Categorization of Papers by Trace Metal Content Using Atomic Absorption Spectrometric and Pattern Recognition Techniques P. J. Simon,' B. C. Giessen, and 1.R. Copeland" Department of Chemistry and The Institute for Chemical Analysis, Applications, and Forensic Science, Northeastern University, Boston, Massachusetts 02 115
Nineteen paper samples representing eleven different types of paper from seven manufacturers were analyzed for Cu, Mn, Sb, Cd, Cr, Co, Ag, Pb, Mg, and Fe using electrothermal atomization atomic absorption spectrometry. Unsupervised learning pattern recognition techniques were utilized for data analysis. Only six features were needed to identify 16 of 19 papers completely. The three not completely separated came from different manufacturing runs of the same type of paper. The five elements found to be most powerful in classifying papers were Cu, Mn, Sb, Cr, and Co. For Pb, high correlation with Mn, Cr, and Co was found. Mg, Fe, and Cd exhibited high intra-sheet scatter. The sixth feature used was density. These results indicate that papers can be characterized using trace metal data.
T h e identity and source of paper is quite important t o the forensic scientist in judicial problems encountered in forgery, counterfeiting, and felonious use of certificates, securities, wills, etc. I t is, therefore, important to be able to state conclusively whether an unknown paper sample does or does not come from a particular batch. T h e primary source of trace metals in paper is contamination of t h e chemicals used as additives such as alumina, TiOa,talc, clay, ZnO, and others ( I , 2). Trace metals may also originate in t h e wood pulp, process water, or process equipment. Characterization of papers has utilized colorimetric methods for certain metals ( 3 ) , often in conjunction with paper or thin-layer chromatographic separation procedures. These techniques are time consuming and semiquantitative a t best. T h e potential for characterizing paper by neutron activation analysis has been shown by two independent laboratories (2, 4 ) . In one study (2) where 600 paper samples were investigated for 23 elements, it was found t h a t certain elements such as Na, Mn, Ag, and Cu have a high frequency of occurrence whereas Ta, As, and Sb have a qualitative significance because of their low frequency of occurrence. These results indicated t h a t papers were uniform in regards t o their trace element concentration and papers from different manufacturers could be distinguished by qualitative and quantitative tests. Barnard e t al. (5,6)used the scanning electron microscope (SEMI for elemental analysis. The SEM x-ray microanalysis technique examined individual particles near the paper surface. Studies on the variation within a sheet and within a box were performed. Better results were obtained if the samples were ashed before examining them under the SEM. These results on 54 different samples for major elements seem t o indicate t h a t SEM data can be used for identification purposes. All elemental amounts determined are relative amounts and not absolute concentrations making these results difficult t o compare directly to other techniques which give actual concentrations. 'Present address, Food and Drug Administration District Laboratory, 585 Commercial Street, Boston, Mass.
Previous work by Langmyhr e t al. ( 7 ) using atomic absorption spectroscopy for the determination of Cu, P b , Cd, and M n suggested t h a t papers could be identified by trace metal content determined by atomic ;absorption spectrometry using a graphite furnace. These results suggest that further work in atomic absorption spectrornetry to determine the number of elements needed to identify papers is appropriate. Electrothermal atomization (nonflamel atomic absorption spectrometry requires minimal analysis time and therefore was used in this study. Using electrothermal atomization, wet digestion of t h e samples was unnecessary, the papers were ashed and analyzed directly. T h e 19 paper samples investigated represent 11 different types of paper and seven manufacturers and are all white bond or thesis paper including the same samples previously investigated using the S E M ( 5 , 6). Data analysis was performed using pattern recognition which has been shown to be quite successful in solving various chemical problems (8-11). In fact, Duewer and Kowalski (12) used pattern recognition to identify papers from t h e data collected by neutron activation analysis ( 4 ) where separation was achieved by paper grade and by paper manufacturer using the concentrations of 10 elements.
EXPERIMENTAL Standards and Reagents. All glassware was first cleaned in hot 1:l (v/v) nitric acid:water for a period of at least 4 h. For subsequent use, glassware and polyethklene bottles were allowed to sit overnight in approximately 10'70 (v/v, nitric acid. All standard solutions were made with distilled deionized water. Acids were Baker Analyzed, Reagent grade. Standard stock solutions of 1 mg/mL concentrations were made using the respective metals (Alfa products) except for cobalt where anhydrous CoC12 (Alfa products) was used. Cu, Pb, Mn, Ccl, Co, Ag, and Mg stock solutions were kept in approximately 1% "OB and Sb, Cr, and Fe in 190HC1. All solutions were stored in polyethylene bottles. Dilutions were made for each element the same day that they were used and were either 1% nitric acid or 1% hydrochloric acid. Instrumentation. A Cahn electrobalance model No. 4100 was used for weighing all of the paper dots. A Varian-Techtron Atomic Absorption Spectrophotometer Model AA-6 in conjunction with a carbon rod atomizer (CRA-63), a carbon cup, a background corrector, and a Varian Aerograph A-25 recorder was used exclusively in this work. The CRA control module controlled i,he time and temperature for the dry, ash, and atomize cycles. When analyzing any particular element, the voltages for the three cycles were kept constant but the times for the dry and ash cycle varied (Le., a longer dry cycle for solutions and a longer ash for the papers). The atomization time and temperature were kept constant for both samples and standards. A hydrogen continuum lamp was used for the background correction spectral source. For the wavelengths selected for manganese (403.2nm) and chromium (357.9 nm), the hydrogen continuum lamp output is quite weak and, consequently, was not used. However, it was found that scattering or nonspecific absorption was not a major factor for these elements. Sample Preparation. Up to four sheets of paper were taken consecutively from each of 19 reams of paper. From each sheet, using a small paper punch, 150 small dots about 3 mm in diameter were punched out and placed in a small plastic tray. Care was ANALYTICAL CHEMISTRY, VOL. 49, NO. 14, DECEMBER 1977
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Table I. AA Instrumental Parameters
Element Cu Pb Mn Sb Cr Co Cd Fe
Mg Ag
Wavelength, nm
Lamp current, mA
328.4 283.4 403.2 217.6 425.5 240.8 228.7 248.3 202.5 328.1
2.5 3.0 4.0 10.0 5.0 5.0 2.5 5.0 10.0 2.5
Spec- Phototral multiband plier pass, voltage, nm V 0.5 0.5 0.5 0.2 0.2 0.5 0.5 0.2 0.5
0.5
380 343 280 440 368 350 306 500 522 253
Table 11. Elemental Concentration Ranges Ash temperature (“C)/ time (s) 110013 55013 80013 800/3 110013 110013 55012 1100/2.5 110013 55013
taken to keep contamination of the papers to a minimum. The sheet being punched was held in the corners where no sample dots were taken for analysis. Also, the first ten dots from each sheet were discarded to eliminate any possibility of cross-contamination. To eliminate variations in moisture content for different types of paper, all paper dots were dried in a vacuum oven at 70 “C for at least 4 h. Samples were then placed in a desiccator. Each dot was weighed individually using a Cahn Balance. In order to eliminate moisture errors due to changes in humidity over the period of weighing, “standard’ dots were weighed before and after each sample. It was found that, at most, the weight difference for the “standard” dots during weighing a sample (over a period of about 2 h) was generally 0.1-0.3 pg and over a complete day no more than 2 Fg which is insignificant when compared to sample weights in the range of 0.3 t o 0.6 mg. Sample dots were stored in small plastic trays with appropriate identification (sample, sheet, and tray). A 50-rg range was used for each tray. The sample weight used for a particular tray was the average weight of all the dots in the tray. Because of the relatively high concentrations of iron and magnesium in papers, a digestive method was used. The same sheets that were used to obtain the other samples were torn into small squares (ca. 5 cm2)using a piece of nitric acid cleaned glass and Teflon-coated tweezers. These papers were dried in the same manner as the dots, weighed on a Mettler type H-15 single pan balance, placed in porcelain crucibles and then into a muffle furnace at 260 “ C overnight. Five mL of concentrated nitric acid were added, placed on a hot plate, and simmered on low to dryness. After cooling, 3 mL of concentrated nitric acid were added to the residues and the digests were brought to a volume of 25-mL with distilled, deionized water and stored in polyethylene bottles. Reagent blanks were also prepared following the same procedure. Analytical Procedure. After instrument warmup and signal optimization, standards and samples were added directly to the graphite cup. The standards were pipetted into the cup using a 5-pL Eppendorf pipet and the papers were placed inside the cup using tweezers and a glass tamping rod to ensure uniform sample ashing. The time between injections was held constant (90 s) throughout a run. Some of the instrument parameters used in this study are shown in Table I. The ash voltage and time were set high and long enough to eliminate any memory effects from the highest standard run. Five or more replicates were run for each element from each sheet of paper. The elemental concentration ranges are given in Table 11.
RESULTS AND DISCUSSION T h e data analysis was accomplished using ARTHUR, a program obtained from the Laboratory for Chemometrics a t t h e University of Washington and modified for use on Northeastern’s CDC Cyber 70. Unsupervised learning routines employing hierarchial clustering or Q mode clustering (HIER) and Zahn minimal spanning tree clustering (TREE) (13, 14) were used. For these clustering algorithms, each group of measurements made on a paper is represented as a point in n-dimensional space. T R E E connects all the points by 2286
ANALYTICAL CHEMISTRY, VOL. 49, NO. 14, DECEMBER 1977
Element cu Pb Mn Sb Cr co Cd Fe Mg
Range, clglg 1.7-9 0.2-17 0.3-20 0.1-14 5-22 0.01-0.36 0.001-0.020 4-158 0.5-520
drawing a “tree” of minimum length in n-dimensional space. Clusters are groups of points whose intrapoint “distance” is significantly smaller than the distance to a neighboring cluster Le., high density clusters of points (leaves) are (hopefully) widely separated on bare branches. HIER initially assumes each point (in this case each sheet of paper) is a separate cluster. An interpattern similarity matrix is then generated and the two points with the smallest similarity coefficient are identified. These two points (the most similar) are then represented as a single point (their center of gravity) and the similarity matrix is regenerated. The result is a dendogram where each point is connected to all others at some level of similarity (see Figure 1). The length of the interconnecting line is an indication of similarity. A length of 0.0 implies that the samples are identical, a length of 1.0 the least similar. A coefficient of
