Publications associées à A data-driven interpretation of the stability of organic molecular crystals

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

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

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

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

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

Machine learning-aided generative molecular design

Philippe Schwaller, Jeff Guo

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Nature Portfolio2024

Confinement-Controlled Crystallization of Guanine

Esther Amstad, Chuen-Ru Li

Guanine crystals are frequently encountered in nature in the beta-polymorph to create structural colors, to enhance the vision of creatures, and for camouflage. Unfortunately, it is challenging to control the crystallization of guanine in aqueous condition ...

Amer Chemical Soc2024

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

EPFL2024

Learning Informative Health Indicators Through Unsupervised Contrastive Learning

Olga Fink

Monitoring the health of complex industrial assets is crucial for safe and efficient operations. Health indicators that provide quantitative real-time insights into the health status of industrial assets over time serve as valuable tools for, e.g., fault d ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Solvation Free Energies from Machine Learning Molecular Dynamics

Nicola Marzari, Nicéphore Arthur François Bonnet

The present work proposes an extension to the approach of [Xi, C; et al. J. Chem. Theory Comput. 2022, 18, 6878] to calculate ion solvation free energies from first-principles (FP) molecular dynamics (MD) simulations of a hybrid solvation model. The approa ...

Amer Chemical Soc2024

NMR Crystallography in the Big Data Era: New Methods and Applications Powered by Machine Learning

Manuel Cordova

Structure determination of materials is key to understanding their physical properties. While single-crystal X-ray diffraction is the gold standard for structures displaying long-range order, many materials of interest are polycrystalline and/or disordered ...

EPFL2023

Direct Observation of the Phase Transition in C60 Fullerene

Chengcheng Yan

In the third study, the order-disorder phase transition of single-crystal C60 is studied using time-resolved electron microscopy. Solid C60 undergoes a first-order phase transition upon heating to 260 K. This is a structural transition from the low-tempera ...

EPFL Infoscience2023

Controlling the crystal structure of succinic acid via microfluidic spray-drying

Aysu Ceren Okur, Esther Amstad

Many properties of materials, including their dissolution kinetics, hardness, and optical appearance, depend on their structure. Unfortunately, it is often difficult to control the structure of low molecular weight organic compounds that have a high propen ...

ROYAL SOC CHEMISTRY2023

Chemical Shift-Dependent Interaction Maps in Molecular Solids

Manuel Cordova, David Lyndon Emsley

Structure determinationof molecular solids through NMR crystallographyrelies on the generation of a comprehensive set of candidate crystalstructures and on the comparison of chemical shifts computed for thosecandidates with experimental values. Exploring t ...

AMER CHEMICAL SOC2023

Pressure-freezing of dodecane: exploring the crystal structures, formation kinetics and phase diagrams for colossal barocaloric effects in n-alkanes

Tomasz Poreba

Barocaloric (BC) materials provide cheaper and more energy efficient alternatives to traditional refrigerants. Some liquid alkanes were recently shown to exhibit a colossal BC effect, matching the entropy changes in commercial vapour-liquid refrigerants. D ...

Royal Soc Chemistry2023

Toward data-driven materials design: From atoms to pilot plants

Kevin Maik Jablonka

Discovering new materials is essential but challenging, time-consuming, and expensive. In many cases, simulations can be useful for estimating material properties. For many of the most interesting properties, however, simulations are infeasible because of ...

EPFL2023

What do we talk about, when we talk about single-crystal termination-dependent selectivity of Cu electrocatalysts for CO2 reduction? A data-driven retrospective

Kevin Rossi

We mine from the literature experimental data on the CO2 electrochemical reduction selectivity of Cu single crystal surfaces. We then probe the accuracy of a machine learning model trained to predict faradaic efficiencies for 11 CO2 reduction reaction prod ...

ROYAL SOC CHEMISTRY2023

Melting pseudosymmetry and thermal expansion in 3-benzoylpropionic acid

Tomasz Poreba

The thermal behavior of 3-benzoylpropionic acid (BPA) was investigated using single-crystal and synchrotron powder X-diffraction, as well as differential scanning calorimetry analysis. The study revealed the existence of two subtly distinct structures of B ...

ROYAL SOC CHEMISTRY2023

Selectively permeable microcapsules

Chuen-Ru Li

Microcapsules are appealing containers for delivering active ingredients, such as drugs and cosmetics, or conducting chemical and biological reactions on a small scale. To control the timing and location of release of these encapsulants, the shells of micr ...

EPFL2023

In Situ and Time-Resolved Transmission Electron Microscopy of Nanoscale Processes

Chengcheng Yan

Observing the fast dynamics of nanoscale systems is crucial in order to understand and ultimately control their behavior. Characterizing these dynamic processes requires techniques with atomic spatial resolution and a temporal resolution that matches the t ...

EPFL2023