Physics-Inspired Equivariant Descriptors of Nonbonded Interactions

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Machine learning for metallurgy I. A neural-network potential for Al-Cu

William Curtin, Albert Johann Glensk, Daniel John Gilles Marchand, Abhinav Jain

High-strength metal alloys achieve their performance via careful control of precipitates and solutes. The nucleation, growth, and kinetics of precipitation, and the resulting mechanical properties, are inherently atomic scale phenomena, particularly during ...

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Accurate molecular polarizabilities with coupled cluster theory and machine learning

Michele Ceriotti, David Mark Wilkins, Andrea Grisafi, Yang Yang

The molecular dipole polarizability describes the tendency of a molecule to change its dipole moment in response to an applied electric field. This quantity governs key intra- and intermolecular interactions, such as induction and dispersion; plays a vital ...

2019

Photocatalytic system comprising a titanium-based mof

Berend Smit, Kyriakos Stylianou, Ngoc Tú Nguyên, Christopher Patrick Ireland, Stavroula Kampouri

The present invention concerns a photocatalytic system comprising or consisting of: a titanium-based metal-organic framework MOF based on or including a single ligand type or a plurality of different ligand types for generating photo-generated charge carri ...

2019

Unsupervised machine learning in atomistic simulations, between predictions and understanding

Michele Ceriotti

Automated analyses of the outcome of a simulation have been an important part of atomistic modeling since the early days, addressing the need of linking the behavior of individual atoms and the collective properties that are usually the final quantity of i ...

2019

DORI Reveals the Influence of Noncovalent Interactions on Covalent Bonding Patterns in Molecular Crystals Under Pressure

Berend Smit, Anne-Clémence Corminboeuf, Benjamin André René Meyer, Senja Dominique Barthel, Laurent Alexis Clément Vannay, Amber Kashan Mace

The study of organic molecular crystals under high pressure provides fundamental insight into crystal packing distortions and reveals mechanisms of phase transitions and the crystallization of polymorphs. These solid-state transformations can be monitored ...

2019

Supercritical water anomalies in the vicinity of the Widom line

Christian Ludwig

Supercritical water is used in a variety of chemical and industrial applications. As a consequence, a detailed knowledge of the structure-properties correlations is of uttermost importance. Although supercritical water was considered as a homogeneous fluid ...

Nature Research2019

Water Activity from Equilibrium Molecular Dynamics Simulations and Kirkwood-Buff Theory

Satoshi Takahama, Mária Lbadaoui-Darvas

Water activity and related thermodynamic properties are calculated for several aqueous solutions using equilibrium molecular dynamics in conjunction with the recent extension of the Kirkwood-Buff (KB) theory for closed systems. The general applicability of ...

AMER CHEMICAL SOC2019

Deciphering crystal packing effects in the spin crossover of six [Fe-II(2-pic)(3)]Cl-2 solvatomorphs

Sergio Vela Llausi

In this work we investigate how the crystal packing affects the spin crossover (SCO) of [Fe-II(2-pic)(3)]Cl-2. Four alcohol solvatomorphs of this compound have been reported to present a transition from a singlet low spin (LS, S = 0) to a quintet high spin ...

ROYAL SOC CHEMISTRY2019

A novel biomechanical approach for animal behaviour recognition using accelerometers

Kamiar Aminian, Pritish Chakravarty

Data from animal-borne inertial sensors are widely used to investigate several aspects of an animal's life, such as energy expenditure, daily activity patterns and behaviour. Accelerometer data used in conjunction with machine learning algorithms have b ...

2019

Noncovalent Molecular Electronics

Molecular electronics covers several distinctly different conducting architectures, including organic semiconductors and single-molecule junctions. The noncovalent interactions, abundant in the former, are also often found in the latter, i.e., the dimer ju ...

2018

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Data from animal-borne inertial sensors are widely used to investigate several aspects of an animal's life, such as energy expenditure, daily activity patterns and behaviour. Accelerometer data used in conjunction with machine learning algorithms have b ...

2019

Noncovalent Molecular Electronics

2018