Ingrowth of human mesenchymal stem cells into porous silk particle reinforced silk composite scaffolds : an in vitro study

Silk fibroin protein is biodegradable and biocompatible, exhibiting excellent mechanical properties for various biomedical applications. However, porous three-dimensional (3-D) silk fibroin scaffolds, or silk sponges, usually fall short in matching the initial mechanical requirements for bone tissue engineering. In the present study, silk sponge matrices were reinforced with silk microparticles to generate protein-protein composite scaffolds with desirable mechanical properties for in vitro osteogenic tissue formation. It was found that increasing the silk microparticle loading led to a substantial increase in the scaffold compressive modulus from 0.3 MPa (non-reinforced) to 1.9 MPa for 1:2 (matrix:particle) reinforcement loading by dry mass. Biochemical, gene expression, and histological assays were employed to study the possible effects of increasing composite scaffold stiffness, due to microparticle reinforcement, on in vitro osteogenic differentiation of human mesenchymal stem cells (hMSCs). Increasing silk microparticle loading increased the osteogenic capability of hMSCs in the presence of bone morphogenic protein-2 (BMP-2) and other osteogenic factors in static culture for up to 6 weeks. The calcium adsorption increased dramatically with increasing loading, as observed from biochemical assays, histological staining, and microcomputer tomography (μCT) analysis. Specifically, calcium content in the scaffolds increased by 0.57, 0.71, and 1.27 mg (per μg of DNA) from 3 to 6 weeks for matrix to particle dry mass loading ratios of 1:0, 1:1, and 1:2, respectively. In addition, μCT imaging revealed that at 6 weeks, bone volume fraction increased from 0.78% for non-reinforced to 7.1% and 6.7% for 1:1 and 1:2 loading, respectively. Our results support the hypothesis that scaffold stiffness may strongly influence the 3-D in vitro differentiation capabilities of hMSCs, providing a means to improve osteogenic outcomes.

Reinforcing silk scaffolds with silk particles

Silk fibroin is a useful protein polymer for biomaterials and tissue engineering. In this work, porogen leached scaffolds prepared from aqueous and HFIP silk solutions were reinforced through the addition of silk particles. This led to about 40 times increase in the specific compressive modulus and the yield strength of HFIP-based scaffolds. This increase in mechanical properties resulted from the high interfacial cohesion between the silk matrix and the reinforcing silk particles, due to partial solubility of the silk particles in HFIP. The porosity of scaffolds was reduced from ≈90% (control) to ≈75% for the HFIP systems containing 200% particle reinforcement, while maintaining pore interconnectivity. The presence of the particles slowed the enzymatic degradation of silk scaffolds.

The influence of processing techniques on the matrix distribution and filtration of clay in a fibre reinforced nanocomposite

A nano-modified matrix based on an epoxy resin and montmorillonite (MMT) layered silicates, was successfully infiltrated through 10 ply of carbon fibre preform. A combined fabrication process of a vacuum assisted resin infusion method (VARIM) followed by a rapid heating rate and mechanical vibration during cure, facilitated the infiltration of the nano-modified matrix through the preform. This was achieved by dispersing the MMT clay in the resin and ensuring that the viscosity of the nano-modified matrix remained low during fabrication. SEM-EDX (energy dispersive X-ray spectroscopy) spectra showed that chemical constituents within MMT clay including silicon, aluminium and magnesium elements had permeated through the fibre preform and were detected throughout the laminate. A homogeneous resin/particle distribution was achieved with the size of clay particles ranging from 100 nm to 1 μm.

A new reinforcement learning-based memetic particle swarm optimizer

Developing an effective memetic algorithm that integrates the Particle Swarm Optimization (PSO) algorithm and a local search method is a difficult task. The challenging issues include when the local search method should be called, the frequency of calling the local search method, as well as which particle should undergo the local search operations. Motivated by this challenge, we introduce a new Reinforcement Learning-based Memetic Particle Swarm Optimization (RLMPSO) model. Each particle is subject to five operations under the control of the Reinforcement Learning (RL) algorithm, i.e. exploration, convergence, high-jump, low-jump, and fine-tuning. These operations are executed by the particle according to the action generated by the RL algorithm. The proposed RLMPSO model is evaluated using four uni-modal and multi-modal benchmark problems, six composite benchmark problems, five shifted and rotated benchmark problems, as well as two benchmark application problems. The experimental results show that RLMPSO is useful, and it outperforms a number of state-of-the-art PSO-based algorithms.

Investigation of effective material properties in composites with internal defect or reinforcement particles

This paper is concerned with the investigation of the effective material properties of internally defective or particle-reinforced composites. An analysis was carried out with a novel method using the two-dimensional special finite element method mixing the concept of equivalent homogeneous materials. A formulation has been developed for a series of special finite elements containing an internal defect or reinforcement in order to assure the high accuracy especially in the vicinity of defects or reinforcements. The adoption of the special finite element can greatly simplify numerical modeling of particle-composites. The numerical result provides the effective material properties of particle-reinforced composite and explains that the size of particles has great influence on the material properties. Numerical examples also demonstrate the validity and versatility of the proposed method by comparing with existing results from literatures.

Fabrication of nano-particle reinforced metal matrix composites

Nanoparticle reinforced metal matrix possess much better mechanical properties over microparticle reinforced metal matrix composites as well as corresponding monolithic matrix materials. However, the fabrication methods of nanoparticle reinforced metal matrix composites are complex and expensive. This paper investigates and discusses the mechanisms of all the fabrication process, such as powder metallurgy, liquid metallurgy, compocasting and hybrid methods, available in the literature. This gives an insight on challenges associated with different processes and ways to improve the fabrication processes. It is found that modified traditional fabrication processes are mainly applied for these materials. The main problem is to achieve reasonably uniform distribution of nanoparticle reinforcement in the methods other than mechanical alloying when the volume or weight percent of reinforcement is higher (> 1%).

Wire EDM mechanism of MMCs with the variation of reinforced particle size

The size of reinforced particles notably affects the electro-discharge machining (EDM) of metal matrix composites (MMCs). This paper explores the mechanism of wire EDM of MMCs with different sizes of reinforced particles as well as the corresponding unreinforced matrix material. The mechanisms of material removal, surface generation, and taper kerf formation were investigated. This study shows that the particles’ ability to protect matrix materials from the intense heat of electric arc controls the material removal rate, surface generation, and taper of kerf. The low melting point matrix material is removed very easily, but the heat resistance reinforced particles delay the removal of material and facilitate the transfer of the workpiece material to wire electrode and vice versa. Thus, the material stays longer in touch with intense heat and affects the surface generation, wire electrode wear, and width of the kerf.