Dispersing fibers in a water dispersion is an important issue for many fiber-based materials that significantly affects the mechanical and many other properties of materials. However, the measurement and assessment of the dispersion effect remains a significant challenge. In this study, we presented an image analysis method based on quadrat analysis from ecology and geography, transforming the issue of the dispersion effect into the statistics of point distribution. Furthermore, we changed the type of sampling and adjusted the shape, size and numbers of each quadrat to investigate its influences on the evaluation results. Our results showed that the area of one quadrat had a more obvious effect on the evaluation results compared to the number of quadrats. In addition, having a quadrat of an optimum shape enlarged the difference in various dispersion effects; the results of a square quadrat exhibited stably in both complete coverage and random sampling. Quadrat analysis realizes good measurement of dispersion states as a result of image processing and offers an assessment of the dispersion effect in a fiber–water dispersion.
RayesNSeehoferDHansenS, et al.
Early enteral supply of lactobacillus and fiber versus selective bowel decontamination: a controlled trial in liver transplant recipients.Transplantation2002;
74: 123–128.
5.
ChoT-HTanakaMOnishiH, et al.
Battery performances and thermal stability of polyacrylonitrile nano-fiber-based nonwoven separators for Li-ion battery. J Power Sources2008;
181: 155–160.
BakisCEBankLCBrownV, et al.
Fiber-reinforced polymer composites for construction—state-of-the-art review. J Compos Constr2002;
6: 73–87.
8.
BehabtuNYoungCCTsentalovichDE, et al.
Strong, light, multifunctional fibers of carbon nanotubes with ultrahigh conductivity. Science2013;
339: 182–186.
9.
LiuFHashimNALiuY, et al.
Progress in the production and modification of PVDF membranes. J Membrane Sci2011;
375: 1–27.
10.
GuanXYChenHRXiaH, et al. Flexible energy harvester based on aligned PZT/SMPU nanofibers and shape memory effect for curved sensors. Compos Part B Eng2020;
197.
11.
ChengKRamakrishnaSLeeK.Electromagnetic shielding effectiveness of copper/glass fiber knitted fabric reinforced polypropylene composites. Compos A Appl Sci Manuf2000;
31: 1039–1045.
12.
MouritzAPBannisterMKFalzonP, et al.
Review of applications for advanced three-dimensional fibre textile composites. Compos A Appl Sci Manuf1999;
30: 1445–1461.
13.
GoutianosSPeijsTNystromB, et al.
Development of flax fibre based textile reinforcements for composite applications. Appl Compos Mater2006;
13: 199–215.
14.
KamiyaRCheesemanBAPopperP, et al.
Some recent advances in the fabrication and design of three-dimensional textile preforms: a review. Compos Sci Technol2000;
60: 33–47.
15.
LinXZhuHYuanX, et al.
The elastic properties of composites reinforced by a transversely isotropic random fibre-network. Compos Struct2019;
208: 33–44.
16.
SoszynskiR.Simulation of two-dimensional nonrandom fibre networks: oriented rectangles with randomly distributed centroids. J Pulp Pap Sci1994;
20: J114–J118.
17.
GuanXYDongYBXiaH, et al.
Mechanical and shape memory performance of shape memory polyurethane-based aligned nanofibers. Polym Test2020;
91.
18.
NiQ-QGuanXZhuY, et al.
Nanofiber-based wearable energy harvesters in different body motions. Compos Sci Technol2020;
200: 108478.
19.
PfeiferSBandaruPR.A methodology for quantitatively characterizing the dispersion of nanostructures in polymers and composites. Mater Res Lett2014;
2: 166–175.
20.
BrookerRDGuildFJTaylorAC.Quantifying the dispersion of carbon nanotubes in thermoplastic-toughened epoxy polymers. J Mater Sci2011;
46: 3108–3118.
21.
YassinMFOhbaM.Effect of street geometrical layout on dispersion emissions of traffic exhaust: experimental simulation. Clean Technol Envir2013;
15: 167–177.
22.
NingFCongWQiuJ, et al.
Additive manufacturing of carbon fiber reinforced thermoplastic composites using fused deposition modeling. Compos B Eng2015;
80: 369–378.
23.
AliAShakerKNawabY, et al.
Hydrophobic treatment of natural fibers and their composites—a review. J Ind Text2018;
47: 2153–2183.
24.
WallenbergerFTWestonN. Natural fibersplasticsandcomposites.
Springer Science & Business Media, 2003. America.
25.
PramanikCGissingerJRKumarS, et al.
Carbon nanotube dispersion in solvents and polymer solutions: mechanisms, assembly, and preferences. ACS Nano2017;
11: 12805–12816.
26.
KazayawokoMBalatineczJMatuanaL.Surface modification and adhesion mechanisms in woodfiber-polypropylene composites. J Mater Sci1999;
34: 6189–6199.
27.
WangBSainM.Dispersion of soybean stock‐based nanofiber in a plastic matrix. Polym Int2007;
56: 538–546.
28.
LeerCCarneiroOSCovasJA, et al.
Dispersion of carbon nanotubes in polycarbonate and its effect on the composite properties.Mater Sci Forum2006; 514: 1125–1130.
29.
GuanXQianXYangZ.Comparison of several image analysis methods for fiber dispersion uniformity in water. J Disper Sci Technol2017;
38: 19–25.
30.
JayachandranA. Fundamentals of fiber dispersion in water. North Carolina State University, 2001. America.
31.
PerryJLiebholdARosenbergM, et al.
Illustrations and guidelines for selecting statistical methods for quantifying spatial pattern in ecological data. Ecography2002;
25: 578–600.
32.
GatrellACBaileyTCDigglePJ, et al.
Spatial point pattern analysis and its application in geographical epidemiology. Trans Inst Br Geogr1996: 21(1): 256–274.
33.
LucioPSde BritoNLC.Detecting randomness in spatial point patterns: a “Stat-Geometrical” alternative. Math Geol2004;
36: 79–99.
34.
StewartGHRoseAB.The significance of life history strategies in the developmental history of mixed beech (Nothofagus) forests, New Zealand. Vegetatio1990;
87: 101–114.
35.
DasDButolaBRenukaS.Optimization of fiber-water dispersion process using Box-Behnken design of experiments coupled with response surface methodology of analysis. J Disper Sci Technol2012;
33: 1116–1120.
36.
DasDButolaBRenukaS.An investigation into fiber dispersion behavior in water with reference to wet-lay nonwoven technology. J Disper Sci Technol2012;
33: 1225–1232.
