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Beer-Lambert Calculator.

Calculate concentration, absorbance, or molar absorptivity using Beer-Lambert law (A = εlc). Includes nucleic acid quantification and common chromophore database.

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Validated2026-04-05
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When to use

  • Determine analyte concentration from a known absorbance reading and extinction coefficient
  • Predict expected absorbance before running a spectrophotometry experiment
  • Look up molar absorptivity values for common chromophores, dyes, and proteins
  • Quantify DNA or RNA concentration from A260/A280 readings
  • Batch-convert absorbance readings at multiple wavelengths to concentrations

Do not use for

  • For turbid or scattering samples without prior clarification — absorbance includes apparent scatter
  • When absorbance exceeds 2.0 — dilute first and re-measure
  • As a substitute for a validated standard curve in regulated assays

Always blank your spectrophotometer with the correct solvent

The blank must match the sample matrix (solvent, buffer, cuvette type). A mismatched blank introduces systematic offset in every reading. For nucleic acids, blank with the elution buffer, not water.

Extinction coefficients are wavelength- and solvent-specific

Literature ε\varepsilon values are measured at a specific wavelength in a specific solvent. Using an ε\varepsilon measured in water for a sample in DMSO, or at 280 nm instead of 260 nm, will give incorrect concentrations.

Path length is NOT always 1 cm

Microvolume instruments like NanoDrop use 0.05–1 mm path lengths. Microplate readers have variable path lengths depending on well volume. Always verify and enter the actual path length.

The A260/A280 ratio is not a purity assay

While A260/A280 \approx 1.8 suggests pure DNA, contamination with co-absorbing substances at both wavelengths (e.g., some phenolic compounds) can yield a “normal” ratio. Gel electrophoresis or fluorometric quantification provides better purity assessment.

1

Method

Direct algebraic solution of the Beer-Lambert equation (A=εlcA = \varepsilon l c). Nucleic acid quantification uses consensus conversion factors (dsDNA: 50 µg/mL per A260, ssDNA: 33, RNA: 40). Extinction coefficients sourced from primary literature and standard biochemistry references.

2

Validated

Last validated 2026-04-05. Calculations are designed for planning and documentation support; verify procurement decisions against manufacturer specifications or institutional SOPs.

3

How to cite

How to Cite

ConductScience Beer-Lambert Calculator (v1.0). ConductScience, Inc. 2026. Available at: https://conductscience.com/tools/beer-lambert-calculator

Beer A. Bestimmung der Absorption des rothen Lichts in farbigen Flüssigkeiten. Ann Phys. 1852;162(5):78–88.

Schmid FX. Biological Macromolecules: UV-visible Spectrophotometry. In: eLS. Wiley; 2001.

Beer-Lambert Law Fundamentals

The Beer-Lambert law relates the attenuation of light to the properties of the material through which it travels:

A=ε×l×cA = \varepsilon \times l \times c

Where: • A = Absorbance (unitless, also called optical density) • ε = Molar absorptivity (Lmol1cm1\text{L} \cdot \text{mol}^{-1} \cdot \text{cm}^{-1}) • l = Path length through the sample (cm) • c = Molar concentration (mol/L)

Absorbance is defined as A = –log₁₀(T), where T is transmittance (I/I₀). This means A = 1 corresponds to 10% transmittance, and A = 2 corresponds to 1% transmittance. The linear relationship holds for dilute, homogeneous solutions of non-interacting chromophores.

Common Pitfalls in Spectrophotometry

Several factors can cause deviations from Beer-Lambert linearity:

High concentration: Molecular interactions and aggregation change the effective ε • Stray light: Instrument imperfections add a constant signal, compressing high-absorbance readings • Scattering: Turbid samples scatter light, mimicking absorbance • Chemical equilibria: pH-dependent speciation can shift with concentration (e.g., indicator dyes) • Fluorescence: Re-emitted photons reach the detector, reducing apparent absorbance • Wrong wavelength: Measuring off-peak reduces sensitivity and may introduce nonlinearity

Best practice: run a standard curve at your exact conditions and verify linearity before quantifying unknowns.

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