  The recently obtained spin-crossover nanoparticles are possible candidates
for applications in the recording media industry as materials for data storage,
or as pressure and temperature sensors. For these applications the
intermolecular interactions and interactions between spin-crossover
nanoparticles are extremely important, as they may be essential factors in
triggering the transition between the two stable phases: the high-spin and
low-spin ones. In order to find correlations between the distributions in size
and interactions and the transition temperatures distribution, we apply the
FORC (First Order Reversal Curves) method, using simulations based on a
mechanoelastic model applied to 2D triangular lattices composed of molecules
linked by springs and embedded in a surfactant. We consider two Gaussian
distributions: one of the size of the nanoparticles and one of the elastic
interactions between edge spin-crossover molecules and the surfactant
molecules. In order to disentangle the kinetic and non-kinetic parts of the
FORC distributions, we compare the results obtained for different temperature
sweeping rates. We also show that the presence of few larger particles in a
distribution centered around much smaller particles dramatically increases the
hysteresis width.
