Publication

Modeling non-covalent interactions in condensed phase

Publications associées (31)

Biophysically accurate and machine learning-based surrogate models to optimize neuroprosthesis design and operation

Electrical stimulation of the nervous system has emerged as a promising assistive technology in case of many injuries and illnesses across various parts of the nervous system. In particular, the invasive neuromodulation of the peripheral nervous system see ...

EPFL2024

Development of Sustainable Carbohydrate-Based Solvents by Acetal Functionalisation of Biomass

Anastasiia Komarova

Organic solvents are ubiquitous in industrial and domestic applications from the production of pharmaceuticals to household consumer products. The negative impact of most traditional solvents, especially aprotic types, on the environment, health, and safet ...

EPFL2024

Localized Ionic Reinforcement of Double Network Granular Hydrogels

Esther Amstad, Alexandra Thoma

Nature produces soft materials with fascinating combinations of mechanical properties. For example, the mussel byssus embodies a combination of stiffness and toughness, a feature that is unmatched by synthetic hydrogels. Key to enabling these excellent mec ...

Wiley-V C H Verlag Gmbh2024

High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

Roya Moghaddasi Fereidani

Molecular quantum dynamics simulations are essential for understanding many fundamental phenomena in physics and chemistry. They often require solving the time-dependent Schrödinger equation for molecular nuclei, which is challenging even for medium-sized ...

EPFL2024

Thermal conductivity of Li 3 PS 4 solid electrolytes with ab initio accuracy

Michele Ceriotti, Federico Grasselli

The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been scarcely investigated despite its relevance to thermal management and (over)he ...

Amer Physical Soc2024

Autorepression of yeast Hsp70 cochaperones by intramolecular interactions involving their J-domains

Paolo De Los Rios, Bruno Claude Daniel Fauvet, Adélaïde Alice Mohr, Satyam Tiwari, Mathieu Rebeaud, Pierre Goloubinoff

The 70 kDa heat shock protein (Hsp70) chaperones control protein homeostasis in all ATP-containing cellular compartments. J-domain proteins (JDPs) coevolved with Hsp70s to trigger ATP hydrolysis and catalytically upload various substrate polypeptides in ne ...

Elsevier Science Inc2024

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Volkan Cevher, Grigorios Chrysos, Fanghui Liu

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

2024

The Mn(VII)-H2O2 oxidation process: Abatement of electron-deficient N-containing organic compounds

Urs von Gunten, Ke Xu

Chemical oxidants applied in water treatment are electrophiles, which preferentially attack sites with higher electron density. This typically results in less efficient oxidative abatement of organic compounds with electronwithdrawing substituents. In this ...

Elsevier Science Sa2024

Surface segregation in high-entropy alloys from alchemical machine learning

Michele Ceriotti, Sandip De, Nataliya Lopanitsyna, Guillaume André Jean Fraux, Arslan Mazitov

High-entropy alloys (HEAs), containing several metallic elements in near-equimolar proportions, have long been of interest for their unique mechanical properties. More recently, they have emerged as a promising platform for the development of novel heterog ...

Iop Publishing Ltd2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Mattia Atzeni

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

The neural correlates of topographical disorientation-a lesion analysis study

Olaf Blanke, Lukas Heydrich, Eva Blondiaux

Topographical disorientation refers to the selective inability to orient oneself in familiar surroundings. However, to date its neural correlates remain poorly understood. Here we use quantitative lesion analysis and a lesion network mapping approach in or ...

Wiley2024