Publications associées à Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images

Electron-beam based nanoscale quantum controls

Advancing quantum technologies depends on the precise control of individual quantum systems, the so-called qubits, and the exploitation of their quantum properties. Nowadays, expanding the number of qubits to be entangled is at the core of the developments ...

EPFL2024

Revealing the Mechanism Underlying 3D-AFM Imaging of Suspended Structures by Experiments and Simulations

Marcos Penedo Garcia

The invention of 3D atomic force microscopy (3D-AFM) has enabled visualizing subnanoscale 3D hydration structures. Meanwhile, its applications to imaging flexible molecular chains have started to be experimentally explored. However, the validity and princi ...

Wiley-V C H Verlag Gmbh2024

Microsecond Time-Resolved Cryo-Electron Microscopy

Oliver Florian Harder

Recently, single-particle cryo-electron microscopy emerged as a technique capable of determining protein structures at near-atomic resolution and resolving protein dynamics with a temporal resolution ranging from second to milliseconds. This thesis describ ...

EPFL2024

Polydopamine-coated photoautotrophic bacteria for improving extracellular electron transfer in living photovoltaics

Fabian Fischer, Ardemis Anoush Boghossian, Charlotte Elisabeth Marie Roullier, Melania Reggente, Mohammed Mouhib, Patricia Brandl, Hanxuan Wang

Living photovoltaics are microbial electrochemical devices that use whole cell–electrode interactions to convert solar energy to electricity. The bottleneck in these technologies is the limited electron transfer between the microbe and the electrode surfac ...

2024

Ghost imaging using two SPAD array detectors: a parameter study towards the realization of a 3D quantum microscope

Claudio Bruschini, Edoardo Charbon, Paul Mos, Yang Lin

Quantum ghost imaging can be an important tool in making optical measurements. One of the most useful aspects of ghost imaging is the unique ability to correlate two sets of independently collected information. We aim to use the principles of ghost imaging ...

Spie-Int Soc Optical Engineering2024

Structural study of nickelate based heterostructures

Jean-Marc Triscone, Duncan Thomas Lindsay Alexander, Bernat Mundet, Chih-Ying Hsu

Heterostructures consisting of SmNiO3 and NdNiO3 alternating layers with additional LaAlO3 spacer layers were grown and fully characterized by means of x-ray diffraction, atomic force microscopy, and scanning transmission electron microscopy. A change in t ...

Aip Publishing2024

Controlling crystal cleavage in focused ion beam shaped specimens for surface spectroscopy

Philip Johannes Walter Moll, Matthias Carsten Putzke, Andrew Scott Hunter

Our understanding of quantum materials is commonly based on precise determinations of their electronic spectrum by spectroscopic means, most notably angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy. Both require atomicall ...

Aip Publishing2024

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

EPFL2024

Advances in High-Speed, Multiparametric Atomic Force Microscopy

Santiago Harald Andany

After decades of technological advancements, high-speed atomic force microscopy (HS-AFM) has emerged as a powerful technique for visualizing dynamic processes. At the nanoscale, the AFM provides valuable insights into the sample by sensing minute interacti ...

EPFL2024

Compact and effective photon-resolved image scanning microscope

Giorgio Tortarolo

Fluorescence confocal laser-scanning microscopy (LSM) is one of the most popular tools for life science research. This popularity is expected to grow thanks to single-photon array detectors tailored for LSM. These detectors offer unique single-photon spati ...

Spie-Soc Photo-Optical Instrumentation Engineers2024

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

Jean-Philippe Thiran, Muhamed Barakovic, Erick Jorge Canales Rodriguez, 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

Fluorescence microscopy: A statistics-optics perspective

Aleksandra Radenovic

Fundamental properties of light unavoidably impose features on images collected using fluorescence microscopes. Accounting for these features is often critical in quantitatively interpreting microscopy images, especially those gathering information at scal ...

Amer Physical Soc2024

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

III-N blue-emitting epi-structures with high densities of dislocations: Fundamental mechanisms for efficiency improvement and applications

Pierre Christophe Lottigier

Since the dawn of humanity, human beings seeked to light their surroundings for their well-being, security and development. The efficiency of ancient lighting devices, e.g. oil lamps or candles, was in the order of 0.03-0.04% and jumped to 0.4-0.6% with th ...

EPFL2024

Boosting likelihood learning with event reweighting

Andrea Wulzer, Siyu Chen, Alfredo Glioti

Extracting maximal information from experimental data requires access to the likelihood function, which however is never directly available for complex experiments like those performed at high energy colliders. Theoretical predictions are obtained in this ...

Springer Nature2024

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

Meta-learning to address diverse Earth observation problems across resolutions

Devis Tuia, Benjamin Alexander Kellenberger, Marc Conrad Russwurm

Earth scientists study a variety of problems with remote sensing data, but they most often consider them in isolation from each other, which limits information flows across disciplines. In this work, we present METEOR, a meta-learning methodology for Earth ...

Springernature2024

Solution-based Cu+ transient species mediate the reconstruction of copper electrocatalysts for CO2 reduction

Raffaella Buonsanti, Anna Loiudice, Jan Vávra, Petru Pasquale Albertini, Gaétan Philippe Louis Ramona

Understanding metal surface reconstruction is of the utmost importance in electrocatalysis, as this phenomenon directly affects the nature of available active sites. However, its dynamic nature renders surface reconstruction notoriously difficult to study. ...

Nature Portfolio2024

A bistable inhibitory optoGPCR for multiplexed optogenetic control of neural circuits

Mauro Pulin

Information is transmitted between brain regions through the release of neurotransmitters from long-range projecting axons. Understanding how the activity of such long-range connections contributes to behavior requires efficient methods for reversibly mani ...

Nature Portfolio2024

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

David Atienza Alonso, Ali Pahlevan, Marina Zapater Sancho, Luis Maria Costero Valero, Darong Huang

Computing servers have played a key role in developing and processing emerging compute-intensive applications in recent years. Consolidating multiple virtual machines (VMs) inside one server to run various applications introduces severe competence for limi ...

2024