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The fitness landscape is a theory applied to the evolutionary dynamics of biological evolution to explain the behavior of evolutionary algorithms in the solution of optimization problems. With the continuous advancement of evolutionary algorithm optimization, a fitness landscape can present more abundant feature information, such as the local fitness, fitness distance correlation, and landscape roughness. These landscape features reflect the optimal solution distribution, quantity, and local unimodal topology of the optimization problem from various angles. This paper expresses the adaptability landscape features of typical optimization problems, engages in a quantitative analysis of the fitness distance correlation information, evaluates the difficulty of solving the problem within the search space, and obtains the correlation degree classification result. The search strategy adapts the mixed mutation and the fitness distance correlation for differential evolution. Empirical studies show that, the fitness distance correlation search strategy for the differential evolution algorithm can avoid falling into the local optimum, improve accuracy and convergence, and solve the single-objective optimization problem in a more comprehensive manner.

The as-extruded Mg-10Al2Y master alloy was chosen as a novel grain refiner for as-cast Mg-3Y alloy. Contrast samples of cast Mg-3Y alloy added with pure Al and Mg-Zr master alloy grain refiners were prepared under the same conditions. In this study, the influence of addition amounts of Al2Y and holding time on grain refinement efficiency as well as tensile properties was investigated. And the grain refining ability of the Al2Y particles was systematically evaluated in terms of the addition amounts, number density of the Al2Y particles and holding time. The finest grains are achieved at 2 wt% Al2Y addition amount, which corresponds to number density of the polygonal Al2Y particles of 420–460 mm–2. The Mg-10Al2Y master alloy has significant refinement performance and no refining recession occurs at the holding time within 60 min, or the settling time up to 180 min. Grain refinement and the second phase strengthening of uniformly distributed Al2Y particles contribute to the simultaneous enhancement on both strength and elongation of Mg-3Y alloy.

Multiobjective particle swarm optimization (MOPSO) algorithm faces the difficulty of prematurity and insufficient diversity due to the selection of inappropriate leaders and inefficient evolution strategies. Therefore, to circumvent the rapid loss of population diversity and premature convergence in MOPSO, this paper proposes a knowledge-guided multiobjective particle swarm optimization using fusion learning strategies (KGMOPSO), in which an improved leadership selection strategy based on knowledge utilization is presented to select the appropriate global leader for improving the convergence ability of the algorithm. Furthermore, the similarity between different individuals is dynamically measured to detect the diversity of the current population, and a diversity-enhanced learning strategy is proposed to prevent the rapid loss of population diversity. Additionally, a maximum and minimum crowding distance strategy is employed to obtain excellent nondominated solutions. The proposed KGMOPSO algorithm is evaluated by comparisons with the existing state-of-the-art multiobjective optimization algorithms on the ZDT and DTLZ test instances. Experimental results illustrate that KGMOPSO is superior to other multiobjective algorithms with regard to solution quality and diversity maintenance.

To realize speed adjustment, achieve adaptive power allocation, and enhance operation safety, a synthetic strategy combining operation control and power allocation is proposed in this article for fuel cell (FC) hybrid tramway. First, the asynchronous motor model based on vector control is established. Considering available power variation with state of charge (SOC), a speed self-adjusting strategy is proposed to adjust the tramway speed actively and maintain the distance unchanged meanwhile. Besides, adaptive droop control is adopted to allocate demand power. To obtain better economic performance and SOC sustaining, the regulation factors for supercapacitor and battery are introduced to optimize the droop coefficients. Then, the proposed strategy is verified under a drive cycle of low floor light rail vehicle in a hardware-in-loop platform. The results demonstrate that the proposed strategy is sufficient to adjust the tramway speed and allocate power among sources to maintain the given speed when without enough power, thus the operation safety and system robustness is reinforced. The comparison with and without regulation factors is conducted to prove the effectiveness of the factors. The proposed strategy is also compared with the equivalent consumption minimization strategy to further prove its priority.

We use coarse-grained molecular dynamics simulations to study the self-assembly behavior of polyoxometalate (POM) nanoparticles (NPs) decorated with mobile polymer ligands under melt conditions. We demonstrate that due to the mobile nature of the grafted ligands on the NP surface, NPs have the ability to expose a part of their surfaces, leading to a block-copolymer-like self-assembly behavior. The exposed NP surface serves as one block and the grafted ligand polymers as another. This system has a strong ability to self-assemble into long-range ordered structures such as block copolymers due to large incompatibility between POM and ligand polymers, i.e., POM NPs can form lamellar, cylindrical, and spherical structures, which are consistent with previous experimental results. More importantly, these ordered structures are on the sub-10 nm scale, which is an important requirement for many applications. At low graft density, we find a new inverse-cylindrical structure formation where polymers form cylinders and POMs form a continuous network structure. A full self-assembly phase diagram is constructed which illustrates rules to manipulate the self-assembly structures of NPs decorated with mobile polymer ligands. We hope that these computational results will be useful for the new design of nanostructures with improved optical or electronic functions.

Effects of Ca addition on as-cast microstructure, mechanical and corrosion properties of Mg–2Zn–0.3Sr alloy were investigated for biodegradable implant application. First, a comparison between Ca a...

The traditional particle swarm optimization algorithm learns from the two best experiences: the best position previously learned by the particle itself and the best position learned by the entire population to date. This learning strategy is simple and ordinary, but when addressing high-dimensional optimization problems, it is unable to quickly find the global optimal solution due to its low efficiency. This paper proposes a multipopulation cooperative particle swarm optimization (MPCPSO) algorithm with a dynamic segment-based mean learning strategy and a multidimensional comprehensive learning strategy. In MPCPSO, the dynamic segment-based mean learning strategy (DSMLS), which is employed to construct learning exemplars, achieves information sharing and coevolution between populations. The multidimensional comprehensive learning strategy (MDCLS) is employed to speed up convergence and improve the accuracy of MPCPSO solutions. Additionally, a differential mutation operator is introduced to increase the population diversity and enhance the global exploration ability of MPCPSO. Sixteen benchmark functions and seven well-known PSO variants are employed to verify the advantages of MPCPSO. The comparison results indicate that MPCPSO has a faster convergence speed, obtains more accurate solutions, and is more robust.

In this work, 8mol% yttria-stabilized zirconia (8YSZ) ripple-shaped electrolytes have been prepared by digital light processing (DLP) 3D printing and their electrochemical performances have been investigated. The total conductivities of flat samples printed at different angles were tested firstly to confirm that there is no huge influence on the electrochemical performance from the printing itself. Then, by using ripple-shaped electrolytes, primary cells were assembled and their electrochemical performance were investigated. Compared with the reference flat cell, an improvement of ~32% was achieved in the power density for the same thickness of the electrolyte (~200 µm) at 800 °C.

Disaggregation enabled by silicon photonic switch fabrics is a path to low-cost and energy-efficient data centers. The routing strategy, which can be seamlessly incorporated into the switch control plane, potentially provides an additional dimension for the physical-layer performance optimization, at no extra cost. In this paper, we analyze the role of optical routing strategies for silicon photonic switch fabrics. We define and quantify the number of global switching states in various switching topologies and discuss their relationship to the number of switch permutations. We propose a topology-agnostic approach that is shown to optimize fabric-wide switch path power penalties and consequently reduce the dynamic-range requirement on receivers. Additionally, it potentially compensates for device fabrication variations by taking advantage of the redundancy in switching states over switch permutations; thus, increasing fabrication tolerance. Significant power penalty improvements are demonstrated via both our simulation and test platforms, even for moderate-scale silicon switches.

We demonstrate the first multi-stage 8 × 8 silicon photonic switch with switching elements based on dual add-drop microrings with a compact footprint of 4 mm2. This device leverages co-design of the switch architecture and the switching elements with a well-balanced set of performance metrics. The switching elements are designed to have a 3-dB optical passband of 165 GHz, exhibiting off- and on-resonance losses of 0.67 dB and 2 dB, respectively. Full characterization of all switch paths shows an end-to-end on-chip loss between 4.4 and 9.6 dB, with worst-case crosstalk leakage averaged at −16 dB. Owing to the efficient doped waveguide thermo-optic phase shifters, the device features a tuning efficiency of 48.85 GHz/mW. The reconfiguration time of the switch fabric is measured to be 1.2 μs and 0.5 μs at the rise and fall edge, respectively. The dual-microring switching element together with the multi-stage architecture preserves an end-to-end passband over 55 GHz. We validate the switch performance with optical paths of varying numbers of on- and off-resonance switching elements – less than 2 dB power penalties are obtained for all data routings at 32 Gbps.

Quantum variational algorithms have garnered significant interest recently, due to their feasibility of being implemented and tested on noisy intermediate scale quantum (NISQ) devices. We examine the robustness of the quantum approximate optimization algorithm (QAOA), which can be used to solve certain quantum control problems, state preparation problems, and combinatorial optimization problems. We demonstrate that the error of QAOA simulation can be significantly reduced by robust control optimization techniques, specifically, by sequential convex programming (SCP), to ensure error suppression in situations where the source of the error is known but not necessarily its magnitude. We show that robust optimization improves both the objective landscape of QAOA as well as overall circuit fidelity in the presence of coherent errors and errors in initial state preparation.

In the cause of working out the challenge of remaining life prediction (RUL) of proton exchange membrane fuel cell (PEMFC) under dynamic operating conditions, this article proposes a PEMFC RUL forecast technique based on the sparse autoencoder (SAE) and deep neural network (DNN). The method extracts the data set from the original experimental data at intervals periods of one hour to realize datum reconstruction. The Gaussian-weighted moving average filter is used to smooth noisy data (voltage and current). The smoothed filtered power output signal of the stack is extracted as an aging indicator. The SAE is used to extract the prediction features automatically, and the DNN is applied to realize the RUL prediction. The proposed method is experimentally verified using 127 369 experimental data. The effectiveness of the novel method is verified by three different training sets and test set configurations. The experimental results reveal that the novel approach has the best prediction effectiveness when the training set length is set to 500 h. At this point, the prediction accuracy can reach 99.68%. The mean absolute error (MAE), mean square error (MSE), and root-mean-square error (RMSE) are minimum values, which are 0.2035, 0.1121, and 0.3348, respectively. The superiority and effectiveness of the proposed approach are further validated by comparison with the K-nearest neighbor and support vector regression machine. The proposed approach can be appropriate for the prediction of the RUL of PEMFC under dynamic conditions.

The coupler knuckle of railway wagon is a complex forging component with big section change. In this paper, a near-net-shape forming process for coupler knuckle based on closed-die forging without flash was proposed and the preforming operation was designed and optimized. Firstly, the shape and the dimension of the preforging were preliminarily designed based on the geometric features of forged knuckle and the flow characteristics of metal in the forging process, and then a multi-objective optimization approach based on the filling capacity, deformation homogeneity, and damage degree of forgings was established, and the response surface method combined with the finite element simulation was used to obtain the optimum geometric parameters of preforging. In order to verify the effectiveness of the near-net-shape forming process and the optimized results on preform design, forming experiments and measurements were carried out; the analyzed results show that based on the designed preforging, near-net-shape forming process is capable of producing coupler knuckle of high quality and without forming defect.

Choosing an appropriate interlayer (IL) is still a crucial challenge for charge balance and exciton regulation in ultra-thin doping-free white organic light-emitting diodes (WOLEDs). Herein, for the first time, the blue thermally activated delayed fluorescence (TADF) 10, 10, 10-(4, 4, 4-Phosphoryltris (benzene-4, 1-diyl)) tris (10Hphenoxazine) (TPXZPO) was selected as the n-type inter-layer (IL) switch. The monochromatic and white light device achieved maximum external quantum efficiencies (EQE) of 24.47% and 14.96%, respectively. More importantly, all devices exhibited extremely low turn-on voltage and stable electroluminescent spectra, with CIE coordinates Δ (x, y) varying only by (0.01, 0.01) in the luminance range of 100 to 10,000 cd/m2. The results showed that new-type IL plays a crucial role in regulating charge and exciton distribution, which could effectively control of the emission zone and the triplet exciton density. This excellent performance demonstrates that the introduction of TADF IL is a promising prospect in the application of high-performance ultra-thin doping-free WOLEDs.

Besides enhancing thermoelectric performance of the existing thermoelectric materials, many efforts have been focused on the exploration of novel thermoelectric materials with potentially high performance typically. This is largely guided by the concept of the intrinsic low lattice thermal conductivity, which is arisen from various mechanisms, such as intrinsic vacancy, low sound velocity, complex crystal structure and lattice anharmonicity. Motivated by the inherent feature of highly disorder cations and intrinsic vacancies introducing strong lattice anharmonicity, this work focuses on a semiconducting compound, ZnIn2Se4, as a potential thermoelectric material. Pristine ZnIn2Se4 shows an n-type conduction and a low carrier concentration of 2.8 × 1018 cm−3. A lattice thermal conductivity as low as ∼0.9 W/m*K at high temperature is obtained, due to the additional phonon scattering by highly disorder cations and intrinsic vacancies. Thus, a peak zT of ∼0.23 is demonstrated in pristine ZnIn2Se4 even with the carrier concentration far deviating from the optimum. This work not only indicates this compound as a promising n-type thermoelectric material, but also provides a direction for enhancement of zT.

In order to improve the robustness of the energy management system (EMS) and avoid the influence of demand power on the design of EMS, a coupled power-voltage equilibrium strategy based on droop control (CPVE-DC) is proposed in this paper. Making use of the principal that the DC bus can directly reflect the changes of load power, the proposed strategy couples DC bus voltage with output powers through droop control to achieve self-equilibrium. The proposed EMS is applied into a hybrid tramway model configured with multiple proton exchange membrane fuel cell (PEMFC) systems, batteries and super capacitors (SCs). FC systems and SC systems are responsible for satisfying most of the demand power, therefore the CPVE-DC strategy generates FCs and SCs reference power through power-voltage droop control on the primary control. Then batteries supplement the rest part of load power and generate DC bus voltage reference value of the next sampling time. With the gambling between output power and DC bus voltage, the hybrid system achieves self-equilibrium and steps into steady operation by selecting appropriate droop coefficients. Then the secondary control of the proposed strategy allocates power between every single unit. In addition, a penalty coefficient is introduced to balance SOC of SCs. The proposed strategy is tested under a real drive cycle LF-LRV on RT-LAB platform. The results demonstrate that the proposed strategy can achieve self-equilibrium and is effective to allocate demand power among these power sources，achieve active control for the range of DC bus voltage and SOC consensus of SCs as well. In addition, some faults are simulated to verify the robustness of the proposed strategy and it turns out that the CPVE-DC strategy possesses higher robustness. Finally, the CPVE-DC strategy is compared with equivalent consumption minimization strategy (ECMS) and the results shows that the proposed strategy is able to get higher average efficiency and lower equivalent fuel consumption.

Benefited from hierarchical porous structure of Loofah sponge (LS) fibers, a 3D electrically and thermally conductive network structure termed conductive cellulose skeleton (Cellulose-RGO-TDI) was fabricated. In addition, PA6 molecular chains were covalently bonded with conductive cellulose skeleton by reaction between imino groups of PA6 and isocyanate groups of Cellulose-RGO-TDI. As a result, PA6/Cellulose-RGO-TDI nano-composite with high electrical and thermal conductivity was fabricated via reactive melt processing. Both RGO outside the fiber and RGO inside the 3D-bundled micro-channel work together to assemble omnibearing trans-scale conductive networks in the whole hierarchical porous structure of the cellulose skeleton. Finally, more integral conductive pathways are established by RGO along the cellulose fiber, which is more beneficial to transmission of charge carrier and phonons in the whole cellulose skeleton. Exfoliated RGO nano-sheets homogeneously dispersed between matrix and cellulose skeleton and a good interface forms, which promoted formation of electrically and thermally conductive network, resulting in the remarkably improved electrically conductivity of 5.8 × 10−1 S/m and thermally conductivity of 0.419 W m−1 K−1 of the composite with 1.2 vol% RGO loading.

The Fenton oxidation of nuclear grade cationic exchange resin was investigated in view of the effects of initial temperature, H2O2 dosage, catalyst type and concentration as well as initial pH. Initial temperature and H2O2 dosage exhibited a significant positive effect on the decomposition of cationic resins, whereas the initial pH showed a negative effect. Ferrous ions had higher catalytic ability than copper ions to the H2O2 activation for resin decomposition, and the best Fe2+ concentration was 0.3 M. Under the conditions of initial temperature of 75 °C, H2O2 dosage of 200 mL, Fe2+ concentration of 0.3 M and initial pH of 0.01, a weight reduction of 73% was achieved. The experimental results on Co-substituted mock samples indicated that the radionuclides loaded in the resins were concentrated in liquid residue. The decomposition of cationic resins followed the two-stage first-order kinetics that composed of a dissolution period of resin beads (first-stage) and a followed degradation stage of resin solution (second-stage). Combined with the UV–visible and infrared spectra and their corresponding density functional theory (DFT) calculations, the dissolution of resin beads was due to the desulfonation of the sulfonated aromatic rings and the oxidative fragmentation of the polymer backbone by hydroxyl radicals ( OH) formed in Fenton reactions. After the dissolution of resin beads, the oxidative degradation and mineralization process proceeded by the attack of OH mainly in aqueous medium.

The energy management strategy is the key to achieve fuel cell hybrid system operation with high-efficiency and low-energy cost. The widely used energy management strategies are established based on the fixed models of power sources energy consumption and efficiency. However, due to the gradual performance degradation of the fuel cell during the service period, some model parameters will change significantly and the fixed models will become increasingly inaccurate over time. Therefore, this paper established time-varying models of power sources energy consumption and efficiency by introducing the fuel cell degradation rate. On this basis, in order to reduce the energy consumption of the system, improve the fuel cell efficiency and relatively maintain the SOC level, a novel dual-mode energy management strategy, DMDEE, for hybrid vehicles was proposed. In order to improve the online operation speed of proposed energy management strategy, the optimal control rules were obtained by offline calculation first. Then through comparison experiments with other two energy management strategies, PMP and PF, it was verified that the proposed strategy can effectively reduce the system energy consumption and improve the efficiency of the fuel cell system, meanwhile could make the SOC regress after its deviating from ideal working area. In addition, the mode switching hysteresis control was also validated. Therefore, the effectiveness and superiority of the proposed energy management strategy in this paper has been verified.

The component identification of textile materials is critical for quality control and measurement in the textile field. A novel hyperspectral imaging method and the related identification model are proposed to classify single-component textiles. Firstly, the hyperspectral data of the single-component fabrics were processed to conduct dimensionality reduction based on locally linear embedding (LLE), principal component analysis (PCA), and locally preserving projection (LPP) algorithms. Moreover, the original data of 288 wavelengths from 920 nm to 2500 nm were compressed to keep the typical wavelength regions. After that, these data were imported into two classifiers (decision tree classifier and K nearest neighbor (KNN) classifier) for training, and an identification model based on these training data was developed for the sample classification. The experimental results showed that all the samples could be identified correctly by the established identification model. The recognition rate and the stability of the classifier based on LPP model and KNN classification algorithm were proved to have the highest accuracy in our research.

We review the motivation, goals, and achievements of the Photonic Integrated Networked Energy efficient datacenter (PINE) project, which is part of the Advanced Research Projects Agency–Energy (ARPA-E) ENergy-efficient Light-wave Integrated Technology Enabling Networks that Enhance Dataprocessing (ENLITENED) program. The PINE program leverages the unique features of photonic technologies to enable alternative mega-datacenters and high-performance computing (HPC) system architectures that deliver more substantial energy efficiency improvements than can be achieved through link energy efficiency alone. In phase 1 of the program, the PINE system architecture demonstrated an average factor of 2.2 × improvement in transactions/joule across a diverse set of HPC and datacenter applications. In phase 2, PINE will demonstrate an aggressive 1.0 pJ/bit total link budget with high-bandwidth-density dense wavelength-division multiplexing (DWDM) links to enable additional 2.5 × or more efficiency gains through deep resource disaggregation.

During the fuel cell vehicles operation, traditional optimization-based power distribution strategy mostly regards PEMFC as a characteristic-fixed DC power supply, which ignoring the problem that the characteristics of PEMFC will significantly change. And in traditional equivalent hydrogen consumption calculation of energy storage system, it ignores the PEMFC consumption nonlinear characteristics and the brake energy used to charge the energy storage system, resulting the calculation inaccuracy. In order to solve the problem above and optimize the overall energy consumption, this paper proposes an equivalent hydrogen consumption calculation method based on energy storage system historical operation data firstly, then proposes an adaptive power distribution strategy based on the PEMFC parameters online identification. Through the experiments, the effectiveness of the adaptive power distribution strategy is verified.

We study the interfacial structure and dynamics of a polymer nanocomposite (PNC) composed of octaaminophenyl polyhedral oligomeric silsesquioxane (OAPS) and poly(2-vinylpyridine) (P2VP) by performing full atomistic molecular dynamics simulations. There are eight aminophenyl groups grafted on the surface of the OAPS particle and the particle has a size comparable to the Kuhn segment of P2VP. These aminophenyl groups can form hydrogen bonds (HBs) with pyridine rings from surrounding P2VP chains. We found that OAPS can form ∼2 HBs on average with surrounding polymer chains. The effect of the HBs is investigated in detail by either switching on or off these HBs in our simulation. By analyzing the interfacial static packing structure and dynamic properties, we demonstrate that the system has an ∼1 nm interface width, similar to the OAPS particle size. We also found that HBs can prevent the further penetration of polymers into the inner zone (grafting layer) of the OAPS, and therefore keep the P2VP chains in the outer layer (>1 nm), remaining bulk-like, which is well consistent with experimental results. In addition, we found that NP diffusion is coupled to the absorbed polymer chains, which also dramatically slows down the diffusion of polymer segments in return. The core–shell model in which the NP and absorbed polymers diffuse as a single object is validated here at the full atomistic level. These results provide atomistic insights into the unique structure and dynamics in the small attractive NP–polymer interfacial region. We hope these results will be helpful for the understanding of peculiar phenomena in attractive polymer nanocomposites containing small NPs.

We presented new physical insights into designing resonator-assisted photonic interleavers. The robust flat-top transmission spectra of the devices can be achieved and interpreted through rigorous mathematical models based on quasi Fourier series.

Although the hard template method is often employed to prepare N-doped mesoporous carbon(N-MC), the removal of the silica template commonly involves the use of highly toxic HF or repeated treatment with NaOH solution. Herein, we report a polyvinylidene fluoride-assisted one-step method for synthesis of N-MC, namely the silica-free N-MC can be prepared via temperature-programmed thermal treatment of a slurry obtained by dispersing nano-silica into a solution containing sucrose, urea, oxalic acid, polyvinylidene fluoride and dimethylacetamide. The resulting N-MC, which owns 3.47%(mass fraction) nitrogen and a surface area of 929 m2/g, is a highly suitable support of Pd catalyst used in hydrodechlorination of 2,4-dichlorophenol, with its performance being much better than those of MC and activated carbon. The excellent catalytic hydrodechlorination activity of the Pd/N-MC catalyst can be attributed to its strong metal-support interaction which results in a good Pd dispersion and high resistance to the growth of nanosized Pd under reaction conditions.

The combination of biomimetic nanochannels and nanostructures provided a new idea for bioanalytical purposes. In this paper, we reported a self-assembled system based on the integration of anodic aluminum oxide (AAO) membranes and CuO method to fabricate CuO nanostructures in the confined area of AAO membranes. Furthermore, we investigated morphologies of the self-assembly systems by field emission scanning electron microscopy (FESEM) and characterized the type and content of microelements by energy dispersive spectrometer. Transmembrane ion current through nanochannels was tested by an electrochemical workstation, and optical properties of the self-assembly systems were characterized by ultraviolet–visible spectrophotometer. We could conclude from the results that the morphology and distribution status of CuO nanostructures are controllable, while ionic current through nanochannels and optical properties of self-assembled systems could be regulated by changing experimental parameters such as electrodeposition time, electrodeposition voltage or annealing temperature. On this base, we utilized the synergistic effect of nanochannels and nanostructures to enhance the sensitivity of biological molecules response. This study not only prepared CuO nanostructures in biomimetic nanochannels controllably, but also provided a novel application paradigm for nanochannels-nanostructures self-assembled system, which could be used for biological analysis and detection.

Adding small nanoparticles (NPs) into polymer melt can lead to a non-Einstein-like decrease in viscosity. However, the underlying mechanism remains a long-standing unsolved puzzle. Here, for an all-polymer nanocomposite formed by linear polystyrene (PS) chains and PS single-chain nanoparticles (SCNPs), we perform large-scale molecular dynamics simulations and experimental rheology measurements. We show that with a fixed (small) loading of the SCNP, viscosity reduction (VR) effect can be largely amplified with an increase in matrix chain length \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N$$\end{document}N, and that the system with longer polymer chains will have a larger VR. We demonstrate that such \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N$$\end{document}N-dependent VR can be attributed to the friction reduction experienced by polymer segment blobs which have similar size and interact directly with these SCNPs. A theoretical model is proposed based on the tube model. We demonstrate that it can well describe the friction reduction experienced by melt polymers and the VR effect in these composite systems., Addition of small nanoparticles into polymer melt can lead to decrease in viscosity but the underlying mechanism for such viscosity reduction remains unclear. Here, the authors investigate the reduction in viscosity by large-scale molecular dynamics simulation and experimental rheology measurements for an all-polymer nanocomposite formed by linear polystyrene chains and PS single-chain nanoparticle.

Exploration of novel thermoelectric materials is of great significance for thermoelectric development. AB2X2 Zintl compounds with rich chemical constitute, have been frequently demonstrated as promising thermoelectric materials because of their low lattice thermal conductivity and tunable band structure. This motivates the current work to focus on the experimental evaluation of thermoelectric potential on SrCd2Sb2, a new member of Zintl compounds. Na-substitution at Sr site leads to an effective increase in Hall carrier concentration from ~ 2.6 × 1018 to ~ 1.1 × 1020 cm−3, enabling a well estimation of transport properties by a single parabolic band (SPB) model with acoustic scattering. This reveals a multi-band transporting behavior in SrCd2Sb2 thermoelectrics with heavy-doping or elevated-temperature, ensuring a 150%-improvement in thermoelectric figure of merit (zT). On the basis of model, a peak zT of ~ 1.4 is achievable by minimizing lattice thermal conductivity, which not only demonstrates this compound as a promising thermoelectric material, but also provides a guidance for further advancements.

We have specified the synthetic conditions to obtain one-directionally ordered CaSi2 microwall arrays vertically grown on a Si substrate. Our basic concept is based on the utilization of the Kirkendall effect for reactive deposition epitaxy (RDE). We found for the first time that: 1) a much larger Ca vapor supply on the Si substrate than the conventional RDE, 2) the adoption of a two-step heating process, and 3) the selection of the crystal axis of the Si surface are the keys to control the microstructures of CaSi2 on the Si substrate. The CaSi phase was first formed on Si, then the CaSi2 phase was formed at the CaSi/Si interface. Based on the Kirkendall effect, the interdiffusion of Ca and Si was enhanced in the vertical direction rather than in the parallel direction to the Si surface. CaSi2 tends to grow along four equivalent Si{111} planes, however, the specific orientation of the Si surface resulted in CaSi2 microwalls grown along its Si(111‾ ) plane, the only plane directing nearly vertical to the surface among the Si{111} planes. These results suggest that the Kirkendall effect under asymmetric growth of target materials would be a rational strategy to obtain their ordered microstructures.

As bytes-per-FLOP ratios continue to decline, communication is becoming a bottleneck for performance scaling. This paper describes bandwidth steering in HPC using emerging reconfigurable silicon photonic switches. We demonstrate that placing photonics in the lower layers of a hierarchical topology efficiently changes the connectivity and consequently allows operators to recover from system fragmentation that is otherwise hard to mitigate using common task placement strategies. Bandwidth steering enables efficient utilization of the higher layers of the topology and reduces cost with no performance penalties. In our simulations with a few thousand network endpoints, bandwidth steering reduces static power consumption per unit throughput by 36% and dynamic power consumption by 14% compared to a reference fat tree topology. Such improvements magnify as we taper the bandwidth of the upper network layer. In our hardware testbed, bandwidth steering improves total application execution time by 69%, unaffected by bandwidth tapering., United States. Advanced Research Projects Agency-Energy. ENLITENED Program (Project award DE-AR00000843), United States. Department of Energy. Office of Science ( Contract DE-AC02-05CH11231)

A successful robot-assisted feeding system requires bite acquisition of a wide variety of food items. It must adapt to changing user food preferences under uncertain visual and physical environments. Different food items in different environmental conditions require different manipulation strategies for successful bite acquisition. Therefore, a key challenge is how to handle previously unseen food items with very different success rate distributions over strategy. Combining low-level controllers and planners into discrete action trajectories, we show that the problem can be represented using a linear contextual bandit setting. We construct a simulated environment using a doubly robust loss estimate from previously seen food items, which we use to tune the parameters of off-the-shelf contextual bandit algorithms. Finally, we demonstrate empirically on a robot-assisted feeding system that, even starting with a model trained on thousands of skewering attempts on dissimilar previously seen food items, $\epsilon$-greedy and LinUCB algorithms can quickly converge to the most successful manipulation strategy., Comment: To appear in IROS 2020; 8 pages incl. references, 8 figures; Abstract presented in IJCAI 2019 AIxFood Workshop; v3: Added simulation and experimental results for conference submission; v4: Added extra results to Experiment 2 for camera-ready submission

Rhombohedral GeTe can be approximated as the directional distortion of the cubic GeTe along [111]. Such a symmetry-breaking of the crystal structure results in an opposite arrangement in energy of the L and Σ valence bands, and a split of them into 3L+1Z and 6Σ+6η, respectively. This enables a manipulation of the overall band degeneracy for thermoelectric enhancements through a precise control of the degree of crystal structure deviating from a cubic structure for the alignment of the split bands. Here, we show the effect of AgBiSe2-alloying on the crystal structure as well as thermoelectric transport properties of rhombohedral GeTe. AgBiSe2-alloying is found to not only finely manipulate the crystal structure for band convergence and thereby an increased band degeneracy, but also flatten the valence band for an increased band effective mass. Both of them result in an increased density of state effective mass and therefore an enhanced Seebeck coefficient along with a decreased mobility. Moreover, a remarkably reduced lattice thermal conductivity of ∼0.4 W/m-K is obtained due to the introduced additional point defect phonon scattering and bond softening by the alloying. With the help of Bi-doping at the Ge site for further optimizing the carrier concentration, thermoelectric figure of merit, zT, of ∼1.7 and average zTave of ∼0.9 are achieved in 5% AgBiSe2-alloyed rhombohedral GeTe, which demonstrates this material as a promising candidate for low-temperature thermoelectric applications.

Made available in DSpace on 2019-10-04T12:38:12Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-07-24 NSERC DG MESI PSIIRI 936 China Scholarship Council Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Trottier Energy Institute FRQNT-RQMP Ion-gated transistors employ ionic gating media (e.g. ionic liquids, polymer electrolytes, aqueous saline solutions) to modulate the density of the charge carriers in the transistor channel. Not only they operate at low voltages (ca 0.5-1 V) but they can also feature printability, flexibility and easy integration with chemo- and bio-sensing platforms. Metal oxides are transistor channel materials interesting for their processability in air, at low temperature. Among metal oxides, tungsten oxide (band gap ca 2.5-2.7 eV) stands out for its electrochromic, gas sensing and photocatalytic properties. Here we demonstrate ion-gated tungsten oxide transistors and phototransistors working in different ion gating media, such as one hydrophobic ionic liquid and an aqueous electrolyte, fabricated both on rigid and flexible substrates. Ion-gated tungsten oxide phototransistors operating in aqueous media could be used as photocatalytic sensors in portable applications. Polytech Montreal, Dept Genie Phys, CP 6079,Succ Ctr Ville, Montreal, PQ H3C 3A7, Canada Univ Fed Minas Gerais, Dept Fis, BR-30123970 Belo Horizonte, MG, Brazil Polytech Montreal, Dept Genie Chim, CP 6079,Succ Ctr Ville, Montreal, PQ H3C 3A7, Canada Univ Estadual Paulista, Dept Fis Quim, Rua Prof Degni 55, BR-14800060 Araraquara, Brazil Univ Montreal, Dept Chim, CP 6128,Succ Ctr Ville, Montreal, PQ H3C 3J7, Canada Univ Bologna, Dipartimento Chim Giacomo Ciamician, Via Selmi 2, I-40126 Bologna, Italy Univ Estadual Paulista, Dept Fis Quim, Rua Prof Degni 55, BR-14800060 Araraquara, Brazil FAPESP: 2014/27079-9 FAPESP: 2015/50526-4 FAPESP: 2016/09033-7

There is an increasing need to develop conducting hydrogels for bioelectronic applications. In particular, poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) hydrogels have become a research hotspot due to their excellent biocompatibility and stability. However, injectable PEDOT:PSS hydrogels have been rarely reported. Such syringe-injectable hydrogels are highly desirable for minimally invasive biomedical therapeutics. Here, an approach is demonstrated to develop injectable PEDOT:PSS hydrogels by taking advantage of the room-temperature gelation property of PEDOT:PSS. These PEDOT:PSS hydrogels form spontaneously after syringe injection of the PEDOT:PSS suspension into the desired location, without the need of any additional treatments. A facile strategy is also presented for large-scale production of injectable PEDOT:PSS hydrogel fibers at room temperature. Finally, it is demonstrated that these room-temperature-formed PEDOT:PSS hydrogels (RT-PEDOT:PSS hydrogel) and hydrogel fibers can be used for the development of soft and self-healable hydrogel bioelectronic devices.

© 2019 IEEE. A common approach to learning to rank is to minimize the pair-wise loss. However, established analysis shows that pair-wise loss does not necessarily lead to an optimal list-wise ranking measures, e.g., average precision (AP) or area under precision-recall curve (AUPRC). It becomes more difficult in the online learning setting, where the data arrives sequentially and is scanned only once. This paper proposes an online learning-to-rank algorithm by minimizing the list-wise ranking error, which achieves a vanishing gap between the list-wise loss and the ranking measures. Experiments also testify the effectiveness and robustness of the proposed online List-wise algorithm.

We have demonstrated a low threshold and tunable flexible random laser (RL) in dye-doped poly ethylene glycol diacrylate (PEG-DA) hydrogel, which was prepared by crosslinking polymerization using PEG-DA monomer and photoinitiator. The random lasering is attributed to the light scattering from the porous structure of hydrogels, and the wavelength of random lasing can be tuned by ~3.2 nm in the temperature range from 30 °C to 70 °C. Under the continuous increasing and decreasing temperature cycle, the random lasing tunable phenomenon can still be observed, which proves that this flexible material can be used as a new temperature sensor. In addition, we also explored the application of flexible laser in phototherapy. Considering the good elasticity and transparency of hydrogels, this thermo-responsive property will be of great significance to the biomedical applications of flexible material.

Spent resins generated from the nuclear industrial processes are still difficult to be treated and disposed. Fenton-like processes have great application potential in the treatment of spent resins, but the Fenton reaction mechanisms and resin degradation pathways remain challenging. In this study, nanoscale Fe0/Cu0 bimetallic catalysts were prepared and characterized for the Fenton-like degradation of the mixture of cationic and anionic resins. High catalytic property of Fe0/Cu0 bimetallic nanoparticles activated by H2O2 was evaluated, according to the effects of various nanoparticles, temperature, catalyst amount, H2O2 concentration and the mixing ratio of cationic and anionic resins. Combined the shape and color changes of mixed resins with the experimental and calculated characterization results, different degradation difficulty of cationic and anionic resins and their degradation mechanisms were studied. According to the density functional theory calculations of the optimized resin molecules with the Fe0/Cu0 catalyst, the mechanisms of Fenton-like reactions and the degradation of mixed resins through the synergistic effect of Fe and Cu species were proposed. The comprehensive Fenton-like reactions and degradation mechanisms provide new insights to advance the treatment of spent resins and organic polymers by Fenton-like processes.

Nitrogen/phosphorus enriched biochars with enhanced porosity were prepared through a one-step pyrolysis of bamboo sawdust activated by guanidine phosphate (GP). The thermal decomposition of GP released alkaline gas and hydrogen proton to create more micropores in biochar matrix which were extended to be mesopores further. Nitrogenous/phosphorous moieties of GP were introduced into biochars efficiently via cross-linking with the carbon skeleton. GP-activated biochar pyrolyzed at 450 °C exhibited enriched surface functional groups (11.3 at.% for N, 4.1 at.% for P), resulting in high sorption capacities for aquatic Pb(II) (166.2 mg/g), Cu(II) (81.7 mg/g), and Cd(II) (60.3 mg/g). Pb(II) was passivated fast with the formation of minerals including Pb5(PO4)3OH and Pb5(PO4)3Cl. Cu(II) was strongly coordinated with the N-containing species especially pyridinic N. Cd(II) was also captured efficiently due to the chemical complexation, cation exchange and cation-π bonds. GP-activated biochars could be well-recycling used to capture these heavy metals. Regarding these, the activation of biomass residuals could be an efficient approach to functionalize the surface of biochars with enhanced porosity, which is great benefiting for the immobilization of heavy metals from contaminated water.

The regulation of charge and exciton distribution play a significant role in ultra-thin non-doped white organic light-emitting diodes (WOLEDs). Herein, the exciplex is selected as an interlayer (IL) switch to adjust the charge balance and regulate exciton distribution in ultra-thin non-doped WOLEDs. The optimal device achieved a maximum external quantum efficiency (EQE) of 22.42 %, a maximum current efficiency of 63.41 cd/A and a maximum power efficiency of 83.04 lm/W. The time‐resolved photoluminescence of different exciplexes has been systematically investigated to reveal the intrinsic luminance mechanism of high-efficiency WOLEDs. In addition, kelvin probe force microscopy (KFPM) results provide new insights in exciplex interlayer switch surface charge effect. These results demonstrate the potential of exciplex IL for exciton confinement, charge balance and carrier transport, which prevent energy loss and reduce triplet-triplet annihilation. Therefore, the utilization of exciplex IL is a promising approach for the development of next-generation WOLEDs.

Si nanosheets connected to Si nanowires were synthesized using a MnCl 2 /Si powder source with an Au catalyst. The synthesis method has benefits in terms of avoiding conventionally used air-sensitive SiH 4 or SiCl 4 . The existence of the Si nanosheets connected to the Si nanowires, like sprouts or leaves with petioles, was observed, and the surface of the nanosheets was Si{111}. The nanosheets were grown in the growth direction of perpendicular to that of the Si nanowires. It was evident from these structural features of the nanosheets that the nanosheets were formed by the twin-plane reentrant-edge mechanism. The feature of the observed lattice fringes, which do not appear for Si bulk crystals, of the Si(111) nanosheets obtained by high resolution transmission electron microscopy was clearly explained due to the extra diffraction spots that arose by the reciprocal lattice streaking effect.

Hybrid organic–inorganic perovskites, represented by materials in the CH3NH3PbI3 series, have become one of the most promising materials for solar cells with a high power conversion efficiency and low cost. The ordered Pb–I cage in such hybrid perovskites can induce the polarized cations to form a variety of polarization domains with long-range order, which will lead to the formation of specific atomic conformations or metastable crystalline phases, unique electronic band structures and optical absorption properties. Such domain-dependent characteristics play a critical role in the phase transition and service stability of such solar cells, and also open up the opportunity of tuning their electronic structure. In the present study, we systematically investigate the band structures and optical absorption properties of different electronically ordered domains in CH3NH3PbI3. By comparing different perovskites containing various cations, we have clarified the important influence of cation polarization on domain-dependent properties. Our results provide not only a possible pathway for the manipulation of band structure by applying an external field, but also a novel scheme for improving the performance and stability of hybrid perovskites.

Ensuring stable red and blue emission from white organic light-emitting devices (WOLEDs) with complementary colors is a major challenge. Here, a novel exciplex systems were used to solve this problem, where a thermally activated delayed fluorescence (TADF) material 10, 10, 10-(4, 4, 4-Phosphoryltris (benzene-4,1-diyl)) tris (10Hphenoxazine) (TPXZPO) and a common hole transporting material N,N′-dicarbazolyl-3,5-benzene (MCP) were mixed with an electron-transporting material (1,3,5-Triazine-2,4,6-triyl)tris(benzene-3,1-diyl)) tris(diphenylphosphineoxide) (PO-T2T) to form exciplex host for red and blue phosphorescent materials, respectively. Benefitted from the high triplet energy of donor and accepter were select to form exciplex host which ensures that excitons are excellent confined to the EMLs. Matched exciplex host-guest systems and a multichannel reverse intersystem crossing reduces energy loss during energy transfer processes and prevents triplet-triplet annihilation. The use of stepped energy transfer channels and exciplex interlayer switch ensures WOLEDs have greater stability. The devices exhibited a maximum power efficiency, current efficiency, and external quantum efficiency of 69.25 lm/W, 56.69 cd/A and 24.55%, respectively. More importantly, the devices exhibited extremely stable color rendering index ranging from 74 to 76 with luminance ranging from 102 to 104 cd/m2. These results indicate that the exciplex are promising for use in developing high performance complementary color WOLEDs.

Particle swarm optimization (PSO) algorithm is a stochastic and population-based optimization algorithm. Its traditional learning strategy is implemented by updating the best position using the particle’s own historical best experience and its neighborhood’s best experience to find the optimal solution of the problem. However, the learning strategy is ineffective when dealing with highly complex problems. In this paper, a particle swarm optimization algorithm based on a multidimensional mean learning strategy is proposed. In this algorithm, an opposition-based learning strategy is utilized to initialize the population to enhance the exploitation capability. Furthermore, the historical best positions of all the particles are reconstructed in a vertical crossover manner that is based on the mean information of multiple optimal dimensions to generate the guiding particles. Additionally, an improved inertia weight is used to further guide all the particle movements to balance the capability of the proposed algorithm for global exploration and local exploitation. The proposed algorithm is tested on 12 benchmark functions and is compared with some well-known PSO algorithms. The experimental results show that the proposed algorithm obtains more competitive optimal solution compared with other PSO algorithms when solving high-dimensional complex problems.

Selection of non-toxic elements existed in human body or certified for tissue regeneration is considered for multifunctional biodegradable metals. The effect of Sr addition on microstructure, mechanical properties, and degradation behavior of biodegradable Mg–2Zn-0.3Ca alloy was studied as an example to gain insight into the Mg–Zn–Ca alloy series. The average grain size of alloys became smaller and more homogeneous distinctly by increasing Sr content. The second phases on the grain boundaries and the interdendritic interstices were also refined with small amount of Sr addition. More concentration of Sr element was detected evidentially at the interface between grains and the second phases. Mg–2Zn-0.3Ca-0.3Sr alloy shows the optimal flexural and compressive strength of (441 ± 18) MPa and (317 ± 13) MPa, respectively. The electrochemical measurement in simulated body fluid showed that addition of Sr would slightly deteriorate the corrosion resistance of Mg–Zn–Ca–Sr alloys. The in-vitro immersion tests were conducted and analyzed in detail by three different immersion stages and got a distinctive corrosion performance compared with the electrochemical measurements. Homogenization annealing was conducted for Mg–2Zn-0.3Ca-0.3Sr alloy, which can reduce dendrite segregation and significantly improve the corrosion resistance of alloy. The degradation process of alloys in simulated body fluid was summarized in detail for Mg–Zn–Ca–Sr alloys. This work not only provides the relationship between microstructure and properties of biodegradable Mg alloys, but also a comprehensive discussion of degradation behavior of Mg–Zn–Ca alloys for orthopedic application.

Polymeric single-chain nanoparticles (SCNPs) are soft nano-objects synthesized by intramolecular crosslinking of isolated single polymer chains. Syntheses of such SCNPs usually need to be performed in a dilute solution. In such a condition, the bonding probability of the two active crosslinking units at a short contour distance along the chain backbone is much higher than those which are far away from each other. Such a reaction condition often results in local spheroidization and, therefore, the formation of loosely packed structures. How to inhibit the local spheroidization and improve the compactness of SCNPs is thus a major challenge for the syntheses of SCNPs. In this study, computer simulations are performed and the fact that a precollapse of the polymer chain conformation in a cosolvent condition can largely improve the probability of the crosslinking reactions at large contour distances is demonstrated, favoring the formations of closely packed globular structures. As a result, the formed SCNPs can be more spherical and have higher compactness than those fabricated in ultradilute good solvent solution in a conventional way. It is believed this simulation work can provide a insight into the effective syntheses of SCNPs with spherical conformations and high compactness.

The diffusion dynamics of fullerene (C 60 ) in unentangled linear atactic polystyrene (PS) and polypropylene (PP) melts and the structure and dynamic properties of polymers in interface area are investigated by performing all-atom molecular dynamics simulations. The comparison of the results in two systems emphasises the influence of local interactions exerted by polymer side group on the diffusion dynamics of the nanoparticle. In the normal diffusive regime at long time scales, the displacement distribution function (DDF) follows a Gaussian distribution in PP system, indicating a normal diffusion of C 60 . However, we observe multiple peaks in the DDF curve for C 60 diffusing in PS melt, which indicates a diffusion mechanism of hopping of C 60 . The attractive interaction between C 60 and phenyl ring side groups are found to be responsible for the observed hopping diffusion. In addition, we find that the C 60 is dynamically coupled with a subsection of a tetramer on PS chain, which has a similar size with C 60 . The phenyl ring on PS chain backbone tends to have a parallel configuration in the vicinity of C 60 surface, therefore neighbouring phenyl rings can form chelation effect on the C 60 surface. Consequently, the rotational dynamics of phenyl ring and the translational diffusion of styrene monomers are found to be slowed down in this interface area. We hope our results can be helpful for understanding of the influence of the local interactions on the nanoparticle diffusion dynamics and interfacial properties in polymer/nanoparticle composites.

Electrolyte-gated transistors hold promise for applications in printable and flexible electronics. Metal oxide semiconductors are particularly interesting as electrolyte-gated channel materials for their abundance, thermodynamic stability and ease of processing under ambient conditions. In this work, we synthesized by sol–gel and hydrothermal methods different types of tungsten oxide to be used as channel materials in ion gel-gated transistors. X-ray diffraction and scanning and transmission electron microscopy revealed that the differently processed oxides show a different structure (hexagonal and monoclinic) and morphology (granular, nanofiber and nanoplate). We studied the electrochemical and transistor properties of the oxides using, as the gating media, two different ion gels prepared from the same ionic liquid, 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM]TFSI), and two different block copolymers. We tentatively propose that for sufficiently high values of the gate–source bias, the doping results from chemical and electrochemical contributions.