Toward the construction of an exchange-correlation potential in electronic-structure calculations of two-particle states in solids

2002 ◽  
pp. 325-339
Author(s):  
A. Gonis
Keyword(s):  
Electronic Structure ◽  
Electronic Structure Calculations ◽  
Exchange Correlation ◽  
Exchange Correlation Potential ◽  
Correlation Potential ◽  
Structure Calculations

IS THERE A METAMAGNETIC PHASE TRANSITION IN Pd?

1993 ◽  
Vol 07 (01n03) ◽  
pp. 275-278 ◽  
Author(s):  
ANDERS HJELM
Keyword(s):  
Phase Transition ◽  
Applied Field ◽  
Zeeman Splitting ◽  
Electronic Structure Calculations ◽  
Spin Orbit Coupling ◽  
Spin Orbit ◽  
Exchange Correlation ◽  
Exchange Correlation Potential ◽  
Correlation Potential ◽  
Structure Calculations

Electronic structure calculations for Pd in external magnetic fields are presented. The external magnetic field is included self consistently by adding the Zeeman term to the variational step. Thereby the Zeeman splitting interacts with the exchange — correlation potential and the spin — orbit coupling. As Pd is on the border of ferromagnetism, calculations of the magnetization as a function of applied field are presented for a variety of exchange — correlation potentials and orbital effects, as well as for expanded crystals. At the experimental lattice constant no phase transition is found.

Message Passing Neural Networks for Partial Charge Assignment to Metal-Organic Frameworks

2020 ◽  
Author(s):  
Ali Raza ◽  
Arni Sturluson ◽  
Cory Simon ◽  
Xiaoli Fern
Keyword(s):  
Electronic Structure ◽  
Message Passing ◽  
Gas Adsorption ◽  
Metal Organic Frameworks ◽  
Computational Cost ◽  
Electronic Structure Calculations ◽  
High Fidelity ◽  
Partial Charges ◽  
Metal Organic ◽  
Structure Calculations

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>

scholarly journals Quantum HF/DFT-embedding algorithms for electronic structure calculations: Scaling up to complex molecular systems

2021 ◽  
Vol 154 (11) ◽  
pp. 114105
Author(s):  
Max Rossmannek ◽  
Panagiotis Kl. Barkoutsos ◽  
Pauline J. Ollitrault ◽  
Ivano Tavernelli
Keyword(s):  
Electronic Structure ◽  
Electronic Structure Calculations ◽  
Scaling Up ◽  
Molecular Systems ◽  
Structure Calculations
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