Topology-Driven Single-Molecule Conductance of Carbon Nanothreads

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This dataset accompanies the publication "Quantum-mechanical effects in photoluminescence from thin crystalline gold films" published in Light: Science & Applications (https://doi.org/10.1038/s41377-024-01408-2). The data can be used to reproduce plots 1-4 ...

Electron-rich organocerium complexes (C5Me4H)(3)Ce and [(C5Me5)(2)Ce(ortho-oxa)], with redox potentials E-1/2 = -0.82 V and E-1/2 = -0.86 V versus Fc/Fc(+), respectively, were reacted with fullerene (C-60) in different stoichiometries to obtain molecular m ...

We report measurements of the in-plane thermoelectric power (TEP) for an overdoped (OD) crystal of the single layer cuprate superconductor Tl2Ba2CuO6+x (Tl2201) at several hole concentrations (p), from 300 or 400 K to below the superconducting transition t ...

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Topological materials have been a main focus of studies in the past decade due to their protected properties that can be exploited for the fabrication of new devices. Among them, Weyl semimetals are a class of topological semimetals with nontrivial linear ...

In the rapidly expanding field of topological materials there is growing interest in systems whose topological electronic band features can be induced or controlled by magnetism. Magnetic Weyl semimetals, which contain linear band crossings near the Fermi ...

Luminescence constitutes a unique source of insight into hot carrier processes in metals, including those in plasmonic nanostructures used for sensing and energy applications. However, being weak in nature, metal luminescence remains poorly understood, its ...

The present work proposes 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 (FP) molecular dynamics (MD) simulations of a hybrid solvation model. The approa ...

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 ...

Using scanning tunneling microscopy (STM), we experimentally and theoretically investigate isolated platinum phthalocyanine (PtPc) molecules adsorbed on an atomically thin NaCl(100) film vapor deposited on Au(111). We obtain good agreement between theory a ...

Excitons play an essential role in the optical response of two-dimensional materials. These are bound states showing up in the band gaps of many-body systems and are conceived as quasiparticles formed by an electron and a hole. By performing real-time simu ...

The phenomenon of allostery, a general property in proteins that has been heralded as "the second secret of life" remains elusive to our understanding and even more challenging to incorporate into protein design. One example of allosteric proteins with gre ...

Charge separation processes in organic semiconductors play a pivotal role in diverse applications ranging from photovoltaics to photocatalysis. Understanding these mechanisms, particularly the role of hybrid charge-transfer (CT) states, is essential for ad ...

The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine learni ...

The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation ...

Molecular dynamics (MD) simulations have emerged as a transformative approach to analyse molecular systems at the atomic level, offering valuable insights into complex biological processes. Many biological phenomena can only accurately be described by inco ...

The discovery of superconductivity in doped infinite-layer nickelate thin films has brought increased attention to the behavior of the doped perovskite phase. Despite this interest, the majority of existing studies pertain to hole-doped perovskite rare-ear ...

Structure determination of amorphous materials remains challenging, owing to the disorder inherent to these materials. Nuclear magnetic resonance (NMR) powder crystallography is a powerful method to determine the structure of molecular solids, but disorder ...

The low-energy electronic structure of nanographenes can be tuned through zero-energy pi-electron states, typically referred to as zero-modes. Customizable electronic and magnetic structures have been engineered by coupling zero-modes through exchange and ...

Smearing techniques are widely used in first-principles calculations of metallic and magnetic materials where they improve the accuracy of Brillouin-zone sampling and lessen the impact of level-crossing instabilities. Smearing introduces a fictitious elect ...

Topology-Driven Single-Molecule Conductance of Carbon Nanothreads

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Dataset to accompany publication "Quantum-mechanical effects in photoluminescence from thin crystalline gold films"

Realization of Organocerium-Based Fullerene Molecular Materials Showing Mott Insulator-Type Behavior

Thermoelectric power of overdoped Tl2201 crystals: charge density waves and T1 and T2 resistivities

Machine learning-aided generative molecular design

Type-I antiferromagnetic Weyl semimetal InMnTi2

Weyl metallic state induced by helical magnetic order

Quantum-mechanical effects in photoluminescence from thin crystalline gold films

Solvation Free Energies from Machine Learning Molecular Dynamics

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

Scanning Tunneling Microscopy for Molecules: Effects of Electron Propagation into Vacuum

Exciton migration in two-dimensional materials

From Sequence to Dynamics to Function: Computational Design of Allostery and Ligand Selectivity in G-Protein Coupled Receptors

Charge-Transfer States in Organic Nanowires

Computational drug development for membrane protein targets

Machine-learning the electronic density of states: electronic properties without quantum mechanics

Advancing first principle-based molecular dynamics of biological systems with machine learning

Competition between Carrier Injection and Structural Distortions in Electron-Doped Perovskite Nickelate Thin Films

Atomic-level structure determination of amorphous molecular solids by NMR

Five-Membered Rings Create Off-Zero Modes in Nanographene

Fermi energy determination for advanced smearing techniques