Polymer Testing最新文献

The increased use of plastics and the associated environmental impact has catalyzed research on the development of bio-derived polymers. Bio-based polyesters have gained increased attention due to the abundance of their starting materials and ease of processing. Lignin is naturally occurring in biomass with rich carbon content, whose functionality and rigidity make it an ideal bio-derived candidate for bio-based polyesters. Herein, a lignin-based polyester with good thermal stability and self-repairability was synthesized from carboxylated lignin and epoxidized soybean oil. The synthesized lignin/epoxidized soybean oil (ESO) vitrimer was brittle such that its mechanical performance could not be recorded. However, when polyethylene glycol (PEG) was incorporated as a plasticizer, polymer samples exhibited acceptable ductility. From thermomechanical analysis of the synthesized polyesters, the plasticizer did not impair thermal stability of polymers, but greatly enhanced mechanical properties. Notably, all samples exhibited stability at high temperatures, and good glass transition temperatures (51.0 ± 0.9–78.0 ± 1.2 °C). The highest tensile strength (3.983 ± 0.1 MPa) and storage modulus (1463.67 ± 12.6 MPa) were recorded for the polyester containing 6 % w/w PEG. Moreover, the polymer samples exhibited self-healing capability at 180 °C. This work expands on valorization of lignin through the synthesis of bio-derived materials.

This research is devoted to developing a finite element model using Abaqus code for the computer simulation of an in-house developed and manufactured rubber bearing subjected to static vertical and cyclic horizontal loads. A high-damping rubber compound was designed. The material behavior of the rubber was assumed to be described by the hyper-viscoelastic model. Both linear (Prony series) and nonlinear (strain hardening power law) viscoelastic relationships were used in conjunction with the Ogden-Roxburgh equation to take the addition of the stress softening phenomenon or Mullins effect into consideration. The parameters of the material model were determined using MCalibration code in which an optimization technique was used, and data obtained in experiments carried out on test specimens were fitted into the selected model. The results of the simulations were compared with their corresponding experimental data carried out on the rubber bearing. The force-displacement behavior, stress and strain fields, and computed energy were presented and discussed. It is shown that the nonlinear viscoelastic model accompanied by the Mullins effect gives the best results. Moreover, the model could accurately predict the energy variations during the earthquake loading.

The present study examined the nonlinear time-dependent behavior of rheodictic polymers, a class of noncrosslinked materials that exhibit flow. Such behavior was addressed with extended Schapery's nonlinear viscoelastic model by introducing new physical quantities, i.e., the flow term ${\Phi }_{\text{flow}}$ and corresponding nonlinear shift parameter $g_{2,\text{flow}}$. While ${\Phi }_{\text{flow}}$ portrays irrecoverable deformation, $g_{2,\text{flow}}$ depicts a nonlinear contribution to flow acceleration. This theory was accompanied by analytical and experimental methodologies for identifying all the parameters in the linear and nonlinear viscoelastic domains. Predictions of long-term time-dependent behavior (in shear) at various stress states show excellent agreement with the experimental data, i.e., within $5\%$ error, obtained for polycarbonate at $130°C$. Surprisingly, the newly introduced $g_{2,\text{flow}}$ indicates that flow retardation occurs with increasing stress, implying that a highly deformed entangled system hinders molecular reptation/disentanglement. Nevertheless, the proposed extension of Schapery's nonlinear viscoelastic model not only allows accurate predictions of the nonlinear time-dependent behavior of rheodictic polymers but also enables a detailed outlook on the underlying molecular mechanisms under severe environmental and loading conditions.

Petroleum-based epoxy resin is commonly used in electrical equipment due to its outstanding performance and affordability. However, its non-melting characteristics present challenges for recycling, leading to significant resource waste and environmental pollution. To address this issue, this study prepared and synthesized a kind of vitrimer epoxy resin polymer material based on disulfide bonds with 2,2′-Diaminodiphenyl disulphide as the curing agent. The research investigated the impact of the curing agent ratio on the resin's structure and properties. The resin was mechanically recovered through hot pressing at high temperature and pressure, and its chemical degradation and recovery were achieved via the reduction reaction of the thiol and disulfide bond. The findings revealed that a curing agent to epoxy group material ratio of 0.75 improved the resin system's electrothermal properties. The electrical insulation property retention rate after hot pressing recovery reached 95 %, with a mechanical property retention rate of 85 %. The disulfide bonds can be reoxidized and crosslinked to realize the recovery and reuse of vitrimer resin degradation solution. Vitrimer epoxy resin based on disulfide bonds is a significant way to realize the environmental protection of epoxy electrical equipment.

A low-carbon and sustainable green rigid polyurethane foam was prepared by compounding montmorillonite (MMT) with homemade barium phytate (BAPA). The flame retardancy, thermal stability and mechanical properties of the modified RPUFs investigated using the limiting oxygen index (LOI) method, cone calorimetry (CONE) and thermogravimetry. The results showed that the BAPA/MMT2 composite containing 2 wt% MMT had the highest LOI (25.1 %), and its peak heat release rate (PHRR) and total heat release (THR) were reduced by 14.33 % and 34.68 %, respectively, compared with that of the BAPA/MMT0 material without added MMT. In addition, the smoke production rate (SPR) and total smoke release (TSR) were reduced by 20.54 % and 30.77 %, respectively. BAPA/MMT2 had good flame retardancy and smoke suppression effect. The mechanical properties of BAPA/MMT2 with 2 wt% MMT were improved. The flame retardant mechanism confirmed that BAPA and MMT synergistically improved the quality of the carbon layer. At the same time, phosphorus-containing compounds (PO·), CO₂ and water vapor were produced, which diluted the combustible gas in the gas phase and inhibit the flames spread. The current results provided a new strategy for the preparation of high-performance RPUFs.

This paper presents the development of multilayered carbon nanotube (CNT)/adhesive (MLCA) films for human body signal detection sensors using a spray-coating method. The chemical composition, adhesion properties, and electrical conductivity of the films were investigated using various adhesives, with the acrylate-based adhesive (ABA) exhibiting superior performance. The surface roughness, thickness, and electrical properties of the films were characterized, and the tunability was demonstrated by adjusting the number of coating layers. Tribological tests were performed to assess the wear resistance and friction behavior of the films. The adhesion stabilities and conformabilities of the films on various substrates were investigated. The films were combined with polydimethylsiloxane (PDMS) and surfactants to create biocompatible and durable sensors. The PDMS-surfactant composite was characterized, and the MLCA film/PDMS-surfactant-based sensor exhibited excellent stability under deformation and biocompatibility. The impedance behavior, temperature, humidity, and strain-sensing capabilities of the sensors were evaluated. The capability of the sensor to detect vital signs was validated by accurately capturing the electrocardiogram (ECG) waveforms. This study provides valuable insights into the design and fabrication of CNT-based conductive films for human body signal-detection sensors, offering a promising approach for the development of flexible and wearable electronic devices.

The present study focuses on investigating the effect of incorporating silica aerogel on the electrical characteristics and sensing capabilities of carbon nanotube (CNT)-embedded PDMS nanocomposites. Initially, the concept of developing nanohybrid clusters composed of CNT and silica aerogel was introduced, followed by comprehensive evaluations of their formation including zeta potential, Raman spectra and FT-IR spectrum. Subsequently, the nanocomposites with varied silica aerogel contents from 0.5 to 2 % by polymer mass were assessed for their sensing capability. It is observed that porosity has exerts perceptible influence on the overall effective electrical conductivity of the sensor below the percolation thresholds, while it does not have any impact beyond this threshold. In addition, the effective medium proposition theory has been modified to analyze both the effective electrical conductivity and the piezoelectric properties of the sensors fabricated. Based on the theoretical and experimental results, the developed CNT@aerogel nanohybrid clusters displayed the potential to enhance sensing sensitivity and increase linearity during stretching condition.

Wearable glucose sensors have attracted significant attention for enabling non-invasive blood glucose measurement without discomfort and risk of infection. However, it is a challenge to simultaneously realize wearable adaptability, biodegradability, and excellent sensing performance. Herein, a cellulose paper-based non-invasive biosensor relying on reverse iontophoresis was designed to detect glucose in interstitial fluid (ISF), and two different enzyme immobilization strategies have been compared. The results showed inkjet-printed cellulose paper-based biosensor (IPB) performances better than the drop-coated cellulose paper-based biosensor (DPB). IPB has twice response current more than DPB in detection range (0–10 mM). In sensitivity, IPB is 1.170 μA/mM three times higher than the DPB (0.376 μA/mM). Besides, IPB's electron-transfer resistance (Rct) is 7.27 kΩ smaller than DPB (Rct = 10.51 kΩ) about 30 %. More importantly, IPB exhibited a good reproducibility (RSD, 4.82 %), which was much less than DPB (RSD, 18.35 %). Furthermore, the IPB realizes noninvasive continuous glucose monitoring over 6 h in volunteer experiments with great analytical performance comparable to commercial devices (Pearson correlation 0.732). Cellulose paper-based glucose sensors with inkjet printing provide non-invasive access to statistically significant diagnostic information, simple and cost-effective, which promotes the application of flexible, wearable, degradable bioelectrodes in continuous glucose monitoring at home, providing a concept for full integration in a compact and portable way in the future.

Electroactive polyvinylidene fluoride (PVDF) with predominantly the β-phase is now challenging the fabricating of PVDF toward energy storage applications. Here, the comprehensive effect of BaTiO₃ nano-particles and mechanical stretching on the improvement of the β-phase of PVDF was investigated. In situ synchrotron wide-angle X-ray diffraction (WAXD) and small-angle X-ray scattering (SAXS) measurements were performed to investigate this behavior. Consequently, the transformation rate of β-crystal for both pure PVDF (BT0) and PVDF/BaTiO₃ (90/10) nanocomposites (BT1) decreases as the stretching temperature increases, implying that the high temperature is unfavorable to the formation of β-crystal phase. A synergistic enhancement of the β-phase of nano-particle additives and stretching was discovered. It was surprisingly observed that α-phase of PVDF would completely transform into β-crystal in BT1 sample at 100 °C during stretching. The mechanism of the synergistic effect of BaTiO₃ nano-particles and mechanical stretching was proposed. Moreover, machine learning was implemented to predict the fraction of β-crystal phase (F(β)) of the PVDF/BaTiO₃ composites under various uni-axial stretching conditions by Python 3.8. The results show that the machine learning technique can rapidly and efficiently discover the ideal value of F(β) and the optimal multivariate coupling conditions.