Publications associées à Building a Consistent and Reproducible Database for Adsorption Evaluation in Covalent-Organic Frameworks

A diversity-driven discovery of potential nanoporous materials for energy-related applications

The design and discovery of potential novel materials is critical for the advancement of climate change mitigation technologies. In this respect, metal-organic frameworks (MOFs) have received considerable attention over the last two decades. The combinatio ...

EPFL2024

Deep learning-based recommendation system for metal-organic frameworks (MOFs)

Berend Smit, Kevin Maik Jablonka, Xiaoqi Zhang

This work presents a recommendation system for metal-organic frameworks (MOFs) inspired by online content platforms. By leveraging the unsupervised Doc2Vec model trained on document-structured intrinsic MOF characteristics, the model embeds MOFs into a hig ...

Royal Soc Chemistry2024

Ru(II)-Arene Complexes of Curcumin and Bisdesmethoxycurcumin Metabolites

Paul Joseph Dyson, Farzaneh Fadaei Tirani, Mouna Hadiji

Curcuminoids and their complexes continue to attract attention in medicinal chemistry, but little attention has been given to their metabolic derivatives. Here, the first examples of (arene)Ru(II) complexes with curcuminoid metabolites, tetrahydrocurcumin ...

Amer Chemical Soc2024

Harnessing Porous Materials for Efficient Gas Capture: A Computational Exploration of Structure, Function, and Workflow Automation

Miriam Jasmin Pougin

Industrial chemistry heavily relies on traditional separation methods which are both energy-demanding and environmentally detrimental. This thesis addresses critical separation challenges, specifically carbon capture applications and the separation of ethy ...

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

The rule of four: anomalous distributions in the stoichiometries of inorganic compounds

Nicola Marzari, Carl Simon Adorf, Marnik Bercx, Elena Gazzarrini

Why are materials with specific characteristics more abundant than others? This is a fundamental question in materials science and one that is traditionally difficult to tackle, given the vastness of compositional and configurational space. We highlight he ...

Nature Portfolio2024

How Reproducible is the Synthesis of Zr-Porphyrin Metal-Organic Frameworks? An Interlaboratory Study

Jocelyn Richard Roth, Wendy Lee Queen, Rawan Al Natour

Metal-organic frameworks (MOFs) are a rapidly growing class of materials that offer great promise in various applications. However, the synthesis remains challenging: for example, a range of crystal structures can often be accessed from the same building b ...

Wiley-V C H Verlag Gmbh2024

Functionalized Å-scale Pores in Graphene for Carbon Capture

Kuang-Jung Hsu

Single-layer graphene, hosting a high density of functionalized molecular-sieving atom-thick pores, is considered to be an excellent material for gas separation membranes. These functionalized atom-thick pores enable the shortest transport pathway across t ...

EPFL2024

Tailoring nanocatalysts and reaction interfaces for water- and CO2-electrolysis

Thi Ha My Pham

Renewable energy sources offer a promising solution for mitigating sustainability and CO2 emissions-related issues due to their vast energy generation capacity. They enable hydrogen production via water electrolysis, as well as carbon capture and utilizati ...

EPFL2024

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

CO2 Capture and Management Strategies for Decarbonizing Secondary Aluminium Production

François Maréchal, Daniel Alexander Florez Orrego, Meire Ellen Gorete Ribeiro Domingos, Réginald Germanier

The production of aluminium largely depends on the use of fossil fuels, resulting in the emission of significant amounts of greenhouse gases. As the aluminium industry is working towards decreasing its environmental burdens, the elimination of direct emiss ...

2024

Beyond the coupled distortion model: structural analysis of the single domain cupredoxin AcoP, a green mononuclear copper centre with original features

Luciano Andres Abriata

Cupredoxins are widely occurring copper-binding proteins with a typical Greek-key beta barrel fold. They are generally described as electron carriers that rely on a T1 copper centre coordinated by four ligands provided by the folded polypeptide. The discov ...

Royal Soc Chemistry2024

Crystal, defect, and morphology engineering of porous two-dimensional materials for ionic separation

Heng-Yu Chi

Ordered two-dimensional (2D) materials hosting Å-scale pores are highly promising for enabling challenging separation, thanks to well-defined pore geometry resulting in tight confinement of ions when hosted inside the pore. In addition, the 2D nature of th ...

EPFL2024

Dataset to accompany publication "Quantum-mechanical effects in photoluminescence from thin crystalline gold films"

Giulia Tagliabue, Fateme Kiani Shahvandi, Theodoros Tsoulos, Alan Richard Bowman

This dataset accompanies the publication "Quantum-mechanical effects in photoluminescence from thin crystalline gold films" published in Light: Science & Applications (https://doi.org/10.1038/s41377-024-01408-2). The data can be used to reproduce plots 1-4 ...

Zenodo2024

Automated all-functionals infrared and Raman spectra

Nicola Marzari, Lorenzo Bastonero

Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture materials' features as spectroscopic fingerprints. Nevertheless, these measurements freq ...

Nature Portfolio2024

Multi-machine benchmark of the self-consistent 1D scrape-off layer model DIV1D from stagnation point to target with SOLPS-ITER

Holger Reimerdes

This paper extends a 1D dynamic physics-based model of the scrape-off layer (SOL) plasma, DIV1D, to include the core SOL and possibly a second target. The extended model is benchmarked on 1D mapped SOLPS-ITER simulations to find input settings for DIV1D th ...

Iop Publishing Ltd2024

Electronic structure and lattice dynamics of 1T-VSe2:Origin of the three-dimensional charge density wave

Ji Dai, Lorenzo Monacelli

To characterize in detail the charge density wave (CDW) transition of 1T-VSe2, its electronic structure and lattice dynamics are comprehensively studied by means of x-ray diffraction, muon spectroscopy, angle resolved photoemission (ARPES), diffuse and ine ...

Amer Physical Soc2024

Design and Synthesis of Bio-based Amphiphiles from Lignocellulosic Biomass

Songlan Sun

In the pursuit of a carbon-neutral chemical industry, minimizing fossil feedstock consumption while integrating renewable carbon sources is imperative. Surfactants, inherently amphiphilic, pose challenges in separation and recovery processes. Given their e ...

EPFL2024

Electronic transport in graphene with out-of-plane disorder

Oleg Yazyev, Yifei Guan

Real-world samples of graphene often exhibit various types of out-of-plane disorder-ripples, wrinkles and folds-introduced at the stage of growth and transfer processes. These complex out-of-plane defects resulting from the interplay between self-adhesion ...

Nature Portfolio2024

Orbital-Resolved DFT plus U for Molecules and Solids

Nicola Marzari, Iurii Timrov, Eric Macke

We present an orbital-resolved extension of the Hubbard U correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of energetic, electronic and structural properties is strongly improved, particula ...

Amer Chemical Soc2024