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Publications associées (26)

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Advances in Magnetics Roadmap on Spin-Wave Computing

Qian Wang, Yiming Li, Dirk Grundler, Xiuwei Zhang

Magnonics addresses the physical properties of spin waves and utilizes them for data processing. Scalability down to atomic dimensions, operation in the GHz-to-THz frequency range, utilization of nonlinear and nonreciprocal phenomena, and compatibility wit ...

Institute of Electrical and Electronics Engineers2022

Modelling and Sensors for Magnetically-Levitated Disc Drives

Juan Patricio Tomás Peralta Fierro

The development of new industrial applications has diverted the focus of research towards compacter and faster rotatory drives. These requirements push the classical ball-bearings of electric motors to the limits in terms of operational lifetime and fricti ...

EPFL2022

Beating the I/O Bottleneck: A Case for Log-Structured Virtual Disks

Vojtech Aschenbrenner

With the increasing dominance of SSDs for local storage, today's network mounted virtual disks can no longer offer competitive performance. We propose a Log-Structured Virtual Disk (LSVD) that couples log-structured approaches at both the cache and storage ...

ASSOC COMPUTING MACHINERY2022

Design of a compliant load cell with adjustable stiffness

Charles Baur, Lennart Rubbert, Michal Stanislaw Smreczak

Manipulation at the sub-micron scale often requires force-sensing capabilities of milli-to nanonewton forces. This article presents a novel design of a compliant load cell with mechanically adjustable stiffness. The system enables adapting force sensitivit ...

2021

Workflow Engineering in Materials Design within the BATTERY 2030+Project

Giovanni Pizzi, Leonid Kahle, Sebastiaan Philippe Huber

In recent years, modeling and simulation of materials have become indispensable to complement experiments in materials design. High-throughput simulations increasingly aid researchers in selecting the most promising materials for experimental studies or by ...

WILEY-V C H VERLAG GMBH2021

Efficient implementation of atom-density representations

Michele Ceriotti, Till Junge, Félix Benedito Clément Musil, Michael John Willatt, Guillaume André Jean Fraux, Max David Veit, Alexander Jan Goscinski

Physically motivated and mathematically robust atom-centered representations of molecular structures are key to the success of modern atomistic machine learning. They lie at the foundation of a wide range of methods to predict the properties of both materi ...

2021