Here we suggest that integral isoconversional method, when applied in a mathematically correct way, can lead to satisfactory results with the least number of adjustable parameters. Differential and incremental methods are used in cases when the apparent activation energy, , varies with the degree of conversion, . However, in some cases the observed () dependence can spuriously be induced by small variations in () curves and there is only little to no benefit gained from allowing arbitrary change of between adjacent conversion levels. As a result, the () dependences are highly “fragile” and subject to minor variations in the experimental data. On the other hand, when the activation energy is optimized globally for all isoconversional levels, a significantly more robust estimate is obtained and the agreement between the experimental and simulated data is still plausible. The approach is demonstrated on two datasets which were evaluated with both variable () dependence and with constant value of .

中文翻译：

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积分等转换方法的数学正确应用


在这里，我们建议积分等转换方法，当以数学上正确的方式应用时，可以用最少数量的可调参数获得令人满意的结果。当表观活化能 随转化程度 变化时，使用微分法和增量法。然而，在某些情况下，观察到的 () 依赖性可能是由 () 曲线的微小变化引起的，并且允许相邻转换级别之间的任意变化几乎没有获得任何好处。因此，() 依赖性非常“脆弱”，并且会受到实验数据的微小变化的影响。另一方面，当针对所有等转化水平对活化能进行全局优化时，获得了明显更稳健的估计，并且实验数据和模拟数据之间的一致性仍然合理。该方法在两个数据集上进行了演示，这两个数据集使用变量 () 依赖性和常数值 进行了评估。