Method for the accurate prediction of electron transfer potentials using an effective absolute potential

2020 ◽  
Vol 22 (44) ◽  
pp. 25833-25840 ◽  
Author(s):  
Michael Busch ◽  
Kari Laasonen ◽  
Elisabet Ahlberg
Keyword(s):  
Electron Transfer ◽  
First Principles ◽  
Accurate Prediction ◽  
Absolute Potential

A method to predict electron transfer potentials from first principles using the experimental pKa as reference is shown.

Combining First-Principles and Data Modeling for the Accurate Prediction of the Refractive Index of Organic Polymers

2017 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
First Principles ◽  
Data Modeling ◽  
Accurate Prediction ◽  
Index Of Refraction ◽  
Structure Theory ◽  
Organic Polymers ◽  
Number Density ◽  
Lorenz Equation ◽  
In Silico Studies ◽  
Wide Range

Organic materials with a high index of refraction (RI) are attracting considerable interest due to their potential application in optic and optoelectronic devices. However, most of these applications require an RI value of 1.7 or larger, while typical carbon-based polymers only exhibit values in the range of 1.3–1.5. This paper introduces an efficient computational protocol for the accurate prediction of RI values in polymers to facilitate in silico studies that an guide the discovery and design of next-generation high-RI materials. Our protocol is based on the Lorentz-Lorenz equation and is parametrized by the polarizability and number density values of a given candidate compound. In the proposed scheme, we compute the former using first-principles electronic structure theory and the latter using an approximation based on van der Waals volumes. The critical parameter in the number density approximation is the packing fraction of the bulk polymer, for which we have devised a machine learning model. We demonstrate the performance of the proposed RI protocol by testing its predictions against the experimentally known RI values of 112 optical polymers. Our approach to combine first-principles and data modeling emerges as both a successful and highly economical path to determining the RI values for a wide range of organic polymers.

scholarly journals Solubility prediction from first principles: a density of states approach

2018 ◽  
Vol 20 (32) ◽  
pp. 20981-20987 ◽  
Author(s):  
Simon Boothroyd ◽  
Andy Kerridge ◽  
Anders Broo ◽  
David Buttar ◽  
Jamshed Anwar
Keyword(s):  
Density Of States ◽  
First Principles ◽  
Fundamental Property ◽  
Accurate Prediction ◽  
Solubility Prediction ◽  
Efficient Approach

Solubility is a fundamental property of widespread significance. Its accurate prediction remains a major challenge. We present a novel, efficient approach to solubility prediction for molecules over a range of conditions based on density of states.

scholarly journals Accurate Prediction of Band Structure of FeS2: A Hard Quest of Advanced First-Principles Approaches

2021 ◽  
Vol 9 ◽  
Author(s):  
Min-Ye Zhang ◽  
Hong Jiang
Keyword(s):  
Band Structure ◽  
First Principles ◽  
High Energy ◽  
Accurate Prediction ◽  
Band Gaps ◽  
Full Potential ◽  
Band Structures ◽  
Electronic Band ◽  
Fundamental Band ◽  
Hybrid Functionals

The pyrite and marcasite polymorphs of FeS2 have attracted considerable interests for their potential applications in optoelectronic devices because of their appropriate electronic and optical properties. Controversies regarding their fundamental band gaps remain in both experimental and theoretical materials research of FeS2. In this work, we present a systematic theoretical investigation into the electronic band structures of the two polymorphs by using many-body perturbation theory with the GW approximation implemented in the full-potential linearized augmented plane waves (FP-LAPW) framework. By comparing the quasi-particle (QP) band structures computed with the conventional LAPW basis and the one extended by high-energy local orbitals (HLOs), denoted as LAPW + HLOs, we find that one-shot or partially self-consistent GW (G0W0 and GW0, respectively) on top of the Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation with a converged LAPW + HLOs basis is able to remedy the artifact reported in the previous GW calculations, and leads to overall good agreement with experiment for the fundamental band gaps of the two polymorphs. Density of states calculated from G0W0@PBE with the converged LAPW + HLOs basis agrees well with the energy distribution curves from photo-electron spectroscopy for pyrite. We have also investigated the performances of several hybrid functionals, which were previously shown to be able to predict band gaps of many insulating systems with accuracy close or comparable to GW. It is shown that the hybrid functionals considered in general fail badly to describe the band structures of FeS2 polymorphs. This work indicates that accurate prediction of electronic band structure of FeS2 poses a stringent test on state-of-the-art first-principles approaches, and the G0W0 method based on semi-local approximation performs well for this difficult system if it is practiced with well-converged numerical accuracy.

Size-independent neural networks based first-principles method for accurate prediction of heat of formation of fuels

2018 ◽  
Vol 148 (24) ◽  
pp. 241738 ◽  
Author(s):  
GuanYa Yang ◽  
Jiang Wu ◽  
ShuGuang Chen ◽  
WeiJun Zhou ◽  
Jian Sun ◽  
...  
Keyword(s):  
Neural Networks ◽  
First Principles ◽  
Heat Of Formation ◽  
Accurate Prediction ◽  
First Principles Method

Combining First-Principles and Data Modeling for the Accurate Prediction of the Refractive Index of Organic Polymers

2017 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
First Principles ◽  
Data Modeling ◽  
Accurate Prediction ◽  
Index Of Refraction ◽  
Structure Theory ◽  
Organic Polymers ◽  
Number Density ◽  
Lorenz Equation ◽  
In Silico Studies ◽  
Wide Range

Organic materials with a high index of refraction (RI) are attracting considerable interest due to their potential application in optic and optoelectronic devices. However, most of these applications require an RI value of 1.7 or larger, while typical carbon-based polymers only exhibit values in the range of 1.3–1.5. This paper introduces an efficient computational protocol for the accurate prediction of RI values in polymers to facilitate in silico studies that an guide the discovery and design of next-generation high-RI materials. Our protocol is based on the Lorentz-Lorenz equation and is parametrized by the polarizability and number density values of a given candidate compound. In the proposed scheme, we compute the former using first-principles electronic structure theory and the latter using an approximation based on van der Waals volumes. The critical parameter in the number density approximation is the packing fraction of the bulk polymer, for which we have devised a machine learning model. We demonstrate the performance of the proposed RI protocol by testing its predictions against the experimentally known RI values of 112 optical polymers. Our approach to combine first-principles and data modeling emerges as both a successful and highly economical path to determining the RI values for a wide range of organic polymers.

Accurate prediction of Pressure and Temperature T1/2 Variation in Solid State Spin Crossover by Ab Initio Methods: the [CoII(dpzca)2] case

2021 ◽  
Author(s):  
Luca Bondì ◽  
Sally Brooker ◽  
Federico Totti
Keyword(s):  
Solid State ◽  
Ab Initio ◽  
First Principles ◽  
Spin Crossover ◽  
Second Order ◽  
Accurate Prediction ◽  
Ab Initio Methods ◽  
State Spin

Spin crossover (SCO) is among the most complicated second-order transitions to be modelled from first principles; especially solid state SCO with the added complexity of (a) interacting molecules and (b)...

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