Publications related to Hydrogen-induced tunable remanent polarization in a perovskite nickelate

Green hydrogen production using Shewanella oneidensis MR-1 bioanode and cuprous oxide-based photocathode

In recent years, many efforts have been made to find alternative renewable energy sources that can ideally replace the use of fossil fuels in all aspects. One of the new emerging energy technologies is the bioelectrochemical system, of which two types are ...

EPFL2024

Biobased surfactant

Jeremy Luterbacher, Stefania Bertella, Anastasiia Komarova, Songlan Sun

The present invention relates to a compound of the general formula (I), and (II)wherein one of R11 and R12 is hydrogen and the other is -CH2-R70, and one of R13 and R14 is hydrogen and the other is -CH2-R71, or wherein one of R11 and R12 is hydrogen and th ...

2024

Biobased surfactant

Jeremy Luterbacher, Stefania Bertella, Anastasiia Komarova, Songlan Sun

The present invention relates to a compound of the general formula (I), (II) and (III), more specifically of formula (Ia), (Ib), (Ic)wherein R11 and R12 or R21 and R22 or R31 and R32 are both hydrogen or form together with CHR50 a cyclic moiety or one of R ...

2024

Safe Deep Neural Networks

Kyle Michael Matoba

The capabilities of deep learning systems have advanced much faster than our ability to understand them. Whilst the gains from deep neural networks (DNNs) are significant, they are accompanied by a growing risk and gravity of a bad outcome. This is troubli ...

EPFL2024

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Romain Christophe Rémy Fleury, Janez Rus

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Mattia Atzeni

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Michele Bianco, Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Tianyue Chen

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Active Power Decoupling for Single-Phase Input-Series-Output-Parallel Solid-State Transformers

Drazen Dujic, Tianyu Wei, Andrea Cervone

Solid-state transformers with input-series outputparallel structures are being considered for a variety of applications requiring MVAC to LVDC conversion. Due to the singlephase AC/DC conversion at the input side, all floating cells of the solid-state tran ...

2024

Engineering Frustrated Lewis Pair Active Sites in Porous Organic Scaffolds for Catalytic CO2 Hydrogenation

Anne-Clémence Corminboeuf, Jacob Terence Blaskovits, Shubhajit Das, Rubén Laplaza Solanas

Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes. Immobilizing the active Lewis sites to a solid support, especially to porous scaffolds, ...

Amer Chemical Soc2024

Stability and degradation of (oxy)nitride photocatalysts for solar water splitting

Sophia Haussener, Franky Esteban Bedoya Lora

Advancing towards alternative technologies for the sustainable production of hydrogen is a necessity for the successful integration of this potentially green fuel in the future. Photocatalytic and photoelectrochemical water splitting are promising concepts ...

2024

3D Printing of Customizable Transient Bioelectronics and Sensors

Danick Briand, Nicolas Francis Fumeaux

Transient electronics have emerged as a new category of devices that can degrade after their functional lifetime, offering tremendous potential as disposable sensors, actuators, wearables, and implants. Additive manufacturing methods represent a promising ...

2024

Reversible photo-electrochemical device for solar hydrogen and power generation

Sophia Haussener, Alexandre Dominique M. Cattry, Saurabh Yuvraj Tembhurne, Matthieu Jonin, Mahendra Patel

A reversible photo-electrochemical device operating under concentrated irradiation could offer a stand-alone solution for producing solar fuel (in photo-driven electrolysis mode) and power (in fuel cell mode). This strategy would present the advantage of h ...

2024

Microbial hydrogen sinks in the sand-bentonite backfill material for the deep geological disposal of radioactive waste

Rizlan Bernier-Latmani, Manon Frutschi, Niels Burzan, Aislinn Ann Boylan, Nicolas Louis Maurice Jacquemin, Simiao Wang, Camille Aude Rolland

The activity of subsurface microorganisms can be harnessed for engineering projects. For instance, the Swiss radioactive waste repository design can take advantage of indigenous microorganisms to tackle the issue of a hydrogen gas (H2) phase pressure build ...

Frontiers Media SA2024

Large impact of phonon lineshapes on the superconductivity of solid hydrogen

Lorenzo Monacelli

Phonon anharmonicity plays a crucial role in determining the stability and vibrational properties of high-pressure hydrides. Furthermore, strong anharmonicity can render phonon quasiparticle picture obsolete questioning standard approaches for modeling sup ...

Nature Portfolio2024

Machine Learning for Modeling Stock Returns

Teng Andrea Xu

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

EPFL2024

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Volkan Cevher, Grigorios Chrysos, Fanghui Liu

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

2024

Random matrix methods for high-dimensional machine learning models

Antoine Philippe Michel Bodin

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

EPFL2024

'Fraternal-twin' ferroelectricity: competing polar states in hydrogen-doped samarium nickelate from first principles

Michele Kotiuga

In ferroelectric switching, an applied electric field switches the system between two polar symmetry-equivalent states. In this work, we use first-principles calculations to explore the polar states of hydrogen-doped samarium nickelate (SNO) at a concentra ...

Iop Publishing Ltd2024

Large-cage occupation and quantum dynamics of hydrogen molecules in sII clathrate hydrates

Richard Gaal, Livia Eleonora Bove Kado, Umbertoluca Ranieri

Hydrogen clathrate hydrates are ice-like crystalline substances in which hydrogen molecules are trapped inside polyhedral cages formed by the water molecules. Small cages can host only a single H-2 molecule, while each large cage can be occupied by up to f ...

Aip Publishing2024