Bragg-Williams Calculator

Model mean-field ordering with clear parameter control. Explore equilibrium magnetization, free energy, and critical temperature. Export results instantly for reports, classes, and labs today.

Enter parameters and press Calculate to see results here.

Inputs

Use Joules for strict SI. eV is also supported and converted internally.

Nearest neighbors per site.
Must be positive.
Mean-field uses zJ in Tc.
Set to 0 for spontaneous ordering.
Between −1 and +1.
Higher helps near Tc.
Stop when |Δm| < tol.

Example Data

These sample rows illustrate typical inputs and the resulting equilibrium magnetization.

z T (K) J (J) H (J) Expected trend
6 300 1.0e-21 0 Often disordered if T > Tc
6 30 1.0e-21 0 More ordering as T decreases
8 300 3.0e-21 0 Higher Tc can allow ordering
6 300 1.0e-21 2.0e-22 Field biases magnetization sign
Tip: use a small nonzero H to pick a stable branch near Tc.

Formula Used

The Bragg-Williams mean-field condition treats spins as uncorrelated and replaces neighbors by an average magnetization. The equilibrium magnetization m satisfies the self-consistent equation:

m = tanh( (z·J·m + H) / (kB·T) )

A convenient free-energy density per spin (up to an additive constant) is:

f(m) = - (z·J/2)·m² - H·m + kB·T ·[ ((1+m)/2)·ln((1+m)/2) + ((1-m)/2)·ln((1-m)/2) ]

The calculator reports the equilibrium value m_eq, the critical temperature Tc = zJ/kB, the reduced temperature T/Tc, and the corresponding F, U, and S per spin.

How to Use This Calculator

  1. Enter z, T, and the coupling J in J or eV.
  2. Set H to zero for spontaneous ordering, or use a small bias.
  3. Choose an initial guess m0 if you expect a specific branch.
  4. Adjust max iterations and tolerance near criticality.
  5. Press Calculate and export results using CSV or PDF.

Bragg-Williams Mean-Field Modeling for Ordering

1) What the model represents

The Bragg-Williams approach is a mean-field description of cooperative ordering where each site interacts with an averaged neighborhood. In magnetic language, the order parameter is the magnetization per spin, m, constrained to the range −1 to +1. This calculator solves the self-consistent condition and reports thermodynamic quantities per spin to support quick comparison across materials, lattices, and temperature sweeps.

2) Core equation and parameters

The equilibrium condition uses m = tanh((zJm + H)/(kB T)), where z is the coordination number, J is the coupling energy, and H is the field-like bias term. The constant kB = 1.380649×10⁻²³ J/K anchors the temperature scale. Entering J in eV is supported using 1 eV = 1.602176634×10⁻¹⁹ J.

3) Critical temperature and lattice data

In this mean-field theory, the critical temperature is Tc = zJ/kB. Typical coordination numbers include simple cubic z = 6, body-centered cubic z = 8, and face-centered cubic z = 12. Increasing z or J raises Tc, making ordering possible at higher temperatures within the model assumptions.

4) Free energy, energy, and entropy outputs

The calculator evaluates a standard mean-field free-energy density per spin, combining an interaction term −(zJ/2)m², a bias contribution −Hm, and a mixing entropy term based on probabilities (1±m)/2. It also reports internal energy U and entropy S = (U − F)/T, helping you track energetic stabilization versus entropic disorder.

5) Reduced temperature for comparisons

The reduced temperature T/Tc enables data collapse across different lattices or couplings. Values above 1 typically yield small m when H = 0, while values below 1 can support nonzero solutions. For sensitivity studies, sweep T and keep z fixed, then compare the resulting m_eq and F.

6) Numerical stability near Tc

Close to Tc, convergence slows because the slope of the fixed-point map approaches unity. The solver uses damping to improve stability. If results appear branch-dependent, try a smaller nonzero H, increase max iterations, or provide a physically motivated initial guess m0, such as 0.01 for weak ordering or 0.8 for strongly ordered states.

7) Interpreting the field term

The parameter H biases the sign and magnitude of m. With H > 0, solutions tend toward positive magnetization, and with H < 0 they tend negative. Using a small bias is a practical way to select a stable branch when multiple solutions exist below Tc.

8) Practical workflow and exports

Start with lattice-appropriate z, select a physically plausible J, and compute Tc to plan your temperature range. Then run a series of temperatures and export each result to CSV for plotting m_eq versus T/Tc, or to PDF for documentation. This supports quick lab-style reporting and consistent classroom demonstrations.

FAQs

1) What does Bragg-Williams assume?

It assumes each site feels an average neighborhood, so correlations are neglected. This simplifies interactions into a mean-field term using the order parameter m.

2) Why can there be multiple solutions below Tc?

Below Tc the free-energy landscape can develop two symmetry-related minima. Small changes in m0 or H may select different stable branches with similar magnitude but opposite sign.

3) How should I choose z?

Use the coordination number for your lattice: simple cubic 6, body-centered cubic 8, and face-centered cubic 12 are common. If unknown, start with 6 and test sensitivity.

4) What units should J and H use?

Use Joules for strict SI. You may also enter eV, which is converted internally using 1 eV = 1.602176634×10⁻¹⁹ J.

5) Why does convergence slow near Tc?

Near criticality, the self-consistency map becomes nearly tangent to the identity line. Increasing iterations, tightening tolerance carefully, or adding a tiny bias H improves stability.

6) Are F, U, and S absolute values?

They are per-spin quantities within a chosen reference, so an additive constant may differ between conventions. Trends versus temperature and parameter changes are the most meaningful outputs.

7) What should I export for plotting?

Export m_eq and T/Tc to build a reduced curve, and include F to compare stability. CSV is convenient for spreadsheets, while PDF is useful for reports and sharing.

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