Trace element determination by femtosecond LA-ICP-MS in 10 mg extraterrestrial geological samples prepared as lithium borate glasses

Abstract

Bulk chemical composition analysis is a primary and pivotal analytical task for extraterrestrial geological samples (e.g., lunar soil, asteroids, or meteoroids). However, the analysis of mg-level consumption of extraterrestrial geological samples poses a significant challenge to existing analytical techniques. In this study, a new method was developed for trace element determination in bulk extraterrestrial geological samples prepared as lithium borate glasses, following customized procedures for X-ray fluorescence (XRF) analysis with a 10 mg sample by femtosecond LA-ICP-MS. All thirty-two trace elements in the borate glass samples were evenly distributed with homogeneity indices (H) < H_crit. For the borate glass samples, Si was more suitable as an internal standard for Co, Ni, Cu, and Zn, whereas Al was better for the others. The femtosecond laser greatly reduces the influence of matrix effects, making calibration with non-matrix-matched external standards (NIST 612 and 614) accurate. Although the mass ratio of the flux and sample was as high as 35 : 1, the analytical results of 32 trace elements in six silicate rock reference materials (covering mafic to felsic rock types) using the developed technique were consistent with the reference values within 10% for most elements, and analytical precision (RSD) was also within 10% for most elements. Finally, one lunar basalt (NWA14526) and one shergottite (NWA13190) were assayed using the proposed method, and a comparison with the results of solution nebulization (SN)-ICP-MS confirmed the reliability of the method. The proposed method, combined with XRF, achieved the rapid, simultaneous, and accurate determination of major and trace elements in the same small sample aliquot (10 mg), which is highly suitable for the analysis of extraterrestrial geological samples.

---

1. Introduction

With the development of deep-space earth science, the demand for extraterrestrial geological sample analysis is also increasing. However, the analysis of the extraterrestrial geological samples poses a huge challenge to existing analytical techniques.

Bulk chemical composition analysis is a pivotal analytical task, not only because it can provide important constraints on various evolution processes but also because it can provide basic data for subsequent research (e.g., remote sensing data calibration and isotope analysis).¹ Instrumental neutron activation analysis (INAA)^2–4 and inductively coupled plasma mass spectrometry (ICP-MS)^5,6 are the most widely used techniques owing to their excellent detection limits and sensitivity for trace element analysis of extraterrestrial materials.

INAA is a non-destructive analysis technique that is important for extraterrestrial materials. However, the results for some elements cannot normally be obtained (e.g. Si, P, Nb, Y, and Er).⁷ ICP-MS is a commonly used comparative technique for the determination of trace elements in geological samples.^8–10 For solution nebulization (SN)-ICP-MS, a low background value and a high sample dilution ratio (>1000) can yield accurate analysis results. However, this technology suffers from large sample consumption and unavailable sample Si information, which limit its application in extraterrestrial sample analysis.^11,12

Compared to SN, laser ablation (LA)-ICP-MS has the advantages of simpler and more rapid sample preparation and higher spatial resolution (generally >2 μm), making it a powerful and attractive analytical technique.^13–15 However, heterogeneity is a ubiquitous problem for bulk analysis, and the common sample preparation methods to date include pressed powder pellets,^16–18 flux-free fusion,^19–26 and flux fusion.^14,24,25 Compared to pressed powder pellets and flux-free fusion, flux fusion can eliminate the problems of mineralogical effects, sample particle size variation and losses of highly volatile elements (e.g., Pb and Zn).^17,27

The flux fusion technique produces sample glasses by melting sample powders mixed with fluxes (e.g., lithium tetraborate and lithium borate) and has been widely used for X-ray fluorescence (XRF) analysis.^28,29 Normally, flux fusion glass is prepared by fusing mixtures of 0.5 g sample powders with 2–10 times the mass of fluxes.^{14,25,30–34} However, 500 mg of sample consumption is not suitable for analyzing extraterrestrial geological samples. In our previous work, we established an analytical method for the determination of major elements in 30 mg samples by WD-XRF, which was successfully applied to the analysis of lunar soil collected by Chang'e-5.^1,35,36 Additionally, in subsequent research, we further reduce sample consumption to 10 mg to analyze particles of different sizes in lunar soil.³⁷ Considering the sample preciousness, data isogenesis, and analysis efficiency, directly analyzing trace elements in this 10 mg XRF fusion glass is the preferred choice. However, a sample-flux dilution ratio of up to 35 times poses challenges in accurately determining the composition of low-content elements; therefore, to the best of our knowledge, no related research has been reported.

In addition, due to the high transmittance of flux fusion glass, very high energy density (usually >10 J cm⁻²) is required for effective ablation when using nanosecond (ns) lasers.²⁴ Besides, the significant thermal effect of ns lasers can cause obvious elemental fractionation and matrix effects, which will directly affect the precision and accuracy of the analysis results when a matrix-matched reference material is unavailable.³⁸ In contrast to ns lasers, the significantly higher pulse power density and shorter pulse duration of femtosecond (fs) lasers result in excellent ablation performance and minimal interactions with matter.³⁹ Therefore, a fs laser is more capable for analysing transparent flux fusion glass and gives higher quality analysis results. But so far, no research work has been conducted on the elemental analysis of flux fusion glass using fs laser.

In this study, we employed a high-repetition-rate GenesisGEO fs laser to analyze lithium borate glasses with a high dilution ratio for the first time. In addition, we used μ-XRF and fs-LA-ICP-MS to test the homogeneity of trace elements in the sample glasses. Meanwhile, different internal standard elements (Si, Ca, and Al) and external standards (NIST SRM 612 and 614 as non-matrix-matched and self-made BHVO-2 lithium borate glass as matrix-matched) were systematically optimized to obtain accurate analysis results. Subsequently, a diverse range of geological reference materials (GRMs), including basalt (JB-1b and GSR-3), andesite (AGV-2), granite (AC-E and GSR-1), and diabase (W-2A), were analyzed to test the reliability of the proposed method. Finally, two extraterrestrial samples were analyzed to confirm the practicality of this method.

2. Experimental

2.1 Reagents, GRMs and natural meteorite samples

Ultrapure Li₂B₄O₇ flux (≥99.99%, Claisse, Quebec, Canada) was used to prepare sample glasses. Ammonium bromide (NH₄Br) (≥99.0%, ACS reagent) was purchased from Sinopharm Chemical Reagent Co. Ltd (Shanghai, China) and used as a releasing agent. A USGS basalt reference material, BHVO-2, was used to prepare the matrix-matched external standard. Six other reference materials, including one diabase (USGS W-2A), two basalts (GSJ JB-1b and NRCG GSR-3), one andesite (USGS AGV-2), and two granites (CRPG AC-E and NRCG GSR-1), covering mafic to felsic rock types, were analyzed to evaluate the performance of the proposed method. Besides, one shergottite sample (NWA13190)⁴⁰ and one lunar basalt sample (NWA14526),⁴¹ which were respectively found in northwest Africa in 2019 and 2021, were analyzed using both the proposed method and the conventional solution ICP-MS method for comparison.

2.2 Instruments

Trace element analyses of the sample fusion glasses were performed using a high-repetition-rate GenesisGEO femtosecond laser coupled to an Agilent 8900 ICP-MS instrument. Ablation was performed using 100 μm-diameter ablating spots at 1 Hz for 45 s after measuring a gas blank for 25 s. A 25 s washout between analyses was used. The gas flows were optimized via spot ablation of NIST SRM 612 to obtain maximum signal intensities while maintaining ThO/Th at <0.3% and U/Th at 0.95–1.05. The details of the operating conditions and measurement parameters for the instruments are listed in Table 1. The relevant information of the femtosecond laser system is listed in Table S1.† Data reduction was obtained using the Iolite4 program.^42,43

Table 1 Typical operating conditions of the ICP-MS and laser ablation systems

ICP-MS (Agilent 8900)
RF power	1550 W
Plasma gas flow	15 L min^−1
Auxiliary gas flow	0.85 L min^−1
Sampling depth	8 mm
Dwell time per isotope	30 ms/10 ms
Detector mode	Dual

---

Laser ablation system (GenesisGEO)
Laser type	High-repetition-rate femtosecond laser
Wavelength	343 nm
Energy density	6.79 J cm^−2
Ablation spot size	100 × 100 μm
Repetition rate	1 Hz
Ablation mode	Single spot
Chamber gas	0.7 L per min He
Cup gas	0.1 L per min He

---

2.3 Sample preparation procedure

After drying, Li₂B₄O₇ flux (350.0 ± 0.3 mg) and a powdered sample (10.00 ± 0.03 mg) were sequentially weighed directly into a specialized small Pt–Au crucible. The flux and sample were mixed gently using a fine glass rod, and 13.3 μL of an ammonium bromide (NH₄Br) aqueous solution (0.36 g mL⁻¹) was added as a releasing agent. Finally, a mini glass disk was prepared using an M4 automatic fluxer (Claisse Fluxy, Corporation Scientifique Claisse, Quebec City, Canada).³⁷ Subsequently, the glass disk was initially measured for major elements by WD-XRF (Malvern PANalytical, Almelo, Netherlands) and subsequently analyzed for trace elements by fs-LA-ICP-MS after cleaning the surface with ethanol.

3. Results and discussion

3.1 Homogeneity of sample fusion glasses

The homogeneity of the sample glass is critical for bulk analysis using LA-ICP-MS. The homogeneity of the elemental distribution in the GRM granite GSR-1 was imaged via a Bruker M4 Tornado plus micro-X-ray fluorescence spectrometer (μ-XRF) to evaluate the quality of the sample glasses.⁴⁴ This sample was selected because its high silica content (72.83%) results in a high sample viscosity, making it difficult for elements to be uniformly distributed. Fig. 1 illustrates the elemental analysis results for Sr and Rb in GSR-1. Notably, both elements are homogeneously distributed in the glass.

Fig. 1 μ-XRF mapping analysis for the trace elements in a borate fusion glass of the GRM granite GSR-1. (a) The sample glass picture during analysis on the μ-XRF sample stage; (b) Sr and Rb mapping results.

Additionally, the homogeneity of the trace elements in GSR-1 (granite), GSR-2 (andesite), and GSR-3 (basalt) was investigated again using fs-LA-ICP-MS measurements. Nine spot analyses (spot size = 100 μm) were arranged in a grid pattern to cover the entire glass (Fig. 2). In this study, we used the homogeneity index (H) to assess the homogeneity of trace elements. H represents the ratio of the expected value of the total combined uncertainty (s_c) to the measurement uncertainty (s_rms):^45,46

s_rms is the root mean square (rms) of the statistically estimated uncertainties s_meas,i individually obtained for each of N measurements. The H value can be considered a particular case of an F-test when the degree of freedom of each population approaches infinity. A value of 1 for the index implies that the sample is homogeneous within the analytical uncertainty of individual measurements. However, the degree of heterogeneity that can be reliably detected depends on the measurement precision and on the number of measurements. The homogeneity of 32 trace elements was examined using the H index (Fig. 2). Not surprisingly, the H values of Co, Ni, and Cu in GSR-1 with concentrations close to the detection limits (Table S2†) are higher than the critical H value (H_crit). The other H indices in the three samples are all lower than H_crit, indicating significant homogeneity.

Fig. 2 Homogeneity index (H) of 32 trace elements in granite GSR-1, andesite GSR-2, and basalt GSR-3 glasses. The illustrations show the layout of nine ablation spots and the fs laser ablation pits, respectively. Except for the high H value of Co, Ni, and Cu in GSR-1 caused by the low measurement precision of low concentrations, the other H values in the three samples are all lower than H_crit, indicating significant homogeneity. H_crit represents the critical homogeneity index. H_crit = 1.39 is plotted, according to the number of measurements (N = 9) and the significance level (α = 0.05).

3.2 Limits of detection (LODs), limits of quantification (LOQs) and flux blanks

The limit of detection (LOD) is calculated according to the approach of Pettke,⁴⁷ and the limit of quantification (LOQ) is calculated as 3.3 times the LOD. The LODs of 32 elements calculated for lithium borate glass BHVO-2 are listed in Table S2† (0.005–23.5 μg g⁻¹). The LODs calculated for NIST 610 are also given (0.007–0.45 μg g⁻¹) and are comparable to those obtained in a recent study of trace element determination in silicate rock fused with lithium metaborate by LA-ICP-MS (0.005–0.73 μg g⁻¹).²⁷ Compared to the LODs calculated for NIST 610, those for BHVO-2 are much higher, which is precisely due to the low signal-to-noise ratio caused by sample dilution up to 35 times.

Two procedure blanks were prepared by melting 350 mg of Li₂B₄O₇ with 10 mg of Al₂O₃ (99.99%, Sigma-Aldrich) to evaluate the effect of impurities in Li₂B₄O₇ flux on the accuracy of analytical results. The results of the procedure blanks are listed in Table S2.† Clearly, the flux contains a small amount of V, Co, Zn, Ba, La, Ce, Ta, and U. Other elements are all lower than the LODs and make little contribution to the corresponding elements in the analyzed silicate rock GRMs. Therefore, the contribution of the total procedure blanks to the LOQ of pollution elements was considered and finally the LOQ was calculated as blank value + 10SD according to the Gold Book of IUPAC.⁴⁸ All results of the eight pollution elements above have deducted the flux blank contributions.

3.3 Effect of internal standard elements

A calibration method using an appropriate internal standard and a NIST reference glass (SRM 610–617) as an external calibrator is typically used to analyze various trace elements in silicate samples.^49,50 Considering the high content of major elements, Si, Ca, Mg, and Al are commonly used as internal standards.^24,51–53 However, using different elements as internal standards for the same unknown element in the same sample may result in different analysis results, which affects their accuracy.⁵¹ Only when the change in behavior (or fractionation effect) of the internal standard element and the targeted element during the ablation process is consistent can the content of the targeted element be accurately determined. In addition, the absolute degree to which fractionation occurs during ablation is highly dependent on numerous factors, including laser operation and the sample matrix.⁵⁴ Considering the special sample matrix of borate glass, we compared the effects of three internal standard elements (Si, Ca, and Al) on the analysis results of the basalt GRM GSR-3 using NIST 614 and 612 as external standards.

As illustrated in Fig. 3, the deviation trend between the contents of the 32 trace elements obtained from the three internal standard elements and the recommended values was consistent. However, compared with Ca and Si, the results for Al for most elements were more consistent with the recommended values, except for Co, Ni, Cu, and Zn. Compared to Ca and Al, Si is more suitable for Co, Ni, Cu, and Zn. Based on these results, Si was used as the internal standard element for the calculation of Co, Ni, Cu, and Zn, and Al was used for the others in this study. These results are consistent with the element fractionation index reported in a previous study,⁵⁴ that is, compared to Ca and Al, the fractionation index of Si is closer to that of Co, Ni, Cu, and Zn.

Fig. 3 Effect of different internal standards on the analytical accuracy [relative deviation (RD)] of the basalt GRM GSR-3. The red circles represent the results calculated using Al as the internal standard. The dark gray and the light blue circles represent the results calculated using Ca and Si as internal standards, respectively.

3.4 Effect of external standards (matrix-matched and non-matrix-matched)

The chosen calibration system is important in instrumental chemical analysis because analytical accuracy is directly related to calibration. The instrument response is, in most cases, dependent on both the chemical and physical nature of the sample material; therefore, samples and calibration standards must be closely matched both chemically and physically. This basic problem is particularly prominent in the analysis of complex materials, such as rocks and minerals.⁵⁵

Considering the significant matrix differences between the sample borate glass and the NIST reference glass, borate glass made from the BHVO-2 sample powder was used as a matrix-matched external standard. The results of the basalt GRM GSR-3 calculated using the matrix-matched external standard BHVO-2 and non-matrix-matched external standard 612 were compared (Fig. 4). Evidently, the results obtained from the matrix-matched external standard BHVO-2 were not as good as expected but were poorer than those obtained from the non-matrix-matched external standard 612.

Fig. 4 Effect of matrix-matched and non-matrix-matched external standards on the analytical accuracy of the basalt GRM GSR-3. The dark red circles represent the results calculated using non-matrix-matched NIST 612 and 614 as external standards. The light red circles represent the results calculated using only non-matrix-matched NIST 612 as an external standard. The white quadrangles represent the results calculated using matrix-matched BHVO-2 as an external standard.

In response to this result, matrix-related problems here may have been overcome by the borate fusion technique, a process wherein a crystalline, heterogeneous rock is transformed into an amorphous homogeneous glass (solid solution) in the flux matrix.⁵⁵ Even if there are certain matrix-related issues, fs lasers are considered stoichiometric erosion processes without any element or isotope fractionation effects. This is because they are absorbed and thermally diffused to a shallow depth by the sample, with almost all laser energy acting on the surface of the sample and the resulting aerosol particles being fine and concentrated.⁵⁶ In comparison, for ns lasers, if calibration is not performed using a matrix-matched external standard, the discrepancies can be up to 25% relative to accepted values even employing a lower sample flux dilution ratio of 1 : 3 or 1 : 5.^57,58 Therefore, the calibration of matrix-matched and non-matrix-matched external standards should achieve similar results here. However, owing to a dilution ratio of up to 35 times, the low concentration of elements in the matrix-matched external standard BHVO-2 resulted in unsatisfactory calibration results. Meanwhile, the analysis results obtained using NIST 612 and 614 as external standards were slightly better compared to those obtained using only NIST 612 as a single external standard (Fig. 4). Therefore, non-matrix-matched external standards, NIST 612 and 614, were used in the subsequent experiments.

3.5 Analytical results of six GRMs

Six silicate rock GRMs, namely AC-E, GSR-1, JB-1b, GSR-3, AGV-2, and W-2A, were analyzed to further evaluate the reliability of the developed method. Fig. 5 shows the analytical results for the six silicate rock GRMs. The measured values in AC-E, GSR-1, JB-1b, GSR-3, AGV-2, and W-2A were consistent with the reference values (from the GeoReM database: https://georem.mpch-mainz.gwdg.de) within 10% for most trace elements, with precisions of better than 10% RSDs for most elements, confirming the reliability of the proposed method for fs-LA-ICP-MS analysis of trace elements in flux fusion silicate rocks.

Fig. 5 (a) Analytical accuracy [relative deviation (RD)] and (b) analytical precision [relative standard deviation (RSD)] for the AC-E, GSR-1, JB-1b, GSR-3, AGV-2, and W-2A borate glasses.

Larger discrepancies (>15%) from the reference values were observed for Co in AGV-2, JB-1b, and W-2A; Ni in JB-1b; Cu in AGV-2 and JB-1b; Zn in GSR-1; and Hf in GSR-1. Besides, Zn in GSR-1; Tm, Yb, and Lu in GSR-3; Lu in AGV-2; and Ta and U in W-2A exhibited relatively higher RSDs.

The overestimation of Co, Ni, Cu, and Zn may be attributed to the contamination from the preparation procedure of the flux fusion glasses. The procedure may need to be stricter when fusion glass is used for trace element analysis. Evidently, when the element content in the sample was very low, this effect was more severe. Another study also noted this phenomenon and attributed these significant differences to the contamination of elements during glass preparation.^24,32

The observed larger RSDs of Zn, Tm, Lu, Ta and U may be attributed to their low mass fractions (reference values, Zn: 28 μg g⁻¹ for GSR-1, the LOQ of which is 26 μg g⁻¹; Tm: 0.28 μg g⁻¹ for GSR-3; Lu: 0.19 μg g⁻¹ for GSR-3; 0.25 μg g⁻¹ for AGV-2; Ta: 0.5 μg g⁻¹ for W-2A; U: 0.5 μg g⁻¹ for W-2A). These results confirm that the proposed method is reliable and suitable for analyzing trace elements in silicate rocks.

3.6 Application to lunar basalt and shergottite samples

One shergottite sample, NWA13190, and one lunar basalt sample, NWA14526, were analyzed using the proposed fs-LA-ICP-MS and SN-ICP-MS methods. To maintain consistency, 10 mg samples were also used for SN-ICP-MS analysis.¹⁰ The analysis results for most elements obtained by these two methods were consistent within a 10% error range (Table 2), which is also the analytical accuracy that the general SN-ICP-MS method can achieve.^5,9 Moreover, we used a smaller sample size of 10 mg, further validating the reliability, operability, and applicability of the proposed fs-LA-ICP-MS method.

Table 2 Trace element composition of shergottite NWA13190 and lunar basalt NWA14526, as measured by fs-LA-ICP-MS and SN-ICP-MS^a

Element	NWA13190 (shergottite)				NWA14526 (lunar basalt)
	fs-LA-ICP-MS (n = 9 spots)		SN-ICP-MS (n = 5)		fs-LA-ICP-MS (n = 9 spots)		SN-ICP-MS (n = 5)
	Mean	±95% CI	Mean	±95% CI	Mean	±95% CI	Mean	±95% CI
a “—” indicates that the concentration is lower than the LOQ; “95% CI” indicates the 95% confidence interval.
Sc	67.3	2.5	64.3	3.2	53.3	2.8	52.2	2.9
V	337	12	333	12	155	5	155	9
Cr	1084	20	1141	22	3569	91	3642	133
Co	37.2	3.0	36.2	0.1	51.2	5.4	50.1	0.9
Ni	63.8	10.0	59.8	2.1	74.0	9.5	74.7	3.2
Cu	—	—	11.9	0.9	—	—	7.46	0.42
Zn	82.4	9.0	80.5	2.1	—	—	6.45	1.42
Ga	19.6	1.7	16.0	0.7	4.32	0.61	4.84	0.39
Rb	6.58	1.12	6.08	0.25	0.961	0.093	0.865	0.038
Sr	85.0	6.2	84.3	4.0	183	12	207	9
Y	26.3	1.2	24.6	1.0	36.9	1.8	36.9	1.1
Zr	78.7	2.2	81.6	3.5	106	4	116	9
Nb	4.76	0.44	4.48	0.14	6.42	0.44	6.17	0.30
Ba	93.0	8.5	91.1	1.2	196	12	206	7
La	3.22	0.13	3.25	0.11	7.08	0.31	6.76	0.36
Ce	7.53	0.32	7.89	0.29	17.9	0.8	17.8	1.1
Pr	1.10	0.08	1.16	0.04	2.41	0.13	2.60	0.16
Nd	5.43	0.41	5.78	0.22	12.0	0.8	12.5	0.7
Sm	2.16	0.15	2.30	0.07	4.09	0.34	4.20	0.24
Eu	0.827	0.064	0.857	0.016	0.898	0.051	0.917	0.011
Gd	3.34	0.12	3.51	0.10	5.47	0.15	5.21	0.26
Tb	0.658	0.052	0.677	0.022	0.943	0.041	0.986	0.048
Dy	4.43	0.21	4.48	0.17	6.26	0.42	6.52	0.31
Ho	0.944	0.020	0.925	0.027	1.38	0.05	1.36	0.05
Er	2.54	0.07	2.67	0.06	3.99	0.25	3.97	0.17
Tm	0.354	0.030	0.373	0.011	0.561	0.049	0.558	0.017
Yb	2.24	0.17	2.26	0.09	3.53	0.21	3.56	0.10
Lu	0.311	0.028	0.344	0.009	0.533	0.051	0.534	0.011
Hf	2.31	0.19	2.20	0.03	2.62	0.24	2.59	0.14
Ta	0.250	0.004	0.255	0.012	0.374	0.011	0.392	0.011
Th	0.509	0.060	0.480	0.004	1.02	0.09	1.07	0.01
U	0.096	0.022	0.116	0.002	0.376	0.018	0.385	0.007

---

4. Conclusions

A novel fs-LA-ICP-MS method for determining 32 trace elements in a 1 : 35 highly diluted borate-fused glass with a sample consumption of 10 mg was developed to meet the scientific research needs for extraterrestrial geological samples. The homogeneity of the elemental distribution in the borate glass and the internal and external standards was systematically studied. The proposed method had three main advantages: (1) directly analyzing the borate fusion glass prepared by XRF omits the sample pre-treatment process for bulk analysis by LA-ICP-MS, greatly simplifying the analysis process, improving the analysis efficiency, and reducing the sample consumption amount; (2) the influence of matrix-related problems was reduced by the excellent performance of the femtosecond laser, which guaranteed the high quality of analytical data; (3) although the mass ratio of the sample powder and flux is as high as 1 : 35, the analytical results of 32 trace elements in six silicate rock reference materials are consistent with the reference values within 10% for most elements, and the analytical precision (RSD) is also within 10% for most elements. One lunar basalt (NWA14526) and one shergottite (NWA13190) sample validated the accuracy and precision of the method.

The proposed method is simple, fast, and accurate and has low sample consumption, making it a promising conventional scheme for the bulk element analysis of extraterrestrial geological samples.

Data availability

The authors confirm that the data supporting the findings of this study are available within the article (and/or its ESI†).

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

This work was financially supported by the Strategy Priority Research Program (Category B) of the Chinese Academy of Sciences (XDB0710000) and the National Natural Science Foundation of China (42073022).

References

1. C. Li, H. Hu, M. F. Yang, Z. Y. Pei, Q. Zhou, X. Ren, B. Liu, D. Liu, X. Zeng, G. Zhang, H. Zhang, J. Liu, Q. Wang, X. Deng, C. Xiao, Y. Yao, D. Xue, W. Zuo, Y. Su, W. Wen and Z. Ouyang, Natl. Sci. Rev., 2022, 9, nwab188.
2. P. H. Warren, E. A. Jerde and G. W. Kallemeyn, Earth Planet. Sci. Lett., 1989, 91, 245–260.
3. M. Ebihara, S. Sekimoto, N. Shirai, Y. Hamajima, M. Yamamoto, K. Kumagai and Y. Oura, Abstracts of Annual Meeting of the Geochemical Society of Japan, 2011, p. 170.
4. Y. Yao, C. Xiao, P. Wang, C. Li and Q. Zhou, J. Am. Chem. Soc., 2022, 144, 5478–5484.
5. K. Zong, Z. Wang, J. Li, Q. He, Y. Li, H. Becker, W. Zhang, Z. Hu, T. He, K. Cao, Z. She, X. Wu, L. Xiao and Y. Liu, Geochim. Cosmochim. Acta, 2022, 335, 284–296.
6. Z. Wang, K. Zong, Y. Li, J. Li, Q. He, Z. Zou, H. Becker, F. Moynier, J. M. D. Day, W. Zhang, Y. Qian, L. Xiao, Z. Hu, Z. She, H. Hui, X. Wu and Y. Liu, Geochim. Cosmochim. Acta, 2024, 373, 17–34.
7. M. D. Norman, W. P. Leeman, D. P. Blanchard, J. G. Fitton and D. James, Geostand. Newsl., 1989, 13, 283–290.
8. A. J. B. Cotta and J. Enzweiler, Geostand. Geoanal. Res., 2012, 36, 27–50.
9. M. Rospabé, M. Benoit and F. Candaudap, Geostand. Geoanal. Res., 2018, 42, 115–129.
10. Y.-H. Liu, S. Guo, W.-J. Li, D.-S. Xue, C.-F. Li and B. Wan, Anal. Chem., 2024, 96, 6523–6527.
11. W. Zhang, Z. C. Hu, Y. S. Liu, H. H. Chen, S. Gao and R. M. Gaschnig, Anal. Chem., 2012, 84, 10686–10693.
12. O. Okina, S. Lyapunov, M. Avdosyeva, B. Ermolaev, V. Golubchikov, A. Gorbunov and V. Sheshukov, Geostand. Geoanal. Res., 2016, 40, 583–597.
13. Y. Liu, Z. Hu, M. Li and S. Gao, Chin. Sci. Bull., 2013, 58, 3863–3878.
14. S. Y. Zhang, H. L. Zhang, Z. Hou, D. A. Ionov and F. Huang, Geostand. Geoanal. Res., 2019, 43, 93–111.
15. I. V. Vikentiev, V. D. Abramova, Y. N. Ivanova, E. E. Tyukova, E. V. Kovalchuk and N. S. Bortnikov, Dokl. Earth Sci., 2016, 470, 976–980.
16. D. Peters and T. Pettke, Geostand. Geoanal. Res., 2017, 41, 5–28.
17. S. Wu, V. Karius, B. C. Schmidt, K. Simon and G. Wörner, Geostand. Geoanal. Res., 2018, 42, 575–591.
18. C. G. C. Patten, A. Beranoaguirre, S. Hector, D. Gudelius, J. Kolb and E. Eiche, Int. J. Mass Spectrom., 2023, 488, 117039.
19. B. Stoll, K. P. Jochum, K. Herwig, M. Amini, M. Flanz, B. Kreuzburg, D. Kuzmin, M. Willbold and J. Enzweiler, Geostand. Geoanal. Res., 2008, 32, 5–26.
20. C. Zhang, Z. Hu, W. Zhang, Y. Liu, K. Zong, M. Li, H. Chen and S. Hu, Anal. Chem., 2016, 88, 10088–10094.
21. L. Zhu, Y. Liu, Z. Hu, Q. Hu, X. Tong, K. Zong, H. Chen and S. Gao, Geostand. Geoanal. Res., 2013, 37, 207–229.
22. Z. He, F. Huang, H. Yu, Y. Xiao, F. Wang, Q. Li, Y. Xia and X. Zhang, Geostand. Geoanal. Res., 2016, 40, 5–21.
23. M. Kurosawa, K. Shima, S. Ishii and K. Sasa, Geostand. Geoanal. Res., 2006, 30, 17–30.
24. S. M. Eggins, Geostand. Newsl., 2003, 27, 147–162.
25. D. Gunther, A. von Quadt, R. Wirz, H. Cousin and V. J. Dietrich, Mikrochim. Acta, 2001, 136, 101–107.
26. J. E. Reid, I. Horn, H. P. Longerich, L. Forsythe and G. A. Jenner, Geostand. Newsl., 1999, 23, 149–155.
27. X. Qiu, Z. Hu, T. He, T. Luo, W. Zhang, M. Li, K. Zong, Z. Wang and Y. Liu, J. Anal. At. Spectrom., 2024, 39, 545–557.
28. F. Claisse, Que. (Prov.), Dep. Mines, Prelim. Rep., 1957, 327, 3.
29. K. Norrish and J. T. Hutton, Geochim. Cosmochim. Acta, 1969, 33, 431–453.
30. F. P. Leitzke, A. C. Wegner, C. C. Porcher, N. I. M. Vieira, J. Berndt, S. Klemme and R. V. Conceição, Braz. J. Geol., 2021, 51, e20200057.
31. C.-S. Park, H. S. Shin, H. Oh, H. Cho and A. C.-s. Cheong, J. Anal. Sci. Technol., 2016, 7, 15.
32. J. Malherbe, F. Claverie, A. Alvarez, B. Fernandez, R. Pereiro and J. L. Molloy, Anal. Chim. Acta, 2013, 793, 72–78.
33. M. Petrelli, D. Perugini, G. Poli and A. Peccerillo, Microchim. Acta, 2007, 158, 275–282.
34. T. D. F. Leite, R. Escalfoni, T. C. O. da Fonseca and N. Miekeley, Spectrochim. Acta, Part B, 2011, 66, 314–320.
35. D.-S. Xue, B.-X. Su, D.-P. Zhang, Y.-H. Liu, J.-J. Guo, Q. Guo, J.-F. Sun and S.-Y. Zhang, J. Anal. At. Spectrom., 2020, 35, 2826–2833.
36. F.-Y. Wu, Q.-L. Li, Y. Chen, S. Hu, Z.-Y. Yue, Q. Zhou, H. Wang, W. Yang, H.-C. Tian, C. Zhang, J.-H. Li, L.-X. Li, H.-J. Hui, C.-L. Li, Y.-T. Lin, X.-H. Li and J. W. Delano, Annu. Rev. Earth Planet. Sci., 2024, 52, 159–194.
37. D.-S. Xue, H.-C. Tian, D.-P. Zhang, Y.-H. Liu, J.-F. Sun, S.-T. Wu, S.-K. Liu, S. Guo and B. Wan, Spectrochim. Acta, Part B, 2022, 193, 106433.
38. B. Fernández, F. Claverie, C. Pécheyran, O. F. X. Donard and F. Claverie, TrAC, Trends Anal. Chem., 2007, 26, 951–966.
39. S. Zhang, M. He, Z. Yin, E. Zhu, W. Hang and B. Huang, J. Anal. At. Spectrom., 2016, 31, 358–382.
40. J. Gattacceca, F. M. McCubbin, J. Grossman, A. Bouvier, E. Bullock, H. Chennaoui Aoudjehane, V. Debaille, M. D'Orazio, M. Komatsu, B. Miao and D. L. Schrader, Meteorit. Planet. Sci., 2021, 56, 1626–1630.
41. J. Gattacceca, F. M. McCubbin, J. Grossman, A. Bouvier, N. L. Chabot, M. D'Orazio, C. Goodrich, A. Greshake, J. Gross, M. Komatsu, B. Miao and D. Schrader, Meteorit. Planet. Sci., 2022, 57, 2102–2105.
42. C. Paton, J. Hellstrom, B. Paul, J. Woodhead and J. Hergt, J. Anal. At. Spectrom., 2011, 26, 2508–2518.
43. B. Paul, J. Petrus, D. Savard, J. Woodhead, J. Hergt, A. Greig, C. Paton and P. Rayner, J. Anal. At. Spectrom., 2023, 38, 1995–2006.
44. J.-H. Li, Q.-L. Li, L. Zhao, J.-H. Zhang, X. Tang, L.-X. Gu, Q. Guo, H.-X. Ma, Q. Zhou, Y. Liu, P.-Y. Liu, H. Qiu, G. Li, L. Gu, S. Guo, C.-L. Li, X.-H. Li, F.-Y. Wu and Y.-X. Pan, Geosci. Front., 2022, 13, 101367.
45. D. Harries, Geochemistry, 2014, 74, 375–384.
46. V. G. Batanova, J. M. Thompson, L. V. Danyushevsky, M. V. Portnyagin, D. Garbe-Schönberg, E. Hauri, J. I. Kimura, Q. Chang, R. Senda, K. Goemann, C. Chauvel, S. Campillo, D. A. Ionov and A. V. Sobolev, Geostand. Geoanal. Res., 2019, 43, 453–473.
47. T. Pettke, F. Oberli, A. Audétat, M. Guillong, A. C. Simon, J. J. Hanley and L. M. Klemm, Ore Geol. Rev., 2012, 44, 10–38.
48. M. Nic Ghiolla Phádraig, J. Jirat, B. Košata, S. A. Jenkins and A. D. Mcnaught, Encyclopedic Dictionary of Polymers, 2006, p. 839.
49. S. E. Jackson, H. P. Longerich, G. R. Dunning and B. J. Fryer, Can. Mineral., 1992, 30, 1049–1064.
50. H. P. Longerich, D. Günther and S. E. Jackson, Anal. Bioanal. Chem., 1996, 355, 538–542.
51. Y. Liu, Z. Hu, S. Gao, D. Günther and J. Xu, Chem. Geol., 2008, 257, 34–43.
52. S. Wu, A. Audétat, K. P. Jochum, H. Wang, J. Chen, B. Stoll, C. Zhang, Z. Bao, S. Yang, C. Li, X. Wang, C. Xu, L. Xu, C. Huang, L. Xie, Y. Yang and J. Yang, Geostand. Geoanal. Res., 2022, 46, 673–700.
53. S. Peng and Q. Hu, Am. J. Anal. Chem., 2012, 03, 168–174.
54. S. E. Jackson and P. Sylvester, Signal, 2008, 10, 100.
55. M. Ødegård and M. Hamester, Geostand. Newsl., 2007, 21, 245–252.
56. B. Fernandez, F. Claverie, C. Pécheyran and O. F. X. Donard, TrAC, Trends Anal. Chem., 2007, 26, 951–966.
57. Z. Yu, M. D. Norman and P. Robinson, Geostand. Newsl., 2007, 27, 67–89.
58. J. S. Becker and H. J. Dietze, Fresenius. J. Anal. Chem., 1999, 365, 429–434.

---

Footnote

† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4ja00275j

---