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The Hefei Advanced Light Facility (HALF) is a fourth-generation vacuum ultraviolet and x-ray diffraction limit synchrotron radiation (DLSR) light source now under preliminary research. To achieve ultralow beam emittance and small beam size, the orbit of the beam in the DLSR storage ring should meet the stability requirement at submicrometer scale. The beam position monitor (BPM) electronics measures the orbit and is hence an essential part of the beam orbit control system. In this article, we design a BPM electronics based on the MicroTCA.4 (Micro Telecom Computing Architecture) standards platform, which consists of a MicroTCA.4 module (including a chassis, a power supply, and a digital board), a customized RF front end module, and a frequency synthesizer. In-phase and quadrature sampling and digital signal processing algorithms are implemented to obtain turn-by-turn data, fast acquisition data at a 10 kHz rate, and slow acquisition data at a 10 Hz rate. To evaluate the performance and function of BPM electronics, we conducted offline tests in the laboratory and beam tests based on the storage ring of Hefei Light Source II (HLS II), a light source similar to the HALF as an alternative. Test results indicate that the performance of MicroTCA.4-based BPM electronics can meet the requirements of the HALF storage ring.

The mechanical properties of poly(arylene sulfide sulfone) (PASS) electrospun membrane were significantly enhanced by co-electrospinning with semi-aromatic nylon poly(m-xylene adipamide) (MXD6), another engineering plastic with high thermal stability and good mechanical properties. The tensile strength of PASS membrane increased with increased incorporation of MXD6, and was tripled when 20% MXD6 was incorporated. The mechanism of the mechanical property improvement is the existence of hydrogen bonding interaction between PASS and MXD6 and between adjacent fibers at the intersections. Thermal properties of the PASS/MXD6 membranes were evaluated by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA), which showed that the membranes could be stably utilized up to 180 °C without any change in appearance and without decomposition. Contact angle measurements of all the membranes showed hydrophobic character. To demonstrate the potential applications of PASS/MXD6 blend membranes, their oil absorption capacities were evaluated with three oils of different viscosities, which proved that the PASS/MXD6 membranes are better absorbents than commercial non-woven polypropylene fibers. Therefore, PASS/MXD6 fibrous membranes produced by electrospinning have a great potential in practical applications.

The manipulation of nanobuilding blocks into a 3D macroscopic monolith with ordered hierarchical structures has been much desired for broad and large-scale practical applications of nanoarchitectures. In this paper, we demonstrate a fully bottom-up strategy for the preparation of aramid aerogel monoliths. The process starts from the synthesis of poly(p-phenylene terephthalamide) (PPTA) through the polycondensation of p-phenylenediamine and terephthaloyl chloride, with the assistance of a nonreactive dispersing agent (polyethylene glycol dimethyl ether), which helps the dispersal of the as-synthesized PPTA in an aqueous medium for the formation of p-aramid nanofibers (ANF). Then the vacuum-assisted self-assembly (Vas) technique is skillfully connected with the ice-templated directional solidification (I) technique, and the combined VasI method successfully tailors the self-assembly of ANF to transform the 1D nanofibers into a 3D aerogel monolith with a specific long-range aligned, lasagna-like, multilaminated internal structure. The study of the aerogel microstructure revealed the dependence of the lamina orientation on the direction of the freezing front of ice crystals. This direction should be parallel to the deposition plane of the Vas process if a long-range aligned lamellar structure is desired. The anisotropy of the multilaminated aerogel was proven by the different results in the radial and axial directions in the compression and thermal conductivity tests. As a kind of organic aerogel, the ANF monolith has typical low density, high porosity, and low thermal conductivity. Additionally, the ANF monolith exhibits high compressive stress and excellent thermal stability. Considering its high performance and facile preparation process, potential applications of the ANF aerogel monolith can be expected.

Aerogel has been widely known as a low-density and highly porous material and is closely connected with the complex processing methods, such as freeze-drying or supercritical drying. In this work, using the polymerization-induced aramid nanofiber (PANF) as a building block, we put forward a modified freezing-drying method for the high-efficiency preparation of all-para-aromatic-amide aerogels. In the preparation process, PANF hydrogel is first frozen at -18 °C and then dried at 20-150 °C for the formation of PANF aerogel. The PANF framework formed during the freezing process is crucial for the formation of the PANF aerogel. Moreover, the space-occupying effect of ice crystals is also helpful for the formation of the macroscopic pore structure in the aerogel. Aerogels with large size or well-controlled shape could be successfully obtained by this method. Through the variation of PANF concentration in the hydrogel and drying temperature, aerogels with different densities (20-185 mg/cm3) could be achieved, and the lowest density is reached at 150 °C, with the PANF concentration of 0.7%. The low-density PANF aerogels show high specific compressive strengths and low thermal conductivities, which are comparable to those resulting from the freeze-drying or supercritical drying method. Furthermore, the shrinkage phenomenon in the drying process could be skillfully utilized for the preparation of PANF aerogel-coated objects. The PANF aerogels could be applied as a thermal insulating material or shock absorption material in practical applications.

Knowledge graphs are usually constructed to describe the various concepts that exist in real world as well as the relationships between them. There are many knowledge graphs in specific fields, but they usually pay more attention on text or structured data, ignoring the image vision information, and cannot play an adequate role in the emerging visualization applications. Aiming at this issue, we design a method that integrates image vision information and text information derived from Wikimedia Commons to construct a domain-specific multi-modal knowledge graph, taking the metallic materials domain as an example to illustrate the method. The text description of each image is regarded as its context semantic to acquire the image's context semantic labels based on the DBpedia resource. Furthermore, we adopt deep neural network model instead of simple visual descriptors to acquire the image's visual semantic labels using the concepts from WordNet. In order to fuse the visual semantic labels and context semantic labels, a path-based concept extension and fusion strategy is proposed based on the conceptual hierarchies of WordNet and DBpedia to obtain the effective extension concepts as well as the links between them, increasing the scale of the knowledge graph and enhancing the correlation between images. The experimental results show that the maximum extension level has a significant impact on the quality of the generated domain knowledge graph, and the best extension level number is respectively determined for both DBpedia and WordNet. In addition, the results of this paper are compared with IMGpedia to further show the effectiveness of the proposed method.

The direct synthesis of polymer microspheres modified by aramid nanofibers (ANFs) is an interesting challenge. This work describes a simple aqueous process to prepare polystyrene (PS)/ANF composite microspheres, where the specific ANF network was "dressed" on PS. ANF was derived from the copolymerization of terephthaloyl chloride, p-phenylene diamine, and methoxypolyethylene glycol and could be dispersed in water stably. We applied the as-synthesized ANF as a Pickering emulsifier in the o/w emulsion of styrene monomer. Radical polymerization was subsequently initiated in the Pickering emulsion system. The combination of ANF with polymer spheres was revealed by scanning electron microscopy (SEM) and thermal gravity analysis. The role of ANF in the monomer emulsion as well as in the polymerization was studied through SEM, optical microscopy, optical stability analyzer, and pulse nuclear magnetic resonance combined with the polymerization kinetic analysis. Moreover, we investigated the effects of other synthesis parameters, such as monomer type, monomer content, pH value, and salt concentration.

The processing of poly(p-phenylene terephthalamide) (PPTA) has long been a great challenge. This work reports a simple "monomers-nanofibers-macroscopic product" (MNM) hierarchical self-assembly approach to build 3D all-PPTA engineering materials. This approach mainly includes the preparation of polymerization-induced aramid nanofibers (PANFs) from monomers and the fabrication of all-PPTA materials from PANF hydrogel. Various 3D architectures, including simple solid bulks and sophisticated honeycombs (HCs), are obtained after the dehydration and shrinking of the PANF hydrogel. The tensile strength and compressive yield strength of PANF bulk are more than 62 and 90 MPa, respectively, which are comparable to typical engineering plastics. The compressive strength of PANF HC with a density of 360 kg m-3 is more than 24 MPa. The thermal stability of PANF bulk and PANF HC are as good as that of Kevlar fiber and almost no decomposition occurred before 500 °C in a nitrogen atmosphere. Furthermore, the MNM process is performed under mild conditions, without high temperature, high pressure, or corrosive solvent. The MNM process is a novel strategy for the processing of all aromatic polyamide materials with complex structures and high performances and would be another development since the breakthrough of liquid crystal spinning technology of PPTA.

This paper proposes a vibration fault diagnosis method based on wavelet preprocessing and Local Mean Decomposition (LMD). In order to obtain time-frequency energy information accurately, flrstly, the original signal is transformed by wavelet. From the viewpoint of energy, using adaptive threshold for denoising, while most of the signal energy is reserved, the in∞uence of most noise is eliminated at the same time. Then, LMD is used to get the signal component which has deflnite physical sense and contains fault information. To identify the abnormal frequency components, the signal component is analyzed in time-frequency domain. Finally, the running state of hydro turbine can be diagnosed by analyzing the time-frequency information of each component signals. This method is applied in the No.1 hydro turbine of a power plant, the analysis shows that this method is efiective, and the running state of the turbine can be correct evaluated.