Publications related to On the use of shape constraints for state estimation in reaction systems

Related publications (28)

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

System for predicting a prognosis of the neuropsychological and/or neuropsychiatric status in a subject

Olaf Blanke, Fosco Bernasconi

The present invention relates to systems and methods for predicting a prognosis of the neuropsychological and/or neuropsychiatric status in a subject based on reports of Minor Hallucination (MH) events in combination with electrophysiological data of the s ...

2024

Inferring free-energy barriers and kinetic rates from molecular dynamics via underdamped Langevin models

David Daniel Girardier, Fabio Pietrucci, Sara Bonella

Rare events include many of the most interesting transformation processes in condensed matter, from phase transitions to biomolecular conformational changes to chemical reactions. Access to the corresponding mechanisms, free-energy landscapes and kinetic r ...

Aip Publishing2023

Real-Time Localization for Closed-Loop Control of Assistive Furniture

Chuanfang Ning, Auke Ijspeert, Alexandre Massoud Alahi, George Adaimi, Anastasia Bolotnikova, Lixuan Tang

For people with limited mobility, navigating in cluttered indoor environment is challenging. In this work, we propose a mobile assistive furniture suite that is designed to ease the life of people with special needs in indoor movement. To enable intelligen ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

CO2 Capture and Release in Amine Solutions: To What Extent Can Molecular Simulations Help Understand the Trends?

Wanda Andreoni, Fabio Pietrucci, Changru Ma

Absorption in amine solutions is a well-established advanced technology for CO2 capture. However, the fundamental aspects of the chemical reactions occurring in solution still appear to be unclear. Our previous investigation of aqueous monoethanolamine (ME ...

2023

Experimental Validation of a Unified and Linear State Estimation Method for Hybrid AC/DC Microgrids

Mario Paolone, Willem Lambrichts

This paper presents the experimental validation of a linear recursive state estimation (SE) process for hybrid AC/DC microgrids proposed in the authors' previous work. The SE uses a unified and linear measurement model that relies on the use of synchronize ...

IEEE2023

Regularization for distributionally robust state estimation and prediction

Giancarlo Ferrari Trecate, Jean-Sébastien Hubert Brouillon

The increasing availability of sensing techniques provides a great opportunity for engineers to design state estimation methods, which are optimal for the system under observation and the observed noise patterns. However, these patterns often do not fulfil ...

2023

Understanding the growth mechanism of BaZrS3 chalcogenide perovskite thin films from sulfurized oxide precursors

Anna Fontcuberta i Morral, Mirjana Dimitrievska, Elias Zsolt Stutz, Santhanu Panikar Ramanandan, Andrea Giunto

Barium zirconium sulfide (BaZrS3) is an earth-abundant and environmentally friendly chalcogenide perovskite with promising properties for various energy conversion applications. Recently, sulfurization of oxide precursors has been suggested as a viable sol ...

IOP Publishing Ltd2023

Bayesian Optimization for Chemical Reactions

Philippe Schwaller, Jeff Guo, Bojana Rankovic

Reaction optimization is challenging and traditionally delegated to domain experts who iteratively pro-pose increasingly optimal experiments. Problematically, the reaction landscape is complex and often requires hundreds of experiments to reach convergence ...

Swiss Chemical Soc2023

Development of next-generation microfluidic systems for enhanced, faster, and cost-effective immunoassays for tissue diagnostics - Ac electrothermal flow & Acoustofluidics

Muaz Salama Abdelmonem Draz

The application of microfluidics in the field of surface-based assays and more specifically, the spatial molecular profiling of tumor tissues has gained a lot of interest, especially with the increased interest in personalized medicine and targeted therapy ...

EPFL2023

Grand canonical Brownian dynamics simulations of adsorption and self-assembly of SAS-6 rings on a surface

Pierre Gönczy, Niccolo Banterle

The Spindle Assembly Abnormal Protein 6 (SAS-6) forms dimers, which then self-assemble into rings that are critical for the nine-fold symmetry of the centriole organelle. It has recently been shown experimentally that the self-assembly of SAS-6 rings is st ...

AIP Publishing2023

Image scanning microscopy with a doughnut beam: signal strength and integrated intensity

Giorgio Tortarolo

We discuss the effects of image scanning microscopy using doughnut beam illumination on the properties of signal strength and integrated intensity. Doughnut beam illumination can give better optical sectioning and background rejection than Airy disk illumi ...

Optica Publishing Group2023

Timing and spatial selection bias in rapid extreme event attribution

Anthony Christopher Davison, Ophélia Mireille Anna Miralles

Selection bias may arise when data have been chosen in a way that subsequent analysis does not account for. Such bias can arise in climate event attribution studies that are performed rapidly after a devastating "trigger event'', whose occurrence correspon ...

ELSEVIER2023

Data-Driven Unknown-Input Observers and State Estimation

Giancarlo Ferrari Trecate, Mustafa Sahin Turan

Unknown-input observers (UIOs) allow for estimation of the states of an LTI system without knowledge of all inputs. In this letter, we provide a novel data-driven UIO based on behavioral system theory and the result known as Fundamental Lemma proposed by J ...

2022

Emergent thermophoretic behavior in chemical reaction systems

Paolo De Los Rios, Daniel Maria Busiello, Shiling Liang

Exposing a solution to a temperature gradient can lead to the accumulation of particles on either the cold or warm side. This phenomenon is known as thermophoresis, and its microscopic origin is still debated. Here, we show that thermophoresis can be obser ...

IOP Publishing Ltd2022

The influence of sulfate addition on hydration kinetics and C-S-H morphology of C3S and C3S/C(3)A systems

Karen Scrivener, Franco Alberto Zunino Sommariva

A comprehensive understanding of hydration kinetics, sulfate requirement and phase assemblage of Portland cement is crucial for further optimization of early-age performance, especially when part of cement is replaced by mineral additions in blended cement ...

Pergamon-Elsevier Science Ltd2022

Dynamical low rank approximation for uncertainty quantification of time-dependent problems

Eva Vidlicková

The quantification of uncertainties can be particularly challenging for problems requiring long-time integration as the structure of the random solution might considerably change over time. In this respect, dynamical low-rank approximation (DLRA) is very a ...

EPFL2022

Graph signal processing tailored for subgraph focus and community structure

Miljan Petrovic

Community structure in graph-modeled data appears in a range of disciplines that comprise network science. Its importance relies on the influence it bears on other properties of graphs such as resilience, or prediction of missing connections. Nevertheless, ...

EPFL2022

Imaging of Chemical Kinetics at the Water–Water Interface in a Free-Flowing Liquid Flat-Jet

Andreas Osterwalder, Bruno Credidio

We present chemical kinetics measurements of the luminol oxidation chemiluminescence (CL) reaction at the interface between two aqueous solutions, using liquid jet technology. Free-flowing liquid microjets are a relatively recent development that have foun ...

2022

Filtered data and eigenfunction estimators for statistical inference of multiscale and interacting diffusion processes

Andrea Zanoni

We study the problem of learning unknown parameters of stochastic dynamical models from data. Often, these models are high dimensional and contain several scales and complex structures. One is then interested in obtaining a reduced, coarse-grained descript ...

EPFL2022