Effect of Micro-Mold Cavity Dimension on Structure andProperty of Polylactic Acid/Polycaprolactone Blend underMicroinjection Molding Conditions

Microinjection molding is a novel frontier polymer processing strategy different from conventional ones. In this paper, three different cavity-sizes of micro-mold tools were firstly fabricated, and the influences of micro-mold cavity dimension on the phase morphology structure, crystallization and orientation, and mechanical performance of the microinjection molded polylactic acid (PLA)/polycaprolactone (PCL) blend microparts were carefully investigated accordingly. The results show that the reduction of the cavity size would result in much higher shear stress field and cooling temperature gradient, which is advantageous to the fibrillation and orientation of PCL-dispersed phase. Consequently, with decreasing the micro-mold cavity dimension from length 26 mm to 15 mm, the interfacial compatibility is improved, significantly increasing number of PCL fibers with smaller diameter are in situ formed in PLA matrix and their orientation degree also obviously increases, which is verified by SEM and 2D-WAXD measurements. The Differential Scanning Calorimetry (DSC) analysis shows that the decrease in cavity dimension causes the enhancement of PLA crystallization property due to shear-induced crystallization, which is reflected by the decreasing PLA cold crystallization temperature and increasing PLA crystallinity (almost doubling that of conventional macropart). As a result, the dynamic/static mechanical property measurements exhibit that with decreasing the cavity size, the storage modulus, and the loss modulus of PLA/PCL blend micropart increase, and the corresponding tensile strength, elongation at break, and Young’s modulus also present an obviously increasing tendency. The related investigations would provide some new spaces and insights for realization of high-performance of PLA/PCL blend micropart.

DHS-Crystallize: Deep-Hybrid-Sequence based method for predicting protein Crystallization

The key method for determining the structure of a protein to date is X-ray crystallography, which is a very expensive technique that suffers from high attrition rate. On the contrary, a sequence-based predictor that is capable of accurately determining protein crystallization property, would not only overcome such limitations, but also would reduce the trial-and-error settings required to perform crystallization. In this work, to predict protein crystallizability, we have developed a novel sequence-based hybrid method that employs two separate, yet fully automated, concepts for extracting features from protein sequences. Specifically, we use a deep convolutional neural network on a publicly available dataset to extract descriptive features directly from the sequences, then fuse such feature with structural-and-physio-chemical driven features (such as amino-acid composition or AAIndex-based physicochemical properties). Dimentionality reduction is then performed on the resulting features and the output vectors are applied to train optimized gradient boosting machine (XGBoostt). We evaluate our method through three publicly available test sets, and show that our proposed DHS-Crystallize algorithm outperforms state-of-the-art methods, and achieves higher performance compared to using DCNN-deriven features, or structural-and-physio-chemical driven features alone.

Higher tear strength of EPDM/SBR/TPR composites foam based on double foaming system

Polymeric foam with lightweight and higher impact strength has been used in many fields due to cost reduction and higher toughness. However, it is often difficult to improve their mechanical property especially tear strength. Here, a double foaming system was designed to increase the tear strength of the foamed ethylene–propylene–diene monomer, styrene–butadiene rubber, and thermoplastic rubber (EPDM/SBR/TPR) materials. The cell size of EPDM/SBR/TPR foam and cell distribution were investigated by scanning electron microscopy, which showed that the cells present a bimodal structure. Besides, the tear strength can reach up to 10 N/mm when the density is about 0.40 g/cm3, which is much superior to those of most engineering plastic foams. Meanwhile, the crystallization property of EPDM/SBR/TPR foams was also demonstrated by X-ray diffraction, thermogravimetric analysis, and differential scanning calorimetry, which indicates that the double foaming system can reduce the crystallization of EPDM/SBR/TPR molecular chains. In addition, the variation of thermal conductivity values depends on the gradual decrease effect of the cell size.

Effects of Boric Acid Ester Modified Magnesium Borate Whisker on the Mechanical Properties and Crystallization Kinetics of Polypropylene Composites

Polypropylene (PP) is notch sensitive and brittle under severe conditions of deformation, limiting wider range of its usage as a structural load-bearing polymer. Hence, in this work the magnesium borate whisker (MBw), with similar mechanical properties to carbon fiber but much less expensive than polycrystalline silicon carbide, was modified by boric acid ester (BAE) and then used to fabricate PP composites. The mechanical properties, morphology, and non-isothermal crystallization property of virgin PP, PP/MBw, and PP/BAE-MBw composites were studied through mechanical testing, scanning electron microscopy (SEM), and differential scanning calorimetry (DSC), respectively. The non-isothermal crystallization data was analyzed via Mo, Kissinger, and Dobreva methods. The results reveal that the incorporation of BAE-MBw into PP matrix results in higher tensile strength and impact strength than those of virgin PP and PP/MBw composite. The activation energies based on Kissinger were 190.20 kJ/mol for virgin PP, 206.59 kJ/mol for PP/MBw, and 218.98 kJ/mol for PP/BAE-MBw. The nucleation activities of whiskers determined by the Dobreva model were 0.86 for PP/MBw and 0.75 for PP/BAE-MBw. As a result, the whiskers, especially the modified whiskers, act as active substrates to facilitate heterogeneous nucleation, which leads to an increase in crystallization rate.

Reinforcing polypropylene with calcium carbonate of different morphologies and polymorphs

The influence of calcium carbonate (CaCO3) with different polymorphs (calcite and aragonite) and morphologies (granular and rod-like) on mechanical and crystallization properties of polypropylene (PP) was investigated. Meanwhile, these CaCO3 fillers coated with oleic acid were added in different contents to PP. The results indicate that the tensile strength, flexural strength, modulus, and crystallization property of the filler-treated samples are improved, but the impact strength decreased. The crystallinity of the composites is higher than that of neat PP. Moreover, in the rod shape filler-treated sample, in both whisker species, the mechanical properties of composites are superior to the particles filled. Differential scanning calorimetry, X-ray diffraction, and mechanical tests display that calcite whisker-reinforced composite has higher crystallization enthalpy, melting enthalpy, degree of crystallinity, and mechanical properties than aragonite whiskers and calcite particles filled composites.