The Use of the Legendre Transform in Chemical Thermodynamics: A Powerful Tool
Starting from Gibbs’ formulation of internal energy, all thermodynamic potentials can be obtained via the Legendre transform, along with a mnemonic rule for their calculation and an analysis of the extensivity of internal energy, culminating in Euler's theorem, the Gibbs–Duhem equation, and the definition of chemical potential.
Renato Veríssimo de Oliveira +2 more
wiley +1 more source
Smooth Wavelet Approximations of Truncated Legendre Polynomials via the Jacobi Theta Function
The family of nth order q-Legendre polynomials are introduced. They are shown to be obtainable from the Jacobi theta function and to satisfy recursion relations and multiplicatively advanced differential equations (MADEs) that are analogues of the ...
David W. Pravica +2 more
doaj +1 more source
Variational Modeling of Porosity Waves
ABSTRACT Mathematical models for finite‐strain poroelasticity in an Eulerian formulation are studied by constructing their energy‐variational structure, which gives rise to a class of saddle‐point problems. This problem is discretized using an incremental time‐stepping scheme and a mixed finite element approach, resulting in a monolithic, structure ...
Andrea Zafferi, Dirk Peschka
wiley +1 more source
Methodological Frameworks for Computational Electrocatalysis: From Theory to Practice
Computational modeling is widely used to investigate electrocatalytic reactions, yet accurately describing electrochemical interfaces remains challenging. This review outlines theoretical and computational strategies, based on density functional theory, to model reaction thermodynamics, solvation effects, applied bias, and kinetics.
Michele Re Fiorentin +8 more
wiley +1 more source
A Thermodynamic Framework for Turing‐Type Instabilities in Porous Media: Part I Theory
Abstract Pattern formation in geological materials is commonly described using analogies to Turing‐type reaction–diffusion systems, yet a unifying thermodynamic explanation remains elusive. Here we develop a multiscale, thermodynamically consistent framework for pattern‐forming instabilities in porous media undergoing coupled thermo–hydro–mechanical ...
Klaus Regenauer‐Lieb +5 more
wiley +1 more source
Dynamic Earthquake Source Inversion With Generative Adversarial Network Priors
Abstract Dynamic earthquake source inversion consists of inferring frictional parameters and initial stress on a fault consistent with recorded seismological and geodetic data and with dynamic earthquake rupture models. In a Bayesian inversion approach, the nonlinear relationship between model parameters and data requires a computationally demanding ...
Jan Premus, Jean Paul Ampuero
wiley +1 more source
Random Wavelet Series: Theory and Applications
Random Wavelet Series form a class of random processes with multifractal properties. We give three applications of this construction. First, we synthesize a random function having any given spectrum of singularities satisfying some conditions (but ...
Aubry, Jean-Marie, Jaffard, Stéphane
core +1 more source
Early Solar Wind and Dynamo Magnetic Field Topology Predictions for (16) Psyche and Other Asteroids
Abstract Asteroid (16) Psyche is a metal‐rich body that might record an ancient coherent magnetization if some relict crust or mantle is preserved. Herein, we use magnetohydrodynamic simulations to predict (16) Psyche's field topology for several distinct pathways: (i) an early solar wind‐induced magnetization imparted after a larger body was impacted,
Atma Anand +3 more
wiley +1 more source
A numerical study on fractional order financial system with chaotic and Lyapunov stability analysis
In the last few decades, academic research has focused more on financial problems and poverty levels. These are among the two major challenges of the modern world today. To understand the challenge of financial crisis and poverty in societies. This paper
Khushbu Agrawal +3 more
doaj +1 more source
Gearbox Compound Fault Diagnosis in Edge-IoT Based on Legendre Multiwavelet Transform and Convolutional Neural Network. [PDF]
Zheng X +5 more
europepmc +1 more source

