Publications associées à Accelerated Discovery of Metal-Organic Frameworks (MOFs) For Energy Related Applications

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

Wendy Lee Queen, Jocelyn Richard Roth, 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

Orientational Self-Sorting in Octahedral Palladium Cages: Scope and Limitations of the “cis Rule”

Kay Severin, Farzaneh Fadaei Tirani, Damien Wen Chen, Jean Charles Edouard de Montmollin, Atena-Bianca Solea

Octahedral coordination cages of the general formula Pd6L1212 were obtained by combining Pd(CH3CN)42 with heteroditopic N-donor ligands. Four different ligands were employed. These ligands have 3-pyridyl donor groups at one end and 4-pyridyl, ...

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

Data from: Optimal blade pitch control for enhanced vertical-axis wind turbine performance

Karen Ann J Mulleners, Sébastien Le Fouest

This directory contains open-source data obtained using a single-bladed H-type vertical-axis wind turbine prototype with individual blade pitching. This data results from the optimisation of the blade's pitching kinematics using a genetic algorithm at two ...

Zenodo2024

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

Reliability and Long-term Performance of Building Integrated Photovoltaic (BIPV) Modules

Ebrar Özkalay

Solar photovoltaics (PV) is one of the most competitive renewable energy technologies in order to meet the increasing global energy demand and decrease CO2 emissions by competing effectively with fossil fuels. One of the important applications of PV energy ...

EPFL2024

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

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

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

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

Solar-assisted clean steam generator, a cleaner production approach for sustainable healthcare facilities

Fernando Porté Agel, Mohammad Jamshidmofid, Ahmad Arabkoohsar

Healthcare sector buildings, particularly hospitals, significantly contribute to global energy consumption and greenhouse gas emissions. Hospitals require a substantial amount of steam, including the essential hygienic or " clean steam, " that is currently ...

Elsevier Sci Ltd2024

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