Analysis of First Order Reversal Curves in the Thermal Hysteresis of Spin-crossover Nanoparticles within the Mechanoelastic Model
Laurentiu Stoleriu, Alexandru Stancu, Pradip Chakraborty, Andreas, Hauser, Cristian Enachescu

TL;DR
This paper uses the FORC method within a mechanoelastic model to analyze the thermal hysteresis of spin-crossover nanoparticles, revealing how size and interaction distributions influence transition behaviors and hysteresis width.
Contribution
It introduces a simulation-based approach applying FORC analysis to spin-crossover nanoparticles within a mechanoelastic framework, highlighting the effects of size and interaction distributions.
Findings
Larger particles significantly increase hysteresis width.
FORC distributions help distinguish kinetic and non-kinetic effects.
Size and elastic interaction distributions correlate with transition temperature variations.
Abstract
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…
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