Quantum chemistry in the 21st century (Special topic article)

2000 ◽  
Vol 72 (8) ◽  
pp. 1405-1423 ◽  
Author(s):  
Christopher J. Barden ◽  
Henry F. Schaefer
Keyword(s):  
Quantum Chemistry ◽  
Density Functional ◽  
Special Topic ◽  
Future Research ◽  
New Era ◽  
Incremental Development ◽  
Quantum Chemical Methods ◽  
Theoretical Predictions ◽  
Ready Availability ◽  
High Level

Quantum chemistry is the field in which solutions to the Schrödinger equation are used to predict the properties of molecules and solve chemical problems. This paper considers possible future research directions in light of the discipline's past successes. After decades of incremental development—accompanied by a healthy dose of skepticism from the experimental community—the ready availability of fast computers has ushered in a "golden age" of quantum chemistry. In this new era of acceptance, theoretical predictions often precede experiment in small molecule chemistry, and quantum chemical methods play an ever greater role in biochemical and other larger systems. Quantum chemists increasingly divide their efforts along three fronts: high-level (spectroscopic) accuracy for small molecules, characterized by such techniques as Brueckner methods, r12 formalisms, and multireference calculations; parameterization- or extrapolation-based intermediate-level schemes (such as Gaussian-N theory) for medium molecules; and lower-level (chemical) accuracy for large molecules, characterized by density functional theory and linear scaling techniques. These tools, and quantum chemistry as a whole, are examined here from a historical perspective and with a view toward their future applications.

The CHAL336 Benchmark Set: How Well Do Quantum-Chemical Methods Describe Chalcogen-Bonding Interactions?

2021 ◽  
Author(s):  
Nisha Mehta ◽  
Thomas Fellowes ◽  
JONATHAN WHITE ◽  
Lars Goerigk
Keyword(s):  
Density Functional ◽  
Noncovalent Interactions ◽  
Interaction Energies ◽  
Chemical Methods ◽  
Dft Methods ◽  
The Past ◽  
Quantum Chemical Methods ◽  
London Dispersion ◽  
High Level ◽  
Selection Of

<div> <div> <div> <p>We present the CHAL336 benchmark set—the most comprehensive database for the assessment of chalcogen-bonding (CB) interactions. After careful selection of suitable systems and identification of three high-level reference methods, the set comprises 336 dimers each consisting of up to 49 atoms and covers both σ- and π-hole interactions across four categories: chalcogen-chalcogen, chalcogen-π, chalcogen-halogen, and chalcogen-nitrogen interactions. In a subsequent study of DFT methods, we re- emphasize the need for using proper London-dispersion corrections when treating noncovalent interactions. We also point out that the deterioration of results and systematic overestimation of interaction energies for some dispersion-corrected DFT methods does not hint at problems with the chosen dispersion correction, but is a consequence of large density-driven errors. We conclude this work by performing the most detailed DFT benchmark study for CB interactions to date. We assess 98 variations of dispersion- corrected and -uncorrected DFT methods, and carry out a detailed analysis of 72 of them. Double-hybrid functionals are the most reliable approaches for CB interactions, and they should be used whenever computationally feasible. The best three double hybrids are SOS0-PBE0-2-D3(BJ), revDSD-PBEP86-D3(BJ), and B2NCPLYP-D3(BJ). The best hybrids in this study are ωB97M-V, PW6B95-D3(0), and PW6B95-D3(BJ). We do not recommend using any lower-rung DFT methods nor the popular B3LYP and MP2 approaches, which have been used to describe CB interactions in the past. We hope to inspire a change in computational protocols surrounding CB interactions that leads away from the commonly used, popular methods to the more robust and accurate ones recommended herein. We would also like to encourage method developers to use our set for the investigation and reduction of density-driven errors in new density functional approximations. </p> </div> </div> </div>

scholarly journals The CHAL336 Benchmark Set: How Well Do Quantum-Chemical Methods Describe Chalcogen-Bonding Interactions?

2021 ◽  
Author(s):  
Nisha Mehta ◽  
Thomas Fellowes ◽  
JONATHAN WHITE ◽  
Lars Goerigk
Keyword(s):  
Density Functional ◽  
Noncovalent Interactions ◽  
Interaction Energies ◽  
Chemical Methods ◽  
Dft Methods ◽  
The Past ◽  
Quantum Chemical Methods ◽  
London Dispersion ◽  
High Level ◽  
Selection Of

<div> <div> <div> <p>We present the CHAL336 benchmark set—the most comprehensive database for the assessment of chalcogen-bonding (CB) interactions. After careful selection of suitable systems and identification of three high-level reference methods, the set comprises 336 dimers each consisting of up to 49 atoms and covers both σ- and π-hole interactions across four categories: chalcogen-chalcogen, chalcogen-π, chalcogen-halogen, and chalcogen-nitrogen interactions. In a subsequent study of DFT methods, we re- emphasize the need for using proper London-dispersion corrections when treating noncovalent interactions. We also point out that the deterioration of results and systematic overestimation of interaction energies for some dispersion-corrected DFT methods does not hint at problems with the chosen dispersion correction, but is a consequence of large density-driven errors. We conclude this work by performing the most detailed DFT benchmark study for CB interactions to date. We assess 98 variations of dispersion- corrected and -uncorrected DFT methods, and carry out a detailed analysis of 72 of them. Double-hybrid functionals are the most reliable approaches for CB interactions, and they should be used whenever computationally feasible. The best three double hybrids are SOS0-PBE0-2-D3(BJ), revDSD-PBEP86-D3(BJ), and B2NCPLYP-D3(BJ). The best hybrids in this study are ωB97M-V, PW6B95-D3(0), and PW6B95-D3(BJ). We do not recommend using any lower-rung DFT methods nor the popular B3LYP and MP2 approaches, which have been used to describe CB interactions in the past. We hope to inspire a change in computational protocols surrounding CB interactions that leads away from the commonly used, popular methods to the more robust and accurate ones recommended herein. We would also like to encourage method developers to use our set for the investigation and reduction of density-driven errors in new density functional approximations. </p> </div> </div> </div>

Computing protein infrared spectroscopy with quantum chemistry

2007 ◽  
Vol 365 (1861) ◽  
pp. 2799-2812 ◽  
Author(s):  
Nicholas A Besley
Keyword(s):  
Infrared Spectroscopy ◽  
Quantum Chemistry ◽  
Nobel Prize ◽  
Quantum Chemical ◽  
Chemical Methods ◽  
New Era ◽  
Quantum Chemical Methods ◽  
Ongoing Work ◽  
Realistic Possibility ◽  
Quantitative Calculations

Quantum chemistry is a field of science that has undergone unprecedented advances in the last 50 years. From the pioneering work of Boys in the 1950s, quantum chemistry has evolved from being regarded as a specialized and esoteric discipline to a widely used tool that underpins much of the current research in chemistry today. This achievement was recognized with the award of the 1998 Nobel Prize in Chemistry to John Pople and Walter Kohn. As the new millennium unfolds, quantum chemistry stands at the forefront of an exciting new era. Quantitative calculations on systems of the magnitude of proteins are becoming a realistic possibility, an achievement that would have been unimaginable to the early pioneers of quantum chemistry. In this article we will describe ongoing work towards this goal, focusing on the calculation of protein infrared amide bands directly with quantum chemical methods.

The CHAL336 Benchmark Set: How Well Do Quantum-Chemical Methods Describe Chalcogen-Bonding Interactions?

2021 ◽  
Author(s):  
Nisha Mehta ◽  
Thomas Fellowes ◽  
JONATHAN WHITE ◽  
Lars Goerigk
Keyword(s):  
Density Functional ◽  
Noncovalent Interactions ◽  
Interaction Energies ◽  
Chemical Methods ◽  
Dft Methods ◽  
The Past ◽  
Quantum Chemical Methods ◽  
London Dispersion ◽  
High Level ◽  
Selection Of

<div> <div> <p> </p><div> <div> <div> <p>We present the CHAL336 benchmark set—the most comprehensive database for the assessment of chalcogen-bonding (CB) interactions. After careful selection of suitable systems and identification of three high-level reference methods, the set comprises 336 dimers each consisting of up to 49 atoms and covers both σ- and π-hole interactions across four categories: chalcogen-chalcogen, chalcogen-π, chalcogen-halogen, and chalcogen-nitrogen interactions. In a subsequent study of DFT methods, we re-emphasize the need for using proper London dispersion corrections when treating noncovalent interactions. We also point out that the deterioration of results and systematic overestimation of interaction energies for some dispersion-corrected DFT methods does not hint at problems with the chosen dispersion correction, but is a consequence of large density-driven errors. We conclude this work by performing the most detailed DFT benchmark study for CB interactions to date. We assess 109 variations of dispersion-corrected and -uncorrected DFT methods, and carry out a detailed analysis of 80 of them. Double-hybrid functionals are the most reliable approaches for CB interactions, and they should be used whenever computationally feasible. The best three double hybrids are SOS0-PBE0-2-D3(BJ), revDSD-PBEP86-D3(BJ), and B2NCPLYP-D3(BJ). The best hybrids in this study are ωB97M-V, PW6B95-D3(0), and PW6B95-D3(BJ). We do not recommend using the popular B3LYP functional nor the MP2 approach, which have both been frequently used to describe CB interactions in the past. We hope to inspire a change in computational protocols surrounding CB interactions that leads away from the commonly used, popular methods to the more robust and accurate ones recommended herein. We would also like to encourage method developers to use our set for the investigation and reduction of density-driven errors in new density functional approximations. </p> </div> </div> </div> </div> </div>

scholarly journals The American newsroom in the new era: factors that influence the adoption or rejection of new technologies by non-management newspaper news producers

2017 ◽  
Author(s):  
◽  
Sintia Radu
Keyword(s):  
New Technologies ◽  
New Technology ◽  
The United States ◽  
Future Research ◽  
Sources Of Information ◽  
Structured Interviews ◽  
New Era ◽  
The Media ◽  
False News ◽  
High Level

Today, journalists need to engage in the most advanced technological methods of reaching their audience more efficiently as media professionals now battle a fast spread of unverified news. Journalists need to be quicker, but also retain the high level of accuracy that distinguishes the media from other sources of information. A very good example of the importance of the media needing to be faster and more accurate than ever, especially in the online environment, is the bombardment with false news on Facebook and Google during the 2016 U.S. elections. The purpose of my thesis is to explore what influences the adoption or resistance to new technology in newsrooms and how new technologies change the journalistic processes. I looked at how nonmanagement news producers dealt with technology throughout time, referring to the previous adoption of now embraced technologies. I also inquired about technologies that they are currently experimenting with, and attempted to predict the probability of them using other new technologies that they might not be familiar with. The research method that I used is qualitative semi-structured interviews with 11 news producers from newspapers across the United States, who talked about their perception on how their newsrooms deal with technology-related decisions. My results showed that non-management news producers believe newspaper newsrooms adopt technology based on preferences and industry practices. The media seems keen on experimenting with new types of technologies, but there are several aspects that they fail to consider. This makes the implementation of these technologies either hard to understand by users or very hard to carry out per se. News producers complained they are overburdened with tasks because of new technology that newsrooms are forcing onto them just because their peers in the industry are using it, while they admitted they would be interested in trying anything that might get them closer to their readers. If the technology serves them or not, they thought this is mostly related to leadership in the company. These results are to be considered by those who build technology for the media and those in charge of incorporating it in the work of news producers. Future research could take into consideration both including more diverse subject categories, as well as the academic environment in which journalism is still taught.

scholarly journals Relative thermodynamic stability of the [C,N,O] linkages as an indication of the most abundant structures in the ISM

2020 ◽  
Vol 639 ◽  
pp. A16
Author(s):  
I. Fourré ◽  
O. Matz ◽  
Y. Ellinger ◽  
J.-C. Guillemin
Keyword(s):  
Density Functional ◽  
Energy Scale ◽  
Negative Ion ◽  
Future Research ◽  
Stable Isomer ◽  
Energy Principle ◽  
Order Of Magnitude ◽  
The Stability ◽  
High Level

Context. Most of the compounds detected in the interstellar medium (ISM) that possess isomers correspond to the thermodynamically most stable isomer of a given chemical formula. Using the minimun energy principle (MEP) as a pragmatic tool is particularly efficient for less than six atoms, but for larger systems combinatorial analysis gives an intractable numbers of isomers. Aims. To make the MEP more applicable, we look for a chemical sieve to filter the thermodynamic data needed to determine which isomers of complex organic molecules (COMs) have higher chances of being present in the ISM. To do so, we investigate whether the nature of the [C,N,O] elementary fragment can be determinant for the stabilization of COMs, taking C2H3NO as a case study. Methods. We employed standard quantum chemistry methods to determine the ordering of fragments and derivatives on the energy scale. Density functional theory treatments were systematically performed, together with high-level coupled cluster calculations to refine relative energies. Results. For C2H3NO we find methylisocyanate CH3NCO, which is a compound that was very recently detected in the ISM, to be the most stable isomer in a corpus of 40 isomers of lowest energy. In neutral form we find the stability ordering of NCO > ONC; the same is true for the negative ion. Attachments of R=H, CH3, C2H5, HC2, H2CCH, and C6H5 and metals Al and Mg to the nitrogen atom of the NCO fragment provide the most stable isomers. The energy differences between the successive isomers on the energy scale R-NCO, R-OCN, R-CNO, and R-ONC are of the same order of magnitude for all carbonaceous R. Conclusions. Combining the criterion of most stable linkage with the MEP concept should greatly reduce the window of potential targets to be searched for in the ISM. Compounds containing the NCO linkage should be preferential targets of future research.

scholarly journals Sulfate radical oxidation of aromatic contaminants: a detailed assessment of density functional theory and high-level quantum chemical methods

2017 ◽  
Vol 19 (3) ◽  
pp. 395-404 ◽  
Author(s):  
Sangavi Pari ◽  
Inger A. Wang ◽  
Haizhou Liu ◽  
Bryan M. Wong
Keyword(s):  
Density Functional Theory ◽  
Quantum Chemical ◽  
Density Functional ◽  
Sulfate Radical ◽  
Chemical Methods ◽  
Functional Theory ◽  
Radical Oxidation ◽  
Quantum Chemical Methods ◽  
Detailed Assessment ◽  
High Level

DFT and high-level quantum methods are utilized to explore sulfate radical-driven oxidation.

Power of Modified Brown-Forsythe and Mixed-Model Approaches in Split-Plot Designs

Methodology ◽  
2017 ◽  
Vol 13 (1) ◽  
pp. 9-22 ◽  
Author(s):  
Pablo Livacic-Rojas ◽  
Guillermo Vallejo ◽  
Paula Fernández ◽  
Ellián Tuero-Herrero
Keyword(s):  
Repeated Measures ◽  
Statistical Power ◽  
Mixed Model ◽  
Covariance Structure ◽  
Simulation Method ◽  
Future Research ◽  
Repeated Measures Design ◽  
Fixed And Random Effects ◽  
Split Plot ◽  
High Level

Abstract. Low precision of the inferences of data analyzed with univariate or multivariate models of the Analysis of Variance (ANOVA) in repeated-measures design is associated to the absence of normality distribution of data, nonspherical covariance structures and free variation of the variance and covariance, the lack of knowledge of the error structure underlying the data, and the wrong choice of covariance structure from different selectors. In this study, levels of statistical power presented the Modified Brown Forsythe (MBF) and two procedures with the Mixed-Model Approaches (the Akaike’s Criterion, the Correctly Identified Model [CIM]) are compared. The data were analyzed using Monte Carlo simulation method with the statistical package SAS 9.2, a split-plot design, and considering six manipulated variables. The results show that the procedures exhibit high statistical power levels for within and interactional effects, and moderate and low levels for the between-groups effects under the different conditions analyzed. For the latter, only the Modified Brown Forsythe shows high level of power mainly for groups with 30 cases and Unstructured (UN) and Autoregressive Heterogeneity (ARH) matrices. For this reason, we recommend using this procedure since it exhibits higher levels of power for all effects and does not require a matrix type that underlies the structure of the data. Future research needs to be done in order to compare the power with corrected selectors using single-level and multilevel designs for fixed and random effects.

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>

BAND NN: A Deep Learning Framework For Energy Prediction and Geometry Optimization of Organic Small Molecules

2019 ◽  
Author(s):  
Siddhartha Laghuvarapu ◽  
Yashaswi Pathak ◽  
U. Deva Priyakumar
Keyword(s):  
Machine Learning ◽  
Density Functional ◽  
Computational Cost ◽  
Geometry Optimization ◽  
Dft Methods ◽  
Energy Prediction ◽  
Machine Learning Model ◽  
Equilibrium Structures ◽  
High Level ◽  
Non Equilibrium

Recent advances in artificial intelligence along with development of large datasets of energies calculated using quantum mechanical (QM)/density functional theory (DFT) methods have enabled prediction of accurate molecular energies at reasonably low computational cost. However, machine learning models that have been reported so far requires the atomic positions obtained from geometry optimizations using high level QM/DFT methods as input in order to predict the energies, and do not allow for geometry optimization. In this paper, a transferable and molecule-size independent machine learning model (BAND NN) based on a chemically intuitive representation inspired by molecular mechanics force fields is presented. The model predicts the atomization energies of equilibrium and non-equilibrium structures as sum of energy contributions from bonds (B), angles (A), nonbonds (N) and dihedrals (D) at remarkable accuracy. The robustness of the proposed model is further validated by calculations that span over the conformational, configurational and reaction space. The transferability of this model on systems larger than the ones in the dataset is demonstrated by performing calculations on select large molecules. Importantly, employing the BAND NN model, it is possible to perform geometry optimizations starting from non-equilibrium structures along with predicting their energies.

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