EVALUATION OF FUNDAMENTAL PARAMETERS FOR QUANTITATIVE X-RAY FLUORESCENCE OF POLYOLEFINS. The Dow Chemical Company, Freeport, TX 77541

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1 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN EVALUATION OF FUNDAMENTAL PARAMETERS FOR QUANTITATIVE X-RAY FLUORESCENCE OF POLYOLEFINS Abstract: Authors: Burns, D.W. *, Wright, M. *,Yusuf, S.O. + * The Dow Chemical Company, Freeport, TX The Dow Chemical Company, Midland, MI X-ray fluorescence (XRF) is an established technology for elemental analysis of polyolefins. XRF is a matrix dependent analysis and accurate results require standards of similar matrices. The preparation of blended, matrix-matched polymer standards requires extensive effort and resources. Another quantitative approach is fundamental parameters (FP) analysis, where standards are either pressed powders or glasses of pure elements or oxides and unlike the sample s matrix. PANalytical s Omnian FP software was evaluated for polyolefins analysis by comparing Omnian data against traditional matrix-matched polymer calibrations. The matrix-matched standards were characterized by inductively coupled plasma atomic emission, neutron activation analysis (NAA) or mass additions. Prior to collecting data for this study, the Omnian software was optimized by supplementing the calibrations with a few polymer standards, creating channels for targeted elements to improve count rates and using the Compton backscatter peaks to estimate the polymer matrix. Over a period of several months, polymer samples were analyzed using Omnian and matrix-matched polymer calibrations. For polymer samples (master batches, preblends, or compounded polymers) where matrix-matched standards were not available or elemental concentrations were high, neutron activation was used to evaluate Omnian results.

2 This document was presented at the Denver X-ray Conference (DXC) on Applications of X-ray Analysis. Sponsored by the International Centre for Diffraction Data (ICDD). This document is provided by ICDD in cooperation with the authors and presenters of the DXC for the express purpose of educating the scientific community. All copyrights for the document are retained by ICDD. Usage is restricted for the purposes of education and scientific research. DXC Website ICDD Website -

3 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Introduction X-ray fluorescence (XRF) has been an established technology for elemental analysis within The Dow Chemical Company for over twenty years. An internal search of Dow R&D reports with the keyword X-ray fluorescence generates over 1200 references. XRF is a matrix dependent analysis, so the observed signal for any given element will vary as the other elements within the sample vary. For accurate quantitative results, this matrix dependence requires samples and standards to be of similar matrices which can be accomplished in a number of ways, such as standard addition or dilution in a common matrix. Additives can be blended into the polymer matrix and characterized, thus allowing routine analysis in a manufacturing environment. The preparation of blended, matrix-matched standards requires extensive effort and resources. Another quantitative approach would be to use fundamental parameters (FP) analysis. In 1968, Criss and Birks compared empirical and fundamental parameter analysis for providing quantitative XRF data (1). The fundamental parameters approach calculates composition based upon the element s observed fluorescence relative to mass absorption coefficients, fluorescence yields, and primary excitation source (2). Because a traditional calibration curve is not constructed and the standards used to calibrate the software are not like the samples, the FP approach is sometimes referred to as a standardless analysis. These standards must be well characterized and can be NIST traceable materials or pure element / oxides in fused glasses or pressed powders. The sample must be flat and homogeneous. If the sample is not infinitely thick in terms of X-ray emission, then the software needs to correct for this effect in its calculations. Within The Dow Chemical Company, fundamental parameters has been used for many years, including the Criss XRF11 software, UniQuant, PCFPW (Fundex Software & Technology, Inc), PANalytical s IQ+ and PANalytical s Omnian. Most manufactures of X-ray fluorescence spectrometers offer some form of fundamental parameters software. At one time, UniQuant was offered with Philips spectrometers and is now offered with Thermo Scientific instruments. PANalytical, formerly Philips, currently offers a fundamental parameters program, Omnian which replaced IQ+. Both UniQuant and Omnian use pure metals and/or pressed oxide powders or glasses to calibrate the software. One significant difference between UniQuant and Omnian is how the data is collected. UniQuant uses channels (peak hooping to a specific 2-theta wavelength) to collect count rates and calculates the background from a few select channels, while Omnian uses 11 spectral scans to collect count rates and backgrounds. Because of the spectral scans, Omnian can provide both qualitative and quantitative data. With the qualitative analysis, Omnian automatically assigns emission peaks and provides a visual confirmation that an element is actually detected which cannot be done with UniQuant. In addition to the spectral scans in Omnian, individual channels can be included to collect count rates at specific wavelengths to improve the sensitivity for that element with the background measured from the scan. Both programs can correct for the sample s matrix and thickness. In addition to the

4 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN supplied Omnian standards, well characterized standards can be tagged and included in the calibration to improve the accuracy for a specific matrix. Neutron activation analysis is used extensively by the National Institute of Standards and Technology (NIST) for chemical analysis and certifying reference materials. A number of analytical techniques are used by NIST to characterize their reference materials, including instrumental neutron activation analysis (INAA or NAA), radiochemical neutron activation analysis, prompt gamma ray activation analysis, neutron depth profiling (NDP) and neutron focusing. More details concerning these techniques can be found at the NIST webpage (3). The Dow Chemical Company began operation of the TRIGA reactor in This capability has provided the company with a unique competitive advantage for elemental analysis using NAA and its role was previously described (4). The technique has been used as a valuable problem solving tool for many sample matrices, including catalyst (5) and polymers (6). As stated by NIST, INAA does not require sample dissolution and depends on the nuclear rather than atomic properties of the element of interest so that any sources of uncertainty or bias in INAA are independent of those associated with most other techniques of chemical analysis (3). Within Dow, NAA is often used as a referee technique for other elemental techniques on many elements and differing matrices and it has been used to characterize various materials for use as XRF calibration standards. Two separate studies were performed to evaluation the fundamental parameters Omnian software for polyolefins analysis. The first study compared Omnian results relative to data using matrixmatched calibrations where numerous analyses (>200) of routine polymer samples were measured over several months. In the second study, 14 polymer blends were measured by Omnian and NAA and results compared for a number of elements. Experimental A PANalytical Axios wavelength dispersive X-ray spectrometer was used in this study. The spectrometer was equipped with a rhodium X-ray tube anode and operated at 2.4 kw power for all measurements using vacuum conditions. Because of the relatively low power, little or no degradation occurred from during the analysis of the polymer plaques. The Axios software is called SuperQ and is used to setup specific applications for routine analysis. The Omnian software is embedded in the SuperQ Setup section of the software. The SuperQ channel set conditions for the Polymer1 application (using matrix-matched calibration) is shown in Table 1. The polymer standards used to calibrate the Polymer1 application are presented in Table 2. The fifteen polymer standards were characterized using ICP (Al, Ca, Na, Ti, and Zn), NAA (Al, Ca, Cl, Na, Ti and Zn), XRF fundamental parameters (Si) or from gravimetric addition data (P and S).

5 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN The Omnian conditions for the spectral scans are presented in Table 3. The Omnian standards were pure element oxides and pressed powders of known concentrations. Separate stable glass monitors were measured for Polymer1 and Omnian to correct for any instrumental drift. The SuperQ calibration summary for the Polymer1 application is summarized in Table 4. Table 1: SuperQ channel set used to calibrate Polymer1 application Channel Na Mg Al Si P S Cl Ca Ti Zn Line KA KA KA KA KA KA KA KA KA KA Crystal PX1 PX1 PE PE Ge Ge Ge LiF LiF LiF Collimator Detector Flow Flow Flow Flow Flow Flow Flow Flow Flow Scint Tube filter None None None None None None None None None None kv ma Angle Offset Bg Offset Bg Offset Bg Offset Bg4 1.7 ( 2T) PHD1-LL PHD1-UL Table 2: Polymer standards used to calibrate Polymer1 application Std # Mg Al Ca Ti Cl Na Zn Si P S <1 < < <1 < < <1 < <1 < < < < < <1 < < < < < < < < < < Standards (6, 10, 11, 14) highlighted in red were used as tagged standards in the Omnian calibration. The matrix was assumed to be CH2.

6 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Table 3: Omnian scan conditions and parameters KA range Te-Ce Mo- Nb-I Kr- Zn- V- K-V P-Cl Si-Si Al- O- LA range Ra- Re- Pr- In- Zr- Rb- Br- V- Crystal LiF 220 LiF LiF LiF LiF LiF LiF Ge1 PE0 PE0 PX1 Collimator 150 µm Detector Scint. Scin Scint. Scint Scint Flow Flow Flow Flow Flow Flo Tube filter Brass Non Brass Al Al Non Non Non Non Non Non Start angle End angle Step size Time (s) Time/step (s) Speed ( 2T/s) kv ma PHD1-LL PHD1-UL Table 4: Calibration summary for SuperQ Polymer1 application Element Na Mg Al Si P D: E: RMS: K: Lo(C) for Zn Element S Cl Ca Ti Zn D: E: RMS: K: D is the intercept and E is the slope of the regression line. RMS is the Root Mean Square and indicates the goodness of the regression for no error weighting. K is the goodness of the regression for Square Error Weighting and this function was used for all the regressions. Lo(C) is the correction factor for Zn on Na and is calculated as a concentration function. A Buehler SimpliMet 3000 mounting press was used to hot press 50-mm diameter plaques. The following pressing conditions were used: sample weight (10 ± 0.01 g), heat time (1.0 min), cool time (3.0 min), pressure (1200 psi), temperature (260 C for polyethylene and 290 C for polypropylene) and mold size (50 mm). As opposed to traditional presses (plates with shims), the SimpliMet press presses one plaque at a time, where pressure is continuously applied to the polymer during heating and cooling resulting in high quality molded plaques. For data

7 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN collection, the plaque was first analyzed using the Polymer1 application and followed by Omnian measurements. Neutron Activation Analysis (NAA) Neutron activation analyses were performed using Dow TRIGA Research Reactor in Midland, MI. Because of the complexity of the blends and master batches, three separate NAA conditions were used. NAA Condition 1: Duplicate samples were prepared by transferring approximately 0.05 grams of the blends into pre-cleaned 1/4 dram vials. Standard aliquots of Al, Ca, S, Si, Ti, Ni, Mg, Na, Cl, Sn, Mn, Rb and Nb were prepared in similar vials by taking appropriate amounts. The samples and standards were sequentially irradiated for 2 min at 100kW reactor power using the pneumatic transfer system of the reactor. After waiting 4 min for each sample, gamma spectroscopy was carried out for 4.5 min. The concentrations of the Al, Ca, S, Si, Ti, Ni, Mg, Na, Cl, Sn, Mn, Rb and Nb in the blend were calculated using CANBERRA software and the standard comparative technique. A correction for the interference of silicon on aluminum and the interference of aluminum on magnesium were corrected, as described previously by Yusuf (6). NAA Condition 2: Duplicate samples were prepared by transferring approximately 0.25 grams of the blends into pre-cleaned 1/4 dram vials. Standard aliquots of Na, Br, Zn, K and Cu were prepared into similar vials by taking appropriate amounts. The samples and standards were sequentially irradiated for 10 min at 250kW reactor power in rotary specimen racks in the reactor. After a waiting time of 5 hrs, the gamma spectroscopy was carried out for 1 hr 6 min. The concentrations of the Na, Br, Zn, K and Cu in the blends were calculated using CANBERRA software and the standard comparative technique. NAA Condition 3: Duplicate samples were prepared by transferring approximately 0.25 grams of the blends into pre-cleaned 1/4 dram vials. Standard aliquots of Cd, Cr, Sr, Fe, Rb, Zr, Nb and Na were prepared into similar vials by taking appropriate amounts. The samples and standards were irradiated for 2 hrs at 250kW reactor power in rotary specimen racks in the reactor. After a waiting time of 16 hrs, the gamma spectroscopy was carried out for 1 hr 23 min. The concentrations of the Cd, Cr, Sr, Fe, Rb, Zr, Nb and Na in the blend were calculated using CANBERRA software and the standard comparative technique. Inductively Coupled Plasma (ICP) Atomic Emission A Perkin Elmer Optima 8300 ICP spectrometer was used in the present study to measure magnesium and aluminum in DHT-4A master blends. The following conditions were used: power 15 W; plasma (Ar) 15 L/min; auxiliary (Ar) 0.2 L/min; nebulizer (Ar) 0.65 L/min; peristaltic pump 1.5 ml/min. Multiple wavelengths (nm) were used: Mg (285.21; ), Al ( ; ). NIST traceable multi-element standards were used for ICP calibration.

8 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN For ICP preparation, samples were weighed into 60 ml quartz crucibles. Two ml of concentrated sulfuric acid was added and ashed in a programmable muffle furnace. The furnace temperature was ramped up to 300 C, held for 1 hr, ramped up to 550 C, held for 3 hr and then turned off and allowed to cool to ~50 C. The ash was digested in hot aqua regia. The digest was quantitatively transferred and diluted to a final weight for ICP analysis. Optimizing Omnian Results and Discussion Prior to beginning this study, a new Omnian calibration was performed using a 37-mm channel mask. Prior to the recalibration, channels for the elements of interest were included with a 10 sec counting for each channel. In addition, four polymer standards were tagged (see Table 2) and included in the calibration. The Compton backscatter peak was utilized to correct for the sample s matrix. Comparing Omnian vs Matrix-Matched Calibrations The detection limit for XRF analysis is inversely proportional to the square root of the counting time on the background. The integration times for the channels (peak and background) in the Polymer1 application was 30 sec for most elements, except sulfur (60 sec) and titanium (90 sec). Since the Omnian application is based on scans, the integration time for the background is very short (i.e sec/step); thus Omnian cannot be considered a trace level analysis and comparisons of Polymer1 and Omnian data at low concentrations would be inappropriate. Thus, an arbitrary level of 20 ppm was set for most elements as the lower level to begin comparing data. Titanium: Although titanium can be present in polymers as TiO 2, the element at low concentrations is usually present as a catalyst residue and typically below 5 ppm. Of the 271 samples evaluated in this study, there were only six samples which Polymer1 showed levels above 7 ppm. As shown in Table 5, titanium ranged from 7.5 ppm to 1560 ppm. The highest standard in the Polymer1 calibration was 13 ppm, so even though XRF calibrations can be linear over 5-6 orders of magnitude, comparing samples at levels of 1500 ppm may be inappropriate. Even so, Omnian results were all within ±10% for Polymer1 data.

9 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Table 5: Comparison of titanium results (ppm) for Polymer1 and Omnian LIMS # Polymer1 Omnian % Difference Average -4.2 Sulfur: Only a few samples showed sulfur with concentration above 20 ppm, so limited conclusions can be reached concerning how well Omnian measures sulfur in polyolefins. The data in Table 6 suggests as the concentration increases; results may possibly improve. Table 6: Comparison of sulfur results (ppm) for Polymer 1 and Omnian LIMS # Polymer1 Omnian %Difference a a a a a Aluminum: For aluminum, 115 samples showed concentrations above 20 ppm. Figure 1 shows plot of the percent difference between Omnian and Polymer1 data versus Polymer1 aluminum concentration (ppm). Most of the percent difference data was within ±5% with a mean percent difference of 2.36% indicating very good agreement. Figure 1: Percent difference between Omnian and Polymer1 versus aluminum (ppm)

10 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Calcium: For calcium, 114 samples showed concentrations above 20 ppm. Figure 2 shows the percent difference between Omnian and Polymer 1 data versus Polymer1 calcium concentration. Most of the percent difference data was within ±5% with a mean percent difference of 1.20% indicating very good agreement. Figure 2: Percent difference between Omnian and Polymer 1 versus calcium (ppm) Chlorine: For chlorine, there were 119 samples with concentrations above 20 ppm. Figure 3 shows the percent difference between Omnian and Polymer1 data plotted against Polymer1 chlorine concentration (ppm). The differences showed very poor agreement with a mean percent difference of 65%, but tended to improve with increasing concentration. Figure 3: Percent difference between Omnian and Polymer1 versus chlorine (ppm) A significant problem with measuring low levels of chlorine in polyolefins is the background. The Kα peak for chlorine is very near one of the Rh Lα peaks from the X-ray tube. Figure 4 shows spectral scans for the chlorine channel in the Polymer1 application, where the large peak is the Ausmon drift monitor. In the other scan of a blank polyethylene sample, the four background correction points are shown which are fitted to a polynomial in the SuperQ software.

11 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Figure 4: Spectral scans for the Polymer1 chlorine channel Figure 5 shows an Omnian spectral scan for a QC sample with a chlorine concentration of about 20 ppm. In the Omnian scan, note the relative noisy background. Because SuperQ is able to use the peak channel with surrounding background points to acquire data at each point for 30 sec, it is better able to correct for the sloping background from the Rh X-ray tube and acquire more accurate data at low concentrations and count rates. Omnian is scanning rapidly (Speed: 2-theta/sec = 0.5) and thus not able to measure the background as accurately. The data collected so far suggests as the chlorine concentration increases, and thus the background becomes less important, there is better agreement with Polymer1 data, although there does appear to be a consistent bias that persists even at the higher concentrations measured. Figure 5: Omnian spectral scan in the chlorine region Magnesium: For magnesium, there were 91 samples with concentrations above 20 ppm. Figure 6 shows the percent difference between Omnian and Polymer1 plotted against Polymer1 magnesium concentration (ppm). The mean percent difference was 8.75% and Omnian results appeared to show marked improvement as the concentration reached about 50 ppm relative to Polymer1 data.

12 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Figure 6: Percent difference between Omnian and Polymer1 versus magnesium (ppm) Silicon: For silicon, there were 114 samples with concentrations above 20 ppm. Figure 7 shows the percent difference between Omnian and Polymer1 plotted against Polymer1 silicon concentration (ppm). Although the mean percent difference was for this data set 9.79%, comparisons below 100 ppm ranged from 4.9% to 88%. At silicon concentrations above 100 ppm, a negative bias of about 11% was obtained for the comparisons. The source of the negative bias is not known. The Polymer1 standards for silicon were characterized using XRF fundamental parameters (PCFPW software). PCFPW was calibrated with oil based standards and may have had stability issues or surface interactions, so it is possible a bias was introduced. Ideally, characterization of the standards should be done using an independent analytical technique, but at the time, XRF-FP was the best option. Figure 7: Percent difference between Omnian and Polymer1 versus silicon (ppm) Sodium: For sodium, there were 84 samples with concentrations above 20 ppm. Figure 8 shows percent difference between Omnian and Polymer1 plotted against Polymer1 sodium concentration (ppm). The mean percent difference was 42%, but Omnian results appeared to show some improvement as the concentration reached about 1500 ppm relative to Polymer1 data.

13 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Figure 8: Percent difference versus sodium (ppm) for Polymer1 and Omnian data Clearly, Omnian did not compare favorably for sodium relative to Polymer1 data. There may be a number of reasons for these poor results. Because the X-rays emitted by sodium in the samples are softer, the signal is adversely affected by surface changes and contamination. In addition, it was learned during the Omnian training class that the sodium standard (Std B) can absorb water from the atmosphere. It was recommended that the Omnian standards be stored in a desiccator. This was not done initially; so given the humid air of the US Gulf Coast, this standard may have been compromised. Unfortunately, the Omnian standards are sold as a set and cannot be purchased individually. Therefore, sodium can be measured for qualitative analysis and levels below ~1500 ppm, but any quantitative results above 1500 ppm should be considered semiquantitative, i.e. ±30%. Further, evaluation of sodium at higher concentrations would be desirable in the future. Phosphorus: For phosphorus, there were 168 samples with concentrations above 20 ppm. Figure 9 shows percent difference between Omnian and Polymer1 data plotted against phosphorus Polymer1 concentration (ppm). The mean percent difference was -4.12% and the majority of the Omnian results showed a negative bias relative to Polymer1 data which tended to become more pronounced with increasing concentration. The reason for this trending in Omnian data and whether the trend increases at higher concentrations is not known at the present time. But even with this negative bias trend, the Omnian results were within 10% of the Polymer1 data.

14 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Figure 9: Percent difference between Omnian and Polymer1 versus phosphorus (ppm) Zinc: For zinc, there were only 30 samples with concentrations above 20 ppm. Figure 10 shows the percent difference between Omnian and Polymer1 plotted against Polymer1 zinc concentration (ppm). The mean percent difference was 0.58% and most of the Omnian results were within ±8% relative to Polymer1 data. Figure 10: Percent difference between Polymer1 and Omnian versus zinc (ppm) Comparing Omnian versus NAA for polymer blends As discussed above, Omnian was compared to results from calibrations using matrix matched polyolefins standards. Master batches or pre-blends tend to have much higher elemental concentrations than typically found in polyolefin products and thus beyond the upper range of the matrix matched calibrations. To evaluate the accuracy of Omnian where matrix matched standards are not readily available or very difficult to blend, NAA was used. Table 7 presents Omnian and NAA results in ppm for the 14 polymer blends. Blank cells mean the element was not detected by Omnian (i.e. a peak was not observed in the Omnian spectra). Because of the complexity of the materials and limitations of NAA, comparisons of some elements (Fe, Ni, P, Pb, Rb, S, Si and Sr) were not possible, either because the concentrations

15 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN were too low or other elements interfered with measurement. Table 8 presents the Omnian results in ppm for the elements not detected or not measured by NAA under the chosen experimental conditions. There were a few exceptions. For example, the NAA detection limit (~3000 ppm) for iron is very high using the procedure for the combined elements in this matrix; but one sample contained about 10% iron, so a comparison was possible. NAA is capable of measuring iron even at much lower levels, but the needed experiments would have created long lived isotopes and thus not a favorable choice for this project. Similarly, only four out of the 14 samples had high enough magnesium levels for NAA to measure under the chosen experimental conditions. Figure 11 shows the polymer blends used in this study. The origins of these blends were from Dow Plastics TS&D or external Dow customers. As can be seen, several have high levels of colorants associated with elements such as Cu, Cr, Fe, Pb, Ti and Al/Mg from talc. The white blends are indicative of high levels of TiO 2. From an analytical perspective, these blends represent a very difficult, complex matrix and are a challenge for most analytical techniques. In all of the blends, there are several hundred ppm to high percent levels of Ti as TiO 2. This high of TiO 2 would make ICP sample preparation very difficult, if not impossible. For NAA, certain combinations of elements have known matrix effects as well. For example, silicon can interfere with aluminum and aluminum can interfere with magnesium, so silicon may also affect magnesium (6). High levels of one element may dictate different NAA conditions for other elements or make it difficult to measure using typical NAA conditions. So analysis of these complex materials is a non-trivial measurement.

16 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Figure 11: Polymer blends used for comparing Omnian and NAA Table 7: Omnian and NAA results (ppm) for the polymer blends Al Al Br Br Ca Ca Cd Cd Blend Omnian NAA Omnian NAA Omnian NAA Omnian NAA a b c d e f g

17 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN h i j k l m n Table 7: Omnian and NAA results (ppm) for the polymer blends (continued) Cl Cl Cr Cr Cu Cu Fe Fe Blend Omnian NAA Omnian NAA Omnian NAA Omnian NAA a b c d e f g h i j 73 k l m 96

18 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN n Table 7: Omnian and NAA results (ppm) for the polymer blends (continued) K K Mg Mg Mn Mn Na Na Blend Omnian NAA Omnian NAA Omnian NAA Omnian NAA a b c d e f g h i j k l m n Table 7: Omnian and NAA results (ppm) for the polymer blends (continued) Nb Nb Sn Sn Ti Ti Zn Zn Blend Omnian NAA Omnian NAA Omnian NAA Omnian NAA a

19 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN b c d e f g h i j k l m n Table 8: Omnian results (ppm) for the polymer blends not measured by NAA Mo Ni P Pb Rb S Si Sr Blend Omnian Omnian Omnian Omnian Omnian Omnian Omnian Omnian a b c d e f g

20 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN h i j k l m n Aluminum: Omnian measured aluminum in all the blends in this study with results (Table 7) ranging from 56 ppm to 3.66%. Figure 12 compares Omnian and NAA results for aluminum in the polymer blends. Excluding two blends (c and n), Omnian results agreed very well with NAA data. Of the 14 blends, the percent difference for 10 blends was less than ±10%. Blend c" proved to be a very troublesome sample; and as will be seen, percent differences for Ca, K, Mg, and Na were also higher than other blends. This blend was re-analyzed by NAA and Omnian, but results did not significantly change. It was also observed that the material flaked off during NAA and may have not been homogeneous. Unfortunately, there was a limited amount of this blend, so further evaluation could not be done. Figure 12: Comparison of Omnian and NAA for aluminum in polymer blends Calcium: Omnian measured calcium in all the blends in this study with results (Table 7) ranging from 19 ppm to 7.7%. The NAA detection limit for calcium was estimated to be ~50 ppm. Omnian reported several blends with levels above 50 ppm, but were not detected by NAA. Omnian spectral scans showed calcium peaks, so its presence is not in question. Figure 13 compares Omnian and NAA results for calcium in the polymer blends. Two blends (c and e) showed relatively large differences between Omnian and NAA. The percent difference of four other blends was within ±15%.

21 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Figure 13: Comparison of Omnian and NAA for calcium in polymer blends Chlorine: Omnian measured chlorine in all the blends in this study with results (Table 7) ranging from 19 ppm to 7.7%. The NAA detection limit for chlorine in these matrices was estimated to be ~100 ppm. Figure 14 compares Omnian and NAA results for chlorine. Four of the eight comparisons showed agreement within ±15%, but four other blends showed higher percent differences. For one blend (h), Omnian was 73% lower than NAA. Relative to the other 13 blends, this blend had a significantly higher level (~10%) of iron present which may have caused the discrepancies. In addition to iron, there were other transition metals (Cr, Cu, Mn, Ti and Zn) present in this blend. Figure 14: Comparison of Omnian and NAA for chlorine in polymer blends Copper: Omnian measured copper in five of the blends with results (Table 7) ranging from 169 ppm to 1%. As can be seen in Figure 15, Omnian and NAA showed good agreement with percent differences of 11% or better.

22 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Figure 15: Comparison of Omnian and NAA for copper in polymer blends Potassium: Omnian measured potassium in nine blends with results (Table 7) ranging from 33 ppm to 1.56%. Figure 16 compares Omnian and NAA results for potassium in the polymer blends. Three blends (e, g and h) were detected by NAA, but there were no peaks in the Omnian spectral scans. In blend f, Omnian measured 96 ppm of potassium, but was not detected by NAA. The other eight blends showed mixed comparisons. Four blends had percent differences within ±14%; while four other blends had percent differences greater than 20%. Blend k showed a 106% difference. The reason for these inconsistent comparisons is not known, a couple of possibilities are sample inhomogeneity or unknown interferences. Figure 16: Comparison of Omnian and NAA for potassium in polymer blends Magnesium: Omnian measured magnesium in all of the blends with results (Table 7) ranging from 17 ppm to 0.13%. NAA was only able to measure magnesium in five blends. Figure 17 compares Omnian and NAA results for magnesium. Poor agreement was found between

23 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Omnian and NAA with the percent difference ranging from 23% to 88%. As with Ca, K, and Na, blend c compared very poorly for magnesium. Figure 17: Comparison of Omnian and NAA for magnesium in polymer blends Previously in a separate study, a DHT-4A master batch was measured by Omnian and NAA. The results compared very well for magnesium with a 3% recovery. In another study, several different DHT-4A master batches were analyzed by ICP, NAA and Omnian. Table 9 compares ICP, NAA and Omnian results for aluminum and magnesium. Omnian results for magnesium were within ±7% of the ICP results and -3% of the NAA result. Previously, the improvements and corrections in the accuracy of NAA measurements of aluminum and magnesium in the presence of silicon were described (6). The agreements seen in this example between NAA, ICP and Omnian are typical and are within the expected uncertainties of the techniques. Table 9: Comparison of Omnian, ICP and NAA results for aluminum and magnesium ICP Omnian ICP Omnian Sample ID Al (%) Al (%) %Difference Mg (%) Mg (%) %Difference NAA Omnian NAA Omnian Sample ID Al (%) Al (%) %Difference Mg (%) Mg (%) %Difference A Sodium: Omnian measured sodium in all of the blends with results (Table 7) ranging from 53 ppm to 1.7%. As discussed in the comparisons of Omnian and Polymer1, it was suggested that levels below 0.15% were not reliable for quantitative measurements and levels above 0.15%

24 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN should be considered semi-quantitative (±30%). As shown in Table 7 and Figure 18, some of the comparisons for Omnian and NAA showed good agreement, but most results showed significant differences. Table 7 also shows results for copper and zinc. Figure 19 shows the Omnian spectrum for the blend e in the region of the sodium Kα fluorescence line. Both zinc (Lα and Lβ1) and copper (Lβ3) are direct line overlaps on sodium Kα. Although copper Lβ1 and Lα do not directly overlap sodium Kα, the close proximity may also interfere with sodium. Omnian can automatically apply a correction for line overlaps. Current Omnian software does not correct for line overlaps from copper. The comparisons in Table 7 suggest the correction factor from zinc s overlap could be improved and a new factor for copper included. These improvements were discussed with PANalytical application specialists and the procedure for empirically determining the overlap correction factor was reviewed. Figure 18: Comparison of Omnian and NAA for sodium in polymer blends

25 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Figure 19: Omnian spectrum in region of sodium (Kα) fluorescence Titanium: Omnian measured titanium in all blends with results (Table 7) ranging from 227 ppm to 44%. Figure 20 compares Omnian and NAA results for titanium in the polymer blends. All of the comparisons were less than ±20% and all but three were ±10%. As discussed in the comparisons of Omnian and Polymer1, comparisons between Omnian and the matrix matched calibration over the range of 8 ppm to 0.15% were within ±8%. The primary issue with the titanium matrix matched calibration was that the highest calibration was 13 ppm. The current data shows that accurate results for titanium can be obtained by Omnian across a wide concentration range. Figure 20: Comparison of Omnian and NAA for titanium in polymer blends Zinc: Omnian measured zinc in all the blends with results (Table 7) ranging from 5 ppm to 0.20%. NAA measured zinc in 9 of the 14 blends. The estimated NAA detection limit was 70 ppm. Figure 21 compares zinc results for Omnian and NAA in the polymer blends. The percent difference range from -8.9% to 14%.

26 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Figure 21: Comparison of Omnian and NAA for zinc in the polymer blends Miscellaneous Elements: Several elements were detected in only a few blends, including bromine, cadmium, chromium, iron, manganese, niobium, and tin and were at sufficient concentrations to allow comparisons between Omnian and NAA. Table 7 presents Omnian and NAA results in ppm for these elements and are compared in Figures 22 and 23. Of these elements, cadmium showed the poorest agreement (-24% difference). For iron, Omnian measured iron in 10 of the 14 blends with results (Table 7) ranging from 27 ppm to 9.6%. Because NAA has a poor detection limit (~3000 ppm) for iron, it is usually not routinely measured; but one blend contained iron levels which were high enough to allow comparison of Omnian and NAA and showed good agreement with a -5.6% difference. Although tin would normally not be a common element in polymers, Omnian measured the element in three of the 14 blends and results agreed within 5% of NAA results. Omnian measured manganese in three of the blends with results ranging from 43 to 94 ppm and agreed within 10% of NAA results. Omnian measured chromium in two blends and results were within 10% of NAA results. Figure 22: Comparison of Omnian and NAA for bromine, chromium and manganese in the polymer blends

27 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN Figure 23: Comparison of Omnian and NAA for cadmium, niobium, tin, chromium and iron in the polymer blends Comparing Omnian XRF-FP and NAA Because of the complex matrix of the polymer blends and NAA limitations and experimental conditions used, comparisons of some elements (Fe, Ni, P, Pb, Rb, S, Si, Sr, and Zr) were not possible, either because the concentrations were too low or other elements interfered with the NAA measurement. Although NAA is not usually affected by the sample s matrix, high levels of certain elements may make it either difficult or impossible to measure other elements of interest using the chosen experimental NAA conditions and setup. The Omnian and the fundamental parameters approach don t suffer from these limitations. Excluding line overlaps, Omnian spectral scans allow an unequivocal identification of the presence of an element and semi-quantitative results can be calculated. In Dow Chemical, NAA is often used as a reference or referee technique for elemental analysis for many different samples types. The choice of whether to use NAA or some other technique is determined by a number of factors: time, cost, priority, needed accuracy, and possible waste from long-lived isotopes. Thus, for the analysis of complex polymer blends, Omnian fundamental parameters analysis would be the method of choice and be able to provide valuable elemental data where NAA is not favorable. Comparing XRF-FP and matrix-matched calibrations When measuring more complex samples such as master batches, blends and compounded polymers, there are other reasons to use fundamental parameters over matrix-matched calibrations. When an additive is present as high percent levels, this could change the matrix enough so that the sample is no longer matrix-matched relative to the standards used in the calibration. Omnian and other suppliers of fundamental parameters software are able to handle such changes in the matrix because the fundamental parameters calculations include mass absorption coefficients and fluorescent yields for all measureable elements. Using the Compton peak to calculate the effects of the matrix also improves the accuracy of the technique. Another problem with matrix-matched calibrations would be spectral interferences and overlaps. As an element s concentration increases, other fluorescent lines (Lα, Lβ, Mα 1, Mα 2, etc ) can

28 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN become significant and overlap other elements of interest. Matrix-matched calibrations can handle this type of overlap but standards need to be prepared appropriately. This was done for the Polymer1 standards to correct for the Zn Lα interference on Na Kα. The Omnian software applies overlap corrections for most common interferences, but as this study documents, the overlap correction of copper (Lβ3) on sodium Kα is not included in the software. The lack of this interference correction was discussed with PANalytical; and currently, Omnian only applies these overlap corrections for elements with atomic number of 30 or higher. It is possible for the user to determine these overlap corrections empirically and enter the correction factors into the overlap table of the Omnian software. At the time of this report, an empirical correction has not been done by the authors. It is highly recommend PANalytical and other suppliers of fundamental parameter software include all potential overlap interference corrections in their product. Conclusions The purpose of the current report was to document the evaluation of the PANalytical Omnian FP software for polyolefin analysis relative to matrix-matched calibrations and NAA. At levels of 20 ppm and above, the mean percent difference between Omnian and matrix-matched calibration results were found to be ±10% or better for the following elements: aluminum, calcium, magnesium, phosphorus, and zinc. At levels above 100 ppm, silicon showed good agreement, but tended to show a negative bias. Because of the low concentrations of titanium and sulfur in the samples, fewer comparisons were possible, but results were generally within ±20%. Unacceptable results were obtained for chlorine (±65%) because of possible background correction issues with Omnian and for sodium (±40%) due to the possible absorption of water in the Omnian standard prior to calibration. The accuracy of all elements improved with increasing concentration. For polymer blends, comparisons between Omnian and NAA show very good agreement (usually better than ±20%) for the following elements: aluminum, bromine, calcium, chromium, copper, iron, manganese, niobium, tin, titanium and zinc. Other elements (cadmium, chlorine, potassium, magnesium and sodium) showed poorer agreement of ±20% or greater. Some of these differences may have been due to Omnian calibrations (Na), sample inhomogeneity or unknown NAA interferences or poor sensitivity for the chosen experimental conditions. Nickel, phosphorus, lead, rubidium, sulfur, silicon and strontium were able to be measured by Omnian but were not measured in the blends by NAA under the chosen experimental conditions. The data from these evaluations show that Omnian fundamental parameters analysis can provide valuable elemental data for the analysis of complex polyolefin blends; and relative to NAA, be a more useful analytical tool.

29 Copyright JCPDS-International Centre for Diffraction Data 2014 ISSN References 1) Criss, J.W. and Birk, L.S. (1968). Calculation Methods for Fluorescent X-Ray Spectrometry Empirical Coefficients vs. Fundamental Parameters, Anal. Chem., 40, ) Bertin, E.P. (1975). Principles and Practices of X-ray Spectrometric Analysis (Plenum Press, New York), 2 nd ed., p ) National Institute of Standards and Technology webparge: 4) Rigot, W.L et al. (2000). The role of neutron activation analysis at The Dow Chemical Company, JRNC, 243, pp ) Yusuf, S. et al. (2013). Improving neutron activation analysis accuracy for the measurement of gold in the characterization of heterogeneous catalyst using a TRIGA reactor, JRNC, 296, pp ) Yusuf, S. (2009). Improving the Detection Limit of Silicon, Magnesium and Aluminum in NNA of Polymers Using a TRIGA Reactor, JRNC, 282, pp