Publication

Multivariate statistical analysis as a tool for the segmentation of 3D spectral data

Publications associées (29)

Quasi-operando Transmission Electron Microscopy Diagnostics for Electrocatalytic Processes in Liquids

It is of great interest to the energy community to understand how the mechano-physico-chemical phenomena that eventually lead to device degradation are related to the startup, operation, and shutdown phases. For electrocatalytic systems operating in liquid ...

Swiss Chemical Soc2024

Measuring electrical properties in semiconductor devices by pixelated STEM and off-axis electron holography (or convergent beams vs. plane waves)

Victor Carle Adrien Boureau

We demonstrate the use of both pixelated differential phase contrast (DPC) scanning transmission electron microscopy (STEM) and off-axis electron holography (EH) for the measurement of electric fields and assess the advantages and limitations of each techn ...

Pergamon-Elsevier Science Ltd2024

A continuous-wave and pulsed X-band electron spin resonance spectrometer operating in ultra-high vacuum for the study of low dimensional spin ensembles

Giovanni Boero, Fabio Donati, Soyoung Oh

We report the development of a continuous-wave and pulsed X-band electron spin resonance (ESR) spectrometer for the study of spins on ordered surfaces down to cryogenic temperatures. The spectrometer operates in ultra-high vacuum and utilizes a half-wavele ...

Aip Publishing2024

Identification of typical district configurations: A two-step global sensitivity analysis framework

François Maréchal, Jonas Schnidrig, Cédric Terrier

The recent geopolitical conflicts in Europe have underscored the vulnerability of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy systems ensuring sustainable energy supply in the future, the ...

Pergamon-Elsevier Science Ltd2024

Pore size estimation in axon-mimicking microfibers with diffusion-relaxation MRI

Jean-Philippe Thiran, Erick Jorge Canales Rodriguez, Muhamed Barakovic, Marco Pizzolato, Tim Bjørn Dyrby

Purpose: This study aims to evaluate two distinct approaches for fiber radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfiber phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approac ...

Wiley2024

Evaluation of Interface and Residual Strain of NiTi Layer Deposited on NiTiX Substrate by Laser Powder Bed Fusion

Christian Leinenbach, Elyas Ghafoori, Irene Ferretto, Mahbod Golrang, Mahshid Memarian

This study investigates the microstructure and properties of functionally graded NiTi alloy bilayers. The NiTi layer is printed by laser powder bed fusion on a NiTiX (where X is Hf or Cu) substrate prepared by vacuum arc remelting. Specimens produced with ...

Wiley-V C H Verlag Gmbh2024

Magnetism of Single Surface Adsorbed Atoms Studied with Radio-Frequency STM

Clément Marie Soulard

This thesis investigates the magnetic properties of single atoms and molecules adsorbed on thin magnesium oxide decoupling layers, grown on a silver single crystal. To address these systems experimentally, we use a low temperature scanning tunneling micros ...

EPFL2024

Controlled Formation of Nanoribbons and Their Heterostructures via Assembly of Mass-Selected Inorganic Ions

Klaus Kern

Control of nanomaterial dimensions with atomic precision through synthetic methods is essential to understanding and engineering of nanomaterials. For single-layer inorganic materials, size and shape controls have been achieved by self-assembly and surface ...

Wiley-V C H Verlag Gmbh2024

Mapping orthorhombic domains with geometrical phase analysis in rare-earth nickelate heterostructures

Duncan Thomas Lindsay Alexander, Bernat Mundet, Jean-Marc Triscone

Most perovskite oxides belong to the Pbnm space group, composed of an anisotropic unit cell, A-site antipolar displacements, and oxygen octahedral tilts. Mapping the orientation of the orthorhombic unit cell in epitaxial heterostructures that consist of at ...

Aip Publishing2024

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024