Modeling non-covalent interactions in condensed phase

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While the accurate description of redox reactions remains a challenge for first-principles calculations, it has been shown that extended Hubbard functionals (DFT+U+V) can provide a reliable approach, mitigating self-interaction errors, in materials with st ...

Lead halide perovskites have emerged as highly efficient solar cell materials. However, to date, the most promising members of this class are polymorphs in which a wide-band-gap delta phase competes with the photoactive perovskite alpha form and the intrin ...

The redox properties of oxides are critical in catalysis and can be modified at the interface between oxides and metals; as a consequence, working catalysts can be reconstructed. Herein, the influence of metal-support interactions on the interface between ...

Humans and animals both use acoustic signals for vocal communication. The advent of self-supervised learning (SSL) has enabled neural networks to learn robust and general feature representations through the intrinsic acoustic structure of input signals, wi ...

The dynamics of neuron populations commonly evolve on low-dimensional manifolds. Thus, we need methods that learn the dynamical processes over neural manifolds to infer interpretable and consistent latent representations. We introduce a representation lear ...

Electrolytic hydrogen is identified as a crucial component in the desired decarbonisation of the chemical industry, utilizing renewable energy to split water into hydrogen and oxygen. Water electrolysis still requires important scientific advances to impro ...

Foundation models are highly versatile neural-network architectures capable of processing different data types, such as text and images, and generalizing across various tasks like classification and generation. Inspired by this success, we propose Foundati ...

This study investigated the regulatory mechanism of calcium-based activators on the reaction kinetics of sodium carbonate-activated slag (SAS), with the aim of revisiting the conventional interpretation based on liquid-phase alkalinity enhancement. By inco ...

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

Triboelectric nanogenerators (TENGs) serve as a key technology in flexible electronic devices, especially tactile sensors, enabling flexible robotic manipulators to effectively interact with their external environment. Persistent challenges include inadequ ...

Microorganisms are essential for life on Earth, performing key roles in numerous biological processes. Their influence extends across a wide spectrum, from human health and ecological balance to advancements in biotechnology and industrial applications. Th ...

Animals, including humans, interact with the external environment primarily through motion. Replicating their motor control skills in artificial embodied agents is a major objective of artificial intelligence research. This thesis presents a collection of ...

Direct light olefin synthesis from CO2 hydrogenation is a new pathway to decarbonize the chemical industry. Inspired by the promising catalytic activity of Ga2O3-based catalysts in alkane dehydrogenation, this study reveals that optimizing Ga content in th ...

Hydrogen clathrate hydrates are ice-like crystalline substances in which hydrogen molecules are trapped inside polyhedral cages formed by the water molecules. Small cages can host only a single H-2 molecule, while each large cage can be occupied by up to f ...

The combination of palladium salts and bipyridyl ligands can lead to the formation of a large variety of coordination complexes, with different shapes and sizes, displaying a very versatile host-guest chemistry. Increasing their structural complexity remai ...

In humans and animals, surprise is a physiological reaction to an unexpected event, but how surprise can be linked to plausible models of neuronal activity is an open problem. We propose a self-supervised spiking neural network model where a surprise signa ...

Post-translational modifications (PTMs) play a pivotal role in regulating protein structure, interaction, and function. Aberrant PTM patterns are associated with diseases. Moreover, individual PTMs have a complex interaction with each other, known as PTM c ...

Excitons play an essential role in the optical response of two-dimensional materials. These are bound states showing up in the band gaps of many-body systems and are conceived as quasiparticles formed by an electron and a hole. By performing real-time simu ...

Neural decoding of the visual system is a subject of research interest, both to understand how the visual system works and to be able to use this knowledge in areas, such as computer vision or brain-computer interfaces. Spike-based decoding is often used, ...

Base excision repair enzymes (BERs) detect and repair oxidative DNA damage with efficacy despite the small size of the defects and their often only minor structural impact. A charge transfer (CT) model for rapid scanning of DNA stretches has been evoked to ...

Modeling non-covalent interactions in condensed phase

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Teaching oxidation states to neural networks

Force-Matching-Based Approach for the Generation of Polarizable and Nonpolarizable Force Fields Applied to CsPbI3

Understanding the interfacial changes of PtCo3O4 catalysts during the dehydrogenation of ammonia borane

Transferability of Learnt Speech Representations for Decoding Non-Human Vocal Communication

MARBLE: interpretable representations of neural population dynamics using geometric deep learning

Operando evidence on the chirality-enhanced oxygen evolution reaction in intrinsically chiral electrocatalysts

Foundation neural-networks quantum states as a unified Ansatz for multiple hamiltonians

New insights into the reaction mechanisms of calcium-based activators modified sodium carbonated activated slag: Precursor dissolution and carboaluminate generation

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Intelligent Soft Robotic System for Sensing and Recognition via Triboelectric‐Based Multi‐Sensor Fusion

Optimality principles for the analysis of biological processes across scales: From enzyme kinetics to microbiome dynamics

Musculoskeletal motor control with reinforcement learning

Selective light olefin synthesis with high ethylene abundance via CO2 hydrogenation over (Ga-In)2O3/SSZ-13 catalysts

Large-cage occupation and quantum dynamics of hydrogen molecules in sII clathrate hydrates

Palladium-based supramolecular assemblies: from complex structures to water-soluble anion-receptors

Fast adaptation to rule switching using neuronal surprise

Investigating the intra-molecular and inter-molecular effects of post-translational modifications on intrinsically disordered protein regions and structured protein regions

Exciton migration in two-dimensional materials

Predicting Visual Stimuli From Cortical Response Recorded With Wide-Field Imaging in a Mouse

Oxidative Defect Detection Within Free and Packed DNA Systems: A Quantum Mechanical/Molecular Mechanics (QM/ MM) Approach