Publications related to Helmholtz free energy

Solvation Free Energies from Machine Learning Molecular Dynamics

Nicola Marzari, Nicéphore Arthur François Bonnet

The present work proposes an extension to the approach of [Xi, C; et al. J. Chem. Theory Comput. 2022, 18, 6878] to calculate ion solvation free energies from first-principles (FP) molecular dynamics (MD) simulations of a hybrid solvation model. The approa ...

Amer Chemical Soc2024

Evolution of water content and suction of Opalinus Clay from recovery at the drilling site to handling in the laboratory

Lyesse Laloui, Alessio Ferrari, Angelica Tuttolomondo

Advanced geotechnical engineering applications, such as shale gas extraction, CO2 geological sequestration, and geological radioactive waste storage, often involve various types of shales located at significant depths. Shales exhibit mechanical properties ...

Pergamon-Elsevier Science Ltd2024

Role of Carbonyl Compounds for N-Nitrosamine Formation during Nitrosation: Kinetics and Mechanisms

Urs von Gunten, Florian Frédéric Vincent Breider, Yishuai Pan

N-Nitrosamines are potential human carcinogens frequently detected in natural and engineered aquatic systems. This study sheds light on the role of carbonyl compounds in the formation of N-nitrosamines by nitrosation of five secondary amines via different ...

2024

Bending and Stretching in a Narrow Ribbon of Nematic Polymer Networks

Harmeet Singh

We study the spontaneous out-of-plane bending of a planar untwisted ribbon composed of nematic polymer networks activated by a change in temperature. Our theory accounts for both stretching and bending energies, which compete to establish equilibrium. We s ...

SPRINGER2023

Influence of Sphericity on Surface Termination of Icosahedral Colloidal Clusters

Esther Amstad

Colloids self-organize into icosahedral clusters composed of a Mackay core and an anti-Mackay shell under spherical confinement to minimize the free energy. This study explores the variation of surface arrangements of colloids in icosahedral clusters, focu ...

Wiley-V C H Verlag Gmbh2023

Fermi energy determination for advanced smearing techniques

Nicola Marzari, Flaviano José Dos Santos

Smearing techniques are widely used in first-principles calculations of metallic and magnetic materials where they improve the accuracy of Brillouin-zone sampling and lessen the impact of level-crossing instabilities. Smearing introduces a fictitious elect ...

AMER PHYSICAL SOC2023

High-order accurate well-balanced energy stable adaptive moving mesh finite difference schemes for the shallow water equations with non-flat bottom topography

Zhenying Zhang, Junming Duan

This paper proposes high-order accurate well-balanced (WB) energy stable (ES) adaptive moving mesh finite difference schemes for the shallow water equations (SWEs) with non flat bottom topography. To enable the construction of the ES schemes on moving mesh ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Control-oriented modeling and analysis of tubular dielectric elastomer actuators dedicated to cardiac assist devices

Yves Perriard, Yoan René Cyrille Civet, Thomas Guillaume Martinez, Armando Matthieu Walter, Ning Liu

This paper deals with the control-oriented modeling of a multilayered dielectric elastomer actuator based tube. The actuator is clamped at both sides and performs a radial displacement. The hyperelastic deformation and the viscoelastic performance, togethe ...

2022

Experimental Method to Distinguish between a Solution and a Suspension

Francesco Stellacci, Quy Ong Khac, Xufeng Xu, Ting Mao, Paulo Henrique Jacob Silva

Dispersion of objects in a fluid phase can be classified as solutions (Gibbs free energy of mixing, Delta G(mix) < 0) or suspensions (Delta G(mix) > 0) depending on their thermodynamic stability. Small objects tend to form solutions, larger ones suspension ...

WILEY2022

Failure mechanism of fine-grained soil-structure interface for energy piles

Lyesse Laloui, Elena Ravera

The response of the soil-structure interface can significantly affect the performance of any geotechnical structure. Thermal cycles are a new factor that influence the response to all structures that have an energy function in addition to the structural on ...

2022

Predicting hot-electron free energies from ground-state data

Michele Ceriotti, Federico Grasselli, Chiheb Ben Mahmoud

Machine-learning potentials are usually trained on the ground-state, Born-Oppenheimer energy surface, which depends exclusively on the atomic positions and not on the simulation temperature. This disregards the effect of thermally excited electrons, that i ...

AMER PHYSICAL SOC2022

A comprehensive framework for hard-magnetic beams: Reduced-order theory, 3D simulations, and experiments

Pedro Miguel Nunes Pereira de Almeida Reis, Dong Yan, Arefeh Abbasi

Thin beams made of magnetorheological elastomers embedded with hard-magnetic particles (hard-MREs) are capable of large deflections under an applied magnetic field. We propose a comprehensive framework, comprising a beam model and 3D finite element modelin ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Adsorption Behavior of the Coenzyme NADH at the Carbon/ Electrolyte Interface Determined by Neutron Reflectometry

The adsorption behavior of beta-nicotinamide adenine dinucleotide (NADH) at the carbon/electrolyte interface has been studied using a combination of neutron reflectometry (NR) and solution depletion isotherms. Coupling the NR technique with an electrochemi ...

2022

Electric metal contacts to monolayer blue phosphorus: electronic and chemical properties

Xiao Zhou, Cheng Chen, Pengfei Ou

The contact nature when monolayer blue phosphorus (blueP) interfaces with three transition metal electrodes (i. e., Pd, Ir, and Pt) was unraveled by the ab initio density functional theory calculations. Specifically, n-type Schottky contact is observed for ...

ELSEVIER2022

Mass-Zero constrained dynamics and statistics for the shell model in magnetic field

Sara Bonella, Alessandro Coretti, David Daniel Girardier

In several domains of physics, including first principle simulations and classical models for polarizable systems, the minimization of an energy function with respect to a set of auxiliary variables must be performed to define the dynamics of physical degr ...

EDP Sciences, Springer2021

Transferable machine-learning models of complex materials: the case of GaAs

Giulio Imbalzano

Molecular simulations allow to investigate the behaviour of materials at the atomistic level, shedding light on phenomena that cannot be directly observed in experiments. Accurate results can be obtained with ab initio methods, while simulations of large-s ...

EPFL2021

Uncertainty estimation for molecular dynamics and sampling

Michele Ceriotti, Venkat Kapil, Yongbin Zhuang, Kevin Rossi, Edgar Albert Engel, Federico Grasselli, Giulio Imbalzano

Machine-learning models have emerged as a very effective strategy to sidestep time-consuming electronic-structure calculations, enabling accurate simulations of greater size, time scale, and complexity. Given the interpolative nature of these models, the r ...

2021

Repair or Degrade: the Thermodynamic Dilemma of Cellular Protein Quality-Control

Paolo De Los Rios, Bruno Claude Daniel Fauvet, Pierre Goloubinoff, Satyam Tiwari, Mathieu Rebeaud

Life is a non-equilibrium phenomenon. Owing to their high free energy content, the macromolecules of life tend to spontaneously react with ambient oxygen and water and turn into more stable inorganic molecules. A similar thermodynamic picture applies to th ...

FRONTIERS MEDIA SA2021

Extraction of Rare Earth Metals: The New Thermodynamic Considerations Toward Process Hydrometallurgy

Christian Ludwig, Rudolf Paul Wilhelm Jozef Struis, Andrea Testino, Ajay Bhagwan Patil

Successful management of secondary waste resources is essential for the viable circular economy. E-waste could serve as the potential urban mining source for the alternative supply chain of critical metals such as rare earth elements (REEs). The hydrometal ...

Springer Nature Switzerland AG2021

Loss landscape and symmetries in Neural Networks

Mario Geiger

Neural networks (NNs) have been very successful in a variety of tasks ranging from machine translation to image classification. Despite their success, the reasons for their performance are still not well-understood. This thesis explores two main themes: lo ...

EPFL2021