Nukleationskerns

Nukleationskerns is a term used in materials science and physical chemistry to denote a mathematical or computational construct that characterizes the initiation of nucleation events in a supersaturated or undercooled system. A nucleation kernel describes how likely it is for a stable nucleus of a given size to form and to grow, serving as a building block in models of nucleation rates and early-stage phase transformation. In practice, kernels can be used as functions K(n) that assign a probability density or rate to the appearance of nuclei containing n atoms or molecules, taking into account factors such as temperature, supersaturation, interfacial energy, and attachment dynamics.

In classical nucleation theory, the kernel is related to the attachment frequency and the Boltzmann factor of crossing the nucleation barrier. In stochastic and phase-field simulations, kernels provide the local propensity for nucleation events, often implemented as spatially distributed probabilities or as a source term in partial differential equations. Common forms include Gaussian, exponential, or log-normal distributions over nucleus size or time, but the specific form depends on the system and data.

Applications include crystallization in alloys and glasses, vapor-phase condensation, and cloud microphysics, where accurate kernels improve predictions of nucleation rates and particle size distributions. Kernels are typically derived from experiments, molecular dynamics simulations, or analytical approximations, and may be tuned to reproduce observed nucleation rates.

Nukleationskerns is sometimes used interchangeably with words like nucleation kernel, nucleation rate kernel, or seed distribution in the literature. The concept is connected to broader ideas such as critical nuclei, nucleation barriers, and growth kinetics.