Smart Structural Materials Research Articles

A review of self-sensing ultra-high performance concrete: Towards next-generation smart structural materials

Today, the desired intelligent civil engineering structures urge the development of high-performance smart structural materials. Self-sensing ultra-high performance concrete (UHPC) emerged in 2014 based on the observation that the concrete structures rendered with randomly distributed conductive additives exhibit electromechanical effects under external loading, and the demand of UHPC from high-strength to sustainable, intelligent, and multifunctional. This smart structural material has since grown greatly and has been considered as one of the potential alternatives to ordinary self-sensing concrete. This paper presents a state-of-the-art review of self-sensing UHPC in terms of its raw materials, mixture design, manufacturing approaches, microstructural characteristics, mechanical properties, electrical resistivity, electromechanical properties, and applications, with a particular focus on stress-deformation/damage behaviour and changes in electrical conduction under external compression, tension, and bending. The novel uncertainties regarding electromechanical effects are thoroughly discussed from the perspective of the continuity of conductive network. Compared with ordinary self-sensing concrete, self-sensing UHPC exhibits significantly reduced porosity, exceptional strength, marginally lower stress/strain sensitivity, heightened damage sensitivity, insensitivity to humidity, and delayed cracking behaviour. In the end, this paper identifies research gaps, challenges, and recommendations in three aspects: (1) scale fabrication and cost control, (2) satisfactory and reliable properties, and (3) from smart structural materials to integrated components to civil engineering structures.

Effect of robotic weaving motion on mechanical and microstructural characteristics of wire arc additively manufactured NiTi shape memory alloy

Abstract The effect of robotic weaving motion on the crystallographic orientation, texture and mechanical properties of thin-walled nickel titanium shape memory alloy fabricated via wire arc additive manufacturing is studied. Crystallographic orientation analysis reveals that the weaving motion alters the epitaxial growth of grains, which reduces the fraction of (001) oriented grains but increased the fraction of (110) and (111) oriented grains. Moreover, the weaving motion increases the fraction of equiaxed grains and homogeneously distributes Ni4Ti3 phases. These changes improve the hardness and strength of the build and also introduce isotropy in mechanical properties. Results of the study reveal that arc weaving strategy has a great potential in achieving near isotropic tensile characteristics and is beneficial in terms of tailoring texture in building nickel titanium thin-walled smart material structures.

Programmable Complex Shape Changing of Polysiloxane Main-Chain Liquid Crystalline Elastomers.

Liquid crystal elastomers (LCEs) are shape-morphing materials whose large and reversible shape transformations are caused by the coupling between the mobile anisotropic properties of liquid crystal (LC) units and the rubber elastic of polymer networks. Their shape-changing behaviors under certain stimuli are largely directed by the LC orientation; therefore, various strategies have been developed to spatially modulate the LC alignments. However, most of these methods are limited as they require complex fabrication technologies or have intrinsic limitations in applicability. To address this issue, programmable complex shape changes in some LCE types, such as polysiloxane side-chain LCEs, thiol-acrylate main-chain LCEs, etc., were achieved by using a mechanical alignment programming process coupled with two-step crosslinking. Here, we report a polysiloxane main-chain LCE with programmable 2- and 3D shape-changing abilities that were created by mechanically programming the polydomain LCE with two crosslinking steps. The resulting LCEs exhibited a reversible thermal-induced shape transformation between the initial and programmed shapes due to the two-way memory between the first and second network structures. Our findings expand on the applications of LCE materials in actuators, soft robotics, and smart structures where arbitrary and easily programmed shape morphing is needed.

A review on 4D printing: Material structures, stimuli and additive manufacturing techniques

Advances in 3D printable smart materials are leading to the development of four-dimensional printing (4DP). Assembling stimulus-responsive materials and combining their functionalities into a single printed construct is an efficient way to improve the shape recovery capability of the smart structure. Three types of multi- material structures are reported in the literature: uniform distribution, gradient distribution, and special patterns. Smart materials have the unique property of changing their shape and properties when activated by external stimuli such as heat, water, or pressure. This article provides an overview of current smart material structures, types of stimuli, and three-dimensional printing (3DP) technologies used to manufacture 4D smart structures.

Development and Prospect of Smart Materials and Structures for Aerospace Sensing Systems and Applications.

The rapid development of the aviation industry has put forward higher and higher requirements for material properties, and the research on smart material structure has also received widespread attention. Smart materials (e.g., piezoelectric materials, shape memory materials, and giant magnetostrictive materials) have unique physical properties and excellent integration properties, and they perform well as sensors or actuators in the aviation industry, providing a solid material foundation for various intelligent applications in the aviation industry. As a popular smart material, piezoelectric materials have a large number of application research in structural health monitoring, energy harvest, vibration and noise control, damage control, and other fields. As a unique material with deformation ability, shape memory materials have their own outstanding performance in the field of shape control, low-shock release, vibration control, and impact absorption. At the same time, as a material to assist other structures, it also has important applications in the fields of sealing connection and structural self-healing. Giant magnetostrictive material is a representative advanced material, which has unique application advantages in guided wave monitoring, vibration control, energy harvest, and other directions. In addition, giant magnetostrictive materials themselves have high-resolution output, and there are many studies in the direction of high-precision actuators. Some smart materials are summarized and discussed in the above application directions, aiming at providing a reference for the initial development of follow-up related research.

Dynamic behavior of structural beams made of innovative smart concrete

The monitoring of structures and infrastructures is nowadays a pivotal activity for guaranteeing the safety of their users. Environmental conditions and exceptional events could affect their performance and integrity, shorten their service lives and even produce unexpected failures. The development of multifunctional smart structural materials with enhanced or novel properties could help to prevent or reduce damages and collapses. Among other building materials, concrete is particularly suitable for such improvements due to its composite nature. The authors have developed a smart concrete doped with carbon microfibers capable to sense variations of applied strains/stresses. The investigation started from the analysis of the performances of small samples, up to the manufacture of two full-scale RC beams. These applications at realistic scales are crucial for a diffuse use of such smart materials in civil engineering. The paper describes the novel characteristics of full-scale smart concrete beams, investigating their main physical, electrical, and monitoring capabilities. For this purpose, dynamic tests are carried out and discussed.

Self-Assembly of Nanowires: From Dynamic Monitoring to Precision Control.

Natural biomaterials often show ordered nanowire structures (ONWS) which display unique structural color or superior mechanical performance. Meanwhile, plenty of modern nanodevices with ONWS have flourished with activities focused on both basic and applied research. Manipulating synthetic nanowire (NW) from a disordered state to a hierarchically ordered structure via various assembly strategies brings about intriguing and exotic chemical/physical properties. In the past decades, many methods have been developed to assemble NWs and fabricate organized architectures, such as Langmuir-Blodgett interfacial assembly, spin-coating assembly, fluid-flow-induced assembly, and ice-template assembly. Nevertheless, for practical applications, large-scale and high-efficiency assembly strategies toward precise controlled architectures are largely limited by the lack understanding of assembly mechanisms. Especially, the manipulation principles and driving forces behind the state-of-art assembly strategies are still unclear. Besides, the lesser research attention on dynamic kinetics also impedes the revelation of the NW self-assembly mechanism. With the emergence of advanced in situ techniques, such as synchrotron-based X-ray techniques and in situ transmission electron microscopy (TEM), the dynamic monitoring of NW behavior in many practical environments becomes possible. In addition, the alignment direction and the stacking manner of NW film are of significance to the final performance. There is a lack of connection between the properties of one-dimensional nanoscale building blocks and the functionalities of the macro-assembly structures. To this end, dynamic monitoring is highly desired, which enables the precision modulation of NW assembly structure, leading to the discovery or prediction of new structures, novel properties, and performance optimization.In this Account, we aim to uncover the underlying kinetics of NW assembly or local reaction and mass transportation processes, as well as to build a solid connection from individual NWs to NW assembly structures with enhanced properties and eventually to macroscopic materials application. We first review the recent progress in state-of-art NW assembly strategies for diverse aligned structures according to the manipulation principle and the driving forces. To systematically review the NW self-assembly strategies, we categorize these strategies into three states: NWs on the liquid interface via surface tension, NW assembly in liquid via solution-shearing flow field, and NW assembly at the solid interval via physical repulsive force. Then, we introduce the existing advanced characterization techniques, including synchrotron-based X-ray scattering and in situ TEM, to dynamically monitor the intermediate states of the NW assembly and transport processes. The comprehensive understanding of this thermodynamic and kinetic mechanism facilitates the rational design, large scale, and high-efficiency fabrication of NW assemblies, thus promoting their applications in tailored optical-electrical electronics, smart electrochromic devices, electrocatalysis, structural materials, and chiral photonic crystals.

Investigation of Resilience of Eccentrically Braced Frames Equipped with Shape Memory Alloys

Abstract Nowadays, the use of smart materials in structures is a major concern to structural engineers. The act of benefiting from numerous advantages of these materials is the main objective of researches and studies focused on seismic and structural engineering. In the present study, in addition to the development of finite element models of several steel frames using ABAQUS software, the effect of shape memory alloys (SMAs) on superelastic behavior and the various types of eccentric braces will be checked. Moreover, it was observed that the use of SMAs within various types of bracing systems of steel frames leads to a decrease in the reduction factor of the frames. Also, the eccentric bracing in which SMAs are utilized in the middle of bracing led to the highest effect on reduction of lateral drift of the frames and decrease of reduction factor. The obtained results indicated that the application of smart materials led to increasing of strain energy and base shear of the first plastic hinge, which is followed by a decrease in the reduction factor of the frame.

Study of the Creation of Aircraft Structural Smart-Materials Based on Evaluation of Strength Properties

Study of the Creation of Aircraft Structural Smart-Materials Based on Evaluation of Strength Properties

Three-dimensional woven structural glass fiber/polytetrafluoroethylene (PTFE) composite antenna with superb integrity and electromagnetic performance

Integration of electronic devices into composites is imperative for the development of smart structural materials, which can address the structure limitations, such as the delamination of structures and degradation of electronic performances. In this study, the 3D orthogonal woven composite antenna (3DIMA) based on glass fiber and PTFE polymer were manufactured for the first time by multiple impregnation and sintering processes to obtain adequate PTFE penetration and good mechanical properties. Consequently, the as-produced 3D integrated microstrip antenna (3DIMA) showed good mechanical properties (bending, compression, impact strength) and electromagnetic performance with proper radiation pattern as well as gain value (1.3 dB), showing similar performance with conventional microstrip antenna. Besides, the simulated return losses and radiation patterns obtained from professional antenna software agreed well with the tested results. Furthermore, the 3DIMA maintained similar radiation pattern even under the low velocity impact with the kenitic engery of 15 J, exhibiting excellent structural integrity.

Sustainability of Civil Structures through the Application of Smart Materials: A Review.

Every year, structural flaws or breakdowns cause thousands of people to be harmed and cost billions of dollars owing to the limitations of design methods and materials to withstand extreme earthquakes. Since earthquakes have a significant effect on sustainability factors, there is a contradiction between these constraints and the growing need for more sustainable structures. There has been a significant attempt to circumvent these constraints by developing various techniques and materials. One of these viable possibilities is the application of smart structures and materials such as shape memory and piezoelectric materials. Many scholars have examined the use of these materials and their structural characteristics up to this point, but the relationship between sustainability considerations and the deployment of smart materials has received little attention. Therefore, through a review of previous experimental, numerical, and conceptual studies, this paper attempts to draw a more significant relationship between smart materials and structural sustainability. First, the significant impact of seismic events on structural sustainability and its major aspects are described. It is then followed by an overview of the fundamentals of smart material’s behaviour and properties. Finally, after a comprehensive review of the most recent applications of smart materials in structures, the influence of their deployment on sustainability issues is discussed. The findings of this study are intended to assist researchers in properly addressing sustainability considerations in any research and implementation of smart materials by establishing a more explicit relationship between these two concepts.

An Detailed review on Applications of Smart Materials in Structural Engineering

Smart structural materials are a fundamental aspect that requires critical analysis in in structural engineering. This research contribution considers two vital crystal structures: Martensite and Austenite with their characteristic variations under different temperatures. From this research, it is seen the smart materials presents two vital features, which are distinguished from typical steels. The first one is the memory shape and the second one is super-elasticity. All of these properties can suit various applications in structural engineering e.g. dual actuators, self-rehabilitation and pre-stress bars. This research is purposed at analyzing the applications of smart materials in the field of structural engineering through the focus of relevant literature reviews, typical collection of data and major mechanic elements of smart materials. In axial tension evaluation, the curve for force and extension and the strain and stress curves of super-elasticity and Shape Memory Alloy (SMA) materials have been considered. The beam experiment with the superelasticity materials considered as the bars for reinforcement has been considered as well. This contribution provides the initial step of evaluation of the wide-range application of smart materials in the field of structural engineering.

Foundations for Soft, Smart Matter by Active Mechanical Metamaterials.

Emerging interest to synthesize active, engineered matter suggests a future where smart material systems and structures operate autonomously around people, serving diverse roles in engineering, medical, and scientific applications. Similar to biological organisms, a realization of active, engineered matter necessitates functionality culminating from a combination of sensory and control mechanisms in a versatile material frame. Recently, metamaterial platforms with integrated sensing and control have been exploited, so that outstanding non‐natural material behaviors are empowered by synergistic microstructures and controlled by smart materials and systems. This emerging body of science around active mechanical metamaterials offers a first glimpse at future foundations for autonomous engineered systems referred to here as soft, smart matter. Using natural inspirations, synergy across disciplines, and exploiting multiple length scales as well as multiple physics, researchers are devising compelling exemplars of actively controlled metamaterials, inspiring concepts for autonomous engineered matter. While scientific breakthroughs multiply in these fields, future technical challenges remain to be overcome to fulfill the vision of soft, smart matter. This Review surveys the intrinsically multidisciplinary body of science targeted to realize soft, smart matter via innovations in active mechanical metamaterials and proposes ongoing research targets that may deliver the promise of autonomous, engineered matter to full fruition.

Computational design optimization of a smart material shape changing building skin tile

The development and evaluation of a computational approach for optimal design of a smart material shape changing building skin is presented and numerically evaluated. Specifically, a unique shape-based approach is utilized to create an optimization approach to identify the activation and actuation mechanisms to minimize the difference between a desired shape and the estimated morphed shape. Three potential metrics of shape difference are considered and their capability to facilitate an efficient optimization process leading to accurate shape matching is evaluated. Details of the optimal design framework are presented, particularly focusing on the shape difference metrics as well as the strategy to parameterize the activation of the smart material. In particular, the parameterization strategy is a unique approach to easily integrate controllable localized activation within a smart material structure in a generally applicable way that does not limit the design search space. A series of numerical design examples are presented based on the concept of a smart material (e.g., shape memory polymer) shape changing tile that can be activated and actuated in a variety of ways to achieve desirable surface wrinkle patterns. These numerical design examples are applied to both 2D and 3D problems and consider a variety of parameterizations and target shapes. Results indicate that the shape-based approach can consistently determine the mechanisms of morphing needed to accurately match a target shape. Furthermore, it is shown that localized material activation can lead to not only a more accurate shape but also requires less energy and actuation devices to do so.

Semi-analytic modelling of transversely isotropic magneto-electro-elastic materials under frictional sliding contact

Functionally graded magneto-electro-elastic (FGMEE) materials has been increasingly used in engineering applications, particularly in smart material or intelligent structure systems. This paper proposes a semi-analytical approach for sliding frictional contact problem between a rigid insulating sphere and a transversely isotropic FGMEE film and half-space based on frequency response functions (FRFs). Multilayered approximation is used to model the functionally graded material (FGM), and the FRFs for each MEE layer are derived explicitly. The unknown coefficients in FRFs are formulated by two matrix equations, and their efficient solution process is proposed. Based on the obtained FRFs, a highly efficient semi-analytical model (SAM) is developed which is able to solve the three-dimensional frictional contact of FGMEE materials with arbitrary layer designs. The model is validated with finite element method and the literature. Furthermore, the pressure/stress distribution and electric/magnetic potential are studied in different FGM designs to investigate the influence of material layout.

Hierarchical hexachiral auxetics for large elasto-plastic deformation

To improve the auxeticity and isotropy behavior of standard hexachiral structures at large elasto-plastic deformation, the authors have earlier proposed a modified hexachiral structure with wavy ligaments (Zhu et al 2018 Smart Material Structures 27 055001). While a significant improvement was achieved with the proposed modified chiral structure, it was reported therewith that its auxeticity and isotropy degrade rapidly at large tensile deformation, in contrast to the excellent performance in compression. The present work builds upon the basic structure proposed in (Zhu et al 2018 Smart Material Structures 27 055001), to further improve the mechanical behavior in tension, without compromising the already excellent performance achieved at large compressive deformation. To reduce the distortion of the central ring in a hexachiral structure—the deformation mechanism that degrades its mechanical performance in tension—a hierarchical hexachiral structure is proposed, where a standard hexachiral structure reinforces the central ring of the basic hexachiral structure in (Zhu et al 2018 Smart Material Structures 27 055001). A significant improvement in mechanical behavior over the basic structure is demonstrated, with potential applications in a protective system.

Carbon fiber reinforced shape memory epoxy composites with superior mechanical performances

For the shape memory polymers' (SMPs) applications in demanding, high performance scenarios are usually limited by their poor mechanical performances during shape transformation. In this work, shape memory epoxy composites (SMEPCs) with superior mechanical properties are fabricated by adding various short and continuous carbon fibers (CFs) into neat shape memory epoxies (SMEPs) matrix. The resultant SMEPC's storage modulus (E’) at room temperature is as high as 37 GPa, and the maximum recovery force exceeds 4.4 GPa, with good shape memory capabilities. These properties are at least an order of magnitude higher than those in existing typical SMP systems. The excellent mechanical properties of the fibers and their ability to retard crack propagation in the matrix are believed to play an important role in achieving high moduli below and above the shape-memory triggering temperature. The potential applications of such SMEPCs are demonstrated with wind blades. Experimental results and numerical models regarding air flow velocity variation as initiated by shape change in the blades indicate that our SMEPCs can sustain continuous stable mechanical state and provide variable wind speeds. These CF reinforced SMEPCs can be employed as smart structural materials to automatically switch shapes in response to the change in environment, such as those seen in aero foils and energy harvesters.

Damage self-sensing behavior of carbon nanofiller reinforced polymer composites with different conductive network structures

Multi-walled carbon nanotube (MWCNTs) and graphene nanoplatelet (GNPs) filled high-density polyethylene (HDPE) composites with randomly dispersed (DCN) and segregated (SCN) conductive network structures were fabricated by a solution-assisted mixing method. The damage self-sensing behavior of the resulting composites was investigated via in situ electrical-mechanical measurements. The results show that nanofiller type and conductive network structure significantly influence the damage self-sensing behavior of the composites. The relative resistance change (RRC) of HDPE/MWCNT composites during tensile deformation can be divided into three stages. Compared to HDPE/MWCNT composites with DCN structures, more robust conductive networks are formed in SCN structures, resulting in smaller RRC. The self-damage sensing behavior of all HDPE/GNP composites follows a similar trend, starting with a quasi-linear increase in RRC followed by a sudden rise induced by brittle fracture of the material. Nanofiller content was also found to affect the damage self-sensing behavior of the composites with a higher nanofiller loading corresponding to a lower damage sensing sensitivity. A modeling study based on tunneling theory was also conducted to further analyze the mechanism. In addition, the tensile properties of the composites were measured. This study provides some important information for development of smart structural materials.

Raman Strain Sensing and Interfacial Stress Transfer of Hierarchical CNT-Coated Carbon Fibers

Hierarchical reinforcements of carbon fibers (CFs) coated with carbon nanotubes (CNTs) were produced via two different methodologies, namely chemical vapor deposition (CVD) and wet chemical treatment. These advanced smart structural materials are possible candidates for inherent strain sensing and improved interfacial properties when incorporated in the volume of structural fiber-reinforced polymer composites. The morphology and wetting properties of the hierarchical CFs were evaluated via SEM and contact angle measurements. Enhanced values in the strain-induced Raman sensing ability of the hierarchical reinforcement produced via CVD in comparison with the uncoated fibers were measured at single fiber level. The residual stress transfer profiles of both the hierarchical and the uncoated carbon fibers were also evaluated using the Raman spectroscopy in order to evaluate the phase interaction in the hierarchical structure. Compressive residual stresses in the order of 1.5 GPa were found to act on the CF surfaces, while tensile residual stresses were measured for both the CNT-coated systems. The effects of the preparation process of the CNT coatings on the residual stress profiles were also prominent, with the CVD-grown coatings resulting in higher tensile residual stresses, 1.76 GPa instead of 1.22 GPa for the coatings produced via wet chemical treatment. The change in the residual stress profiles established the interaction between the CFs and the CNTs via an anchoring mechanism which significantly altered the stress field at the vicinity of the interface.

3D mixed micromechanics-FEM modeling of piezoresistive carbon nanotube smart concrete

Within the novel approach for structural health monitoring of civil engineering structures based on smart self-sensing structural materials, Carbon NanoTube (CNT)-reinforced cement-based composites, often termed “smart concretes”, have drawn rising interest. These composites exhibit self-sensing capabilities resulting in measurable variations of their electrical properties under applied mechanical deformations. This, along with the similarity between these composites and conventional structural concrete, makes it possible to devise cost-efficient distributed monitoring systems for large-scale Reinforced Concrete (RC) structures. While several papers in the literature have focused on pilot applications of smart concrete strain sensors embedded into large RC components, the response of these sensors is not yet fully understood at the fundamental physical level and, as a consequence, their output is not properly interpreted. In order to shed some light on this issue, previous work by the authors focused on laterally unconstrained uni-axial loading conditions. This work extends the previous studies by presenting a mixed micromechanics and finite element approach for the analysis of CNT-reinforced composites subjected to arbitrary strain states. The two mechanisms that contribute to the electrical conductivity of CNT-reinforced composites, namely electron hopping and conductive networking, are contemplated within a percolation framework in the micromechanics model. On the basis of the micromechanics model, the 3D piezoresistivity matrix is determined, for the first time in the literature, by means of virtual dilation and distortion tests. Afterwards, the electro-mechanical modeling of three-dimensional composite elements is conducted by a multi-physics finite element code. The potential of the presented approach is illustrated by extensive parametric analyses, as well as a comparison against experimental data, including application of the mixed micromechanics-finite-element multi-physics formulation for electro-mechanical modeling of three-dimensional elements.