Mechanical Properties of Single-Layer Diamond Reinforced Poly(vinyl alcohol) Nanocomposites through Atomistic Simulation

Low-dimensional carbon nanostructures are ideal nanofillers to reinforce the mechanical performance of polymer nanocomposites due to their excellent mechanical properties. Through molecular dynamics simulations, the mechanical performance of poly(vinyl alchohol) (PVA) nanocomposites reinforced with a single-layer diamond – diamane is investigated. It is found the PVA/diamane exhibits similar interfacial strengths and pull-out characteristics with the PVA/bilayer-graphene counterpart. Specifically, when the nanofiller is fully embedded in the nanocomposite, it is unable to deform simultaneously with the PVA matrix due to the weak interfacial load transfer efficiency, thus the enhancement effect is not significant. In comparison, diamane can effectively promote the tensile properties of the nanocomposite when it has a laminated structure as it deforms simultaneously with the matrix. With this configuration, the interlayer sp³ bonds endows diamane with a much higher resistance under compression and shear tests, thus the nanocomposite can reach very high compressive and shear stress. Overall, enhancement on the mechanical interlocking at the interface as triggered by surface functionalization is only effective for the fully embedded nanofiller. This work provides a fundamental understanding of the mechanical properties of PVA nanocomposites reinforced by diamane, which can shed lights on the design and preparation of next generation high-performance nanocomposites.     

Hydrogen storage capacity and reversibility of Li-decorated B4CN3 monolayer revealed by first-principles calculations

This work explored the feasibility of Li decoration on the B₄CN₃ monolayer for hydrogen (H₂) storage performance using first-principles calculations. The results of density functional theory (DFT) calculations showed that each Li atom decorated on the B₄CN₃ monolayer can physically adsorb four H₂ molecules with an average adsorption energy of ?0.23 eV/H₂, and the corresponding theoretical gravimetric density could reach as high as 12.7 wt%. Moreover, the H₂ desorption behaviors of Li-decorated B₄CN₃ monolayer at temperatures of 100, 200, 300 and 400 K were simulated via molecular dynamics (MD) methods. The results showed that the structure was stable within the prescribed temperature range, and a large amount of H₂ could be released at 300 K, indicative of the reversibility of hydrogen storage. The above findings demonstrate that the Li-decorated B₄CN₃ monolayer can serve as a favorable candidate material for high-capacity reversible hydrogen storage application.     

Effect of interface types on the heat-resistance of Cansas-II SiCf /SiC composites

The heat-resistance of the Cansas-II SiC/CVI-SiC mini-composites with a PyC and BN interface was studied in detail. The interfacial shear strength of the SiC/PyC/SiC mini-composites decreased from 15 MPa to 3 MPa after the heat treatment at 1500 °C for 50 h, while that of the SiC/BN/SiC mini-composites decreased from 248 MPa to 1 MPa, which could be mainly attributed to the improvement of the crystallization degree of the interface and the decomposition of the matrix. Aside from the above reasons, the larger declined fraction of the interfacial shear strength of the SiC/BN/SiC mini-composites might also be related to the gaps in the BN interface induced by the volatilization of B₂O₃·SiO₂ phase, leading to a significant larger declined fraction of the tensile strength of the SiC/BN/SiC mini-composites due to the obvious expansion of the critical flaws on the fiber surface. Therefore, compared with the CVI BN interface, the CVI PyC interface has better heat-resistance at high temperatures up to 1500 °C due to the fewer impurities in PyC.     

Machine learning algorithm selection for windage alteration fault diagnosis of mine ventilation system

Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation.     

The formed surface characteristics of SiCf/SiC composite in the nanosecond pulsed laser ablation

For the advantages of high-temperature resistance, corrosion resistance and ultra-high hardness, SiC_f/SiC composite is becoming a preferred material for manufacturing aero-engine parts. However, the anisotropy and heterogeneity bring great challenges to the processing technology. In this study, a nanosecond pulsed laser is applied to process SiC_f/SiC composite, where the influence of the scanning speed and laser scanning direction to the SiC fibers on the morphology of ablated grooves is investigated. The surface characteristics after ablation and the involved chemical reaction of SiC_f/SiC are explored. The results show that the increased laser scanning speed, accompanied by the decreasing spot overlap rate, leads to the less accumulation of energy on the material surface, so the ablation effect drops. In addition, for the anisotropy of the SiC_f/SiC material, the obtained surface characteristics are closely dependent on the laser scanning direction to the SiC fibers, resulting in different groove morphology. The element composition and phase analysis of the machined surface indicate that the main deposited product is SiO₂ and the carbon substance. The results can provide preliminary technical support for controlling the machining quality of ceramic matrix composites.     

Steering feel improvement by mathematical modeling of the Electric Power Steering system

Currently, the Electric Power Steering (EPS) system is an essential component of the vehicle because it provides assistive steering torque to the driver. To ensure a faster steering response, the position of the EPS in some vehicles is moved closer to the tire rather than the steering wheel. The steering torque, which is provided by the EPS in the steering system, mainly affects the driver’s feel while steering. Therefore, the driver often feels uncomfortable owing to such positioning of the EPS in the steering system. In particular, the nonlinearity of the Universal Joint (UJ), which is one of parts of the steering system, can be felt at the steering wheel side.In this paper, we proposed an algorithm based on the mathematical model of the steering torque in the steering system to improve the steering feel. The mathematical model is structured using parameters that can be obtained from the information of the steering system. Moreover, the formulation of the steering torque consists of the two parts, namely the deformation part, which describes the propagation inside the steering system, and the friction part that describes the inherent friction in the UJ.Simulation and experiments were conducted to verify the proposed mathematical model with similar conditions to the real tire load during the steering motion. Furthermore, to improve the driver’s feel during steering, a torque compensation algorithm is proposed and verified through experiments.     

Numerical simulation analysis and experimental validation on wear/fracture mechanisms of polycrystalline cubic boron nitride superabrasives in high-speed grinding

In this study, a two-dimensional finite element model is proposed to investigate the wear/fracture mechanisms of polycrystalline cubic boron nitride (PCBN) superabrasives in high-speed grinding process. The special geometric microstructures of PCBN grains are constructed by using the classic Voronoi tessellation technique, and cohesive elements are embedded into the geometric model of PCBN grains as the potential crack propagation paths for simulating the wear/fracture behaviours of PCBN grains under grinding loads. The effects of uncut chip thickness per grain (a_gmax) on the stress distribution characteristics and wear/fracture behaviours of PCBN grains during grinding are discussed in detail. Results show that the wear behaviour of PCBN grains during grinding mainly occurs around the grain vertex region; however, the fracture behaviour, leading to the quick failure of PCBN grains, is prone to appear around the grain–filler bonding interface, which is usually on the opposite side of the in-feed direction. Moreover, to separate the PCBN grains from the macro-fracture during grinding, the uncut chip thickness per grain should be kept smaller than 1.0?µm to prevent the unfavourable fracture behaviour from appearing around the grain–filler bonding interface. Furthermore, the corresponding single-grain grinding trials are performed to validate the numerical simulation results by evaluating the wear/fracture morphologies of the PCBN superabrasives in the actual grinding operation.     

Enhanced electromagnetic wave dissipation features of magnetic Ni microspheres by developing core-double shells structure

Readily oxidization of magnetic particles is a common drawback of these type of materials which reduce their electromagnetic wave dissipation performance. In this study, the magnetic core-double shells structured (Ni/SiO₂/Polyaniline) composite has been developed for protection of the core from oxidation and in consequent improvement the complex permittivity. Solvothermal and in-situ polymerization methods were utilized for decorating Ni micro-particles with SiO₂ and conductive polyaniline polymer respectively. All physico-chemical, magnetic and electromagnetic features were evaluated via XRD, FTIR, XPS, FESEM, VSM and VNA analysis. The double shells composite possesses significant performance in terms of reflection loss and effective absorption bandwidth. The results reveal that the maximum dissipation capacity of the double shells composite is – 32.5 dB at 16.5 GHz with 4.5 GHz effective absorption bandwidth and 1.5 mm thickness. Enhancement in microwave dissipation features are arises from synergistic influence of various phenomena such as interfacial polarization, multiple Debye relaxation, natural ferromagnetic resonance and proper impedance matching characteristic. Overall, developing double shells structure on magnetic Ni microsphere particles had a meaningful effect on tuning the microwave absorption performance.     

Influence of surface topography evolution of grinding wheel on the optimal material removal rate in grinding process of cemented carbide

Most of the reported studies on the optimization of grinding parameters do not consider the evolution of the surface topography of grinding wheels, and the established empirical models will no longer apply when the surface conditions of the grinding wheel changes. In this paper, an integrated model based on the surface topography of grinding wheel is established. The grinding process of cemented carbide is simulated using the established model, and the simulation results are analyzed to obtain the surface roughness model and the specific grinding energy model based on the undeformed chip thickness distribution. Subsequently, the grinding constraint models are defined according to the two grinding constraints—surface roughness and specific grinding energy. Through inversion analysis, the maximum material removal rate of the given grinding wheel surface conditions satisfying the defined grinding constraints are obtained, and the influence rules of the grinding wheel surface conditions on the maximum material removal rate are analyzed. Then the grinding wheel surface conditions are adjusted by changing the radial dressed height of the grinding wheel and the arrangement distance of the grains in wheel circumferential direction to improve the maximum material removal rate of the grinding wheel. Finally, the optimization results are verified through grinding tests of cemented carbide.