1951
DOI: 10.1021/ed028p123
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The origins of Beer's law

Abstract: Traces the development of Beer's law by examining Beer's original, 1852 paper on the subject.

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Cited by 71 publications
(32 citation statements)
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“…These objectives are formalized as a source separation problem, where the linear instantaneous mixture model holds. In the case of optical spectroscopy, this model is validated according to Beer-Lambert law [4] (also termed as Beer's law or BeerLambert-Bouguer law [5]). The pure component spectra are identified as the estimated sources and the concentrations as the mixing coefficients.…”
Section: Introductionmentioning
confidence: 99%
“…These objectives are formalized as a source separation problem, where the linear instantaneous mixture model holds. In the case of optical spectroscopy, this model is validated according to Beer-Lambert law [4] (also termed as Beer's law or BeerLambert-Bouguer law [5]). The pure component spectra are identified as the estimated sources and the concentrations as the mixing coefficients.…”
Section: Introductionmentioning
confidence: 99%
“…8 For the first 0.2ps, the particles were damped to T 0 , followed by a relaxation period of 0.8ps which as shown in Figure 2(b), the laser was starting at t=1.0ps. The laser energy was deposited on each atom according to the Lambert–Beer’s law 14 where R is the surface reflectivity of silicon, I 0 is the initial laser intensity and α is the linear absorption coefficient of silicon. For the present simulation, the silicon was divided into several layers along the direction of laser.…”
Section: Simulation Modelmentioning
confidence: 99%
“…As a consequence, December [9]). The data processing corresponds to a source separation problem where the linear instantaneous mixture model holds with relatively small concentrations of the components in absorption spectroscopy, thanks to the Beer-Lamber law [10].…”
Section: ) Mixing Modelsmentioning
confidence: 99%
“…, y N ) denotes the mutual information between the estimated signals y(n). There are several algorithms for solving (10), where main difficulties are related to the estimation of the mutual information and to the existence of spurious local minima in this cost function. In [50], for instance, December 19, 2013 DRAFT the optimization problem expressed in (10) was tackled by a bio-inspired optimization method that is robust to convergence to local minima and that does not require the calculation of the derivatives of (10).…”
Section: A Nonlinear Independent Component Analysismentioning
confidence: 99%