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The purpose of this paper is to develop and test the thermal interface materials (TIM) for application in assembly of semiconductor chips to package. Good adhesion properties (>5 MPa shear strength) and low thermal interface resistance (better than for SAC solders) are the goal of this research.

Mechanical and thermal properties of TIM joints between gold plated contacts of chip and substrate were investigated. Sintering technique based on Ag pastes was applied for purpose of this study. Performance properties were assessed by shear force tests and thermal measurements. Scanning electron microscopy was used for microstructural observations of cross-section of formed joints.

It was concluded that the best properties are achieved for pastes containing spherical Ag particles of dozens of micrometer size with flake shaped Ag particles of few micrometers size. Sintering temperature at 230°C and application of 1 MPa force on the chip during sintering gave the higher adhesion and the lowest thermal interface resistance.

The new material based on Ag paste containing mixtures of Ag particles of different size (form nanometer to dozens of microns) and shape (spherical, flake) suspended in resin was proposed. Joints prepared using sintering technique and Ag pastes at 230°C with applied pressure shows better mechanical and thermal than other TIM materials such as thermal grease, thermal gel or thermally conductive adhesive. Those material could enable electronic device operation at temperatures above 200°C, currently unavailable for Si-based power electronics.

This study aims to present a novel methodology for the evaluation of tribological properties of new nanocomposites with the A356 alloy matrix reinforced with aluminium oxide (Al₂O₃) nanoparticles.

Metal matrix nanocomposites (MMnCs) with varying amounts and sizes of Al₂O₃ particles were produced using a compocasting process. The influence of four factors, with different levels, on the wear rate, was analysed with the help of the design of experiments (DoE). A regression model was developed by using the response surface methodology (RSM) to establish a relationship between the observed factors and the wear rate. An artificial neural network was also applied to predict the value of wear rate. Adequacy of models was compared with experimental values. The extreme values of wear rate were determined with a genetic algorithm and particle swarm optimization using the RSM model.

The combination of optimization methods determined the values of the factors which provide the highest wear resistance, namely, reinforcement content of 0.44 wt.% Al₂O₃, sliding speed of 1 m/s, normal load of 100 N and particle size of 100 nm. Used methods proved as effective tools for modelling and predicting of the behaviour of aluminium matrix nanocomposites.

The specific combinations of the optimization methods has not been applied up to now in the investigation of MMnCs. In addition, using of small content of ceramic nanoparticles as reinforcement has been poorly investigated. It can be stated that the presented approach for testing and prediction of the wear rate of nanocomposites is a very good base for their future research.

Porous implant surface is shown to facilitate bone in-growth and cell attachment, improving overall osteointegration, while providing adequate mechanical integrity. Recently, biodegradable material possessing such superior properties has been the focus with an aim of revolutionizing implant’s design, material and performance. This paper aims to present a comprehensive investigation into the design and development of low elastic modulus porous biodegradable Mg-3Si-5HA composite by mechanical alloying and spark plasma sintering (MA-SPS) technique.

This paper presents a comprehensive investigation into the design and development of low elastic modulus porous biodegradable Mg-3Si-5HA composite by MA-SPS technique. As the key alloying elements, HA powders with an appropriate proportion weight 5 and 10 are mixed with the base elemental magnesium (Mg) particles to form the composites of potentially variable porosity and mechanical property. The aim is to investigate the performance of the synthesized composites of Mg-3Si together with HA in terms of mechanical integrity hardness and Young’s moduli corrosion resistance and in-vitro bioactivity.

Mechanical and surface characterization results indicate that alloying of Si leads to the formation of fine Mg2 Si eutectic dense structure, hence increasing hardness while reducing the ductility of the composite. On the other hand, the allying of HA in Mg-3Si matrix leads to the formation of structural porosity (5-13 per cent), thus resulting in low Young’s moduli. It is hypothesized that biocompatible phases formed within the composite enhanced the corrosion performance and bio-mechanical integrity of the composite. The degradation rate of Mg-3Si composite was reduced from 2.05 mm/year to 1.19 mm/year by the alloying of HA elements. Moreover, the fabricated composites showed an excellent bioactivity and offered a channel/interface to MG-63 cells for attachment, proliferation and differentiation.

Overall, the findings suggest that the Mg-3Si-HA composite fabricated by MA and plasma sintering may be considered as a potential biodegradable material for orthopedic application.

The purpose of this study is the introduction and validation of a new technique for process monitoring during electron beam melting (EBM).

In this study, a backscatter electron detector inside the building chamber is used for image acquisition during EBM process. By systematic variation of process parameters, the ability of displaying different topographies, especially pores, is investigated. The results are evaluated in terms of porosity and compared with optical microscopy and X-ray computed tomography.

The method is capable of detecting major flaws (e.g. pores) and gives information about the quality of the resulting component.

Image acquisition by evaluating backscatter electrons during EBM process is a new approach in process monitoring which avoids disadvantages restricting previously investigated techniques.

Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.

The surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.

To address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.

This study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

The purpose of this paper is to examine the effectiveness of an improved dummy variables control grey model (DVCGM) considering the hysteresis effect of government policies in China's energy intensity (EI) forecasting.

Energy consumption is considered as an important driver of economic development. China has introduced policies those aim at the optimization of energy structure and EI. In this study, EI is forecasted by an improved DVCGM, considering the hysteresis effect of energy-saving policies of the government. A nonlinear optimization method based on particle swarm optimization (PSO) algorithm is constructed to calculate the hysteresis parameter. A one-step rolling mechanism is applied to provide input data of the prediction model. Grey model (GM) (1, N), DVCGM (1, N) and ARIMA model are applied to test the accuracy of the improved DVCGM (1, N) model prediction.

The results show that the improved DVCGM provides reliable results and works well in simulation and predictions using multivariable data in small sample size and time-lag virtual variable. Accordingly, the improved DVCGM notes the hysteresis effect of government policies and significantly improves the prediction accuracy of China's EI than the other three models.

This study estimates the EI considering the hysteresis effect of energy-saving policies in China by using an improved DVCGM. The main contribution of this paper is to propose a model to estimate EI, considering the hysteresis effect of energy-saving policies and improve forecasting accuracy.