A fast method for the chemical analysis of clays by total-reflection x-ray fluorescence spectroscopy (TXRF)

Applied Clay Science 180 (2019) 105201

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Applied Clay Science journal homepage: www.elsevier.com/locate/clay

Research paper

A fast method for the chemical analysis of clays by total-reflection x-ray fluorescence spectroscopy (TXRF)

T

Ignazio Allegrettaa, , Biancamaria Ciascab, Maria D.R. Pizzigalloa, Veronica M.T. Lattanziob, Roberto Terzanoa ⁎

a b

Dipartimento di Scienze del Suolo, della Pianta e degli Alimenti, Università di Bari “Aldo Moro”, Via G. Amendola 165/A, 70126 Bari, Italy Istituto di Scienze delle Produzioni Alimentari, Consiglio Nazionale delle Ricerche, via Amendola 122/O, 70126 Bari, Italy

ARTICLE INFO

ABSTRACT

Keywords: TXRF Clays Elemental analysis Method development

A new, fast and cheap method for the analysis of clays using total-reflection x-ray fluorescence spectroscopy (TXRF) has been developed following a full factorial experimental design to optimize the sample preparation conditions. The optimized method consists of the dispersion of 50 mg of clay into 2.5 ml of 1% Triton X-100 solution, the deposition of 5 μl of the suspension onto a siliconized quartz reflector and drying it at 50 °C on a heating plate. By using a commercial benchtop instrument, 15 major and trace elements were correctly quantified with 1000 s live time acquisitions. Thirty minutes were sufficient for both sample preparation and analysis. Validation experiments, performed using a certified reference material, showed recoveries in the range 80–120% for the main targeted elements, whereas the within laboratory reproducibility (RSDWLR) and the repeatability (RSDr) were lower than 20%, demonstrating the good precision and reliability of the method. Only in the case of Si, the RSDWLR and RSDr were higher than 20%, due to the variable contribution of the quartz reflector. Suitable LOD and LOQ values were estimated, varying from 0.1–0.4% for Al to 1–2 mg/kg for Sr, with higher sensitivity for elements with higher fluorescence energy (and high atomic number, Z). Finally, a good agreement was obtained between the results of the analysis of reference materials performed with the new TXRF method and a reference method, such as wavelength dispersive x-ray fluorescence spectroscopy (WDXRF). Based on the above performances, this method may represent a valuable and reliable alternative analytical tool when only small amounts of clay samples are available such as in the case of mineral synthesis, clays extraction from soils and sorption tests.

1. Introduction

AES or ICP-MS analysis is very complex and time-consuming. In fact, it consists of several steps, including fusion, dehydration (or fusion and coagulation), and sample decomposition. Hazardous chemicals (i.e., strong acids) and very expensive tools (e.g., platinum crucibles) are also required. Furthermore, in some applications such as clays microsyntheses or sorption tests, the amount of sample necessary to accomplish the standard methods is often too large (1.2 g per replicate). Gutsuz et al. (2017) have developed a method that requires only 200 mg of sample for the production of beads, which are then dissolved in HNO3 for ICP-MS analysis. However, also in this case, the sample preparation required several steps, and the thermal treatment (at 1050 °C) may cause the loss by volatilization of elements such as As, Hg and Se. Neutron activation analysis (NAA) is another analytical technique used for the elemental characterization of clays. Even if the amount of sample required for NAA is very small (80–130 mg) and no

Clays and clay minerals are widespread natural materials whose characterization is needed in several research (e.g., geology, environmental sciences, archaeometry, material science, soil science, etc.) and industrial fields (e.g., ceramic and composite production, food processing, mining, pharmacy, etc.). Together with mineralogical and physical investigations, chemical analysis of clay samples is a crucial step in their study and characterization. Several methods are available for the chemical analysis of clays and aluminosilicates. The most common ones require the use of analytical instruments based on inductively coupled plasma sources associated to atomic emission spectrometers (ICP-AES) or mass spectrometers (ICP-MS) (Gutsuz et al., 2017; Ndzana et al., 2018). According to standard analytical methods (UNI ISO 215871:2007 and UNI ISO 21587-3:2007), the sample preparation for ICP-

⁎

Corresponding author. E-mail address: [email protected] (I. Allegretta).

https://doi.org/10.1016/j.clay.2019.105201 Received 7 December 2018; Received in revised form 18 June 2019; Accepted 24 June 2019 0169-1317/ © 2019 Elsevier B.V. All rights reserved.

Applied Clay Science 180 (2019) 105201

I. Allegretta, et al.

sample preparation is needed, the analysis can last several days, depending on the radionuclide lifetime (Hein et al., 2002, 2004). X-ray based spectroscopies are also widely used for the chemical analysis of clays. Among them, wavelength dispersive x-ray fluorescence (WDXRF) spectroscopy is the most common and diffuse (Allegretta et al., 2017a; D'Elia et al., 2018; Hein et al., 2002, 2004; Lorentz et al., 2018; Ogundiran and Kumar, 2015). For this kind of analysis, samples can be prepared as pressed pellets or fused beads. In the first case, 1–5 g of samples are ground and mixed with a binding agent and then pressed. In this way, the sample preparation is very fast, but the large amount of sample needed remains a critical issue. On the other side, when preparing fused beads, 300 mg of sample are mixed with a fusing agent (usually lithium borate) and then poured in platinum crucibles for thermal treatment (800–1000 °C), resulting however in a much longer sample preparation procedure (Margui et al., 2016). In the field of x-ray based techniques, total-reflection x-ray fluorescence spectroscopy (TXRF) is a very good method for the analysis of small amounts of sample (20–100 mg), requiring a very simple and fast sample preparation procedure. The possibility to perform direct analysis with limited sample treatment makes this technique suitable for the chemical characterization of several kinds of environmental and geological samples (Klockenkämper and von Bohlen, 2015). Gerowinski and Goetz (1987) analysed major, minor and trace elements in different soil reference materials using TXRF on acid digested samples. Towett et al. (2013, 2015) investigated soil samples without preliminary digestion, using slurries, resulting in a much faster sample preparation. In only few cases, the elemental composition of rocks and aluminosilicate materials was determined by TXRF (Cherkashina et al., 2013, 2014). In these cases, only few elements were quantified and no specific study was carried out to set up the most suitable analytical parameters for the TXRF analysis. The problem of sample pretreatment for TXRF analysis of aluminosilicates was first faced by García-Heras et al. (1997), who focused their attention on specimen grinding and dispersant medium. This is the only case in which a clay sample was analysed by TXRF, even if the clay reference material was analysed only to validate a method for ceramic characterization. To our knowledge, no TXRF method has been developed for the analysis of clays. In particular, such a method could be advantageous when the amount of sample is scarce (e.g., deriving from clay extractions from soils, microsyntheses, sorption tests, etc.) or not sufficient for the application of other methodologies. For this reason, the present work aims at setting up a fast and robust analytical method for the direct analysis of clays using TXRF spectroscopy. To this purpose, samples were analysed as slurries and a full factorial experimental design was used to determine the best sample preparation procedure. The method was optimized and validated employing two standard certified reference clay materials and TXRF results were compared with those obtained by WDXRF, used as reference analytical method.

critical angle depends on the material of the sample carrier and the energy of the incident beam. When this condition is satisfied, the incident beam does not refract into the sample carrier but is totally reflected, producing several advantages for XRF analyses: i) reduction of matrix absorption effects, ii) increase of the signal-to-noise (S/N) ratio, and iii) consequent improvement of the detection limit (in the range of mg/kg for solids and μg/l or lower in the case of liquids). However, to achieve these results, a monochromatic x-ray beam is required. For this reason, TXRF spectrometers are commonly equipped with a filter, a reflector and a series of slits that cut off the bremsstrahlung and focalize the monochromatic beam onto a second reflector (the sample carrier), where the sample is deposited. The versatility of the technique allows to analyse several kinds of materials, such as liquids (Borgese et al., 2018), gases (Böttger et al., 2018), biological samples (Allegretta et al., 2017b; Markert et al., 1994), vegetables (Allegretta et al., 2019; Paradiso et al., 2018), nanomaterials (Bahadir et al., 2018), soils (Towett et al., 2013, 2015), minerals (Cherkashina et al., 2013, 2014), composites (GarcíaHeras et al., 1997, 2001), etc. For solid samples, small specimens can be directly analysed by suspending the powdered material in a liquid dispersant agent where an internal standard is added. Then, a small volume (few microliters) of the suspension is deposited on a sample carrier (reflector) and the liquid completely evaporated before the analysis. Further information on the physics, instrumentation and performances of TXRF are available in Klockenkämper and von Bohlen (2015). 3. Materials and methods 3.1. Experimental design 3.1.1. Optimization of the analytical procedure A set of eight aluminosilicate reference materials (GS-N, UB-N, BEN, AC-E, PM-S, DR-N, WS-E and AN-G, SARM-CRPG, France) were used to test the linearity of the instrument response and to calibrate the element relative sensitivities (Sr). For this step, Se was used as internal standard and its Sr was set equal to 1. A chemometric approach was used to optimize the conditions for the elemental analysis of clays in order to obtain maximum recovery rates. For this purpose, a full factorial design was generated using the software package MINITAB™ Statistical Software for Windows, version 14 (Minitab, State College, PA, USA). A phlogopite reference material (Mica-Mg by SARM-CRPG, France) was employed. Three independent factors were tested: sample weight (A), dispersant volume (B) and reflector type (C), in order to get information about the effect of these three factors and their interactions on the recovery. Each factor (A, B and C) was set at two levels (low and high, see Table 1). The effect to be observed was the change in recovery rates when switching each factor from one level to the other. In addition, two centre points were also considered (Table 1), to determine the analytical error in this series of experiments. Calculated error was then used to check whether the effects and the interactions were significant or not. A total of 20 experiments were conducted in a randomized order. At the end, for the optimization, the following ten sample preparations were done:

2. Basics of total-reflection X-ray fluorescence Generally, in X-ray fluorescence spectroscopy (XRF), a primary xray beam (generated by the bombardment of an anode with accelerated electrons) is focused on a sample. The interaction between the primary beam and the elements constituting the sample generates a secondary xray radiation which is characterized by different emission lines (K, L and M lines). These lines are characteristic of each chemical element and are produced by the removal of a bound inner electron, exited by the primary beam, which is then replaced by an outer bound electron. A background signal is also present in the secondary radiation. It is produced by the inelastic scattering of the primary beam continuous spectrum (also called bremsstrahlung) (Beckhoff et al., 2006). TXRF is a special type of x-ray fluorescence spectroscopy (XRF). Differently from traditional XRF (where the incidence angle of the primary x-ray beam to the sample is about 45°), the x-ray beam impinges the sample at an angle lower than a critical angle (< 1°). The

Table 1 Parameters and their levels considered in the experimental design for the optimization of the method. Variables

Sample weight (mg) Dispersant volume (ml) Reflector

2

Levels Low

Centre point

High

50 2.5 Quartz

75 3.75

100 5 Plexiglas

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• 50 mg of clay in 2.5 ml of Triton X-100, deposited on quartz reflector; • 50 mg of clay in 2.5 ml of Triton X-100, deposited on plexiglas reflector; • 50 mg of clay in 5 ml of Triton X-100, deposited on quartz reflector; • 50 mg of clay in 5 ml of Triton X-100, deposited on plexiglas reflector; • 75 mg of clay in 3.75 ml of Triton X-100, deposited on quartz reflector; • 75 mg of clay in 3.75 ml of Triton X-100, deposited on plexiglas reflector; • 100 mg of clay in 2.5 ml of Triton X-100, deposited on quartz reflector; • 100 mg of clay in 2.5 ml of Triton X-100, deposited on plexiglas reflector; • 100 mg of clay in 5 ml of Triton X-100, deposited on quartz reflector; • 100 mg of clay in 5 ml of Triton X-100, deposited on plexiglas re-

TXRF analyses were carried out using a benchtop S2 Picofox (Bruker Nano GmbH, Germany) spectrometer at environmental pressure. The instrument was equipped with a Mo microfocus tube working at 50 kV and 600 μA, a multilayer monochromator and an XFlash® silicon drift detector with 30 mm2 active area and an energy resolution lower than 150 eV at Mn-Kα. All samples were analysed for 1000 s live time, as suggested by Towett et al. (2013). 3.3. WDXRF analyses For WDXRF analyses, 5.0 g of powdered clay were mixed with 2 ml of 2% (w/v) solution of Elvacite® 2046 (PANalytical B.V., The Netherlands) in RPE grade acetone (Carlo Erba Reagenti Spa, Italy). After acetone evaporation, the powder was poured into an aluminium cup where 5.0 g of RPE grade boric acid (Carlo Erba Reagenti Spa, Italy) were previously weighed. Then, the sample was pressed at 25 t for 5 min, in order to obtain a flat and uniform disk. Sample analysis was carried out using a Supermini200 WDXRF spectrometer (Rigaku Corporation, Japan) equipped with a Pd source (200 W, 50 kV, 4 mA), a Zr filter, and three interchangeable crystals (LiF, PET and RX25) which focus the secondary beam on a proportional counter or a scintillator detector. Analysis were performed under vacuum (< 12 Pa). The instrument was calibrated using a set of 16 aluminosilicate reference materials by SARM-CRPG (France).

flector.

3.1.2. Validation design The optimized TXRF method was validated using a zinnwaldite reference material (ZW-C by SARM-CRPG, France). The validation experiments were carried out according to a 2-day nested design. According to the experimental design, 5 independent analyses were carried out on each day. In addition, three instrumental replicates for each sample were measured, resulting in 30 measurements in total. The analytical results, expressed as mg/kg, were then subjected to analysis of variance (ANOVA) as specified by ISO 5725-3 (1994). The model that underlies the analysis of variance of the data collected following this fully nested design is expressed by the following equation:

3.4. Optical and electron microscopy observations

where Yijk is the value of the single measurement, TV is the true value, Di is the between-day variability (days number from 1 to i), Sij is the between-sample preparation variability (replicated sample preparations number from 1 to j) and Rijk is the variability associated to the instrumental analysis (instrumental replicate number from 1 to k). The sum of the last two factors (instrumental analysis and between-sample preparation variability) gives the precision under repeatability conditions, whereas the sum of all components (including the between-day variability) gives the within laboratory reproducibility. The precision is expressed in terms of relative standard deviation of repeatability (RSDr) and relative standard deviation of within laboratory reproducibility (RSDWLR). The trueness of the method was evaluated via the analysis of ZW-C reference material as closeness of agreement between the value obtained from the optimized TXRF method and the certified reference concentrations and expressed as recovery. Limit of detection (LOD) and limit of quantification (LOQ) were also assessed according to Klockenkämper and von Bohlen (2015).

Optical and electron microscopies were used to evaluate the quality of sample deposition on the reflector. In particular, an SZH10 stereomicroscope (Olympus Optical Co. GmbH, Germany) equipped with optical fibre illumination was used to study the shape of the deposition on both quartz and plexiglas reflectors. A field emission gun scanning electron microscope (FEG-SEM) Zeiss Σigma 300 VP (Zeiss, Germany), equipped with a secondary electron detector, was used for the determination of the thickness of the deposition. In particular, 5 μl of suspension were pipetted onto the reflectors (near the border and not at the centre). Then, the reflectors were fixed from their lateral side onto aluminium stubs. In order to ensure the electron conductivity, copper connections were created between the reflector and the stub and, finally, the sample was carbon coated. In this way, the electron beam impinged on the sample horizontally ad a transversal view of the deposition could be acquired. FEG-SEM analyses were carried out at 5–15 kV with 7.5 mm working distance. For the determination of the clay grain size, 10 mg of the clay material were suspended into 100 ml of distilled water. After vortexing, 100 μl were pipetted onto an aluminium stub covered by a carbon tape and after drying at room temperature it was carbon coated. An area of 1.0 × 1.4 mm, corresponding to the central part of the stub, was observed using the secondary electron detector. The image was then processed using AZtecFeature software (Oxford Instruments, United Kingdom) in order to determine the average size of about 1300 identified particles.

3.2. TXRF analysis

4. Results and discussion

Clay samples were finely ground for 2 min with a vibromilling system (MM400, Retsch, Germany), weighed in a 10 ml polypropylene tube and suspended in a 1% Triton X-100 (Sigma Aldrich CHEMIE GmbH, Germany) solution, used as dispersant agent. After slurry preparation, 10 μl of Se 1000 mg/l standard solution (Sigma Aldrich CHEMIE GmbH, Germany) were added to the suspension. The suspension was vortexed for 30 s and then placed in an ultrasonic bath for 10 min. After vortexing again for 30 s, 5 μl of suspension were pipetted onto a reflector (made of quartz or plexiglas) under a laminar flow hood. The deposited drop was left drying on a heating plate at 50 °C for 5–10 min. After drying, the reflector was loaded on a reflector holder and analysed.

For TXRF analyses, the quality of sample deposition on the sample carrier is extremely important to obtain good quantitative data. In particular, the deposition of a thin-film of material characterized by very fine particles is fundamental. According to García-Heras et al. (1997), a grain size of 10 μm is suitable to get reliable quantitative TXRF data for aluminosilicate materials. As shown in Fig. 1, the grain size of both Mica-Mg and ZW-C reference materials analysed was lower than 10 μm, for most of the particles. In particular, for Mica-Mg (Fig. 1A), the average grain size was 4.6 μm with 92% of the particles having a size < 10 μm. In the case of ZW-C (Fig. 1B), the average grain size was 5.6 μm, and 84% of the particles had a grain size < 10 μm. In both cases, the features classified as larger than 10 μm were mostly

Yijk = TV + Di + Sij + Rijk

3

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Table 2 Fluorescence line used for the element detection and the calculated relative sensitivities (Sr).

Fig. 1. Particle grain size in terms of equivalent circular diameter (ECD) of Mica-Mg (A) and ZW-C (B) after image analysis of FEG-SEM micrograph.

Element

Fluorescence Line

Energy (keV)

Sr

Mg Al Si Cl K Ca Ti V Cr Mn Fe Ni Cu Zn Ga Se Rb Sr Ba Pb

Kα Kα Kα Kα Kα Kα Kα Kα Kα Kα Kα Kα Kα Kα Kα Kα Kα Kα Lα Lα

1.125 1.486 1.740 2.622 3.314 3.692 4.512 4.953 5.415 5.900 6.405 7.480 8.046 8.637 9.251 11.224 13.396 14.165 4.466 10.551

0.000153 0.000595 0.002285 0.014477 0.037427 0.083714 0.142429 0.177963 0.230296 0.280364 0.355982 0.517312 0.581101 0.675427 0.775121 1.000000 1.163880 1.166584 0.064744 0.674929

A

aggregates of two or more particles having individually a grain size lower than 10 μm. For this reason, the grain size of both samples could be considered suitable for the preparation of suspensions for TXRF analyses. For most of the clays, this prerequisite can be considered easily achievable for the intrinsic characteristics of these materials. Another parameter to monitor is the thickness of the dried deposition. In order to avoid the mass adsorption effect of the sample, the thickness of the deposition should be lower than a critical thickness (tcrit). According to Klockenkämper and von Bohlen (2015), tcrit ≈ 50 nm for mineral powders. However, the particle size of both Mica-Mg and ZW-C did not allow to achieve such a thin deposition and therefore mass adsorption effects cannot be neglected. For this reason, the relative TXRF sensitivity (Sr) of each element was preliminarily calibrated using eight aluminosilicate reference materials (GS-N, UB-N, BE-N, AC-E, PMS, DR-N, WS-E and AN-G, SARM-CRPG, France) prepared in the same way as the samples. Selenium internal standard was used for the relative sensitivity calibration and the Sr of Se was considered equal to 1. This operation was done after testing the linearity of the response between the fluorescence intensity and the real concentration of the element in the aluminosilicate reference materials (Fig. S1). Since Si and S were also present in quartz and plexiglas reflectors, respectively, their relative sensitivity was obtained by interpolating the relative sensitivities of the other elements with a fifth-degree polynomial function. The values of Sr calculated for each specific element line are reported in Table 2. In order to reduce the size of the sample dispersion on the reflector surface, usually hydrophobization of the sample carrier with a siliconizing agent is needed. While for quartz carriers this is a common practice (Cherkashina et al., 2013, 2014; Towett et al., 2013, 2015), for plexiglas reflectors no indications are reported in the literature. The siliconizing agent (silicon solution, SERVA, Germany) allowed to obtain a less dispersed dried deposition on plexiglas reflectors (Fig. 2A and B), even if the deposition on the quartz reflectors was more regular and uniform (Fig. 2C).

2 mm

B

2 mm

C

2 mm

Fig. 2. Dried deposition of clay on a non‑siliconized plexiglas reflector (A), a siliconized plexiglas reflector (B) and a siliconized quartz reflector (C).

4.1. Optimization

detected in the spectrum. Since TXRF analyses were carried out in air at atmospheric pressure, a weak peak of Ar was also visible in the spectrum. Because of atmospheric Ar, Na, an important major element in clays, cannot be detected by TXRF, since its fluorescence lines are absorbed by Ar atoms. Prost et al. (2018) and Streli et al. (2004)

For the method optimization, the Mica-Mg reference material was employed and its TXRF spectrum is reported in Fig. 3. The K-lines of major (Mg, Al, Si, K, Ca, Ti, Mn and Fe) and minor (Cl, V, Cr, Ni, Cu, Zn, Ga, Rb and Sr) elements and the L-lines of Ba and Pb were clearly 4

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I. Allegretta, et al.

Ni Cu Ga Zn

Pb Se

Rb Sr

Ca- Kα

Fe Mn

K - Kβ

Ti Ba

Cr

log I (cps)

Si

Ca

K

log I (cps)

Mg Al

B K - Kα

A

.

.

.

E (keV)

.

.

.

E (keV)

Fig. 3. TXRF spectra of the clay reference material Mica-Mg prepared using 50 mg of sample, 2.5 ml of Triton solution and deposited on a quartz (black) and plexiglas (red) reflectors (A). The magnification of the spectra in the range 3.0–4.0 keV, shows the overlapping of the K-Kβ and Ca-Kα lines (B). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

demonstrated that analysing samples under vacuum and using a low energy source could overcome this problem, allowing the detection of light elements (also with atomic numbers lower than Na). The experimental design matrix and the recoveries obtained in each condition are shown in Table 3. According to these results, the highest number of elements which was possible to quantify with a good accuracy was achieved for samples prepared using 50 mg of material dispersed into 2.5 ml Triton solution and deposited onto quartz reflectors. In fact, with this sample preparation, 15 different elements (on 19 detected elements) were quantified with a recovery in the range 80–120%. Among these elements, all major elements (except for Ca) and trace elements (Cl, Ni, Cu, Zn, Ga, Rb, Sr and Pb) were correctly quantified. Calcium was not correctly quantified because the intense potassium K-β signal overlaps with the very weak calcium K-α peak (Fig. 3B), thus biasing its correct quantification. Good results were also

obtained with 75 mg of sample, 3.75 ml of dispersant agent and using quartz reflectors (13 elements correctly quantified), even if an important major element, Mg, was not correctly quantified. When plexiglas was used as reflector, accurate data were obtained using 50 mg of sample into 5 ml of dispersant or 100 mg into 2.5 ml (12 elements). However, in these cases, major elements concentrations strongly differed from reference values. Statistical significance of the experimental factors contributions, and their first-order interactions, were determined by analysis of variance (ANOVA). The estimated standardized effects on the recovery of some relevant elements (Mg, Si, K, Fe, Sr and Ba) are summarized in Fig. 4. These elements were chosen because their characteristic fluorescence signals (K-lines for Mg, Si, K, Fe, Sr and L-lines for Ba) cover all the energy ranges comprised in the spectrum of the detected elements. The red dotted line is calculated from the random error obtained from

Table 3 Recovery (%) obtained for each element after the preparation of slurries using different parameters and TXRF analysis. A recovery of 80–120% was considered acceptable for the correct element detection. The certified concentration of each element is also reported. Sample weight (mg)

50

50

50

50

75

75

100

100

100

100

Triton solution volume (ml)

2.5

2.5

5

5

3.75

3.75

2.5

2.5

5

5

Reflector Mg Al Si Cl K Ca Ti V Cr Mn Fe Ni Cu Zn Ga Rb Sr Ba Pb Total number of elements with a recovery in the range 80–120%

Quartz 111 102 85 100 107 36 84 133 65 82 92 96 86 104 86 105 113 75 109 15

Plexiglas 222 185 126 179 149 42 112 185 110 105 116 122 46 126 111 128 126 92 159 6

Quartz 132 123 123 132 117 36 87 145 64 82 90 94 21 97 84 98 103 71 86 10

Plexiglas 214 192 127 169 132 27 95 106 99 87 97 104 39 104 94 104 106 81 94 12

Quartz 131 115 100 110 112 42 87 156 56 84 93 96 17 101 86 103 108 72 117 13

Plexiglas 246 204 139 200 154 42 114 167 82 105 116 119 28 126 110 127 119 91 181 7

Quartz 51 49 42 59 74 37 64 163 46 67 76 79 32 86 72 91 96 54 112 4

Plexiglas 172 137 92 118 118 34 90 137 90 87 97 100 23 108 92 110 112 79 123 12

Quartz 110 98 86 97 94 30 71 105 64 68 76 80 39 83 71 85 89 63 83 11

Plexiglas 236 194 132 184 142 40 104 170 76 95 105 108 24 112 101 113 107 81 129 9

5

Reference Value

mg/kg 12.30 (%) 8.04 (%) 17.89 (%) 800 8.25 (%) 0.06 (%) 0.98 (%) 90 100 0.20 (%) 6.62 (%) 110 4 290 21 1300 27 4000 9

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Mg

Si

2.20

K

2.20

2.20

C

C

B

B

A

A

A

AB

AB

AC

B

AC

AB

AC

ABC

BC

ABC

BC

ABC 0

5

10

15

20

C

BC 0

2

4

6

Fe

8

10

12

0

14

C A

A

AB

B

AB

ABC

AC

AC

AC

AB

BC

B

ABC

B

BC

BC

ABC

3

4

5

6

0.0

A = sample weight

8

10

2.20

A

2

6

Ba 2.20

C

1

4

Sr

2.20

0

2

C

0.5

1.0

1.5

2.0

B = dispersant volume

2.5

0

1

2

3

4

5

6

C = reflector

Fig. 4. Pareto charts of Mg, Si, K, Fe, Sr and Ba showing the contribution of the sample weight (A), dispersant volume (B), reflector (C) and their combination (AB, AC, BC, ABC) for the quantification of the quantification of the elements.

reflector. In fact, considering only the tests where quartz reflectors were employed, the best performances for both major and trace elements were obtained when the ratio between sample weight and solution volume (A/B) was equal to 20 mg/ml (Table 3). When the ratio was higher than 20 mg/ml (e.g., 100 mg in 2.5 ml), the thickness of the deposition increased to a size that reduced the total reflection effect (Fig. 5), causing a higher matrix absorption of the fluorescence signal and the consequent underestimation of almost all elements (Table 3). On the contrary, when the sample was too much diluted in the dispersant agent (i.e. 50 mg into 5 ml), a slight overestimation of the light elements was observed (Table 3). In the case of Si, all the variables and their interactions (AB, AC, BC and ABC) affected its quantification, suggesting that a right balance among the three variables needs to be found for its correct analysis. Quartz reflectors are made of SiO2 and, for this reason, the thickness of the sample deposition layer also influences the fluorescence signal of the Si of the reflector. In fact, when A/B was < 20 mg/ml, less material was deposited onto the reflector, thus increasing the reflector contribution to the silicon K-α signal and causing an overestimation of Si in the sample. Similarly to what happens for the other elements, when A/B was > 20 mg/ml, the higher thickness of the deposition caused a larger matrix absorption and thus an underestimation of Si. Since the best results were achieved suspending 50 mg of clay into 2.5 ml of Triton X-100 solution and using quartz as sample carrier, this procedure was identified as the optimized method and was, therefore, subjected to a validation process.

the replicates of the experiments having all factors at the centre level. The bars overcoming the red dotted line represent the factors (single variables and their combinations) which significantly affect the element quantification. Generally, with the increase of the element characteristic K fluorescence energy (i.e. increase of Z), the number of factors affecting the quantification of the element concentration is reduced. In fact, for elements quantified using K-α lines (e.g., Mg, Si, K, Fe and Sr, Fig. 4) the number of factors influencing the quantification changes from 5 (for low Z elements like Mg) to 1 (for high Z elements like Sr). However, for elements quantified using L-lines (e.g., Ba, Fig. 4), which have a higher Z than Sr and Fe, the number of factors which affected their quantification increases again to 2. Among all the studied factors, the material of the reflector (C) was the variable which mostly affected the recovery of the elements. This could be explained since quartz and plexiglas have two different critical angles of 0.10° and 0.076°, respectively (Klockenkämper and von Bohlen, 2015). Since in commercial TXRF spetrometers the incident beam is set at a fixed angle (usually at the quartz critical angle), other types of reflectors, like plexiglas ones, can suffer for a not perfect geometry thus giving slightly biased results (Table 3). The second variable which affected the correct element quantification was the sample weight (A). In particular, the higher the amount of suspended sample, the thicker is the deposition layer, with a consequent reduction of the total reflection effect due to matrix absorption attenuation. In fact, both the primary beam and the reflected beam should pass through and emerge from the sample layer with a consequent x-ray attenuation, mainly due to photoelectric adsorption (Klockenkämper and von Bohlen, 2015). The effect of the dispersant volume (B) on the quantified values was very low with the exception of Mg and Si, for which it was comparable to that of the sample weight. An important factor influencing data quantification was the combination of the two variables A and B (AB), in particular for the elements with lower energy fluorescence emissions (from Mg to Ti). This highlights the importance of the concentration of sample particles suspended in the dispersant agent, which affects the thickness and the distribution of the deposition layer on the

4.2. Validation The optimized method was subjected to intra-laboratory validation using Zinnwaldite reference material (ZW-C) as test material. According to the optimized protocol, 50 mg of sample were suspended in 2.5 ml of Triton solution, followed by the deposition of 5 μl of suspension on quartz reflectors. A typical TXRF spectrum of ZW-C is shown in Fig. 6. The detected elements were Al, Si, K, Ca, Ti, Cr, Mn, Fe, 6

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A

B

Fig. 5. Secondary electron FEG-SEM micrographs showing the thickness of the clay deposition onto a quartz reflector of a suspension made with 2.5 ml of dispersant agent, 50 mg (A) and 100 mg of sample (B). Ca

Al

Fe Mn

K Ti

Pb Se

reference values (11 ± 16.87 mg/kg for Ni and 82 ± 23.75 mg/kg for Pb, Govindaraju et al., 1994). Regarding to aluminium, its K-α peak overlapped with the L-lines of rubidium, whose intensity was one order of magnitude higher than in the case of the Mica-Mg reference material. This, in addition to the presence of the potassium escape peak (1.574 keV), could lead to an incorrect deconvolution of the aluminium K-α fluorescence peak, thus causing an overestimation of this element. In Table 4, the data of the within laboratory reproducibility (RSDWLR) and repeatability (RSDr) are also reported. As mentioned before, RSDWLR takes into account the contribution of three sources of variability (day, sample preparation and instrumental analysis) while RSDr includes the variability associated to sample preparation and instrumental analysis. The highest RSDWLR was obtained for Cr, Ni and Si for which it exceeded 20%. However, while for Cr and Ni this could be explained by the high variability of these elements in the reference material (see Govindaraju et al., 1994), for Si the high RSDWLR could be imputed to the contribution of the quartz reflector. Despite the contribution of the reflector, the overall method precision was considered fit-for-the purpose of clay analysis. Regarding RSDr, it followed the same trend of RSDWLR and for some elements (Si, K, Ca, Ti, Mn, Fe, Zn, Ga, Rb and Sr) it was even lower, testifying the good precision of the method. The contributions given by the analytical replicates (Instrument), sample preparation (Sample) and the day of the analysis (Day) were different and depended on the element. However, the different contributions were irrelevant due to the very low RSDr, which testified a satisfactory repeatability and precision of the method. Finally, the limit of detection (LOD) and quantification (LOQ) were also determined according to Klockenkämper and von Bohlen (2015):

Rb Sr

Cr

log I (cps)

Si

Ni Cu Ga Zn

E (keV)

Fig. 6. TXRF spectrum of ZW-C reference material.

Ni, Cu, Zn, Ga, Rb, Sr and Pb. The fluorescence lines of atmospheric Ar, the source (Mo) and the internal standard (Se) were also observed. The results of the validation process are shown in Table 4. With the exception of Al, Ni and Pb, all the elements had a recovery in the range 80–120% demonstrating the good accuracy of the method. The overestimation of Ni and Pb with respect to the reference values could be imputed to an uneven distribution of these elements in the test sample, as suggested by the high standard deviations associated with the

Table 4 Results of the validation performed on the ZW-C reference material. The reference value (RV), the determined concentration (Mean), the recovery, the within laboratory reproducibility (RSDWLR), the repeatability (RSDr) with its different contributions (Day, Sample and Instrument), the limits of detection (LOD) and quantification (LOQ) are reported for each element. Elements

RV (mg/kg) Mean (mg/kg) Recovery (%) RSDWLR (%) RSDr (%) Day Sample Instrument LOD (mg/kg) LOQ (mg/kg)

Al

Si

K

Ca

Ti

Cr

Mn

Fe

Ni

Cu

Zn

Ga

Rb

Sr

Pb

97,600 131,938 135 5 5 0 19 81 1153 3845

252,200 247,412 98 24 21 21 8 71 279 930

63,600 65,803 103 7 4 65 9 26 24 81

2600 2264 87 11 5 79 9 12 8 25

300 270 90 9 6 52 28 20 5 17

56 63 112 95 95 0 95 5 4 12

7500 6175 82 12 6 77 13 10 4 14

66,200 55,359 84 10 6 66 21 13 4 12

11 14 127 37 37 0 1 99 1 3

39 26 68 12 12 2 26 71 1 3

1050 1052 100 11 7 63 21 16 1 3

99 81 82 10 5 68 21 11 1 2

8500 7734 91 11 6 69 20 11 1 3

17 18 108 15 10 58 28 14 1 2

80 126 158 18 18 0 0 100 1 2

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A

B TXRF WDXRF Recovery (%)

Recovery (%)

TXRF WDXRF

Fig. 7. Comparison of TXRF and WDXRF results obtained on Mica-Mg (A) and ZW-C (B) reference materials.

LOD = 3

are the most important for clay characterization, in particular to support XRD mineralogical analyses (Omotoso et al., 2006; Ottner et al., 2000). Results showed that almost all elements were in the range 80–120% of recovery for both techniques. Excluding potassium, TXRF data were more dispersed than WDXRF ones. This is due to the larger amount of sample used in WDXRF analyses (5 g) which allows to reduce errors due to sample heterogeneity. Moreover, even if the majority of the analysed samples had an average grain size lower than 10 μm (Fig. 1), some aggregates could have formed during the deposition of the sample on quartz reflectors, thus slightly modifying the response of the sample to primary beam excitation and increasing data variability in TXRF. This effect was more evident for Si analysis, where the composition of the quartz reflector contributed to the variability of Si quantification. As expected, Na could be analysed only with WDXRF since the analyses was performed under vacuum (Table 5). WDXRF was less accurate than TXRF for the quantification of Mg in Mica-Mg reference material (Fig. 7A). In the case of ZW-C (Fig. 7B), where Mg concentration was lower (965 mg/kg), TXRF was not able to detect the element, while WDXRF strongly underestimated it since it was close to its LOQ (1050 mg/kg). Calcium in Mica-Mg was underestimated with TXRF, while it was not detected at all with WDXRF, due to its very low concentration and the overlapping with the strong potassium K-β signal, which covered the calcium K-α peak. However, Fig. 7 clearly

Ci 2Nback Nnet

LOQ = 10

Ci 2Nback Nnet

where Ci, Nnet and Nback are the concentration of the analysed element, the net area of the peak of the analysed element and the background count rate, respectively. Both LOD and LOQ decreased with the increase of the element atomic number (Table 4). LOD varied from 1153 mg/kg for Al to < 1 mg/kg for Sr. In the case of LOQ, it ranged from 3845 mg/ kg for Al to 2 mg/kg for Ga, Sr, and Pb. These values confirm that this method is suitable for the characterization and study of clays, where elements concentration are usually higher than the LOQs calculated for each element. 4.3. Comparison with WDXRF TXRF results on both ZW-C and Mica-Mg were compared with the data obtained by WDXRF, used as reference analytical method (Fig. 7 and Table 5). In fact, WDXRF is a widely used and worldwide recognized method for clay analyses (Allegretta et al., 2017a; D'Elia et al., 2018; Hein et al., 2002, 2004; Lorentz et al., 2018; Ogundiran and Kumar, 2015). The comparison was done on major elements, since they

Table 5 Certified concentration. TXRF and WDXRF results obtained on both Mica-Mg and ZW-C reference materials. Both the oxide concentration (Conc.) and the standard deviation (σ) are expressed in weight percentage. Element

Mica-Mg

ZW-C

Certified Value

SiO2 TiO2 Al2O3 Fe2O3 MnO MgO CaO Na2O K2O Li2O P2O5 F LOIa a b

TXRF

WDXRF

Certified Value

TXRF

WDXRF

Conc. (%)

σ (%)

Conc. (%)

σ (%)

Conc. (%)

σ (%)

Conc. (%)

σ (%)

Conc. (%)

σ (%)

Conc. (%)

σ (%)

38.30 1.63 15.20 9.46 0.26 20.40 0.08 0.12 10.00 0.05 0.01 2.85 1.75b

0.36 0.10 0.44 0.34 0.04 0.04 0.04 0.21 0.29 0.02 0.27 0.11 –

32.72 1.37 15.56 8.75 0.21 22.54 0.03 – 10.67 – – – –

0.89 0.02 1.09 0.27 0.01 1.04 0.00 – 0.04 – – – –

37.50 1.74 12.50 9.74 0.24 25.47 – 0.24 10.24 – – – –

0.38 0.02 0.15 0.09 0.00 0.20 – 0.02 0.70 – – – –

54.00 0.05 18.45 9.46 0.97 0.16 0.37 0.33 7.72 4.85 0.03 5.45 2.30b

0.98 0.02 0.66 0.47 0.10 0.05 0.07 0.10 0.41 0.80 0.04 0.66 –

52.98 0.03 24.93 7.92 0.80 – 0.31 – 7.98 – – – –

11.90 0.00 1.27 0.64 0.07 – 0.03 – 0.43 – – – –

54.13 0.05 19.20 10.35 0.97 0.08 0.31 0.47 7.90 – – – –

0.54 0.00 0.18 0.09 0.01 0.00 0.01 0.05 0.54 – – – –

LOI: Loss on ignition. proposed value. 8

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shows that the two techniques give substantially the same information regarding the average elemental composition of clays with good accuracy and different grades of precision, mostly depending on the element and type of clay.

https://doi.org/10.1016/j.sab.2018.07.016. Beckhoff, B., Kanngiesser, B., Langhoff, N., Wedell, R., Wolff, H. (Eds.), 2006. Handbook of Practical x-Ray Fluorescence Analysis. Springer-Verlag, Berlin Heildeberg. Borgese, L., Dalipi, R., Riboldi, A., Bilo, F., Zacco, A., Federici, S., Bettinelli, M., Bontempi, E., Depero, L.E., 2018. Comprehensive approach to the calidation of the standard method for total reflection x-ray fluorescence analysis of water. Talanta. 181, 165–171. https://doi.org/10.1016/j.talanta.2017.12.087. Böttger, S., Tyssebotn, I.M.B., Jansen, W., Fittschen, U.E.A., 2018. Evaluating internal standards for the determination of gas phase mercury using silver nanoparticle assisted total reflection x-ray fluorescence. Spectrochim. Acta B 147, 93–99. https:// doi.org/10.1016/j.sab.2018.05.013. Cherkashina, T.Yu., Panteeva, S.V., Finkelshtein, A.L., Makagon, V.M., 2013. Determination of Rb, Sr, Cs, Ba, and Pb in K-feldspars in small sample amounts by total reflection X-ray fluorescence. X-Ray Spectrom. 42, 207–212. https://doi.org/10. 1002/xrs.2469. Cherkashina, T.Yu., Panteeva, S.V., Pachkova, G.V., 2014. Applicability of direct total reflection X-ray fluorescence spectrometry for multielement analysis of geological and environmental objects. Spectrochim. Acta B 99, 59–66. https://doi.org/10.1016/ j.sab.2014.05.013. D'Elia, A., Pinto, D., Eramo, G., Giannossa, L.C., Ventruti, G., Laviano, R., 2018. Effects of processing on the mineralogy and solubility of carbonate-rich clays for alkaline activation purpose: mechanical, thermal activation in red/ox atmosphere and their combination. Appl. Clay Sci. 152, 9–21. https://doi.org/10.1016/j.clay.2017.11.036. García-Heras, M., Fernández-Ruiz, R., Tornero, J.D., 1997. Analysis of archaeological ceramics by TXRF and contrasted with NAA. J. Archaeol. Sci. 24, 1003–1014. https:// doi.org/10.1006/jasc.1996.0178. 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John Wiley & Sons Inc., Hoboken. Lorentz, B., Shanahan, N., Stetsko, Y.P., Zayed, A., 2018. Characterization of Florida kaolin clays using multiple-technique approach. Appl. Clay Sci. 161, 326–333. https://doi.org/10.1016/j.clay.2018.05.001. Margui, E., Queralt, I., Van Grieken, R., 2016. Sample preparation for x-ray fluorescence analysis. In: Meyers, R.A. (Ed.), Encyclopedia of Analytical Chemistry. John Wiley & Sons Inc, Hoboken, pp. 1–25. https://doi.org/10.1002/9780470027318.a6806m. pub3. Markert, B., Reus, U., Herpin, U., 1994. The application of TXRF in instrumental multielement analysis of plants, demonstrated with species of moss. Sci. Total Environ. 152, 213–220. https://doi.org/10.1016/0048-9697(94)90312-3. Ndzana, G.m., Huanf, H., Wang, J.B., Zhang, Z.Y., 2018. Characteristics of clay minerals in soil particles from an argillic horizon of Alfisol in Central China. Appl. Clay Sci. 151, 148–156. https://doi.org/10.1016/j.clay.2017.10.014. Ogundiran, M.B., Kumar, S., 2015. 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5. Conclusions In the present study, a new fast method for the chemical characterization of clays using TXRF was developed and discussed. The method was optimized and validated using two certified reference materials (phlogopite Mica-Mg and zinnwaldite ZW-C) and then compared with a widely used and recognized method such as WDXRF. The best sample preparation procedure consisted in dispersing 50 mg of clay into 2.5 ml of 1% Triton X-100 solution, depositing 5 μl of the suspension onto a siliconized quartz reflector and drying it at 50 °C on a heating plate. TXRF analysis was carried out for 1000 s live time with a commercial benchtop instrument. In this way, 15 major, minor and trace elements were correctly quantified. Sodium could not be determined due to its very weak fluorescence signal that is absorbed by atmospheric Ar. The within laboratory riproducibility and the repeatability were lower than 20%, demonstrating the good precision and reliability of the method. Only in the case of Si, the RSDWLR and RSDr were higher than 20%, due to the variable contribution of the quartz reflector. The LOD and LOQ are suitable for the application of the method to the analysis of clays, varying from 0.1–0.4% for Al to 1–2 mg/kg for Sr, with higher sensitivity for elements with higher fluorescence energy. TXRF results were similar to those of WDXRF, suggesting the possibility to use of this technique instead of “more traditional” ones. The developed method was simple, fast, cheap and eco-friendly. Moreover, since a small amount of sample is required, the method could be applied especially to those fields of research in which a small quantity of sample can be produced such as mineral synthesis, clays extraction from soils, sorption tests, etc. Further developments of the method should concern the implementation of TXRF spectrometers with vacuum pump and/or low energy tubes which may allow to detect also Na, which is an important element for clay characterization. Based on the satisfactory results obtained in the intra-laboratory validation study, the method proposed herein can be considered for full inter-laboratory validation, in order to evaluate its robusteness among different laboratories and propose a standard reference protocol for the analysis of clay by TXRF. Supplementary data to this article can be found online at https:// doi.org/10.1016/j.clay.2019.105201. Acknowledgments TXRF analysis were performed at the “Micro X-ray Lab” of the University of Bari (Italy) supported by Regione Puglia (Programma Operativo Regione Puglia - FERS 2000–2006 -Risorse Liberate Obiettivo Convergenza). References Allegretta, I., Eramo, G., Pinto, D., Hein, H., 2017a. The effect of the mineralogy, microstructure and firing temperature on the effective thermal conductivity of traditional hot processing ceramics. Appl. Clay Sci. 135, 260–270. https://doi.org/10. 1016/j.clay.2016.10.001. Allegretta, I., Porfido, C., Panzarino, O., Fontanella, M.C., Beone, G.M., Spagnuolo, M., Terzano, R., 2017b. Determination of as concentration in earthworm coelomic fluid extracts by total-reflection X-ray fluorescence spectrometry. Spectrochim. Acta B 130, 21–25. https://doi.org/10.1016/j.sab.2017.02.003. Allegretta, I., Gattullo, C.E., Renna, M., Paradiso, V.M., Terzano, R., 2019. Rapid multielement characterization of microgreens via total-reflection X-ray fluorescence (TXRF) spectrometry. Food Chem. 296, 86–93. https://doi.org/10.1016/j.foodchem. 2019.05.187. Bahadir, Z., Torrent, L., Hidalgo, M., Marguì, E., 2018. Simultaneous determination of silver and gold nanoparticles by cloud point extraction and total reflection X-ray fluorescence analysis. Spectrochimica Acta Part B: Atomic Spectroscopy 149, 22–29.

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UNI ISO 21587-3:2007, 2007. Chemical Analysis of Aluminosilicate Refractory Products (Alternative to the X-Ray Fluorescence Method) - Part 3: Inductively Coupled Plasma and Atomic Absorption Spectrometry Methods.

Web References SARM-CRPG, France, 2019. Les materiaux de reference. http://helium.crpg.cnrs-nancy. fr/SARM/pages/geostandards.html, Accessed date: 18 June 2019.

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