scholarly journals TD-DFT: An Exploration of the Energies and Structures of Crystal Violet and a Variety of Cr(III) Complex Ions

2021 ◽  
Author(s):  
◽  
Richard Kleingeld
Keyword(s):  
Electron Density ◽  
Density Functional ◽  
Computational Cost ◽  
Empty Space ◽  
Electronic Energy ◽  
Computational Method ◽  
Complex Ions ◽  
Phase Measurements ◽  
Td Dft ◽  
Electron Correlation Effects

<p>Spectroscopy is the science of utilising light in order to divine information about a molecule or system of molecules. Specifically, the absorption, emission, and scattering of different wavelengths of light can provide data about bond strength, bond order, vibrational frequency, and excitation energy [1, 2]. As the wavelength and therefore energy of the incident photons can be set by the instrument, the exact energies of absorbance or emission of the molecule can be measured. This data can be gathered experimentally using specialised equipment however some molecules resist synthesis, and so a wealth of data about many theoretically possible species eludes us. We may also want to isolate the molecule in “empty space” whereas “gas phase” measurements are not always possible. This is one place where computational chemistry comes to the fore. Using an appropriate computational method such as density functional theory (DFT), data can be theoretically derived and calculated for many interesting areas of chemistry. DFT is a computational method based on the findings of Hohenberg and Kohn in 1964 that the ground state electronic energy of a system can be determined completely by the electron density [3-6]. This means that it has a considerably higher efficiency as a computational method compared to the wave function approach, where the number of variables increases exponentially as your system increases in size, as the electron density has the same number of variables regardless of the size of the system [7]. The use of an appropriate functional to map the electron density and the energy is one of the vital choices in utilising this method, but if chosen well can provide good results with a much lower computational cost than other methods, while still accounting for electron correlation effects [8]. It has become a very popular method due to its versatility and generally good accuracy with relatively low computational expense when compared to ab initio methods [9].</p>

scholarly journals TD-DFT: An Exploration of the Energies and Structures of Crystal Violet and a Variety of Cr(III) Complex Ions

2021 ◽  
Author(s):  
◽  
Richard Kleingeld
Keyword(s):  
Electron Density ◽  
Density Functional ◽  
Computational Cost ◽  
Empty Space ◽  
Electronic Energy ◽  
Computational Method ◽  
Complex Ions ◽  
Phase Measurements ◽  
Td Dft ◽  
Electron Correlation Effects

<p>Spectroscopy is the science of utilising light in order to divine information about a molecule or system of molecules. Specifically, the absorption, emission, and scattering of different wavelengths of light can provide data about bond strength, bond order, vibrational frequency, and excitation energy [1, 2]. As the wavelength and therefore energy of the incident photons can be set by the instrument, the exact energies of absorbance or emission of the molecule can be measured. This data can be gathered experimentally using specialised equipment however some molecules resist synthesis, and so a wealth of data about many theoretically possible species eludes us. We may also want to isolate the molecule in “empty space” whereas “gas phase” measurements are not always possible. This is one place where computational chemistry comes to the fore. Using an appropriate computational method such as density functional theory (DFT), data can be theoretically derived and calculated for many interesting areas of chemistry. DFT is a computational method based on the findings of Hohenberg and Kohn in 1964 that the ground state electronic energy of a system can be determined completely by the electron density [3-6]. This means that it has a considerably higher efficiency as a computational method compared to the wave function approach, where the number of variables increases exponentially as your system increases in size, as the electron density has the same number of variables regardless of the size of the system [7]. The use of an appropriate functional to map the electron density and the energy is one of the vital choices in utilising this method, but if chosen well can provide good results with a much lower computational cost than other methods, while still accounting for electron correlation effects [8]. It has become a very popular method due to its versatility and generally good accuracy with relatively low computational expense when compared to ab initio methods [9].</p>

Developing orbital-free quantum crystallography: the local potentials and associated partial charge densities

2021 ◽  
Vol 77 (4) ◽  
Author(s):  
Vladimir Tsirelson ◽  
Adam Stash
Keyword(s):  
Density Functional Theory ◽  
Electron Density ◽  
Density Functional ◽  
Electronic Energy ◽  
Physical Content ◽  
Functional Theory ◽  
Orbital Free ◽  
The One ◽  
Physical And Chemical ◽  
Quantum Crystallography

This work extends the orbital-free density functional theory to the field of quantum crystallography. The total electronic energy is decomposed into electrostatic, exchange, Weizsacker and Pauli components on the basis of physically grounded arguments. Then, the one-electron Euler equation is re-written through corresponding potentials, which have clear physical and chemical meaning. Partial electron densities related with these potentials by the Poisson equation are also defined. All these functions were analyzed from viewpoint of their physical content and limits of applicability. Then, they were expressed in terms of experimental electron density and its derivatives using the orbital-free density functional theory approximations, and applied to the study of chemical bonding in a heteromolecular crystal of ammonium hydrooxalate oxalic acid dihydrate. It is demonstrated that this approach allows the electron density to be decomposed into physically meaningful components associated with electrostatics, exchange, and spin-independent wave properties of electrons or with their combinations in a crystal. Therefore, the bonding information about a crystal that was previously unavailable for X-ray diffraction analysis can be now obtained.

scholarly journals Multi-fidelity prediction of molecular optical peaks with deep learning

2021 ◽  
Author(s):  
Kevin Greenman ◽  
William Green ◽  
Rafael Gómez-Bombarelli
Keyword(s):  
Optical Properties ◽  
Statistical Methods ◽  
Message Passing ◽  
Density Functional ◽  
Molecular Design ◽  
Chemical Space ◽  
Epistemic Uncertainty ◽  
Computational Cost ◽  
Regression Tree ◽  
Td Dft

Optical properties are central to molecular design for many applications, including solar cells and biomedical imaging. A variety of ab initio and statistical methods have been developed for their prediction, each with a trade-off between accuracy, generality, and cost. Existing theoretical methods such as time-dependent density functional theory (TD-DFT) are generalizable across chemical space because of their robust physics-based foundations but still exhibit random and systematic errors with respect to experiment despite their high computational cost. Statistical methods can achieve high accuracy at a lower cost, but data sparsity and unoptimized molecule and solvent representations often limit their ability to generalize. Here, we utilize directed message passing neural networks (D-MPNNs) to represent both dye molecules and solvents for predictions of molecular absorption peaks in solution. Additionally, we demonstrate a multi-fidelity approach based on an auxiliary model trained on over 28,000 TD-DFT calculations that further improves accuracy and generalizability, as shown through rigorous splitting strategies. Combining several openly-available experimental datasets, we benchmark these methods against a state-of-the-art regression tree algorithm and compare the D-MPNN solvent representation to several alternatives. Finally, we explore the interpretability of the learned representations using dimensionality reduction and evaluate the use of ensemble variance as an estimator of the epistemic uncertainty in our predictions of molecular peak absorption in solution. The prediction methods proposed herein can be integrated with active learning, generative modeling, and experimental workflows to enable the more rapid design of molecules with targeted optical properties.

Fast computation of DFT nuclear gradient with multiresolution*This article is dedicated to Dr. Russell J. Boyd for his distinguished career in chemical research.

2011 ◽  
Vol 89 (6) ◽  
pp. 657-662 ◽  
Author(s):  
Nicholas J. Russ ◽  
Chun-min Chang ◽  
Jing Kong
Keyword(s):  
Density Functional Theory ◽  
Electron Density ◽  
Density Functional ◽  
Density Functional Theory Calculation ◽  
Computational Cost ◽  
Basis Sets ◽  
Local Spin Density Approximation ◽  
Functional Theory ◽  
Exchange Correlation ◽  
The Impact

We present an efficient algorithm for evaluating the exchange-correlation contribution to the nuclear gradients of density-functional theory calculation within the local spin-density approximation. The algorithm is an extension of the multiresolution exchange-correlation (mrXC) method, which treats smooth and compact parts of the electron density separately. The nuclear gradient of the smooth density is calculated on the even-spaced grid while the compact part of the density is handled on the normal atom-centered grid (ACG). The overall formulism is still formally based on the ACG, and thus does not change the results of the existing ACG-based algorithms for all-electron density-functional theory (DFT) calculations. The variation of the positions and weights of ACG owing to the nuclear perturbation is also handled rigorously. Benchmark calculations with different basis sets and sizes of ACG show that mrXC reduces the computational cost by several times without loss of accuracy. It also lessens the impact on the CPU time when the size of the ACG is increased.

scholarly journals Ground State Properties of the Wide Band Gap Semiconductor Beryllium Sulfide (BeS)

Materials ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6128
Author(s):  
Blaise A. Ayirizia ◽  
Janee’ S. Brumfield ◽  
Yuriy Malozovsky ◽  
Diola Bagayoko
Keyword(s):  
Band Gap ◽  
Lattice Constant ◽  
Ground State ◽  
Density Functional ◽  
Local Density ◽  
Wide Band ◽  
Electronic Energy ◽  
Computational Method ◽  
Energy Bands ◽  
Ground State Properties

We report the results from self-consistent calculations of electronic, transport, and bulk properties of beryllium sulfide (BeS) in the zinc-blende phase, and employed an ab-initio local density approximation (LDA) potential and the linear combination of atomic orbitals (LCAO). We obtained the ground state properties of zb-BeS with the Bagayoko, Zhao, and Williams (BZW) computational method, as enhanced by Ekuma and Franklin (BZW-EF). Our findings include the electronic energy bands, the total (DOS) and partial (pDOS) densities of states, electron and hole effective masses, the equilibrium lattice constant, and the bulk modulus. The calculated band structure clearly shows that zb-BeS has an indirect energy band gap of 5.436 eV, from Γ to a point between Γ and X, for an experimental lattice constant of 4.863 Å. This is in excellent agreement with the experiment, unlike the findings of more than 15 previous density functional theory (DFT) calculations that did not perform the generalized minimization of the energy functional, required by the second DFT theorem, which is inherent to the implementation of our BZW-EF method.

Benchmarking Computational Alchemy for Carbide, Nitride, and Oxide Catalysts

2018 ◽  
Author(s):  
Charles D. Griego ◽  
Karthikeyan Saravanan ◽  
John Keith
Keyword(s):  
Density Functional Theory ◽  
Transition Metal ◽  
Density Functional ◽  
Computational Cost ◽  
Oxide Catalysts ◽  
Computational Method ◽  
Metal Alloys ◽  
Functional Theory ◽  
Transition Metal Alloys

<p>Kohn-Sham density functional theory (DFT)-based searches for hypothetical catalysts are too computationally demanding for wide searches through diverse materials space. Our group has been critically evaluating the performance of an alternative computational method called computational alchemy. An advantage with this method is that it effectively brings no computational cost once a single DFT reference calculation is made. Extending from our 2017 publication in <i>J. Phys. Chem. Lett </i>(DOI: 10.1021/acs.jpclett.7b01974) that tested computational alchemy for transition metal alloys, we now assess the accuracy of computational alchemy schemes on carbides, nitrides, and oxides. </p>

Benchmarking Computational Alchemy for Carbide, Nitride, and Oxide Catalysts

2018 ◽  
Author(s):  
Charles D. Griego ◽  
Karthikeyan Saravanan ◽  
John Keith
Keyword(s):  
Density Functional Theory ◽  
Transition Metal ◽  
Density Functional ◽  
Computational Cost ◽  
Oxide Catalysts ◽  
Computational Method ◽  
Metal Alloys ◽  
Functional Theory ◽  
Transition Metal Alloys

<p>Kohn-Sham density functional theory (DFT)-based searches for hypothetical catalysts are too computationally demanding for wide searches through diverse materials space. Our group has been critically evaluating the performance of an alternative computational method called computational alchemy. An advantage with this method is that it effectively brings no computational cost once a single DFT reference calculation is made. Extending from our 2017 publication in <i>J. Phys. Chem. Lett </i>(DOI: 10.1021/acs.jpclett.7b01974) that tested computational alchemy for transition metal alloys, we now assess the accuracy of computational alchemy schemes on carbides, nitrides, and oxides. </p>

Electronic Structure Benchmark Calculations of Inorganic and Biochemical Carboxylation Reactions

2018 ◽  
Author(s):  
Oscar A. Douglas-Gallardo ◽  
David A. Sáez ◽  
Stefan Vogt-Geisse ◽  
Esteban Vöhringer-Martinez
Keyword(s):  
Electronic Structure ◽  
Chemical Reactions ◽  
Density Functional ◽  
Correlation Energy ◽  
Electronic Energy ◽  
Basis Sets ◽  
Electronic Correlation ◽  
Correct Description ◽  
Carbon Dioxide Co2 ◽  
High Level

<div><div><div><p>Carboxylation reactions represent a very special class of chemical reactions that is characterized by the presence of a carbon dioxide (CO2) molecule as reactive species within its global chemical equation. These reactions work as fundamental gear to accomplish the CO2 fixation and thus to build up more complex molecules through different technological and biochemical processes. In this context, a correct description of the CO2 electronic structure turns out to be crucial to study the chemical and electronic properties associated with this kind of reactions. Here, a sys- tematic study of CO2 electronic structure and its contribution to different carboxylation reaction electronic energies has been carried out by means of several high-level ab-initio post-Hartree Fock (post-HF) and Density Functional Theory (DFT) calculations for a set of biochemistry and inorganic systems. We have found that for a correct description of the CO2 electronic correlation energy it is necessary to include post-CCSD(T) contributions (beyond the gold standard). These high-order excitations are required to properly describe the interactions of the four π-electrons as- sociated with the two degenerated π-molecular orbitals of the CO2 molecule. Likewise, our results show that in some reactions it is possible to obtain accurate reaction electronic energy values with computationally less demanding methods when the error in the electronic correlation energy com- pensates between reactants and products. Furthermore, the provided post-HF reference values allowed to validate different DFT exchange-correlation functionals combined with different basis sets for chemical reactions that are relevant in biochemical CO2 fixing enzymes.</p></div></div></div>

The Nature of S-N Bonding in Sulfonamides and Related Compounds: Insights into π-Bonding Contributions from Sulfur K-Edge XAS

2020 ◽  
Author(s):  
Tulin Okbinoglu ◽  
Pierre Kennepohl
Keyword(s):  
Density Functional ◽  
Chemical Properties ◽  
Functional Theory ◽  
Rotational Barriers ◽  
Td Dft ◽  
Nitrogen Bonds ◽  
X Ray Absorption ◽  
Related Compounds ◽  
And Chemical Properties

Molecules containing sulfur-nitrogen bonds, like sulfonamides, have long been of interest due to their many uses and chemical properties. Understanding the factors that cause sulfonamide reactivity is important, yet their continues to be controversy regarding the relevance of S-N π bonding in describing these species. In this paper, we use sulfur K-edge x-ray absorption spectroscopy (XAS) in conjunction with density functional theory (DFT) to explore the role of S<sub>3p</sub> contributions to π-bonding in sulfonamides, sulfinamides and sulfenamides. We explore the nature of electron distribution of the sulfur atom and its nearest neighbors and extend the scope to explore the effects on rotational barriers along the sulfur-nitrogen axis. The experimental XAS data together with TD-DFT calculations confirm that sulfonamides, and the other sulfinated amides in this series, have essentially no S-N π bonding involving S<sub>3p</sub> contributions and that electron repulsion and is the dominant force that affect rotational barriers.

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