scholarly journals Application of Explicitly Localized Molecular Orbitals to Electronic Structure Calculations

2012 ◽  
Vol 66 (4) ◽  
pp. 178-181 ◽  
Author(s):  
Piotr de Silva ◽  
Marcin Makowski ◽  
Jacek Korchowiec
1989 ◽  
Vol 169 ◽  
Author(s):  
J. A. Cogordan

AbstractMolecular ab initio seIf-consistent calculations on clusters simulating the copper-oxygen layers in the Yba2Cu3O6;δ are reported. The electronic structure, of this layer, was computed for different sets of values of the lattice parameters (a,b,c), according to their dependence on the oxygen stiochiometry. For the molecular orbitals , two different electronic occupations are considered, a closed shell and an open shell. For the open shell, an electron has been excited to the first virtual molecular orbital. It is found that this excited state has lower energy than the closed shell configuration for 0 < δ < 1. Molecular energies an electronic population are reported.


2020 ◽  
Author(s):  
Ali Raza ◽  
Arni Sturluson ◽  
Cory Simon ◽  
Xiaoli Fern

Virtual screenings can accelerate and reduce the cost of discovering metal-organic frameworks (MOFs) for their applications in gas storage, separation, and sensing. In molecular simulations of gas adsorption/diffusion in MOFs, the adsorbate-MOF electrostatic interaction is typically modeled by placing partial point charges on the atoms of the MOF. For the virtual screening of large libraries of MOFs, it is critical to develop computationally inexpensive methods to assign atomic partial charges to MOFs that accurately reproduce the electrostatic potential in their pores. Herein, we design and train a message passing neural network (MPNN) to predict the atomic partial charges on MOFs under a charge neutral constraint. A set of ca. 2,250 MOFs labeled with high-fidelity partial charges, derived from periodic electronic structure calculations, serves as training examples. In an end-to-end manner, from charge-labeled crystal graphs representing MOFs, our MPNN machine-learns features of the local bonding environments of the atoms and learns to predict partial atomic charges from these features. Our trained MPNN assigns high-fidelity partial point charges to MOFs with orders of magnitude lower computational cost than electronic structure calculations. To enhance the accuracy of virtual screenings of large libraries of MOFs for their adsorption-based applications, we make our trained MPNN model and MPNN-charge-assigned computation-ready, experimental MOF structures publicly available.<br>


2021 ◽  
Vol 154 (11) ◽  
pp. 114105
Author(s):  
Max Rossmannek ◽  
Panagiotis Kl. Barkoutsos ◽  
Pauline J. Ollitrault ◽  
Ivano Tavernelli

2021 ◽  
Vol 155 (3) ◽  
pp. 034110
Author(s):  
Prakash Verma ◽  
Lee Huntington ◽  
Marc P. Coons ◽  
Yukio Kawashima ◽  
Takeshi Yamazaki ◽  
...  

2016 ◽  
Vol 18 (1) ◽  
pp. 403-413 ◽  
Author(s):  
Bin-Bin Xie ◽  
Shu-Hua Xia ◽  
Xue-Ping Chang ◽  
Ganglong Cui

Sequential vs. concerted S1 relaxation pathways.


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