-
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... -
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... -
Designing Singlet Fission Candidates from Donor-Acceptor Copolymers
Singlet Fission (SF) has demonstrated significant promise for boosting the power conversion efficiency (PCE) of solar cells. Traditionally, SF is targeted as an intermolecular... -
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... -
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 several theories to predict the oxidation... -
Pure Magnesium DFT calculations for interatomic potential fitting
This dataset provides DFT (density functional theory as implemented in VASP, Vienna Ab Initio Simulation Package) calculations for pure Magnesium. It was designed by Binglun... -
SPAᴴM(a,b): encoding the density information from guess Hamiltonian in quantu...
Recently, we introduced a class of molecular representations for kernel-based regression methods — the spectrum of approximated Hamiltonian matrices (SPAᴴM) — that takes... -
Data-powered augmented volcano plots for homogeneous catalysis
Transitioning from small-scale to big-data studies has the potential to reveal new layers of intricacy that better facilitate and rationalize catalytic behavior. Given the... -
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... -
Searching for the thinnest metallic wire
One-dimensional materials have gained much attention in the last decades: from carbon nanotubes to ultrathin nanowires, to few-atom atomic chains, these can all display unique... -
Searching for the thinnest metallic wire
One-dimensional materials have gained much attention in the last decades: from carbon nanotubes to ultrathin nanowires, to few-atom atomic chains, these can all display unique... -
Engineering frustrated lewis pair active sites in porous organic scaffolds f...
Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes.... -
Engineering frustrated lewis pair active sites in porous organic scaffolds f...
Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes.... -
Engineering frustrated lewis pair active sites in porous organic scaffolds f...
Frustrated Lewis pairs (FLPs), featuring reactive combinations of Lewis acids and Lewis bases, have been utilized for myriad metal-free homogeneous catalytic processes.... -
Adaptive energy reference for machine-learning models of the electronic densi...
The electronic density of states (DOS) provides information regarding the distribution of electronic states in a material, and can be used to approximate its optical and... -
Adaptive energy reference for machine-learning models of the electronic densi...
The electronic density of states (DOS) provides information regarding the distribution of electronic states in a material, and can be used to approximate its optical and... -
Adaptive energy reference for machine-learning models of the electronic densi...
The electronic density of states (DOS) provides information regarding the distribution of electronic states in a material, and can be used to approximate its optical and... -
Adaptive energy reference for machine-learning models of the electronic densi...
The electronic density of states (DOS) provides information regarding the distribution of electronic energy levels in a material, and can be used to approximate its optical and... -
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,... -
Evaluation of photocatalysts for water splitting through combined analysis of...
To examine whether suitable conditions occur for the water splitting reaction at their interfaces with liquid water, we determine the pH-dependent surface coverage for a series...
