Publications related to Structured and porous materials particularly suitable as polarizing agents in dissolution dynamic nuclear polarization

Tuning the reactivity of uranium towards small molecules in multimetallic complexes

One of the main goals of organometallic chemistry in the last decades was the activation of small molecule in mild reaction conditions. Even though multiple examples of catalytic cycles able to produce fine chemicals from cheap and abundant sources using t ...

EPFL2023

Synthesis, isolation and application of a sila-ketenyl anion

Rosario Scopelliti, Shiori Fujimori

Ynolates or ketenyl anions, [RCCO]-, are negatively charged reactive intermediates, which can be generated in situ and used for divergent chemical transformations. Ynolates can react either at the oxygen or carbon centres or across the C-C triple bond, mak ...

Springernature2023

Expanding computational biochemistry towards complex and non-natural compounds

Anastasia Sveshnikova

In the beginning was the metabolism. The biochemical processes that make life possible transformed the soup of chemicals into the life on Earth we know today. Since then, living organisms have evolved, and life on Earth has become more complex. Living orga ...

EPFL2023

Hybridization driving distortions and multiferroicity in rare-earth nickelates

Nicola Marzari, Iurii Timrov, Michele Kotiuga, Luca Binci

For decades transition-metal oxides have generated a huge interest due to the multitude of physical phenomena they exhibit. In this class of materials, the rare-earth nickelates, RNiO3, stand out for their rich phase diagram stemming from complex couplings ...

Amer Physical Soc2023

Influence of aerosol acidity and organic ligands on transition metal solubility and oxidative potential of fine particulate matter in urban environments

Gerhard Lammel, Athanasios Nenes

The adverse health effects of air pollution around the world have been associated with the inhalation of fine particulate matter (PM2.5). Such outcomes are thought to be related to the induction of oxidative stress due to the excess formation of reactive o ...

Elsevier2023

Visualization and modelling of dynamic flow in fibrous preforms for liquid composite molding

Helena Luisa Teixido Pedarros

Nowadays, Liquid Composite Molding techniques are often used to manufacture high quality fiber reinforced composite parts at a relatively low cost. These involve an infiltration process, in which a liquid resin is forced to ingress into a dry fibrous porou ...

EPFL2023

Modelling of metal alloys in realistic conditions with machine learning

Nataliya Lopanitsyna

Computer simulations based on statistical methods have emerged as a powerful tool for studying structure-property relationships at the atomistic level. However, to provide reliable insights into materials in realistic conditions, it is essential to accurat ...

EPFL2023

cell2mol: encoding chemistry to interpret crystallographic data

Anne-Clémence Corminboeuf, Sergio Vela Llausi, Yuri Cho, Rubén Laplaza Solanas

The creation and maintenance of crystallographic data repositories is one of the greatest data-related achievements in chemistry. Platforms such as the Cambridge Structural Database host what is likely the most diverse collection of synthesizable molecules ...

NATURE PORTFOLIO2022

Maintenance scheduling of manufacturing systems based on optimal price of the network

Olga Fink

Goods can exhibit positive externalities impacting decisions of customers in social networks. Suppliers can integrate these externalities in their pricing strategies to increase their revenue. Besides optimizing the prize, suppliers also have to consider t ...

2022

Opinion Formation over Adaptive Networks

Virginia Bordignon

An adaptive network consists of multiple communicating agents, equipped with sensing and learning abilities that allow them to extract meaningful information from measurements. The objective of the network is to solve a global inference problem in a decent ...

EPFL2022

Investigating cognitive ability using action-based models of structural brain networks

Enrico Amico

Recent developments in network neuroscience have highlighted the importance of developing techniques for analysing and modelling brain networks. A particularly powerful approach for studying complex neural systems is to formulate generative models that use ...

OXFORD UNIV PRESS2022

Applicability of the landscape evolution model in the absence of rills

David Andrew Barry, Paolo Perona, Seifeddine Jomaa, Andrea Rinaldo, Mohsen Cheraghi, Andrea Cimatoribus

Despite numerous applications of physically-based models for incised landscapes, their applicability for overland flow on unchanneled surfaces is not known. This work challenges a widely used landscape evolution model for the case of non-uniform rainfall a ...

2022

Pivotal Role of Intersite Hubbard Interactions in Fe-Doped alpha-MnO2

Iurii Timrov

We present a first-principles investigation of the structural, electronic, and magnetic properties of the pristine and Fe-doped alpha-MnO2 using density-functional theory with extended Hubbard functionals. The onsite U and intersite V Hubbard parameters ar ...

AMER CHEMICAL SOC2022

Mapping Catalyst‐Solvent Interplay in Competing Carboamination/Cyclopropanation Reactions

Anne-Clémence Corminboeuf, Matthew Wodrich, Nicolai Cramer, Miyeon Chang, Simone Gallarati

Group 9 metals, in particular Rh III complexes with cyclopentadienyl ligands, are competent C–H activation catalysts. Recently, a Cp*Rh III catalyzed reaction of alkenes with N -enoxyphthalimides showed divergent outcome based on the solvent, with carboami ...

2022

Modeling non-covalent interactions in condensed phase

Veronika Juraskova

The modeling of non-covalent interactions, solvation effects, and chemical reactions in complex molecular environment is a challenging task. Current state-of-the-art approaches often rely on static computations using implicit solvent models and harmonic ap ...

EPFL2022

Galvanic replacement reactions of Ga and In with Cu for the synthesis of bimetallic nanoparticles

Laia Castilla Amorós

The need for efficient and selective catalysts, capable of driving important conversions to build a more sustainable society, encourages the development of synthetic approaches towards new nanomaterials. Cu-based bimetallic nanoparticles (NPs) promise to f ...

EPFL2022

Using collective knowledge to assign oxidation states of metal cations in metal-organic frameworks

Seyedmohamad Moosavi, Berend Smit, Daniele Ongari, Kevin Maik Jablonka

Knowledge of the oxidation state of metal centres in compounds and materials helps in the understanding of their chemical bonding and properties. Chemists have developed theories to predict oxidation states based on electron-counting rules, but these can f ...

NATURE RESEARCH2021

True scale-free networks hidden by finite size effects

Andrea Rinaldo, Samir Suweis, Amos Maritan

We analyze about 200 naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned on the basis of statisti ...

National Academy of Sciences2021

The physics of higher-order interactions in complex systems

Enrico Amico, Benedetta Franceschiello

Network representations of complex systems are limited to pairwise interactions, but real-world systems often involve higher-order interactions. This Perspective looks at the new physics emerging from attempts to characterize these interactions. ...

NATURE PORTFOLIO2021

Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data

Tao Lin, Sai Praneeth Reddy Karimireddy, Martin Jaggi, Sebastian Urban Stich

Decentralized training of deep learning models is a key element for enabling data privacy and on-device learning over networks. In realistic learning scenarios, the presence of heterogeneity across different clients' local datasets poses an optimization ch ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021