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Cellular electrophysiology is often modeled using the cable equations. The cable model can only be used when ionic concentration effects and three dimensional geometry effects are negligible. The Poisson model, in which the electrostatic…

Neurons and Cognition · Quantitative Biology 2009-01-27 Yoichiro Mori

The transport approach is a useful tool to study dynamics of non-equilibrium systems. For heavy-ion collisions at intermediate energies, where both the smooth nucleon potential and the hard-core nucleon-nucleon collision are important, the…

Nuclear Theory · Physics 2019-04-02 Jun Xu

Parameterized partial differential equations (PDEs) underpin the mathematical modeling of complex systems in diverse domains, including engineering, healthcare, and physics. A central challenge in using PDEs for real-world applications is…

Machine Learning · Computer Science 2026-04-07 Xuyang Li , Mahdi Masmoudi , Rami Gharbi , Nizar Lajnef , Vishnu Naresh Boddeti

We evaluate the exponentially rare fluctuations of the ionic current for a dilute electrolyte by means of macroscopic fluctuation theory. We consider the fluctuating hydrodynamics of a fluid electrolyte described by a stochastic…

Statistical Mechanics · Physics 2025-07-25 Jafar Farhadi , David T. Limmer

A model for ionic and electronic grain boundary transport through thin films, scales or membranes with columnar grain structure is introduced. The grain structure is idealized as a lattice of identical hexagonal cells - a honeycomb pattern.…

Materials Science · Physics 2017-05-05 M. P. Tautschnig , N. M. Harrison , M. W. Finnis

The mathematical P2D model is a system of strongly coupled nonlinear parabolic-elliptic equations that describes the electrodynamics of lithium-ion batteries. In this paper, we present the numerical analysis of a finite element-implicit…

Numerical Analysis · Mathematics 2021-09-23 Rodolfo Bermejo

The three-dimensional electrostatic field configuration in gas ionization detectors has been simulated using an efficient and precise nearly exact boundary element method (NEBEM) solver set up to solve an integral equation of the first…

Instrumentation and Detectors · Physics 2007-05-23 N. Majumdar , S. Mukhopadhyay

Physics-Informed Neural Networks present a novel approach in SciML that integrates physical laws in the form of partial differential equations directly into the NN through soft constraints in the loss function. This work studies the…

Neural and Evolutionary Computing · Computer Science 2026-02-17 Suhas Suresh Bharadwaj , Reuben Thomas Thovelil

A connection between the impedance spectroscopy response of anomalous Poisson-Nernst-Planck (PNPA) diffusional models and of equivalent circuits containing constant phase elements (CPE) is established for a typical electrolytic cell. The…

A nonlinear phase-field model is developed to simulate corrosion damage. The motion of the electrode$-$ electrolyte interface follows the usual kinetic rate theory for chemical reactions based on the Butler-Volmer equation. The model links…

Chemical Physics · Physics 2024-08-28 M. Makuch , S. Kovacevic , M. R. Wenman , E. Martínez-Pañeda

Electric double-layer capacitors (EDLCs), consisting of an ionic fluid between two metallic electrodes, are electrochemical energy storage devices complementary to batteries, allowing for a faster charge/discharge. The charging dynamics in…

Soft Condensed Matter · Physics 2026-05-19 Megh Dutta , Ivan Palaia , Emmanuel Trizac , Benjamin Rotenberg

Ionic liquids offer unique bulk and interfacial characteristics as battery electrolytes. Our continuum approach naturally describes the electrolyte on a macroscale. An integral formulation for the molecular repulsion,which can be…

Chemical Physics · Physics 2022-11-30 Max Schammer , Arnulf Latz , Birger Horstmann

The Poisson-Boltzmann equation (PBE) is an implicit solvent continuum model for calculating the electrostatic potential and energies of ionic solvated biomolecules. However, its numerical solution remains a significant challenge due strong…

Numerical Analysis · Mathematics 2023-06-13 Cleophas Kweyu , Venera Khoromskaia , Boris Khoromskij , Matthias Stein , Peter Benner

The quasi-neutral hybrid model with kinetic ions and fluid electrons is a promising approach for bridging the inherent multi-scale nature of many problems in space and laboratory plasmas. Here, a novel, implicit, particle-in-cell based…

Plasma Physics · Physics 2018-11-14 A. Stanier , L. Chacón , G. Chen

Room temperature ionic liquids are attractive to numerous applications and particularly, to renewable energy devices. As solvent free electrolytes, they demonstrate a paramount connection between the material morphology and Coulombic…

Chemical Physics · Physics 2016-03-15 Nir Gavish , Arik Yochelis

In this paper, we propose a Poisson-Nernst-Planck-Navier-Stokes-Cahn-Hillard (PNP-NS-CH)model for an electrically charged droplet suspended in a viscous fluid subjected to an external electric field. Our model incorporates spatial…

Fluid Dynamics · Physics 2023-05-18 Yuzhe Qin , Huaxiong Huang , Zilong Song , Shixin Xu

Partial Differential Equations (PDE) are fundamental to model different phenomena in science and engineering mathematically. Solving them is a crucial step towards a precise knowledge of the behaviour of natural and engineered systems. In…

The increasing need for portable and large-scale energy storage systems requires development of new, long lasting and highly efficient battery systems. Solid state NMR spectroscopy has emerged as an excellent method for characterizing…

Chemical Physics · Physics 2023-07-10 Shira Haber , Michal Leskes

Continuum models for ion transport through polyamide nanopores require solving partial differential equations (PDEs) through complex pore geometries. Resolving spatiotemporal features at this length and time-scale can make solving these…

Machine Learning · Computer Science 2023-05-03 Danyal Rehman , John H. Lienhard

In this study, we present a novel computational framework that integrates the finite volume method with graph neural networks to address the challenges in Physics-Informed Neural Networks(PINNs). Our approach leverages the flexibility of…

Fluid Dynamics · Physics 2024-05-08 Tianyu Li , Yiye Zou , Shufan Zou , Xinghua Chang , Laiping Zhang , Xiaogang Deng
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