Related papers: Revealing Fast Ionic Conduction in Solid Electroly…
The manipulation of trapped charged particles by electric fields is an accurate, robust and reliable technique for many applications or experiments in high-precision spectroscopy. The transfer of the ion sample between multiple traps allows…
Nonlinear conductivity effects are studied experimentally and theoretically for thin samples of disordered ionic conductors. Following previous work in this field the {\it experimental nonlinear conductivity} of sodium ion conducting…
Solid ionic conductors are essential components of batteries and fuel cells. In many cases, ionic conduction through crystalline materials with substitutional disorder can be modeled with atomic-scale lattice model percolation simulations.…
A superintense laser pulse illuminating a thin solid-density foil can, in principle, accelerate the entire foil, therefore yielding dense, collimated, and quasi-monoenergetic ion beams. These unique features render radiation pressure…
A new model for the electrical conductivity of dense plasmas with a mixture of ion species, containing no adjustable parameters, is presented. The model takes the temperature, mass density and relative abundances of the species as input. It…
Heating and ionization are among the most fundamental processes in relativistic laser--solid interactions; however, their spatiotemporal evolution remains challenging to capture experimentally. Here we present detailed diagnosis of…
This study introduces a machine learning framework to predict the suitability of ionic liquids with unknown physical properties as propellants for electrospray thrusters based on their molecular structure. We construct a training dataset by…
We present a study of the performance of the trapped-ion driven geometric phase gates introduced in [New J. Phys. 15, 083001 (2013)] when realized in a stimulated Raman transition. We show that the gate can achieve errors below the…
The irradiation with fast ions with kinetic energies of > 10 MeV leads to the deposition of a high amount of energy along their trajectory (up to several ten keV/nm). The energy is mainly transferred to the electronic subsystem and induces…
Raman transitions have a wide range of applications in atomic physics and have recently been proposed as a means for improving high-precision high-voltage measurements. Here, we present a theoretical analysis and a first experimental…
We present a comprehensive framework for interpreting electron recoil signals induced by fast-moving dark matter (DM), applicable across a wide range of theoretically motivated models. Amid both null results in conventional weakly…
Most water in the universe may be superionic, and its thermodynamic and transport properties are crucial for planetary science but difficult to probe experimentally or theoretically. We use machine learning and free energy methods to…
Transforming CO$_2$ into methanol represents a crucial step towards closing the carbon cycle, with thermoreduction technology nearing industrial application. However, obtaining high methanol yields and ensuring the stability of…
Rayleigh-Taylor (RT) instability occurs in a variety of scenario as a consequence of fluids of different densities pushing against the density gradient. For example, it is expected to occur in the ion acceleration of solid density targets…
Drag and diffusion of mobile ions in solids are of interest for both purely theoretical and applied scientific communities. This article proposes a theoretical description of ion drag in solids that can be used to estimate ionic…
We have developed a new data-driven paradigm for the rapid inference, modeling and simulation of the physics of transport phenomena by deep learning. Using conditional generative adversarial networks (cGAN), we train models for the direct…
We simulate the dynamics, including laser cooling, of 3D ion crystals confined in a Penning trap using a newly developed molecular dynamics-like code. The numerical integration of the ions' equations of motion is accelerated using the fast…
Next-generation high-energy-density batteries require ideally stable metal anodes, for which smooth metal deposits during battery recharging are considered a sign of interfacial stability that can ensure high efficiency and long cycle life.…
We propose an approach for exploiting machine learning to approximate electronic fields in crystalline solids subjected to deformation. Strain engineering is emerging as a widely used method for tuning the properties of materials, and this…
There is a growing interest in the development of functional metal oxides with mixed ionic electronic conduction for their application in different strategic fields. In particular, ionic transport-related phenomena are of primary importance…