal centres in modulating the activity of the oxygen reduction reaction (ORR). Co₃HITP₂ and Ni₃HITP₂ are compared. Unpaired 3d electrons in Co₃HITP₂ result in less coplanarity but more radical character. Thus, despite of a reduced crystallinity and conductivity, the best ORR activity, comparable to 20 % Pt/C, is obtained for Co₃HITP₂, showing the 3d orbital configuration of the metal centre promotes ORR. Experimental and DFT studies show a transition of ORR pathway from four‐electron for Co₃HITP₂ to two‐electron for Ni₃HITP₂. Rechargeable zinc–air batteries using Co₃HITP₂ as the air cathode catalyst demonstrate excellent energy efficiency and stability.     

Behaviour of silicon ointment for power-cable insulation under external heating

Journal of Thermal Analysis and Calorimetry - The burning process and typical fire parameters of power-cable silicon ointment were explored experimentally using a cone calorimeter, and the effects...     

Comparison of the active components of Aster tataricus from different regions and related processed products by ultra‐high performance liquid chromatography with tandem mass spectrometry

We investigated crude Aster tataricus, vinegar‐processed Aster tataricus, honey‐processed Aster tataricus, and steamed Aster tataricus as a case study and developed a comprehensive strategy integrating quantitative analysis and chemical pattern recognition methods for the evaluation and differentiation of Aster tataricus from different regions, as well as related processed products. In the study, 15 batches of raw Aster tataricus collected from seven provinces were analyzed. A sensitive and rapid ultra‐high performance liquid chromatography with tandem mass spectrometry method for simultaneous determination of 15 compounds was established to evaluate the quality of raw and processed Aster tataricus. Furthermore, multivariate statistical techniques were applied to compare the differences among Aster tataricus samples. As a result, the herbs collected from seven provinces were divided into two categories, and chlorogenic acid was the most important component distinguishing between the regions. Moreover, all of the raw and processed samples were classified by partial least squares discriminant analysis based on the 15 analyzed compounds. Results showed that raw Aster tataricus, vinegar‐processed Aster tataricus, honey‐processed Aster tataricus, and steamed Aster tataricus were clustered in four different areas. Shionone, chlorogenic acid and kaempferol were the significant constituents differentiating the raw and differently processed Aster tataricus samples.     

Transformations of N-arylpropiolamides to indoline-2,3-diones and acids via C≡C triple bond oxidative cleavage and C(sp^2)–H functionalization

A new palladium-catalyzed oxidative conversion of N-arylpropiolamides and H2O to various indoline-2,3-diones and acids through the C≡C triple bond cleavage and C(sp2)–H functionalization is described,which is promoted by a cooperative action of catalytic CuBr2,2,2,6,6-tetramethyl-1-piperidinyloxy(TEMPO)and O2.The method provides a practical tool for transformations of alkynes by means of a C–H functionalization strategy,which enables the formation of one C–C bond and multiple C–O bonds in a single reaction with high substrates compatibility and excellent functional group tolerance.     

Machine-Learning Adsorption on Binary Alloy Surfaces for Catalyst Screening

Over the last few years, machine learning is gradually becoming an essential approach for the investigation of heterogeneous catalysis. As one of the important catalysts, binary alloys have attracted extensive attention for the screening of bifunctional catalysts. Here we present a holistic framework for machine learning approach to rapidly predict adsorption energies on the surfaces of metals and binary alloys. We evaluate different machine-learning methods to understand their applicability to the problem and combine a tree-ensemble method with a compressed-sensing method to construct decision trees for about 60000 adsorption data. Compared to linear scaling relations, our approach enables to make more accurate predictions lowering predictive root-mean-square error by a factor of two and more general to predict adsorption energies of various adsorbates on thousands of binary alloys surfaces, thus paving the way for the discovery of novel bimetallic catalysts.