The shape – morphing performance of magnetoactive soft materials

Magnetoactive soft materials (MSMs) are soft polymeric composites filled with magnetic particles that are an emerging class of smart and multifunctional materials with immense potentials to be used in various applications including but not limited to artificial muscles, soft robotics, controlled drug delivery, minimally invasive surgery, and metamaterials. Advantages of MSMs include remote contactless actuation with multiple actuation modes, high actuation strain and strain rate, self-sensing, and fast response etc. Having broad functional behaviours offered by the magnetic fillers embedded within non-magnetic matrices, MSMs are undoubtedly one of the most promising materials in applications where shape-morphing, dynamic locomotion, and reconfigurable structures are highly required. This review article provides a comprehensive picture of the MSMs focusing on the materials, manufacturing processes, programming and actuation techniques, behaviours, experimental characterisations, and device-related achievements with the current state-of-the-art and discusses future perspectives. Overall, this article not only provides a comprehensive overview of MSMs’ research and development but also functions as a systematic guideline towards the development of multifunctional, shape-morphing, and sophisticated magnetoactive devices

Shape-driven segmentation of the arterial wall in intravascular ultrasound images

Segmentation of arterial wall boundaries from intravascular images is an important problem for many applications in the study of plaque characteristics, mechanical properties of the arterial wall, its 3D reconstruction, and its measurements such as lumen size, lumen radius, and wall radius. We present a shape-driven approach to segmentation of the arterial wall from intravascular ultrasound images in the rectangular domain. In a properly built shape space using training data, we constrain the lumen and media-adventitia contours to a smooth, closed geometry, which increases the segmentation quality without any tradeoff with a regularizer term. In addition to a shape prior, we utilize an intensity prior through a non-parametric probability density based image energy, with global image measurements rather than pointwise measurements used in previous methods. Furthermore, a detection step is included to address the challenges introduced to the segmentation process by side branches and calcifications. All these features greatly enhance our segmentation method. The tests of our algorithm on a large dataset demonstrate the effectiveness of our approach

Simulation modelling and visualisation: toolkits for building artificial worlds

Simulations users at all levels make heavy use of compute resources to drive computational simulations for greatly varying applications areas of research using different simulation paradigms. Simulations are implemented in many software forms, ranging from highly standardised and general models that run in proprietary software packages to ad hoc hand-crafted simulations codes for very specific applications. Visualisation of the workings or results of a simulation is another highly valuable capability for simulation developers and practitioners. There are many different software libraries and methods available for creating a visualisation layer for simulations, and it is often a difficult and time-consuming process to assemble a toolkit of these libraries and other resources that best suits a particular simulation model. We present here a break-down of the main simulation paradigms, and discuss differing toolkits and approaches that different researchers have taken to tackle coupled simulation and visualisation in each paradigm

Design, Actuation, and Functionalization of Untethered Soft Magnetic Robots with Life-Like Motions: A Review

Soft robots have demonstrated superior flexibility and functionality than conventional rigid robots. These versatile devices can respond to a wide range of external stimuli (including light, magnetic field, heat, electric field, etc.), and can perform sophisticated tasks. Notably, soft magnetic robots exhibit unparalleled advantages among numerous soft robots (such as untethered control, rapid response, and high safety), and have made remarkable progress in small-scale manipulation tasks and biomedical applications. Despite the promising potential, soft magnetic robots are still in their infancy and require significant advancements in terms of fabrication, design principles, and functional development to be viable for real-world applications. Recent progress shows that bionics can serve as an effective tool for developing soft robots. In light of this, the review is presented with two main goals: (i) exploring how innovative bioinspired strategies can revolutionize the design and actuation of soft magnetic robots to realize various life-like motions; (ii) examining how these bionic systems could benefit practical applications in small-scale solid/liquid manipulation and therapeutic/diagnostic-related biomedical fields

Control and manipulation of nanoparticles for fabrication of metal matrix composites

The mechanical properties of composite materials are mainly determined by their microstructures that depend on comprising phases and their properties, the shape and size of those phases, and their distribution. By controlling and optimizing the various aspects of the microstructure, composites with improved mechanical properties can be created. One of the challenges, however, is the lack of scalable fabrication method capable of making complex structures. The conventional fabrication techniques for MMCs have been limited to fabricating simple structures with homogeneous dispersion of constituents. In this work, various fabrication approaches that can control the microstructure in metal matrix reinforced with nanoparticles have been studied. Mechanical alloying (ball milling) was used to control the dispersion of graphene sheets in homogeneous reinforced aluminum composites. Spray assisted deposition of nanoparticles was used to fabricate layered composites with uniformly and hierarchically reinforced interfaces. Magnetic field assisted deposition was studied to manipulate and deposit nanoparticles into micro-patterns that can be used to create hierarchically layered composites. Homogeneously reinforced aluminum alloy (Al6061) reinforced composites with graphene have been synthesized using mechanical alloying followed by semisolid sintering. The ball milling was used to control the dispersion as well as the cluster size of the graphene within the matrix. The effect of ball milling time on the fabricated composites was studied. A significant enhancement in the mechanical properties of the graphene reinforced composites was observed compared with the matrix material processed at the same condition. Layered composites, which are uniformly or hierarchically reinforced at the interfaces, have been synthesized by implementing two processing concepts: spray assisted deposition and metallurgy (semi-solid sintering). Ultrasonic spray deposition creates nano-/micro-/meso-scale patterns on metallic sheets, which are then stacked together, densified, and synthesized into a composite through pressure assisted semi-solid sintering process. Silicon carbide (SiC) nanoparticle reinforced lightweight alloys (i.e. Magnesium Alloy (AZ31) and Al6061) have been synthesized. The synthesized composites showed an improvement in the strength with minor decrease on the total elongation. Magnetic field directed manipulation of nanoparticles was demonstrated to self-assemble and deposit nanoparticles into user-defined micro-patterns on Al substrate for potential use in synthesis of hierarchically structure layered composites. The magnetic field was modulated by machining (e.g. micro-milling and laser machining) user-defined pattern of protrusions on the magnetic source surface. The deposition of magnetic particles as well as mixtures of magnetic and nonmagnetic nanoparticles was studied