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A calibration curve plot showing limit of detection (LOD), limit of quantification (LOQ), dynamic range, and limit of linearity (LOL).. In analytical chemistry, a calibration curve, also known as a standard curve, is a general method for determining the concentration of a substance in an unknown sample by comparing the unknown to a set of standard samples of known concentration. [1]
Common anechoic chamber experiments include measuring the transfer function of a loudspeaker or the directivity of noise radiation from industrial machinery. In general, the interior of an anechoic chamber can be very quiet, with typical noise levels in the 10–20 dBA range. In 2005, the best anechoic chamber measured at −9.4 dBA. [2]
Once the presence of certain substances in a sample is known, the study of their absolute or relative abundance could help in determining specific properties. Knowing the composition of a sample is very important, and several ways have been developed to make it possible, like gravimetric [3] and volumetric analysis. Gravimetric analysis yields ...
This is a chamber freely open to atmosphere, where the fill gas is ambient air. The domestic smoke detector is a good example of this, where a natural flow of air through the chamber is necessary so that smoke particles can be detected by the change in ion current. Other examples are applications where the ions are created outside the chamber ...
The chamber pressure depends on the amount of propellant that has burned, the temperature of the gases, and the volume of the chamber. The burn rate of the propellant depends on the chemical make up and shape of the propellant grains. The temperature depends on the energy released and the heat loss to the sides of the barrel and chamber.
Recurrence quantification analysis (RQA) is a method of nonlinear data analysis (cf. chaos theory) for the investigation of dynamical systems. It quantifies the number and duration of recurrences of a dynamical system presented by its phase space trajectory.
It is generally accepted, that while label-free quantification is the least accurate of the quantification paradigms, it is also inexpensive and reliable when put under heavy statistical validation. There are two different methods of quantification in label-free quantitative proteomics: AUC (area under the curve) and spectral counting.
The range of quantification specifies the set of values that the variable takes. In the examples above, the range of quantification is the set of natural numbers. Specification of the range of quantification allows us to express the difference between, say, asserting that a predicate holds for some natural number or for some real number.