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DFT-Derived Reactive Potentials for the Simulation of Activated Processes: the Case of CdTe and CdTe:S

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Structure and dynamics of liquid water from ab initio simulations: adding Minnesota density functionals to Jacob's ladder

Ursula Röthlisberger, Justin Villard, Martin Peter Bircher

The accurate representation of the structural and dynamical properties of water is essential for simulating the unique behavior of this ubiquitous solvent. Here we assess the current status of describing liquid water using ab initio molecular dynamics, wit ...

Cambridge2024

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

Ksenia Briling

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 ...

EPFL2024

The complexity of biological systems and processes, spanning molecular to macroscopic scales, necessitates the use of multiscale simulations to get a comprehensive understanding. lar dynamics (MD) simulations are crucial for capturing processes beyond the ...

Current Biology Ltd2024

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Justin Villard

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

EPFL2023

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We present an efficient method to compute diffusion coefficients of multiparticle systems with strong interactions directly from the geometry and topology of the potential energy field of the migrating particles. The approach is tested on Li-ion diffusion ...

Washington2023

Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows

Giovanni Pizzi, Antimo Marrazzo, Junfeng Qiao, Miki Bonacci, Andrea Ferretti

The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations ...

NATURE PORTFOLIO2023

Assessing the persistence of chalcogen bonds in solution with neural network potentials

Rubén Laplaza Solanas, Frédéric Célerse, Veronika Juraskova

Non-covalent bonding patterns are commonly harvested as a design principle in the field of catalysis, supramolecular chemistry, and functional materials to name a few. Yet, their computational description generally neglects finite temperature and environme ...

2022

Structure and Reactivity of N-Heterocyclic Alkynyl Hypervalent Iodine Reagents

Rosario Scopelliti, Jérôme Waser, Farzaneh Fadaei Tirani, Matthew Wodrich, Eliott Hugo Joran Le Du

Ethynylbenziodoxol(on)e (EBX) cyclic hypervalent iodine reagents have become popular reagents for the alkynylation of radicals and nucleophiles, but only offer limited possibilities for further structure and reactivity fine-tuning. Herein, the synthesis of ...

2021

Solidification is a phase transformation of utmost importance in material science, for it largely controls materials' microstructure on which a wide range of mechanical properties depends. Almost every human artifact undergoes a transformation that leads t ...

EPFL2020

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High-Performance Computing is impacting on all biomedical sciences, including molecular biophysics. Here, we describe general parallel computing strategies (multi-threading and distributed computing) used in all the natural sciences, including molecular bi ...

WILEY-V C H VERLAG GMBH2020