Finite-temperature materials modeling from the quantum nuclei to the hot electron regime

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High-dimensional data must be highly structured to be learnable. Although the compositional and hierarchical nature of data is often put forward to explain learnability, quantitative measurements establishing these properties are scarce. Likewise, accessin ...

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 ...

Electrically connected and plasmonically enhanced molecular junctions combine the optical functionalities of high field confinement and enhancement (cavity function), and of high radiative efficiency (antenna function) with the electrical functionalities o ...

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Quantum optics studies how photons interact with other forms of matter, the understanding of which was crucial for the development of quantum mechanics as a whole. Starting from the photoelectric effect, the quantum property of light has led to the develop ...

In the past decades, a significant increase of the transistor density on a chip has led to exponential growth in computational power driven by Moore's law. To overcome the bottleneck of traditional von-Neumann architecture in computational efficiency, effo ...

Surface-based inflatables are composed of two thin layers of nearly inextensible sheet material joined together along carefully selected fusing curves. During inflation, pressure forces separate the two sheets to maximize the enclosed volume. The fusing c ...

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Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by f ...

At room temperature, mechanical motion driven by the quantum backaction of light has been observed only in pioneering experiments in which an optical restoring force controls the oscillator stiffness1,2. For solid-state mechanical resonators in which oscil ...

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 ...

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We study the statistical mechanics and the equilibrium dynamics of a system of classical Heisenberg spins with frustrated interactions on a d -dimensional simple hypercubic lattice, in the limit of infinite dimensionality d -> infinity . In the analysis we ...

With growing awareness of the vulnerability of the near-Earth space region and the anticipated surge in satellite objects, efforts are underway to assess and implement various mitigation strategies. These aim to minimize the impact of space activities and ...

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

Transition metal oxides represent a class of materials displaying very unusual electronic, structural and magnetic properties. They are extremely interesting, both from a technological and fundamental point of view. The most important characteristic of the ...

Finite-temperature materials modeling from the quantum nuclei to the hot electron regime

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Exploring the portability of ML-based lightning nowcasting models

Probing the latent hierarchical structure of data via diffusion models

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

Light Emission and Conductance Fluctuations in Electrically Driven and Plasmonically Enhanced Molecular Junctions

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

Room-Temperature Quantum Optomechanics and Free-Electron Quantum Optics

Towards Scalable Electronics: Synthetic 2D Materials for Large-Area 2D Circuit Integration

Computational Homogenization for Inverse Design of Surface-based Inflatables

Meta-learning to address diverse Earth observation problems across resolutions

Assessing the Performance of Deep Learning Predictions for Dynamic Aperture of a Hadron Circular Particle Accelerator

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

Room-temperature quantum optomechanics using an ultralow noise cavity

Solvation Free Energies from Machine Learning Molecular Dynamics

Random matrix methods for high-dimensional machine learning models

Computational fluid dynamics simulations of the heat transfer properties of graphene-based nanolubricants and application to hydrodynamic lubrication

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

Frustrated magnets in the limit of infinite dimensions: Dynamics and disorder-free glass transition

Design for demise applied to spacecraft structural panels and experiments for ClearSpace One platform

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Magnetic orderings and electronic structure of complex oxides from advanced Hubbard functionals