Spectroscopy
Beer's Law Calculator
A = ε·b·c live: read absorbance and %T from concentration, path length and molar absorptivity — then add stray light and a polychromatic beam to see real calibration curves bend from the ideal line.
Open model → InteractivePhotometric Error
Why measurement precision depends on where you read: relative concentration error vs absorbance across the three noise regimes, and the optimal-absorbance sweet spot near A ≈ 0.4.
Open model → InteractiveCalibration Methods
External-standard vs standard-addition on one plot: fit standards, recover an unknown, and watch a matrix effect bias one method while the other still lands on the truth.
Open model → InteractiveTransmission Fitting (TFit)
The capstone: fit the transmission model instead of taking log(I₀/I) and get hyperlinear absorbance — a straight line over a 10,000× range where the classic methods roll off.
Open model →All four models explore the same measurement: how a spectrophotometer turns light absorbed by a sample into a concentration. Beer's Law lays out the underlying equation, A = ε·b·c. Photometric Error asks how far you can trust a given reading once instrument noise is factored in, and finds the absorbance where that noise hurts you least. Calibration Methods compares two ways to build the working curve, including the case where the sample's own matrix interferes with the signal. Transmission Fitting goes furthest, replacing the textbook log(I₀/I) definition itself with a model fit that removes the stray-light and finite-bandwidth errors baked into the ordinary method. Together they cover the theory behind an absorbance reading and the real instrumental limits that separate it from that theory.