Publications related to Characterization and optimization of liquid electrodes for lateral dielectrophoresis

Related publications (29)

A method and system for optimizing design, implantation, and stimulation protocols of electrodes stimulating the nervous system

A method for optimizing at least one of a geometry, an implantation procedure, and/or stimulation protocol of one or more electrodes for an electrical stimulation of a target structure in a nervous system of a living being by a computer device, the method ...

2024

Strain-based analysis on the influence of local undercut geometry on fatigue crack initiation life

Alain Nussbaumer

The local undercut defects at the weld toe provide a potential initiation site for fatigue cracks and significantly impact the structure's fatigue strength. The influence of continuous undercut depth on fatigue performance is widely studied, but the resear ...

2024

FENNECS: a novel particle-in-cell code for simulating the formation of magnetized non-neutral plasmas trapped by electrodes of complex geometries

Guillaume Michel Le Bars, Stefano Alberti, Jean-Philippe Hogge, Joaquim Loizu Cisquella, Jérémy Genoud, Francesco Romano

This paper presents the new 2D electrostatic particle -in -cell code FENNECS developed to study the formation of magnetized non -neutral plasmas in geometries with azimuthal symmetry. This code has been developed in the domain of gyrotron electron gun desi ...

2024

Into the ice: Exploration and data capturing in glacial moulins by a tethered robot

Josephine Anna Eleanor Hughes, Max Mirko Polzin

Glacial moulins (cylindrical meltwater drainage shafts) provide valuable insights into glacier dynamics, but are inaccessible and hazardous environments for humans to study. Exploring them using passive sensor probes has revealed their complex geometry, wh ...

Wiley2024

Stress tolerance of lightweight glass-free PV modules for vehicle integration

Kléber Nicolet-dit-Félix, Christophe Ballif, Matthieu Despeisse, Aïcha Hessler-Wyser, Jacques Levrat, Antonin Faes, Gianluca Cattaneo, Umang Bhupatrai Desai, Fahradin Mujovi

Electric vehicles (EVs) currently dominate the sales in the automotive market. A big leap in this market can be made by developing a photovoltaic product that can be integrated to an EV, as it can boost the driving range of the EV while reducing the chargi ...

Edp Sciences S A2024

Geometric Learning: Leveraging differential geometry for learning and control

Bernardo Fichera

In this thesis, we concentrate on advancing high-level behavioral control policies for robotic systems within the framework of Dynamical Systems (DS). Throughout the course of this research, a unifying thread weaving through diverse fields emerges, and tha ...

EPFL2024

Incorporating Projective Geometry into Deep Learning

Michal Jan Tyszkiewicz

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

EPFL2024

High brightness neutron source optimized for very high pulsed magnetic field experiments

Mina Akhyani

Conducting neutron scattering experiments in the presence of high pulsed magnetic fields, namely above 40 T, provides valuable information about the magnetic structures of materials. However, these experiments are challenging and time-consuming because the ...

EPFL2024

Multimaterial Volumetric Printing of Silica-Based Glasses

Christophe Moser, Damien Claude-Marie Loterie, Paul Delrot, Antoine Vincent Boniface, Jorge Andres Madrid Wolff

Silicate glasses have played a major role as structural and functional materials in human civilization since ancient Egypt. Despite their widespread use and importance in modern society, silica glasses with complex geometries are only fabricated in automat ...

Wiley2024

Energy-Efficient Particle Accelerators for Research

Mike Seidel

Particle accelerators are the drivers for large-scale research infrastructures for particle physics but also for many branches of condensed matter research. The types of accelerator-driven research infrastructures include particle colliders, neutron, muon ...

2024

Highly anisotropic carbon fiber electrodes for DEAs and their dynamic non-monotonic conductive properties

Yves Perriard, Stefania Maria Aliki Konstantinidi

A common method for creating compliant electrodes for dielectric elastomer actuators (DEAs) and soft sensors is to incorporate electrically conductive carbon particles into a polymer matrix. However, using unidirectional aligned carbon fibers instead not o ...

Society of Photo-Optical Instrumentation Engineers (SPIE)2024

Organic matters, but inorganic matters too: column examination of elevated mercury sorption on low organic matter aquifer material using concentrations and stable isotope ratios

Lorenz Schwab

Sorption of mercury (Hg) in soils is suggested to be predominantly associated with organic matter (OM). However, there is a growing collection of research that suggests that clay minerals and oxides are also important solid phases for the sorption of solu ...

2024

T-5 configurations and hyperbolic systems

Riccardo Tione, Carl Johan Peter Johansson

In this paper, we study the rank-one convex hull of a differential inclusion associated to entropy solutions of a hyperbolic system of conservation laws. This was introduced in [B. Kirchheim, S. Muller and V. S(sic)ver & aacute;k, Studying Nonlinear PDE by ...

WORLD SCIENTIFIC PUBL CO PTE LTD2023

Some Physical Implications Of Absolute Geometries In The Description Of Complex Systems Dynamics

Maria-Alexandra Paun

Some implications of absolute geometries in the description of complex systems dynamics, at various scale resolutions are highlighted. In such context, by means of an analytic geometry of 2 x 2 matrices, a generalization of the standard velocities space in ...

UNIV POLITEHNICA BUCHAREST, SCI BULL2023

Advancing first principle-based molecular dynamics of biological systems with machine learning

François Louis Mouvet

Molecular dynamics (MD) simulations have emerged as a transformative approach to analyse molecular systems at the atomic level, offering valuable insights into complex biological processes. Many biological phenomena can only accurately be described by inco ...

EPFL2023

Understanding the role of Hubbard corrections in the rhombohedral phase of BaTiO3

Nicola Marzari, Iurii Timrov, Michele Kotiuga, Lorenzo Bastonero

We present a first-principles study of the low-temperature rhombohedral phase of BaTiO3 using Hubbardcorrected density-functional theory. By employing density-functional perturbation theory, we compute the onsite Hubbard U for Ti(3d) states and the intersi ...

Amer Physical Soc2023

Pathways to enhance electrochemical CO2 reduction identified through direct pore-level modeling

Sophia Haussener, Etienne Boutin, Shuo Liu, Evan Fair Johnson

Electrochemical conversion of CO2 to fuels and valuable products is one pathway to reduce CO2 emissions. Electrolyzers using gas diffusion electrodes (GDEs) show much higher current densities than aqueous phase electrolyzers, yet models for multi-physical ...

2023

Frequency and time domains interactions in nanophotonics

Andrei Kiselev

In this thesis, we discuss the problems of scattering and optical manipulation related to nanosystems of different complexities. The multipolar decomposition method is used to represent scattering processes in nanosystems as a series of elementary excitati ...

EPFL2023

A multi scale consolidation model for press moulding of hybrid textiles into complex geometries

Vincent Werlen

Side-by-side hybrid textiles are an intermediate step for the production of fibre-reinforced thermoplastic composites. Press moulding these materials combining reinforcing fibre textiles and thermoplastic matrix textiles or flexible layers is a promising m ...

EPFL2023

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Sabine Süsstrunk, Mathieu Salzmann, Chen Liu, Yulun Jiang

We address the problem of stably and efficiently training a deep neural network robust to adversarial perturbations bounded by an

l_1

norm. We demonstrate that achieving robustness against

l_1

-bounded perturbations is more challenging than in the

l_2

...

2023