A Dual-Element Stoichiometric-Consistency Workflow Using Simultaneous Al and K Measurement for Reliable Alum Assay and Adulteration Screening

A Dual-Element Stoichiometric-Consistency Workflow Using Simultaneous Al and K Measurement for Reliable Alum Assay and Adulteration Screening | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Dual-Element Stoichiometric-Consistency Workflow Using Simultaneous Al and K Measurement for Reliable Alum Assay and Adulteration Screening Zhiji Chen, Li Wang, Micong C. Jin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8850541/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background The zinc chloride back-titration procedure in GB 1886.229–2016 converts total aluminum to alum content (reported as anhydrous AlK(SO 4 ) 2 on a dry basis) without measuring potassium, but it does not measure potassium and therefore lacks an internal Al–K stoichiometric check and potentially missing adulteration-related inconsistencies (e.g., substitution with sodium/ferric alum or addition of potassium salts). Methods Al and K were simultaneously quantified by ICP-MS. Alum content was independently calculated from Al and from K (as anhydrous AlK(SO 4 ) 2 , dry basis), and their agreement was assessed by both the K/Al molar ratio and a relative deviation metric (Δ = |C K - C Al | / ((C K + C Al )/2) × 100%). Decision rules were pre-defined (R = K/Al molar ratio; Δ agreement metric) to classify stoichiometrically consistent vs. K-deficient or Al-deficient patterns and to select the appropriate conversion channel. Results The workflow showed good linearity (r > 0.9997), good precision (RSD < 8%), and satisfactory spike recoveries (99.6–107.8%). It enabled rapid screening and corrected quantification in typical adulteration scenarios, whereas the Al-only conversion in the national standard could substantially overestimate alum content under Al-rich substitution. Market samples and simulated adulteration mixtures were used to demonstrate screening sensitivity and quantification correction compared with GB 1886.229–2016. Conclusions By operationalizing Al-K dual-element stoichiometric screening (K/Al and Δ-based agreement) and applying correction-based quantification for abnormal samples, this practical workflow addresses the analytical blind spot of Al-only conversion and provides a robust solution for routine quality control and regulatory surveillance of food additive alum. alum inductively coupled plasma–mass spectrometry (ICP-MS) simultaneous determination of aluminum and potassium authenticity/purity assessment back titration Introduction Potassium aluminum sulfate (alum, AlK(SO4) 2 ·12H 2 O) is a traditional food additive that is widely used in fried products, jellyfish processing, and starch-based noodles, where it functions primarily as a leavening agent, coagulant/firming agent, and water clarifier. Because alum contains aluminum (Al), excessive intake may pose potential risks to human health, including effects on the nervous system (Liu 2023; Wang 2021). Accordingly, many countries have established strict regulations on its permitted uses and maximum levels in foods. In China, the National Food Safety Standard for the Use of Food Additives (GB 2760–2024) specifies maximum use levels of alum for different food categories. Therefore, accurate determination of both the content and purity of alum used as a food additive is essential for ensuring food safety, standardizing industrial practice, and protecting consumer health. In China, the National Food Safety Standard for Food Additive—Potassium Aluminum Sulfate (Alum) (GB 1886.229–2016) specifies a zinc chloride back-titration method for alum assay. In this procedure, aluminum content is determined and then converted to alum content according to the stoichiometry of alum (AlK(SO 4 ) 2 ·12H 2 O). However, this approach has a fundamental conceptual limitation: it implicitly assumes that all aluminum present originates from pure alum, and it provides no independent check of the accompanying potassium required by alum stoichiometry. In real manufacturing and distribution chains, cheaper aluminum alums such as sodium aluminum sulfate (sodium alum) and ferric aluminum sulfate (ferric alum) may be used fraudulently to partially replace alum. Under such circumstances, the back-titration method cannot differentiate the source of aluminum and will incorrectly convert total aluminum to alum, resulting in inflated assay values that do not reflect the true amount of potassium alum added. This creates a regulatory blind spot and may increase food safety risks. A robust solution requires simultaneous determination of the characteristic cations K and Al and explicit use of their stoichiometric relationship. The K/Al molar ratio can be used for verify whether a sample matches the theoretical ratio of pure alum (approximately 1:1), thereby enabling authenticity and purity assessment and facilitating the detection of admixture with other alums. Moreover, because potassium is the unique characteristic cation of potassium alum, K-based quantification provides a direct route to estimating the true alum content in the presence of Al-rich substitutes. we developed an inductively coupled plasma–mass spectrometry (ICP-MS) method (Huang 2018; He 2017) for the simultaneous determination of Al and K, and evaluated its performance through systematic method validation and real-sample testing. On this basis, we further established an implementation-ready workflow that couples K/Al ratio screening with conversion correction to support both discrimination (purity/authenticity) and quantification (true alum content) under non-ideal, adulterated conditions. Compared with conventional single-element conversion, the key contributions are: ( 1 ) translating Al–K stoichiometric constraints into two computable QC metrics (R = K/Al molar ratio and Δ, the relative deviation between Al-derived and K-derived alum contents) that enable intrinsic authenticity/purity assessment; ( 2 ) providing an implementation-ready decision workflow (“screen → select conversion channel → interpret”) that yields a corrected alum content estimate under typical adulteration patterns; and ( 3 ) validating the criteria and applicability boundaries using simulated adulteration scenarios (Al-rich substitution and K-salt addition) and commercial samples, with direct comparison to the Al-only conversion embedded in GB 1886.229–2016. 1. Materials and Methods 1.1. Instruments and Reagents A NexION 300D inductively coupled plasma–mass spectrometer (ICP-MS; PerkinElmer, USA) equipped with a high-salt-resistant sample introduction system was used. An analytical balance (readability: 0.1 mg) and a Milli-Q ultrapure water system (Millipore, USA) were employed. Aluminum standard solution (1000 mg/L) and potassium standard solution (1000 mg/L) were obtained from the National Center of Analysis and Testing for Nonferrous Metals and Electronic Materials (China). Zinc chloride standard solution (1.0002 mol/L) was purchased from Sichuan Pushiao Reference Materials Technology Co., Ltd. Disodium ethylenediaminetetraacetate (EDTA-2Na) standard solution (0.1017 mol/L) was supplied by Tanmo Quality Inspection Technology Co., Ltd. Argon gas (purity ≥ 99.999%) was used for the plasma. Potassium aluminum sulfate (alum), and potassium sulfate (analytical grade, purity > 99.5%) were purchased from Sinopharm Chemical Reagent Co., Ltd. Sodium aluminum sulfate (analytical grade, purity > 98%) was purchased from Shanghai Haohong Biomedical Technology Co., Ltd. Hydrochloric acid and nitric acid (Suprapur grade) were obtained from Merck. Internal standard solutions of Sc, Ge, and Rh (500 µg/L) were obtained from the National Center of Analysis and Testing for Nonferrous Metals and Electronic Materials (China). Ultrapure water (resistivity ≥ 18.2 MΩ·cm) produced by the Milli-Q system was used throughout. 1.2. Preparation of Solutions Appropriate aliquots of the 1000 mg/L Al and K stock standard solutions were accurately transferred and serially diluted with 1% (v/v) nitric acid to prepare a mixed Al–K working standard solution with final concentrations of 1.0 mg/L for both Al and K. All standards and samples were prepared in 1% (v/v) HNO₃ to match the matrix of the calibration solutions. 1.3. Calibration Curve A series of mixed calibration standards was prepared by serial dilution of Al and K standard solutions with 1% (v/v) nitric acid. The concentrations of both Al and K were 0, 0.2, 0.5, 1.0, 2.0, and 5.0 mg/L (0 corresponds to the reagent blank). Calibration curves were constructed by linear regression of signal intensity (cps) versus concentration (mg/L). The analyte-to-internal-standard signal ratio was used for calibration. 1.4. ICP-MS Operating Conditions Instrument parameters were optimized using a 1 µg/L tuning solution containing Be, Ce, Fe, In, Li, Mg, Pb, and U. The optimized operating conditions were as follows: RF power, 1300 W; nebulizer (carrier) gas flow, 0.99 L/min; auxiliary gas flow, 1.2 L/min; sampler and skimmer cones, platinum; peristaltic pump speed, 20.0 rpm; number of sweeps, 20; dwell time, 50 ms; acquisition mode, peak hopping; helium collision gas flow, 3 mL/min; RPq (low-mass cutoff), 0.25. The doubly charged ratio was controlled at Ce²⁺/Ce⁺ < 3.0%, and the oxide ratio at CeO⁺/Ce⁺ < 2.5%. Rh ( 103 Rh) was used as the internal standard and introduced online at 20 µg/L. Ge ( 72 Ge, 200 µg/L) and Sc ( 45 Sc, 100 µg/L) were evaluated only during internal-standard selection and were not used for final quantification. All reported concentrations were corrected using the analyte-to- 103 Rh signal ratio. 1.5. Sample Preparation Approximately 1.0 g of alum sample was accurately weighed (to 0.1 mg) into a suitable vessel. Ultrapure water (20 mL) and hydrochloric acid (20 mL; 1 + 1, v/v) were added, and the mixture was heated until complete dissolution, yielding a clear solution. After cooling to room temperature, the solution was diluted to 100.0 mL with 1% (v/v) nitric acid, followed by a 500-fold dilution to ensure that Al and K concentrations in the final test solution fell within the linear range of the ICP-MS calibration curves. For samples showing visible insoluble residue, the solution was filtered prior to volume make-up. 1.6. Calculation of Alum Content and Decision Logic In this study, “alum (potassium aluminum sulfate) content” was expressed on a dry basis as specified in Appendix A of GB 1886.229–2016, calculated as anhydrous potassium aluminum sulfate (AlK(SO 4 ) 2 ) as the measurement basis (relative molecular mass = 258.19). The corresponding theoretical mass fractions are w(Al) = 26.98/258.19 = 10.450% and w(K) = 39.10/258.19 = 15.144%. Unless otherwise stated, “content (%)” refers to mass fraction on a dry basis. 1.6.1. Calculation of the K/Al Molar Ratio The mass concentrations of Al and K (mg/L) in the test solution were determined and converted to mass fractions in the sample (mg/g). The K/Al molar ratio (R) was calculated as (R is used as the primary stoichiometric-screening indicator; theoretical R ≈ 1.00 for pure AlK(SO 4 ) 2 ): $$\:\text{R}\text{=}\frac{{\text{w}}_{\text{K}}/{\text{M}}_{\text{K}}}{{\text{w}}_{\text{Al}}/{\text{M}}_{\text{Al}}}$$ 1 Where w K and w Al are the mass fractions of K and Al in the sample (mg/g), respectively; M K =39.10 g/mol, M Al =26.98 g/mol. The mass fraction w (mg/g) was obtained from the measured concentration C (mg/L) using: $$\:\text{w}\text{=}\frac{\text{C}\text{×}\text{V}\text{×}\text{DF}}{\text{m}}$$ 2 where V is the final volume (L) after dissolution (0.100 L), DF is the subsequent dilution factor (500), and m is the sample mass (g). 1.6.2. Purity Assessment and Conversion Strategy Decision criteria and internal-consistency check. First compute the K/Al molar ratio R using Eq. ( 1 ). If 0.95 ≤ R ≤ 1.05, the sample is considered stoichiometrically consistent with potassium alum within analytical uncertainty. Then compute the relative deviation between the two independent alum content estimates: Δ = |C K −C Al | / ((C K +C Al )/2) × 100%, where C K is alum content converted from K and C Al is alum content converted from Al. A practical acceptance criterion is Δ ≤ 5% (to be confirmed/adjusted by each laboratory based on its precision and recovery). If Δ > 5%, re-prepare the sample and re-measure; if still > 5%, report both channels and flag the sample for further investigation. When R is within [0.95, 1.05], the sample is considered stoichiometrically consistent with potassium alum within analytical uncertainty; the interval should be set/confirmed by the laboratory using repeated measurements of qualified alum materials and error-propagation of Al and K determinations: K-based conversion: (alum, %) = w K ×258.19/(M K ×10) Al-based conversion: (alum, %) = w Al ×258.19/(M Al ×10) where w K and w Al are in mg/g; division by 10 converts mg/g to % (10 mg/g = 1%) When R < 0.95, an Al-rich/K-deficient pattern was indicated, consistent with partial substitution by other aluminum alums (e.g., sodium alum or ferric alum). In this case, the K-based converted value was taken as the estimate of true alum content. When R > 1.05, a K-rich/Al-deficient pattern was indicated, suggesting the presence of added potassium salts or other potassium sources (e.g., potassium sulfate). In this case, the Al-based converted value was taken as the estimate of true alum content. In addition, for samples within [0.95, 1.05], agreement between K-based and Al-based alum contents was evaluated as an internal consistency check; large discrepancies were flagged for repeat preparation and remeasurement. 1.6.3. Comparison with the National Standard Method Results obtained using the national standard (zinc chloride back-titration) were used as a reference comparator. This method inherently assumes that all measured aluminum originates from alum. Accordingly, it was expected to bias high when Al-rich substitutes were present. 1.7. Method Validation Method performance was evaluated in terms of linear range, limit of detection (LOD), limit of quantification (LOQ), precision, and spike recovery. All experiments were conducted in six replicates, and data are reported as mean ± standard deviation. LOD and LOQ were calculated based on the standard deviation of reagent blanks (σ) as LOD=3σ and LOQ=10σ, with the corresponding concentration converted to sample-level values using the same preparation and dilution scheme. 2. Results 2.1. Effects of ICP-MS Determination Conditions 2.1.1. Optimization of ICP-MS Instrument Parameters ICP-MS exhibits substantial differences in inherent sensitivity among elements, primarily due to their physicochemical properties (e.g., first ionization energy), ion transport efficiency in the plasma/interface, and detector response characteristics. Potassium (K) has a relatively low first ionization energy (419 kJ/mol), is readily ionized, and typically provides high ICP-MS sensitivity. In contrast, aluminum (Al) has a higher first ionization energy (577 kJ/mol), generally shows lower sensitivity, and is more susceptible to matrix effects and polyatomic interferences. When measured under identical instrumental conditions, K and Al signals may differ by several orders of magnitude. It is generally accepted that simultaneous determination of K and Al at comparable signal levels can minimize the impact of detector nonlinearity and short-term instrumental fluctuations on their signal ratio. This helps (i) maintain the linearity and fitting quality of calibration curves and (ii) improve ratio stability during sample analysis, because minor instrumental drift tends to affect both elements more uniformly when their signals are within a similar magnitude range. Detector attenuation (electronic dilution) was applied to equalize the signal magnitude of K and Al, thereby reducing the risk of detector nonlinearity and improving ratio stability, without changing the solution concentration. As shown in Table 1 , varying the K/Al signal intensity ratio had negligible impact on the calculated K/Al molar ratio, which remained within 1.01–1.02 and was consistent with the stoichiometric characteristics of potassium aluminum sulfate. Notably, the K/Al signal intensity ratio of 1.38 provided the best stability (lowest RSD). Therefore, to maximize method stability and accuracy, electronic dilution factors of 0.0150 for K and 0.0145 for Al were selected for subsequent sample measurements. Table 1 Effect of K/Al signal intensity ratio on the calculated K/Al molar ratio (n = 6) Electronic dilution factor K/Al signal intensity ratio K/Al molar ratio SD RSD(%) K Al 0.0150 0.0140 0.91 1.01 0.02 1.7 0.0145 1.38 1.01 0.01 1.0 0.0150 2.20 1.02 0.02 2.1 2.1.2. Optimization of the Internal Standard for ICP-MS Determination The use of an internal standard (IS) is a common strategy in ICP-MS to compensate for signal drift caused by variations in nebulization efficiency, plasma instability, changes in ion transmission, and matrix effects, thereby improving quantitative accuracy and inter-run comparability. Selection of a suitable IS generally follows these criteria: (i) negligible or very low background levels in the sample; (ii) chemical stability in the employed acid matrix without precipitation; (iii) stable signal intensity with moderate sensitivity; and (iv) physicochemical behavior as similar as possible to the analytes in terms of mass-to-charge ratio (m/z) and ionization/transport characteristics, while avoiding notable isotopic overlap or polyatomic interferences. A potassium aluminum sulfate solution with an Al concentration of 3 mg/L was used as a model sample (theoretical K/Al molar ratio = 1.00). The K/Al molar ratio and its stability were evaluated in different HCl and HNO₃ matrices. Three candidate internal standards— 45 Sc, 103 Rh, and 72 Ge—were tested for signal correction, and the resulting K/Al molar ratios were compared (Table 2 ). Table 2 Effect of different internal standards on the calculated K/Al molar ratio of a potassium aluminum sulfate model sample (n = 6) Sample preparation / matrix 45 Sc IS 103 Rh IS 72 Ge IS Molar ratio RSD(%) Molar ratio RSD(%) Molar ratio RSD(%) Dissolution with heated HCl (1 + 1, v/v) 1.02 0.8 1.02 0.8 1.02 0.8 Dissolution with heated HCl (1 + 3, v/v) 0.86 0.9 0.99 0.9 0.86 2.6 Dissolution with heated HNO₃ (1 + 1, v/v) 0.88 0.6 0.98 6.8 0.88 2.0 Dissolution by soaking in ultrapure water 0.86 0.9 0.99 0.9 0.87 1.5 As shown in Table 2 , the K/Al molar ratios corrected using ⁴⁵Sc or ⁷²Ge exhibited larger fluctuations across acid matrices and deviated overall from the theoretical value. In contrast, 103 Rh produced K/Al molar ratios in the range of 0.98–1.02, which were closer to the theoretical ratio and showed better agreement among different matrices. Considering both accuracy and method robustness, 103 Rh was selected as the online internal standard for subsequent method validation and sample analysis. This choice is also consistent with the need to stabilize the K/Al ratio across different dissolution matrices encountered in routine testing. 2.2. Method Validation To assess the reliability of the proposed ICP-MS method for simultaneous determination of aluminum and potassium, method performance was systematically evaluated in terms of linear range, limit of detection (LOD), limit of quantification (LOQ), precision, and accuracy. 2.2.1. Linear Range, LOD, and LOQ A series of mixed calibration standards for aluminum (Al) and potassium (K) was prepared over the concentration range of 0.02–5.0 mg/L, including a reagent blank. Standards were analyzed under the optimized ICP-MS conditions, and calibration curves were constructed by linear regression of the analyte-to-internal-standard signal ratio versus concentration (mg/L). Both Al and K showed excellent linearity across the tested range, with correlation coefficients (r) > 0.9997. Eleven blank solutions were prepared and analyzed to obtain the standard deviation (σ). The LOD and LOQ were calculated as 3σ and 10σ, respectively. The LOD and LOQ for Al were 0.0015 mg/L and 0.005 mg/L, respectively, whereas those for K were 0.009 mg/L and 0.03 mg/L, respectively. These sensitivity levels are sufficient for the quantification of Al and K as major constituents in alum samples. For completeness, the corresponding sample-level LOD/LOQ can be reported by propagating the preparation and dilution factors. Here we additionally report the sample-level values by propagating V = 0.100 L and DF = 500 (see Eq. 2 ) to aid method transfer. 2.2.2. Precision and Accuracy Accuracy and repeatability were evaluated by spike-recovery experiments. A certified alum reference material (purity > 99.5%) was selected as the test matrix. Low, medium, and high levels of Al and K standard solutions were spiked into the matrix, and each level was analyzed in six replicates. Recoveries and relative standard deviations (RSDs) were calculated, and the results are summarized in Table 3 . As shown, satisfactory recoveries were obtained for both Al and K across all spiking levels, with acceptable intra-day and inter-day precision. Intra-day precision was evaluated within the same analytical batch, whereas inter-day precision was evaluated across different days using fresh preparations. Table 3 Spike recoveries and precision for Al and K determined by ICP-MS (n = 6) Element Background (mg/L) Spike amount (mg/L) Measured value (mg/L, mean ± SD) Measured spike concentration ( mg/L, mean ± SD) Average recovery(%) Intra-day precision (RSD,%) Inter-day precision(RSD, %) Al 209.0 1280.7 ± 7.7 221.7 ± 7.7 106.1 3.4 3.3 1059.0 522.5 1622.6 ± 29.4 563.6 ± 29.4 107.9 5.2 5.0 1045.0 2099.7 ± 50.2 1040.7 ± 50.2 99.6 4.8 4.8 K 302.9 1888.1 ± 23.7 326.3 ± 23.7 107.7 7.3 5.0 1561.8 757.2 2370.2 ± 46.1 808.4 ± 46.1 106.7 5.7 5.0 1514.4 3086.9 ± 63.3 1525.0 ± 63.3 100.7 4.2 3.5 Note: Measured spike concentration was calculated as (measured value − background). Since background was treated as a constant, the SD of measured spike concentration equals that of measured value. 2.3. Performance Comparison Between the Proposed Method and the National Standard for Pure and Adulterated Samples To verify the accuracy and reliability of the proposed ICP-MS method based on simultaneous determination of Al and K under practical conditions, and to systematically demonstrate the inherent limitation of the current national standard method (zinc chloride back-titration) in alum purity assessment, two comparative experiments were designed. For all experiments, samples from the same batch were analyzed in parallel using the ICP-MS method and the national standard method (GB 1886.229–2016; back titration), and the results were compared. Statistical comparisons were conducted using a two-tailed t-test with a significance level of 0.05 unless otherwise stated. 2.3.1. Analysis of a High-Purity Alum Sample An analytical-grade alum sample (purity > 99.5%) was used as the test material. The analytical results obtained by the two methods are summarized in Table 4 . For the high-purity alum sample, the proposed method yielded a K/Al molar ratio of 1.01 ± 0.01, in excellent agreement with the theoretical value. Alum content calculated independently from Al and from K was 99.7% and 100.4%, respectively, demonstrating close agreement between the two calculations and thereby cross-validating the accuracy of Al and K determination by the proposed method. Moreover, neither of the ICP-MS-derived results differed significantly from the value obtained by the national standard back-titration method (99.8%) (P > 0.05). These findings indicate that, for pure alum, the proposed method provides accuracy comparable to that of the national standard, while additionally enabling internal cross-checking between elements. Table 4 Comparison of analytical results for a high-purity alum sample Method Al (mg/g) K(mg/g) K/Al molar ratio Alum content by Al (%) Alum content by K (%) Alum content by national standard (%) ICP-MS 104.2 ± 2.2 151.7 ± 4.1 1.01 ± 0.01 99.7 ± 2.1 100.4 ± 2.7 - National standard (back titration) 104.4 ± 1.8 - - - - 99.8 ± 1.7 2.3.2. Identification and Accurate Quantification of Simulated Adulterated Alum Samples To mimic adulteration practices commonly encountered in the market, two laboratory-prepared mixed samples with known compositions were formulated: (i) 70% (w/w) alum + 30% (w/w) sodium aluminum sulfate (sodium alum), and (ii) 70% (w/w) alum + 30% (w/w) potassium sulfate. In the first mixture, Al originates from both alum and sodium alum, whereas K originates only from alum; therefore, the expected K/Al molar ratio is markedly 1. Accordingly, for the K-rich/Al-deficient case, the true alum content should be derived from the Al-based conversion. The analytical results obtained by the two methods, together with interpretation against the known “true” composition, are summarized in Table 5 . Table 5 Results for simulated adulterated samples and interpretation against known composition Sample composition Method Result Interpretation 70% alum + 30% sodium alum ICP-MS: K/Al molar ratio 0.71 ± 0.06 Significantly < 1, indicating non-stoichiometric alum and the presence of Al-containing substitutes ICP-MS (K-based conversion) Alum = 70.0% ± 4.1% In close agreement with the true value (70%), accurately reflecting the alum fraction ICP-MS (Al-based conversion) Alum = 98.7% ± 2.6% Substantially biased high because Al from sodium alum is incorrectly converted to alum National standard (total-Al conversion) Alum = 98.5% ± 0.3% Severely overestimated for the same reason (assumes all Al originates from alum). Estimated adulterant level Sodium alum ≈ 30.0% Approximated from the difference between total Al and the Al attributable to alum; close to the true addition level (30%) 70% alum + 30% potassium sulfate ICP-MS: K/Al molar ratio 2.37 ± 0.03 Significantly > 1, indicating non-stoichiometric alum and the presence of additional K sources ICP-MS (K-based conversion) Alum = 151.9% ± 2.5% Far above plausible values, directly flagging abnormal composition ICP-MS (Al-based conversion) Alum = 64.2% ± 0.7% Close to the true value (70%), reflecting the alum fraction under K-rich conditions National standard (total-Al conversion) Alum = 65.6% ± 0.4% Also close to the true alum fraction, but provides no information on the K-containing adulterant Estimated adulterant level Other K salts ≈ 36.8% Inferred from total Al and K to estimate purity and to preliminarily attribute the adulterant type 2.4. Screening of Commercial Samples: Purity Survey of Marketed “Food Additive Alum” Products To evaluate the practical utility of the proposed method for market surveillance and to obtain an initial overview of the quality status of alum products available on the market, two analytical-grade potassium aluminum sulfate reagents (S1–S2) and three commercially marketed “food additive alum” products from different brands/batches (S3–S5) were randomly purchased. All samples were analyzed using the established ICP-MS method for simultaneous determination of Al and K, and results were compared in parallel with those obtained using the national standard back-titration method (Table 6 ). Table 6 Screening results for commercial alum samples Sample ID ICP-MS results National standard result Preliminary purity assessment (based on K/Al and conversion consistency) K/Al molar ratio Alum by Al (%) Alum by K (%) Difference (%) Alum (%) S1 1.01 98.1 98.8 0.7 99.6 Consistent with potassium alum; results agree and meet specification.。 S2 0.00 97.7 0.2 97.5 96.2 Clear adulteration; K/Al deviates markedly from 1 and K is nearly absent, indicating the product is not potassium alum.。 S3 1.02 96.8 98.7 2.0 97.0 Consistent with potassium alum; results generally agree and meet specification。 S4 0.76 86.9 65.5 21.4 87.1 Clear adulteration; low K/Al indicates Al-rich/K-deficient substitution. K-based alum content (65.5%) differs markedly from the national standard。 S5 0.99 90.7 89.5 1.2 88.2 Stoichiometrically consistent with potassium alum, but with low overall content; may indicate process issues or dilution As shown in Table 6 , samples S1, S3, and S5 exhibited K/Al molar ratios close to 1 (0.99–1.02). The alum contents calculated independently from Al and from K were in close agreement (difference < 2%) and were broadly consistent with the national standard results, supporting the accuracy of the proposed method for authentic potassium alum. Notably, although S5 was classified as stoichiometrically consistent with potassium alum, its alum content (~ 90.7%) was substantially lower than the typical purity of food additive–grade alum (commonly > 99.5%). This finding suggests potential shortcomings in manufacturing control or possible dilution, highlighting the need for strengthened quality assurance during production and procurement. In contrast, samples S2 and S4 clearly demonstrate the advantage of the proposed approach for adulteration detection. Sample S2 showed a K/Al molar ratio of ~ 0.00, indicating an extreme case in which an Al-containing salt was used to masquerade as alum. Under this scenario, the national standard method reported 96.2%, which could be misinterpreted as “compliant,” whereas the K-based alum content was only 0.2%, confirming that Al-only conversion cannot identify such adulteration. Sample S4 exhibited a low K/Al ratio (0.76) and a large discrepancy (21.4 percentage points) between Al-based and K-based alum contents, indicating Al-rich/K-deficient substitution. The corrected (K-based) alum content was only 65.5%, representing substantial quality and integrity concerns. 3. Discussion Under adulteration conditions, the two approaches showed markedly different performance, underscoring the necessity of the proposed workflow. The national standard back-titration method measures only total aluminum and implicitly assumes that all Al originates from alum, resulting in a severely biased estimate for Al-rich substitution. For the 70% alum + 30% sodium alum mixture, the reported value (~ 98.5%) deviated from the true alum content (70%) by more than 28 percentage points. In regulatory practice, such a bias could lead to adulterated products being misclassified as compliant or even “high-purity,” creating a significant surveillance gap. In contrast, the ICP-MS approach simultaneously quantifies K and Al and uses the K/Al molar ratio (theoretical ≈ 1) as the key decision metric, enabling effective authenticity screening (K/Al = 0.71 for the sodium-alum mixture). Based on the rationale that potassium is the unique characteristic cation of potassium alum, the workflow then applies the appropriate conversion rule—K-based conversion for Al-rich/K-deficient cases—yielding an accurate estimate of true alum content (70.0%), consistent with the known formulation. Additionally, the difference between measured total Al and Al attributable to alum can be used to approximate the level of Al-containing adulterants (e.g., sodium alum), providing useful information for trace-back and enforcement. For K-salt adulteration (e.g., potassium sulfate), the workflow similarly flags abnormality through an elevated K/Al ratio (2.37) and corrects alum quantification by selecting the Al-based conversion under K-rich/Al-deficient conditions, while also offering preliminary inference on adulterant type. Notably, an implausibly high K-based converted “alum content” (e.g., > 100%) serves as an immediate red-flag output that is easy to interpret in routine screening. Because ICP-MS acquires multi-element data in a single run, additional elemental signals can be incorporated in future extensions for improved adulterant attribution. Furthermore, the screening of commercially available alum products conducted in this study further demonstrates the practical value of the proposed method for detecting potential issues of insufficient purity and product adulteration. Because the conventional back-titration method measures total Al only and assumes it derives entirely from alum, it may fail for adulterated samples such as S2 and S4 (Table 6 ) and can even yield misleading “pass” results. By contrast, the proposed workflow uses the K/Al molar ratio as an intrinsic consistency check to flag abnormal compositions—either Al-rich/K-deficient (R 1.05)—and then applies the corresponding conversion rule (K-based or Al-based) to quantify the true alum content. This enables estimation of adulteration extent and provides a more reliable analytical basis for regulatory surveillance. Because the core of the proposed workflow is the simultaneous acquisition of Al and K followed by a stoichiometric consistency check, the approach is not inherently dependent on ICP-MS. For alum raw materials and their adulterated products, Al and K are typically present at relatively high levels; therefore, most multi-element analytical platforms capable of quantitative determination can meet the requirements for simultaneous measurement. When available, ICP-MS offers clear advantages, including high sensitivity and versatile interference-control strategies (e.g., collision/reaction cell operation), making it well suited to complex matrices and expanded multi-element screening. In routine or resource-limited laboratories, inductively coupled plasma–optical emission spectrometry (ICP-OES) can also provide simultaneous quantification of Al and K with lower operating cost, reduced maintenance burden, and higher throughput. When implementing the workflow on ICP-OES, the following considerations are recommended: selection of spectral lines with minimal interference and appropriate background correction; suitable dilution and/or matrix matching for high-HCl media and samples with high total dissolved solids; and control of matrix effects using external calibration with internal standardization and/or standard addition as needed. Importantly, regardless of whether ICP-MS or ICP-OES is used, the K/Al consistency threshold and the “missing characteristic element” correction rule proposed in this study can be directly applied, provided that linearity, precision, and recovery meet routine quality-control criteria. This enables cross-platform and multi-level adoption of the workflow. 4. Conclusions The comparative experiments demonstrate that the principal limitation of the current national standard back-titration method is that it measures total Al only and assumes all Al originates from potassium alum. This assumption leads to systematic positive bias when Al-rich/K-deficient substitutes are present. The workflow proposed here uses the K/Al molar ratio (R) as a dual-element consistency indicator to screen authenticity and then, for abnormal ratios, selects the conversion pathway based on a ‘missing characteristic element’ principle to obtain corrected estimates for typical adulteration patterns. Compared with Al-only conversion, the workflow outputs both (i) a corrected quantitative estimate of true potassium alum content and (ii) an interpretable flag (R and Δ) that supports enforcement-oriented decision making. The approach is transferable to ICP-MS and other multi-element platforms (e.g., ICP-OES) after local verification of precision and recovery. Declarations Author Contribution Zhiji Chen: Writing-original draft, Methodology, Investigation, Formal analysis. Li Wang: Formal analysis, Validation. Micong Jin: Conceptualization, Writing-review & editing, Validation, Resources, Supervision, Funding acquisition. Acknowledgments This work was supported by the Ningbo Municipal Key Medical Discipline Construction Project (2022-B18), the Ningbo Medical and Health Brand Discipline Construction Project (PPXK2024-09), and the Zhejiang Science and Technology Plan for Disease Prevention and Control (Project No. 2026JKY219). References Liu YJ, Li CL, Meng Q (2023) Research progress on aluminum-containing food additives and their detection technologies and monitoring analysis. Food Ind Sci Technol 44(7):470–474. https://doi.org/10.13386/j.issn1002-0306.2022050366 Wang HW, Pang YH, Zhang SJ, Li SH (2021) Determination of trace aluminum in food additives by collision cell-ICP-MS. J Food Saf Qual Inspection 12(13):5191–5195. https://doi.org/10.19812/j.cnki.jfsq11-5956/ts.2021.13.015 GB 2760–2024 National Food Safety Standard—Standard for Uses of Food Additives GB 1886.229–2016 National Food Safety Standard—Food Additive: Potassium Aluminum Sulfate (Alum) Huang XL, Zhou ZH, Xing SW, Liu D, Hu YJ, He B, Ai X (2018) Determination of aluminum in dried kelp by microwave digestion–ICP-OES. Food Ferment Technol 54(4):84–86. https://doi.org/10.3969/j.issn.1674-506X.2018.04-017 He ZC, Yu JH, Zheng XC, Jiang YT (2017) Determination of aluminum in puffed foods by ICP-OES. Guangdong Trace Elements Science. 2017;24(6):11–13. https://doi.org/10.16755/j.cnki.issn.1006-446x.2017.06.003 GB 5009 182–2017. National Food Safety Standard—Determination of Aluminum in Foods Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 09 Mar, 2026 Reviews received at journal 08 Mar, 2026 Reviewers agreed at journal 01 Mar, 2026 Reviewers invited by journal 27 Feb, 2026 Editor assigned by journal 11 Feb, 2026 Submission checks completed at journal 11 Feb, 2026 First submitted to journal 11 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8850541","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":598862201,"identity":"f8bbbd08-023e-4271-a530-76e573de985b","order_by":0,"name":"Zhiji Chen","email":"","orcid":"","institution":"Ningbo Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Zhiji","middleName":"","lastName":"Chen","suffix":""},{"id":598862202,"identity":"c149655f-8eb0-457e-9313-ca76eddff60d","order_by":1,"name":"Li Wang","email":"","orcid":"","institution":"Ningbo Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Wang","suffix":""},{"id":598862203,"identity":"c720b3fd-0fe2-4663-b893-51fcbcefdd00","order_by":2,"name":"Micong C. Jin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAnklEQVRIiWNgGAWjYBACxgYGBgOGCgk5eRK1nLEwNmwgzaq2ikSGA8SqZp52+EHBz3kSCYwNzA8f3SDKgtlpBoa92yTy2BnYjI1ziNOSw2DMuE2imLGBh02aBC1zJBIbDpCmpYE0LUC/9ByTMDZsJtYvhrOTnxn8qKmTk2dvfviYOC0NDGwGYBYzMcpBAJhOmB8Qq3gUjIJRMApGKAAAHZ0rkgqer6wAAAAASUVORK5CYII=","orcid":"","institution":"Ningbo Center for Disease Control and Prevention","correspondingAuthor":true,"prefix":"","firstName":"Micong","middleName":"C.","lastName":"Jin","suffix":""}],"badges":[],"createdAt":"2026-02-11 10:42:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8850541/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8850541/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104402062,"identity":"86933353-016b-41d5-9db4-e17dd4a2a884","added_by":"auto","created_at":"2026-03-11 12:14:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1157685,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8850541/v1/dae6dd9d-ee25-4fa5-9716-f1055b183451.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Dual-Element Stoichiometric-Consistency Workflow Using Simultaneous Al and K Measurement for Reliable Alum Assay and Adulteration Screening","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePotassium aluminum sulfate (alum, AlK(SO4)\u003csub\u003e2\u003c/sub\u003e\u0026middot;12H\u003csub\u003e2\u003c/sub\u003eO) is a traditional food additive that is widely used in fried products, jellyfish processing, and starch-based noodles, where it functions primarily as a leavening agent, coagulant/firming agent, and water clarifier. Because alum contains aluminum (Al), excessive intake may pose potential risks to human health, including effects on the nervous system (Liu 2023; Wang 2021). Accordingly, many countries have established strict regulations on its permitted uses and maximum levels in foods. In China, the National Food Safety Standard for the Use of Food Additives (GB 2760\u0026ndash;2024) specifies maximum use levels of alum for different food categories. Therefore, accurate determination of both the content and purity of alum used as a food additive is essential for ensuring food safety, standardizing industrial practice, and protecting consumer health.\u003c/p\u003e \u003cp\u003eIn China, the National Food Safety Standard for Food Additive\u0026mdash;Potassium Aluminum Sulfate (Alum) (GB 1886.229\u0026ndash;2016) specifies a zinc chloride back-titration method for alum assay. In this procedure, aluminum content is determined and then converted to alum content according to the stoichiometry of alum (AlK(SO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e\u0026middot;12H\u003csub\u003e2\u003c/sub\u003eO). However, this approach has a fundamental conceptual limitation: it implicitly assumes that all aluminum present originates from pure alum, and it provides no independent check of the accompanying potassium required by alum stoichiometry. In real manufacturing and distribution chains, cheaper aluminum alums such as sodium aluminum sulfate (sodium alum) and ferric aluminum sulfate (ferric alum) may be used fraudulently to partially replace alum. Under such circumstances, the back-titration method cannot differentiate the source of aluminum and will incorrectly convert total aluminum to alum, resulting in inflated assay values that do not reflect the true amount of potassium alum added. This creates a regulatory blind spot and may increase food safety risks.\u003c/p\u003e \u003cp\u003eA robust solution requires simultaneous determination of the characteristic cations K and Al and explicit use of their stoichiometric relationship. The K/Al molar ratio can be used for verify whether a sample matches the theoretical ratio of pure alum (approximately 1:1), thereby enabling authenticity and purity assessment and facilitating the detection of admixture with other alums. Moreover, because potassium is the unique characteristic cation of potassium alum, K-based quantification provides a direct route to estimating the true alum content in the presence of Al-rich substitutes. we developed an inductively coupled plasma\u0026ndash;mass spectrometry (ICP-MS) method (Huang 2018; He 2017) for the simultaneous determination of Al and K, and evaluated its performance through systematic method validation and real-sample testing. On this basis, we further established an implementation-ready workflow that couples K/Al ratio screening with conversion correction to support both discrimination (purity/authenticity) and quantification (true alum content) under non-ideal, adulterated conditions.\u003c/p\u003e \u003cp\u003eCompared with conventional single-element conversion, the key contributions are: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) translating Al\u0026ndash;K stoichiometric constraints into two computable QC metrics (R\u0026thinsp;=\u0026thinsp;K/Al molar ratio and Δ, the relative deviation between Al-derived and K-derived alum contents) that enable intrinsic authenticity/purity assessment; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) providing an implementation-ready decision workflow (\u0026ldquo;screen \u0026rarr; select conversion channel \u0026rarr; interpret\u0026rdquo;) that yields a corrected alum content estimate under typical adulteration patterns; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) validating the criteria and applicability boundaries using simulated adulteration scenarios (Al-rich substitution and K-salt addition) and commercial samples, with direct comparison to the Al-only conversion embedded in GB 1886.229\u0026ndash;2016.\u003c/p\u003e"},{"header":"1. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.1. Instruments and Reagents\u003c/h2\u003e \u003cp\u003eA NexION 300D inductively coupled plasma\u0026ndash;mass spectrometer (ICP-MS; PerkinElmer, USA) equipped with a high-salt-resistant sample introduction system was used. An analytical balance (readability: 0.1 mg) and a Milli-Q ultrapure water system (Millipore, USA) were employed.\u003c/p\u003e \u003cp\u003eAluminum standard solution (1000 mg/L) and potassium standard solution (1000 mg/L) were obtained from the National Center of Analysis and Testing for Nonferrous Metals and Electronic Materials (China). Zinc chloride standard solution (1.0002 mol/L) was purchased from Sichuan Pushiao Reference Materials Technology Co., Ltd. Disodium ethylenediaminetetraacetate (EDTA-2Na) standard solution (0.1017 mol/L) was supplied by Tanmo Quality Inspection Technology Co., Ltd. Argon gas (purity\u0026thinsp;\u0026ge;\u0026thinsp;99.999%) was used for the plasma. Potassium aluminum sulfate (alum), and potassium sulfate (analytical grade, purity\u0026thinsp;\u0026gt;\u0026thinsp;99.5%) were purchased from Sinopharm Chemical Reagent Co., Ltd. Sodium aluminum sulfate (analytical grade, purity\u0026thinsp;\u0026gt;\u0026thinsp;98%) was purchased from Shanghai Haohong Biomedical Technology Co., Ltd. Hydrochloric acid and nitric acid (Suprapur grade) were obtained from Merck. Internal standard solutions of Sc, Ge, and Rh (500 \u0026micro;g/L) were obtained from the National Center of Analysis and Testing for Nonferrous Metals and Electronic Materials (China). Ultrapure water (resistivity\u0026thinsp;\u0026ge;\u0026thinsp;18.2 MΩ\u0026middot;cm) produced by the Milli-Q system was used throughout.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.2. Preparation of Solutions\u003c/h2\u003e \u003cp\u003eAppropriate aliquots of the 1000 mg/L Al and K stock standard solutions were accurately transferred and serially diluted with 1% (v/v) nitric acid to prepare a mixed Al\u0026ndash;K working standard solution with final concentrations of 1.0 mg/L for both Al and K. All standards and samples were prepared in 1% (v/v) HNO₃ to match the matrix of the calibration solutions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1.3. Calibration Curve\u003c/h2\u003e \u003cp\u003eA series of mixed calibration standards was prepared by serial dilution of Al and K standard solutions with 1% (v/v) nitric acid. The concentrations of both Al and K were 0, 0.2, 0.5, 1.0, 2.0, and 5.0 mg/L (0 corresponds to the reagent blank). Calibration curves were constructed by linear regression of signal intensity (cps) versus concentration (mg/L). The analyte-to-internal-standard signal ratio was used for calibration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e1.4. ICP-MS Operating Conditions\u003c/h2\u003e \u003cp\u003eInstrument parameters were optimized using a 1 \u0026micro;g/L tuning solution containing Be, Ce, Fe, In, Li, Mg, Pb, and U. The optimized operating conditions were as follows: RF power, 1300 W; nebulizer (carrier) gas flow, 0.99 L/min; auxiliary gas flow, 1.2 L/min; sampler and skimmer cones, platinum; peristaltic pump speed, 20.0 rpm; number of sweeps, 20; dwell time, 50 ms; acquisition mode, peak hopping; helium collision gas flow, 3 mL/min; RPq (low-mass cutoff), 0.25. The doubly charged ratio was controlled at Ce\u0026sup2;⁺/Ce⁺ \u0026lt; 3.0%, and the oxide ratio at CeO⁺/Ce⁺ \u0026lt; 2.5%. Rh (\u003csup\u003e103\u003c/sup\u003eRh) was used as the internal standard and introduced online at 20 \u0026micro;g/L. Ge (\u003csup\u003e72\u003c/sup\u003eGe, 200 \u0026micro;g/L) and Sc (\u003csup\u003e45\u003c/sup\u003eSc, 100 \u0026micro;g/L) were evaluated only during internal-standard selection and were not used for final quantification. All reported concentrations were corrected using the analyte-to-\u003csup\u003e103\u003c/sup\u003eRh signal ratio.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e1.5. Sample Preparation\u003c/h2\u003e \u003cp\u003eApproximately 1.0 g of alum sample was accurately weighed (to 0.1 mg) into a suitable vessel. Ultrapure water (20 mL) and hydrochloric acid (20 mL; 1\u0026thinsp;+\u0026thinsp;1, v/v) were added, and the mixture was heated until complete dissolution, yielding a clear solution. After cooling to room temperature, the solution was diluted to 100.0 mL with 1% (v/v) nitric acid, followed by a 500-fold dilution to ensure that Al and K concentrations in the final test solution fell within the linear range of the ICP-MS calibration curves. For samples showing visible insoluble residue, the solution was filtered prior to volume make-up.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e1.6. Calculation of Alum Content and Decision Logic\u003c/h2\u003e \u003cp\u003eIn this study, \u0026ldquo;alum (potassium aluminum sulfate) content\u0026rdquo; was expressed on a dry basis as specified in Appendix A of GB 1886.229\u0026ndash;2016, calculated as anhydrous potassium aluminum sulfate (AlK(SO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e) as the measurement basis (relative molecular mass\u0026thinsp;=\u0026thinsp;258.19). The corresponding theoretical mass fractions are w(Al)\u0026thinsp;=\u0026thinsp;26.98/258.19\u0026thinsp;=\u0026thinsp;10.450% and w(K)\u0026thinsp;=\u0026thinsp;39.10/258.19\u0026thinsp;=\u0026thinsp;15.144%. Unless otherwise stated, \u0026ldquo;content (%)\u0026rdquo; refers to mass fraction on a dry basis.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e1.6.1. Calculation of the K/Al Molar Ratio\u003c/h2\u003e \u003cp\u003eThe mass concentrations of Al and K (mg/L) in the test solution were determined and converted to mass fractions in the sample (mg/g). The K/Al molar ratio (R) was calculated as (R is used as the primary stoichiometric-screening indicator; theoretical R\u0026thinsp;\u0026asymp;\u0026thinsp;1.00 for pure AlK(SO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e):\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\text{R}\\text{=}\\frac{{\\text{w}}_{\\text{K}}/{\\text{M}}_{\\text{K}}}{{\\text{w}}_{\\text{Al}}/{\\text{M}}_{\\text{Al}}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere \u003cem\u003ew\u003c/em\u003e\u003csub\u003eK\u003c/sub\u003e and \u003cem\u003ew\u003c/em\u003e\u003csub\u003eAl\u003c/sub\u003e are the mass fractions of K and Al in the sample (mg/g), respectively; M\u003csub\u003eK\u003c/sub\u003e=39.10 g/mol, M\u003csub\u003eAl\u003c/sub\u003e =26.98 g/mol.\u003c/p\u003e \u003cp\u003eThe mass fraction w (mg/g) was obtained from the measured concentration C (mg/L) using:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\text{w}\\text{=}\\frac{\\text{C}\\text{\u0026times;}\\text{V}\\text{\u0026times;}\\text{DF}}{\\text{m}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere V is the final volume (L) after dissolution (0.100 L), DF is the subsequent dilution factor (500), and m is the sample mass (g).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e1.6.2. Purity Assessment and Conversion Strategy\u003c/h2\u003e \u003cp\u003eDecision criteria and internal-consistency check. First compute the K/Al molar ratio R using Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). If 0.95\u0026thinsp;\u0026le;\u0026thinsp;R\u0026thinsp;\u0026le;\u0026thinsp;1.05, the sample is considered stoichiometrically consistent with potassium alum within analytical uncertainty. Then compute the relative deviation between the two independent alum content estimates: Δ = |C\u003csub\u003eK\u003c/sub\u003e\u0026minus;C\u003csub\u003eAl\u003c/sub\u003e| / ((C\u003csub\u003eK\u003c/sub\u003e+C\u003csub\u003eAl\u003c/sub\u003e)/2) \u0026times; 100%, where C\u003csub\u003eK\u003c/sub\u003e is alum content converted from K and C\u003csub\u003eAl\u003c/sub\u003e is alum content converted from Al. A practical acceptance criterion is Δ\u0026thinsp;\u0026le;\u0026thinsp;5% (to be confirmed/adjusted by each laboratory based on its precision and recovery). If Δ\u0026thinsp;\u0026gt;\u0026thinsp;5%, re-prepare the sample and re-measure; if still\u0026thinsp;\u0026gt;\u0026thinsp;5%, report both channels and flag the sample for further investigation.\u003c/p\u003e \u003cp\u003eWhen R is within [0.95, 1.05], the sample is considered stoichiometrically consistent with potassium alum within analytical uncertainty; the interval should be set/confirmed by the laboratory using repeated measurements of qualified alum materials and error-propagation of Al and K determinations:\u003c/p\u003e \u003cp\u003eK-based conversion: (alum, %) =\u003cem\u003ew\u003c/em\u003e\u003csub\u003eK\u003c/sub\u003e\u0026times;258.19/(M\u003csub\u003eK\u003c/sub\u003e\u0026times;10)\u003c/p\u003e \u003cp\u003eAl-based conversion: (alum, %) =\u003cem\u003ew\u003c/em\u003e\u003csub\u003eAl\u003c/sub\u003e\u0026times;258.19/(M\u003csub\u003eAl\u003c/sub\u003e\u0026times;10)\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003ew\u003c/em\u003e\u003csub\u003eK\u003c/sub\u003e and \u003cem\u003ew\u003c/em\u003e\u003csub\u003eAl\u003c/sub\u003e are in mg/g; division by 10 converts mg/g to % (10 mg/g\u0026thinsp;=\u0026thinsp;1%)\u003c/p\u003e \u003cp\u003eWhen R\u0026thinsp;\u0026lt;\u0026thinsp;0.95, an Al-rich/K-deficient pattern was indicated, consistent with partial substitution by other aluminum alums (e.g., sodium alum or ferric alum). In this case, the K-based converted value was taken as the estimate of true alum content. When R\u0026thinsp;\u0026gt;\u0026thinsp;1.05, a K-rich/Al-deficient pattern was indicated, suggesting the presence of added potassium salts or other potassium sources (e.g., potassium sulfate). In this case, the Al-based converted value was taken as the estimate of true alum content.\u003c/p\u003e \u003cp\u003eIn addition, for samples within [0.95, 1.05], agreement between K-based and Al-based alum contents was evaluated as an internal consistency check; large discrepancies were flagged for repeat preparation and remeasurement.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e1.6.3. Comparison with the National Standard Method\u003c/h2\u003e \u003cp\u003eResults obtained using the national standard (zinc chloride back-titration) were used as a reference comparator. This method inherently assumes that all measured aluminum originates from alum. Accordingly, it was expected to bias high when Al-rich substitutes were present.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e1.7. Method Validation\u003c/h2\u003e \u003cp\u003eMethod performance was evaluated in terms of linear range, limit of detection (LOD), limit of quantification (LOQ), precision, and spike recovery. All experiments were conducted in six replicates, and data are reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. LOD and LOQ were calculated based on the standard deviation of reagent blanks (σ) as LOD=3σ and LOQ=10σ, with the corresponding concentration converted to sample-level values using the same preparation and dilution scheme.\u003c/p\u003e \u003c/div\u003e"},{"header":"2. Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Effects of ICP-MS Determination Conditions\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1. Optimization of ICP-MS Instrument Parameters\u003c/h2\u003e \u003cp\u003eICP-MS exhibits substantial differences in inherent sensitivity among elements, primarily due to their physicochemical properties (e.g., first ionization energy), ion transport efficiency in the plasma/interface, and detector response characteristics. Potassium (K) has a relatively low first ionization energy (419 kJ/mol), is readily ionized, and typically provides high ICP-MS sensitivity. In contrast, aluminum (Al) has a higher first ionization energy (577 kJ/mol), generally shows lower sensitivity, and is more susceptible to matrix effects and polyatomic interferences. When measured under identical instrumental conditions, K and Al signals may differ by several orders of magnitude.\u003c/p\u003e \u003cp\u003eIt is generally accepted that simultaneous determination of K and Al at comparable signal levels can minimize the impact of detector nonlinearity and short-term instrumental fluctuations on their signal ratio. This helps (i) maintain the linearity and fitting quality of calibration curves and (ii) improve ratio stability during sample analysis, because minor instrumental drift tends to affect both elements more uniformly when their signals are within a similar magnitude range.\u003c/p\u003e \u003cp\u003eDetector attenuation (electronic dilution) was applied to equalize the signal magnitude of K and Al, thereby reducing the risk of detector nonlinearity and improving ratio stability, without changing the solution concentration.\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, varying the K/Al signal intensity ratio had negligible impact on the calculated K/Al molar ratio, which remained within 1.01\u0026ndash;1.02 and was consistent with the stoichiometric characteristics of potassium aluminum sulfate. Notably, the K/Al signal intensity ratio of 1.38 provided the best stability (lowest RSD). Therefore, to maximize method stability and accuracy, electronic dilution factors of 0.0150 for K and 0.0145 for Al were selected for subsequent sample measurements.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of K/Al signal intensity ratio on the calculated K/Al molar ratio (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eElectronic dilution factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eK/Al signal intensity ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eK/Al molar ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRSD(%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.0150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2. Optimization of the Internal Standard for ICP-MS Determination\u003c/h2\u003e \u003cp\u003eThe use of an internal standard (IS) is a common strategy in ICP-MS to compensate for signal drift caused by variations in nebulization efficiency, plasma instability, changes in ion transmission, and matrix effects, thereby improving quantitative accuracy and inter-run comparability. Selection of a suitable IS generally follows these criteria: (i) negligible or very low background levels in the sample; (ii) chemical stability in the employed acid matrix without precipitation; (iii) stable signal intensity with moderate sensitivity; and (iv) physicochemical behavior as similar as possible to the analytes in terms of mass-to-charge ratio (m/z) and ionization/transport characteristics, while avoiding notable isotopic overlap or polyatomic interferences.\u003c/p\u003e \u003cp\u003eA potassium aluminum sulfate solution with an Al concentration of 3 mg/L was used as a model sample (theoretical K/Al molar ratio\u0026thinsp;=\u0026thinsp;1.00). The K/Al molar ratio and its stability were evaluated in different HCl and HNO₃ matrices. Three candidate internal standards\u0026mdash;\u003csup\u003e45\u003c/sup\u003eSc, \u003csup\u003e103\u003c/sup\u003eRh, and \u003csup\u003e72\u003c/sup\u003eGe\u0026mdash;were tested for signal correction, and the resulting K/Al molar ratios were compared (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of different internal standards on the calculated K/Al molar ratio of a potassium aluminum sulfate model sample (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSample preparation / matrix\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003csup\u003e45\u003c/sup\u003eSc IS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003csup\u003e103\u003c/sup\u003eRh IS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003csup\u003e72\u003c/sup\u003eGe IS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMolar ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRSD(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMolar ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRSD(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMolar ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRSD(%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDissolution with heated HCl (1\u0026thinsp;+\u0026thinsp;1, v/v)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDissolution with heated HCl (1\u0026thinsp;+\u0026thinsp;3, v/v)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDissolution with heated HNO₃ (1\u0026thinsp;+\u0026thinsp;1, v/v)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDissolution by soaking in ultrapure water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the K/Al molar ratios corrected using ⁴⁵Sc or ⁷\u0026sup2;Ge exhibited larger fluctuations across acid matrices and deviated overall from the theoretical value. In contrast, \u003csup\u003e103\u003c/sup\u003eRh produced K/Al molar ratios in the range of 0.98\u0026ndash;1.02, which were closer to the theoretical ratio and showed better agreement among different matrices. Considering both accuracy and method robustness, \u003csup\u003e103\u003c/sup\u003eRh was selected as the online internal standard for subsequent method validation and sample analysis. This choice is also consistent with the need to stabilize the K/Al ratio across different dissolution matrices encountered in routine testing.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Method Validation\u003c/h2\u003e \u003cp\u003eTo assess the reliability of the proposed ICP-MS method for simultaneous determination of aluminum and potassium, method performance was systematically evaluated in terms of linear range, limit of detection (LOD), limit of quantification (LOQ), precision, and accuracy.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Linear Range, LOD, and LOQ\u003c/h2\u003e \u003cp\u003eA series of mixed calibration standards for aluminum (Al) and potassium (K) was prepared over the concentration range of 0.02\u0026ndash;5.0 mg/L, including a reagent blank. Standards were analyzed under the optimized ICP-MS conditions, and calibration curves were constructed by linear regression of the analyte-to-internal-standard signal ratio versus concentration (mg/L). Both Al and K showed excellent linearity across the tested range, with correlation coefficients (r)\u0026thinsp;\u0026gt;\u0026thinsp;0.9997.\u003c/p\u003e \u003cp\u003eEleven blank solutions were prepared and analyzed to obtain the standard deviation (σ). The LOD and LOQ were calculated as 3σ and 10σ, respectively. The LOD and LOQ for Al were 0.0015 mg/L and 0.005 mg/L, respectively, whereas those for K were 0.009 mg/L and 0.03 mg/L, respectively. These sensitivity levels are sufficient for the quantification of Al and K as major constituents in alum samples. For completeness, the corresponding sample-level LOD/LOQ can be reported by propagating the preparation and dilution factors. Here we additionally report the sample-level values by propagating V\u0026thinsp;=\u0026thinsp;0.100 L and DF\u0026thinsp;=\u0026thinsp;500 (see Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) to aid method transfer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. Precision and Accuracy\u003c/h2\u003e \u003cp\u003eAccuracy and repeatability were evaluated by spike-recovery experiments. A certified alum reference material (purity\u0026thinsp;\u0026gt;\u0026thinsp;99.5%) was selected as the test matrix. Low, medium, and high levels of Al and K standard solutions were spiked into the matrix, and each level was analyzed in six replicates. Recoveries and relative standard deviations (RSDs) were calculated, and the results are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. As shown, satisfactory recoveries were obtained for both Al and K across all spiking levels, with acceptable intra-day and inter-day precision. Intra-day precision was evaluated within the same analytical batch, whereas inter-day precision was evaluated across different days using fresh preparations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSpike recoveries and precision for Al and K determined by ICP-MS (n\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBackground (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpike amount (mg/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMeasured value (mg/L, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMeasured spike concentration ( mg/L, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAverage recovery(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntra-day precision\u003c/p\u003e \u003cp\u003e(RSD,%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eInter-day precision(RSD, %)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e209.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1280.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e221.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e106.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1059.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e522.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1622.6\u0026thinsp;\u0026plusmn;\u0026thinsp;29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e563.6\u0026thinsp;\u0026plusmn;\u0026thinsp;29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e107.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1045.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2099.7\u0026thinsp;\u0026plusmn;\u0026thinsp;50.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e1040.7\u0026thinsp;\u0026plusmn;\u0026thinsp;50.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e99.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e302.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1888.1\u0026thinsp;\u0026plusmn;\u0026thinsp;23.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e326.3\u0026thinsp;\u0026plusmn;\u0026thinsp;23.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e107.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1561.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e757.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2370.2\u0026thinsp;\u0026plusmn;\u0026thinsp;46.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e808.4\u0026thinsp;\u0026plusmn;\u0026thinsp;46.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e106.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1514.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3086.9\u0026thinsp;\u0026plusmn;\u0026thinsp;63.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e1525.0\u0026thinsp;\u0026plusmn;\u0026thinsp;63.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e100.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNote: Measured spike concentration was calculated as (measured value\u0026thinsp;\u0026minus;\u0026thinsp;background). Since background was treated as a constant, the SD of measured spike concentration equals that of measured value.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Performance Comparison Between the Proposed Method and the National Standard for Pure and Adulterated Samples\u003c/h2\u003e \u003cp\u003eTo verify the accuracy and reliability of the proposed ICP-MS method based on simultaneous determination of Al and K under practical conditions, and to systematically demonstrate the inherent limitation of the current national standard method (zinc chloride back-titration) in alum purity assessment, two comparative experiments were designed. For all experiments, samples from the same batch were analyzed in parallel using the ICP-MS method and the national standard method (GB 1886.229\u0026ndash;2016; back titration), and the results were compared. Statistical comparisons were conducted using a two-tailed t-test with a significance level of 0.05 unless otherwise stated.\u003c/p\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1. Analysis of a High-Purity Alum Sample\u003c/h2\u003e \u003cp\u003eAn analytical-grade alum sample (purity\u0026thinsp;\u0026gt;\u0026thinsp;99.5%) was used as the test material. The analytical results obtained by the two methods are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. For the high-purity alum sample, the proposed method yielded a K/Al molar ratio of 1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01, in excellent agreement with the theoretical value. Alum content calculated independently from Al and from K was 99.7% and 100.4%, respectively, demonstrating close agreement between the two calculations and thereby cross-validating the accuracy of Al and K determination by the proposed method. Moreover, neither of the ICP-MS-derived results differed significantly from the value obtained by the national standard back-titration method (99.8%) (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). These findings indicate that, for pure alum, the proposed method provides accuracy comparable to that of the national standard, while additionally enabling internal cross-checking between elements.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of analytical results for a high-purity alum sample\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAl (mg/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eK(mg/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eK/Al molar ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAlum content by Al (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAlum content by K (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAlum content by national standard (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICP-MS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e104.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNational standard (back titration)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e104.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2. Identification and Accurate Quantification of Simulated Adulterated Alum Samples\u003c/h2\u003e \u003cp\u003eTo mimic adulteration practices commonly encountered in the market, two laboratory-prepared mixed samples with known compositions were formulated: (i) 70% (w/w) alum\u0026thinsp;+\u0026thinsp;30% (w/w) sodium aluminum sulfate (sodium alum), and (ii) 70% (w/w) alum\u0026thinsp;+\u0026thinsp;30% (w/w) potassium sulfate. In the first mixture, Al originates from both alum and sodium alum, whereas K originates only from alum; therefore, the expected K/Al molar ratio is markedly\u0026thinsp;\u0026lt;\u0026thinsp;1. In the second mixture, Al originates only from alum, whereas K originates from both alum and potassium sulfate; therefore, the expected K/Al molar ratio is markedly\u0026thinsp;\u0026gt;\u0026thinsp;1. Accordingly, for the K-rich/Al-deficient case, the true alum content should be derived from the Al-based conversion. The analytical results obtained by the two methods, together with interpretation against the known \u0026ldquo;true\u0026rdquo; composition, are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults for simulated adulterated samples and interpretation against known composition\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample composition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResult\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInterpretation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70% alum\u0026thinsp;+\u0026thinsp;30% sodium alum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICP-MS: K/Al molar ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificantly\u0026thinsp;\u0026lt;\u0026thinsp;1, indicating non-stoichiometric alum and the presence of Al-containing substitutes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICP-MS (K-based conversion)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlum\u0026thinsp;=\u0026thinsp;70.0% \u0026plusmn; 4.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIn close agreement with the true value (70%), accurately reflecting the alum fraction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICP-MS (Al-based conversion)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlum\u0026thinsp;=\u0026thinsp;98.7% \u0026plusmn; 2.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSubstantially biased high because Al from sodium alum is incorrectly converted to alum\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNational standard (total-Al conversion)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlum\u0026thinsp;=\u0026thinsp;98.5% \u0026plusmn; 0.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSeverely overestimated for the same reason (assumes all Al originates from alum).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimated adulterant level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSodium alum\u0026thinsp;\u0026asymp;\u0026thinsp;30.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eApproximated from the difference between total Al and the Al attributable to alum; close to the true addition level (30%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70% alum\u0026thinsp;+\u0026thinsp;30% potassium sulfate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICP-MS: K/Al molar ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSignificantly\u0026thinsp;\u0026gt;\u0026thinsp;1, indicating non-stoichiometric alum and the presence of additional K sources\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICP-MS (K-based conversion)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlum\u0026thinsp;=\u0026thinsp;151.9% \u0026plusmn; 2.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFar above plausible values, directly flagging abnormal composition\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICP-MS (Al-based conversion)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlum\u0026thinsp;=\u0026thinsp;64.2% \u0026plusmn; 0.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eClose to the true value (70%), reflecting the alum fraction under K-rich conditions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNational standard (total-Al conversion)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlum\u0026thinsp;=\u0026thinsp;65.6% \u0026plusmn; 0.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAlso close to the true alum fraction, but provides no information on the K-containing adulterant\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimated adulterant level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther K salts\u0026thinsp;\u0026asymp;\u0026thinsp;36.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInferred from total Al and K to estimate purity and to preliminarily attribute the adulterant type\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Screening of Commercial Samples: Purity Survey of Marketed \u0026ldquo;Food Additive Alum\u0026rdquo; Products\u003c/h2\u003e \u003cp\u003eTo evaluate the practical utility of the proposed method for market surveillance and to obtain an initial overview of the quality status of alum products available on the market, two analytical-grade potassium aluminum sulfate reagents (S1\u0026ndash;S2) and three commercially marketed \u0026ldquo;food additive alum\u0026rdquo; products from different brands/batches (S3\u0026ndash;S5) were randomly purchased. All samples were analyzed using the established ICP-MS method for simultaneous determination of Al and K, and results were compared in parallel with those obtained using the national standard back-titration method (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eScreening results for commercial alum samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eICP-MS results\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNational standard result\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePreliminary purity assessment (based on K/Al and conversion consistency)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eK/Al molar ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlum by Al (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAlum by K (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDifference (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAlum (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e99.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eConsistent with potassium alum; results agree and meet specification.。\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e97.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eClear adulteration; K/Al deviates markedly from 1 and K is nearly absent, indicating the product is not potassium alum.。\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eConsistent with potassium alum; results generally agree and meet specification。\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e87.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eClear adulteration; low K/Al indicates Al-rich/K-deficient substitution. K-based alum content (65.5%) differs markedly from the national standard。\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eStoichiometrically consistent with potassium alum, but with low overall content; may indicate process issues or dilution\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, samples S1, S3, and S5 exhibited K/Al molar ratios close to 1 (0.99\u0026ndash;1.02). The alum contents calculated independently from Al and from K were in close agreement (difference\u0026thinsp;\u0026lt;\u0026thinsp;2%) and were broadly consistent with the national standard results, supporting the accuracy of the proposed method for authentic potassium alum. Notably, although S5 was classified as stoichiometrically consistent with potassium alum, its alum content (~\u0026thinsp;90.7%) was substantially lower than the typical purity of food additive\u0026ndash;grade alum (commonly\u0026thinsp;\u0026gt;\u0026thinsp;99.5%). This finding suggests potential shortcomings in manufacturing control or possible dilution, highlighting the need for strengthened quality assurance during production and procurement.\u003c/p\u003e \u003cp\u003eIn contrast, samples S2 and S4 clearly demonstrate the advantage of the proposed approach for adulteration detection. Sample S2 showed a K/Al molar ratio of ~\u0026thinsp;0.00, indicating an extreme case in which an Al-containing salt was used to masquerade as alum. Under this scenario, the national standard method reported 96.2%, which could be misinterpreted as \u0026ldquo;compliant,\u0026rdquo; whereas the K-based alum content was only 0.2%, confirming that Al-only conversion cannot identify such adulteration. Sample S4 exhibited a low K/Al ratio (0.76) and a large discrepancy (21.4 percentage points) between Al-based and K-based alum contents, indicating Al-rich/K-deficient substitution. The corrected (K-based) alum content was only 65.5%, representing substantial quality and integrity concerns.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Discussion","content":"\u003cp\u003eUnder adulteration conditions, the two approaches showed markedly different performance, underscoring the necessity of the proposed workflow. The national standard back-titration method measures only total aluminum and implicitly assumes that all Al originates from alum, resulting in a severely biased estimate for Al-rich substitution. For the 70% alum\u0026thinsp;+\u0026thinsp;30% sodium alum mixture, the reported value (~\u0026thinsp;98.5%) deviated from the true alum content (70%) by more than 28 percentage points. In regulatory practice, such a bias could lead to adulterated products being misclassified as compliant or even \u0026ldquo;high-purity,\u0026rdquo; creating a significant surveillance gap.\u003c/p\u003e \u003cp\u003eIn contrast, the ICP-MS approach simultaneously quantifies K and Al and uses the K/Al molar ratio (theoretical\u0026thinsp;\u0026asymp;\u0026thinsp;1) as the key decision metric, enabling effective authenticity screening (K/Al\u0026thinsp;=\u0026thinsp;0.71 for the sodium-alum mixture). Based on the rationale that potassium is the unique characteristic cation of potassium alum, the workflow then applies the appropriate conversion rule\u0026mdash;K-based conversion for Al-rich/K-deficient cases\u0026mdash;yielding an accurate estimate of true alum content (70.0%), consistent with the known formulation. Additionally, the difference between measured total Al and Al attributable to alum can be used to approximate the level of Al-containing adulterants (e.g., sodium alum), providing useful information for trace-back and enforcement.\u003c/p\u003e \u003cp\u003eFor K-salt adulteration (e.g., potassium sulfate), the workflow similarly flags abnormality through an elevated K/Al ratio (2.37) and corrects alum quantification by selecting the Al-based conversion under K-rich/Al-deficient conditions, while also offering preliminary inference on adulterant type. Notably, an implausibly high K-based converted \u0026ldquo;alum content\u0026rdquo; (e.g., \u0026gt;\u0026thinsp;100%) serves as an immediate red-flag output that is easy to interpret in routine screening. Because ICP-MS acquires multi-element data in a single run, additional elemental signals can be incorporated in future extensions for improved adulterant attribution.\u003c/p\u003e \u003cp\u003eFurthermore, the screening of commercially available alum products conducted in this study further demonstrates the practical value of the proposed method for detecting potential issues of insufficient purity and product adulteration. Because the conventional back-titration method measures total Al only and assumes it derives entirely from alum, it may fail for adulterated samples such as S2 and S4 (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) and can even yield misleading \u0026ldquo;pass\u0026rdquo; results. By contrast, the proposed workflow uses the K/Al molar ratio as an intrinsic consistency check to flag abnormal compositions\u0026mdash;either Al-rich/K-deficient (R\u0026thinsp;\u0026lt;\u0026thinsp;0.95) or K-rich/Al-deficient (R\u0026thinsp;\u0026gt;\u0026thinsp;1.05)\u0026mdash;and then applies the corresponding conversion rule (K-based or Al-based) to quantify the true alum content. This enables estimation of adulteration extent and provides a more reliable analytical basis for regulatory surveillance.\u003c/p\u003e \u003cp\u003eBecause the core of the proposed workflow is the simultaneous acquisition of Al and K followed by a stoichiometric consistency check, the approach is not inherently dependent on ICP-MS. For alum raw materials and their adulterated products, Al and K are typically present at relatively high levels; therefore, most multi-element analytical platforms capable of quantitative determination can meet the requirements for simultaneous measurement. When available, ICP-MS offers clear advantages, including high sensitivity and versatile interference-control strategies (e.g., collision/reaction cell operation), making it well suited to complex matrices and expanded multi-element screening.\u003c/p\u003e \u003cp\u003eIn routine or resource-limited laboratories, inductively coupled plasma\u0026ndash;optical emission spectrometry (ICP-OES) can also provide simultaneous quantification of Al and K with lower operating cost, reduced maintenance burden, and higher throughput. When implementing the workflow on ICP-OES, the following considerations are recommended: selection of spectral lines with minimal interference and appropriate background correction; suitable dilution and/or matrix matching for high-HCl media and samples with high total dissolved solids; and control of matrix effects using external calibration with internal standardization and/or standard addition as needed.\u003c/p\u003e \u003cp\u003eImportantly, regardless of whether ICP-MS or ICP-OES is used, the K/Al consistency threshold and the \u0026ldquo;missing characteristic element\u0026rdquo; correction rule proposed in this study can be directly applied, provided that linearity, precision, and recovery meet routine quality-control criteria. This enables cross-platform and multi-level adoption of the workflow.\u003c/p\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eThe comparative experiments demonstrate that the principal limitation of the current national standard back-titration method is that it measures total Al only and assumes all Al originates from potassium alum. This assumption leads to systematic positive bias when Al-rich/K-deficient substitutes are present. The workflow proposed here uses the K/Al molar ratio (R) as a dual-element consistency indicator to screen authenticity and then, for abnormal ratios, selects the conversion pathway based on a \u0026lsquo;missing characteristic element\u0026rsquo; principle to obtain corrected estimates for typical adulteration patterns. Compared with Al-only conversion, the workflow outputs both (i) a corrected quantitative estimate of true potassium alum content and (ii) an interpretable flag (R and Δ) that supports enforcement-oriented decision making. The approach is transferable to ICP-MS and other multi-element platforms (e.g., ICP-OES) after local verification of precision and recovery.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eZhiji Chen: Writing-original draft, Methodology, Investigation, Formal analysis. Li Wang: Formal analysis, Validation. Micong Jin: Conceptualization, Writing-review \u0026amp; editing, Validation, Resources, Supervision, Funding acquisition.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThis work was supported by the Ningbo Municipal Key Medical Discipline Construction Project (2022-B18), the Ningbo Medical and Health Brand Discipline Construction Project (PPXK2024-09), and the Zhejiang Science and Technology Plan for Disease Prevention and Control (Project No. 2026JKY219).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLiu YJ, Li CL, Meng Q (2023) Research progress on aluminum-containing food additives and their detection technologies and monitoring analysis. Food Ind Sci Technol 44(7):470\u0026ndash;474. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.13386/j.issn1002-0306.2022050366\u003c/span\u003e\u003cspan address=\"10.13386/j.issn1002-0306.2022050366\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang HW, Pang YH, Zhang SJ, Li SH (2021) Determination of trace aluminum in food additives by collision cell-ICP-MS. J Food Saf Qual Inspection 12(13):5191\u0026ndash;5195. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.19812/j.cnki.jfsq11-5956/ts.2021.13.015\u003c/span\u003e\u003cspan address=\"10.19812/j.cnki.jfsq11-5956/ts.2021.13.015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGB 2760\u0026ndash;2024 National Food Safety Standard\u0026mdash;Standard for Uses of Food Additives\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGB 1886.229\u0026ndash;2016 National Food Safety Standard\u0026mdash;Food Additive: Potassium Aluminum Sulfate (Alum)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang XL, Zhou ZH, Xing SW, Liu D, Hu YJ, He B, Ai X (2018) Determination of aluminum in dried kelp by microwave digestion\u0026ndash;ICP-OES. Food Ferment Technol 54(4):84\u0026ndash;86. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3969/j.issn.1674-506X.2018.04-017\u003c/span\u003e\u003cspan address=\"10.3969/j.issn.1674-506X.2018.04-017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe ZC, Yu JH, Zheng XC, Jiang YT (2017) Determination of aluminum in puffed foods by ICP-OES. Guangdong Trace Elements Science. 2017;24(6):11\u0026ndash;13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.16755/j.cnki.issn.1006-446x.2017.06.003\u003c/span\u003e\u003cspan address=\"10.16755/j.cnki.issn.1006-446x.2017.06.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGB 5009 182\u0026ndash;2017. National Food Safety Standard\u0026mdash;Determination of Aluminum in Foods\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"food-analytical-methods","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Food Analytical Methods](https://www.springer.com/journal/12161)","snPcode":"12161","submissionUrl":"https://submission.nature.com/new-submission/12161/3","title":"Food Analytical Methods","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"alum, inductively coupled plasma–mass spectrometry (ICP-MS), simultaneous determination of aluminum and potassium, authenticity/purity assessment, back titration","lastPublishedDoi":"10.21203/rs.3.rs-8850541/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8850541/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe zinc chloride back-titration procedure in GB 1886.229\u0026ndash;2016 converts total aluminum to alum content (reported as anhydrous AlK(SO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e on a dry basis) without measuring potassium, but it does not measure potassium and therefore lacks an internal Al\u0026ndash;K stoichiometric check and potentially missing adulteration-related inconsistencies (e.g., substitution with sodium/ferric alum or addition of potassium salts).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eAl and K were simultaneously quantified by ICP-MS. Alum content was independently calculated from Al and from K (as anhydrous AlK(SO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e, dry basis), and their agreement was assessed by both the K/Al molar ratio and a relative deviation metric (Δ = |C\u003csub\u003eK\u003c/sub\u003e - C\u003csub\u003eAl\u003c/sub\u003e| / ((C\u003csub\u003eK\u003c/sub\u003e + C\u003csub\u003eAl\u003c/sub\u003e)/2) \u0026times; 100%). Decision rules were pre-defined (R\u0026thinsp;=\u0026thinsp;K/Al molar ratio; Δ agreement metric) to classify stoichiometrically consistent vs. K-deficient or Al-deficient patterns and to select the appropriate conversion channel.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe workflow showed good linearity (r\u0026thinsp;\u0026gt;\u0026thinsp;0.9997), good precision (RSD\u0026thinsp;\u0026lt;\u0026thinsp;8%), and satisfactory spike recoveries (99.6\u0026ndash;107.8%). It enabled rapid screening and corrected quantification in typical adulteration scenarios, whereas the Al-only conversion in the national standard could substantially overestimate alum content under Al-rich substitution. Market samples and simulated adulteration mixtures were used to demonstrate screening sensitivity and quantification correction compared with GB 1886.229\u0026ndash;2016.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eBy operationalizing Al-K dual-element stoichiometric screening (K/Al and Δ-based agreement) and applying correction-based quantification for abnormal samples, this practical workflow addresses the analytical blind spot of Al-only conversion and provides a robust solution for routine quality control and regulatory surveillance of food additive alum.\u003c/p\u003e","manuscriptTitle":"A Dual-Element Stoichiometric-Consistency Workflow Using Simultaneous Al and K Measurement for Reliable Alum Assay and Adulteration Screening","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-04 11:06:35","doi":"10.21203/rs.3.rs-8850541/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-09T07:35:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-09T02:21:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"24869290332088391917879379592658108336","date":"2026-03-01T18:01:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-27T11:33:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-12T01:07:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-12T01:06:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Food Analytical Methods","date":"2026-02-11T10:04:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"food-analytical-methods","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Food Analytical Methods](https://www.springer.com/journal/12161)","snPcode":"12161","submissionUrl":"https://submission.nature.com/new-submission/12161/3","title":"Food Analytical Methods","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"67812772-5758-4f3a-a975-7bdd7fcc877a","owner":[],"postedDate":"March 4th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-26T09:38:51+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-04 11:06:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8850541","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8850541","identity":"rs-8850541","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}