Multivariate self-modeling curve resolution (SMCR) methods are the best choice for analyzing chemical data when there is not any prior knowledge about the chemical or physical model of the process under investigation [[1Q3: The reference ‘1’ is only cited in the abstract and not in the text. Please introduce a citation in the text.]]. However, the rotational ambiguity is the main problem of SMCR methods, yielding a range of feasible solutions. It is, therefore, important to determine the range of all feasible solutions of SMCR methods. Different methods have been presented in the literature to find feasible solutions of two, three, and four component systems. Here, a novel simple SMCR method is presented for calculating the boundaries of feasible solutions of two-component systems.

At first, the simple strategy is presented for calculating the feasible solutions of two-component systems. Next, four different experimental two-component systems are analyzed in detail for calculating the boundaries of feasible solutions in both spaces, including complex formation equilibrium, keto-enol tautomerization kinetic, lipidomics data, and a case for quantification of an analyte in gray systems. In all cases, the boundaries of range of feasible solutions are properly determined by the proposed simple strategy.

如果没有关于所研究过程的化学或物理模型的任何先验知识，则多变量自建模曲线分辨率（SMCR）方法是分析化学数据的最佳选择[[1Q3：参考文献'1'仅在摘要而不是文字。请在本文中引入引文。]]。但是，旋转歧义性是SMCR方法的主要问题，产生了一系列可行的解决方案。因此，重要的是确定SMCR方法的所有可行解决方案的范围。文献中提出了不同的方法来找到两个，三个和四个组件系统的可行解决方案。在这里，提出了一种新颖的简单SMCR方法来计算两组分系统可行解的边界。

首先，提出了一种简单的策略来计算两部件系统的可行解。接下来，详细分析了四个不同的实验两组分系统，以计算两个空间中可行溶液的边界，包括复杂的地层平衡，酮-烯醇互变异构动力学，脂质组学数据以及灰色系统中分析物定量的情况。在所有情况下，通过所提出的简单策略都可以适当确定可行解范围的边界。