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Universal machine learning for the response of atomistic systems to external fields

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Machine learned interatomic interaction potentials have enabled efficient and accurate molecular simulations of closed systems. However, external fields, which can greatly change the chemical structure and/or reactivity, have been seldom included in curren ...
Berlin2023

Mercury Isotope Fractionation during Dark Abiotic Reduction of Hg(II) by Dissolved, Surface-Bound, and Structural Fe(II)

Lorenz Schwab

Stable mercury (Hg) isotope ratios are an emerging tracer for biogeochemical transformations in environmental systems, but their application requires knowledge of isotopic enrichment factors for individual processes. We investigated Hg isotope fractionatio ...
Washington2023

Transport across thin membranes: Effective solute flux jump

François Gallaire, Pier Giuseppe Ledda, Giuseppe Antonio Zampogna

A model to describe the transport across membranes of chemical species dissolved in an incompressible flow is developed via homogenization. The asymptotic matching between the microscopic and macroscopic solute concentration fields leads to a solute flux j ...
AIP Publishing2022

Continuous dissipative phase transitions with or without symmetry breaking

Fabrizio Minganti

The paradigm of second-order phase transitions (PTs) induced by spontaneous symmetry breaking (SSB) in thermal and quantum systems is a pillar of modern physics that has been fruitfully applied to out-of-equilibrium open quantum systems. Dissipative phase ...
IOP Publishing Ltd2021

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