RESUMO
Poly(ethylene glycol) (PEG) boasts excellent thermal energy storage capabilities but lacks efficiency in thermal conductivity and solar absorption. Simultaneously, the escalating concern surrounding the substantial volume of discarded cotton fabric underscores environmental issues. In this study, we devised composite phase change materials (PCMs) by embedding PEG into a carbon cotton material (CCM), varying PEG content from 50 to 80%, and conducted a comprehensive analysis of their thermal properties and solar-to-thermal conversion. The CCM, crafted from a waste 100% cotton towel through carbonization, provided an optimal porous structure that accommodated a significant 70% PEG content without any leakage, thanks to interactions such as surface tension, capillary forces, and interfacial hydrogen bonds. These PEG/CCM composites exhibited impressive crystallization fractions (>92%), resulting in notable thermal energy storage capacities ranging from 85.3 to 143.2 J/g as the PEG content increased from 50 to 80%. Moreover, these composites showed high thermal stability and exceptional cycling durability even after 500 melting/crystallization cycles. Notably, their thermal conductivities markedly increased to a range of 0.46-0.85 W/m·K compared to pure PEG's modest 0.24 W/m·K. Furthermore, the PEG/CCM composites substantially augmented visible and near-infrared (VIS-NIR) light absorption. Evaluation of solar-to-thermal conversion illustrated the composite's ability to efficiently convert solar energy into thermal energy, storing and subsequently releasing it through melting and crystallization processes. This study introduces a novel class of composite PCMs characterized by cost-effectiveness, outstanding thermal performance, and impressive solar-to-thermal conversion capabilities. These composite PCMs hold significant promise for large-scale solar-to-thermal energy storage applications while contributing to the sustainability of cotton waste management.
RESUMO
Objective: This study aimed to assess the effectiveness and determine the optimal cut-off point of the ADNEX model in women presenting with a pelvic or adnexal tumor. Method: All women presented with adnexal mass and were scheduled for operation at Hue University of Medicine and Pharmacy Hospital and Hue Central Hospital, Vietnam during June 2019 May 2021 were included and categorized according to their histopathologic reports into ovarian cancer groups and benign ovarian tumor groups. Multivariable logistic regression was used to explore for potential predictors. The ADNEX model with and without CA125 was used to assess the risk of ovarian cancer preoperative. The goldden standard to evaluate the accuracy of ultrasonography using the ADNEX model was the pathological report. In addition, the accuracy as well as optimum cut-off point of the ADNEX model was estimated with and without CA125. Results: A total of 461 participants were included in analysis and predictive model development, 65 patients in ovarian cancer group and 361 in benign tumor group. The ADNEX model combined with CA125 proved to be a useful predictor with an area under ROC of 0.961 (0.940 0.977) with Youden's index of 0.8395, p < 0.001. The ADNEX model without CA125 also had high predictive value between benign and malignant tumors, with an area under ROC of 0.956 (0.933 0.973) with Youden's index of 0.8551, p < 0.001. Cut-off of the ADNEX with CA125 was 13.5 and without CA125 was 13.1 for sensitivities were 90.8 (81.0 96.5) and 93.9 (85.0 97.5), specificities 93.2 (90.2 95.5) and 91.67 (88.5 94.2). The difference in the predictive value of malignancy-risk between the ADNEX model with CA125, without CA125 was not statistically significant, p=0.4883. Conclusion: The ADNEX model, with or without the combining marker CA 125, provides a valuable predictive value for ovarian tumor malignancy preoperative.