  Segregation to defects, in particular to grain boundaries (GBs), is an
unavoidable phenomenon leading to changed material behavior over time. With the
increase of available computational power, unbiased quantum-mechanical
predictions of segregation energies, which feed classical thermodynamics models
of segregation (e.g., McLean isotherm), become available. In recent years, huge
progress towards predictions closely resembling experimental observations was
made by considering the statistical nature of the segregation process due to
competing segregation sites at a single GB and/or many different types of
co-existing GBs. In the present work, we further expand this field by
explicitly showing how compositional disorder, present in realistic engineering
alloys (e.g. steels or Ni-based superalloys), gives rise to a spectrum of
segregation energies. With the example of a $\Sigma 5$ GB in a Ni-based model
alloy (Ni-Co-Cr-Ti-Al), we show that the segregation energies of Fe, Mn, W, Nb
and Zr are significantly different from those predicted for pure elemental Ni.
We further use the predicted segregation energy spectra in a statistical
evaluation of GB enrichment, which allows for extracting segregation enthalpy
and segregation entropy terms related to the chemical complexity in
multi-component alloys.
