Publications associées à A systematic approach for thermal stability predictions of chemicals and their risk assessment: Pattern recognition and compounds classification based on thermal decomposition curves

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Julian Thomas Blackwell, Tanja Christina Käser Jacober, Paola Mejia Domenzain, Vinitra Swamy, Isadora Alves de Salles

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

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

Thermal transport of glasses via machine learning driven simulations

Federico Grasselli

Accessing the thermal transport properties of glasses is a major issue for the design of production strategies of glass industry, as well as for the plethora of applications and devices where glasses are employed. From the computational standpoint, the che ...

Frontiers Media Sa2024

Planning urban proximities: An empirical analysis of how residential preferences conflict with the urban morphologies and residential practices

Vincent Kaufmann, Luca Giovanni Pattaroni, Marc-Edouard Baptiste Grégoire Schultheiss

Urban proximity planning is foreseen as a solution to foster a “sustainable” city, including economic viability, environmental soundness and social inclusivity. This paper focuses on the inclusivity aspects by questioning the adoption of urban proximities: ...

2024

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

Ion Spectroscopy Reveals Structural Difference for Proteins Microhydrated by Retention and Condensation of Water

Oleg Boyarkine, Andrei Zviagin

Protein ubiquitin in its +7 charge state microhydrated by 5 and 10 water molecules has been interrogated in the gas phase by cold ion UV/IR spectroscopy. The complexes were formed either by condensing water onto the unfolded bare proteins in a temperature- ...

Amer Chemical Soc2024

Health Prediction for Lithium-Ion Batteries Under Unseen Working Conditions

Florent Evariste Forest, Yunhong Che

Battery health prediction is significant while challenging for intelligent battery management. This article proposes a general framework for both short-term and long-term predictions of battery health under unseen dynamic loading and temperature conditions ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Innovative thermophysical characterization of an ATF composite cladding: the case of silicon carbide

Andrea Cavaliere

Nuclear power is a powerful technology that plays an important role in the fight against climate change, and research is continuously engaged in studies that could further improve its safety. After the Fukushima accident, Accident Tolerant Fuels research h ...

EPFL2024

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the ...

Amer Chemical Soc2024

Multimodal fusion of liquid biopsy and CT enhances differential diagnosis of early-stage lung adenocarcinoma

Jun Lu, Hua Zhong, Li Zhang, Yunhua Zhang, Jiancheng Yang

This research explores the potential of multimodal fusion for the differential diagnosis of early-stage lung adenocarcinoma (LUAD) (tumor sizes < 2 cm). It combines liquid biopsy biomarkers, specifically extracellular vesicle long RNA (evlRNA) and the comp ...

Nature Portfolio2024

Efficient and insightful descriptors for representing molecular and material space

Alexander Jan Goscinski

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

EPFL2024

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

Melting pseudosymmetry and thermal expansion in 3-benzoylpropionic acid

Tomasz Poreba

The thermal behavior of 3-benzoylpropionic acid (BPA) was investigated using single-crystal and synchrotron powder X-diffraction, as well as differential scanning calorimetry analysis. The study revealed the existence of two subtly distinct structures of B ...

ROYAL SOC CHEMISTRY2023

Tailor-made Piezoelectric Elastomer Materials

Francis Owusu

Recent advancements in miniature devices with higher computational capabilities and ultralow power consumption have accelerated the development of wearable sensors, actuators, and energy harvesters everywhere. The ultimate aim of such a technological revol ...

EPFL2023

Advancing efficiency and reliability in thermal analysis of laser powder-bed fusion

Christian Leinenbach, Thomas Mayer, Rafal Wróbel

In laser based powder-bed fusion of metals (PBF-LB/M), parts are fabricated by melting layers of powder using a high-intensity laser beam. During this process, the material is exposed to rapid cooling rates and intense thermal gradients, which are the unde ...

2023

A Geometric Transformer for Structural Biology: Development and Applications of the Protein Structure Transformer

Lucien Fabrice Krapp

Proteins, the central building blocks of life, play pivotal roles in nearly every biological function. To do so, these macromolecular structures interact with their surrounding environment in complex ways, leading to diverse functional behaviors. The predi ...

EPFL2023

Landscapes of DNA Mechanics and Genomes

Thomas Antonin Zwahlen

The local physical properties - such as shape and flexibility - of the DNA double-helix is today widely believed to be influenced by nucleic acid sequence in a non-trivial way. Furthermore, there is strong evidence that these properties play a role in many ...

EPFL2023

AIFORE: Smart Fuzzing Based on Automatic Input Format Reverse Engineering

Chunmin Zhang, Mathias Josef Payer, Zhiyao Feng, Ji Shi

Knowledge of a program's input format is essential for effective input generation in fuzzing. Automated input format reverse engineering represents an attractive but challenging approach to learning the format. In this paper, we address several challenges ...

Usenix Assoc2023

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Nicola Parolini, Ntorina Thanou, David Kraus, Andrea Kraus, Daniel Lopez, Markus Scholz, Benjamin Bejar Haro, Daniel Rodrigo Lopez, Ekaterina Krymova, Tao Sun

Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive p ...

eLIFE SCIENCES PUBL LTD2023

Characterisation and hydration kinetics of beta-C2S synthesised with K2SO4 as dopant

Karen Scrivener, Shashank Bishnoi, Franco Alberto Zunino Sommariva, Sreejith Krishnan

In this study, a protocol for synthesising beta-C2S using K2SO4 as a dopant has been reported. Quantitative X-Ray diffraction was used to characterise synthesised samples. It was observed that it is possible to synthesise beta-C2S with high purity (>96 wt% ...

Pergamon-Elsevier Science Ltd2023