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Stern–Volmer Analysis

Fit Stern–Volmer responses with the same layered model system and publication export workflow.

1. Data Input

Upload a file with two columns: first column = [H]₀ / mM, second column = F₀ / F.
A header row is allowed and will be ignored automatically.

2. Model Presets

3. Set Parameters

Kd
Fix
Dissociation Constant Host-Dye (range: 0.1 nM – 100 mM)
Stoichiometry (n)
Fix
For 1:1 Exact and 1:1 Hill Approximation models, n is fixed to 1. For Hill Empirical, this control becomes the Hill exponent h.
α (Fractional Dimness)
Fix
α = relative brightness of the bound state (0–2; α > 1 means bound state is brighter).
kq·τ0 / mM⁻¹
Fix
kq·τ0 = dynamic quenching parameter (0.0001–100; log slider).
Weighted Fitting
Optional weighting for heteroscedastic Stern–Volmer noise.

4. Fit and Update

Tip: click a point in the residual plot to exclude or restore it from the fit.
Stern–Volmer Model:
\[ \frac{F_0}{F} = \frac{1 + k_q\tau_0[H]_{\mathrm{free}}}{1-\theta(1-\alpha)} \]

Binding / Occupancy Model:
\[ \theta = \frac{([I]_0+[H]_0+K_d)-\sqrt{([I]_0+[H]_0+K_d)^2 - 4[I]_0[H]_0}}{2[I]_0} \]

Free host term:
\[ [H]_{\mathrm{free}} = [H]_0 - \theta[I]_0 \]

5. Fit Report

Model output
Fit summary, parameter estimates, and quality notes will appear here after you update the model.
6. Final Figure
Preset and layout
Journal theme: Style:
Journal theme and Column now both trigger the matching preset values. Width stays tied to the active journal/column preset even when stats block or residual analysis is changed.
Manual sizing and output
Width: mm Height: mm DPI:
Axis/frame scale: Font scale:
Stats block: Residual:
Fitting Strategy:
1. Start from the two-layer preset that best matches your expected binding model and quenching behavior.
2. Use simpler constrained presets first, then unlock more parameters only if residuals remain structured.
3. For independent n-Sites, consider fixing n initially. For Hill fits, treat h as empirical.
4. Ensure residuals scatter randomly around zero before interpreting the fitted mechanism.
Hongbin Wu AG Cordes / TU Dortmund hongbin.wu@tu-dortmund.de