Open AccessMisuse of Beer–Lambert Law and other calibration curves
Author(s) -
Rosario Delgado
Publication year - 2022
Publication title -
royal society open science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 51
ISSN - 2054-5703
DOI - 10.1098/rsos.211103
Subject(s) - calibration curve , calibration , beer–lambert law , sample (material) , analyte , line (geometry) , absorbance , reading (process) , systematic error , computer science , law , statistics , mathematics , optics , physics , chemistry , chromatography , geometry , political science , detection limit
Calibration curves allow instrument calibration by predicting the concentration of an analyte in a sample from the reading of the instrument. This curve is constructed as the regression straight line that best fits the relationship between some known concentration standards and their respective instrument readings. An example is the Beer–Lambert Law, used to predict the concentration of a new sample from its absorbance obtained by spectrometry. The issue is that usually this methodology is misapplied. In this paper, we want to clarify this point, explaining what the error consists of and how (easily) to fix it, with the intention of ensuring that it does not continue to be reproduced in the experimental scientific work.