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The purpose of this paper is to study the effect of alignment of conductive particles on the piezoresistivity of composite based on a theoretical model. The piezoresistivity of composite is associated with the characteristics of conductive network formed by the conductive particles distributed in the composite, which can be changed through aligning the conductive particles.

The orientations of the tunnel resistors formed by each two adjacent conductive particles are dependent on the aligned level of the conductive particles, and different orientations induce different deformations for a tunnel resistor under external strain, which determines the piezoresistivity of the composites. To investigate the resistance behavior of composites with various characteristics of conductive networks, a piezoresistivity model is developed in this paper by considering the aligned level of conductive particles.

The results obtained from the proposed piezoresistivity model indicate that the sensitivity and stability of composites can be enhanced through aligning the conductive particles. Also, the piezoresistivity of composites filled with randomly distributed conductive particles is isotropic, and it turns to be anisotropic when the conductive particles are aligned.

The change and its mechanism of the piezoresistivity upon the aligned level of conductive particles have been pointed out in this paper based on the proposed model. The achievement of this paper will help the people understand, predict and optimize the piezoresistivity of composites, and provide a new approach to design a strain sensor based on the piezoresistivity.

A generalized distribution with wide range of skewness and elongation will be suitable for the data mining and compatible for the misspecification of the distribution. Hence, the purpose of this paper is to present a distribution-based approach for estimating degradation reliability considering these conditions.

Tukey’s g-and-h distribution with the quantile expression is introduced to fit the degradation paths of the population over time. The Newton–Raphson algorithm is used to approximately evaluate the reliability. Simulation verification for parameter estimation with particle swarm optimization (PSO) is carried out. The effectiveness and validity of the proposed approach for degradation reliability is verified by the two-stage verification and the comparison with others’ work.

Simulation studies have proved the effectiveness of PSO in the parameter estimation. Two degradation datasets of GaAs laser devices and crack growth are performed by the proposed approach. The results show that it can well match the initial failure time and be more compatible than the normal distribution and the Weibull distribution.

Tukey’s g-and-h distribution is first proposed to investigate the influence of the tail and the skewness on the degradation reliability. In addition, the parameters of the Tukey’s g-and-h distribution is estimated by PSO with root-mean-square error as the object function.

The effect of using microcrystalline cellulose (MCC) as an additive in coating paint films for non-stick coatings was studied in this work. This paper aims to discuss the benefits of MCC blended in the coating paint film that consists of poly(methyl methacrylate) (PMMA) and dammar.

PMMA and dammar mixed at a specific Wt.% ratio with xylene as its solvent. Two sets of mixtures were prepared, where one mixture contained MCC and another, without. The mixtures were applied to metal substrates as coating paint films. The performance of the non-stick coating paint film was observed through the adhesive test between adhesion layers on the coating paint film and also through the cross-hatch test for the adhesion of the non-stick coating paint film to the metal substrate. The results correlate with the surface roughness and glossiness tests.

The results showed that for the coating paint films, Sample B consisted of 80:20 Wt.% ratio of PMMA-dammar with an addition of 5 Wt.% MCC had an excellent performance as non-stick coating paint films. The MCC formed microparticles on the surface of the coating paint film sample and this causes the coating paint film samples with MCC to develop a rougher surface compared to the coating paint film without MCC. Sample B coating paint film had the highest average surface roughness (Ra) of 383 µm. The cross-hatch test showed the coating paint film with the addition of MCC had stronger adhesiveness on the substrate’s surface thus prevents the coating from peeling off from the surface.

The developed coating paint film in this study would be suitable for outdoor applications to prevent illegal advertisements and stickers.

MCC added to the coating paint film improves the surface performance as a non-stick coating.