Publications associées à Understanding the diversity of the metal-organic framework ecosystem

Publications associées (45)

Radical-Mediated Azidation of Benzylic C-H Bonds and Azidofunctionalization of Alkenes

Organic azides are known for their reactivity and broad applicability in organic synthesis. These compounds are pivotal in various chemical transformations, including nucleophilic substitution and cycloaddition reactions. Beyond synthetic chemistry, organi ...

EPFL2025

Domain shift, domain adaptation, and generalization: A focus on MRI

Tobias Kober, Meritxell Bach Cuadra, Veronica Lily Ravano, Jonas Richiardi

Differences in acquisition protocols or hardware result in measurable changes in image characteristics. These differences affect distributional properties and can also affect the spatial and temporal characteristics of the images. Likewise, the distributio ...

Academic Press2025

Harnessing modular approaches in the study of crystalline sorbents

Balázs Álmos Novotny

Sorbent are the workhorses of most contemporary separation processes. Crystalline sorbents boast descript structures that facilitate in silico study. Their diversity is matched by their varied applications. At the forefront of their currently researched ap ...

EPFL2025

Engineering Frustrated Lewis Pair Active Sites in Porous Organic Scaffolds for Catalytic CO2 Hydrogenation

Anne-Clémence Corminboeuf, Rubén Laplaza Solanas, Shubhajit Das, Jacob Terence Blaskovits

Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes. Immobilizing the active Lewis sites to a solid support, especially to porous scaffolds, ...

Amer Chemical Soc2024

Distribution Testing with a Confused Collector

Nathaniel Idein Harms

We are interested in testing properties of distributions with systematically mislabeled samples. Our goal is to make decisions about unknown probability distributions, using a sample that has been collected by a confused collector, such as a machine-learni ...

Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing2024

Exploring crystallographic texture manipulation in stainless steels via laser powder bed fusion: insights from neutron diffraction and machine learning

Roland Logé

Laser powder bed fusion of metals (PBF-LB/M) is a pivotal additive manufacturing technique that enables the production of intricate components. In addition to enabling the production of complex shapes, it allows for a high degree of freedom in manipulating ...

Taylor & Francis2024

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

Wendy Lee Queen, Jocelyn Richard Roth

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

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Lakmal Buddika Meegahapola

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

EPFL2024

Oxidase-Type C-H/C-H Coupling Using an Isoquinoline-Derived Organic Photocatalyst

Xile Hu, Lei Zhang

Oxidase-type oxidation is an attractive strategy in organic synthesis due to the use of O-2 as the terminal oxidant. Organic photocatalysis can effect metal-free oxidase chemistry. Nevertheless, current methods are limited in reaction scope, possibly due t ...

Wiley-VCH Verlag GmbH2022

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

2

-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

EPFL2024

Development of metal-organic frameworks based on N-heterocyclic ligands

Ilia Kochetygov

Metal-organic frameworks (MOFs) have firmly established in the field of porous materials since their early discovery in the 1990s. With a plethora of applications, these materials offer endless possibilities owing to their tunable, modular nature. The vast ...

EPFL2022

Engineering novel protein interactions with therapeutic potential using deep learning-guided surface design

Anthony Marchand

Proteins are foundational biomolecules of life playing a crucial role in a myriad of biological processes. Their function often requires interplay with other biomolecules, including proteins themselves. Protein-protein interactions (PPIs) are essential for ...

EPFL2024

Organic Chemistry and Synthesis Rely More and More upon Catalysts

Pierre Vogel

A few months before the COVID-19 pandemic, Pierre Vogel and Kendall N. Houk published with a new textbook Wiley-VCH, "Organic Chemistry: Theory, Reactivity, and Mechanisms in Modern Synthesis", with a foreword from the late Roberts H. Grubbs. The book demo ...

MDPI2022

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Olga Fink, Hao Lu

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

2024

Amine Functionalization in Porous Adsorbents for Carbon Capture and Conversion

Anita Justin

Metal-organic Frameworks (MOFs) are a class of crystalline porous materials with exceptionally high surface area, chemical tunability and stability. Due to alarming CO2 emission and global concern, research is focused on developing porous materials like MO ...

EPFL2022

Model Tuning and Performance Evaluation in Machine Learning Models for PV Power Forecasting: Case Study of a BIPV System in Switzerland

Hugo James André Quest

High PV penetration into the electricity grid can lead to issues such as congestion if PV systems are not integrated effectively. Accurate PV power forecasting helps to address this issue. In recent years machine learning approaches have gotten a lot of at ...

Institute of Electrical and Electronics Engineers Inc.2024

Diversifying Databases of Metal Organic Frameworks for High-Throughput Computational Screening

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

By combining metal nodes and organic linkers, an infinite number of metal organic frameworks (MOFs) can be designed in silico. Therefore, when making new databases of such hypothetical MOFs, we need to ensure that they not only contribute toward the growth ...

AMER CHEMICAL SOC2021

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

Controlling On-Surface Photoactivity: The Impact of π-Conjugation in Anhydride-Functionalized Molecules on a Semiconductor Surface

Christian Wäckerlin

On-surface synthesis has become a prominent method for growing low-dimensional carbon-based nanomaterials on metal surfaces. However, the necessity of decoupling organic nanostructures from metal substrates to exploit their properties requires either trans ...

Wiley-VCH Verlag GmbH2024

Luminescent, porous, metal-organic crystals: Design, synthesis, and applications

Fatmah Ebrahim

The work presented in this thesis is focused on the design and discovery of new luminescent, porous, crystalline materials for targeted applications. In particular, we focus on luminescent Metal-Organic Frameworks (MOFs) and Organic Molecules of Intrinsic ...

EPFL2020