Struct EntanglementModel 

pub struct EntanglementModel {
    pub density: f64,
    pub molecular_weight: f64,
    pub entanglement_mw: f64,
    pub temperature: f64,
    pub friction_coeff: f64,
    pub segment_length: f64,
}

Entanglement and reptation dynamics model.

Describes chain diffusion, plateau modulus, and Rouse-reptation crossover.

Fields

density: f64

Polymer density ρ [kg/m³]

molecular_weight: f64

Number-average molecular weight M_n [kg/mol]

entanglement_mw: f64

Entanglement molecular weight M_e [kg/mol]

temperature: f64

Temperature [K]

friction_coeff: f64

Monomeric friction coefficient ζ_0 [N·s/m]

segment_length: f64

Segment length b [m]

Implementations

impl EntanglementModel

pub fn new( density: f64, molecular_weight: f64, entanglement_mw: f64, temperature: f64, friction_coeff: f64, segment_length: f64, ) -> Self

Create entanglement model.

Arguments

• density - Polymer density [kg/m³]
• molecular_weight - Polymer M_n [kg/mol]
• entanglement_mw - Entanglement M_e [kg/mol]
• temperature - Temperature [K]
• friction_coeff - Monomeric friction coefficient [N·s/m]
• segment_length - Statistical segment length [m]

pub fn plateau_modulus(&self) -> f64

Plateau modulus G_N = ρRT / M_e [Pa].

pub fn entanglement_number(&self) -> f64

Number of entanglements per chain Z = M_n / M_e.

pub fn rouse_time(&self) -> f64

Rouse relaxation time: τ_R = ζ_0 * N² * b² / (6π² * kT).

pub fn reptation_time(&self) -> f64

Reptation (terminal) time: τ_d = 3 * Z³ * τ_e (simplified: τ_d ~ Z³ * τ_R).

pub fn diffusion_coefficient(&self) -> f64

Self-diffusion coefficient in reptation regime: D ~ kTM_e / (ζN²).

pub fn is_entangled(&self) -> bool

Is the chain entangled? (M_n > 2 * M_e is the common criterion)