Piezoresistive behavior of elastomer composites with segregated network of carbon nanostructures and alumina

Electrically conductive elastomer composites(CECs)with segregated networks of conductive nanofillers show high potential in stretchable strain sensors due to balanced mechanical and electrical properties,yet the sensitivity at low strain is generally insufficient for practical application.Herein,we report an easy and effective way to improve the resistive response to low strain for CECs with segregated network structure via adding stiff alumina into carbon nanostructures(CNS).The CEC containing 0.7 wt%CNS and 5 wt%Al_(2)O_(3) almost sustains the same elasticity(elongation at break of~900%)and conductivity(0.8 S/m)as the control,while the piezoresistive sensitivity is significantly improved.Thermoplastic polyurethane(TPU)composites with a segregated network of hybrid nanofillers(CNS and Al_(2)O_(3))show much higher strain sensitivity(Gauge factor,GF-566)at low strain(45%strain)due to a local stress concentration effect,this sensitivity is superior to that of TPU/CNS composites(GF-11).Such a local stress concentration effect depends on alumina content and its distribution at the TPU particle interface.In addition,CECs with hybrid fillers show better reproducibility in cyclic piezoresistive behavior testing than the control.This work offers an easy method for fabricating CECs with a segregated filler network offering stretchable strain sensors with a high strain sensitivity.

In silico optimization of actuation performance in dielectric elastomercomposites via integrated finite element modeling and deep learning

Dielectric elastomers(DEs)require balanced electric actuation performance and mechanical integrity under applied voltages.Incorporating high dielectric particles as fillers provides extensive design space to optimize concentration,morphology,and distribution for improved actuation performance and material modulus.This study presents an integrated framework combining finite element modeling(FEM)and deep learning to optimize the microstructure of DE composites.FEM first calculates actuation performance and the effective modulus across varied filler combinations,with these data used to train a convolutional neural network(CNN).Integrating the CNN into a multi-objective genetic algorithm generates designs with enhanced actuation performance and material modulus compared to the conventional optimization approach based on FEM approach within the same time.This framework harnesses artificial intelligence to navigate vast design possibilities,enabling optimized microstructures for high-performance DE composites.

Preparation and Mechanical Performance of Rare Earth- Containing Composite Elastomer

Rare earth -containing PSBR sheet was prepared by reaction of rare earth alkoxide with quaternary ammonium salt of pyridine modified SBR (PSBR) latex, and then it was blended with natural rubber (NR) to produce rare earth - containing composite elastomer. It is found that mechanical performance can be improved remarkably. Analyzed by infrared spectrometry (IR), differential scanning calorimetry (DSC) and cross-linking densitometry, the relationship between structure and performance was discussed.

Thermal Oxidation Resistance of Rare Earth-Containing Composite Elastomer

The rare earth-containing composite elastomer was obtained by the reaction of vinyl pyridine-SBR (PSBR) latex with rare earth alkoxides, and its thermal oxidation resistance was studied. After aging test, it is found that its retention rate of mechanical properties is far higher than that of the control sample. The results of thermogravimetric analysis show that its thermal-decomposing temperature rises largely. The analysis of oxidation mechanisms indicates that the main reasons for thermal oxidation resistance are that rare earth elements are of the utility to discontinue autoxidation chain reaction and that the formed complex structure has steric hindrance effect on oxidation.

Building Magnetoresponsive Composite Elastomers for Bionic Locomotion Applications

The ability of natural living organisms,transferring deformations into locomotion,has attracted researchers’increasing attention in building bionic actuators and smart systems.As a typical category of functional materials,magnetoresponsive composite elastomers,comprised of flexible elastomer matrices and rigid magnetic particles,have been playing critical roles in this field of research due to their dynamic changes in response to applied magnetic field direction and intensity.The magnetically driven bionic actuators based on magnetoresponsive composite elastomers have been developed to achieve some specific functions in some special fields.For instance,under the control of the applied magnetic field,the bionic actuators can not only generate time-varying deformation,but also motion in diverse environments,suggesting new possibilities for target gripping and directional transporting especially in the field of artificial soft robots and biological engineering.Therefore,this review comprehensively introduces the component,fabrication,and bionic locomotion application of magnetoresponsive composite elastomers.Moreover,existing challenges and future perspectives are further discussed.

Self-polymerization of Eu(TTA)_3AA in rubber and their fluorescence effect

A simple europium complex,Eu（TTA）3 AA（TTA=4,4,4-trifluoro-1-（2-thienyl）-1,3-butanedione,AA=acrylic acid） was synthesized by a simple solution method.Then,two kinds of rubber matrix,nitrile-butadiene rubber（NBR） and silicone rubber（SiR） were used as the substrate for Eu（TTA）3 AA to prepare fluorescence composites.The neat Eu（TTA）3 AA complex showed the ability of self-polymerization when it was heated at 145 °C.It was found that the fluorescence intensity of the neat Eu（TTA）3 AA decreased over 70% when the polymerization time was over 25 min at 145 °C.The results also revealed that the polymerizated Eu（TTA）3 AA could be dispersed in nano-scale in two matrices and the luminescent intensities decreased 52% in NBR matrix,and 95% in SiR matrix compared with two relative compounds without crosslinking.To optimize the luminescence intensity of the composites,the Eu（TTA）3 AA polymerization kinetic process in matrix was investigated in detail by controlling the temperature,the crosslinking agent,etc.The results showed that the peroxide could accelerate Eu（TTA）3 AA self-polymerization in the rubber matrix,and therefore improved the dispersion,but not be helpful for the luminescence intensity enhancement.In addition,the relatively higher luminescence intensity in Eu（TTA）3 AA/NBR in comparison to that of Eu（TTA）3 AA/SiR might contribute to the interaction between nitrile group（–CN） in NBR and Eu-complexes,suggesting that the luminescence intensity of the composites also depended on the matrix characteristics.