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紫外-可见吸收光谱结合高斯多峰拟合技术测定甲基红酸离解常数(英文) 被引量:10

Determination of Acid Dissociation Constant of Methyl Red by Multi-Peaks Gaussian Fitting Method Based on UV-Visible Absorption Spectrum
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摘要 在一定pH值范围内,甲基红(MR)水溶液紫外-可见吸收光谱特征是酸式甲基红(HMR)最大吸收峰((530±15)nm)与碱式甲基红(MR-)最大吸收峰((435±20)nm)叠合在一起.本文用高斯多峰拟合技术实现了HMR和MR-叠合峰的分峰拟合计算.拟合计算输出两个吸收峰的积分面积即峰强度A1和A2,A1和A2之比与MR-和HMR浓度之比.进而计算甲基红水溶液酸离解平衡常数pKa.用本方法测量298.15K时的pKa值为4.76.拟合优度高,拟合度R2、拟合优度χ2分别达到0.998和10-5以下.深入探讨了表面活性剂十二烷基硫酸钠(SDS)、十六烷基三甲基溴化铵(CTAB)聚集行为对甲基红pKa的影响.与传统分光光度测量方法相比,紫外-可见吸收光谱结合高斯多峰拟合技术结果更可靠,测量步骤和数据处理过程更简单,更具有普适性. UV-visible electronic absorption spectra of methyl red(MR)aqueous solutions are characterized by the overlap of a principal peak atλ max((520±15)nm)with a shoulder peak atλ max((435±20)nm),which are assigned to acidic species(HMR)and basic species of methyl red,respectively.In this study,the spectra and the integrated absorbance of the MR-and HMR peaks(denoted A 1 and A 2,respectively)were interpreted using a new multi-peaks Gaussian fitting method.From the absorbance ratio A 1 /A 2 and the concentration ratio c MR-/c HMR,the average acid dissociation constant(pK a)was determined as 4.76 at 298.15 K.The goodness is high and the values of R 2(degree of fitting)andχ 2(chi-square test for goodness of fit) were 0.998 and below 10-5,respectively.The effects of aggregation behavior of sodium dodecyl sulfate(SDS)and cetylammonium bromide(CTAB)on pK a were also investigated via this method.The multi-peaks Gaussian fitting method was shown to determine pK a more reliably and simply than traditional spectrophotometric techniques.
出处 《物理化学学报》 SCIE CAS CSCD 北大核心 2012年第5期1030-1036,共7页 Acta Physico-Chimica Sinica
基金 The project was supported by the National Natural Science Foundation of China(20903028) Scientific Research Foundation for Returned Scholars from Ministry of Education of China,and Scientific Research Foundation for Yangcheng Scholar,China(10A041G)~~
关键词 甲基红 紫外-可见吸收光谱 叠合峰 酸离解常数 高斯多峰拟合 Methyl red UV-visible absorption spectrum Overlap peak Acid dissociation constant Multi-peaks Gaussian fitting
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