Adaptive Neuro-Fuzzy Inference System to Predict the Release of Microplastic Fibers during Domestic Washing

2023

Toxics

The increase in the global population is directly responsible for the acceleration in the production as well as the consumption of textile products. The use of textiles and garment materials is one of the primary reasons for the microfibers generation and it is anticipated to grow increasingly. Textile microfibers have been found in marine sediments and organisms, posing a real threat to the environment as it is invisible pollution caused by the textile industry. To protect against the damaging effects that microplastics can have, the formulation of mitigation strategies is urgently required. Therefore, the primary focus of this review manuscript is on finding an environmentally friendly long-term solution to the problem of microfiber emissions caused by the domestic washing process, as well as gaining an understanding of the various properties of textiles and how they influence this problem. In addition, it discussed the effect that mechanical and chemical finishes have on microfiber emissions and identified research gaps in order to direct future research objectives in the area of chemical finishing processes. In addition to that, it included a variety of preventative and minimizing strategies for reduction. Last but not least, an emphasis was placed on the potential and foreseeable applications of machine vision (i.e., quantification, data storage, and data sharing) to reduce the amount of microfibers emitted by residential washing machines.

Section: Machine Vision Can Control the Microfiber Releasesmentioning

confidence: 99%

Environmentally Friendly Approach to the Reduction of Microplastics during Domestic Washing: Prospects for Machine Vision in Microplastics Reduction

2023

Toxics

“…Microplastics are further divided into two categories, primary and secondary microplastics; this information has been clearly discussed in many recent articles [ 10 , 11 , 12 , 13 , 14 , 15 , 16 ]. Microplastics can stem from a range of resources consisting of synthetic textiles, tires, roadway markings, aquatic coverings, personal care/cosmetic products, and crafted plastic pellets, as well as from the gradual fragmentation of bigger plastics over time [ 17 ]; among these sources, the domestic washing of garments has the highest potential for the generation of microplastics [ 18 , 19 , 20 , 21 , 22 , 23 , 24 ] ( Figure 1 ). In addition to petroleum-based plastic fibers, man-made cellulose fibers (e.g., viscose rayon) have also been detected in different environmental matrices of deep-sea sediment and macroinvertebrate fishes, thus increasing the interest of the scientific community in this kind of plastic pollution, which is usually underestimated [ 25 , 26 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

Microfiber Emissions from Functionalized Textiles: Potential Threat for Human Health and Environmental Risks

2023

Toxics

Self Cite

The growing worldwide population is directly responsible for the increased production and consumption of textile products. One of the key reasons for the generation of microfibers is the use of textiles and garment materials, which is expected to increase. The textile industry is responsible for the invisible pollution that is created by textile microfibers, which have been detected in marine sediments and organisms. The present review paper demonstrates that the microfibers discharged from functionalized textiles exhibit non-biodegradable characteristics and that a considerable proportion of them possess toxic properties. This is primarily attributed to the impact of textiles’ material functionalization on their biodegradability. The potential for these microfibers, which are released from textiles that contain a variety of dyes, toxic chemicals, and nanomaterials, to pose a variety of health risks to both humans and other living organisms is discussed in this paper. In addition, this paper covers a wide variety of preventative and minimizing measures for reduction, which are discussed in terms of several phases ranging from sustainable production through the consumer, end of life, domestic washing, and wastewater treatment phases.

“…ANN are applied in various fields like as water resources engineering, traffic engineering 13 , detection of structural damage 14 , concrete strength prediction 15 , in textiles, yarn strength 16 , 17 , fabric pilling properties 18 , mechanical properties 19 , color strength prediction 20 , fabric finishing 21 , microplastic emission during domestic washing 22 .…”

Section: Introductionmentioning

confidence: 99%

Neural network model applied to electromagnetic shielding effectiveness of ultra-light Ni/Cu coated polyester fibrous materials

Muthusamy

Militký

2022

Sci Rep

Self Cite

The purpose of effective electromagnetic interference (EMI) shielding is to prevent EMI from smartphone, wireless, and utilization of other electronic devices. The electrical conductivity of materials strongly influences on the EMI shielding properties. In this work, mainly focus to predict the EMI shielding effectiveness on the ultralight weight fibrous materials by artificial neural network (ANN). Prior to the ANN modelling, the ultra-lightweight fibrous materials were electroplated with different concentration of Ni/Cu and then coated with different silanes. This work utilizes the algorithm to provide accurate quantitative values of EMI shielding effectiveness (EM SE). To compare its performance, the experimental and the predicted EM SE values were validated by root-mean-square error (RMSE), mean absolute percentage error (MAPE) values and correlation coefficient ‘r’. The proposed ANN results accurately predict the experimental data with correlation coefficients of 0.991 and 0.997. Further due to its simplicity, reliability as well as its efficient computational capability the proposed ANN model permits relatively fast, cost effective and objective estimates to be made of serving in this industry.