Publications associées à Molecular hypergraph neural networks

Publications associées (30)

Structural divergence of molecular hole selective materials for viable p-i-n perovskite photovoltaics: a comprehensive review

Perovskite solar cells (PSCs) have garnered significant attention within the photovoltaic research community due to their remarkable progress in just one decade. Among the device configurations, the p-i-n structured PSC offers several advantages, including ...

Royal Society of Chemistry2024

From PV to EV: Mapping the Potential for Electric Vehicle Charging with Solar Energy in Europe

Christophe Ballif, Nicolas Würsch, Alejandro Pena Bello, Noémie Alice Yvonne Ségolène Jeannin, Jérémy Dumoulin

The electrification of the transport sector is a key element in decarbonizing our societies. However, energy systems will have to cope with additional electricity demand due to the charging needs of electric vehicles (EVs) together with the integration of ...

2024

Reliability and Long-term Performance of Building Integrated Photovoltaic (BIPV) Modules

Ebrar Özkalay

Solar photovoltaics (PV) is one of the most competitive renewable energy technologies in order to meet the increasing global energy demand and decrease CO2 emissions by competing effectively with fossil fuels. One of the important applications of PV energy ...

EPFL2024

Elimination of buried interfacial voids for efficient perovskite solar cells

Bin Ding, Xianfu Zhang

Establishing optimal interfacial contact is crucial for enhancing the efficiency of perovskite solar cells (PSCs). However, formation of voids at buried interface of perovskite films often hinders this critical objective. Our investigation reveals that the ...

Elsevier2024

Network time series forecasting in photovoltaics power production

Jelena Simeunovic

Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of more renewable energy sources into the power grid. PV power production is highly intermittent, due to the stochastic cloud behaviour and cloud dynamics. Previous w ...

EPFL2024

Stress tolerance of lightweight glass-free PV modules for vehicle integration

Kléber Nicolet-dit-Félix, Christophe Ballif, Matthieu Despeisse, Aïcha Hessler-Wyser, Jacques Levrat, Antonin Faes, Gianluca Cattaneo, Umang Bhupatrai Desai, Fahradin Mujovi

Electric vehicles (EVs) currently dominate the sales in the automotive market. A big leap in this market can be made by developing a photovoltaic product that can be integrated to an EV, as it can boost the driving range of the EV while reducing the chargi ...

Edp Sciences S A2024

Shortwave Infrared-Sensitive, Narrowband Organic Upconversion Devices with a Gain

Wei-Hsu Hu

Sensing and imaging of light in the shortwave infrared (SWIR) range is increasingly used in various fields, including bio-imaging, remote sensing, and semiconductor process control. SWIR-sensitive organic photodetectors (OPDs) are promising because organic ...

EPFL2024

Controlling On-Surface Photoactivity: The Impact of π-Conjugation in Anhydride-Functionalized Molecules on a Semiconductor Surface

Christian Wäckerlin

On-surface synthesis has become a prominent method for growing low-dimensional carbon-based nanomaterials on metal surfaces. However, the necessity of decoupling organic nanostructures from metal substrates to exploit their properties requires either trans ...

Wiley-VCH Verlag GmbH2024

Investigating Non-equilibrium Physics in Wide Bandgap Semiconductors and Quantum Materials via Ultrafast Spectroscopy

Hui-Yuan Chen

This thesis uses femtosecond laser spectroscopy in studying strong correlation in condensed matters that are pertinent to future technology: a wide bandgap perovskite and a quantum material, with the employment of ultrafast time-resolved spectroscopy in th ...

EPFL2024

Computational Studies on the Stability of Organic-Inorganic Hybrid Halide Lead Perovskites

Mathias Dankl

Perovskite-based solar cells are currently the most rapidly advancing photovoltaic technology but concerns about their long-term stability are still impeding full-scale commercialization. This thesis provides computational insights into some of the stabili ...

EPFL2024

Advanced Manufacturing and Characterization of Building-Integrated Photovoltaic Modules

Alejandro Borja Block

Photovoltaic (PV) technology is necessary for global decarbonization. However, one of the challenges of the technology is that its land use may conflict with other space demands. Building-integrated photovoltaic (BIPV) is a solution to efficiently use the ...

EPFL2024

The connection of the acyclic disconnection and feedback arc sets - On an open problem of Figueroa et al

Lukas Fritz Felix Vogl

We examine the connection of two graph parameters, the size of a minimum feedback arcs set and the acyclic disconnection. A feedback arc set of a directed graph is a subset of arcs such that after deletion the graph becomes acyclic. The acyclic disconnecti ...

Elsevier2024

Gibbs sampling the posterior of neural networks

Lenka Zdeborová, Emanuele Troiani, Giovanni Piccioli

In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

Iop Publishing Ltd2024

Assessing the Charge Carrier Dynamics at Hybrid Interfaces of Organic Photoanodes for Solar Fuels

Kevin Sivula, Yongpeng Liu, Han-Hee Cho

Organic semiconductors (OSCs) have emerged as promising active layers for photoanodes to drive photoelectrochemical (PEC) oxidation reactions. Interfacing an OSC with an inorganic electron transport layer (ETL) is key to enabling both high performance and ...

Amer Chemical Soc2024

Interfacial engineering through lead binding using crown ethers in perovskite solar cells

Kevin Sivula, Jun Ho Yum, Jovana Milic, Jiyoun Seo, Yeonju Kim

In the domain of perovskite solar cells (PSCs), the imperative to reconcile impressive photovoltaic performance with lead-related issue and environmental stability has driven innovative solutions. This study pioneers an approach that not only rectifies lea ...

Elsevier2024

Towards improving full-length ribosome density prediction by bridging sequence and graph-based representations

Mohan Vamsi Nallapareddy, Pierre Vandergheynst, Felix Naef, Cédric Gobet, Francesco Craighero

Translation elongation plays an important role in regulating protein concentrations in the cell, and dysregulation of this process has been linked to several human diseases. In this study, we use data from ribo-seq experiments to model ribosome densities, ...

PMLR2024

Identification and Mitigation of Degradation Mechanisms Induced by Heat and Light in NiOx-based Perovskite Solar Cells

Marion Solange Madeleine Dussouillez

Perovskite solar cells (PSCs) offer an attractive solution to increase the efficiency of PV panels via perovskite/silicon tandems thanks to their potential cost-effectiveness and high efficiency. In inverted PSC architecture (p-i-n), commonly used hole con ...

EPFL2024

Reach For the Arcs: Reconstructing Surfaces from SDFs via Tangent Points

Yingying Ren

We introduce an algorithm to reconstruct a mesh from discrete samples of a shape's Signed Distance Function (SDF). A simple geometric reinterpretation of the SDF lets us formulate the problem through a point cloud, from which a surface can be extracted wit ...

Association for Computing Machinery2024

Tracking deep-level defects in degrading perovskite solar cells with a multifactorial approach

Vivek Subramanian

In this work, we provide a mechanistic understanding of the degradation of perovskite solar cells in operation by focusing on methylammonium lead triiodide (CH3NH3PbI3 or MAPbI3) and tracking the evolution of electronic defects via photo-induced current tr ...

Elsevier2024

Benchmarking machine-readable vectors of chemical reactions on computed activation barriers

Anne-Clémence Corminboeuf, Puck Elisabeth van Gerwen, Ksenia Briling, Yannick Calvino Alonso

In recent years, there has been a surge of interest in predicting computed activation barriers, to enable the acceleration of the automated exploration of reaction networks. Consequently, various predictive approaches have emerged, ranging from graph-based ...

Royal Soc Chemistry2024