Publications associées à An Integrated Adaptive Model for Overheating Risk Prediction

Hydrogen-induced tunable remanent polarization in a perovskite nickelate

Materials with field-tunable polarization are of broad interest to condensed matter sciences and solid-state device technologies. Here, using hydrogen (H) donor doping, we modify the room temperature metallic phase of a perovskite nickelate NdNiO3 into an ...

Nature Portfolio2024

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

Machine learning models for prediction of electrochemical properties in supercapacitor electrodes using MXene and graphene nanoplatelets

Mohammad Khaja Nazeeruddin

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

Elsevier Science Sa2024

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

Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction

Adrien Raphaël Depeursinge, Julien René Pierre Fageot, Daniel Abler

Assessing the individual risk of Major Adverse Cardiac Events (MACE) is of major importance as cardiovascular diseases remain the leading cause of death worldwide. Quantitative Myocardial Perfusion Imaging (MPI) parameters such as stress Myocardial Blood F ...

Nature Portfolio2024

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Paul Scharnhorst

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

EPFL2024

Beyond the average consumer: Mapping the potential of demand-side management among patterns of appliance usage

Claudia Rebeca Binder Signer, Matteo Barsanti, Selin Yilmaz

To support the decarbonisation of the power sector and offset the volatility of a system with high levels of renewables, there is growing interest in residential Demand-Side Management (DSM) solutions. Traditional DSM strategies require consumers to active ...

2024

Quantifying mass transport limitations in a microfluidic CO2 electrolyzer with a gas diffusion cathode

Sophia Haussener, Venu Gopal Agarwal

A gas diffusion electrode (GDE) based CO2 electrolyzer shows enhanced CO2 transport to the catalyst surface, significantly increasing current density compared to traditional planar immersed electrodes. A two-dimensional model for the cathode side of a micr ...

2024

Dataset for "Low-temperature processing of screen-printed piezoelectric KNbO3 with integration onto biodegradable paper substrates"

Luis Guillermo Villanueva Torrijo, Danick Briand, Morgan Mc Kay Monroe

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “Low-temperature processing of screen-printed piezoelectric KNbO3 with integration onto biodegradable paper ...

Zenodo2023

500 MHz high resolution proximity sensors with fully integrated digital counter

Giovanni Boero, Nergiz Sahin Solmaz, Reza Farsi

We report on the design and characterization of two inductive proximity sensors based on LC oscillators operating at 500 MHz. The distance from the target is obtained by measuring the oscillation frequency variation. Both sensors contain an off-chip LC res ...

ELSEVIER SCI LTD2023

Low-temperature processing of screen-printed piezoelectric KNbO3 with integration onto biodegradable paper substrates

Luis Guillermo Villanueva Torrijo, Danick Briand, Morgan Mc Kay Monroe

The development of fully solution-processed, biodegradable piezoelectrics is a critical step in the development of green electronics towards the worldwide reduction of harmful electronic waste. However, recent printing processes for piezoelectrics are hind ...

2023

Spatial Distributions of Diarrheal Cases in Relation to Housing Conditions in Informal Settlements: A Cross-Sectional Study in Abidjan, Côte d’Ivoire

Jérôme Chenal, Vitor Pessoa Colombo, Jürg Utzinger

In addition to individual practices and access to water, sanitation, and hygiene (WASH) facilities, housing conditions may also be associated with the risk of diarrhea. Our study embraced a broad approach to health determinants by looking at housing depriv ...

2023

Dc-Link Ripple Suppression of Cascaded H-Bridge Based MV Grid Emulator Apparatus for Analysis and Testing of Grid-Tied Converters in Distribution System

Drazen Dujic, Chengmin Li, Xin Xiang, Jing Sheng

The medium-voltage grid emulator is gaining popularity for testing grid-code compliance of large-capacity converters for renewable energy resources. The cascaded H-bridge converter based on active-front-ends is a promising candidate for high-power grid emu ...

2023

Distributional Regression and Autoregression via Optimal Transport

Laya Ghodrati

We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of

\R^d

. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...

EPFL2023

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Hugo Chao Cui, Florent Gérard Krzakala, Lenka Zdeborová

We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

2023

A 0.21-ps FOM Capacitor-Less Analog LDO with Dual-Range Load Current for Biomedical Applications

Mahsa Shoaran, Yasemin Engür

This paper presents an output capacitor-less low-dropout regulator (LDO) with a bias switching scheme for biomedical applications with dual-range load currents. Power optimization is crucial for systems with multiple activation modes such as neural interfa ...

ArXiv2023

Surface Charge Boundary Condition Often Misused in CO2 Reduction Models

Sophia Haussener, Etienne Boutin, Evan Fair Johnson

The Poisson-Nernst-Planck equations have been used to model species transport in electrochemical CO2 reduction, where the surface charge boundary condition accounts for the potential drop across the Stern layer. A direct comparison of the published models ...

AMER CHEMICAL SOC2023

Environmental determinants of access to shared sanitation in informal settlements: a cross-sectional study in Abidjan and Nairobi

Jérôme Chenal, Vitor Pessoa Colombo, Jürg Utzinger

Background Universal access to basic sanitation remains a global challenge, particularly in low- and middle-income countries. Efforts are underway to improve access to sanitation in informal settlements, often through shared facilities. However, access to ...

2023

Diverse parameters of ambulatory knee moments differ with medial knee osteoarthritis severity and are combinable into a severity index

Julien Favre, Brigitte Jolles-Haeberli

Objective: To characterize ambulatory knee moments with respect to medial knee osteoarthritis (OA) severity comprehensively and to assess the possibility of developing a severity index combining knee moment parameters. ...

FRONTIERS MEDIA SA2023

Sampling of alternatives in migration aspiration models

Michel Bierlaire, Evangelos Paschalidis

The use of discrete choice models (DCMs) is a regular approach to investigating migration aspirations concerning destination choices. However, given the complex substitution patterns between destinations, more advanced model specifications than the multino ...

2023