Smart material

About: Smart material is a research topic. Over the lifetime, 3704 publications have been published within this topic receiving 74280 citations. The topic is also known as: intelligent material & responsive material.

Model-Based Robust Control Design for Magnetostrictive Transducers Operating in Hysteretic and Nonlinear Regimes

Abstract: This paper addresses the development of robust control designs for high-performance smart material transducers operating in nonlinear and hysteretic regimes. While developed in the context of a magnetostrictive transducer used for high-speed, high-accuracy milling, the resulting model-based control techniques can be directly extended to systems utilizing piezoceramic or shape memory alloy compounds due to the unified nature of models used to quantify hysteresis and nonlinearities inherent to all of these materials. When developing models and corresponding inverse filters or compensators, significant emphasis is placed on the utilization of the material's physics to provide the accuracy and efficiency required for real-time implementation of resulting model-based control designs. In the material models, this is achieved by combining energy analysis with stochastic homogenization techniques, whereas the efficiency of forward algorithms is combined with monotonicity properties of the material behavior to provide highly efficient inverse algorithms. These inverse filters are then incorporated in H2 and Hinfin theory to provide robust control algorithms capable of providing high-accuracy tracking even though the actuators are operating in nonlinear and hysteretic regimes. Through numerical examples, it is illustrated that the robust designs incorporating inverse compensators can achieve the required tracking tolerance of 1-2 mum for the motivating milling application, whereas robust designs which treat the uncompensated hysteresis and nonlinearities as unmodeled disturbances cannot achieve design specifications

Photomechanical Organic Crystals as Smart Materials for Advanced Applications.

Abstract: Photomechanical molecular crystals are receiving much attention due to their efficient conversion of light into mechanical work and advantages including faster response time; higher Young's modulus; and ordered structure, as measured by single-crystal X-ray diffraction. Recently, various photomechanical crystals with different motions (contraction, expansion, bending, fragmentation, hopping, curling, and twisting) are appearing at the forefront of smart materials research. The photomechanical motions of these single crystals during irradiation are triggered by solid-state photochemical reactions and accompanied by phase transformation. This Minireview summarizes recent developments in growing research into photoresponsive molecular crystals. The basic mechanisms of different kinds of photomechanical materials are described in detail; recent advances in photomechanical crystals for promising applications as smart materials are also highlighted.

Bioinspired Smart Materials for Directional Liquid Transport

Abstract: Bioinspired materials capable of driving liquid in a directional manner have wide potential applications in many chemical engineering processes, such as heat transfer, separation, microfluidics, and so on. Numerous natural materials and systems such as spider silk, cactus, shorebirds, desert beetles, butterfly wing, and Nepenthes alata have been serving as a rich source of inspirations in the area. During the last decades, great efforts have been devoted to design bioinspired smart materials for directional liquid transport. In this review, we begin by introducing several natural materials and systems with surface structural features contributing for their directional liquid transport property, followed by the basic concepts and theories about surface wettability, droplet motion, and driving forces with different structural features. Then, we summarize some typical applications of such bioinspired smart materials in industrial processes and chemical engineering, particularly in heat transfer, separation, ...

Mechanisms of triple-shape polymeric composites due to dual thermal transitions

Abstract: Shape memory polymers (SMPs) are a class of smart materials capable of fixing a temporary shape and recovering the permanent shape in response to environmental stimuli such as heat, electricity, irradiation, moisture, or magnetic field, among others. Recently, multi-shape SMPs, which are capable of fixing more than one temporary shape and recovering sequentially from one temporary shape to another and eventually to the permanent shape, have attracted increasing attention. In general, there are two approaches to achieve a multi-shape memory effect (m-SME): the first one requires the SMP to have a broad temperature range of thermomechanical transition, such as a broad glass transition. The second approach uses multiple transitions to achieve m-SME, most notably, using two distinct transition temperatures to obtain a triple-shape memory effect (t-SME). The recently reported approach for designing and fabricating triple-shape polymeric composites (TSPCs) provides a much larger degree of design flexibility by separately tuning the two functional components (matrix and fiber network) to achieve optimum control of properties. The triple-shape memory behavior demonstrated by a TSPC is studied in this paper. This composite is composed of an epoxy matrix, providing a rubber–glass transition to fix one temporary shape, and an interpenetrating crystallizable PCL fiber network providing the system the melt–crystal transition to fix a second temporary shape. A one-dimension (1D) model that combines viscoelasticity for amorphous shape memory polymers (the matrix) with a constitutive model for crystallizable shape memory polymers (the fiber network) is developed to describe t-SME. The model includes the WLF and Arrhenius equations to describe the glass transition of the matrix, and the kinetics of crystallization and melting of the fiber network. The assumption that the newly formed crystalline phase of the fiber network is initially in a stress-free state is used to model the mechanics of evolving crystallizable phases. Experiments including uniaxial tension, stress relaxation, and triple-shape memory testing were carried out for parameter identification. The model accurately captures t-SME exhibited in experiments. The stress and stored energy analysis during the shape memory cycle provides insight into the mechanisms of shape fixing for the two different temporary shapes, the nature of both recovery events, as well as a guidance on how to design transitions to achieve the desired behavior.