We present a numerical method to compute non-equilibrium memory kernels based on experimental data or molecular dynamics simulations. The procedure uses a recasting of the non-stationary generalized Langevin equation, in which we expand the memory kernel in a series that can be reconstructed iteratively. Each term in the series can be computed based solely on knowledge of the two-time auto-correlation function of the observable of interest. As a proof of principle, we apply the method to crystallization from a super-cooled Lennard Jones melt. We analyze the nucleation and growth dynamics of crystallites and observe that the memory kernel has a time extent that is about one order of magnitude larger than the typical timescale needed for a particle to be attached to the crystallite in the growth regime.

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Recently, the reversible heat production during the electric double layer (EDL) buildup in a sodium chloride solution was measured experimentally [Janssen et al., Phys. Rev. Lett. 119, 166002 (2017)] and matched with theoretical predictions from density functional theory and molecular dynamics simulations [Glatzel et al., J. Chem. Phys. 154, 064901 (2021)]. In the latter, it was found that steric interactions of ions with the electrode’s walls, which result in the so-called Stern layer, are sufficient to explain the experimental results. As only symmetric ion sizes in a restricted primitive model were examined, it is instructive to investigate systems of unequal ion sizes that lead to modified Stern layers. In this work, we explore the impact of ion asymmetry on the reversible heat production for each electrode separately. In this context, we further study an extension of the primitive model where hydration shells of ions can evade in the vicinity of electrode’s walls. We find a strong dependence on system parameters such as particle sizes and the total volume taken by particles. Here, we even found situations where one electrode was heated and the other electrode was cooled at the same time during charging, while, in sum, both electrodes together behaved very similarly to the already mentioned experimental results. Thus, heat production should also be measured in experiments for each electrode separately. By this, the importance of certain ingredients that we proposed to model electrolytes could be confirmed or ruled out experimentally, finally leading to a deeper understanding of the physics of EDLs.

We study marginally compact macromolecular trees that are created by means of two different fractal generators. In doing so, we assume Gaussian statistics for the vectors connecting nodes of the trees. Moreover, we introduce bond-bond correlations that make the trees locally semiflexible. The symmetry of the structures allows an iterative construction of full sets of eigenmodes (notwithstanding the additional interactions that are present due to semiflexibility constraints), enabling us to get physical insights about the trees' behavior and to consider larger structures. Due to the local stiffness the self-contact density gets drastically reduced.

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