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Abstract Shape‐memory polymers (SMPs) are smart materials that change shape when exposed to stimuli and have various applications in different fields due to their unique properties. Light, as a kind of electromagnetic radiation, plays an important role in understanding the structure‐property relations of SMPs, preparing original shapes, using them as non‐contact stimuli sources, and tuning the optical properties of SMPs. This review provides a comprehensive review of the involvement of light in structure‐preparation‐stimuli‐application of SMPs. The review is divided into four sections. First, applications of optical/spectroscopic approaches that provide information for understanding structure‐property relations in SMPs, especially during programming and recovery. Second, describes how to build SMPs with light, including different photochemical reactions and 3D photocuring technologies. Third, discusses how light is used to trigger the shape change of SMPs through both photochemical and photothermal mechanisms. Last, focuses on how to take advantage of the shape‐memory effect to tune the optical characteristics of polymers, including various structures of SMP color‐changing materials and their synthetic strategies. Future research could focus on developing efficient photothermal fillers, new 3D printing techniques for SMPs, exploring their use in biomedical and wearable devices, and optimizing SMPs for industrial applications.

The global production of macadamia nuts has witnessed a significant increase, resulting in the accumulation of large quantities of discarded nutshells. These nutshells possess the properties of remarkable hardness and toughness, which are comparable to those of aluminum. Incorporating natural fillers to enhance the properties of composite materials for various applications, including light duty, structural, and semi-structural purposes, is a common practice. Given their inherent hardness and toughness, macadamia nutshells present an intriguing choice as fillers, provided that the manufacturing conditions are economically viable. With the urgent need to shift toward natural fillers and reduce reliance on synthetics, exploring macadamia nutshells as components of natural fiber composites becomes imperative. This review aims to comprehensively examine the existing body of knowledge on macadamia nutshells and their bio-synthetic polymer composites, highlighting key research findings, achievements, and identifying knowledge gaps. Furthermore, the article will outline prospective areas of focus for future research endeavors in this domain, aligning with the universal goal of minimizing synthetic materials.

There is a need to create next-generation polymer composites having high property, unique function, and intelligent behaviors, such as shape memory effect (SME) and self-healing (SH) capability. Rare earth complexes can provide luminescence for polymers, and their dispersion is highly affected by ligand structures. Here, we created three different REOCs with different ligands before studying the effects of ligands on REOC dispersion in polyurea–urethane (PUU) with disulfide bonds in main chains. In addition, the effects of different REOCs on mechanical properties, luminescent functions, and intelligent behaviors of PUU composites were studied. The results showed that REOC I (Sm(TTA)3phen: TTA, thenoyltrifluoroacetone; phen, 1,10-phenanthroline) has incompatible ligands with the PUU matrix. REOC I and REOC III (Sm(BUBA)3phen: BUBA, 4-benzylurea-benzoic acid) with amine and urea groups facilitate their dispersion. It was REOC III that helped the maintenance of mechanical properties of PUU composites due to the good dispersion and the needle-like morphologies. Due to more organic ligands of REOC III, the fluorescence intensity of composite materials is reduced. The shape recovery ratio of the composite was not as good as that of pure PUU when a large amount of fillers was added. Besides, REOC I reduced the self-healing efficiency of PUU composites due to poor dispersion, and the other two REOCs increased the self-healing efficiency. The results showed that ligands in REOCs are important for their dispersion in the PUU matrix. The poor dispersion of REOC I is unbeneficial for mechanical properties and intelligent behavior. The high miscibility of REOC II (Sm(PABA)3phen: PABA, 4-aminobenzoic acid) decreases mechanical properties as well but ensures the good shape recovery ratio and self-healing efficiency. The mediate miscibility and needle-like morphology of REOC III are good for mechanical properties. The shape recovery ratio, however, was decreased.

A considerable amount of research has focused on monitoring structural damage using Structural Health Monitoring (SHM) technologies, which has had recent advances. However, it is important to note the challenges and unresolved problems that disqualify currently developed monitoring systems. One of the frontline SHM technologies, the Electromechanical Impedance (EMI) technique, has shown its potential to overcome remaining problems and challenges. Unfortunately, the recently developed neural network algorithms have not shown significant improvements in the accuracy of rate and the required processing time. In order to fill this gap in advanced neural networks used with EMI techniques, this paper proposes an enhanced and reliable strategy for improving the structural damage detection via: (1) Savitzky–Golay (SG) filter, using both first and second derivatives; (2) Probabilistic Neural Network (PNN); and, (3) Simplified Fuzzy ARTMAP Network (SFAN). Those three methods were employed to analyze the EMI data experimentally obtained from an aluminum plate containing three attached PZT (Lead Zirconate Titanate) patches. In this present study, the damage scenarios were simulated by attaching a small metallic nut at three different positions in the aluminum plate. We found that the proposed method achieves a hit rate of more than 83%, which is significantly higher than current state-of-the-art approaches. Furthermore, this approach results in an improvement of 93% when considering the best case scenario.

Evaluation of the thoracic injury due to blunt impacts during the contact and collision sports activity is very crucial for the development and validation of the chest protectors for the athletes and safety balls of the sports such as cricket, baseball, lacrosse and the golf. In order to evaluate the thoracic injury due to solid sports ball impacts, a series of nonlinear transient dynamic, finite element simulations were carried out by impacting the FE model surrogate of the thorax “MTHOTA” (Mechanical THOrax for Trauma Assessment) with a baseball (both soft-core and synthetic) and a cricket ball at impact speed of 10 - 45 m/s, with an increment of 5 m/s. Only for the impact speed for which measured VCmax was 1 m/s, further simulations were carried out by introducing the ball spin (1000 - 8000 rpm, with an increment of 1000 rpm). Soft-core baseball, synthetic baseball and cricket ball impacts have caused VCmax = 1.0 m/s (25% probability for AIS3+ injuries) at impact speeds of 30.7 m/s, 27.9 m/s and 23.2 m/s respectively. For the normal impacts, spin (about impact direction and two directions perpendicular to the impact direction) of the ball has got no impact on the blunt thoracic trauma. At usual pitching speeds, soft-core baseball didn’t offer any safety and performance point of view, it was found to be as bad as synthetic baseball. Deflection response of the MTHOTA and the solid sports ball - MTHOTA energy interactions have yielded VCmax ∝ [(TEmax)1748, (Time rate of KEmax)0.9489, (Deformation velocitymax)2.3227, and (Impact velocitybaseball)2.548]. Similarly, Stored Energy Criterion and Energy Storing Rate Criterion (Wang, 1989) have yielded the relations Peak stored energy ∝ (Peak deflection MTHOTA)1.253 and Rate of peak stored energy ∝ (Peak deflection MTHOTA × Rate of peak deflection MTHOTA)0.5554.

Without being able to evaluate blunt thoracic trauma in terms of an acceptable injury criterion, it is not possible to develop or validate non-lethal projectiles, bullet proof vests and chest protectors for sports personnel etc. In order for the assessment of the blunt trauma caused by high speed projectiles, a novel design of a mechanical surrogate of the thorax (Mechanical THOrax for Trauma Assessment: MTHOTA) was conceptualized. An iterative impact analyses in the virtual testing environment were carried out by impacting the finite element model of the mechanical thorax with 37 mm diameter, 100 mm long wooden baton weighing 140 grams (20 m/s and 40 m/s impact speeds) and 37 mm diameter, 28.5 mm long wooden baton weighing 30 grams with 60 m/s impact speed. From the output of every simulation, force dynamic response (force-time), deflection dynamic response (deflection-time) and force-deflection response were elicited and compared with the corresponding human response corridors developed by Wayne State University's researchers. By suitably changing the design parameters of the mechanical surrogate, simulation iterations were continued till the responses were correlated with the human response corridors. Values of viscous criterion (VCmax), product of maximum chest deflection and the rate at which chest deforms, obtained from MTHOTA were in very good agreement with those obtained from the cadaveric test data. The methodology, concept and validation of the MTHOTA have been presented in this paper.