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Institution

École Polytechnique Fédérale de Lausanne

FacilityLausanne, Switzerland
About: École Polytechnique Fédérale de Lausanne is a facility organization based out in Lausanne, Switzerland. It is known for research contribution in the topics: Population & Catalysis. The organization has 44041 authors who have published 98296 publications receiving 4372092 citations. The organization is also known as: EPFL & ETHL.


Papers
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Journal ArticleDOI
TL;DR: Ferroelectric, dielectric, and piezoelectric properties of ferroelectric thin films and ceramics are reviewed with the aim of providing an insight into different processes which may affect the behaviour of Ferroelectric devices.
Abstract: Ferroelectric, dielectric and piezoelectric properties of ferroelectric thin films and ceramics are reviewed with the aim of providing an insight into different processes which may affect the behaviour of ferroelectric devices, such as ferroelectric memories and micro-electro-mechanical systems. Taking into consideration recent advances in this field, topics such as polarization switching, polarization fatigue, effects of defects, depletion layers, and depolarization fields on hysteresis loop behaviour, and contributions of domain-wall displacement to dielectric and piezoelectric properties are discussed. An introduction into dielectric, pyroelectric, piezoelectric and elastic properties of ferroelectric materials, symmetry considerations, coupling of electro-mechanical and thermal properties, and definitions of relevant ferroelectric phenomena are provided.

1,835 citations

Journal ArticleDOI
TL;DR: A better knowledge of the molecular mechanisms conducive to the appearance of differentiated myofibroblasts in each pathological situation will be useful for the understanding of fibrosis development in different organs and the planning of strategies aiming at their prevention and therapy.
Abstract: The crucial role played by the myofibroblast in wound healing and pathological organ remodeling is well established; the general mechanisms of extracellular matrix synthesis and of tension production by this cell have been amply clarified. This review discusses the pattern of myofibroblast accumulation and fibrosis evolution during lung and liver fibrosis as well as during atheromatous plaque formation. Special attention is paid to the specific features characterizing each of these processes, including the spectrum of different myofibroblast precursors and the distinct pathways involved in the formation of differentiated myofibroblasts in each lesion. Thus, whereas in lung fibrosis it seems that most myofibroblasts derive from resident fibroblasts, hepatic stellate cells are the main contributor for liver fibrosis and media smooth muscle cells are the main contributor for the atheromatous plaque. A better knowledge of the molecular mechanisms conducing to the appearance of differentiated myofibroblasts in each pathological situation will be useful for the understanding of fibrosis development in different organs and for the planning of strategies aiming at their prevention and therapy.

1,834 citations

Journal ArticleDOI
TL;DR: This work demonstrates the promising catalytic activity of single-layered double hydroxides for the oxygen evolution reaction and reports an orthogonal approach to improve the activity of catalysts without alternating their compositions or structures.
Abstract: The oxygen evolution reaction is a key reaction in water splitting. The common approach in the development of oxygen evolution catalysts is to search for catalytic materials with new and optimized chemical compositions and structures. Here we report an orthogonal approach to improve the activity of catalysts without alternating their compositions or structures. Specifically, liquid phase exfoliation is applied to enhance the oxygen evolution activity of layered double hydroxides. The exfoliated single-layer nanosheets exhibit significantly higher oxygen evolution activity than the corresponding bulk layered double hydroxides in alkaline conditions. The nanosheets from nickel iron and nickel cobalt layered double hydroxides outperform a commercial iridium dioxide catalyst in both activity and stability. The exfoliation creates more active sites and improves the electronic conductivity. This work demonstrates the promising catalytic activity of single-layered double hydroxides for the oxygen evolution reaction.

1,816 citations

Journal ArticleDOI
TL;DR: The simple mesoscopic CH(3)NH( 3)PbI(3)/TiO(2) heterojunction solar cell shows impressive photovoltaic performance, with short-circuit photocurrent J(sc)= 16.1 mA/cm(2), open-circuits photovvoltage V(oc) = 0.631 V, and a fill factor FF =0.57.
Abstract: We report for the first time on a hole conductor-free mesoscopic methylammonium lead iodide (CH3NH3PbI3) perovskite/TiO2 heterojunction solar cell, produced by deposition of perovskite nanoparticles from a solution of CH3NH3I and PbI2 in γ-butyrolactone on a 400 nm thick film of TiO2 (anatase) nanosheets exposing (001) facets. A gold film was evaporated on top of the CH3NH3PbI3 as a back contact. Importantly, the CH3NH3PbI3 nanoparticles assume here simultaneously the roles of both light harvester and hole conductor, rendering superfluous the use of an additional hole transporting material. The simple mesoscopic CH3NH3PbI3/TiO2 heterojunction solar cell shows impressive photovoltaic performance, with short-circuit photocurrent Jsc= 16.1 mA/cm2, open-circuit photovoltage Voc = 0.631 V, and a fill factor FF = 0.57, corresponding to a light to electric power conversion efficiency (PCE) of 5.5% under standard AM 1.5 solar light of 1000 W/m2 intensity. At a lower light intensity of 100W/m2, a PCE of 7.3% was m...

1,799 citations

Proceedings Article
20 Jun 2018
TL;DR: This talk will introduce this formalism and give a number of results on the Neural Tangent Kernel and explain how they give us insight into the dynamics of neural networks during training and into their generalization features.
Abstract: At initialization, artificial neural networks (ANNs) are equivalent to Gaussian processes in the infinite-width limit, thus connecting them to kernel methods. We prove that the evolution of an ANN during training can also be described by a kernel: during gradient descent on the parameters of an ANN, the network function (which maps input vectors to output vectors) follows the so-called kernel gradient associated with a new object, which we call the Neural Tangent Kernel (NTK). This kernel is central to describe the generalization features of ANNs. While the NTK is random at initialization and varies during training, in the infinite-width limit it converges to an explicit limiting kernel and stays constant during training. This makes it possible to study the training of ANNs in function space instead of parameter space. Convergence of the training can then be related to the positive-definiteness of the limiting NTK. We then focus on the setting of least-squares regression and show that in the infinite-width limit, the network function follows a linear differential equation during training. The convergence is fastest along the largest kernel principal components of the input data with respect to the NTK, hence suggesting a theoretical motivation for early stopping. Finally we study the NTK numerically, observe its behavior for wide networks, and compare it to the infinite-width limit.

1,787 citations


Authors

Showing all 44420 results

NameH-indexPapersCitations
Michael Grätzel2481423303599
Ruedi Aebersold182879141881
Eliezer Masliah170982127818
Richard H. Friend1691182140032
G. A. Cowan1592353172594
Ian A. Wilson15897198221
Johan Auwerx15865395779
Menachem Elimelech15754795285
A. Artamonov1501858119791
Melody A. Swartz1481304103753
Henry J. Snaith146511123155
Kurt Wüthrich143739103253
Richard S. J. Frackowiak142309100726
Jean-Paul Kneib13880589287
Kevin J. Tracey13856182791
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023234
2022704
20215,247
20205,644
20195,432
20185,094