Oxidation and Reduction Pathways in the Knowles Hydroamination via a Photoredox-Catalyzed Radical Reaction**

Systematic reaction path exploration revealed the entire mechanism of Knowles's light-promoted catalytic intramolecular hydroamination. Bond formation/cleavage competes with single electron transfer (SET) between the catalyst and substrate. These processes are described by adiabatic processes through transition states in an electronic state and non-radiative transitions through the seam of crossings (SX) between different electronic states. This study determined the energetically favorable SET path by introducing a practical computational model representing SET as non-adiabatic transitions via SXs between substrate's potential energy surfaces for different charge states adjusted based on the catalyst's redox potential. Calculations showed that the reduction and proton shuttle process proceeded concertedly. Also, the relative importance of SET paths (giving the product and leading back to the reactant) varies depending on the catalyst's redox potential, affecting the yield.     

Hydrogen Bond Networks Stabilized High-Capacity Organic Cathode for Lithium-Ion Batteries

High-capacity small organic materials are plagued by their high solubility. Here we proposed constructing hydrogen bond networks (HBN) via intermolecular hydrogen bonds to suppress the solubility of active material. The illustrated 2, 7- diamino-4, 5, 9, 10-tetraone (PTO-NH₂) molecule with intermolecular hydrogen (H) bond between O in −C=O and H in −NH₂, which make PTO-NH₂ presents transverse two-dimensional extension and longitudinal π–π stacking structure. In situ Fourier transform infrared spectroscopy (FTIR) has tracked the reversible evolution of H-bonds, further confirming the existence of HBN structure can stabilize the intermediate 2-electron reaction state. Therefore, PTO-NH₂ with HBN structure has higher active site utilization (95 %), better cycle stability and rate performance. This study uncovers the H-bond effect and evolution during the electrochemical process and provides a strategy for materials design.     

Thermally Responsive Selenide-containing Materials Based on Transalkylation of Selenonium Salts

Covalent adaptable networks (CANs) possess unique properties as a result of their internal dynamic bonds, such as self-healing and reprocessing abilities. In this study, we report a thermally responsive C−Se dynamic covalent chemistry (DCC) that relies on the transalkylation exchange between selenonium salts and selenides, which undergo a fast transalkylation reaction in the absence of any catalyst. Additionally, we demonstrate the presence of a dissociative mechanism in the absence of selenide groups. After incorporation of this DCC into selenide-containing polymer materials, it was observed that the cross-linked networks display varying dynamic exchange rates when using different alkylation reagents, suggesting that the reprocessing capacity of selenide-containing materials can be regulated. Also, by incorporating selenonium salts into polymer materials, we observed that the materials exhibited good healing ability at elevated temperatures as well as excellent solvent resistance at ambient temperature. This novel dynamic covalent chemistry thus provides a straightforward method for the healing and reprocessing of selenide-containing materials.     

A Dissipative Reaction Network Drives Transient Solid–Liquid and Liquid–Liquid Phase Cycling of Nanoparticles

Transient states maintained by energy dissipation are an essential feature of dynamic systems where structures and functions are regulated by fluxes of energy and matter through chemical reaction networks. Perfected in biology, chemically fueled dissipative networks incorporating nanoscale components allow the unique properties of nanomaterials to be bestowed with spatiotemporal adaptability and chemical responsiveness. We report the transient dispersion of gold nanoparticles in water, powered by dissipation of a chemical fuel. A dispersed state that is generated under non-equilibrium conditions permits fully reversible solid–liquid or liquid–liquid phase transfer. The molecular basis of the out-of-equilibrium process is reversible covalent modification of nanoparticle-bound ligands by a simple inorganic activator. Activator consumption by a coupled dissipative reaction network leads to autonomous cycling between phases. The out-of-equilibrium lifetime is tunable by adjusting the pH value, and reversible phase cycling is reproducible over several cycles.     

弹性力学的实时神经计算原理与数值仿真

针对现代结构分析的特点，提出了基于神经网络结构的弹性力学分析原理；给出求解该问题的网络———改进的Ｈｏｐｆｉｅｌｄ和ＴＨ网络．提出用ＢＰ网络来实现单元刚度矩阵的实时计算．最后，对两个简单结构的弹性力学神经计算进行了数值仿真     

Self-assembled nanoribbons and nanotubes in water: energetic vs entropic networks

We present a comparative investigation of two opposite classes of self-assembled fibrillar networks. Ribbons and tubes having cross-sectional dimensions in the nanoscale can be formed in aqueous solutions of steroids derived, respectively, from deoxycholic (DC) and lithocholic (LC) acids. Rheological features distinguish energetic networks of DC ribbons rigidly fixed in cylindrical bundles and entropic transient networks of LC tubes weakly interacting in shear-sensitive suspensions. The two classes are characterized by their frequency sweep profiles, viscoelastic linear domains, scaling laws of the elastic shear modulus vs concentration, kinetics of formation of the networks, and their optical birefringence aspects. A theoretical context for networks of rigid fibers is used to account for the scaling exponents α in the G’ (and σ*) ∝C ^α laws (α=2.0 and 1.0, respectively, for DC and LC). The evolution observed in DC gels from ribbons to cylindrical fibers with monodisperse sections made up with four ribbons is an indication of an equilibrated balance between face-to-face attractions and untwisting elastic processes of the constitutive ribbons.Paper presented at the Annual Meeting of the European Society of Rheology, Grenoble, April 2005     

Experiments on 40 Gb/s Transmission with Wavelength Conversion: Results from the IST ATLAS Project

In this article we report the main experimental results obtained in the framework of the IST ATLAS project regarding the transmission at 40 Gb/s over long terrestrial links, including the frequency conversion of a signal. We report the single-channel 40 Gb/s transmission over a link 500 km long with an amplifier spacing of 100 km, both with G.652 fibers and G.653 fibers by periodically compensating the chromatic dispersion with dispersion-compensating fibers. We report the single-channel transmission at 40 Gb/s, also, after the wavelength conversion of a channel with both PPLN and semiconductor optical amplifier devices. In particular, 500 km distances are obtained with PPLN wavelength conversion and 300 km distances with semiconductor optical amplifiers. Some results have been reported for electronic devices operating at 40 Gb/s.     

Simultaneous Determination of Multicomponents in Air Toxic Organic Compounds Using Artificial Neural Networks in Ftir Spectroscopy

The application of Artificial Neural Networks (ANNs) for nonlinear multivariate calibration using simulated FTIR data was demonstrated in this paper. Neural networks consisting of three layers of nodes were trained by using the back-propagation learning rule. Since parameters affect the performance of the network greatly, simulated data were used to train the network in order to get a satisfactory combination of all parameters. The mixtures of four air toxic organic compounds whose FTIR spectra are overlapped were chosen to evaluate the calibration and prediction ability of the network. The relative standard error (RSD%), the percent standard error of prediction samples (%SEP) and the percent standard error of calibration samples (%SEC) are used for evaluating the ability of the neural network.     

Information spreading in Delay Tolerant Networks based on nodes’ behaviors

Information spreading in DTNs (Delay Tolerant Networks) adopts a store–carry–forward method, and nodes receive the message from others directly. However, it is hard to judge whether the information is safe in this communication mode. In this case, a node may observe other nodes’ behaviors. At present, there is no theoretical model to describe the varying rule of the nodes’ trusting level. In addition, due to the uncertainty of the connectivity in DTN, a node is hard to get the global state of the network. Therefore, a rational model about the node’s trusting level should be a function of the node’s own observing result. For example, if a node finds k nodes carrying a message, it may trust the information with probability p(k). This paper does not explore the real distribution of p(k), but instead presents a unifying theoretical framework to evaluate the performance of the information spreading in above case. This framework is an extension of the traditional SI (susceptible-infected) model, and is useful when p(k) conforms to any distribution. Simulations based on both synthetic and real motion traces show the accuracy of the framework. Finally, we explore the impact of the nodes’ behaviors based on certain special distributions through numerical results.