Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

Selective Binding of Cyclodextrins with Leflunomide and Its Pharmacologically Active Metabolite Teriflunomide

The selectivity of encapsulation of leflunomide and teriflunomide by native α-, β- and γ-cyclodextrins was investigated through ¹H NMR and molecular modeling. Thermodynamic analysis revealed the main driving forces involved in the binding. For α-cyclodextrin, the partial encapsulation was obtained while deep penetration was characterized for the other two cyclodextrins, where the remaining polar fragment of the molecule is located outside the macrocyclic cavity. The interactions via hydrogen bonding are responsible for high negative enthalpy and entropy changes accompanying the complexation of cyclodextrins with teriflunomide. These results were in agreement with the molecular modeling calculations, which provide a clearer picture of the involved interactions at the atomic level.     

Covalent Complex of DNA and Bacterial Topoisomerase: Implications in Antibacterial Drug Development

A topoisomerase-DNA transient covalent complex can be a druggable target for novel topoisomerase poison inhibitors that represent a new class of antibacterial or anticancer drugs. Herein, we have investigated molecular features of the functionally important Escherichia coli topoisomerase I (EctopoI)-DNA covalent complex (EctopoIcc) for molecular simulations, which is very useful in the development of new antibacterial drugs. To demonstrate the usefulness of our approach, we used a model small molecule (SM), NSC76027, obtained from virtual screening. We examined the direct binding of NSC76027 to EctopoI as well as inhibition of EctopoI relaxation activity of this SM via experimental techniques. We then performed molecular dynamics (MD) simulations to investigate the dynamics and stability of EctopoIcc and EctopoI-NSC76027-DNA ternary complex. Our simulation results show that NSC76027 forms a stable ternary complex with EctopoIcc. EctopoI investigated here also serves as a model system for investigating a complex of topoisomerase and DNA in which DNA is covalently attached to the protein.     

Hydroxyethyl cellulose filled with M2+ chelate complexes with ethylenediaminetetraacetic acid (EDTA) as an effective electron-injection layer for polymer light-emitting diodes

An effective electron-injection layer (EIL) is crucial to the development of highly efficient polymer light-emitting diodes (PLEDs) using stable, high work-function aluminium as the cathode. This work presents the first investigation using hydroxyethyl cellulose (HEC), filled with chelate complexes [(CH₃COO)₂-M, EDTA-M; M: Ca²⁺, Mg²⁺], as an electron-injection layer (EIL) to fabricate multilayer polymer light-emitting diodes (ITO/PEDO:PSS/HY-PPV/EIL/Al) by spin-coating processes. Devices based on HEC doped with EDTA-M provided the best performance. The maximum luminance and maximum current efficiency of polymer light-emitting diodes with EDTA-Ca in an HEC layer were 7502 cd/m² and 2.85 cd/A, respectively, whereas those with EDTA-Mg were 8443 cd/m² and 3.12 cd/A, which was approximately seven- to eight-fold of that without EIL. This performance enhancement was attributed to electron donation from the chelator that reduces metal cations to a “pseudo-metallic state”, enabling it to act as an intermediate step to facilitate electron injection. The results demonstrate that chelates of bivalent cations with EDTA can potentially serve as electron-injection materials for optoelectronic applications.     

Microencapsulation of camellia oil to maintain thermal and oxidative stability with focus on protective mechanism

Camellia oil (CO) microcapsules were developed using chitosan–soybean protein isolate (CS-SPI) complexes as wall materials and transglutaminase (TGase) as the cross-linking agent. Results indicated that CO/SPI under the ratio of 1:2 exhibited the highest microencapsulation efficiency and yield, possessing the best encapsulation effect. Morphology observation showed that CO microcapsules were intact, compact and nearly spherical. The microencapsulated CO exhibited the improved thermal resistance and significantly lower peroxide values after 3 days storage, demonstrating that the produced microcapsule was a promising way to maintain the thermal and oxidative stability of camellia oil. It could be found evidence from FTIR, which indicated that covalent cross-linking and hydrogen bonding might be involved among wall materials, and physical interactions between the core and wall materials. Therefore, the produced CO microcapsules could be an effective way to protect camellia oil, which was helpful for improving the processing and storage qualities of camellia oil.     

Deep-blue thermally activated delayed fluorescence emitter with a very high fluorescence rate

Conventional thermally activated delayed fluorescence (TADF) molecules achieve small energy differences between the lowest singlet and triplet excited states (ΔE_ST) by enhancing the intramolecular charge transfer, which inevitably leads to a wide emission spectrum and low fluorescence rate. Here, we prepared a deep blue TADF molecule via a small ΔE_ST pyridine-phenol fluoroboron complex as the acceptor. The small ΔE_ST is maintained when carbazole donors are attached to the 4-position of the phenyl rings in the fluoroboron complex. Benefiting from the strong electron coupling between the donor (D) and acceptor (A) moieties, the compound Cz-4-BF exhibits a high fluorescence rate of 4.8 × 10⁸ s⁻¹ and a small D-A dihedral angle change in the excited state. Consequently, a photoluminescence (PL) quantum yield of nearly 100% and a PL spectrum with full-width at half-maximum (FWHM) < 60 nm were obtained in solution and low-concentration doped films. A TADF-sensitized fluorescence (TSF) device containing Cz-4-BF achieves an external quantum efficiency of 21%, which is higher than the devices employing classical fluorescent emitters and multiple resonance-type TADF emitters. The Cz-4-BF-based TSF device shows significantly improved color coordinates of (0.14, 0.10) versus a control device without Cz-4-BF.     

A complex network approach to environmental impact assessment

This article proposes a complex network methodology for the process of Environmental Impact Assessment (EIA) that limits subjectivity and reduces uncertainty by incorporating elements of complex systems theory in the stages of identification and assessment of the significance of environmental impacts. The proposed methodology reduces the sources of uncertainty, which emerge from the use of simplified models that analyse the environment-activity interactions in a unidirectional fashion. This proposal determines the significance of environmental impacts through multidirectional or complex causal relationships. Likewise, it limits the subjectivity of the evaluator by using these causality relationships instead of criteria based on the impacts’ attributes. The application of the proposed methodology demonstrates the advantages of (i) prioritizing the impacts according to their capacity to interact with other impacts, and (ii) the possibility to redirect the environmental management plans towards the prevention of impacts of higher complexity and to reduce the importance of derived impacts.

The application of the proposed methodology reveals that the percentage of irrelevant and moderate impacts is reduced, whereas the percentage of severe and critical impacts increase, in comparison to the conventional methodologies.     

基于深度神经网络的表面划痕识别方法

为实现亮度不均的复杂纹理背景下表面划痕的鲁棒、精确、实时识别，提出一种基于深度神经网络的表面划痕识别方法。用于表面划痕识别的深度神经网络由风格迁移网络和聚焦卷积神经网络（CNN）构成，其中风格迁移网络针对亮度不均的复杂背景下的表面划痕进行预处理，风格迁移网络包括前馈转换网络和损失网络，首先通过损失网络提取亮度均匀模板的风格特征和检测图像的知觉特征，对前馈转换网络进行离线训练，获取网络最优参数值，最终使风格迁移网络生成亮度均匀且风格一致的图像，然后，利用所提出的基于聚焦结构的聚焦卷积神经网络对生成图像中的划痕特征进行提取并识别。以光照变化的金属表面为例，进行划痕识别实验，实验结果表明：与需要人工设计特征的传统图像处理方法及传统深度卷积神经网络相比，划痕漏报率低至8.54%，并且收敛速度更快，收敛曲线更加平滑，在不同的深度模型下均可取得较好的检测效果，准确率提升2%左右。风格迁移网络能够保留完整划痕特征的同时有效解决亮度不均的问题，从而提高划痕识别精度；同时聚焦卷积神经网络能够实现对划痕的鲁棒、精确、实时识别，大幅度降低划痕漏报率和误报率。     

Disease Ionomics: Understanding the Role of Ions in Complex Disease

Ionomics is a novel multidisciplinary field that uses advanced techniques to investigate the composition and distribution of all minerals and trace elements in a living organism and their variations under diverse physiological and pathological conditions. It involves both high-throughput elemental profiling technologies and bioinformatic methods, providing opportunities to study the molecular mechanism underlying the metabolism, homeostasis, and cross-talk of these elements. While much effort has been made in exploring the ionomic traits relating to plant physiology and nutrition, the use of ionomics in the research of serious diseases is still in progress. In recent years, a number of ionomic studies have been carried out for a variety of complex diseases, which offer theoretical and practical insights into the etiology, early diagnosis, prognosis, and therapy of them. This review aims to give an overview of recent applications of ionomics in the study of complex diseases and discuss the latest advances and future trends in this area. Overall, disease ionomics may provide substantial information for systematic understanding of the properties of the elements and the dynamic network of elements involved in the onset and development of diseases.     

复杂炼油塔模拟的改进联立方程内外层算法

在内外层算法的基础上，采用联立方程思想将主塔、侧线汽提塔视为一个整体进行建模，并针对复杂炼油塔的特点对算法提出了改进。首先，由于传统内外层法简化的K值模型对组成的变化不敏感，在处理带有石油的体系时，容易出现迭代次数较多，甚至部分塔板温度更新异常的问题，因此采用了汽相分数加和式推导了简化的K值模型加权因子。其次，借鉴流量加和法思想，规定侧线汽提塔的塔底产品流量作为设计变量，增强了算法收敛的稳定性。为验证改进后算法的有效性，采用不同的算法对实际的常压塔进行了模拟，结果显示改进后的算法适合应用于复杂炼油塔的模拟计算。