Application of a quantum genetic algorithm and QTAIM analysis in the study of structural and electronic properties of neutral bimetallic clusters NaxLiy (4 ≤ x + y ≤ 10)

Silva, Frederico Teixeira; Rocha-Santos, Acassio; Firme, Caio Lima; Souza, Leonardo A. De; Anjos, Italo Curvelo dos; Belchior, Jadson C.

doi:10.1007/s00894-020-04576-1

Cited by 3 publications

(1 citation statement)

References 75 publications

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“…The first quantum genetic algorithm that uses Gaussian-type orbital basis for atomic cluster optimization QGA 28 relied only on standard GA operators. This approach works well, as shown by recent work 30 for a small number of atoms. However, for bigger clusters, this becomes computationally prohibitive due to the need to evaluate several clusters using ab initio level theory.…”

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confidence: 71%

An approach based on genetic algorithms and machine learning coupled for studying alloy and molecular clusters by optimizing quantum energy surfaces

Rezende,

De Souza,

Belchior

2023

J Comput Chem

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A new genetic algorithm has been proposed focusing on direct ab initio potential energy surface (PES) global minima search. Besides the commonly used operators, this new approach uses an operator to: improve the initial cluster generation, classify and compare all generated clusters, and use machine learning to model the quantum PES used in parallel optimization. Part of the validation process for this methodology was done with 19,38,55) and Au n Ag n (n ¼ 10,20,30, 40,50,60,70, and 75). The results are in fair agreement with the literature and led to a new global minimum for Cu 12 Au 7 . A search has been done for the lowest energies of Li n nanoclusters with 2-8 atoms using the DFT approach and for Li 3 , Li 4 ,Li 2 H, Li 3 H using DLPNO-CCSD(T) approach. NQGA successfully performed the MP2 optimizations for ðH 2 OÞ 11 cluster. In all cases, the proposed genetic algorithm located the previously reported global minima with very efficient performance. The new proposed methodology makes it possible to optimize cluster geometries directly using high-level ab initio methods relinquishing any bias introduced by a classical approach. Our results show that this proposed method has great potential applications due to its flexibility and efficiency in identifying global minima in the tested atomic systems.

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supporting

confidence: 71%

An approach based on genetic algorithms and machine learning coupled for studying alloy and molecular clusters by optimizing quantum energy surfaces

Rezende,

De Souza,

Belchior

2023

J Comput Chem

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Planar pentacoordinate s-block metals

Wang¹,

Kalita²,

Orozco‐Ic³

et al. 2023

Chem. Sci.

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Theoretical insights into the structure, stability, thermochemistry, and bonding in hydrated N2O clusters

Manogaran,

Ambigapathy,

Pandiaraj

et al. 2023

Preprint

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We have investigated the structure, stability, thermochemistry, and bonding in microhydrated N2O clusters (N2O‧Wn (n = 1–12)). To do this we used various theoretical methods and techniques including density functional theory (DFT), quantitative molecular electrostatic potential surface (MESP), quantum theory of atoms in molecules (QTAIM), and noncovalent interaction analysis (NCI). A detailed density functional search shows that N2O lies on the top of the water molecules and water molecules tend to form a cage structure. The existence of water in cage geometry and segregation of N2O unveils the presence of weak bonding between N2O and water cluster. The computed adsorption energy (ΔEabs), association energy (AE), and incremental association energy (ΔEIA) were all negative which means the complexes are stabilized. In small size clusters the most stable isomer dominates the relative population at all temperatures. In cluster with 6 and more water all the isomers contribute at the high atmospheric temperature. The formation of all the hydrated N2O complexes is enthalpically favored over the range of atmospheric altitudes. In general, the free energy change and enthalpy change decrease with the increase in altitude. The enthalpy change for the clusters unveils a distinct inflection at the tropopause. MESP analysis shows a higher Vs,max value on the hydrogen atom of a water molecule at the terminal end which helps for the addition of water molecules. QTAIM and NCI analyses reveal that N2O-water complexes are predominately stabilized by weak noncovalent interactions like N‧‧‧OW, O‧‧‧Ow, and O‧‧‧Hw. Overall, this work helps in understanding the structure, and stability of hydrated N2O molecules at different altitudes of the atmosphere.

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Application of a quantum genetic algorithm and QTAIM analysis in the study of structural and electronic properties of neutral bimetallic clusters NaxLiy (4 ≤ x + y ≤ 10)

Cited by 3 publications

References 75 publications

An approach based on genetic algorithms and machine learning coupled for studying alloy and molecular clusters by optimizing quantum energy surfaces

An approach based on genetic algorithms and machine learning coupled for studying alloy and molecular clusters by optimizing quantum energy surfaces

Planar pentacoordinate s-block metals

Theoretical insights into the structure, stability, thermochemistry, and bonding in hydrated N2O clusters

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