Sulfur isotope ratios are among the most commonly studied isotope systems in geochemistry. While sulfur isotope ratio analyses of materials such as bulk rock samples, gases, and sulfide grains are routinely carried out, in-situ analyses of silicate glasses such as those formed in magmatic systems are relatively scarce in the literature. Despite a number of attempts in recent years to analyse sulfur isotope ratios in volcanic and experimental glasses by secondary ion mass spectrometry (SIMS), the effects of instrumental mass fractionation (IMF) during analysis remain poorly understood. In this study we use more than 600 sulfur isotope analyses of nine different glasses to characterise the matrix effects that arise during sulfur isotope analysis of glasses by SIMS. Samples were characterised for major element composition, sulfur content, and sulfur isotope ratios by independent methods. Our glasses contain between 500 and 3400 ppm sulfur and cover a wide compositional range, including low-silica basanite, rhyolite, and phonolite, allowing us to investigate composition-dependent IMF. We use SIMS in multi-collection mode with a Faraday cup/electron multiplier detector configuration to achieve uncertainty of 0.3‰ to 2‰ (2σ) on measured δ³⁴S. At high sulfur content, the analytical error of our SIMS analyses is similar to that of bulk analytical methods, such as gas-source isotope ratio mass spectrometry. We find IMF causes an offset of −12‰ to +1‰ between bulk sulfur isotope ratios and those measured by SIMS. Instrumental mass fractionation correlates non-linearly with glass sulfur contents and with a multivariate regression model combining glass Al, Na, and K contents. Both ln(S) and Al-Na-K models are capable of predicting IMF with good accuracy: 84% (ln(S)) and 87% (Al-Na-K) of our analyses can be reproduced within 2σ combined analytical uncertainty after a correction for composition-dependent IMF is applied. The process driving IMF is challenging to identify. The non-linear correlation between glass S content and IMF in our dataset resembles previously documented correlation between glass H₂O abundance and IMF during D/H ratio analyses by SIMS, and could be attributed to changes in ³²S⁻ and ³⁴S⁻ ion yields with changing S content and glass composition. However, a clear correlation between S ion yields and S content cannot be identified in our dataset. We speculate that accumulation of alkalis at the SIMS crater floor may be the principal driving force of composition-dependent IMF. Nonetheless, other currently unknown factors could also influence IMF observed during S isotope ratio analyses of glasses by SIMS. Our results demonstrate that the use of multiple, well-characterised standards with a wide compositional range is required to calibrate SIMS instruments prior to sulfur isotope analyses of unknown silicate glasses. Matrix effects related to glass Al-Na-K contents are of particular importance for felsic systems, where alkali and aluminium contents can vary considerably more than in mafic magmas.

硫同位素比是地球化学中最常研究的同位素系统之一。虽然通常对诸如块状岩石样品，气体和硫化物颗粒之类的材料进行硫同位素比分析，但在文献中对硅酸盐玻璃（如在岩浆系统中形成的硅酸盐玻璃）的原位分析相对较少。尽管近年来进行了许多尝试通过二次离子质谱（SIMS）分析火山玻璃和实验玻璃中硫同位素比的尝试，但在分析过程中仪器质量分数（IMF）的影响仍然知之甚少。在这项研究中，我们使用了九种不同玻璃的600多种硫同位素分析来表征SIMS对玻璃的硫同位素分析过程中产生的基质效应。对样品进行了主要元素组成，硫含量，和硫同位素比采用独立方法。我们的玻璃含有500至3400 ppm的硫，并且覆盖范围很广的成分，包括低硅质硅钙石，流纹岩和方沸石，这使我们能够研究与成分有关的IMF。我们在法拉第杯/电子倍增检测器配置的多收集模式下使用SIMS，以实现0.3‰至2‰（2σ）上测得的δ ³⁴ S.在高的硫含量，我们的SIMS的分析误差分析类似于散装的分析方法，诸如气源同位素比质谱法。我们发现，IMF导致大体积硫同位素比与SIMS测量值之间的偏移为-12‰至+ 1‰。仪器的质量分数与玻璃硫含量和玻璃铝，钠和钾含量的多元回归模型非线性相关。ln（S）模型和Al-Na-K模型均能够准确预测IMF：我们的分析中84％（ln（S））和87％（Al-Na-K）可以在2σ内重现对成分相关的IMF进行校正后，合并的分析不确定性将被应用。确定IMF的过程具有挑战性。在我们的数据集中酷似玻璃S含量和IMF之间的非线性关系以前记录的Glass H.之间的相关性₂ IMF中d / H比值由SIMS分析Ó丰度和，并且可能归因于在变化³²小号^-和³⁴小号^-随着S含量和玻璃组成的变化，离子产率也会提高。但是，在我们的数据集中无法确定S离子产率与S含量之间的明确关联。我们推测，SIMS火山口底部的碱积累可能是依赖成分的IMF的主要驱动力。但是，其他目前未知的因素也可能会影响通过SIMS分析玻璃的S同位素比时观察到的IMF。我们的结果表明，在未知硅酸盐玻璃的硫同位素分析之前，需要使用多种具有广泛成分特征的标准品来校准SIMS仪器。与玻璃Al-Na-K含量有关的基体效应对于长素体系统尤为重要，在长素体系统中，碱金属和铝含量的变化远大于镁铁质岩浆中的变化。