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Learning the energy curvature versus particle number in approximate density f...
The average energy curvature as a function of the particle number is a molecule-specific quantity, which measures the deviation of a given functional from the exact conditions... -
Local kernel regression and neural network approaches to the conformational l...
The application of machine learning to theoretical chemistry has made it possible to combine the accuracy of quantum chemical energetics with the thorough sampling of... -
Moiré Flat Bands in Twisted Double Bilayer Graphene
We investigate twisted double bilayer graphene (TDBG), a four-layer system composed of two AB-stacked graphene bilayers rotated with respect to each other by a small angle. Our... -
Characterization of chemisorbed species and active adsorption sites in Mg-Al ...
Mg-Al mixed metal oxides (MMOs), derived from the decomposition of layered double hydroxides (LDHs), have been purposed as a material for CO2 capture of industrial plant... -
Hamiltonian-Reservoir Replica Exchange and Machine Learning Potentials for Co...
This work combines a machine learning potential energy function with a modular enhanced sampling scheme to obtain statistically converged thermodynamical properties of flexible... -
Charge separation and charge carrier mobility in photocatalytic metal-organic...
Metal-Organic Frameworks (MOFs) are highly versatile materials owing to their vast structural and chemical tunability. These hybrid inorganic-organic crystalline materials offer... -
Assessing the persistence of chalcogen bonds in solution with neural network ...
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,... -
Linear and quadratic magnetoresistance in the semimetal SiP2
Multiple mechanisms for extremely large magnetoresistance (XMR) found in many topologically nontrivial/trivial semimetals have been theoretically proposed, but experimentally it... -
Learning on-top: regressing the on-top pair density for real-space visualizat...
The on-top pair density [Π(r)] is a local quantum chemical property, which reflects the probability of two electrons of any spin to occupy the same position in space. Simplest... -
Direct, mediated and delayed intramolecular singlet fission mechanism in dono...
Donor-acceptor (D-A) extended copolymers have shown great potential to be exploited for intramolecular Singlet Fission (iSF) because of their modular tunability and intrinsic... -
Structure-property maps with kernel principal covariates regression
Data analyses based on linear methods constitute the simplest, most robust, and transparent approaches to the automatic processing of large amounts of data for building... -
Controlling the quantum spin Hall edge states in two-dimensional transition m...
Two-dimensional transition metal dichalcogenides (TMDs) of Mo and W in their 1T′ crystalline phase host the quantum spin Hall (QSH) insulator phase. We address the electronic... -
Inexpensive modeling of quantum dynamics using path integral generalized Lang...
The properties of molecules and materials containing light nuclei are affected by their quantum mechanical nature. Accurate modeling of these quantum nuclear effects requires... -
Band gaps of liquid water and hexagonal ice through advanced electronic-struc...
The fundamental band gaps of liquid water and hexagonal ice are calculated through advanced electronic-structure methods. We compare specifically the performance of... -
Using collective knowledge to assign oxidation states
Knowledge of the oxidation state of a metal centre in a material is essential to understand its properties. Chemists have developed theories to predict the oxidation state based... -
Iterative unbiasing of quasi-equilibrium sampling
This repository contains the PLUMED-2 input files required to generate the data used in the ITRE publications. ITRE is a method to reweight Molecular Dynamics trajectory biased... -
Theory-guided design of high-strength, high-melting point, ductile, low-densi...
The search for new high-temperature alloys that can enable higher-efficiency/lower-emissions power generation has accelerated with the discovery of body-centered cubic (bcc)... -
Inexpensive modeling of quantum dynamics using path integral generalized Lang...
The properties of molecules and materials containing light nuclei are affected by their quantum mechanical nature. Accurate modeling of these quantum nuclear effects requires... -
Thermodynamics and dielectric response of BaTiO₃ by data-driven modeling
Modeling ferroelectric materials from first principles is one of the successes of density-functional theory, and the driver of much development effort, requiring an accurate... -
Is a single conformer sufficient to describe the reorganization energy of amo...
The reorganization energy (λ), which quantifies the structural rearrangement of a molecule when accommodating a charge, is a key parameter in the evaluation of charge mobility...