Search Results (5)

The use of washing machines to wash textiles gradually breaks down synthetic fibers like polyethylene terephthalate (PET) or polyester (PES) in diverse clothing materials, a process that is growing in notoriety because it generates microplastics (MPs). In this study, we investigated the emission of microfibers, including both microplastic fibers (MPFs) and natural fibers (MFs), from top-loading washing machines. Our investigation focused on four popular textiles with prevalent weave structures (plain, satin, and twill): (i) PES, (ii) tetron cotton (TC), (iii) chief value cotton (CVC), and (iv) cotton (CO) fabrics. This study also examined the effects of textile weight and detergent dosage on MF emissions. After washing, MFs were collected through filtration, and their concentrations were determined using micro-Fourier Transform Interferometry (μFTIR). The results showed varying concentrations of MFs in the washing effluent depending on the type of textile. Specifically, CVC exhibited the highest emission at 4022 particles/L, followed by TC, PES, and CO at 2844 particles/L, 2382 particles/L, and 2279 particles/L, respectively. The hydrophobic nature of PES makes this type of textile prone to rapid degradation in detergent-rich environments, leading to high MF emissions. Additionally, the mechanical properties of textiles, such as tensile and bending strengths, may play a crucial role in the generation of MFs in washing machines. Textiles made of CO with twill weaves demonstrated superior strength and correlated with lower emissions of MFs. In comparison, textiles made of CVC and satin weave exhibited lower mechanical properties, which could explain their high emissions of MFs. Finally, the MF emissions of textiles composed of PES and TC, which are plain weaved, could be attributed to their intermediate mechanical properties compared with those of CVC and CO. Full article

Polyester/cotton fabrics with different proportions of Tetron Cotton, TC (35% Cotton/65% PET), and Chief Value Cotton, CVC (60% Cotton/40% PET), were investigated by removing the cotton component under various phosphoric acidic conditions including the use of cellulase enzymes. The remaining polyethylene terephthalate (PET) component was spun using the melt spinning method. Only 85% H₃PO₄-Enz_TC could be spun into consistent filament fibers. The effects of Acid-Enz TC (obtained from a powder preparation of 85% H₃PO₄-Enz_TC) at different weight amounts (1, 2, 5, and 10 %wt) blending with WF-rPET powder prepared by white recycled polyester fabric were evaluated for fiber spinnability at different winding speeds of 1000 and 1500 m/min. The results revealed that recycled PET fiber spun by adding Acid-Enz_TC up to 10 %wt gave uniformly distributed filament fibers. A comparative study of the physical, thermal, and mechanical properties also investigated the relationship between the effect of Acid-Enz_TC and the structure of the obtained fibers. Acid-Enz_TC:WF-rPET (5:95) was the optimal ratio. The thermal values were analyzed by DSC and TGA and crystallinity was analyzed by XRD, with mechanical strength closed to 100% WF-rPET. The FTIR analysis of the functional groups showed the removal of cotton from the blended fabrics. Other factors such as the Acid-Enz_TC component in WF-rPET, extraction conditions, purity, thermal, chemical, and exposure experiences also affected the formability and properties of recycled PET made from non-single-component raw materials. This study advanced the understanding of recycling PET from TC fabrics by strategically removing cotton from polyester–cotton blends and then recycling using controlled conditions and processes via the melt spinning method. Full article

A capacitance-to-voltage converter (CVC) is proposed in this paper and applied to a readout circuit for a micro-electro-mechanical system (MEMS) accelerometer to improve the power efficiency. In a traditional readout circuit, the front-end CVC has to operate at a high sampling frequency to resist thermal noise deterioration due to the large parasitic capacitance introduced by the mechanical sensing element. Thus, the back-end analog-to-digital converter (ADC) also has to operate at a high sampling frequency to avoid noise aliasing when sampling the output signal of the CVC, which leads to high power consumption. The average CVC technique is proposed in this paper to reduce the sampling frequency requirement of the back-end ADC and thus reduce the power consumption. Both the traditional readout circuit and the proposed readout circuit are simulated with a commercial 0.18 μm BCD process. The simulation results show that noise aliasing occurs, and the noise power spectral density (PSD) of the traditional readout circuit increases by 12 dB when the sampling frequency of back-end ADC is reduced by 24 dB. However, in the proposed readout circuit, a noise aliasing effect does not occur. Moreover, the proposed readout circuit reduces the power consumption by 53% without thermal noise deterioration. In addition, the proposed CVC circuits are fabricated in an 0.18 μm BCD process, and the test results show that the presented readout circuit based on the average CVC technique can obtain better performance than the traditional CVC-based readout circuit. Full article

The outbreak of COVID-19 has already generated a huge societal, economic and political losses worldwide. The present study aims to investigate the antiviral activity of Poly(hexamethylene biguanide) hydrochloride (PHMB) treated fabric against COVID-19 by using the surrogate Feline coronavirus. The antiviral analysis indicated that up to 94% of coronavirus was killed after contacting the CVC fabric treated with PHMB for 2 h, which suggests that PHMB treated fabric could be used for developing protective clothing and beddings with antiviral activity against coronavirus and can play a role in fighting the transmission of COVID-19 in the high-risk places. Full article

We present an animal model used to evaluate the in vivo performance of electrochemical amperometric continuous lactate sensors compared to blood gas instruments. Electrochemical lactate sensors were fabricated, placed into 5 Fr central venous catheters (CVCs), and paired with wireless potentiostat devices. Following in vivo evaluation and calibration, sensors were placed within the jugular and femoral veins of a porcine subject as a preliminary assessment of in vivo measurement accuracy. The mobile electronic circuit potentiostat devices supplied the operational voltage for the sensors, measured the resultant steady-state current, and recorded the sensor response values in internal memory storages. An in vivo time trace of implanted intravenous (IV) sensors demonstrated lactate values that correlated well with the discrete measurements of blood samples on a benchtop point-of-care sensor-based instrument. Currents measured continuously from the implanted lactate sensors over 10 h were converted into lactate concentration values through use of a two-point in vivo calibration. Study shows that intravenously implanted sensors had more accurate readings, faster peak-reaching rates, and shorter peak-detection times compared to subcutaneously placed sensors. IV implanted and subcutaneously placed sensors closer to the upper body (in this case neck) showed faster response rates and more accurate measurements compared to those implanted in the lower portion of the porcine model. This study represents an important milestone not only towards continuous lactate monitoring for early diagnosis and intervention in neonatal patients with congenital heart disease undergoing cardiopulmonary bypass surgeries, but also in the intervention of critical ill patients in the Intensive Care Units or during complex surgical procedures. Full article