Semiempirical Quantum-Chemical Methods with Orthogonalization and Dispersion Corrections

Dral, Pavlo O.; Wu, Xin; Thiel, Walter

doi:10.1021/acs.jctc.8b01265

Cited by 64 publications

(66 citation statements)

References 169 publications

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“…Similarly, for another data set, reaction energies in the HC7/11 set, 37 AIQM1 accuracy is also very close to that 13 of CCSD(T)*/CBS (MADs of 1.4 and 1.6 kcal/mol, respectively) and clearly outperforms both ODM2 and ANI-1ccx with MADs of 5.37 and 2.53 kcal/mol, 13,17 respectively (Figure 4b). Curiously, for both IsoL6/11 and HC7/11 data sets, even AIQM1@DFT (MADs 1.5 and 9.2 kcal/mol, respectively) is much better than more expensive ωB97X/6-31G* tested previously 13 (MADs 3.8 and 16.4 kcal/mol, respectively).…”

Section: Performance For Energiessupporting

confidence: 53%

Artificial Intelligence-Enhanced Quantum Chemical Method with Broad Applicability

Zheng

Zubatyuk

et al. 2021

Preprint

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High-level quantum mechanical (QM) calculations are indispensable for accurate explanation of natural phenomena on the atomistic level. Their staggering computational cost, however, poses great limitations, which luckily can be lifted to a great extent by exploiting advances in artificial intelligence (AI). Here we introduce the general-purpose, highly transferable artificial intelligence-quantum mechanical method 1 (AIQM1). It approaches the accuracy of the 'gold-standard' coupled cluster QM method with low computational speed of the approximate low-level semiempirical QM methods. AIQM1 can provide accurate groundstate energies for diverse organic compounds as well as geometries for even challenging systems such as large conjugated compounds (fullerene C60) close to experiment. Noteworthy, our method's accuracy is also good for ions and excited-state properties, although the neural network part of AIQM1 was never fitted to these properties.

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Section: Performance For Energiessupporting

confidence: 53%

Artificial Intelligence-Enhanced Quantum Chemical Method with Broad Applicability

Zheng

Zubatyuk

et al. 2021

Preprint

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“…There is not a universal, objective way to conduct a parametrization and, furthermore, with the use of genetic algorithms, one may obtain many solutions than can be equally valid. For general discussions on parameterizations for SQM methods, the reader may consult the studies on the development of the PMO2a 16 and ODMx 17 methods. For the formic acid dimer, because there are 15 different types of pairwise interactions, the total number of parameters is 60, without including those associated with the cutoff function given by eq 2 .…”

Section: Resultsmentioning

confidence: 99%

“… 41 , 42 For the recent ODMx methods, several training sets were used, including the abovementioned S66 data set. 25 − 27 Parameterization of semiempirical Hamiltonians and correction potentials for noncovalent interactions is a key issue, and the procedure followed within the ODMx methods is extensively discussed in the recent article by Dral et al 17 …”

Section: Introductionmentioning

confidence: 99%

New Approach for Correcting Noncovalent Interactions in Semiempirical Quantum Mechanical Methods: The Importance of Multiple-Orientation Sampling

Pérez-Tabero

Fernández

Cabaleiro‐Lago

et al. 2021

J. Chem. Theory Comput.

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A new approach is presented to improve the performance of semiempirical quantum mechanical (SQM) methods in the description of noncovalent interactions. To show the strategy, the PM6 Hamiltonian was selected, although, in general, the procedure can be applied to other semiempirical Hamiltonians and to different methodologies. A set of small molecules were selected as representative of various functional groups, and intermolecular potential energy curves (IPECs) were evaluated for the most relevant orientations of interacting molecular pairs. Then, analytical corrections to PM6 were derived from fits to B3LYP-D3/def2-TZVP reference–PM6 interaction energy differences. IPECs provided by the B3LYP-D3/def2-TZVP combination of the electronic structure method and basis set were chosen as the reference because they are in excellent agreement with CCSD(T)/aug-cc-pVTZ curves for the studied systems. The resulting method, called PM6-FGC (from functional group corrections), significantly improves the performance of PM6 and shows the importance of including a sufficient number of orientations of the interacting molecules in the reference data set in order to obtain well-balanced descriptions.

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“…A general similarity between all SQM methods is parameterization, which, if conducted carefully, can minimize accuracy issues for special purpose applications. [30][31][32][33][34][35][36] Among the most frequently used Hartree-Fock based zero-differential overlap (ZDO) methods are PM6, [37][38][39][40][41][42] -used for the computation of ground state structures and energies [43][44][45][46] -and OM2, [47][48][49][50][51] which is extensively applied in excited state dynamics studies. [52][53][54][55][56] Over the past decades, density functional tight binding (DFTB) methods, [57][58][59][60][61][62][63][64][65][66] as derived from DFT, have found more attention, whereat in recent years the extended tightbinding (xTB) family of methods has been developed.…”

Section: Introductionmentioning

confidence: 99%

A Robust Non-Self-Consistent Tight-Binding Quantum Chemistry Method for large Molecules

Pracht

Caldeweyher²,

Ehlert³

et al. 2019

Preprint

106

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We propose a semiempirical quantum chemical method, designed for the fast calculation of molecular Geometries, vibrational Frequencies and Non-covalent interaction energies (GFN) of systems with up to a few thousand atoms. Like its predecessors GFN-xTB and GFN2-xTB, the new method termed GFN0-xTB is parameterized for all elements up to radon (Z = 86) and mostly shares well-known density functional tight-binding approximations as well as basis set and integral approximations. The main new feature is the avoidance of the self-consistent charge iterations leading to speed-ups of a factor of 2-20 depending on the size and electronic complexity of the system. This is achieved by including only quantum mechanical contributions up to first-order which are incorporated similar to the previous versions without any pair-specific parameterization. The essential electrostatic electronic interaction is treated by a classical electronegativity equilibration charge model yielding atomic partial charges that enter the electronic Hamiltonian indirectly. Furthermore, the atomic charge-dependent D4 dispersion correction is included to account for long range London correlation effects. Formulas for analytical total energy gradients with respect to nuclear displacements are derived and implemented in the xtb code allowing numerically very precise structure optimizations. The neglect of self-consistent energy terms not only leads to a large gain in computational speed but also can increase robustness in electronically difficult situations because ill-convergence or artificial charge-transfer (CT) is avoided. The comparison of GFN0-xTB and GFN/GFN2-xTB allows dissection of quantum electronic polarization and CT effects thereby improving our understanding of chemical bonding. Compared the the most sophisticated multipole-based GFN2-xTB model (which approaches DFT accuracy for the target properties closely), GFN0-xTB performs slightly worse for non-covalent interactions and molecular structures, while very good results are observed for conformational energies. Vibrational frequencies are obtained less accurately than with GFN/GFN2-xTB but they may still be useful for various purposes like estimating relative thermostatistical reaction energies. Most exceptional is the fact that even relatively complicated transition metal complex structures can be accurately optimized with a non-self-consistent quantum approach. The new method bridges the gap between force-fields and traditional semiempirical methods with its excellent computational cost to accuracy ratio and is intended to explore the chemical space of large molecular systems and solids.

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Semiempirical Quantum-Chemical Methods with Orthogonalization and Dispersion Corrections

Cited by 64 publications

References 169 publications

Artificial Intelligence-Enhanced Quantum Chemical Method with Broad Applicability

Artificial Intelligence-Enhanced Quantum Chemical Method with Broad Applicability

New Approach for Correcting Noncovalent Interactions in Semiempirical Quantum Mechanical Methods: The Importance of Multiple-Orientation Sampling

A Robust Non-Self-Consistent Tight-Binding Quantum Chemistry Method for large Molecules

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