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Density functional perturbation theory for one-dimensional systems: implement...
The electronic and vibrational properties and electron-phonon couplings of one-dimensional materials will be key to many prospective applications in nanotechnology.... -
Solvation free energies from machine learning molecular dynamics
In this paper, we propose 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... -
Dramatic acceleration of the Hopf cyclization on gold(111): from enediynes to...
Hopf et al. first reported the high-temperature 6π-electrocyclization of cis-hexa-1,3-diene-5-yne to benzene in 1969. Subsequent studies using this cyclization have been limited... -
A bridge between trust and control: Computational workflows meet automated ba...
Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by a full control of the data gathering process. In this... -
Tailoring magnetism of graphene nanoflakes via tip-controlled dehydrogenation
Atomically precise graphene nanoflakes called nanographenes have emerged as a promising platform to realize carbon magnetism. Their ground state spin configuration can be... -
Emergent half-metal with mixed structural order in (111)-oriented (LaMnO₃)₂ₙ|...
Using first-principles techniques, we study the structural, magnetic, and electronic properties of (111)-oriented (LaMnO₃)₂ₙ|(SrMnO₃)ₙ superlattices of varying thickness... -
Unearthing the foundational role of anharmonicity in heat transport in glasses
The time-honored Allen-Feldman theory of heat transport in glasses is generally assumed to predict a finite value for the thermal conductivity, even if it neglects the... -
The energy landscape of magnetic materials
Magnetic materials can display many solutions to the electronic-structure problem, corresponding to different local or global minima of the energy functional. In Hartree-Fock or... -
Seebeck coefficient of ionic conductors from Bayesian regression analysis
We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo... -
Electronic decoupling and hole-doping of graphene nanoribbons on metal substr...
In this record we provide the data to support our recent finding on the intercalation of gold chloride underneath atomically precise graphene nanoribbons (GNRs). GNRs have a... -
Ferrimagnetism induced by thermal vibrations in oxygen-deficient manganite he...
Super-exchange most often leads to antiferromagnetism in transition-metal perovskite oxides, yet ferromagnetism or ferrimagnetism would be preferred for many applications, for... -
Quantum phase diagram of high-pressure hydrogen
The interplay between electron correlation and nuclear quantum effects makes our understanding of elemental hydrogen a formidable challenge. Here, we present the phase diagram... -
Reduction of precious metal ions in aqueous solutions by contact-electro-cata...
Contact-Electro-Catalysis is an emerging catalytic principle that takes advantage of exchanges of electrons occurring through contact electrification events at solid-liquid... -
Infrared-active phonons in one-dimensional materials and their spectroscopic ...
Dimensionality provides a clear fingerprint on the dispersion of infrared-active, polar-optical phonons. For these phonons, the local dipoles parametrized by the Born effective... -
Achieving 19% efficiency in nonfused ring electron acceptor solar cells via s...
Nonfused ring electron acceptors (NFREAs) are interesting n-type near infrared (NIR) photoactive semiconductors with strong molecular absorption and easy synthetic route.... -
Neural network potential for Zr-H
The introduction of Hydrogen (H) into Zirconium (Zr) influences many mechanical properties, especially due to low H solubility and easy formation of Zirconium hydride phases.... -
High-throughput computational screening for solid-state Li-ion conductors
We present a computational screening of experimental structural repositories for fast Li-ion conductors, with the goal of finding new candidate materials for application as... -
High-throughput computational screening for solid-state Li-ion conductors
We present a computational screening of experimental structural repositories for fast Li-ion conductors, with the goal of finding new candidate materials for application as... -
A general framework for active space embedding methods: applications in quant...
We developed a general framework for hybrid quantum-classical computing of molecular and periodic embedding calculations based on an orbital space separation of the fragment and... -
High-quality data enabling universality of band-gap descriptor and discovery ...
Extensive machine-learning assisted research has been dedicated to predicting band gaps for perovskites, driven by their immense potential in photovoltaics. Yet, the...