(557d) Surface Area Determination of Kevlar® Particles in Suspensions Containing Iron Impurities Using Low-Field Nuclear Magnetic Resonance Relaxometry
2020 Virtual AIChE Annual Meeting
(557d) Surface Area Determination of Kevlar® Particles in Suspensions Containing Iron Impurities Using Low-Field Nuclear Magnetic Resonance Relaxometry
Polymeric matrix composites (PMC)are engineeredmaterials designed toendureelevated mechanical and thermal stress.As an example, Kevlar®, commonly used to fabricate bulletproof vests,is also awell-knownfiber used in PMCs. Surface area and porosity are key characteristics enabling the dissipation of impact energy and regulating the chemical interactions in the interface of material layers. Common methods used in the characterization of theseattributeshave limitations for polymer particle suspensions such as Kevlar® pulps. Mercury intrusion provides uncertainties arising from damage to pores associated with high pressure.Nitrogen (N2) adsorption-desorption requires material outgassing at high temperatures, which may causepolymeric fibers to collapse.As an alternative, nuclear magnetic resonance (NMR) can be usedto characterize wetted surface areas of aqueous polymer particle suspensions under conditions similar to industrial application.The NMR response is influenced by the strength of fluid/particle surface interaction,and the surface area available, among other factors. Inthe presence of paramagnetic species, the NMR signal may be further affected and, if not accounted, yield misleading results. Therefore, a method to determine the wetted specific surface areas of Kevlar® particles in the presence of paramagnetic iron (Fe) impurities is proposed in this study.
The six different Kevlar® particles used in the experimentsweredivided into two main categories according to their particle sizes: pulps and micropulps. The latter species is obtained via size reduction of pulps. In their characterization,scanning electron microscopy (SEM) elucidated morphological differences, highlighting structural changes of Kevlar® pulps as they are milled to obtain the micropulps.Subsequently, BET gas adsorption was utilized to assess the specific surface area of samplesdried at either high orcryogenic (lyophilization) temperatures. The specific surface area of Kevlar® pulps was found to increase by as large as a factor of three when particle size was reduced by milling pulp materials (7 â 17 m2 g-1) to micropulps (20 â 24 m2 g-1). Furthermore, signs of particle collapsewere observed, as the lyophilized samples presented a higher specific surface area than the vacuum dried ones. Based on the noticeable differences in the SEM and BET results, Kevlar® samples were suspended in deionized water and analyzed using aNMR benchtop instrument, with a magnetic field of 0.47 T and a radio frequency of 20 MHz.Initially, the NMR relaxation rates were assumed to be strictly related to the wetted surface areas but to ensure the samples were uniform in composition, further investigation was done. Inductively coupled plasma optical emission spectroscopy (ICP-MS) indicated the presence of trace iron varying inthe range 11 - 2,633 ppm.In systems withparamagnetic impurities such as iron or manganese, the relaxation rate of the fluid will be enhanced via electron-proton coupling and may dominate the signal. To address the influence of iron, the surface relaxivity of Kevlar®, was determined as 0.7 µm s-1based on a linear relationship between the iron content and its perturbation of the transverse relaxation time T2 of the system. Lastly, the wetted specific surface area was calculated from the NMR data, wherevalues in good agreement with those obtained from the BET analysis of lyophilized samples were found. The trends related to the foreseen effects of polymer drying and particle size reduction were also present.It is envisioned that the present method can be expanded to a large set of polymer chemistries and could enable high-throughput wetted surface area measurements. The ability toaccomplish complete analyses within a much shorter time than the BET method is also an attractive feature over conventional methodology.