Highly stretchable graphene kirigami with tunable mechanical properties.

In recent years, kirigami techniques have inspired the design of graphene-based nanodevices with exceptional stretchability and ductility. Based on an I-shaped cutting pattern, here we propose a graphene kirigami that exhibits remarkable stretchability and ductility in two independent planar directions along with negative Poisson's ratios. The deformation mechanism underlying the high stretchability of the structure is the flipping and rotation of its cutting ligaments during elongation. Molecular dynamics simulations show that the yield and fracture strains of graphene kirigami can be enhanced by factors of 6 and 10 in the two planar directions. In addition, the mechanical properties of the graphene kirigami can be tuned by altering the cutting geometric parameters as well as incorporating distinct cutting patterns in series. We develop a numerical algorithm to predict the stress-strain response of the series-connected graphene kirigami, and verify its accuracy using appropriate simulations. On this basis, the stress-strain response of the series-connected graphene kirigami can be tuned by altering its geometric parameters and the number of building blocks. This graphene kirigami could be applied to the design and development of next-generation flexible electronics such as stretchable electrodes and strain sensors.

Protective water curtains as wave attenuators for blast-resistant tunnels.

Tunnels, as highly cost-demanding infrastructures which facilitate the transportation of people and goods, have been a target of terrorist attacks within the past few decades. The significance of the destructive impact of explosives on these structures has resulted in research on the development of blast-resistant design approaches. In this paper, water curtains are proposed as a blast-resistant system due to the established performance of water against explosives in free fields in previous studies as well as its capability to mitigate the potential incoming fire after an explosion. A parametric study was conducted for this purpose, considering the effects of curtain thickness, the distance of the curtain from the tunnel opening, and the amount of TNT charge. Accordingly, fifty-two finite element (FE) models were created in the FE package ABAQUS to investigate the performance of a water wall in a typical tunnel through the Eulerian approach to simulation. The water curtains had four different thicknesses and were located at three different distances from the reference point. TNT explosive charges were placed at the tunnel opening with four different masses. The thicker walls nearer to the tunnel opening were found to be more effective. However, the peak pressure reduction in all charges was in a desirable range of 53 to 80%. The parametric study also illustrated that the peak pressures were more sensitive to wall thickness rather than TNT charges mass and the wall distance from the explosives. We anticipate this preliminary study to be a starting point for the further development of the concept of water curtains for blast mitigation.

The fusion-fission optimization (FuFiO) algorithm.

Fusion-Fission Optimization (FuFiO) is proposed as a new metaheuristic algorithm that simulates the tendency of nuclei to increase their binding energy and achieve higher levels of stability. In this algorithm, nuclei are divided into two groups, namely stable and unstable. Each nucleus can interact with other nuclei using three different types of nuclear reactions, including fusion, fission, and ß-decay. These reactions establish the stabilization process of unstable nuclei through which they gradually turn into stable nuclei. A set of 120 mathematical benchmark test functions are selected to evaluate the performance of the proposed algorithm. The results of the FuFiO algorithm and its related non-parametric statistical tests are compared with those of other metaheuristic algorithms to make a valid judgment. Furthermore, as some highly-complicated problems, the test functions of two recent Competitions on Evolutionary Computation, namely CEC-2017 and CEC-2019, are solved and analyzed. The obtained results show that the FuFiO algorithm is superior to the other metaheuristic algorithms in most of the examined cases.

Additive Manufacturing Technologies for Drug Delivery Applications.

Patient to patient variability is one of the issues when administering medications to individuals with different health conditions, pharmacokinetic, age, fitness, gender, and race. This requires introducing smart and personalised drug delivery systems with controlled release profile manufactured using novel approaches. Additive manufacturing (AM) provides opportunities such as full customisation, design freedom, and on-site manufacturing, and materials recycling. As a result, the academic and industrial demand for additive manufacturing for drug delivery has been continuously increasing and showing impressive results for a wide range of products. This paper provides an extensive overview of AM technologies and their applications for drug delivery. The review discusses AM technologies including their working principles, processed materials, as well as current progress in drug delivery to produce personalized dosages for every patient with controlled release profile. AM potentials, industrial scale, and challenges are investigated with regards to practice and industrial applications. The paper covers novel possibilities of AM technologies and their pharmaceuticals applications, which indicate a promising healthcare future.

Rotorigami: A rotary origami protective system for robotic rotorcraft.

Applications of aerial robots are progressively expanding into complex urban and natural environments. Despite remarkable advancements in the field, robotic rotorcraft is still drastically limited by the environment in which they operate. Obstacle detection and avoidance systems have functionality limitations and substantially add to the computational complexity of the onboard equipment of flying vehicles. Furthermore, they often cannot identify difficult-to-detect obstacles such as windows and wires. Robustness to physical contact with the environment is essential to mitigate these limitations and continue mission completion. However, many current mechanical impact protection concepts are either not sufficiently effective or too heavy and cumbersome, severely limiting the flight time and the capability of flying in constrained and narrow spaces. Therefore, novel impact protection systems are needed to enable flying robots to navigate in confined or heavily cluttered environments easily, safely, and efficiently while minimizing the performance penalty caused by the protection method. Here, we report the development of a protection system for robotic rotorcraft consisting of a free-to-spin circular protector that is able to decouple impact yawing moments from the vehicle, combined with a cyclic origami impact cushion capable of reducing the peak impact force experienced by the vehicle. Experimental results using a sensor-equipped miniature quadrotor demonstrated the impact resilience effectiveness of the Rotary Origami Protective System (Rotorigami) for a variety of collision scenarios. We anticipate this work to be a starting point for the exploitation of origami structures in the passive or active impact protection of robotic vehicles.

Anchoring like octopus: biologically inspired soft artificial sucker.

This paper presents a robotic anchoring module, a sensorized mechanism for attachment to the environment that can be integrated into robots to enable or enhance various functions such as robot mobility, remaining on location or its ability to manipulate objects. The body of the anchoring module consists of two portions with a mechanical stiffness transition from hard to soft. The hard portion is capable of containing vacuum pressure used for actuation while the soft portion is highly conformable to create a seal to contact surfaces. The module is integrated with a single sensory unit which exploits a fibre-optic sensing principle to seamlessly measure proximity and tactile information for use in robot motion planning as well as measuring the state of firmness of its anchor. In an experiment, a variable set of physical loads representing the weights of potential robot bodies were attached to the module and its ability to maintain the anchor was quantified under constant and variable vacuum pressure signals. The experiment shows the effectiveness of the module in quantifying the state of firmness of the anchor and discriminating between different amounts of physical loads attached to it. The proposed anchoring module can enable many industrial and medical applications where attachment to environment is of crucial importance for robot control.