Publications associées à Force Field Development from Periodic Density Functional Theory Calculations for Gas Separation Applications Using Metal-Organic Frameworks

Publications associées (32)

Highly Active Photoreduction of Atmospheric-Concentration CO2 into CH3COOH over Palladium Particles on Nb2O5 Nanosheets

The endeavor to drive CO2 photoreduction towards the synthesis of C2 products is largely thwarted by the colossal energy hurdle inherent in C−C coupling. Herein, we load active metal particles on metal oxide nanosheets to build the dual metal pair sites fo ...

Wiley-VCH Verlag GmbH2025

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

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

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

Sauradeep Majumdar

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

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

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

Thermal transport of glasses via machine learning driven simulations

Federico Grasselli, Paolo Pegolo

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

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, Dareen Zuhir Omar Dardor

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

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Paolo Pegolo

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

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

Climate neutrality of the French energy system: overview and impacts of sustainable aviation fuel production

François Maréchal

(Formula presented.) emission reduction of sectors such as aviation, maritime shipping, road haulage, and chemical production is challenging but necessary. Although these sectors will most likely continue to rely on carbonaceous energy carriers, they are e ...

2024

Computational Studies on the Stability of Organic-Inorganic Hybrid Halide Lead Perovskites

Mathias Dankl

Perovskite-based solar cells are currently the most rapidly advancing photovoltaic technology but concerns about their long-term stability are still impeding full-scale commercialization. This thesis provides computational insights into some of the stabili ...

EPFL2024

Inverse design of metal-organic frameworks for direct air capture of CO2via deep reinforcement learning

Berend Smit, Sauradeep Majumdar, Xiaoqi Zhang

The combination of several interesting characteristics makes metal-organic frameworks (MOFs) a highly sought-after class of nanomaterials for a broad range of applications like gas storage and separation, catalysis, drug delivery, and so on. However, the e ...

Royal Soc Chemistry2024

Magnetism of Single Surface Adsorbed Atoms Studied with Radio-Frequency STM

Clément Marie Soulard

This thesis investigates the magnetic properties of single atoms and molecules adsorbed on thin magnesium oxide decoupling layers, grown on a silver single crystal. To address these systems experimentally, we use a low temperature scanning tunneling micros ...

EPFL2024

Densification and shaping of pure Cu-BTC powders using a solid-state chemical transformation

Wendy Lee Queen, Mehrdad Asgari, Vikram Vinayak Karve, Mathieu Soutrenon, Jordi Espin Marti

MOFs are a class of porous crystalline materials whose unique properties have led to applicability in several fields ranging from gas adsorption to drug delivery. Despite their high potential, MOFs are usually found as fine powders, a property that can lim ...

Iop Publishing Ltd2024

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

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

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

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

Nonempirical semilocal density functionals for correcting the self-interaction of polaronic states

Alfredo Pasquarello, Stefano Falletta

Through the use of the piecewise-linearity condition of the total energy, we correct the self-interaction for the study of polarons by constructing nonempirical functionals at the semilocal level of theory. We consider two functionals, the gamma DFT and mu ...

Aip Publishing2024

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Justin Villard

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

EPFL2023