- Email: [email protected]
A method for identification of interfering signals in EPR dating of tooth enamel
Radiation Measurements 32 (2000) 781±785
www.elsevier.com/locate/radmeas
A method for identi®cation of interfering signals in EPR dating of tooth enamel Robert B. Hayes a,*, Edwin H. Haskell b a
Westinghouse Government Services Group, P.O. Box 2078, MS 452-09, Carlsbad, NM 88221, USA Center for Applied Dosimetry, University of Utah Radiobiology Division, 729 Arapeen Dr., Salt Lake City, UT 84108, USA
b
Received 30 October 1999; received in revised form 6 March 2000; accepted 24 April 2000
Abstract In this paper, a method for identifying interfering EPR signals in fossil tooth enamel is presented. This method consists of optimizing EPR parameters to enhance spectral resolution of the fossil signals followed by a g-factor and intensity normalized subtraction of a high-dosed, modern tooth enamel sample spectrum. By scanning the modern tooth enamel sample with the same parameters as the fossil sample, the dierence spectrum of the fossil and modern irradiated tooth enamel samples can resolve numerous hyper®ne and other interfering signals. This method was successfully applied to a fossil sample studied elsewhere (GruÈn, R., 1998a. Ancient TL 16, 51±55; GruÈn, R., Clapp, R., 1996. Ancient TL 14, 1±5; Martin Jonas, 1997. Ph.D. Thesis, Cambridge University; Jonas, M., GruÈn, R., 1997. Radiat. Meas. 27, 49±58; Vanhaelewyn et al., 2000. Appl. Radiat. Isot. 52, 1317±1326). This sample has shown discrepancies in dose estimations obtained from the power absorption curve versus those obtained from the ®rst derivative spectra (GruÈn, R., 1998b. Radiat. Meas. 29, 177±193). The reason for this, and other discrepancies, are accounted for by the signals resolved using the method presented here. 7 2000 Elsevier Science Ltd. All rights reserved. Keywords: EPR; ESR; Tooth enamel; Dating; Dosimetry
1. Introduction Impurities in fossil tooth enamel can introduce EPR signals that interfere with dosimetric evaluation. If the assumption is made that the EPR signal of the fossil tooth used for dosimetric evaluation is dominated by an asymmetric CO2ÿ center as with modern human teeth (Callens et al., 1987), then interfering signals present in that sample can be resolved. This is achieved using high resolution spectral techniques to obtain the
* Corresponding author. Fax: +1-505-234-8298. E-mail address: [email protected] Hayes).
(R.B.
dierence spectrum from a modern dosed enamel sample and the original fossil sample. A method for analyzing the dierence spectrum can then be used to determine the CO2ÿ signal intensity.
2. Materials and methods 2.1. General The sample used was E1047 (GruÈn, 1998a, 1998b; GruÈn and Clapp, 1996; Jonas, 1997; Jonas and GruÈn, 1997; Vanhaelewyn et al., 2000). All error estimates are given at the one standard deviation level unless otherwise stated.
1350-4487/00/$ - see front matter 7 2000 Elsevier Science Ltd. All rights reserved. PII: S 1 3 5 0 - 4 4 8 7 ( 0 0 ) 0 0 1 0 8 - 6
782
R.B. Hayes, E.H. Haskell / Radiation Measurements 32 (2000) 781±785
2.2. Experimental con®guration EPR parameters used were 20.5 ms time constant, 20.5 s sweep time, 0.1 mT modulation, 2 mW microwave power, 2048 ®eld resolution and 12 mT sweep width. An in cavity Mn++ standard in the con®guration of Haskell et al. (1998) was used for g-factor normalization. A Bruker ER082C heat exchanger was used to maintain constant magnet and klystron temperatures. Irradiations were done using a Sheppard Mark I Model 20 Cs-137 irradiator with a dose rate of 30 Gy/ min to hydroxyapatite. Sample irradiations were done using a rotating aluminum cylindrical vessel with a wall thickness of 3 mm. Sample spectra were normalized on mass according to the method of Hayes et al. (2000) which corrects for the modulation amplitude and microwave power distribution variations in the cavity. Grain sizes used were E150 mm.
The irradiated E1047 aliquot was scanned both 1 h and 1 week post irradiation. Following this, the aliquot
2.3. Analysis method Spectra were obtained from undosed and dosed (600 Gy) aliquots of E1047. Spectra used for dierence analysis were taken from American wisdom teeth irradiated to doses of 100 Gy and 1 kGy.
Fig. 1. Method used in resolving impurity (or transient) signals in sample. The standard dosimetric signal (dashed line) is ®rst aligned to the sample spectrum (continuous line superimposed on the standard dosimetric signal) in g-factor using the Mn++ lines from the in-cavity standard as described by Haskell et al. (1998) (these are shown at the ®eld positions, 342.6 and 351.2 mT). The standard dosimetric signal spectrum is then intensity normalized to the sample spectrum such that the dierence spectrum (lower trace) appears to have no signi®cant oset in any of the resultant signal components.
Fig. 2. Spectra used in transient signal analysis. (A) The sample spectra taken after the 600 Gy dose was applied along with the standard dosimetric signal (bottom) used for these measurements. These spectra from top to bottom are: the sample spectrum taken 1 h after irradiation, the sample spectrum taken 1 week after irradiation, the sample spectrum after a 908C anneal for 2.5 h and the bottom spectrum is the 600 Gy standard dosimetric signal spectrum. (B) The resolved transient signal components. The upper spectrum shows the signal that decayed out of the total spectrum after a 1 week wait. The second spectrum from the top shows the spectrum that was removed from the ``1 week wait'' spectrum by a 1 h anneal. The second spectrum from the bottom shows the signals removed from the 1 h anneal spectrum by an additional 1.5 h, 908C anneal. The bottom spectrum shows the signals removed by an additional 2 day anneal. Note that the inverted septet indicates the generation of the septet through the ®nal extended anneal.
R.B. Hayes, E.H. Haskell / Radiation Measurements 32 (2000) 781±785
was annealed at 908C for periods of 1 h, 1.5 h, 2 days and 2 weeks, and scanned between intervals. The method used for resolving interfering signals is shown in Fig. 1. The g-factor normalization was done using the Mn++ lines shown near 342.6 and 351.2 mT (with apparent g-factors of 2.0315 and 1.9818, respectively). The intensity normalization was carried out such that the dierence signal appeared to have no osets in the resultant signal components and that the overall dierence appeared to have a zero baseline.
783
3. Results 3.1. Interfering signals The impurity signal found in the unirradiated E1047 aliquot is shown in the lower trace of Fig. 1. The eects of transient EPR signals in the sample are shown in Fig. 2. Fig. 2A shows the time sequenced spectra of the 600 Gy aliquot. The bottom trace in Fig. 2A is the standard dosimetric signal after g-factor and intensity normalization to the 2.5 h annealed sample spectrum (which is the second spectrum from the bottom). Fig. 2B shows the isolated transient signals. 3.2. Measurement reproducibility In practice, the result shown in Fig. 1 for intensity normalization was estimated from repeated trials to be 3%. Maximal deviation of the ®tted standard was also estimated to be about 7%. The reproducibility of this method for modeling the CO2ÿ dosimetric signal in modern tooth enamel (no impurity signals) subsequent to annealing after a 10 Gy dose has been rigorously determined to be 1.5% for larger grain and smaller mass samples (Hayes et al., 2000; Hayes, 1999). It can be expected, therefore, that the precision (reproducibility) of the method will be inversely proportional to the relative intensity of any interfering impurity signals. 3.3. Resolved transient and impurity signals in absorption curve spectra The relative eects of both the impurity and transient signals in the absorption curve sample spectra are shown in Fig. 3A and B, respectively. The transient signals, shown in Fig. 3B, depict the residual transient signal components still remaining after allowing the sample to be at ambient temperature for 1 week.
4. Discussion
Fig. 3. Absorption spectra of sample with resolved impurity and transient signals. (A) The absorption spectra of the unirradiated sample spectrum (from Fig. 1) superimposed onto the resolved impurity signal (from the lower trace of Fig. 1). (B) The 600 Gy irradiated sample absorption spectrum 1 week after irradiation. Superimposed on this ®gure is the resolved transient signal still present in the sample after the 1 week wait following irradiation (this was generated from the dierence spectrum of the bottom trace in Fig. 2A from the second trace from the top in Fig. 2A).
GruÈn (1998b) demonstrated the following points with E1047: 1. The dose estimate derived from the spectra as determined from speci®c spectral positions using dose versus magnetic ®eld (DMF) plots vary for both the absorption curve and its ®rst derivative. 2. The dose estimates found from DMF plots show little if any internal consistency. 3. Those regions that appear to exhibit plateau behavior in the absorption and ®rst derivative spectra
784
R.B. Hayes, E.H. Haskell / Radiation Measurements 32 (2000) 781±785
disagree with each other outside of experimental error. These eects can be explained qualitatively considering the presence of both the impurity and transient signals unresolved in the previous study (GruÈn, 1998b). As shown in Figs. 1±3, these signals can contribute more than 10% of the total intensity at various magnetic ®eld positions in the spectra. In the absorption
curves, they systematically increase the resultant spectral intensity of the curve throughout the region analyzed. In the absorption curve derivative spectra they contribute both positive and negative osets depending on the ®eld position in the spectra. According to the literature (Jonas and Marseglia, 1997; Lyons, 1997) and as seen by GruÈn (1998b), doses derived in DMF plots from the derivative spectra of samples such as these should show high variation with ®eld position comparable to the linewidth of both the impurity and transient signal components present. 4.1. Predicted eects on dose responses Considering now only the qualitative eects on DMF plots derived from the absorption curves, the impurity signals will primarily eect the low dose measurements as seen in Fig. 3A. At higher doses, eects from the transient signals will become dominant (Fig. 3B) The presence of these signals in the EPR spectrum will generate systematic changes in the dose response of a sample. Speci®cally, the impurity signal resolved in Fig. 3A will increase the y-intercept of the dose response creating a positive dose oset. However, the transient signals (Fig. 3B) will only serve to increase the initial slope of the dose response creating a negative dose oset. The interplay of these two eects is discussed next. 4.2. Correlation between predicted and previously measured DMF plots
Fig. 4. Theoretical eects of transient and impurity signals on dose reconstructions utilizing DMF plots. (A) From bottom to top are shown an intensity adjusted transient signal absorption curve (from Fig. 3A), an inverted, intensity adjusted and vertically shifted impurity signal absorption curve (from Fig. 3B) and the top spectrum is an ad-hod combination of the two lower spectra. (B) The DMF plot from GruÈn (1998b); Fig. 11c superimposed on a vertically altered version of the upper trace in (A). The region marked by an asterisk () denotes the location of the most unstable transient signal and is attributed to dierent decay times between this study and that of GruÈn (1998b).
An approximation of the magnetic ®eld dependence of these eects is shown in Fig. 4A. Here we show from bottom to top, the absorption curve of transient an inverted absorption curve from signals present 1 week after irradiation the impurity and an ad-hoc combination of the two lower spectra (note that the amplitudes in Fig. 4A have been modi®ed from their original values in Fig. 3). Note that the upper trace in Fig. 4A models the same characteristic features found in the absorption spectra DMF plots of GruÈn (1998b) shown in Fig. 4B (see GruÈn, 1998b; Fig. 11). The double arrows shown in Fig. 4 represent the maximum and second minimum positions of the stable dosimetric signal in tooth enamel. 4.3. Cause of the deviation at 345.2 mT The deviation marked by the asterisk in Fig. 4B correlates with the same g-factor of the transient signal marked by an asterisk in the upper trace of Fig. 2B. It is likely, therefore, that the deviation between DMF and modeled spectra in Fig. 4B is due to the dierences in temporal decay between our irradiated sample
R.B. Hayes, E.H. Haskell / Radiation Measurements 32 (2000) 781±785
and that of GruÈn (1998b). This is because the relative decay of this signal is greater than that of the other transient signals for the 1 week interval. 4.4. Recommended annealing procedure The presence of a residual transient signal component indicates that a simple 2.5 h, 908C anneal should be sucient to fully remove all the transient signal components in agreement with the results found for modern tooth enamel by Sholom et al. (1998).
5. Conclusion A methodology was presented enabling reliable impurity and transient signal detection and corrections. Impurity and transient signals appeared to be resolvable within the 5% level using this methodology. Actual precision of the method will be dependent on the relative contribution of all interfering signals. The apparent dose discrepancies found by GruÈn (1998b) in the accuracy of dose reconstruction of the fossil sample E1047 have been resolved. These apparent discrepancies have been shown to be attributable to both impurity signals in the sample and residual transient signals still present in the sample at the time of EPR scanning.
Acknowledgements We would like to thank both Prof. Rainer GruÈn and Prof. Gerry Kenner for their detailed and insightful reviews of this manuscript. We would also like to thank Prof. Rainer GruÈn for graciously providing us with the sample for this study and Prof. Ray Warters for allowing us the use of the Mark I irradiator.
785
References Callens, F., Verbeek, R., Matthys, P., Martens, L., Boesman, 2ÿ E., 1987. The contribution of CO3ÿ to the ESR 3 and CO spectrum near g 2 of powdered human tooth enamel. Calcif. Tissue Int. 41, 124±129. GruÈn, R., 1998a. Dose determination on fossil tooth enamel using ESR spectrum deconvolution with Gaussian and Lorentzian peak shapes. Ancient TL 16, 51±55. GruÈn, R., 1998b. Reproducibility measurements for ESR signal intensity and dose determination: high precision but doubtful accuracy. Radiat. Meas. 29, 177±193. GruÈn, R., Clapp, R., 1996. An automated sample changer for Bruker ESR spectrometers. Ancient TL 14, 1±5. Haskell, E.H., Hayes, R.B., Kenner, G.H., 1998. A high sensitivity EPR technique for alanine dosimetry. Radiat. Prot. Dosim. 77, 43±49. Hayes, R.B., 1999. Electron paramagnetic resonance dosimetry: methodology and material characterization. Ph.D. Thesis, University of Utah, Salt Lake City. Hayes, R.B., Haskell, E.H., Barrus, J.K., Kenner, G.H. Romanyukha, A.A., 2000. Accurate EPR radiosensitivity calibration using small sample masses. Nucl. Inst. Meth. Phys. Res. A., 441, 535±550. Jonas, M., 1997. Electron spin resonance dating and dosimetry of tooth enamel. Ph.D. Thesis, Cambridge University, Cambridge. Jonas, M., GruÈn, R., 1997. Q-band ESR studies of fossil tooth enamel: implications for spectrum deconvolution and dating. Radiat. Meas. 27, 49±58. Jonas, M., Marseglia, 1997. The case for the use of integrated spectrum deconvolution in ESR dating Ð a numerically generated example. Radiat. Meas. 27, 359±364. Lyons, R.G., 1997. The dierence in integrating. Radiat. Meas. 27, 345±350. Sholom, S.V., Haskell, E.H., Hayes, R.B., Kenner, G.H., Chumak, V.V., 1998. In¯uence of crushing and additive irradiation procedures on EPR of tooth enamel. Radiat. Meas. 29, 105±111. Vanhaelewyn, G., Callens, F., GruÈn, R., 2000. EPR spectrum deconvolution and dose assessment of fossil tooth enamel using maximum likelihood common factor analysis. Appl. Radiat. Isot. 52, 1317±1326.
www.elsevier.com/locate/radmeas
A method for identi®cation of interfering signals in EPR dating of tooth enamel Robert B. Hayes a,*, Edwin H. Haskell b a
Westinghouse Government Services Group, P.O. Box 2078, MS 452-09, Carlsbad, NM 88221, USA Center for Applied Dosimetry, University of Utah Radiobiology Division, 729 Arapeen Dr., Salt Lake City, UT 84108, USA
b
Received 30 October 1999; received in revised form 6 March 2000; accepted 24 April 2000
Abstract In this paper, a method for identifying interfering EPR signals in fossil tooth enamel is presented. This method consists of optimizing EPR parameters to enhance spectral resolution of the fossil signals followed by a g-factor and intensity normalized subtraction of a high-dosed, modern tooth enamel sample spectrum. By scanning the modern tooth enamel sample with the same parameters as the fossil sample, the dierence spectrum of the fossil and modern irradiated tooth enamel samples can resolve numerous hyper®ne and other interfering signals. This method was successfully applied to a fossil sample studied elsewhere (GruÈn, R., 1998a. Ancient TL 16, 51±55; GruÈn, R., Clapp, R., 1996. Ancient TL 14, 1±5; Martin Jonas, 1997. Ph.D. Thesis, Cambridge University; Jonas, M., GruÈn, R., 1997. Radiat. Meas. 27, 49±58; Vanhaelewyn et al., 2000. Appl. Radiat. Isot. 52, 1317±1326). This sample has shown discrepancies in dose estimations obtained from the power absorption curve versus those obtained from the ®rst derivative spectra (GruÈn, R., 1998b. Radiat. Meas. 29, 177±193). The reason for this, and other discrepancies, are accounted for by the signals resolved using the method presented here. 7 2000 Elsevier Science Ltd. All rights reserved. Keywords: EPR; ESR; Tooth enamel; Dating; Dosimetry
1. Introduction Impurities in fossil tooth enamel can introduce EPR signals that interfere with dosimetric evaluation. If the assumption is made that the EPR signal of the fossil tooth used for dosimetric evaluation is dominated by an asymmetric CO2ÿ center as with modern human teeth (Callens et al., 1987), then interfering signals present in that sample can be resolved. This is achieved using high resolution spectral techniques to obtain the
* Corresponding author. Fax: +1-505-234-8298. E-mail address: [email protected] Hayes).
(R.B.
dierence spectrum from a modern dosed enamel sample and the original fossil sample. A method for analyzing the dierence spectrum can then be used to determine the CO2ÿ signal intensity.
2. Materials and methods 2.1. General The sample used was E1047 (GruÈn, 1998a, 1998b; GruÈn and Clapp, 1996; Jonas, 1997; Jonas and GruÈn, 1997; Vanhaelewyn et al., 2000). All error estimates are given at the one standard deviation level unless otherwise stated.
1350-4487/00/$ - see front matter 7 2000 Elsevier Science Ltd. All rights reserved. PII: S 1 3 5 0 - 4 4 8 7 ( 0 0 ) 0 0 1 0 8 - 6
782
R.B. Hayes, E.H. Haskell / Radiation Measurements 32 (2000) 781±785
2.2. Experimental con®guration EPR parameters used were 20.5 ms time constant, 20.5 s sweep time, 0.1 mT modulation, 2 mW microwave power, 2048 ®eld resolution and 12 mT sweep width. An in cavity Mn++ standard in the con®guration of Haskell et al. (1998) was used for g-factor normalization. A Bruker ER082C heat exchanger was used to maintain constant magnet and klystron temperatures. Irradiations were done using a Sheppard Mark I Model 20 Cs-137 irradiator with a dose rate of 30 Gy/ min to hydroxyapatite. Sample irradiations were done using a rotating aluminum cylindrical vessel with a wall thickness of 3 mm. Sample spectra were normalized on mass according to the method of Hayes et al. (2000) which corrects for the modulation amplitude and microwave power distribution variations in the cavity. Grain sizes used were E150 mm.
The irradiated E1047 aliquot was scanned both 1 h and 1 week post irradiation. Following this, the aliquot
2.3. Analysis method Spectra were obtained from undosed and dosed (600 Gy) aliquots of E1047. Spectra used for dierence analysis were taken from American wisdom teeth irradiated to doses of 100 Gy and 1 kGy.
Fig. 1. Method used in resolving impurity (or transient) signals in sample. The standard dosimetric signal (dashed line) is ®rst aligned to the sample spectrum (continuous line superimposed on the standard dosimetric signal) in g-factor using the Mn++ lines from the in-cavity standard as described by Haskell et al. (1998) (these are shown at the ®eld positions, 342.6 and 351.2 mT). The standard dosimetric signal spectrum is then intensity normalized to the sample spectrum such that the dierence spectrum (lower trace) appears to have no signi®cant oset in any of the resultant signal components.
Fig. 2. Spectra used in transient signal analysis. (A) The sample spectra taken after the 600 Gy dose was applied along with the standard dosimetric signal (bottom) used for these measurements. These spectra from top to bottom are: the sample spectrum taken 1 h after irradiation, the sample spectrum taken 1 week after irradiation, the sample spectrum after a 908C anneal for 2.5 h and the bottom spectrum is the 600 Gy standard dosimetric signal spectrum. (B) The resolved transient signal components. The upper spectrum shows the signal that decayed out of the total spectrum after a 1 week wait. The second spectrum from the top shows the spectrum that was removed from the ``1 week wait'' spectrum by a 1 h anneal. The second spectrum from the bottom shows the signals removed from the 1 h anneal spectrum by an additional 1.5 h, 908C anneal. The bottom spectrum shows the signals removed by an additional 2 day anneal. Note that the inverted septet indicates the generation of the septet through the ®nal extended anneal.
R.B. Hayes, E.H. Haskell / Radiation Measurements 32 (2000) 781±785
was annealed at 908C for periods of 1 h, 1.5 h, 2 days and 2 weeks, and scanned between intervals. The method used for resolving interfering signals is shown in Fig. 1. The g-factor normalization was done using the Mn++ lines shown near 342.6 and 351.2 mT (with apparent g-factors of 2.0315 and 1.9818, respectively). The intensity normalization was carried out such that the dierence signal appeared to have no osets in the resultant signal components and that the overall dierence appeared to have a zero baseline.
783
3. Results 3.1. Interfering signals The impurity signal found in the unirradiated E1047 aliquot is shown in the lower trace of Fig. 1. The eects of transient EPR signals in the sample are shown in Fig. 2. Fig. 2A shows the time sequenced spectra of the 600 Gy aliquot. The bottom trace in Fig. 2A is the standard dosimetric signal after g-factor and intensity normalization to the 2.5 h annealed sample spectrum (which is the second spectrum from the bottom). Fig. 2B shows the isolated transient signals. 3.2. Measurement reproducibility In practice, the result shown in Fig. 1 for intensity normalization was estimated from repeated trials to be 3%. Maximal deviation of the ®tted standard was also estimated to be about 7%. The reproducibility of this method for modeling the CO2ÿ dosimetric signal in modern tooth enamel (no impurity signals) subsequent to annealing after a 10 Gy dose has been rigorously determined to be 1.5% for larger grain and smaller mass samples (Hayes et al., 2000; Hayes, 1999). It can be expected, therefore, that the precision (reproducibility) of the method will be inversely proportional to the relative intensity of any interfering impurity signals. 3.3. Resolved transient and impurity signals in absorption curve spectra The relative eects of both the impurity and transient signals in the absorption curve sample spectra are shown in Fig. 3A and B, respectively. The transient signals, shown in Fig. 3B, depict the residual transient signal components still remaining after allowing the sample to be at ambient temperature for 1 week.
4. Discussion
Fig. 3. Absorption spectra of sample with resolved impurity and transient signals. (A) The absorption spectra of the unirradiated sample spectrum (from Fig. 1) superimposed onto the resolved impurity signal (from the lower trace of Fig. 1). (B) The 600 Gy irradiated sample absorption spectrum 1 week after irradiation. Superimposed on this ®gure is the resolved transient signal still present in the sample after the 1 week wait following irradiation (this was generated from the dierence spectrum of the bottom trace in Fig. 2A from the second trace from the top in Fig. 2A).
GruÈn (1998b) demonstrated the following points with E1047: 1. The dose estimate derived from the spectra as determined from speci®c spectral positions using dose versus magnetic ®eld (DMF) plots vary for both the absorption curve and its ®rst derivative. 2. The dose estimates found from DMF plots show little if any internal consistency. 3. Those regions that appear to exhibit plateau behavior in the absorption and ®rst derivative spectra
784
R.B. Hayes, E.H. Haskell / Radiation Measurements 32 (2000) 781±785
disagree with each other outside of experimental error. These eects can be explained qualitatively considering the presence of both the impurity and transient signals unresolved in the previous study (GruÈn, 1998b). As shown in Figs. 1±3, these signals can contribute more than 10% of the total intensity at various magnetic ®eld positions in the spectra. In the absorption
curves, they systematically increase the resultant spectral intensity of the curve throughout the region analyzed. In the absorption curve derivative spectra they contribute both positive and negative osets depending on the ®eld position in the spectra. According to the literature (Jonas and Marseglia, 1997; Lyons, 1997) and as seen by GruÈn (1998b), doses derived in DMF plots from the derivative spectra of samples such as these should show high variation with ®eld position comparable to the linewidth of both the impurity and transient signal components present. 4.1. Predicted eects on dose responses Considering now only the qualitative eects on DMF plots derived from the absorption curves, the impurity signals will primarily eect the low dose measurements as seen in Fig. 3A. At higher doses, eects from the transient signals will become dominant (Fig. 3B) The presence of these signals in the EPR spectrum will generate systematic changes in the dose response of a sample. Speci®cally, the impurity signal resolved in Fig. 3A will increase the y-intercept of the dose response creating a positive dose oset. However, the transient signals (Fig. 3B) will only serve to increase the initial slope of the dose response creating a negative dose oset. The interplay of these two eects is discussed next. 4.2. Correlation between predicted and previously measured DMF plots
Fig. 4. Theoretical eects of transient and impurity signals on dose reconstructions utilizing DMF plots. (A) From bottom to top are shown an intensity adjusted transient signal absorption curve (from Fig. 3A), an inverted, intensity adjusted and vertically shifted impurity signal absorption curve (from Fig. 3B) and the top spectrum is an ad-hod combination of the two lower spectra. (B) The DMF plot from GruÈn (1998b); Fig. 11c superimposed on a vertically altered version of the upper trace in (A). The region marked by an asterisk () denotes the location of the most unstable transient signal and is attributed to dierent decay times between this study and that of GruÈn (1998b).
An approximation of the magnetic ®eld dependence of these eects is shown in Fig. 4A. Here we show from bottom to top, the absorption curve of transient an inverted absorption curve from signals present 1 week after irradiation the impurity and an ad-hoc combination of the two lower spectra (note that the amplitudes in Fig. 4A have been modi®ed from their original values in Fig. 3). Note that the upper trace in Fig. 4A models the same characteristic features found in the absorption spectra DMF plots of GruÈn (1998b) shown in Fig. 4B (see GruÈn, 1998b; Fig. 11). The double arrows shown in Fig. 4 represent the maximum and second minimum positions of the stable dosimetric signal in tooth enamel. 4.3. Cause of the deviation at 345.2 mT The deviation marked by the asterisk in Fig. 4B correlates with the same g-factor of the transient signal marked by an asterisk in the upper trace of Fig. 2B. It is likely, therefore, that the deviation between DMF and modeled spectra in Fig. 4B is due to the dierences in temporal decay between our irradiated sample
R.B. Hayes, E.H. Haskell / Radiation Measurements 32 (2000) 781±785
and that of GruÈn (1998b). This is because the relative decay of this signal is greater than that of the other transient signals for the 1 week interval. 4.4. Recommended annealing procedure The presence of a residual transient signal component indicates that a simple 2.5 h, 908C anneal should be sucient to fully remove all the transient signal components in agreement with the results found for modern tooth enamel by Sholom et al. (1998).
5. Conclusion A methodology was presented enabling reliable impurity and transient signal detection and corrections. Impurity and transient signals appeared to be resolvable within the 5% level using this methodology. Actual precision of the method will be dependent on the relative contribution of all interfering signals. The apparent dose discrepancies found by GruÈn (1998b) in the accuracy of dose reconstruction of the fossil sample E1047 have been resolved. These apparent discrepancies have been shown to be attributable to both impurity signals in the sample and residual transient signals still present in the sample at the time of EPR scanning.
Acknowledgements We would like to thank both Prof. Rainer GruÈn and Prof. Gerry Kenner for their detailed and insightful reviews of this manuscript. We would also like to thank Prof. Rainer GruÈn for graciously providing us with the sample for this study and Prof. Ray Warters for allowing us the use of the Mark I irradiator.
785
References Callens, F., Verbeek, R., Matthys, P., Martens, L., Boesman, 2ÿ E., 1987. The contribution of CO3ÿ to the ESR 3 and CO spectrum near g 2 of powdered human tooth enamel. Calcif. Tissue Int. 41, 124±129. GruÈn, R., 1998a. Dose determination on fossil tooth enamel using ESR spectrum deconvolution with Gaussian and Lorentzian peak shapes. Ancient TL 16, 51±55. GruÈn, R., 1998b. Reproducibility measurements for ESR signal intensity and dose determination: high precision but doubtful accuracy. Radiat. Meas. 29, 177±193. GruÈn, R., Clapp, R., 1996. An automated sample changer for Bruker ESR spectrometers. Ancient TL 14, 1±5. Haskell, E.H., Hayes, R.B., Kenner, G.H., 1998. A high sensitivity EPR technique for alanine dosimetry. Radiat. Prot. Dosim. 77, 43±49. Hayes, R.B., 1999. Electron paramagnetic resonance dosimetry: methodology and material characterization. Ph.D. Thesis, University of Utah, Salt Lake City. Hayes, R.B., Haskell, E.H., Barrus, J.K., Kenner, G.H. Romanyukha, A.A., 2000. Accurate EPR radiosensitivity calibration using small sample masses. Nucl. Inst. Meth. Phys. Res. A., 441, 535±550. Jonas, M., 1997. Electron spin resonance dating and dosimetry of tooth enamel. Ph.D. Thesis, Cambridge University, Cambridge. Jonas, M., GruÈn, R., 1997. Q-band ESR studies of fossil tooth enamel: implications for spectrum deconvolution and dating. Radiat. Meas. 27, 49±58. Jonas, M., Marseglia, 1997. The case for the use of integrated spectrum deconvolution in ESR dating Ð a numerically generated example. Radiat. Meas. 27, 359±364. Lyons, R.G., 1997. The dierence in integrating. Radiat. Meas. 27, 345±350. Sholom, S.V., Haskell, E.H., Hayes, R.B., Kenner, G.H., Chumak, V.V., 1998. In¯uence of crushing and additive irradiation procedures on EPR of tooth enamel. Radiat. Meas. 29, 105±111. Vanhaelewyn, G., Callens, F., GruÈn, R., 2000. EPR spectrum deconvolution and dose assessment of fossil tooth enamel using maximum likelihood common factor analysis. Appl. Radiat. Isot. 52, 1317±1326.