Analytical and Bioanalytical Chemistry

, Volume 385, Issue 2, pp 272–280

Influence of laser wavelength on LIBS diagnostics applied to the analysis of ancient bronzes

  • L. Fornarini
  • V. Spizzichino
  • F. Colao
  • R. Fantoni
  • V. Lazic
Special Issue Paper

DOI: 10.1007/s00216-006-0300-1

Cite this article as:
Fornarini, L., Spizzichino, V., Colao, F. et al. Anal Bioanal Chem (2006) 385: 272. doi:10.1007/s00216-006-0300-1

Abstract

In this work the influence of laser wavelength upon the analytical results obtained from applying LIBS diagnostics to bronzes was investigated theoretically and experimentally at 1,064 nm and 355 nm. The laser ablation process was modeled for a set of reference samples of quaternary Cu/Sn/Pb/Zn alloys and the difference between plume composition and known target stoichiometry was estimated for both of the wavelengths considered. LIBS measurements were performed on the same set of reference samples and under the same experimental conditions to validate the model at different wavelengths. Results from the application of the model to calculate sample optical properties during laser irradiation, absorption in the plasma and plasma temperature are also presented.

Keywords

LIBS Laser ablation Copper alloys Bronze Modeling 

Introduction

Laser induced breakdown spectroscopy (LIBS) is a well-known, useful tool for performing direct chemical analysis of solid samples. The technique is minimally invasive, which means that it can be applied to the analysis of delicate specimens such as artifacts and artistic objects. Bronze was one of the first alloys developed by ancient metal workers. Their ability to resist corrosion ensured that copper, bronze and brass have remained functional as well as decorative materials used over many millenia to the present day.

Quantitative LIBS analysis of ancient copper-based alloys suffers from problems related to fractionation, which causes marked differences in composition between the ablated plasma and the sample surface. The process of surface evaporation from bronzes is quite complex, mostly due to large differences in the physical properties of the metal constituents (Cu, Sn, Zn, Pb), and this means that the stoichiometry of the plasma analyzed can vary significantly from that of the original surface. When analyzing ancient bronzes, there is also the additional problem of the need to accurately determine the lead content, which is strongly related to the age and intended use of the artwork [1].

The influence of laser wavelength on fractionation during the process of laser ablation has already been addressed by the analytical community [2, 3, 4, 5, 6, 7, 8]. Ablation mechanisms are known to be influenced by the photon energy of the laser. In general, greater ablation efficiency (amount of mass removed per unit energy), reduced plasma shielding and confinement of sample heating are achieved by using short laser wavelengths (UV) and short laser pulse durations [9, 10, 11, 12]. Fractionation is also known to be a function of the properties of the laser beam (irradiance, pulse duration, wavelength) and the optical properties of the sample; several investigators have reported reduced fractionation when using UV lasers instead of infrared (IR) lasers [4, 13].

Understanding and limiting fractionation mechanisms is of great interest for LIBS quantitative analysis in order to obtain the desired testing accuracy and due to the need to determine the appropriate settings for which the ablated mass vapor is chemically equal to the original sample.

Previously published works on the LIBS analysis of brass alloys have shown that the plume composition matches that of the target more closely if lasers with shorter wavelength are employed and high fluences are used [7, 9, 14]. To our knowledge no data exist on bronze samples. A deeper understanding of the processes involved can also be gained by combining experimental results with models derived from computer simulation.

In this work, the influence of laser wavelength (wavelengths of 355 nm and 1,064 nm were used) upon analytical results of LIBS diagnostics has been investigated both theoretically and experimentally on quaternary bronzes to determine whether improvements are also possible for these alloys. The laser ablation process was modeled for a set of reference samples of quaternary Cu/Sn/Pb/Zn alloys and the difference in plume composition with respect to the known target stoichiometry was estimated for both of the wavelengths considered. The model was based on a one-dimensional heat-flow calculation and was applied to nanosecond laser pulses. The influence of the target properties on the temperature and plume stoichiometry was derived from thermal vaporization processes [15].

LIBS measurements were performed on the set of reference samples considered for modeling and under the same experimental conditions, so that they could be compared to the model findings and to check whether it is possible to improve the capabilities of LIBS for quantitative analysis.

Experimental

The reference bronze samples analyzed here were from different sources, and their compositions are listed in Table 1. Their elemental concentration ranges correspond to those characteristic of ancient archeological findings. Note that one of the samples does not contain zinc (the sample labeled as CSM).
Table 1

Standard bronze samples used in this work. Concentrations are given in %wt

Standard

Cu

Zn

Sn

Pb

B30

77.55

0.99

9.80

10.0

B4

83.7

1.38

11.10

2.54

LPb

88.14

0.47

9.78

0.79

HPb

82.47

5.86

5.29

5.55

CSM

90.12

0

7.9

1.8

Laser ablation of samples was achieved using a Q-switched Nd:YAG laser (model Handy, Quanta System, Solbiate Olona, Italy). Initial experiments were performed with the laser emitting at 1,064 nm, emission at 355 nm was then employed in later tests. In both cases the laser pulse duration was about 8 ns and the repetition rate was 1 Hz. All of the experiments were carried out in air without any control of the surrounding atmosphere. Plasma emission was collected at an angle of about 30° with respect to the laser beam axis. The signal was carried by an optical fiber bundle with a diameter of 0.1 mm. The latter was mounted onto the entrance slit of a Mechelle 5000 spectrograph (Andor, South Windsor, CT, USA). The spectra were recorded using a gated ICCD (iStar DH734, Andor), whose gate aperture was synchronized with the laser burst with an optical trigger. Some preliminary tests were performed to study the temporal behavior of the plasma emission generated. A window suitable for signal maximization was chosen in the temporal range where conditions close to LTE were considered to exist [16]. A delay from the laser pulse of 1,500 ns and an acquisition gate width of 2,000 ns were chosen for laser excitation at 1,064 nm. Data acquisition was performed by accumulating signal over 20 laser pulses at fixed position. Similarly, for a laser operating at 355 nm, the delay from the laser pulse was set to 1,000 ns and the gate width to 1,500 ns. Under these conditions, parameters characterizing the plasma were calculated for both laser wavelengths.

Measurements were carried out at various energy densities over the range 50–250 J/cm2 in order to study the effect of the fluence value on the stoichiometry during the vaporization of metallic targets.

Laser pulse energy was measured behind the focusing lens by means of a Gentec (Markham, Canada) ED-500 energy meter. In order to determine the laser fluence on the sample, the diameters of the laser-produced craters were measured using an optical microscope. Values of 330–400 μm were obtained on average for each series of six measurements.

Energy values for experiments performed at the fundamental laser wavelength and at its third harmonic were selected in order to obtain comparable fluences. The atomic lines used to detect the elements under study here are listed in Table 2, together with their corresponding excitation energies.
Table 2

Atomic lines chosen for detection of the elements under study with their corresponding excitation energies

Element

Wavelength (nm)

Ek (eV)

Cu

510.55

3.817

Pb

405.78

4.375

Sn

286.33

4.329

Zn

472.21

6.655

Peak line emissions, after background subtraction, were determined as average values from a series of six measurements, and the error bars used in the calibration plots were calculated to the 95% confidence interval. The background intensity used for line intensity correction was measured as the average of a wavelength range that was at least 1 nm wide. A range that was free from discrete emission lines and as close as possible to the atomic peak selected for the analysis was chosen when deriving the background relevant to each element.

Theoretical model and results

The interactions between the incoming radiation and the solid sample depend upon numerous variables related to the laser, the sample and the surrounding atmosphere. These variables include wavelength, energy, spatial and temporal profile of the laser beam, and the thermal properties of the sample. The incident beam is partially reflected by the sample surface and partially absorbed by the bulk to a degree that depends on the nature of the target and the temperature it reaches under laser irradiation. The rate of the radiation–solid interaction is also known to depend on the laser wavelength [17]. A theoretical model [18] has been used to evaluate the difference between the responses of bronze targets to either 355 nm or 1,064 nm radiation.

The model is based on a one-dimensional heat flow calculation, where reflection and absorption at the target surface, heat conduction towards the bulk and evaporation from the surface are considered according to the equation:
$$\rho c_{{\text{p}}} {\left( T \right)}\frac{{\partial T}}{{\partial t}} = \frac{\partial }{{\partial x}}{\left( {K{\left( T \right)}\frac{{\partial T}}{{\partial x}}} \right)} + S{\left( {x,t} \right)},$$
(1)
where K (T) is the thermal conductivity, T is the temperature, ρ is the density, and cp(T) is the specific heat capacity. \(S{\left( {x,t} \right)} = {\left( {1 - T{\left( T \right)}} \right)}P{\left( t \right)}e^{{ - \alpha {\left( T \right)}x}} \) is the heat generation function at position x and time t, which depends on the optical absorption coefficient α, the surface reflectivity R and the time evolution of the laser beam power P (t).
The influence of temperature on the optical properties of the target was evaluated via the relation between electrical conductivity and temperature, based on the Drude model for metals [19], where the complex dielectric constant is written as:
$$\varepsilon = 1 - \frac{{\omega ^{2}_{{\text{p}}} }}{{\omega ^{2} + \gamma ^{2} }} + i\frac{{\gamma \omega ^{2}_{{\text{p}}} }}{{\omega {\left( {\omega ^{2} + \gamma ^{2} } \right)}}},$$
(2)
where \(\omega _{{\text{p}}} = {\left( {\frac{{4\pi N_{{\text{e}}} e^{2} }}{{m^{ * } }}} \right)}^{{1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-\nulldelimiterspace} 2}} \) is the plasma frequency, \(\gamma = \frac{{\omega ^{2}_{{\text{p}}} }}{{4\pi \sigma }}\) is the damping rate, \(\omega = \frac{{2\pi c}}{\lambda }\) is the frequency of the light at the wavelength λ, m* is the effective mass of the carrier, Ne is the carrier density, σ is the electrical conductivity, e is the charge on the electron, and c is the velocity of light.
Calculated variations in each optical property with time under laser irradiation are shown in Fig. 1 for the two wavelengths considered. During the laser pulse the temperature of the surface increases to a maximum value, which is reached at the end of it. As the temperature increases, both the reflectance and the absorption decrease until the surface of the material becomes more and more transparent to the laser radiation, which penetrates deeper into the sample. Because the liquid underneath can also reach this condition upon subsequent heating, the heating front propagates into the interior liquid until the laser heating ceases.
Fig. 1a, b

Time evolutions of the optical properties of bronze during laser ablation (sample HPb, laser fluence 100 J/cm2): a absorption coefficient; b reflectance. The time evolution of the laser pulse is also shown

In all of the samples analyzed, the reflectance of bronze is lower and the absorption coefficient is higher for laser irradiation at 355 nm, indicating that the surface temperature reaches its maximum value in a shorter time upon UV excitation. For a wavelength of 1,064 nm, the model predicts a longer penetration depth, together with a slower rise in surface temperature. The kinks observed in Fig. 1 are due to sharp variations in α and R that occur during phase transitions.
The influence of the properties of the target upon the temperature and plume stoichiometry is derived from thermal vaporization, as this is the main mechanism involved in nanosecond laser ablation under the experimental conditions considered here [11, 15, 20].The molar flux of evaporating atoms is calculated using the Hertz–Knudsen equation [21]:
$$ \mu = 0.82\frac{{P_{{sat}} }} {{{\left( {2\pi m_{w} R_{G} T_{{\iota \nu }} } \right)}^{{1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-\nulldelimiterspace} 2}} }}, $$
(3)
where Psat is the equilibrium vapor pressure, Tlv is the interfacial evaporation temperature corresponding to Psat, RG is the gas constant, mw is the atomic weight, and 0.82 is a coefficient accounting for the back-flow of the evaporated vapor towards the surface [22]. For a multicomponent alloy, the evaporative flux for each species can be derived from solution thermodynamics theory [23]. The vaporization characteristics of bronze were calculated based on data for reference bronze samples [24]. The vapor formed is assumed to propagate away from the target at the same temperature as the liquid surface, and it plays no role in the conduction process.
Two major mechanisms have been assumed to contribute to the laser absorption inside the plasma [for details see 18]: inverse bremsstrahlung (IB) and photoionization (PI). The cross-sections (in cm2) of each are given by the two equations below:
$$ \sigma _{{{\text{ib}}}} = \frac{{3.7 \times 10^{{18}} }} {{T^{{1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-\nulldelimiterspace} 2}}_{{\text{e}}} v^{3} }}Z^{2} {\left[ {\exp {\left( {\frac{{hv}} {{k_{{\text{B}}} T_{{\text{e}}} }}} \right)} - 1} \right]}n_{{\text{e}}} n_{{\text{i}}} + \frac{{e^{2} }} {{\pi m_{{\text{e}}} cv^{2} }}n_{{\text{o}}} n_{{\text{e}}} \sigma _{{{\text{coll}}}} {\left( {\frac{{8k_{{\text{B}}} T_{{\text{e}}} }} {{\pi m_{{\text{e}}} }}} \right)}. $$
(4)
$$\sigma _{{{\text{pi}}}} \cong {\left( {7.9 \times 10^{{ - 18}} } \right)}{\left( {\frac{{E_{{{\text{in}}}} }}{{hv}}} \right)}^{3} {\left( {\frac{{I_{{\text{H}}} }}{{E_{{{\text{in}}}} }}} \right)}^{{1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-\nulldelimiterspace} 2}} ,$$
(5)
In the above equations, ν is the laser irradiation frequency, Te is the electron temperature, ne, ni and no are the number densities of electrons, ions and neutral atoms, respectively, me is the mass of the electron, Z is the ionic charge, h is Planck’s constant, and σcoll is the cross-section for electron–neutral collision, while Ein is the excited state ionization energy, is the incident laser photon energy, and IH the hydrogen atom ionization energy expressed in the same units as [25].
We can therefore calculate the laser irradiance absorbed by the plasma:
$$I_{{{\text{ass}}}} = I{\left( t \right)} \times {\left( {1 - e^{{ - \delta }} } \right)} \times {\left( {1 + R \times e^{{ - \delta }} } \right)}$$
(6)
where δ is the plasma optical density, given by: \(\delta = {\left( {\sigma _{{{\text{\rm {IB}}}} \rm n_{e}} + \sigma _{{{\text{PI}}}} n_{{\text{o}}} } \right)}H.\) Where H is the height of the vapor cloud.
The laser wavelength also influences the quantity of energy absorbed in the plasma and the attenuation of the beam upon reaching the target surface. The estimated percentages of light transmitted through the plasma for the two cases considered here are shown in Fig. 2.
Fig. 2

Light transmitted through the plasma. Sample HPb, laser fluence 100 J/cm2

The IB absorption process is less efficient in the UV than in the IR for both electron–neutral and electron–ion collisions [26]. Due to plasma absorption, less energy reaches the sample’s surface at longer wavelengths, while the energy absorbed in the plasma increases its temperature. The maximum plasma temperatures reached for the laser wavelengths considered here calculated at the maximum of the laser pulse are reported in Table 3.
Table 3

Maximum temperatures reached in the plasma, obtained from theoretical simulations, calculated for the maximum of the laser pulse (15 ns)

Wavelength (nm)

Tmax(K)

1064

38700 K

355

27600 K

Noting the theoretical results outlined above, we should expect the surface temperature to grow more rapidly for 355 nm radiation. This could affect the relative amounts of the elements in the plasma and minimize (at low fluence) the excess of zinc. As previously observed [18, 27], Zn also evaporates at low surface temperatures, in agreement with its low boiling point and heat of vaporizationcompared to the other elements. Therefore, we expect that the slower the heating process, the higher the zinc content in the plume. At high fluences, the percentage of evaporated Cu, Sn, and Pb increases as higher surface temperatures are reached, where they evaporate more rapidly [18].

The overall effect of the considered wavelengths on the target temperature at low laser fluence (where differences are enhanced) is shown in Fig. 3.
Fig. 3

Surface temperature profiles versus time for the two laser wavelengths used on the bronze sample HPb at a fluence of 20 J/cm2. The time evolution of the laser pulse is also reported. Assumed error on T<1%

Experimental results

Spectra

LIBS spectra obtained by laser irradiation at the different wavelengths are compared in Fig. 4. Three different spectral regions have been selected to show differences in signal intensity and background emission in detail. The first remark that we should make is that the background continuum emission after the same optimization was performed on the data acquisition window is much stronger in the visible–near IR for spectra produced by the 1,064 nm laser. This is due to the higher absorption in the plasma caused by the inverse bremsstrahlung, whose cross-section is proportional to λ3, where λ is the laser excitation wavelength. In Table 4, the average background values for three spectral ranges (275–286 nm, 500–600 nm, 760–860 nm) are reported. Each average was calculated for a spectral range that was free from emission lines and wider than 1 nm. The same intervals were selected for both wavelengths.
Fig. 4

Comparison between the spectra produced by the laser at 355 nm and those produced by the laser at 1,064 nm. From top: magnifications of the UV, visible and IR spectral regions, respectively

Table 4

The average background values for the three spectral ranges 275–286 nm, 500–600 nm, 760–860 nm

Selected spectral ranges

Laser excitation wavelength: 355 nm

Laser excitation wavelength: 1,064 nm

275–286 nm

2020±190

1290±300

500–600 nm

190±90

1530±930

760–860 nm

2400±320

9000±2300

The spectra obtained using the IR laser (at 1,064 nm) were acquired using longer acquisition delays (see Experimental section) than those obtained with UV ablation. However, the plasma temperature, as measured using a Boltzmann plot applied to relatively weak Cu transitions, was much higher for IR ablation (13,000±1,200 K) than for UV laser ablation (9,700±800 K). This difference is attributable to the more efficient plasma heating achieved by the IR laser. Plasma electron densities were determined from Stark broadening of the Ca+ ionic line at 393.37 nm, as this element was present as an impurity in some of the samples. The measured electron density for the sample B30 was (3.3±0.7)×1017 cm−3 and (1.0±0.2)×1017 cm−3 for IR and UV laser excitation respectively.

Differences in line intensities were also apparent in these spectra. The spectrum for 1,064 nm irradiation is more intense than the one for 355 nm irradiation in the near-UV region, where ionic lines are preferentially found, and in the near-IR, where emissions from light elements present in air are located. This reflects the higher temperature caused by the greater absorption of the laser light at this UV wavelength, which is rapidly converted into kinetic energy and ionization. On the other hand, the spectrum at 355 nm shows a higher intensity in the visible region. The temperature and electron density reached in this case are most favorable for populating the levels involved in transitions in the visible range.

However, in general, higher atomic copper emission intensity is observed in the three examined ranges for the UV excitation wavelength.

Plume composition versus laser fluence

We investigated the influence of the laser beam irradiance on plume composition from the same bronze samples for different wavelengths.

Once local thermal equilibrium (LTE) is assumed [16] in the selected time window, the temperature and electron density are derived from the spectra and quantitative analysis is performed by using the calibration-free method [28, 29]. The calibration-free procedure permits quantitative analyses to be performed on samples with unknown matrices, for which calibration curves are not available. The algorithm is based on the closure condition and on the assumption that the plasma composition is representative of the solid target. The closure condition can be expressed as
$$ {\sum {_{\alpha } C_{\alpha } = 1,} } $$
(7)
where all of the α species present in the plasma are summed. The CF method is not able to account for nonstoichiometric evaporation since the evaporation process itself is not included. Therefore, the result it gives should be corrected by a factor that takes into account any differences between the plasma and sample composition, independently determined by means of theoretical considerations.
The plasma concentrations of the elements obtained in this way are plotted versus laser energy density for the two wavelengths considered here in Fig. 5 for the HPb sample. Under infrared laser irradiation, the zinc content in the plasma showed a strong dependence on the laser fluence. Its concentration decreased with energy density, approaching the stochiometric value. Pb, Sn and Cu exhibited less clear-cut dependencies on the fluence. However the concentrations of Pb and Sn were always underestimated with respect to their real contents in the target. Under ultraviolet laser excitation, the evaluated elemental content was almost independent of the fluence. The values obtained were always closer to those of the target than the values obtained upon IR laser irradiation. This behavior is in agreement with the theoretical observations reported above: when the sample temperature increases slowly, the plasma becomes enriched in the most volatile element.
Fig. 5a, b

Calibration-free analysis: experimentally derived differences (expressed in %) between the elemental concentrations in the plasma and those in the target for the bronze sample HPb at different fluences for a λ=1,064 nm and b λ=355 nm

However, the plume composition of the bronze never reached stoichiometric values at either wavelength, even at high fluences, and it was always too rich in zinc. The fact that the plume is rich in the most volatile element also indicates the thermal process governs the laser ablation in all of the cases examined here [7, 33].

Similar results were obtained from the model calculations, as shown in Fig. 6 for the different laser excitations. Theoretical data also show a drop in the relative Pb and Sn contents in the plume with fluence, while the Cu concentration remains almost constant.
Fig. 6a, b

Simulated differences (expressed in %) between the elemental concentrations in plasma and those in the target for the bronze sample HPb at different fluences for a λ=1,064 nm and b λ=355 nm

From the literature, the Zn/Cu ratio in plasma produced by ablation of brass materials with 30 ns laser pulses at 248 nm reaches the stoichiometric value for irradiances higher than 0.3 GW/cm2 [7, 14]. For bronze samples, the stoichiometric values for the elements in the plasma are never reached, since the four elements have different thermal properties and so they behave differently with fluence and never attain reciprocal compensation. A nonstoichiometric amount of just one element in the plasma is able to modify the proportions of the other three. A more complex behavior therefore exists due to the higher number of elements involved in the ablation process.

Calibration graphs

Calibration plots reporting peak line intensities as a function of the elemental concentration were analyzed for the two cases examined. Different ablation rates might be expected for different samples, due to variations in composition and surface reflectivity, so data need to be properly normalized prior to making any comparisons [30]. In many cases, line peak normalization for the continuum emission compensates well for the variability in the ablation rate [31, 32], so internal standardization with respect to the background level was carried out first. In Fig. 7, data normalized for the background emission are shown for laser irradiation at 355 nm. However, the calibration plots reporting peak line intensities as a function of the elemental concentration for a laser fluence of 250 J/cm2 do not show regular behavior for any of the elements aside from zinc. This occurs also upon laser irradiation at 1064 nm as previously reported [18].
Fig. 7

Analytical peak intensity normalized on background emission as a function of the certified element concentration in samples for λ=355 nm

As already seen for 1,064 nm laser irradiation [18], experimental data normalization using the atomic emission intensity of copper upon UV irradiation did not improve the result.

Internal standardization based on ratios of other elements to Zn has already been shown [18] to lead to the best calibration for bronze samples for 1,064 nm laser irradiation. The behavior of the Zn concentration in the plume, unlike those of Cu, Sn and Pb, suggests that the presence and quantity of zinc in bronze samples may account for the anomalies in the calibration plots. Standardization on zinc was therefore applied to our experimental data taken at the two different laser wavelengths.

Reciprocal ratios were plotted so that the sample without zinc could also be included in the graphs. The ratios of the Zn analytical peak intensity to the emission peaks from the three other elements as a function of their certified concentration ratios for λ=355 nm are shown in Fig. 8. Good linear trends were obtained using this approach, demonstrating that the ablation process at both 355 nm and 1,064 nm is governed by the content of zinc in the alloy. From these results, the zinc ratio seems to adequately account for the changes in the ablation components in the different samples for both of the wavelengths under study.
Fig. 8

Ratio of the analytical Zn peak intensity and the emission peak from the other three elements, as a function of the element concentration ratio in the sample at two laser fluences (left: 65 J/cm2, right: 250 J/cm2) and λ=355 nm

Conclusions

The influence of laser wavelength upon analytical results of LIBS diagnostics of bronzes has been investigated theoretically and experimentally in this work for the laser wavelengths of 1,064 nm and 355 nm, and these results have been compared. The laser wavelengths are those most commonly used in LIBS diagnostics, so the comparison of results between these two cases can help to improve the analytical capabilities of LIBS.

According to model calculations, more limited thermal effects are expected if a laser of a shorter wavelength is used, due to the shorter penetration depth of the light. This is of great significance to the analysis of archeological specimens. The results from the theoretical analysis indicate that the surface temperature grows more rapidly when 355 nm is used rather than 1,064 nm wavelength. This can affect the ratio of the elements in the plasma, which minimizes the excess of zinc in the plume even at low fluence.

The concentrations of the elements in the plasma obtained via calibration-free analysis of the experimental data, show that the zinc content in the plasma is strongly dependent on the laser irradiance for IR excitation. Its concentration decreases with the fluence, approaching the stoichiometric value, while Pb, Sn, and Cu do not exhibit strong dependencies on the fluence. However, lead and tin concentrations remain underestimated. For ultraviolet light, there is almost no dependence of the plasma element's concentration on fluence in the range investigated here. The concentration obtained with the 355nm wavelength is in any case closer to the one of the target with respect to the one obtained with IR light for all considered elements.

It should be pointed out, however, that the plume composition in bronzes for both wavelengths never reaches stoichiometry values even at high fluences, and always remains too rich in zinc content. This is in contrast to what is reported for brass [33], where stoichiometry is obtained in the plume for a UV laser and at high fluences. A more complex behavior exists in bronze samples due to the higher number of elements involved in the ablation process of the quaternary alloy considered.

The fact the plume is rich in the most volatile element, as theoretically predicted from thermal arguments, allows us to conclude that the thermal process is the dominant effect for the samples and the experimental conditions used here and analyzed by LIBS.

An internal standardization approach based on ratios of the other elements to Zn (previously suggested for IR irradiation [18]) was then applied to our experimental data taken under UV irradiation, and results were compared with the previous results for IR radiation. In both cases this approach gave the best normalization when calibrating the bronze samples.

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • L. Fornarini
    • 1
  • V. Spizzichino
    • 1
  • F. Colao
    • 1
  • R. Fantoni
    • 1
  • V. Lazic
    • 1
  1. 1.ENEA Frascati, FIS-LASFrascatiItaly

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