Publications associées à Data Reconciliation in Reaction Systems using the Concept of Extents

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

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

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

Global existence for perturbations of the 2D stochastic Navier-Stokes equations with space-time white noise

Martin Hairer

We prove global in time well-posedness for perturbations of the 2D stochastic Navier-Stokes equations partial derivative( t)u + u center dot del u = Delta u - del p + sigma + xi, u(0, center dot ) = u(0),div (u) = 0, driven by additive space-time white noi ...

Springernature2024

Oxidation processes and me

Urs von Gunten

This publication summarizes my journey in the field of chemical oxidation processes for water treatment over the last 30+ years. Initially, the efficiency of the application of chemical oxidants for micropollutant abatement was assessed by the abatement of ...

Pergamon-Elsevier Science Ltd2024

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Ksenia Briling

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

EPFL2024

Extensions of Peer Prediction Incentive Mechanisms

Adam Julian Richardson

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

EPFL2024

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

Mario Paolone, Vladimir Sovljanski

Electrochemical Impedance Spectroscopy (EIS) and Equivalent Circuit Models (ECMs) are widely used to characterize the impedance and estimate parameters of electrochemical systems such as batteries. We use a generic ECM with ten parameters grouped to model ...

2024

New Applications of 1,3,2-Diazaphospholenes in Catalysis

Johannes Klett

The constant urge to construct new molecules in an economical and sustainable fashion led to the development of numerous metal-catalyzed transformations. Organocatalysts consisting of abundant and more sustainable elements offer an elegant solution to over ...

EPFL2024

FETCH: A Fast and Efficient Technique for Channel Selection in EEG Wearable Systems

David Atienza Alonso, Amir Aminifar, Alireza Amirshahi, José Angel Miranda Calero, Jonathan Dan

The rapid development of wearable biomedical systems now enables real-time monitoring of electroencephalography (EEG) signals. Acquisition of these signals relies on electrodes. These systems must meet the design challenge of selecting an optimal set of el ...

2024

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

Tobias Kippenberg, Nils Johan Engelsen, Alberto Beccari

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by 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

Probing Catalytic Sites and Adsorbate Spillover on Ultrathin FeO2-x Film on Ir(111) during CO Oxidation

Harald Brune, Hao Yin, Wei Fang

The spatially resolved identification of active sites on the heterogeneous catalyst surface is an essential step toward directly visualizing a catalytic reaction with atomic scale. To date, ferrous centers on platinum group metals have shown promising pote ...

Amer Chemical Soc2024

Optimal Depth of Discharge for Electric Batteries with Robust Capacity-Shrinkage Estimator

Thomas Alois Weber

A user’s benefit from the energy stored in a battery over its lifetime depends on the time-varying characteristics of the battery, which are in turn affected by the chosen usage behavior. Both the capacity shrinkage and the number of lifetime cycles are st ...

2024

Graph generative deep learning models with an application to circuit topologies

Igor Krawczuk

Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

EPFL2024

Room-temperature quantum optomechanics using an ultralow noise cavity

Tobias Kippenberg, Nils Johan Engelsen, Alberto Beccari, Guanhao Huang

At room temperature, mechanical motion driven by the quantum backaction of light has been observed only in pioneering experiments in which an optical restoring force controls the oscillator stiffness1,2. For solid-state mechanical resonators in which oscil ...

Nature Portfolio2024

OASIS: An integrated optimisation framework for activity scheduling

Janody Pougala

Activity-based models offer the potential for a far deeper understanding of daily mobility behaviour than trip-based models. Based on the fundamental assumption that travel demand is derived from the need to do activities, they are flexible tools that aim ...

EPFL2024

Scalable constrained optimization

Maria-Luiza Vladarean

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

EPFL2024

Exploiting the Signal-Leak Bias in Diffusion Models

Sabine Süsstrunk, Radhakrishna Achanta, Mahmut Sami Arpa, Athanasios Fitsios, Martin Nicolas Everaert

There is a bias in the inference pipeline of most diffusion models. This bias arises from a signal leak whose distribution deviates from the noise distribution, creating a discrepancy between training and inference processes. We demonstrate that this signa ...

2024

BENIGN LANDSCAPES OF LOW-DIMENSIONAL RELAXATIONS FOR ORTHOGONAL SYNCHRONIZATION ON GENERAL GRAPHS

Nicolas Boumal

Orthogonal group synchronization is the problem of estimating n elements Z(1),& mldr;,Z(n) from the rxr orthogonal group given some relative measurements R-ij approximate to Z(i)Z(j)(-1). The least-squares formulation is nonconvex. To avoid its local minim ...

Siam Publications2024

Self-catalysed frontal polymerisation enables fast and low-energy processing of fibre reinforced polymer composites

Véronique Michaud, Baris Çaglar, Jacobus Gerardus Rudolph Staal

Frontal polymerisation has the potential to bring unprecedented reductions in energy demand and process time to produce fibre reinforced polymer composites. Production of epoxy-based fibre reinforced polymer parts with high fibre volume content, commonly e ...

2024