Multifunctional bio-films based on silk nanofibres/peach gum polysaccharide for highly sensitive temperature, flame, and water detection

Given their environment friendliness, light weight, and availability, bio-films have attracted wide interest for various applications in sensor materials. However, obtaining sensors with good environmental stability, excellent flame retardancy, and high wet strength remains a challenge. Herein, we prepared sensitive water, temperature and flame-responsive multi-function bio-films (named as PSCG bio-films) by combining peach gum polysaccharide, silk nanofibres, citric acid, and graphene. The PSCG bio-films demonstrated good flexibility, rapid and consistent water absorption, and stable wet strength at different temperatures. The bio-films showed excellent water sensitivity and rapid fire responsiveness within a short time frame (2 s); moreover, the response and recovery times of the bio-films in the temperature range of 50-150 °C were 0.1 and 0.3 s, respectively. In addition, the bio-films can be applied to micro-sized fire early warning devices and personalized breath monitoring. Our work presents a facile and green approach (without toxic solvent) to fabricate multi-function sensors with applications in various industries.

UHMWPE-Based Glass-Fiber Composites Fabricated by FDM. Multiscaling Aspects of Design, Manufacturing and Performance

The aim of the paper was to improve the functional properties of composites based on ultra-high molecular weight polyethylene (UHMWPE) by loading with reinforcing fibers. It was achieved by designing the optimal composition for its subsequent use as a feedstock for 3D-printing of guides for roller and plate chains, conveyors, etc. As a result, it was experimentally determined that loading UHMWPE with 17% high density polyethylene grafted with VinylTriMethoxySilane (HDPE-g-VTMS) was able to bind 5% glass fillers of different aspect ratios, thereby determining the optimal mechanical and tribological properties of the composites. Further increasing the content of the glass fillers caused a deterioration in their tribological properties due to insufficient adhesion of the extrudable matrix due to the excessive filler loading. A multi-level approach was implemented to design the high-strength anti-friction ‘UHMWPE+17%HDPE-g-VTMS+12%PP’-based composites using computer-aided algorithms. This resulted in the determination of the main parameters that provided their predefined mechanical and tribological properties and enabled the assessment of the possible load-speed conditions for their operation in friction units. The uniform distribution of the fillers in the matrix, the pattern of the formed supermolecular structure and, as a consequence, the mechanical and tribological properties of the composites were achieved by optimizing the values of the main control parameters (the number of processing passes in the extruder and the aspect ratio of the glass fillers).

Molecular Simulation and Statistical Learning Methods toward Predicting Drug-Polymer Amorphous Solid Dispersion Miscibility, Stability, and Formulation Design

Amorphous solid dispersions (ASDs) have emerged as widespread formulations for drug delivery of poorly soluble active pharmaceutical ingredients (APIs). Predicting the API solubility with various carriers in the API-carrier mixture and the principal API-carrier non-bonding interactions are critical factors for rational drug development and formulation decisions. Experimental determination of these interactions, solubility, and dissolution mechanisms is time-consuming, costly, and reliant on trial and error. To that end, molecular modeling has been applied to simulate ASD properties and mechanisms. Quantum mechanical methods elucidate the strength of API-carrier non-bonding interactions, while molecular dynamics simulations model and predict ASD physical stability, solubility, and dissolution mechanisms. Statistical learning models have been recently applied to the prediction of a variety of drug formulation properties and show immense potential for continued application in the understanding and prediction of ASD solubility. Continued theoretical progress and computational applications will accelerate lead compound development before clinical trials. This article reviews in silico research for the rational formulation design of low-solubility drugs. Pertinent theoretical groundwork is presented, modeling applications and limitations are discussed, and the prospective clinical benefits of accelerated ASD formulation are envisioned.

Influences of interface structure on tribological properties of engineering polymer blends: a review

Polymer blends have been widely used as tribological materials for replacements of traditional metals and ceramics. Polymer blends consist of the reinforced phase, the matrix phase and interfaces between reinforced and matrix phase. Although the interface structure of polymer blends is usually small in size, it is one of the key factors for deciding the physical and tribological properties of polymer blends. Thus, this review highlights the most recent trends in the field of influences of interface structure on tribological properties of engineering polymer blends. Emphasis is given to the improvement methods of interfacial compatibility of polymer blends and the behavior variation of interface structure during friction process.