Zengmei Wang

Crystallization, phase evolution and ferroelectric properties of sol–gel-synthesized Ba(Ti0.8Zr0.2)O3–x(Ba0.7Ca0.3)TiO3 thin films

A lead-free piezoelectric material with ultra-high properties, Ba(Ti0.8Zr0.2)O3–x(Ba0.7Ca0.3)TiO3(BZT–xBCT) nanocrystals was synthesized via a sol–gel method, and the corresponding thin films were also deposited on Pt/Ti/SiO2/Si substrates by a spin-coating approach. The BZT–xBCT thin film exhibited a high remnant polarization of 22.15 μC cm−2 with a large coercive field of 68.06 kV cm−1. The resultant gel is calcined at various elevated temperatures and studied with FTIR/XRD/Raman/DSC-TGA/AFM/SEM techniques for gel composition, crystallization, phase transition, thermochemistry and the morphology of the film. Although the room temperature crystal structure of the BZT–xBCT nanocrystals appears to be a standard perovskite structure by conventional X-ray diffraction (XRD), Raman spectroscopy demonstrates the presence of non-centrosymmetric regions arising from the off-centering of the titanium (zirconium) atoms. The Raman spectra findings demonstrate the degree by which the tetragonal phase grows with the increase of calcining temperature in BZT–0.5BCT, and the characteristic ferroelectric–ferroelectric phase transition in BZT–xBCT while going through the MPB process. The structural and constituent evolution for the conversion process from gel to ceramic, as well as the formation mechanism of the BZT–0.5BCT crystallite, were also elucidated.

Fabrication of Li 4 Ti 5 O 12 -TiO 2 Nanosheets with Structural Defects as High-Rate and Long-Life Anodes for Lithium-Ion Batteries

Development of high-power lithium-ion batteries with high safety and durability has become a key challenge for practical applications of large-scale energy storage devices. Accordingly, we report here on a promising strategy to synthesize a high-rate and long-life Li4Ti5O12-TiO2 anode material. The novel material exhibits remarkable rate capability and long-term cycle stability. The specific capacities at 20 and 30 C (1 C = 175 mA g−1) reach 170.3 and 168.2 mA h g−1, respectively. Moreover, a capacity of up to 161.3 mA h g−1 is retained after 1000 cycles at 20 C, and the capacity retention ratio reaches up to 94.2%. The extraordinary rate performance of the Li4Ti5O12-TiO2 composite is attributed to the existence of oxygen vacancies and grain boundaries, significantly enhancing electrical conductivity and lithium insertion/extraction kinetics. Meanwhile, the pseudocapacitive effect is induced owing to the presence of abundant interfaces in the composite, which is beneficial to enhancing specific capacity and rate capability. Additionally, the ultrahigh capacity at low rates, greater than the theoretical value of spinel Li4Ti5O12, may be correlated to the lithium vacancies in 8a sites, increasing the extra docking sites of lithium ions.

Carbon-coated Li4Ti5O12–TiO2 microspheres as anode materials for lithium ion batteries

ABSTRACT While spinel Li4Ti5O12 has attracted great attention owing to its excellent cycling stability and safety as anode materials of lithium ion batteries, there is still a challenge to produce high-performance Li4Ti5O12 with a cost-effective and scalable process. Herein, we developed a facile one-pot strategy for scalable synthesis of carbon-coated Li4Ti5O12–TiO2 microspheres. The novel material not only delivered a high capacity of 162.5 mA h g−1 after 100 cycles at 0.5 C but also exhibited excellent rate capability and cycling stability. The capacity of up to 146.6 mA h g−1 was retained after 350 cycles at 5 C, and no obvious capacity reduction was found during cycles. The superior electrochemical performance can be attributed primarily to the uniform carbon layer outside and the high density of grain boundary in the compact microspheres, resulting in enhanced electrical conductivity and more channels for lithium ion insertion/extraction reaction.

High output power density nanogenerator based on lead-free 0.96(K0.48Na0.52)(Nb0.95Sb0.05)O3–0.04Bi0.5(Na0.82K0.18)0.5ZrO3 piezoelectric nanofibers

Piezoelectric nanogenerators that power micro/nano devices by converting surrounding tiny mechanical vibration into electrical energy and getting rid of batteries and power cables is attracting increasing attention in recent years. Piezoelectric nanocomposites combining the flexibility of polymers and piezoelectricity of nanostructures are the current research hot spot in this field. However, usually the piezoelectric constant (d33) of piezoelectric nanostructures cannot compete with those of ceramics, and that of lead-free nanostructures is even worse, leading to low output voltages and seriously restricting their applications. Here, we report a new piezoelectric nanocomposite based on 0.96(K0.48Na0.52)(Nb0.95Sb0.05)O3–0.04Bi0.5(Na0.82K0.18)0.5ZrO3 (KNNS–BNKZ) electrospun nanofibers with a ultrahigh d33 of 338 pm V−1 and significantly improved energy harvesting performance. Our KNNS–BNKZ nanofiber-based nanogenerator can generate an output voltage up to 10 V which is more than three times that of other reported lead-free piezoelectric nanocomposites. In addition, our nanogenerator can charge a capacitor up to 0.33 μF and 8 V in 45 seconds by hand-pressing after rectifying, showing its great potential in powering micro/nano electronic devices and sensors.

An investigation into the dynamic indentation response of metallic materials

The dynamic indentation response of several ductile metallic materials [Al(111), polycrystalline copper, Fe, and Ti6Al4V] has been investigated using a pendulum-based nano-impact test. The impact process involves repetitive contact cycles until finally coming to rest in the material. Each cycle includes four phases: acceleration, indentation, rebound, and deceleration. The dynamic indentation resistance of the metallic materials scales with their hardness determined under quasi-static conditions. However, through a one-dimensional analytical model, it has been shown that the relationship between the dynamic resistance and the depth during indentation cannot be adequately described using the quadratic relationship commonly found under quasi-static conditions. A power law relationship with a reduced index was proposed and it is found the index is around 1 when the quasi-static and dynamic compliance are similar. A linear relationship between impact resistance and depth has been found during rebound, where the released elastic energy is much higher than that produced by quasi-static nanoindentation.

Effects of TiO2 content on the microstructure, mechanical properties and photocatalytic activity of three dimensional TiO2–Graphene composite prepared by hydrothermal reaction

A series of three dimensional (3D) porous TiO2–graphene (TGR) hydrogel samples with different mass ratio of graphene to TiO2 were obtained using a one-step hydrothermal method. Their microstructure, mechanical properties, and photocatalytic activity were investigated. The TGR samples exhibited well defined interconnected 3D porous network microstructure and good mechanical strength. Moreover, the pore size and the compressive strength could be easily adjusted by changing the content of TiO2, showing a decreasing tendency with the increase of the relative content of TiO2. The results of the photodegradation of methylene blue indicated that the photocatalytic activity of the TGR samples can be significantly enhanced, compared to the pure TiO2 nanoparticles. The TGR sample also showed good durability and reusability. The mechanisms resulting in the improvement of photocatalytic activity were investigated with DRS, PL spectra, and adsorption experiment under dark conditions. It was found that adsorption is the dominant factor for the enhanced photocatalytic activity.

High-performance Cu nanoparticles/three-dimensional graphene/Ni foam hybrid for catalytic and sensing applications

A novel hybrid of Cu nanoparticles/three-dimensional graphene/Ni foam (Cu NPs/3DGr/NiF) was prepared by chemical vapor deposition, followed by a galvanic displacement reaction in Ni- and Cu-ion-containing salt solution through a one-step reaction. The as-prepared Cu NPs/3DGr/NiF hybrid is uniform, stable, recyclable and exhibits an extraordinarily high catalytic efficiency for the reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP) with a reduction rate constant K = 0.056 15 s-1, required time ∼30 s and excellent sensing properties for the non-enzymatic amperometric hydrogen peroxide (H2O2) with a linear range ∼50 μM-9.65 mM, response time ∼3 s, detection limit ∼1 μM. The results indicate that the as-prepared Cu NPs/3DGr/NiF hybrid can be used to replace expensive noble metals in catalysis and sensing applications.

Electrochemical performances of Mg45M5Co50 (M=Pd, Zr) ternary hydrogen storage electrodes

Abstract In order to improve the discharge capacity and cyclic life of Mg–Co-based alloy, ternary Mg 45 M 5 Co 50 (M=Pd, Zr) alloys were synthesized via mechanical alloying. TEM analysis demonstrates that these alloys all possess body-centered cubic (BCC) phase in nano-crystalline. Electrochemical experiments show that Mg 45 Zr 5 Co 50 electrode exhibits the highest capacity (425 mA·h/g) among the Mg 45 M 5 Co 50 (M=Mg, Pd, Zr) alloys. And Mg 45 Pd 5 Co 50 electrode lifts not only the initial discharge capacity (379 mA·h/g), but also the discharge kinetics, e.g., exchange current density and hydrogen diffusion ability from that of Mg 50 Co 50 . It could be concluded that the electrochemical performances were enhanced by substituting Zr and Pd for Mg in Mg–Co-based alloy.

An efficient method based on machine learning for estimation of the wall parameters in through-the-wall imaging

ABSTRACT The estimation of the wall parameters is important in through-the-wall radar imaging (TWRI). Ambiguities in the wall characteristics, including wall thickness, permittivity, and conductivity, will distort the imaging and shift the target position. To obtain a quick and accurate estimation of wall parameters, an efficient method based on machine learning is proposed. The estimation problem is converted to a regression problem. A map between wall parameters and the received signals is established and is regressed as a linear formulation after machine learning; in this manner, the wall parameters can be estimated in few seconds. The measurement results demonstrate that the estimated approach has the advantages of high precision and low computational time. The influence of the size, the location, the number of the targets and the length of the wall, the sampling interval, and noise on the estimation problems is discussed, and the image entropy is given to verify the effectiveness of the estimation values. The results based on support vector machines and least-square support vector machines (LS-SVMs), which are both machine-learning approaches, are compared. The comparison results reveal that the LS-SVM-based method can provide comparable performances in terms of accuracy and convenience but poor performances in terms of generalization and robustness.