Digital Twin Geometry for Fibrous Air Filtration Media

Computational modeling of air filtration is possible by replicating nonwoven nanofibrous meltblown or electrospun filter media with digital representative geometry. This article presents a methodology to create and modify randomly generated fiber geometry intended as a digital twin replica of fibrous filtration media. Digital twin replicas of meltblown and electrospun filter media are created using Python scripting and Ansys SpaceClaim. The effect of fiber stiffness, represented by a fiber relaxation slope, is analyzed in relation to resulting filter solid volume fraction and thickness. Contemporary air filtration media may also be effectively modeled analytically and tested experimentally in order to yield valuable information on critical characteristics, such as overall resistance to airflow and particle capture efficiency. An application of the Single Fiber Efficiency model is incorporated in this work to illustrate the estimation of performance for the generated media with an analytical model. The resulting digital twin fibrous geometry compares well with SEM imagery of fibrous filter materials. This article concludes by suggesting adaptation of the methodology to replicate digital twins of other nonwoven fiber mesh applications for computational modeling, such as fiber reinforced additive manufacturing and composite materials.

Seepage Time Soft Sensor Model of Nonwoven Fabric Based on the Extreme Learning Machine Integrating Monte Carlo

Nonwoven fiber materials are materials with multifunctional purposes, and are widely used to make masks for preventing the new Coronavirus Disease 2019. Because of the complexity and particularity of their structure, it becomes difficult to model the penetration and flow characteristics of liquid in nonwoven fiber materials. In this paper, a novel seepage time soft sensor model of nonwoven fabric, based on Monte Carlo (MC), integrating extreme learning machine (ELM) (MCELM) is proposed. The Monte Carlo method is used to expand data samples. Then, an ELM method is used to establish the prediction model of the dyeing time of the nonwoven fiber material overlaps with the porous medium, as well as the insertion degree and height of the different quantity of hides. Compared with the back propagation (BP) neural network and radial basis function (RBF) neural network, the results show that the prediction model based on the MCELM method has significant power in terms of accuracy and prediction speed, which is conducive to the precise and rapid manufacture of nonwoven fiber materials in practical applications between liquid seepage characteristics and structural characteristics of porous media. Furthermore, the relationship between the proposed models has certain value for predicting the behavior and use of nonwoven fiber materials with different structural characteristics and related research processes.

Impact of Water and UV Irradiation on Nonwoven Polylactide/Natural Rubber Fiber

A nonwoven fiber made of polylactide/natural rubber with a rubber content from 0 to 15 wt.% was obtained by electrospinning from a solution. The water sorption test showed that the addition of natural rubber into the polylactide matrix did not significantly affect the degree of water absorption of the fibers, which was in the range of 48.9–50.6%. The melt flow rate only increased by 0.5 g/10 min at a content of 15 wt.% natural rubber. The thermal characteristics after 120 days of degradation in distilled water and UV irradiation (50 h) at a wavelength of 365 nm were determined using differential scanning calorimetry. Changes in the values of the phase transition temperatures and the degree of crystallinity were determined. It was determined that the fiber samples from all compositions retained the propensity for photo- and hydrolytic degradation.

Preparation of Poly-1-butene Nanofiber Mat and Its Application as Shutdown Layer of Next Generation Lithium Ion Battery

Nonwoven nanofiber webs from polyolefin show great potential in various fields such as nanofilters, high performance membranes and separators in lithium ion batteries (LiB). Although nonwoven microfiber webs can be obtained by the well-established melt-blown method, it is relatively difficult to produce nonwoven nanofiber web using polyolefin (polyethylene and polypropylene). There have been several reports on the preparation of polyolefin nanofibers by melt-electrospinning, although this approach presents several intrinsic disadvantages, i.e., high processing costs, the requirement of complex equipment, and poor control over pore size or fiber diameter. Solution-based electrospinning has the potential to overcome the drawbacks of melt-electrospinning, but the solubility of most polyolefin is poor. In this study, we found that poly-1-butene, a member of the poly(alpha-olefin) family, can be used in the electrospinning process. We set the concentration of the polymeric solution for electrospinning at 0.65–1.7 g/mL. Here, we report on the fabrication of nonwoven fiber webs composed of poly-1-butene and their copolymers. The diameter of the nonwoven fiber mat was 0.2–0.4 μm, which can be applicable for shutdown layer. As a representative application, we prepared a poly-1-butene nanofiber separator with an appropriate pore size by electrospinning for use as the shut-down layer of a next-generation LiB. The PB-based nanofiber mat provided shutdown ability at around 100 to 120 °C.