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Fick's Second Law of Diffusion

Fick's second law describes how a concentration profile changes over time when diffusion is not steady. It says the rate of change of concentration equals D times the second derivative of concentration with respect to distance. For example, it predicts how deep carbon penetrates into steel during carburising, or how dopants spread in silicon during annealing. It is solved numerically or with error functions for practical diffusion problems.

Materials Science Diffusion Process Design

Fick's Second Law Calculator∂C/∂t = D · ∂²C/∂x²

dC/dt = D · d²C/dx²
dC/dt = temporal gradient (mol/m³·s)  ·  D = diffusion coefficient (m²/s)  ·  d²C/dx² = spatial curvature (mol/m⁵)
⟹ Solve⟷dC/dt, D, d²C/dx²
m²/s
mol/m⁵
mol/m³·s
Please fix the errors above.
Solve for:
Presets:
Temporal Gradient—
—
D: —d²C/dx²: —dC/dt: —
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Rate of Change Gauge—
Slow (< 1) Moderate (1–100) Rapid (> 100)
∂C/∂t = D · ∂²C/∂x²  ·  Describes how concentration changes over time due to diffusion

Variables

Symbol Quantity Unit
dC/dt Rate of change of concentration with time
D Diffusion coefficient m2/s
d2C/dx2 Second spatial derivative of concentration

What it means

Fick’s second law is the differential equation that describes how the concentration C changes with time t and position x during non‑steady‑state diffusion: ∂C/∂t = D ∂²C/∂x². It is derived from Fick’s first law and the conservation of mass. Solving this equation with appropriate initial and boundary conditions (e.g., error function solutions) allows prediction of concentration profiles after a given time. This is crucial for designing diffusion treatments, such as case hardening (carburising, nitriding), homogenisation of alloys, and dopant diffusion in semiconductors. It is also used in modelling corrosion, diffusion in polymers, and biological systems. Understanding Fick’s second law is essential for materials engineers and chemical engineers to control processing parameters and achieve desired compositions.

Worked example

Fick's Second Law – Two Examples

Real‑World
Scenario: A carburising process for steel uses D = 1×10⁻¹¹ m²/s for 2 hours. The heat treatment engineer needs to estimate the diffusion depth using the approximation √(Dt) to determine if the case depth meets the specification.
ParameterValue
D1×10⁻¹¹ m²/s
t2 hours = 7200 s
1Diffusion depth ≈ √(D×t) = √(1e-11 × 7200) = √(7.2e-8) = 2.68×10⁻⁴ m ≈ 0.27 mm
Result 0.27 mm ✓ Shallow case
Scenario: Dopant diffusion in silicon at D = 1×10⁻¹² m²/s for 4 hours. The semiconductor engineer estimates the diffusion length to ensure proper junction depth in a transistor fabrication process.
ParameterValue
D1×10⁻¹² m²/s
t4 hours = 14400 s
1Diffusion depth ≈ √(1e-12 × 14400) = √(1.44e-8) = 1.2×10⁻⁴ m = 0.12 mm
Result 0.12 mm ✓ Deeper
Materials insight: Fick's second law describes how concentration changes with time. Diffusion length scales as √(Dt), which is useful for estimating case depths in heat treatment.

Common mistakes

  • Fick’s second law: ∂C/∂t = D·∂²C/∂x² – describes non‑steady‑state (transient) diffusion.
  • Partial derivatives: Use partial differential equations – not ordinary derivatives.
  • D: Assume D is constant (independent of concentration) – otherwise, the equation becomes non‑linear.
  • Boundary conditions: Solutions depend on initial and boundary conditions – choose the appropriate solution (e.g., error function for infinite source).
  • Units: C in mol/m³, t in s, x in m, D in m²/s.

Applications

Fick's second law (∂C/∂t = D·∂²C/∂x²) describes transient diffusion, enabling the prediction of concentration changes over time. It is used to model diffusion in non‑steady‑state conditions, such as during heat treatment, carburising, and homogenisation of alloys. Engineers use it to determine the diffusion time required to achieve a desired case depth, to simulate the concentration profile, and to design schedules for heat treatments. It is also applied in the study of corrosion, sintering, and material degradation. By solving Fick's second law with appropriate boundary conditions, materials engineers can control diffusion processes to enhance surface properties and overall performance.

  • Carburising and nitriding process design for case hardening
  • Homogenisation heat treatments for cast alloys
  • Diffusion in semiconductors and thin‑film deposition
  • Hydration and drying of polymers and ceramics
  • Prediction of diffusion‑controlled phase transformations