Abstract Traditional processing of Mӧssbauer spectroscopy measurements assumes a decomposition of the spectra into separate multiplets corresponding to particular non-equivalent states of the resonance atom. When the number of spectra is large (e.g. in kinetic, corrosion and phase transition studies), this procedure becomes time-consuming. Moreover, traditional processing assumes some hypotheses on the number of non-equivalent states and initial multiplet parameters. The results of the processing strongly depend on these hypotheses and may be quite subjective. In an attempt to circumvent this issue, we studied the potential of Multivariate curve resolution (MCR) to unravel mixed multiplets spectra into their individual contributions. The application of MCR to Mӧssbauer studies was found to be quite challenging due to 1) long acquisition times limiting the number of available samples, 2) presence of critical spectral overlaps and 3) occasional deviations from the ideal bilinear assumption. In this report, we show how these limitations can be circumvented under certain conditions.

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关于 Mӧssbauer 光谱研究中多元曲线分辨率的潜力和局限性

摘要 Mӧssbauer 光谱测量的传统处理假设将光谱分解为对应于共振原子的特定非等效状态的单独多重峰。当光谱数量很大时（例如在动力学、腐蚀和相变研究中），这个过程会变得很耗时。此外，传统处理对非等效状态的数量和初始多重态参数假设了一些假设。处理的结果强烈依赖于这些假设并且可能非常主观。为了规避这个问题，我们研究了多元曲线分辨率 (MCR) 的潜力，将混合多重峰光谱分解为它们各自的贡献。由于 1) 长采集时间限制了可用样本的数量，2) 存在临界光谱重叠以及 3) 偶尔偏离理想的双线性假设，因此发现将 MCR 应用于 Mӧssbauer 研究非常具有挑战性。在本报告中，我们展示了如何在特定条件下规避这些限制。