École Polytechnique Fédérale de Lausanne

Cobalt-Catalyzed Enantioselective Intermolecular C–H Carboamination with Racemic Allenes

Abstract Enantioselective carboamination of allenes especially in conjunction with 3D-metal catalysis remains a significant challenge. We report chiral cyclopentadienyl cobaltIII-catalyzed regio-, chemo-, and enantioselective intermolecular C–H carboamination of racemic allenyl e...

Up to 16% Optical Carbon‐13 Hyperpolarization of Donor–Acceptor Molecules at 14.1 T

ABSTRACT Solid‐state nuclear magnetic resonance (NMR) is a powerful technique for structure determination with applications ranging from biology to material sciences. However, its inherent low sensitivity prevents many applications. In solids, optical hyperpolarization techniques...

Hydromechanical Behaviour of Intact and Recompacted Crushed Caprock for Underground CO2 Storage

Abstract This work investigates the hydromechanical behaviour of Opalinus Clay (OPA) shale as a caprock material for geological storage of CO $$_2$$ 2 . In addition to intact OPA, the hydromechanical response of crushed material is evaluated to simulate damaged zones around injec...

OmniTraj: Pre-training on heterogeneous data for adaptive and zero-shot human trajectory prediction

Accurate trajectory prediction of vulnerable road users is a cornerstone of safe autonomous driving and intelligent transportation systems. While large-scale pre-training has advanced this field, achieving robust zero-shot generalization remains a critical challenge for real-worl...

Feature Selection in Multivariate Linear Regression Models for Data-Efficient Reaction Optimization

Abstract We introduce NaviCat ReaFS (reaction feature selection), a framework for testing and supporting multivariate linear regression models for reaction optimization in small, heterogeneous datasets, where overfitting risk is high and additional experiments are costly. ReaFS c...

Few-shot neuromorphic vision in a nonlinear photonic network laser

With the growing prevalence of artificial intelligence (AI), demand increases for hardware that mimics the brain’s ability to extract structure from limited data. In the retina, ganglion cells detect features from sparse inputs via lateral inhibition, where neurons antagonistical...

Error Indicators and Adaptivity for a Least-Squares Method Applied to the Monge-Ampère Equation

Abstract We introduce novel a posteriori error indicators for a nonlinear least-squares solver for smooth solutions of the Monge-Ampère equation on convex polygonal domains in $$\mathbb {R}^2$$ R 2 . The theoretical analysis is carried out for smooth solutions. At each iteration,...

Machine learning interatomic potentials for solid-state precipitation

Machine learning interatomic potentials (MLIPs) are routinely used to model diverse atomistic phenomena, yet parameterizing them to accurately capture solid-state phase transformations remains difficult. We present error metrics and data-generation schemes designed to streamline...

Noncollinear kagome magnet driven by giant antisymmetric exchange

Kagome lattices host exotic phenomena such as quantum spin liquids, topological Weyl nodes, and flat bands. The kagome ferromagnet Co3Sn2S2 has been a focus of debate due to conflicting reports on its magnetic character. Here, using weakly perturbative probes—primarily neutron sc...

Impact of calcined clays additions on phase assemblage and mechanical strength of autoclaved low-clinker fiber cement matrices

Calcined clays are promising constituents for use in low-clinker autoclaved fiber cement production. Previous studies on the use of calcined clays in autoclaved fiber cement matrices have shown that their behavior is complex and sometimes counterintuitive. This study investigates...

Artificial intelligence is reshaping neuroscience across scales

Across every scale at which we study the brain, from folded proteins and single neurons to cortical populations and the moving body, artificial intelligence (AI) has shifted from a bespoke tool into a driver of measurement and, increasingly, a generative engine for hypotheses. He...

Explainable AI–enhanced pavement deterioration modeling using hybrid classification–regression deep learning architecture

Abstract Effective Pavement Management System (PMS) planning depends on the ability to anticipate both the severity and physical extent of multiple distress types under real-world data constraints. This work introduces an interpretable dual-stage Deep Learning (DL) framework that...

Temperature dependence of HCN channel kinetics: A systematic comparison across mammalian isoforms and species

Abstract Hyperpolarization‐activated, cyclic nucleotide‐gated (HCN) channels are important regulators of cardiac pacemaking and neuronal excitability, yet their temperature dependence has not been compared systematically across mammalian isoforms and species in standardized exper...

Morphological State Transitions and Sediment Transport Variability in Braided Rivers

Abstract Sediment transport in braided rivers shows significant temporal variability, characterized by intense bursts of transport rates even under steady‐state conditions. These fluctuations are often viewed as the consequence of random variations in the local hydraulic conditio...

Time-resolved laser speckle contrast imaging (TR-LSCI) of cerebral blood flow response to intracranial pressure elevation

Significance: Cerebral autoregulation (CA) reflects the dynamic coupling among cerebral blood flow (CBF), intracranial pressure (ICP), and arterial blood pressure (ABP); its failure contributes to secondary brain injury. Existing bedside methods rely on indirect or spatially limi...

AutoPot: Automated and massively parallelized construction of machine-learning potentials

Machine-learning potentials (MLIPs) have been a breakthrough for computational physics in bringing the accuracy of quantum mechanics to atomistic modeling. To achieve near-quantum accuracy, it is necessary that neighborhoods contained in the training set are rather close to the o...

Multiband condensate of magnons in two dimensions

Wavelike bosonic particles can accumulate in a single mode characterized by a particular wavelength, and such condensates are at the heart of phenomena such as superconductivity and superfluidity where usually a single complex number describes their state. If there are several fl...

Non-Hermitian trapping of Dirac exciton-polariton condensates in a perovskite metasurface

Massless Dirac particles avoid trapping because of their exceptional tunneling properties manifested in the so-called Klein paradox. This conclusion stems from the conservative treatment, but so far, it has not been extended to a non-Hermitian framework. Recently, driven-dissipat...

Agrivoltaics can reduce political polarization and local opposition to solar energy on land

Abstract As solar energy deployment on land intensifies, political polarization and local opposition increasingly challenge its social acceptance. We propose that agrivoltaics – a dual land-use technology that combines solar power generation with agricultural production – can hel...

Thermal cycling–induced nitriding increases energy-storage density in titanate ferroelectric films

Enhancing dielectric energy-storage density ( U e ) requires maximizing the difference between maximum and remanent polarizations (Δ P ). Improving Δ P remains fundamentally challenging, as existing strategies rarely achieve simultaneous high maximum polarization and low remanent...