Search

The cathode of solid oxide electrolysis cell (SOEC) is used as a place for fuel gas electrolysis/co-electrolysis, and its performance significantly affects the efficiency of electrolysis. La0.75Sr0.25Cr0.5Mn0.5O3-δ (LSCM) is a potential SOEC cathode material due to its excellent redox stability and catalytic ability for fuel gas. An electrolyte-supported LSCM/YSZ/LSCM symmetrical cell and LSCM/YSZ/LSCF full cell were prepared and evaluated for high temperature steam electrolysis, carbon dioxide electrolysis and co-electrolysis. Under the applied voltage, both the symmetrical electrolysis cell and the full electrolysis cell can effectively electrolysis CO2 and H2O. During the experiment, by changing the operating conditions, the influence of different temperatures, concentration of CO2 and H2O, and applied voltage was studied to evaluate the electrochemical performance of SOEC. In order to further verify the long-term performance of SOEC, constant voltage was applied for co-electrolysis of CO2 and H2O. During the entire electrolysis process, the SOEC showed a stable current density of 0.1A·cm-2 under the applied voltage 1.5 V for more than 24 h.

The working fluid is a critical component in direct absorption solar collectors. Nanoparticle (NP) suspensions can be used as efficient solar absorption media. In this work, Cu@C core–shell NPs were designed to enhance the solar absorption performance by the coupled effect of the local surface plasmon resonance of the Cu core and the strong intrinsic absorption of the C shell. Results showed that the core radius (rc) and shell thickness (ts) had significant effects on the optical properties of Cu@C NPs. The largest absorption power per unit volume of single Cu@C NP was achieved at rc − ts = 25–4 nm. Taking into account the multi-scattering effect in the NP suspensions, the maximum solar absorption efficiency of Cu@C NP suspensions was obtained as 95.6% at rc − ts = 25–14 nm when the volume fraction fv = 100 ppm and height h = 3 mm. These results indicate that the scattering effect is significant to evaluate the solar absorption performance of NP suspensions and the core–shell size parameters should be considered cautiously for the solar thermal conversion applications.

In RFID systems, tag grouping is to inform each tag in the interrogator's RF field which group it belongs to by assigning them a group ID. With this information, the reader can write the same data into a group of tags in one transmission by taking their shared group ID as the destination address, which plays a vital role in improving inventory efficiency. Existing work proposes some efficient protocols but suffers from two defects: slot waste and data redundancy. To address these problems, we in this paper propose a two-phase grouping scheme that improves the grouping efficiency via slot reuse as well as data compression. For slot waste, we try to reconcile collision slots and turn some of them into useful again by re-assigning a new slot to collision tags, which increases the number of useful slots and reduces slot waste. For data redundancy, we encode group IDs with lossless coding algorithms and reduce the data redundancy caused by repetitive transmission of group IDs. Two coding methods, Huffman coding and arithmetic coding , are adopted to shorten the length of the bit vector comprised by group IDs. Theoretical analyses and extensive simulations show that our best protocol improves the time efficiency by 51.9 percent compared with the state-of-the-art.

Leaching of scheelite ore with phytate is a novel and clean hydrometallurgical method of isolating tungsten, which achieves efficient decomposition under atmospheric pressure. However, realizing the separation and recycling of tungstate and phytate has become an additional and subsequent problem, which had not been encountered in the traditional tungsten metallurgical process. In determining ways to overcome this obstacle, ion exchange methods exhibit promising routes to separate tungstate and phytate. Before performing this new method, it is prudent to study the kinetics of the ion exchange process. The effects of WO3 concentration, phytate concentration, resin particle size, and reaction temperature were investigated. Results show that a pseudo-second-order model can describe the adsorption kinetic behavior of phytate and tungstate in the mixed solution. The apparent activation energies of WO3 and phytate, based on the Arrhenius expression, were calculated as 21.4 kJ/mol and 21.8 kJ/mol, indicating that the adsorption processes of phytate and tungstate are diffusion-controlled.

Orthogonal time frequency space (OTFS) modulation has been proposed to achieve outstanding performances over delay-Doppler channels in comparison with orthogonal frequency division multiplexing (OFDM) systems. Particularly, transmitter and receiver structures of OTFS are same as those of asymmetric OFDM (A-OFDM) waveforms, and OTFS is simplified as A-OFDM over static multipath channels. In this letter, we propose an integrated waveform framework based on weighted-type fractional Fourier transform (WFRFT) with two-dimensional adjustable parameters and strong scalability, called as WFRFT-OTFS, which can be reduced to OTFS, A-OFDM, hybrid carrier (HC), OFDM and other waveforms. Basically, theoretical BER expressions of integrated WFRFT-OTFS framework over multipath channels with zero forcing (ZF) and minimum mean square error (MMSE) receivers are derived through fusing different waveform components and verified by simulation results.

Thermally fully developed electrokinetic flow of nanofluid is investigated in a microannulus under the effect of electromagnetic field. The electroviscous effect on heat transfer of nanofluid is analyzed theoretically. Based on the Debye–Huckel linearization approximation, the analytical expressions of electrical potential, flow velocity and streaming potential are derived. Then, the temperature distribution of nanofluid is obtained by the finite difference numerical method. The influences of nanoparticle volume fraction, magnetic field and radius ratio on streaming potential and temperature are discussed in detail. It is revealed that the streaming potential can be enhanced with the increase in magnetic field strength. For various nanoparticle volume fractions, a threshold value of magnetic field strength can be obtained. Besides, local fluid temperature can effectively be enhanced with the increase in nanoparticle volume fraction. Finally, the effect of convective heat transfer can be regulated by the nanoparticle volume fraction, magnetic field strength and microannulus scale. The present work can provide a theoretical contribution to the flow and heat transfer of nanofluid in microannulus.

A series of 0.75Ba(1−x)La2x/3TiO3-0.25Bi(Mg0.5Ti0.5)O3 (x = 0–0.2) ceramics have been synthesized by doping La2O3 into 0.75BaTiO3-0.25Bi(Mg0.5Ti0.5)O3 (0.75BT-0.25BMT), and their structure and dielectric properties investigated. Upon characterizing the structural properties, the single-phase perovskite structure is identified for all the samples and the long-range order of 0.75BT-0.25BMT is verified to be further destroyed with the addition of La2O3. Moreover, it is found that the density of 0.75BT-0.25BMT can be improved by doping with La2O3, which also promotes the grain growth. Regarding the dielectric properties, the peak shifting effect induced by La3+ improves the permittivity-temperature stability of 0.75BT-0.25BMT remarkably by strengthening its relaxation behavior. Among all the samples, 0.75Ba0.8La0.4/3TiO3-0.25Bi(Mg0.5Ti0.5)O3 shows the most outstanding permittivity-temperature stability with er = 572 ± 15% (compared with er at 25 °C) over the temperature range −70°C–238 °C at 1 kHz, which is notably better than that of 0.75BT-0.25BMT (−4°C–58 °C) and satisfies the specification of the X9R multilayer ceramic capacitor (MLCC). Our work provides one promising option for selecting an alternative dielectric material in terms of permittivity-temperature stability, which advances the development of the X9R MLCC.

Modern hydrometallurgy has been developing for more than 100 years and the related articles keep piling up. Based on a bibliometric analysis of the articles in Hydrometallurgy, the most authoritative journal in the field of hydrometallurgy, we try to catch the research and development trends from a global perspective. Firstly, keywords burstness shows that rare earth, recycling, lithium, ionic liquid, and thorium are the hotspots in recent years, and the economic and technological reasons behind them were discussed in depth. Secondly, the proportion of biohydrometallurgy grows fast from 5% to 13% and the related articles are almost all about bioleaching. There are some new directions such as direct preparation of materials in hydrometallurgical processes and ion-imprinted techniques. Thirdly, the advanced instrument analysis methods such as XAFS (X-ray absorption fine structure), gene sequencing, and micro-CT promote the deep understanding of hydrometallurgy mechanism. Finally, the cooperation network and contribution of the main institutes were mapped.

Eutectic AlSi alloy was pressure infiltrated into a porous C/C skeleton to develop a low cost new C/C composite for application without extreme high temperature. C/C composite possessed a density of 1.7 g/cm3 was prepared for comparison. The effects of filling AlSi with and without Al-Ti-C grain refiner on the microstructure and properties of C/C composites were mainly studied. Result indicated that the introduced AlSi interpenetrated with C/C skeleton and made the composites compact. In comparison with C/C composite, the compressive strength and particle erosion resistance were greatly enhanced while the density and thermal expansion coefficient (CTE) increased slightly. After adding the refiner, Si network involved dendritic Al in C/C-AlSi was transformed to refined mixed AlSi, Al bulk and Si surrounded dendritic Al, and two kinds of micro-cracks came into being, which resulted in the decreased strength, improved erosion property and increased CTE of C/C-AlSiR. Both AlSi textures and micro-cracks in the modified C/C composites determined the crack propagation and led to their different compressive behaviors and anti-erosion abilities.

A thorough understanding of the decomposition of perfluoropolyether (PFPE) lubricants is crucial to achieve heat-assisted magnetic recording (HAMR). In contrast to previous studies, which focused on thermal and catalytic decompositions, we gain insights into the mechano-chemical decomposition of PFPE films confined between the head and disk by performing reactive molecular dynamics simulations with our new ReaxFF force field. By quantifying the decomposition time constants under the operation conditions of HAMR, we infer that, within a heating time of ∼1 ns, pure thermal decomposition hardly occurs, whereas mechano-chemical decomposition is highly likely to occur. The decomposition rate constant of the PFPE films subjected to confined shear increases with normal pressure. The increase is well-fitted by a linear stress-activated Arrhenius curve at high normal pressures, whereas this is not the case at low normal pressures. We caution against extrapolating the linear stress-activated Arrhenius curve, which could cause significant overestimation of decomposition rate constants at low normal pressures. We find that the mechano-chemical decomposition of PFPEs is mainly attributed to the dissociation of C–OH and ether C–O bonds in the polar end groups, and in the main chain, the C–O bond is more likely to dissociate than the C–C bond., ファイル公開：2021-10-15

The innovative technology of coleaching scheelite concentrates by a mixture of sulfuric acid and phosphoric acid is an environmentally friendly and low-cost technology. Although the world’s first p...

Collecting in shallow water (water depth: ~30 m) is an emerging field that requires robotics for replacing human divers. Soft robots have several promising features (e.g., safe interaction with the environments, lightweight, etc.) for performing such tasks. In this article, we developed an underwater robotic system with a three-degree-of-freedom (3-DoF) soft manipulator for spatial delicate grasping in shallow water. First, we present the design and fabrication of the soft manipulator with an opposite-bending-and-stretching structure (OBSS). Then, we proposed a simple and efficient kinematics method for controlling the spatial location and trajectory of the soft manipulator’s end effector. The inverse kinematics of the OBSS manipulator can be solved efficiently (computation time: 8.2 ms). According to this inverse kinematics method, we demonstrated that the OBSS soft manipulator could track complex two-dimensional and three-dimensional trajectories, including star, helix, etc. Further, we performed real-time closed-loop pick-and-place experiments of the manipulator with binocular and on-hand cameras in a lab aquarium. Hydrodynamic experiments showed that the OBSS soft manipulator produced little force (less than 0.459 N) and torque (less than 0.228 N·m), which suggested its low-inertia feature during the underwater operation. Finally, we demonstrated that the underwater robotic system with the OBSS soft manipulator successfully collected seafood animals at the bottom of the natural oceanic environment. The robot successfully collected eight sea echini and one sea cucumber within 20 minutes at a water depth of around 10 m.

Most existing robotic fish have a large body size driven by servo motor system, while conventional small-sized actuators hardly generate a high swimming performance. This paper reports a miniature untethered robotic fish, whose body length is 69 mm. In particular, a newly designed magnetic actuator system (MAS) is equipped, which guarantees both small-sized dimension and flexibility of the robot. More specifically, the magnetic field generated by a permanent magnet is first investigated based on Biot–Savart law. Then, a novel tail-beating rhythm called magnetically actuated pulse width modulation (MAPWM) is modeled for the new actuator system. Further, an MAPWM-based control method is presented, in which the duty ratio of MAPWAM is innovatively utilized to realize the turning maneuvers for the first time. In addition, Lagrangian method is employed to establish the dynamic model to assess the MAPWM-based control method and the turning performance of the robotic fish. To further improve the maneuverability, the effect of a shape-variable caudal fin is analyzed based on computational fluid dynamics and the built dynamic model. Finally, combined with the MAS, the MAPWM-based control method, and the optimally selected caudal fin, extensive aquatic experiments are conducted on the robotic prototype. The results indicate that the developed miniature robotic fish achieves a considerably higher level of maneuverability in terms of turning radius when compared to swimming robots with equivalent dimensions.

A transparent display allows us to see both the projection image displayed on it and the view behind it at the same time, which can be widely used in the car windshield, shop windows, and so on. To achieve the transparent display with the simple and easily available plasmonic nanoparticles, plasmonic Au-Ag nanoparticles with the strong scattering ability were used to achieve the objective of selectively scattering red, blue, and green light for the transparent screen in this work. Firstly, the optimized size parameters for these three color transparent displays were obtained theoretically. On the other hand, plasmonic nanoparticles used for the blue and green color transparence screen were reported in the previous experiments. Finally, a red color transparent display with the wide viewing angle was made based on the optimized Au nanoparticles experimentally.

An interesting attempt to develop low temperature sintering glass-ceramic/ceramic composite based on La2O3-B2O3-CaO (LBC) glass-ceramic and LaBO3 ceramic, which was reported to be the main crystalline phase precipitated from La2O3-B2O3-based glass-ceramics, has been taken. The sintering behavior, phase evolution, microstructures and dielectric properties of LBC/LaBO3 composites have been studied. The densification of LBC/LaBO3 composite is achieved by partially reactive sintering. The LaBO3 filler is directly involved in the sintering process of glass/ceramic composite as additional liquid phase provider at high sintering temperature, and it will suppress the formation of other crystalline phases so that the produced LBC/LaBO3 composites exhibit unusual simple phase structures, which is beneficial to regulate the performance of composites. LBC/LaBO3 composite with 50 wt% LaBO3 sintered at 950 oC for 2 h has a dielectric constant er = 10.12, a dielectric loss tanδ = 1.82 × 10―3, a Q × f = 9312 GHz (at 16.95 GHz), and shows good chemical compatibility while co-firing with Ag electrode. This indicates that LBC glass/LaBO3 ceramic composites have a potential to meet the requirements of microwave LTCC applications.

Radio Frequency IDentification (RFID) technology has been widely used in missing tag identification to reduce the economic loss caused by theft. Although many advanced works have been proposed, they cannot work properly in an open RFID system with unexpected tags. That is because the unexpected tags may reply to the reader when it is the missing tags’ turn, such that the replies are mistakenly treated as the missing tags’, leading to failure to detect the missing tags. To solve the problem, this article proposes an order-based missing tag identification protocol (OMTI) that efficiently identifies all missing tags even with the presence of unexpected tags. The key of OMTI is that we dynamically assign each tag an exclusive slot rather than use random hashes in traditional design. Namely, OMTI off-line serializes all known tags in advance by assigning each of them a unique and continuous slot, on-line identifies missing tags by checking tags’ responses in each slot, and dynamically updates the slot assignment to ensure the high efficiency of the next execution. Besides, we enhance OMTI to make it embrace newly added tags and spread to the multi-reader case from the single one. The simulation results demonstrate that OMTI can significantly reduce the identification time compared to the state-of-the-art.

In this paper, a nondominated sorting genetic algorithm (NSGA)-II-based calibration algorithm for the underwater binocular vision measurement system is proposed. The underwater measurement results will be incorrect with the binocular camera model in air. To deal with this problem, a refractive camera model and an akin triangulation are proposed to establish the nonlinear relationship with housing parameters between the object and its corresponding image plain points. A novel usage of checkerboard based on the relative position relationship of corners is employed to set three optimal goals, i.e., the distance difference, the vertical direction difference, and the parallel direction difference. The process of calibration is regarded as a multiobjective optimization and solved by NSGA-II. Finally, experimental results demonstrate the validity and effectiveness of the proposed calibration algorithm.

Anatase titania anchored graphene oxide (TGO) and sodium ligninsulfonate (SLS) were introduced into the chitosan (CS) proton exchange membrane (PEM) by solution casting to improve its mechanical st...

The dissolution behavior of a rare-earth element in H2SO4-H3PO4-H3PW12O40 solution has been investigated. The results showed that La2(SO4)3 dissolution increased with increasing H3PO4 or H3PW12O40 concentration in single H3PO4 or H3PW12O40 solution. The presence of H3PW12O40 can improve La2(SO4)3 dissolution owing to its coordination toward La3+ in H3PO4-H3PW12O40 mixed solution. However, La2(SO4)3 dissolution decreased gradually with increasing H2SO4 concentration in H2SO4-H3PW12O40 mixed solution. In these solutions, increasing the temperature showed an adverse effect on La2(SO4)3 dissolution. In H2SO4-H3PO4-H3PW12O40 solution, when the concentration of H2SO4 or/and H3PO4 was lower, increasing the H3PO4 concentration or decreasing the temperature was beneficial to La2(SO4)3 dissolution. However, when H2SO4 or H3PO4 reached a certain concentration, some H3PW12O40 precipitated from the mixed solution. Furthermore, increasing the H3PO4 concentration was found to be harmful, while increasing the temperature could increase La2(SO4)3 dissolution. Nevertheless, increasing the H2SO4 concentration showed an adverse effect on La2(SO4)3 dissolution regardless of the H3PO4 concentration.

With the increased use of natural gas, it is valuable to study energy recovery ratio in the natural gas pressure reduction stations (PRSs). This paper focused on recovering the energy in PRSs as well as low-grade waste heat by a coupled power generation system (CPGS). The CPGS integrates a natural gas expansion (NGE) subsystem and an organic Rankine cycle (ORC) subsystem driven by low-temperature waste heat. Firstly, a comparative analysis is carried out between the separated natural gas expansion system and the separated ORC system. Then, the effects of heat source conditions, upstream pressure of natural gas and the isentropic efficiency of the natural gas expander are investigated. At last, working fluids selection is conducted with respect to two different pressure ranges of natural gas. The results show that there is an optimal temperature and mass flow rate of the heat source that maximizes the system exergy efficiency. With the increase of the upstream pressure of natural gas, the net power output and waste heat recovery factor increase while the system exergy efficiency has an optimal point. Furthermore, the isentropic efficiency of the natural gas expander has a great influence on the net power output of the system.

The cofiring process of Au paste containing various amount of glass additive with different properties and CaO–B2O3–SiO2 (CBS) green tapes was investigated. The initial shrinkage temperature of Au paste was strongly associated with the softening point and the content of glass additive. The swell of sample and its mechanism during cofiring process was reported. The sheet resistivity of Au electrode was greatly depended on the content of CBS glass additive. When the content of CBS glass additive with the softening point of 704 °C was 3 wt %, the Au electrode exhibited the highest conductivity with the sheet resistivity of 2.4 mΩ/sq. The results obtained in this paper revealed the relationship between the glass additive and cofiring defects of Au electrode in the metal/ceramic multilayer structure, which gave an avenue to manufacture Low temperature co-fired ceramics (LTCC) modules with good quality.

In this paper, we propose a lightweight system, RDS-SLAM, based on ORB-SLAM2, which can accurately estimate poses and build semantic maps at object level for dynamic scenarios in real time using only one commonly used Intel Core i7 CPU. In RDS-SLAM, three major improvements, as well as major architectural modifications, are proposed to overcome the limitations of ORB-SLAM2. Firstly, it adopts a lightweight object detection neural network in key frames. Secondly, an efficient tracking and prediction mechanism is embedded into the system to remove the feature points belonging to movable objects in all incoming frames. Thirdly, a semantic octree map is built by probabilistic fusion of detection and tracking results, which enables a robot to maintain a semantic description at object level for potential interactions in dynamic scenarios. We evaluate RDS-SLAM in TUM RGB-D dataset, and experimental results show that RDS-SLAM can run with 30.3 ms per frame in dynamic scenarios using only an Intel Core i7 CPU, and achieves comparable accuracy compared with the state-of-the-art SLAM systems which heavily rely on both Intel Core i7 CPUs and powerful GPUs.

Variations of lake area and shoreline can indicate hydrological and climatic changes effectively. Accordingly, how to automatically and simultaneously extract lake area and shoreline from remote sensing images attracts our attention. In this paper, we formulate lake area and shoreline extraction as a multitask learning problem. Different from existing models that take the deep and complex network architecture as the backbone to extract feature maps, we present LaeNet—a novel end-to-end lightweight multitask fully CNN with no-downsampling to automatically extract lake area and shoreline from remote sensing images. Landsat-8 images over Selenco and the vicinity in the Tibetan Plateau are utilized to train and evaluate our model. Experimental results over the testing image patches achieve an Accuracy of 0.9962, Precision of 0.9912, Recall of 0.9982, F1-score of 0.9941, and mIoU of 0.9879, which align with the mainstream semantic segmentation models (UNet, DeepLabV3+, etc.) or even better. Especially, the running time of each epoch and the size of our model are only 6 s and 0.047 megabytes, which achieve a significant reduction compared to the other models. Finally, we conducted fieldwork to collect the in-situ shoreline position for one typical part of lake Selenco, in order to further evaluate the performance of our model. The validation indicates high accuracy in our results (DRMSE: 30.84 m, DMAE: 22.49 m, DSTD: 21.11 m), only about one pixel deviation for Landsat-8 images. LaeNet can be expanded potentially to the tasks of area segmentation and edge extraction in other application fields.

Temperature sensing plays a significant role in upholding quality assurance and meeting regulatory compliance in a wide variety of applications, such as fire safety and cold chain monitoring. However, existing temperature measurement devices are bulky, cost-prohibitive, or battery-powered, making item-level sensing and intelligence costly. In this paper, we present a novel tag-based thermometer called Thermotag, which uses a common passive RFID tag to sense the temperature with competitive advantages of being low-cost, battery-free, and robust to environmental conditions. The basic idea of Thermotag is that the resistance of a semiconductor diode in a tag's chip is temperature-sensitive. By measuring the discharging period through the reverse-polarized diode, we can estimate the temperature indirectly. We propose a standards-compliant measurement scheme of the discharging period by using a tag's volatile memory and build a mapping model between the discharging period and temperature for accurate and reliable temperature sensing. We implement Thermotag using a commercial off-the-shelf RFID system, with no need for any firmware or hardware modifications. Extensive experiments show that the temperature measurement has a large span ranging from 0 °C to 85 °C and a mean error of 2.7 °C.

An ultrasensitive strategy based on sandwich immunoassay coupled with isothermal exponential amplification reaction (IMEXPAR) is proposed for the determination of tumor protein Mucin 1 (MUC1). An immuno-PCR plate was prepared from modification of the primary MUC1-antibody (Ab1) onto the inner-well of the PCR plate. A biotinylated secondary MUC1-antibody tagged with the biotinylated EXPAR primer (P-Ab2) was prepared through biotin-streptavidin reaction. In the presence of target MUC1, sandwich-type combinations were specifically formed in the immuno-PCR plate. With further addition of amplification template, polymerase and nicking enzyme, EXPAR was specifically triggered, producing numerous primer replica in minutes, and greatly enhanced fluorescence of SYBR Green I. The proposed strategy has a good linear relationship with the logarithm of the MUC1 concentration ranging from 3 pM to 3 nM with a limit of detection of 1.63 pM (S/N = 3), which is two orders of magnitude lower than those of other methods. Owing to the specificity of immuno-reaction and EXPAR, the selectivity of the strategy is favorable, even if for the homologous protein. The proposed strategy was further applied for the MUC1 determination in human serum, and a satisfactory recovery range of 98.7%–105.3% was obtained. The strategy can be facilely extended to the ultrasensitive determination of various proteins.

The viscoelasticity of the crosslinked semiflexible polymer networks—such as the internal cytoskeleton and the extracellular matrix—that provide shape and mechanical resistance against deformation is assumed to dominate tissue mechanics. However, the mechanical responses of soft tissues and semiflexible polymer gels differ in many respects. Tissues stiffen in compression but not in extension1–5, whereas semiflexible polymer networks soften in compression and stiffen in extension6,7. In shear deformation, semiflexible polymer gels stiffen with increasing strain, but tissues do not1–8. Here we use multiple experimental systems and a theoretical model to show that a combination of nonlinear polymer network elasticity and particle (cell) inclusions is essential to mimic tissue mechanics that cannot be reproduced by either biopolymer networks or colloidal particle systems alone. Tissue rheology emerges from an interplay between strain-stiffening polymer networks and volume-conserving cells within them. Polymer networks that soften in compression but stiffen in extension can be converted to materials that stiffen in compression but not in extension by including within the network either cells or inert particles to restrict the relaxation modes of the fibrous networks that surround them. Particle inclusions also suppress stiffening in shear deformation; when the particle volume fraction is low, they have little effect on the elasticity of the polymer networks. However, as the particles become more closely packed, the material switches from compression softening to compression stiffening. The emergence of an elastic response in these composite materials has implications for how tissue stiffness is altered in disease and can lead to cellular dysfunction9–11. Additionally, the findings could be used in the design of biomaterials with physiologically relevant mechanical properties. Tissue rheology emerges from the interplay between fibrous networks and cell inclusions, and the mechanical properties of tissues are modulated by restricting the relaxation modes of fibres close to volume-conserving cells.

Selenium-substituted HA (Se/HA) particles with special micro/nanohybrid morphologies were prepared hydrothermally. With increasing Se substitution, Se/HA transitioned from a ribbon-like morphology, to a radical form, and further to microspheres (diameters: ∼10 μm) assembled from nanosheets (thickness: 2–5 μm; length and width: ∼100 nm). Chemical analyses confirmed increasing incorporation of Se in Se/HA particles, with increasing Se/(Se + P) molar ratio of the raw materials for their synthesis. Rat calvarial osteoblasts (RCOBs) adhered and spread on the Se/HA particles with Se/(Se + P) ratios ranging 0–0.05. Particles synthesized at Se/(Se + P) = 0.05 showed increased alkaline phosphatase activity of bone marrow mesenchymal stem cells, likely due to their micro/nano-sized surface morphology. Se released from particles effectively inhibited human osteosarcoma cell growth by inducing apoptosis. Therefore, Se/HA prepared at Se/(Se + P) = 0.05 presented a potential material for bone defect repair after surgical tumor removal, offering safety, increased osteogenic differentiation of stem cells, and inhibition of tumor cell growth. These results also suggest that trace element substitution is an effective approach to simultaneously imparting desirable microstructures and biological functions to bio-ceramics.

The effects of alkaline-earth oxides (SrO, CaO, MgO) on the densification and microwave properties of low-temperature fired BaO–Al2O3–SiO2 (BAS) glass–ceramic/Al2O3 composites have been investigated. By adding alkaline-earth oxides, the softening and crystallization behaviors of BAS-based glass–ceramics, which determine the densification of composites, are sequentially weakened in the order of BAS, SrO–BaO–Al2O3–SiO2 (SBAS), CaO–BaO–Al2O3–SiO2 (CBAS) and MgO–BaO–Al2O3–SiO2 (MBAS). It is also found in the above BAS-based glass–ceramics that the addition of alkaline-earth oxides plays a more profound role on crystallization behavior than on softening behavior, leading to the expansion of the interval between crystallization and softening temperatures (i.e., densification temperature range) to different degrees depending on the type of oxides added. As a result, the microstructures of oxides-modified glass–ceramic/Al2O3 composites (SBAS/Al2O3, CBAS/Al2O3, MBAS/Al2O3) are much denser than those of BAS/Al2O3. The properties of such composites are determined by the interplay among density of microstructure, amount and relative ratio of crystalline and residual glass phases related to the crystallization behavior and interfacial reaction. Detailed analyses suggest that CBAS/Al2O3 achieves optimal properties among all the four composites. Specifically, for CBAS/Al2O3 the dielectric constant, dielectric loss, bending strength and CTE value are 5.81 ± 0.12 (at ~ 10 GHz), (2.04 ± 0.12) × 10−3 (at ~ 10 GHz), 155 ± 7 MPa and 6.58 ± 0.11 ppm/°C, respectively. Our findings may provide a new avenue to design LTCC substrate materials as feasible candidates for microwave devices.

Low-softening-point La2O3-B2O3-CaO-P2O5 (LBCP) glass-ceramic/cordierite composite systems have been prepared in this work. Influence of the ratio of La2O3 to B2O3 and the content of cordierite on the sintering behavior, microstructure, sintering quality, thermal properties and dielectric properties of composites are studied. The results show that high La2O3/B2O3 ratio improves the crystalline quality of LBCP glass-ceramic, but also narrows its process window. The increase of cordierite content reduces the coefficient of thermal expansion (CTE) value of composites obviously. However, excess cordierite is detrimental to the densification of the composite microstructure, and too low cordierite content causes serious foaming. Sample containing 30 wt% LBCP1 glass-ceramic and 70 wt% cordierite sintered at 850 °C shows excellent properties: relative density of 95.26%, CTE value of 4.12 ppm/°C, dielectric constant of 4.78 (1 MHz)/4.52 (12.8 GHz), dielectric loss of 2.3 × 10−3 (1 MHz)/2.5 × 10−3 (12.8 GHz) and the ability to co-fire with silver, which suggests that LBCP glass/cordierite composite system has potential to meet the requirements of LTCC substrate material.

A novel method was proposed in this study to recycle WC and Co from cemented carbide scraps by remelting and electrodissolution. WC was recrystallized and purified through melting process. The WC that embedded in alloy was independent of each other and thus was easily separated by electrodissolution. The effects of dissolving parameters were investigated, and the results indicated that the maximum dissolving rate was 0.045 g·h−1·cm−2 and the anodic passivation was not found even at 500 A·m−2 of current density. In addition, the temperature and concentration of HCl were irrelevant to the rate and the current efficiency of the electrolysis. The SEM showed that the final WC powder was 5–20 μm in particle size with a regular shape, and the Co was directly recycled from the cathode at the same time.

A novel method is proposed in this study to synthesize coarse-grained tungsten carbide (WC) directly from scheelite/wolframite concentrates. The synthetic process was divided into two parts, carburization and crystallization. WC was enriched in iron melt with the increase of temperature and further purified by crystallizing during the cooling process. The thermodynamics calculation for the reduction process and phase diagram analysis for crystallization were investigated. The scanning microscope (SEM) showed that the obtained sample was on the millimeter scale with a tri-prism shape, and all peaks detected by x-ray diffraction matched well with the WC structure. This method will shorten the WC preparation process greatly, and the obtained coarse-crystalline WC may have potential application in conventional cemented carbide, especially for mining and construction tools.

The issues in charging guiding for electric vehicles are meaningful studies in recent years, especially for electric taxis which need to be recharged during working hours. However, with the popularity of taxi-booking apps, how to obtain an effective charging guiding for taxis having advance orders becomes an urgent problem to be solved. To optimize various special interests while satisfying the constraints of online advance orders, a charging guiding strategy based on consortium blockchain is proposed in this paper. Firstly, a taxi charging guiding architecture based on consortium blockchain is designed, and an improved practical byzantine fault tolerance algorithm is proposed to solve the problem of charging information disconnection and trust between multiple charging station operators. Secondly, we establish the charging guiding model for electric taxis based on multi-objective optimization. The model aims to meet the constraints of online advance orders, maximize passengers' satisfaction and operators' service efficiency, and minimize the charging costs of taxis. Finally, the optimization model is solved by quantum-behaved particle swarm optimization. In order to verify the effectiveness of the proposed guiding strategy, main urban areas of a city are taken as examples for simulation. The results show that the proposed strategy has increased the passengers' satisfaction by 0.44%, and has decreased the expense cost, the time cost and distance cost by 2.38%, 5.72%, and 17.25% respectively, comparing with PSO based strategy while balancing the utilization of charging equipment.

The Mo/Pt/Ag laminated metal matrix composites (LMMCs) have been used as interconnected materials of solar cell array of spacecraft at low-Earth orbit (LEO), where the interconnectors are vulnerable to the combined effects of atomic oxygen (AO) and thermal cycles. To enhance its resistance to LEO environment, the metallurgical bonding Mo/Pt/Ag LMMCs was prepared in this work with optimized processing parameters. During the process, the multiple calenderings and annealing at a protecting atmosphere were performed to improve the surface activity of Mo and Pt. Consequently, the expectant metallurgical bonding interfaces of Mo/Pt and Pt/Ag were successfully constructed through the atomic diffusion accelerated by the improvement of surface activity. Additionally, the resulting microstructure of the Mo/Pt interface was confirmed to be composed of MoPt and Mo3Pt alloy phases, and the Pt/Ag interface consisted of distorted and tangled Pt and Ag lattices. Besides, the interfacial type and the orientation relationships of constituent phases were determined. Lastly, the as-obtained Mo/Pt/Ag LMMCs is assessed to have good resistance to thermal fatigue and AO erosion by the thermal cycling and AO exposure experiments.

The invention discloses a globally coordinated distributed predictive control algorithm based on a system decomposition index. The algorithm comprises the steps of (S101) performing AP-CCA-based system decomposition according to system input and output data, obtaining a corresponding decomposition index Iij, and establishing a predictive model for each subsystem by using a least squares modeling method, (S102) allowing each subsystem to establish an optimal control problem by using the information of each subsystem and an associated subsystem, wherein the different influences of the associatedsubsystem on the system are expressed by a correlation coefficient between subsystems, (S103) obtaining input variables of the subsystem and the associated subsystem at a previous time from a globalinput variable set for each subsystem at a control time k, solving an optimization problem in (S102), and obtaining an optimal control law Delta ui, M(k) of each subsystem, (S104) weighting and calculating the actual application amount of each control variable by using Delta ui, M(k) in (S103) and Iij in (S101) and acting on a controlled object, and (S105) continuing the time to a time k+1, returning to (S103), and repeating the above process. According to the invention, the control is finer, and the effect is better.

As a novel computing technology closer to business ends, edge computing has become an effective solution for delay sensitive business of power Internet of Things (IoT) and promotes the application and development of the IoT technology in smart grids. However, the inherent characteristics of a single edge node with limited resources may fail to meet the delay requirements for access ubiquitous IoT businesses of massive access. Multiple edge nodes are needed to cooperate with each other to optimize workload allocation to provide lower delay services. To this end, this paper proposes a workload allocation mechanism, orienting edge computing-based power IoT, which minimizes service delay. The workload optimization allocation model is established, and the optimal workload allocation oriented on delay among multiple edge nodes is further realized on the basis of computing resource optimization within the single edge node. The balanced initialization, resource allocation, and task allocation (BRT) algorithm are proposed. Based on the balanced initialization of workload within edge nodes, the particle swarm algorithm modified by the pheromone strategy is used to solve the problem of the computing resources’ allocation inside edge nodes. Finally, the task allocation among multiple edge servers is converted into a semi-definite programming problem. The simulation results show that the proposed BRT algorithm reduces the service delay by 9.1%, 16.9%, and 26.4%, and the service delay growth rate by 24.6%, 34.5%, and 38.7%, respectively, compared with the simulated annealing algorithm (SAA), LoAd Balancing (LAB), and Latency-awarE workloAd offloaDing (LEAD) algorithms.

Alkaline-lacustrine deposition and its evolution model in Permian Fengcheng Formation at the Mahu sag, Junggar Basin were investigated through core and thin-section observation, geochemical and elemental analysis, logging response and lithofacies identification. Six lithofacies are developed in the Fengcheng Formation. The Feng 2 Member (P1f2) is dominated by lithofacies with alkaline minerals, while the upper part of the Feng 1 Member (P1f1) and the lower part of the Feng 3 Member (P1f3) are primarily organic-rich mudstones that are interbedded with dolomite and dolomitic rock. Paleoenvironment evolution of Fengcheng Formation can be divided into 5 stages, which was controlled by volcanic activity and paleoclimate. The first stage (the early phase of P1f1) was characterized by intensive volcanic activity and arid climate, developing pyroclastics and sedimentary volcaniclastic rocks. The secondary stage (the later phase of P1f1) had weak volcanic activity and humid climate that contributed to the development of organic-rich mudstone, forming primary source rock in the Fengcheng Formation. The increasing arid climate at the third stage (the early phase of P1f2) resulted in shrinking of lake basin and increasing of salinity, giving rise to dolomite and dolomitic rocks. The continuous aird climate, low lake level and high salinity at the fourth stage (the later phase of P1f2) generated special alkaline minerals, e.g., trona, indicating the formation of alkaline-lacustrine. The humid climate made lake level rise and desalted lake water, therefore, the fifth stage (P1f3) dominated by the deposition of terrigenous clastic rocks and dolomitic rocks. Key words: Junggar Basin, Permian Fengcheng Formation, depositional characteristics, paleoenvironment reconstruction, alkaline-lacustrine deposition, lithofacies, Mahu sag

In this paper, we investigate BER performances of hybrid carrier (HC) framework based on weighted-type fractional Fourier transform (WFRFT) precoding with transmitter (TX) in-phase/quadrature (IQ) imbalance. Orthogonal frequency division multiplexing (OFDM) and single carrier (SC) systems with IQ imbalance are unified in proposed HC framework. Considering IQ imbalance as interference, the signal-to-interference-plus-noise ratio (SINR) of HC scheme is calculated, and then theoretical BER expressions over fading channels with zero forcing (ZF) and minimum mean square error (MMSE) equalizers are derived. Since a performance gain is involved in SC scheme with IQ imbalance interference, SC BER is theoretically given as a special case. Furthermore, we also put forward an IQ imbalance compensation method for HC framework through removing IQ imbalance interference at the cost of enlarged noise. The postcompensation noise of HC scheme is calculated and used to derive analytical BER expressions. The compensation performances of HC with ZF and MMSE receivers are verified through theoretical and simulated results.

Plasmonic nanofluids show great interests for light-matter applications due to the tunable optical properties. By tuning the nanoparticle (NP) parameters (material, shape, and size) or base fluid, plasmonic nanofluids can either absorb or transmit the specific solar spectrum and thus making nanofluids ideal candidates for various solar applications, such as: full spectrum absorption in direct solar absorption collectors, selective absorption or transmittance in solar photovoltaic/thermal (PV/T) systems, and local heating in the solar evaporation or nanobubble generation. In this chapter, we first summarized the preparation methods of plasmonic nanofluids, including the NP preparation based on the top-down and bottom-up, and the nanofluid preparation based on one-step and two-step. And then solar absorption performance of plasmonic nanofluids based on the theoretical and experimental design were discussed to broaden the absorption spectrum of plasmonic nanofluids. At last, solar thermal applications and challenges, including the applications of direct solar absorption collectors, solar PT/V systems, solar distillation, were introduced to promote the development of plasmon nanofluids.

Passive daytime radiative cooling (PDRC) has drawn significant attention recently for electricity-free cooling. Porous polymers are attractive for PDRC since they have excellent performance and scalability. A fundamental question remaining is how PDRC performance depends on pore properties (e.g., radius, porosity), which is critical to guiding future structure designs. In this work, optical simulations are carried out to answer this question, and effects of pore size, porosity, and thickness are studied. We find that mixed nanopores (e.g., radii of 100 and 200 nm) have a much higher solar reflectance Rsolar (0.951) than the single-sized pores (0.811) at a thickness of 300 μm. With an Al substrate underneath, Rsolar, thermal emittance eLWIR, and net cooling power Pcool reach 0.980, 0.984, and 72 W/m2, respectively, under a semihumid atmospheric condition. These simulation results provide a guide for designing high-performance porous coating for PDRC applications.

The cost of dedicated sensors has hampered the collection of the high-quality seismic response data required for real-time health monitoring and damage assessment. The emergence of crowdsensing technology, where a large number of mobile devices collectively share data and extract information of common interest, may help remove such obstacles and mitigate the seismic hazard. The present study proposes a crowdsensing-oriented vibration acquisition and identification method based on time–frequency characteristics and deep transfer learning. It can distinguish the responses during an earthquake event from vibration under serviceability conditions. The core classification process is performed using a combination of wavelet transforms and deep transfer networks. The latter were pre-trained using finite element models calibrated with the monitored seismic responses of the structures. The validation study confirmed the superior identification accuracy of the proposed method.

Based on the time-sharing price and the technology of interaction between power grid and electric vehicle, the V2G model of electric vehicle is established. Taking the minimum user cost and load fluctuation as the objective function, the charging and discharging model of electric vehicles, wind power generation, photovoltaic power generation and thermal power generation systems are constructed. When solving the optimal solution of the model, genetic algorithm is used. After the optimal solution is obtained, the optimization model can make use of the random residual power, reduce the abandoned air volume and light volume, and achieve the purpose of restraining the load fluctuation and reducing the user cost.

Grasping is one of the main approaches for robots to move and manipulation objects. Recently, more and more deep neural networks which need a large amount of data are applied to machine learning. However, the number of images in the real scene is far less than the number of images in the datasets commonly used in deep learning. And there is a certain difference between the simulation data and real data. So there will be a phenomenon of domain migration, which will lead to a decline in network performance. In order to make the network more efficient and extract more accurate features, we design and implement the algorithm combining MMD oriented anchor frame mechanism to capture and detect the grasp location. Different from prior research has directly reducing the MMD distance between source domain and target domain , we between source domain and target domain to produce a Gaussian distribution as the middle distribution to reduce the gap between simulation data and real data. After experimental verification, the accuracy of our algorithm on the simulation dataset and real dataset reached 90.10% and 90.96% respectively.

Cells can respond to signals generated by other cells that are remarkably far away. Studies from at least the 1920's showed that cells move toward each other when the distance between them is on the order of a millimeter, which is many times the cell diameter. Chemical signals generated by molecules diffusing from the cell surface would move too slowly and dissipate too fast to account for these effects, suggesting that they might be physical rather than biochemical. The non-linear elastic responses of sparsely connected networks of stiff or semiflexible filament such as those that form the extracellular matrix (ECM) and the cytoskeleton have unusual properties that suggest multiple mechanisms for long-range signaling in biological tissues. These include not only direct force transmission, but also highly non-uniform local deformations, and force-generated changes in fiber alignment and density. Defining how fibrous networks respond to cell-generated forces can help design new methods to characterize abnormal tissues and can guide development of improved biomimetic materials.

RFID is becoming ubiquitously available in our daily life. After RFID tags are deployed to make attached objects identifiable, a natural next step is to communicate with the tags and collect their information for the purpose of tracking tagged objects or monitoring their surroundings in real time. In this paper, we study an under-investigated problem range detection in a commodity RFID system, which aims to check if there are any tags with the data between an upper and lower boundary in a time-efficient way. This is important especially in a large RFID system, which can help users quickly pinpoint the target tags (if any) and give an early warning to users for taking urgent actions and reducing the potential risk in the nascent stage. We propose two tailored protocols, selective query and range query (RQ), to achieve range detection within the scope of the C1G2 standard. The novelty is that, instead of querying each tag, we exploit the capability of C1G2-compatible selection and quickly separate target tags from others by silencing most of tags. The final result is that our best protocol RQ is able to achieve a range detection with only one query command. We implement the proposed protocols in commodity RFID systems, without any modifications of hardware. Extensive experiments show that RQ is able to improve the time efficiency by near 30×, compared with the baseline.

Temperature sensor is one of the most widespread technologies in the IoT era. Wireless temperature monitoring systems are convenient to deploy and can drive mass applications in the fields of smart home, transportation and logistics. Currently, wireless temperature monitoring products are based on microelectronic and semiconductor components, which are not cost-effective (e.g., a few dollars) and more importantly, generate electronic wastes. In this work, we present ThermoWave, a new paradigm of wireless temperature monitoring that is ecological, battery-less, and ultra-low cost. Specifically, ThermoWave is on the basis of the thermal scattering effect on millimeter-wave (mmWave) signals. Specifically, cholesteryl materials align their molecular patterns at different environmental temperatures, and this temperature-induced pattern change will be modulated and sensed by the scattered mmWave signals. There are three functional modules in the ThermoWave system. The ThermoTag is a cholesteryl material inked film or paper tag that can be conveniently attached to the object of interest to monitor temperature changes. Each ThermoTag costs less than 0.01 dollars. The temperature modulated mmWave scattering will be received by a mmWave-radar based ThermoScanner and demodulated by a software-based temperature decoder ThermoSense, which includes a model-based method (i.e., ThermoDot) for point temperature estimation and a data-driven method (i.e., ThermoNet) for thermal imaging. We prototype and evaluate the ThermoWave system performance in both controlled and real-world setups. Experimental results show that the ThermoWave achieves the precision of ±1.0°F in the range of 30°F to 120°F in a controlled setup. We also investigate the performance in real-world applications, and the ThermoWave can reach the ±3.0°F precision in the temperature estimation. We also test and discuss sustainability, durability, robustness, and cost-effectiveness of the ThermoWave in both design and experiments.

Zoledronic acid (ZA) is a bisphosphonate (BP) drug that has been widely used in clinical treatments as a potent bone resorption inhibitor. In recent years, an increasing number of cases of bisphosphonate-associated osteonecrosis of the jaw (BRONJ) have been reported. This is a severe maxillofacial complication characterized clinically by bone exposure, necrosis, pain, and halitosis. Its pathogenesis is still not clear, and there is no effective clinical treatment known. Therefore, prevention of BRONJ is especially important. To provide a new research direction for the treatment of BRONJ, this study used a new tetrahedral framework nucleic acid (TFNA), which can antagonize the inhibitory effect of ZA on the differentiation and maturation of osteoclasts (OCs). In vivo and in vitro experiments showed that TFNAs at a specific concentration exhibited no cytotoxicity and could reverse the inhibition of ZA on OC differentiation and maturation, effectively inhibiting the formation of BRONJ.

Learning an optimal policy for autonomous driving task to confront with complex environment is a long- studied challenge. Imitative reinforcement learning is accepted as a promising approach to learn a robust driving policy through expert demonstrations and interactions with environments. However, this model utilizes non-smooth rewards, which have a negative impact on matching between navigation commands and trajectory (state-action pairs), and degrade the generalizability of an agent. Smooth rewards are crucial to discriminate actions generated from sub-optimal policy. In this paper, we propose a navigation command matching (NCM) model to address this issue. There are two key components in NCM, 1) a matching measurer produces smooth navigation rewards that measure matching between navigation commands and trajectory; 2) attention-guided agent performs actions given states where salient regions in RGB images (i.e. roadsides, lane markings and dynamic obstacles) are highlighted to amplify their influence on the final model. We obtain navigation rewards and store transitions to replay buffer after an episode, so NCM is able to discriminate actions generated from suboptimal policy. Experiments on CARLA driving benchmark show our proposed NCM outperforms previous state-of-the- art models on various tasks in terms of the percentage of successfully completed episodes. Moreover, our model improves generalizability of the agent and obtains good performance even in unseen scenarios.

The fundamental problem of Zero-Shot Learning (ZSL) is that the one-hot label space is discrete, which leads to a complete loss of the relationships between seen and unseen classes. Conventional approaches rely on using semantic auxiliary information, e.g. attributes, to re-encode each class so as to preserve the inter-class associations. However, existing learning algorithms only focus on unifying visual and semantic spaces without jointly considering the label space. More importantly, because the final classification is conducted in the label space through a compatibility function, the gap between attribute and label spaces leads to significant performance degradation. Therefore, this paper proposes a novel pathway that uses the label space to jointly reconcile visual and semantic spaces directly, which is named Attributing Label Space (ALS). In the training phase, one-hot labels of seen classes are directly used as prototypes in a common space, where both images and attributes are mapped. Since mappings can be optimized independently, the computational complexity is extremely low. In addition, the correlation between semantic attributes has less influence on visual embedding training because features are mapped into labels instead of attributes. In the testing phase, the discrete condition of label space is removed, and priori one-hot labels are used to denote seen classes and further compose labels of unseen classes. Therefore, the label space is very discriminative for the Generalized ZSL (GZSL), which is more reasonable and challenging for real-world applications. Extensive experiments on five benchmarks manifest improved performance over all of compared state-of-the-art methods.

Antimicrobial peptides (AMPs) have been an attractive alternative to traditional antibiotics. However, considerable efforts are needed to further enhance their antimicrobial effects and stability against bacterial degradation. Tetrahedral framework nucleic acids (tFNAs), a new class of three-dimensional nanostructures, have been utilized as a delivery vehicle. In this study, tFNAs were combined for the first time with an antimicrobial peptide GL13K, and the effects of the resultant complexes against Escherichia coli (sensitive to GL13K) and Porphyromonas gingivalis (capable of degrading GL13K) were investigated. tFNA-based delivery enhanced the effects of GL13K against E. coli. The tFNA vehicle both increased bacterial uptake and promoted membrane destabilization. Moreover, it enhanced the effects of GL13K against P. gingivalis by protecting the peptide against degradation in the protease-rich extracellular environment. Therefore, tFNA provides a delivery vehicle for AMPs targeting a broad range of disease.