Size-Dependent Filtration Efficiency
A detailed description of the samples included in the present study, including fabric characterization and grams per square meter (GSM-g/m2), is provided in Supplementary Table (S. Table) 1a and b. The size-dependent FE of each barrier face covering, and double-layer home fabric material are presented in S. Table 2. The use of barrier face coverings in future SARS-related pandemics remains a possibility (Konda et al. 2020), and the size of the causative viruses varies widely (Abdelrahman et al. 2020). In addition, research results have indicated that different material samples a have different particle FE as a function of particle diameter (Joo et al. 2021) as noticeable in the current study (Fig. 1a, b). For most samples, FE was higher for particle size 0.03–0.08 µm. Particle size 0.1 µm has a distinctively higher FE before a slight reduction with increasing particle size. Particle size 0.3 µm-D is within the most penetrating particle size (MPPS, low FE) range.
For particle size 0.06 µm-d, the lowest FE was recorded for pillowcase fabric (7.14%), bandana face covering (11.48%), and tank top fabric (13.30%), while denim (84.00%), velcro mask (81.88%), and surgical mask (75.46%) were the highest. For particle size 0.1 µm-d, pillowcase (17.05%), tank top (22.56%), and t-shirt II (24.84%) have the lowest FE, while velcro mask (82.34%), surgical mask (81.53%), and denim fabric (79.36%) have the highest. Except for denim, polo-style fabric (only at 0.03 µm-D), collared shirt (only at 0.03–0.04 µm-D), and towel (only at 0.03–0.10 µm-D), all home fabric samples showed particle FE lower than 45% in the entire particle size range. It is noteworthy that bandana and neck gaiter showed FE lower than 30% in the entire size range (S. Table 2). FE across the entire size range were compared with ASTM (F3502-21) values of < 20% for lower performance and > 50% for higher performance barrier face coverings. R95 (3 M) masks were included as reference for performance comparison. Results are presented in Fig. 2a–e. Of all the ready-made barrier face covering samples included in the present study, 68.75% have at least one size-dependent FE that is less than 20%, while 81.25% have at least one FE that is less than 50%. All home fabric samples have FE below 50%, except collared shirt (only at 0.03 µm-D) and denim (all sizes). Similar results were documented by Drewnick et al. (2021) for 0.03–0.25 µm diameter particles at both lower (5.3 cm/s) and higher (12.9 cm/s) face velocities. Double-layer neck gaiter and bandana have FE below 30% for all particle sizes (S. Table 2).
In the present study, statistically significant (p < 0.05) positive correlation was observed between GSM and FE (Table 1), that is, the higher the density of the tested samples, the higher is the FE. The observed relationship is also size-dependent, because FE progressively decrease with increasing particulate diameter (S. Table 2). The relationship was supported by research outcome reported by Joo et al. (2021) that observed higher filtration performance for material samples with higher density. For home fabrics, towel (430.89 g/m2), denim (407.74 g/m2), and polo-style shirt (210.69 g/m2) have higher density with size-dependent FE range of 28.20–70.17%, 65.23–93.88% and 14.82–48.84%, respectively. On the other hand, Dutch wax print fabric (94.57 g/m2), t-shirt I (116.66 g/m2), and bedspread (118.07 g/m2) are fabric samples with lower density and respective lower FE range of 9.26–28.79%, 8.09–33.84%, and 3.11–25.00%. Fiber contents or knitted/woven characterization appeared not to impact FE. Although the increase in FE with increasing GSM can be translated to increasing the number of layers to achieve higher FE performance, the impact on breathability deserves attention.
Breathability of Samples
Pressure differentiation values and patterns were very similar within face covering samples regardless of particulate size. Only minor variations were observed (S. Table 3). Therefore, only 0.03, 0.06, and 0.1 (µm-D) were selected for face coverings’ breathability comparisons among samples (Fig. 3). Other size-sample comparisons are given in S. Fig. 3. The need for alternative materials for use in barrier face coverings is unprecedented. Acceptable material must be effective in slowing the spread of respiratory diseases by adequately filtering respiratory droplets and aerosols that might contain causative viruses yet providing sufficient breathability. In the present study, breathability is observed to decrease (increasing Δp) with increasing FE. An optimal high-performance face covering must have high FE, high breathability (low Δp), and be washable without performance compromise (Bagheri et al. 2021).
The highest breathability was observed for tank top (0.781–0.801 mmH2O), t-shirt I (1.039–1.055 mmH2O), and bandana (1.447–1.464 mmH2O), while the lowest was noticed in denim (71.425–71.604 mmH2O), Dutch wax print fabrics (21.613–21.659 mmH2O), and cotton face coverings (15.857–15.905 mmH2O). The high breathability observed in the present study may be explained by the generally low FE. Pressure differentiations (Δp) across the entire size range were also compared with the ASTM Standard values of > 15 mmH2O for lower performance and < 5 mmH2O for higher performance barrier face coverings. The majority of the samples in the present study are breathable and have the high-performance Δp range suggested in the ASTM Standard (Fig. 3). Of all the total 16 different samples included in the study, only collared shirt (5.56–5.59 mmH2O), Dutch wax print fabric (21.61–21.66 mmH2O), fashion (10.63–10.66 mmH2O), and cotton face coverings (15.86–15.91 mmH2O) have Δp in the low-performance category.
The comparatively high Δp in Dutch wax prints may be due to the resins and dyes used in their production. The inter-fiber spaces of barrier face coverings are the pores that allow the passage of some particles including air. This is a key distinction in aerosol filtration models that establish what passes through or gets captured via direct impaction, diffusion, or interception. The waxes, paints or dye used on face covering samples can block many of the inter-fiber spaces thus increasing Δp, because transmission energy is inversely proportional to pore sizes (Aydin et al. 2020). Particle size does not seem to impact breathability (S. Table 3). The similarity observed in the correlation may be due to the small variation in breathability within each sample despite increasing particle size. The correlation between GSM and Δp is presented in Table 1.
Nanobeads Flow Resistance and Overall Performance Evaluation
The experimental average percentage recoveries of nanobeads in 2.5, 5.0 and 20.0 µL challenge solution were 87.93%, 81.26% and 99.18%, respectively. The DF was 1.97 (± 0.056) and average fluorescence of Isolution was 13,371.30 (± 465.46). The percentage flow of latex beads was estimated from fluorescence intensity and presented in Table 2. Most of the tested samples resisted the flow of nanobead-containing droplets except bandana, neck gaiter masks, t-shirt I, tank top, and bedspread fabrics. The highest flow was recorded for tank top (1.12%) and the lowest was recorded for bedspread (0.05%). No specific flow pattern could be attributed to the fabric characteristics (thickness, density, weave type or material composition). As suggested by Aydin et al. (2020), the most likely explanation could be sample porosity. The backside illumination intensity method described by Aydin et al. (2020) can be used to evaluate the porosity of fabric samples used at alternative barrier face coverings. It should be noted that the flow-through fabrics were among the samples with the highest particle penetration (100 – FE) and highest breathability (lower Δp). Particle penetration ranges of bandana, neck gaiter, t-shirt I, tank top and bedspread were 74.98–95.84%, 70.55–90.38%, 66.16–91.92%, 77.45–93.48%, and 75.00–96.39%, respectively, while Δp were 1.45–1.46 mmH2O, 2.84–2.86 mmH2O, 1.04–1.06 mmH2O, 0.78–0.80 mmH2O, and 2.38–2.41 mmH2O, respectively. These are among the lowest FE and Δp documented in the current study.
In the present study, the velocity of incident droplets ranged from 239.35 to 6252.29 cm/s measured within 1 cm from the nozzle of the bottle. The median velocity of tracked droplets ranged from 1007.58 to 1689.94 cm/s. The experimental set up mimicked a real-life sneezing scenario and how barrier face coverings can resist the flow of ejected droplets. The maximum droplet velocity of a typical sneeze was previously documented to range from 1200 to 1500 cm/s with varying droplet numbers (Bahl et al. 2020). The nanobead experiment was performed with respective number of layers of materials in already-made masks as sold and one layer of home fabric samples. However, homemade fabrics are usually sewn using two layers. Therefore, the experiments were repeated only for the flow-through fabrics using two layers and no flow of nanobeads were recorded. It is important to note that it required two layers of neck gaiter and bandana samples to resist the flow of 0.1 µm nanobeads carried by droplets at 239.35 to 6252.29 cm/s. In general, the results of the present study indicated that the droplet blocking efficiency of most samples were high for single layers and no flow was observed for multiple-layered samples. The results are like the ones reported by Aydin et al. (2020) which indicated that the median droplet blocking efficiency of home fabrics was more than 70%, and at 2–3 layers, droplet blocking efficiency of home fabrics were comparable to that of medical face masks.
The statistically significant (p < 0.05) correlation between FE and breathability has been indicated by the results of the current study (Table 3) as supported by other studies (Kähler and Hain, 2020; Hao et al. 2020; Zhao et al. 2020; Bagheri et al. 2021). Since the relationships between FE and breathability were inverse, to determine the samples with an optimum performance, the overall performance (qF) of barrier face covering samples were estimated. This was achieved by combining both the FE and Δp using Eq. (2) that have been formulated to estimate the quality of filter samples by considering both parameters simultaneously. The qF of samples are provided in Table 4 and S. Table 4. Relative performance of samples to R95 masks is presented in Fig. 4a–d.
Dutch wax print (0.034), pillowcase (0.067), and bedspread (0.098) fabrics and fashion face covering (0.100) were samples with the lowest qF values. Velcro mask (3.362) with inner filter, surgical masks (3.494), t-shirt I (2.958) and tank top (2.418) fabrics were samples with the highest qF. The range of qF values for R95 mask was 12.334–13.374. In the current study, using the FE and Δp values suggested in the ASTM standard, qF for low-performance and high-performance barrier face coverings were estimated as 0.112 and 1.040, respectively. Twenty-five percent (25%) of the samples have at least one qF value below the value categorized as low at any of the particle sizes examined. Only 12.5% of the samples have a qF range that is higher than the qF value for high performance barrier face coverings across all particle sizes. Surgical and velcro masks ranked higher among common already-made masks. For particle size 0.03–0.10, t-shirt I, towel, tank top and Polo-style fabrics ranked higher among home fabrics for alternative face masks. Size-dependent performances were generally lower for particle size 0.15–0.40 and were similar in pattern to the sizes reported by Dhanraj et al. (2021). Many were below the qF value for a high-performance face covering (Table 4). Relative performance of samples with R95 mask is given in Fig. 4.
The high overall performance of R95, surgical and velcro masks are directly related to their higher FE and lower Δp. Similar performances at submicron and supermicron aerosol sizes have been reported (Liu and Zhao 2021). Size-dependent FE of samples were further highlighted when relative performances of samples were estimated against R95 masks. It should be noted that relative performances were lower at MPPS (Fig. 4c, d).