Jinsong Leng

Bio: Jinsong Leng is an academic researcher from Harbin Institute of Technology. The author has contributed to research in topics: Shape-memory polymer & Materials science. The author has an hindex of 57, co-authored 526 publications receiving 14901 citations. Previous affiliations of Jinsong Leng include Beijing University of Technology & Nanyang Technological University.

Shape memory polymers and their composites in aerospace applications: a review

Abstract: As a new class of smart materials, shape memory polymers and their composites (SMPs and SMPCs) can respond to specific external stimulus and remember the original shape. There are many types of stimulus methods to actuate the deformation of SMPs and SMPCs, of which the thermal- and electro-responsive components and structures are common. In this review, the general mechanism of SMPs and SMPCs are first introduced, the stimulus methods are then discussed to demonstrate the shape recovery effect, and finally, the applications of SMPs and SMPCs that are reinforced with fiber materials in aerospace are reviewed. SMPC hinges and booms are discussed in the part on components; the booms can be divided again into foldable SMPC truss booms, coilable SMPC truss booms and storable tubular extendible member (STEM) booms. In terms of SMPC structures, the solar array and deployable panel, reflector antenna and morphing wing are introduced in detail. Considering the factors of weight, recovery force and shock effect, SMPCs are expected to have great potential applications in aerospace.

Critical factors on manufacturing processes of natural fibre composites

Abstract: Elevated environmental awareness of the general public in reducing carbon footprints and the use nonnaturally decomposed solid wastes has resulted in an increasing use of natural materials, biodegradable and recyclable polymers and their composites for a wide range of engineering applications. The properties of natural fibre reinforced polymer composites are generally governed by the pre-treated process of fibre and the manufacturing process of the composites. These properties can be tailored for various types of applications by properly selecting suitable fibres, matrices, additives and production methods. Besides, due to the complexity of fibre structures, different mechanical performances of the composites are obtained even with the use of the same fibre types with different matrices. Some critical issues like poor wettability, poor bonding and degradation at the fibre/matrix interface (a hydrophilic and hydrophobic effect) and damage of the fibre during the manufacturing process are the main causes of the reduction of the composites’ strength. In this paper, different manufacturing processes and their suitability for natural fibre composites, based on the materials, mechanical and thermal properties of the fibres and matrices are discussed in detail.

A Review of Shape Memory Polymers and Composites: Mechanisms, Materials, and Applications

Abstract: Over the past decades, interest in shape memory polymers (SMPs) has persisted, and immense efforts have been dedicated to developing SMPs and their multifunctional composites. As a class of stimuli-responsive polymers, SMPs can return to their initial shape from a programmed temporary shape under external stimuli, such as light, heat, magnetism, and electricity. The introduction of functional materials and nanostructures results in shape memory polymer composites (SMPCs) with large recoverable deformation, enhanced mechanical properties, and controllable remote actuation. Because of these unique features, SMPCs have a broad application prospect in many fields covering aerospace engineering, biomedical devices, flexible electronics, soft robotics, shape memory arrays, and 4D printing. Herein, a comprehensive analysis of the shape recovery mechanisms, multifunctionality, applications, and recent advances in SMPs and SMPCs is presented. Specifically, the combination of functional, reversible, multiple, and controllable shape recovery processes is discussed. Further, established products from such materials are highlighted. Finally, potential directions for the future advancement of SMPs are proposed.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.