Publications by authors named "Aris Marcolongo"

Article Synopsis
  • The study highlights the challenges of calculating ionic transport properties through traditional methods, which can be costly and inefficient.
  • A new approach using spectral decomposition of ionic displacement covariance is introduced, offering a way to identify diffusion eigenmodes that capture the correlation structure of ionic movements.
  • The method is validated with mathematical proofs and applied to practical electrolyte materials, showing its effectiveness in reducing uncertainty and speeding up calculations of ionic conductivity.
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Thermal and other transport coefficients were recently shown to be largely independent of the microscopic representation of the energy (current) densities or, more generally, of the relevant conserved densities/currents. In this Article, we show how this , which is intimately related to the intrinsic indeterminacy of the energy of individual atoms in interacting systems, can be exploited to optimize the statistical properties of the current time series from which the transport coefficients are evaluated. To this end, we introduce and exploit a variational principle that relies on the metric properties of the conserved currents, treated as elements of an abstract linear space.

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The effects of stress-induced lattice distortions (strain) on the conductivity of Y-doped BaZrO, a high-temperature proton conductor with key technological applications for sustainable electrochemical energy conversion, are studied. Highly ordered epitaxial thin films are grown in different strain states while monitoring the stress generation and evolution in situ. Enhanced proton conductivity due to lower activation energies is discovered under controlled conditions of tensile strain.

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The evaluation of transport coefficients in extended systems, such as thermal conductivity or shear viscosity, is known to require impractically long simulations, thus calling for a paradigm shift that would allow to deploy state-of-the-art quantum simulation methods. We introduce a new method to compute these coefficients from optimally short molecular dynamics simulations, based on the Green-Kubo theory of linear response and the cepstral analysis of time series. Information from the full sample power spectrum of the relevant current for a single and relatively short trajectory is leveraged to evaluate and optimally reduce the noise affecting its zero-frequency value, whose expectation is proportional to the corresponding conductivity.

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