3D-Printed Polycaprolactone-Based Containing Calcium Zirconium Silicate: Bioactive Scaffold for Accelerating Bone Regeneration.

There is an essential clinical need to develop rapid process scaffolds to repair bone defects. The current research presented the development of calcium zirconium silicate/polycaprolactone for bone tissue engineering utilising melt extrusion-based 3D printing. Calcium zirconium silicate (CZS) nanoparticles were added to polycaprolactone (PCL) porous scaffolds to enhance their biological and mechanical properties, while the resulting properties were studied extensively. No significant difference was found in the melting point of the samples, while the crystallisation temperature points of the samples containing bioceramic increased from 36.1 to 40.2 °C. Thermal degradation commenced around 350 °C for all materials. According to our results, increasing the CZS content from 0 to 40 wt.% (PC40) in porous scaffolds (porosity about 55-62%) improved the compressive strength from 2.8 to 10.9 MPa. Furthermore, apatite formation ability in SBF solution increased significantly by enhancing the CZS percentage. According to MTT test results, the viability of MG63 cells improved remarkably (~29%) in PC40 compared to pure PCL. These findings suggest that a 3D-printed PCL/CZS composite scaffold can be fabricated successfully and shows great potential as an implantable material for bone tissue engineering applications.

3D and 4D Printing of PETG-ABS-Fe3O4 Nanocomposites with Supreme Remotely Driven Magneto-Thermal Shape-Memory Performance.

This study introduces novel PETG-ABS-Fe3O4 nanocomposites that offer impressive 3D- and 4D-printing capabilities. These nanocomposites can be remotely stimulated through the application of a temperature-induced magnetic field. A direct granule-based FDM printer equipped with a pneumatic system to control the output melt flow is utilized to print the composites. This addresses challenges associated with using a high weight percentage of nanoparticles and the lack of control over geometry when producing precise and continuous filaments. SEM results showed that the interface of the matrix was smooth and uniform, and the increase in nanoparticles weakened the interface of the printed layers. The ultimate tensile strength (UTS) increased from 25.98 MPa for the pure PETG-ABS sample to 26.3 MPa and 27.05 MPa for the 10% and 15% Fe3O4 nanocomposites, respectively. This increase in tensile strength was accompanied by a decrease in elongation from 15.15% to 13.94% and 12.78%. The results of the shape-memory performance reveal that adding iron oxide not only enables indirect and remote recovery but also improves the shape-memory effect. Improving heat transfer and strengthening the elastic component can increase the rate and amount of shape recovery. Nanocomposites containing 20% iron oxide demonstrate superior shape-memory performance when subjected to direct heat stimulation and a magnetic field, despite exhibiting low print quality and poor tensile strength. Smart nanocomposites with magnetic remote-control capabilities provide opportunities for 4D printing in diverse industries, particularly in medicine, where rapid speed and remote control are essential for minimally invasive procedures.

Multiscale modeling of unfolding and bond dissociation of rubredoxin metalloprotein.

Mechanical properties of proteins that have a crucial effect on their operation. This study used a molecular dynamics simulation package to investigate rubredoxin unfolding on the atomic scale. Different simulation techniques were applied, and due to the dissociation of covalent/hydrogen bonds, this protein demonstrates several intermediate states in force-extension behavior. A conceptual model based on the cohesive finite element method was developed to consider the intermediate damages that occur during unfolding. This model is based on force-displacement curves derived from molecular dynamics results. The proposed conceptual model is designed to accurately identify bond rupture points and determine the associated forces. This is achieved by conducting a thorough comparison between molecular dynamics and cohesive finite element results. The utilization of a viscoelastic cohesive zone model allows for the consideration of loading rate effects. This rate-dependent model can be further developed and integrated into the multiscale modeling of large assemblies of metalloproteins, providing a comprehensive understanding of mechanical behavior while maintaining a reduced computational cost.

Various FDM Mechanisms Used in the Fabrication of Continuous-Fiber Reinforced Composites: A Review.

Fused Deposition Modeling (FDM) is an additive manufacturing technology that has emerged as a promising technique for fabricating 3D printed polymers. It has gained attention recently due to its ease of use, efficiency, low cost, and safety. However, 3D-printed FDM components lack sufficient strength compared to those made using conventional manufacturing methods. This low strength can be mainly attributed to high porosity and low sinterability of layers and then to the characteristics of the polymer used in the FDM process or the FDM process itself. Regarding polymer characteristics, there are two main types of reinforcing fibers: discontinuous (short) and continuous. Continuous-fiber reinforced composites are becoming popular in various industries due to their excellent mechanical properties. Since continuous reinforcing fibers have a more positive effect on increasing the strength of printed parts, this article focuses primarily on continuous long fibers. In addition to polymer characteristics, different mechanisms have been developed and introduced to address the issue of insufficient strength in 3D-printed FDM parts. This article comprehensively explains two main FDM mechanisms: in-situ fusion and ex-situ prepreg. It also provides relevant examples of these mechanisms using different reinforcing elements. Additionally, some other less frequently utilized mechanisms are discussed. Each mechanism has its own advantages and disadvantages, indicating that further development and modification are needed to increase the strength of 3D-printed FDM parts to be comparable to those produced using traditional methods.

Enhancing the Thermal Performance of Shape Memory Polymers: Designing a Minichannel Structure.

This research proposes a numerical approach to improve the thermal performance of shape memory polymers (SMPs) while their mechanical properties remain intact. Sixteen different 3D minichannel structures were numerically designed to investigate the impact of embedded water flow in microchannel networks on the thermal response and shape recovery of SMPs. This work employs two approaches, each with different physics: approach A focuses on solid mechanics analysis and, accordingly, thermal analysis in solids without considering the fluid. approach B tackles solid and fluid mechanics analysis and thermal analysis in both solid and fluid subdomains, which inherently calls for fluid-structure coupling in a uniform procedure. Finally, the results of these two approaches are compared to predict the SMP's thermal and mechanical behavior. The structural designs are then analyzed in terms of their shape recovery speed, recovery ratio, and recovery parameters. The results indicate that isotropic structures thermally outperform their anisotropic counterparts, exhibiting improved thermal characteristics and faster shape recovery. Additionally, it was observed that polymeric structures with a low volume fraction of embedded branches thermally perform efficiently. The findings of this study predict that the geometrical angle between the main branch and sub-branches of SMP favorably impacts the enhancement of thermal characteristics of the structure, accelerating its shape recovery. Approach B accelerates the shape recovery rate in SMPs due to fluid flow and uniform heat transfer within the structures.

In silico optimization of aligned fiber electrodes for dielectric elastomer actuators.

Dielectric elastomer actuators (DEAs) exhibit fast actuation and high efficiencies, enabling applications in optics, wearable haptics, and insect-scale robotics. However, the non-uniformity and high sheet resistance of traditional soft electrodes based on nanomaterials limit the performance and operating frequency of the devices. In this work, we computationally investigate electrodes composed of arrays of stiff fiber electrodes. Aligning the fibers along one direction creates an electrode layer that exhibits zero stiffness in one direction and is predicted to possess high and uniform sheet resistance. A comprehensive parameter study of the fiber density and dielectric thickness reveals that the fiber density primary determines the electric field localization while the dielectric thickness primarily determines the unit cell stiffness. These trends identify an optimal condition for the actuation performance of the aligned electrode DEAs. This work demonstrates that deterministically designed electrodes composed of stiff materials could provide a new paradigm with the potential to surpass the performance of traditional soft planar electrodes.

Direct Pellet Three-Dimensional Printing of Polybutylene Adipate-co-Terephthalate for a Greener Future.

The widespread use of conventional plastics in various industries has resulted in increased oil consumption and environmental pollution. To address these issues, a combination of plastic recycling and the use of biodegradable plastics is essential. Among biodegradable polymers, poly butylene adipate-co-terephthalate (PBAT) has attracted significant attention due to its favorable mechanical properties and biodegradability. In this study, we investigated the potential of using PBAT for direct pellet printing, eliminating the need for filament conversion. To determine the optimal printing temperature, three sets of tensile specimens were 3D-printed at varying nozzle temperatures, and their mechanical properties and microstructure were analyzed. Additionally, dynamic mechanical thermal analysis (DMTA) was conducted to evaluate the thermal behavior of the printed PBAT. Furthermore, we designed and printed two structures with different infill percentages (40% and 60%) to assess their compressive strength and energy absorption properties. DMTA revealed that PBAT's glass-rubber transition temperature is approximately -25 °C. Our findings demonstrate that increasing the nozzle temperature enhances the mechanical properties of PBAT. Notably, the highest nozzle temperature of 200 °C yielded remarkable results, with an elongation of 1379% and a tensile strength of 7.5 MPa. Moreover, specimens with a 60% infill density exhibited superior compressive strength (1338 KPa) and energy absorption compared with those with 40% infill density (1306 KPa). The SEM images showed that with an increase in the nozzle temperature, the quality of the print was greatly improved, and it was difficult to find microholes or even a layered structure for the sample printed at 200 °C.

Application of the Quality by Design Concept (QbD) in the Development of Hydrogel-Based Drug Delivery Systems.

Hydrogel-based drug delivery systems are of interest to researchers for many reasons, such as biocompatibility, high diversity, and the possibility of administration from different routes. Despite these advantages, there are challenges, such as controlling the drug release rate and their mechanical properties during the manufacturing of these systems. For this reason, there is a need for the production and development of such drug delivery systems with a scientific strategy. For this reason, the quality by design (QbD) approach is used for the development of drug delivery systems. This approach, by identifying the most effective factors in the manufacturing of pharmaceutical products and controlling them, results in a product with the desired quality with the least number of errors. In this review article, an attempt is made to discuss the application and method of applying this approach in the development of hydrogel-based drug delivery systems. So that for the development and production of these systems, according to the type of drug delivery system, what target characteristics should be considered (QTPP) and what factors, such as material properties (CMA) or process parameters (CPP), should be taken into account to reach the critical quality attributes of the product (CQA).

Tablet Geometry Effect on the Drug Release Profile from a Hydrogel-Based Drug Delivery System.

In order to achieve the optimal level of effectiveness and safety of drugs, it is necessary to control the drug release rate. Therefore, it is important to discover the factors affecting release profile from a drug delivery system. Geometry is one of these effective factors for a tablet-shaped drug delivery system. In this study, an attempt has been made to answer a general question of how the geometry of a tablet can affect the drug release profile. For this purpose, the drug release process of theophylline from two hundred HPMC-based tablets, which are categorized into eight groups of common geometries in the production of oral tablets, was simulated using finite element analysis. The analysis of the results of these simulations was carried out using statistical methods including partial least squares regression and ANOVA tests. The results showed that it is possible to predict the drug release profile by knowing the geometry type and dimensions of a tablet without performing numerous dissolution tests. Another result was that, although in many previous studies the difference in the drug release profile from several tablets with different geometries was interpreted only by variables related to the surface, the results showed that regardless of the type of geometry and its dimensions, it is not possible to have an accurate prediction of the drug release profile. Also, the results showed that without any change in the dose of the drug and the ingredients of the tablet and only because of the difference in geometry type, the tablets significantly differ in release profile. This occurred in such a way that, for example, the release time of the entire drug mass from two tablets with the same mass and materials but different geometries can be different by about seven times.

pH-Sensitive Hydrogel Bilayers: Investigation on Transient Swelling-Induced Bending through Analytical and FEM Approaches.

pH-responsive hydrogels are recognized as versatile sensors and actuators due to their unique time-dependent properties. Specifically, pH-sensitive hydrogel-based bilayers exhibit remarkable bending capabilities when exposed to pH-triggered swelling. This study introduces a semi-analytical technique that combines non-linear solid mechanics with ionic species transport to investigate the bending behavior of such bilayers. The technique is validated through numerical simulations, exploring the influence of kinetic and geometric properties on bilayer behavior. The results highlight the significance of the interfacial region, particularly in configurations with lower hydrogel geometric ratios, which are susceptible to rupture. The study also uncovers the benefits of a lower hydrogel layer ratio in improving the swelling rate and final deflection, with a stronger effect observed in the presence of a buffer solution. Additionally, the compressibility of the elastomer contributes to the durability of the final bent shape. These findings enhance our understanding of pH-sensitive hydrogel-based bilayers and offer valuable insights for their design and optimization in diverse applications.

Unraveling the effect of hydrogenation on the mechanical properties of coiled carbon nanotubes: a molecular dynamics study.

With the increase in the utilization of nanomaterials in daily life, carbon nanostructures have received the attention of many researchers due to their special physical, chemical, and electrical properties. Chemical functionalization is one of the common methods to improve the thermomechanical properties of carbon nanomaterials used for specific applications. In this research, the effect of functionalization with hydrogen atoms on the mechanical properties of coiled carbon nanotubes with different geometrical dimensions has been examined. In addition, the mechanical properties of CCNTs with random and patterned distributions of hydrogen atoms have been investigated. The random distribution of hydrogen atoms up to 10% causes a sharp decrease in the mechanical properties of CCNTs such as the Young's modulus and spring constant, and increasing the percentage of H-coverage by more than 10% does not cause a significant effect on the mentioned properties. Also, unlike other carbon nanostructures, the stretchability of most CCNTs increases by increasing the percentage of hydrogenation beyond 30 percent. On investigating the effect of temperature on the properties of hydrogenated CCNTs, the temperature increase does not affect the Young's modulus and spring constant, and also there is no explicit relationship between their stretchability and temperature. Exploring the mechanical behavior of hydrogen-functionalized CCNTs via the tensile test and also how their mechanical properties change compared to those of pure CCNTs can help researchers in many applications.

Design of Refractory Alloys for Desired Thermal Conductivity via AI-Assisted In-Silico Microstructure Realization.

A computational methodology based on supervised machine learning (ML) is described for characterizing and designing anisotropic refractory composite alloys with desired thermal conductivities (TCs). The structural design variables are parameters of our fast computational microstructure generator, which were linked to the physical properties. Based on the Sobol sequence, a sufficiently large dataset of artificial microstructures with a fixed volume fraction (VF) was created. The TCs were calculated using our previously developed fast Fourier transform (FFT) homogenization approach. The resulting dataset was used to train our optimal autoencoder, establishing the intricate links between the material's structure and properties. Specifically, the trained ML model's inverse design of tungsten-30% (VF) copper with desired TCs was investigated. According to our case studies, our computational model accurately predicts TCs based on two perpendicular cut-section images of the experimental microstructures. The approach can be expanded to the robust inverse design of other material systems based on the target TCs.

Finite Bending of Fiber-Reinforced Visco-Hyperelastic Material: Analytical Approach and FEM.

This paper presents a new anisotropic visco-hyperelastic constitutive model for finite bending of an incompressible rectangular elastomeric material. The proposed approach is based on the Mooney-Rivlin anisotropic strain energy function and non-linear visco-hyperelastic method. In this study, we aim to examine the mechanical response of a reinforced viscoelastic rectangular bar with a group of fibers under bending. Anisotropic materials are typically composed of one (or more) family of reinforcing fibers embedded within a soft matrix material. This operation may lead to an enhancement in the strength and stiffness of soft materials. In addition, a finite element simulation is carried out to validate the accuracy of the analytical solution. In this research, the well-known stress relaxation test, as well as the multi-step relaxation test, are examined both analytically and numerically. The results obtained from the analytical solution are found to be in good agreement with those from the finite element method. Therefore, it can be deduced that the proposed model is competent in describing the mechanical behavior of fiber-reinforced materials when subjected to finite bending deformations.

A New Strategy for Achieving Shape Memory Effects in 4D Printed Two-Layer Composite Structures.

In this study, a new strategy and design for achieving a shape memory effect (SME) and 4D printed two-layer composite structures is unveiled, thanks to fused deposition modeling (FDM) biomaterial printing of commercial filaments, which do not have an SME. We used ABS and PCL as two well-known thermoplastics, and TPU as elastomer filaments that were printed in a two-layer structure. The thermoplastic layer plays the role of constraint for the elastomeric layer. A rubber-to-glass transition of the thermoplastic layer acts as a switching phenomenon that provides the capability of stabilizing the temporary shape, as well as storing the deformation stress for the subsequent recovery of the permanent shape by phase changing the thermoplastic layer in the opposite direction. The results show that ABS-TPU had fixity and recovery ratios above 90%. The PCL-TPU composite structure also demonstrated complete recovery, but its fixity was 77.42%. The difference in the SME of the two composite structures is related to the transition for each thermoplastic and programming temperature. Additionally, in the early cycles, the shape-memory performance decreased, and in the fourth and fifth cycles, it almost stabilized. The scanning electron microscopy (SEM) photographs illustrated superior interfacial bonding and part integrity in the case of multi-material 3D printing.

Silk Fibroin Hydrogel Reinforced With Magnetic Nanoparticles as an Intelligent Drug Delivery System for Sustained Drug Release.

Due to the well-known biocompatibility, tunable biodegradability, and mechanical properties, silk fibroin hydrogel is an exciting material for localized drug delivery systems to decrease the therapy cost, decrease the negative side effects, and increase the efficiency of chemotherapy. However, the lack of remote stimuli response and active drug release behavior has yet to be analyzed comparatively. In this study, we developed magnetic silk fibroin (SF) hydrogel samples through the facile blending method, loaded with doxorubicin hydrochloride (DOX) and incorporated with different concentrations of iron oxide nanoparticles (IONPs), to investigate the presumable ability of controlled and sustained drug release under the various external magnetic field (EMF). The morphology and rheological properties of SF hydrogel and magnetic SF hydrogel were compared through FESEM images and rheometer analysis. Here, we demonstrated that adding magnetic nanoparticles (MNPs) into SFH decreased the complex viscosity and provided a denser porosity with a bigger pore size matrix structure, which allowed the drug to be released faster in the absence of an EMF. Release kinetic studies show that magnetic SF hydrogel could achieve controlled release of DOX in the presence of an EMF. Furthermore, the drug release from magnetic SF hydrogel decreased in the presence of a static magnetic field (SMF) and an alternating magnetic field (AMF), and the release rate decreased even more with the higher MNPs concentration and magnetic field strength. Subsequently, Wilms' tumor and human fibroblast cells were cultured with almost the same concentration of DOX released in different periods, and cell viability was investigated using MTT assay. MTT results indicated that the Wilms' tumor cells were more resistant to DOX than the human fibroblasts, and the IC50 values were calculated at 1.82 ± 0.001 and 2.73 ± 0.004 (µg/ml) for human fibroblasts and Wilms' tumor cells, respectively. Wilms' tumor cells showed drug resistance in a higher DOX concentration, indicating the importance of controlled drug delivery. These findings suggest that the developed magnetic SFH loaded with DOX holds excellent potential for intelligent drug delivery systems with noninvasive injection and remotely controlled abilities.

Multiphysics modeling and experiments on ultrasound-triggered drug delivery from silk fibroin hydrogel for Wilms tumor.

In this study, silk fibroin hydrogel is employed as a carrier for vincristine and ultrasound as a method to accelerate the drug release. The Acoustic, deformation, swelling, and diffusion fields are coupled in a multi-physics model to optimize the drug delivery. A transient acoustic structure model and a chemically controlled mechanism are implemented, while a coupled model of deformation and diffusion takes the impact of mechanical forces into account. An evaluation of the model is made through experiments. To monitor the drug release rate over 40 days following injection of silk hydrogel syringes containing vincristine, they were triggered by ultrasound in some selected time intervals. Drug release rates were determined using different power intensities and induction times. Computed simulation results and laboratory experiments revealed that ultrasound could cause a significant improvement in drug release rate, with an increase of up to 10 times over a release without ultrasound stimulation. By increasing the ultrasound power and induction time up to their peak value, the drug release rate rises and drops then. Predictions of the drug release rate by the model were in good agreement with those observed in experiments. This makes the model a valuable tool for potential predictions. Results showed that the ultrasound triggers the increased cell death rates, but the Wilms tumor cells were resistant to higher concentrations of released drugs.

Computational analysis of vincristine loaded silk fibroin hydrogel for sustained drug delivery applications: Multiphysics modeling and experiments.

In this paper, silk fibroin hydrogel is used as a drug carrier for vincristine. To optimize drug delivery, a multi-physics model is proposed that couples the deformation and diffusion fields. We applied inverse analysis and general continuum mechanics to define material parameters and mechanical properties. To examine the mass transport and chemical behavior, an affinity-based diffusion and degradation of a drug-loaded polymer matrix is employed. Some experiments are carried out to examine the capability of the presented model. After preparing the vincristine loaded silk hydrogel syringes, they were injected into PBS and enzyme solutions to monitor the drug release rate for 40 days. Obtained results from the computational simulation and laboratory tests showed that the silk fibroin hydrogel was deswelled after about 40 days in enzyme solution. Degradation led to faster and higher doses of vincristine drug release in comparison to the case of PBS solution. Results revealed that more than 80% of the drug was released in the first 5 days in the enzyme solution, but in PBS solution only 10% of the drug was released during 40 days. The model predictions of deswelling behavior and drug release rate were in good agreement with those of experimental results. Therefore, it can be employed as a reliable tool for further predictions.

A computational simulation of electromembrane extraction based on Poisson - Nernst - Planck equations.

Electromembrane extraction (EME) has attracted a great deal of interest in researchers because of its advantages. For analysis, design and optimization purposes, understanding the ion transport mechanisms in the organic supported liquid membrane (SLM) is of prominent importance, where the interplay between the passive diffusion and electric-driven mass transport across SLM affects the mass transfer. In present work, a 2D numerical simulation is developed to examine the mass transfer behavior and the analyte recovery in EME devices. The presented model is capable of describing the effect of different parameters on the recovery of the EME setup. Initial analyte concentration in the sample solution, SLM thickness, applied potential, permittivity, diffusion coefficient, and the reservoir pH within both the sample and acceptor, can be considered as process variables. Predicted results revealed that the most important factors playing key role in EME, are the analyte diffusivity, distribution coefficient of the analyte as well as the level of protonation in both the donor and acceptor solutions. The proposed model is helpful in predicting the mass transfer behavior of the EME process in practical applications.

Modeling of human intervertebral disc annulus fibrosus with complex multi-fiber networks.

Collagen fibers within the annulus fibrosus (AF) lamellae are unidirectionally aligned with alternating orientations between adjacent layers. AF constitutive models often combine two adjacent lamellae into a single equivalent layer containing two fiber networks with a crisscross pattern. Additionally, AF models overlook the inter-lamellar matrix (ILM) as well as elastic fiber networks in between lamellae. We developed a nonhomogenous micromechanical model as well as two coarser homogenous hyperelastic and microplane models of the human AF, and compared their performances against measurements (tissue level uniaxial and biaxial tests as well as whole disc experiments) and seven published hyperelastic models. The micromechanical model had a realistic non-homogenous distribution of collagen fiber networks within each lamella and elastic fiber network in the ILM. For small matrix linear moduli (<0.2 MPa), the ILM showed substantial anisotropy (>10%) due to the elastic fiber network. However, at moduli >0.2 MPa, the effects of the elastic fiber network on differences in stress-strain responses at different directions disappeared (<10%). Variations in sample geometry and boundary conditions (due to uncertainty) markedly affected stress-strain responses of the tissue in uniaxial and biaxial tests (up to 16 times). In tissue level tests, therefore, simulations should represent testing conditions (e.g., boundary conditions, specimen geometry, preloads) as closely as possible. Stress/strain fields estimated from the single equivalent layer approach (conventional method) yielded different results from those predicted by the anatomically more accurate apparoach (i.e., layerwise). In addition, in a disc under a compressive force (symmetric loading), asymmetric stress-strain distributions were computed when using a layerwise simulation. Although all developed and selected published AF models predicted gross compression-displacement responses of the whole disc within the range of measured data, some showed excessively stiff or compliant responses under tissue-level uniaxial/biaxial tests. This study emphasizes, when constructing and validating constitutive models of AF, the importance of the proper simulation of individual lamellae as distinct layers, and testing parameters (sample geometric dimensions/loading/boundary conditions).

Multi-Trigger Thermo-Electro-Mechanical Soft Actuators under Large Deformations.

Dielectric actuators (DEAs), because of their exceptional properties, are well-suited for soft actuators (or robotics) applications. This article studies a multi-stimuli thermo-dielectric-based soft actuator under large bending conditions. In order to determine the stress components and induced moment (or stretches), a nominal Helmholtz free energy density function with two types of hyperelastic models are employed. Non-linear electro-elasticity theory is adopted to derive the governing equations of the actuator. Total deformation gradient tensor is multiplicatively decomposed into electro-mechanical and thermal parts. The problem is solved using the second-order Runge-Kutta method. Then, the numerical results under thermo-mechanical loadings are validated against the finite element method (FEM) outcomes by developing a user-defined subroutine, UHYPER in a commercial FEM software. The effect of electric field and thermal stimulus are investigated on the mean radius of curvature and stresses distribution of the actuator. Results reveal that in the presence of electric field, the required moment to actuate the actuator is smaller. Finally, due to simplicity and accuracy of the present boundary problem, the proposed thermally-electrically actuator is expected to be used in future studies and 4D printing of artificial thermo-dielectric-based beam muscles.