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Anisotropic exchange Hamiltonian, magnetic phase diagram, and domain inversion of Nd2Zr2O7

Publications associées (34)

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Starting from our big universe to the microscopic world, phase transitions play an important role in nature. Just after the Big Bang our universe experienced multiple phase transitions, from high-temperature plasma to the matter we know today.Phase transit ...

EPFL2023

Nature-Inspired Stalactite Nanopores for Biosensing and Energy Harvesting

Aleksandra Radenovic, Mukeshchand Thakur, Andrey Chernev, Vasily Artemov, Lucie Navratilova, Nianduo Cai, Yunfei Teng, Tzu-Heng Chen

Nature provides a wide range of self-assembled structures from the nanoscale to the macroscale. Under the right thermodynamic conditions and with the appropriate material supply, structures like stalactites, icicles, and corals can grow. However, the natur ...

WILEY-V C H VERLAG GMBH2023

Temperature Dependent Properties of the Aqueous Electron

Alfredo Pasquarello, Jinggang Lan

The temperature-dependent properties of the aqueous electron have been extensively studied using mixed quantum-classical simulations in a wide range of thermodynamic conditions based on one-electron pseudopotentials. While the cavity model appears to expla ...

WILEY-V C H VERLAG GMBH2022

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We model, via classical molecular dynamics simulations, the plastic phase of ice VII across a wide range of the phase diagram of interest for planetary investigations. Although structural and dynamical properties of plastic ice VII are mostly independent o ...

AIP Publishing2022

Uncertainty estimation for molecular dynamics and sampling

Michele Ceriotti, Federico Grasselli, Yongbin Zhuang, Venkat Kapil, Kevin Rossi, Edgar Albert Engel, Giulio Imbalzano

Machine-learning models have emerged as a very effective strategy to sidestep time-consuming electronic-structure calculations, enabling accurate simulations of greater size, time scale, and complexity. Given the interpolative nature of these models, the r ...

2021

Characterising Structure and Stability of Materials using Machine Learning

Andrea Anelli

The search of novel materials using in-silico high-throughput screening is emerging as a fundamental step in the pipeline of materials discovery, but its low yields in terms of synthesisable structures limit its effectiveness. In order to isolate configura ...

EPFL2020

Flat-Histogram Monte Carlo as an Efficient Tool To Evaluate Adsorption Processes Involving Rigid and Deformable Molecules

Berend Smit, Matthew David Witman

Monte Carlo simulations are the foundational technique for predicting thermodynamic properties of open systems where the process of interest involves the exchange of particles. Thus, they have been used extensively to computationally evaluate the adsorptio ...

2018

Patchy Surfaces

Nikolaos Nianias

Tailoring solid surfaces attracts a number of technological and scientific interest with numerous applications. One method to modify a solid surface is via the formation of a molecular film. The adsorbed molecules assemble spontaneously (self assemble) for ...

EPFL2018

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We report magnetic and thermodynamic properties of a 4d1 (Mo5+) magnetic insulator MoOPO4 single crystal, which realizes a J1−J2 Heisenberg spin-1/2 model on a stacked square lattice. The specific-heat measurements show a magnetic transition at 16 K which ...

Amer Physical Soc2017

The methane deliverable capacity of adsorbent materials is a critical performance metric that will determine the viability of using adsorbed natural gas (ANG) technology in vehicular applications. ARPA-E recently set a target deliverable capacity of 315 cc ...

Elsevier2017