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Related papers: Electro-Neutral Models for dynamic Poisson-Nernst-…

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A generalized fluid-particle hybrid model for collisionless plasmas under the assumption of quasi-neutrality is presented. The system consists of fluid ions and electrons as well as arbitrary numbers of species whose dynamics is governed by…

Space Physics · Physics 2018-05-09 Takanobu Amano

Physics-informed neural networks (PINNs) are neural networks that embed the laws of dynamical systems modeled by differential equations into their loss function as constraints. In this work, we present a PINN framework applied to oncology.…

Machine Learning · Computer Science 2025-10-16 Kayode Olumoyin , Katarzyna Rejniak

Boundary conditions (BCs) are a key component in every Physics-Informed Neural Network (PINN). By defining the solution to partial differential equations (PDEs) along domain boundaries, BCs constrain the underlying boundary value problem…

Machine Learning · Computer Science 2023-10-05 Sebastian Barschkis

The Vlasov-Poisson-Fokker-Planck (VPFP) system is a fundamental model in plasma physics that describes the Brownian motion of a large ensemble of particles within a surrounding bath. Under the high-field scaling, both collision and field…

Numerical Analysis · Mathematics 2023-08-11 Shi Jin , Zheng Ma , Tian-ai Zhang

Form-finding of unilateral membrane structures is commonly addressed by solving equilibrium equations with Finite Element Methods (FEMs). This paper investigates Physics-Informed Neural Networks (PINNs) as an alternative, where the…

Computational Engineering, Finance, and Science · Computer Science 2026-05-05 Luigi Sibille , Sigrid Adriaenssens , Carlo Olivieri

In this paper, we propose and analyze a second order accurate (in both time and space) numerical scheme for the Poisson-Nernst-Planck-Navier-Stokes system, which describes the ion electro-diffusion in fluids. In particular, the…

Numerical Analysis · Mathematics 2025-03-12 Yuzhe Qin , Cheng Wang

The description of a conducting medium in thermal equilibrium, such as an electrolyte solution or a plasma, involves nonlinear electrostatics, a subject rarely discussed in the standard electricity and magnetism textbooks. We consider in…

Chemical Physics · Physics 2018-08-01 C. G. Gray , P. J. Stiles

In this work, we present the physics-informed neural network (PINN) model applied particularly to dynamic problems in solid mechanics. We focus on forward and inverse problems. Particularly, we show how a PINN model can be used efficiently…

Neural and Evolutionary Computing · Computer Science 2025-12-16 Vijay Kag , Venkatesh Gopinath

The linearized of the Poisson-Nernst-Planck (PNP) equation under closed ends around a neutral state is studied. It is reduced to a damped heat equation under non-local boundary conditions, which leads to a stochastic interpretation of the…

Mathematical Physics · Physics 2023-03-28 Gershon Wolansky

A new model for the electrical conductivity of dense plasmas with a mixture of ion species, containing no adjustable parameters, is presented. The model takes the temperature, mass density and relative abundances of the species as input. It…

Plasma Physics · Physics 2020-04-22 C. E. Starrett , N. R. Shaffer , D. Saumon , R. Perriot , T. Nelson , L. A. Collins , C. Ticknor

A review of the present state of investigations of the pseudospin-electron model (PEM), which is used in the theory of strongly correlated electron systems, is given. The model is used to describe the systems with the locally anharmonic…

Strongly Correlated Electrons · Physics 2016-11-23 Ihor Stasyuk

Tensor networks (TNs) enable compact representations of large tensors through shared parameters. Their use in probabilistic modeling is particularly appealing, as probabilistic tensor networks (PTNs) allow for tractable computation of…

Machine Learning · Computer Science 2025-10-02 Marawan Gamal Abdel Hameed , Guillaume Rabusseau

It is economical to devise ways and means to simplify a multi-species particle system. The single fluid MHD description of a plasma is sufficiently adequate to study plasma phenomena . A plasma containing multi-species of particles can also…

Plasma Physics · Physics 2021-06-16 V. Krishan

Understanding the long-term transport of hydrogen isotopes in plasma-facing materials, such as tungsten, is critical for the steady-state operation of magnetic confinement fusion reactors. However, dynamically updating the transition…

Rapid aerodynamic screening of turbomachinery blades across wide operating envelopes remains a major computational bottleneck in preliminary design, particularly for energy-conversion and storage systems such as emerging Carnot batteries.…

Fluid Dynamics · Physics 2026-05-25 Yuan Huang , Francesca di Mare

The Poisson-Boltzmann (PB) equation provides a mean-field theory of electrolyte solutions at interfaces and in confinement, describing how ions reorganize close to charged surfaces to form the so-called electrical double layer (EDL), with…

Soft Condensed Matter · Physics 2024-09-10 Cecilia Herrero , Laurent Joly

We discuss various models of ion transport through cell membrane channels. Recent experimental data shows that sizes of ion channels are compared to those of ions and that only few ions may be simultaneously in any single channel.…

Subcellular Processes · Quantitative Biology 2007-06-06 Jan Gomulkiewicz , Jacek Miekisz , Stanislaw Miekisz

This paper analyzes various schemes for the Euler-Poisson-Boltzmann (EPB) model of plasma physics. This model consists of the pressureless gas dynamics equations coupled with the Poisson equation and where the Boltzmann relation relates the…

Analysis of PDEs · Mathematics 2014-04-08 Pierre Degond , Hailiang Liu , Dominique Savelief , Marie-Hélène Vignal

For multispecies ions, we study boundary layer solutions of charge conserving Poisson-Boltzmann (CCPB) equations [50] (with a small parameter \k{o}) over a finite one-dimensional (1D) spatial domain, subjected to Robin type boundary…

Analysis of PDEs · Mathematics 2015-04-28 Chiun-Chang Lee , Hijin Lee , YunKyong Hyon , Tai-Chia Lin , Chun Liu

Modeling the dynamics of cellular differentiation is fundamental to advancing the understanding and treatment of diseases associated with this process, such as cancer. With the rapid growth of single-cell datasets, this has also become a…