Nitrogen pair − hydrogen complexes in ZnO and p-type doping.

2012 ◽  
Vol 1394 ◽  
Author(s):  
Adisak Boonchun ◽  
Walter R. L. Lambrecht ◽  
Jiraroj T-Thienprasert ◽  
Sukit Limpijumnong
Keyword(s):  
Electronic Structure ◽  
Electronic Structure Calculations ◽  
Defect Level ◽  
Hybrid Functional ◽  
Defect Complexes ◽  
P Type ◽  
Structure Calculations

ABSTRACTElectronic structure calculations using the Heyd-Scuseria-Ernzerhof (HSE) hybrid functional are presented for NO-pair complexes with and without hydrogen to test the hypothesis that such defect complexes could lead to shallower levels than for isolated NO and hence p-type doping. The H is found to bind strongly to one of the N in the pair and removes thecorresponding defect level from the gap but the second N’s polaronic defect level in the gap remains deep.

Theoretical Search for p-Type Dopants in Mg2X (X= Si, Ge) Semiconductors for Thermoelectricity

2012 ◽  
Vol 194 ◽  
pp. 266-271 ◽  
Author(s):  
Janusz Toboła ◽  
Piotr Zwolenski ◽  
Stanisław Kaprzyk
Keyword(s):  
Electronic Structure ◽  
Seebeck Coefficient ◽  
Fermi Level ◽  
Density Of States ◽  
Electronic Structure Calculations ◽  
Potential Approximation ◽  
Calculated Density ◽  
Self Consistent ◽  
P Type ◽  
Structure Calculations

Electronic structure calculations of doped Mg2(Si-Ge) semiconductors were performed by the charge self-consistent Korringa-Kohn-Rostoker method with the coherent potential approximation (KKR-CPA) in order to search for p-type impurities. It was predicted that Li and Na (located on Mg site) as well as B, Ru, Mo and W (located on Si site) are expected to behave as hole donors in Mg2(Si-Ge). Using the calculated density of states in doped Mg2Si in the vicinity of the Fermi level, the linear term of thermopower was also estimated from the simplified Mott's formula. The RT Seebeck coefficient may range from 120μV/K (Li) to almost 300μV/K (Ru) at the 1% content of doped impurities.

First-principles studies of a two-dimensional electron gas at the interface of polar/polar LaAlO3/KNbO3 superlattices

2019 ◽  
Vol 21 (15) ◽  
pp. 8046-8053 ◽  
Author(s):  
Le Fang ◽  
Chen Chen ◽  
Yali Yang ◽  
Yabei Wu ◽  
Tao Hu ◽  
...  
Keyword(s):  
Electronic Structure ◽  
First Principles ◽  
Electron Gas ◽  
Electronic Structure Calculations ◽  
Two Dimensional ◽  
Dimensional Electron ◽  
Two Dimensional Electron Gas ◽  
Dimensional Electron Gas ◽  
P Type ◽  
Structure Calculations

We explored the possibility of producing a two-dimensional electron gas (2DEG) in polar/polar (LaAlO3)m/(KNbO3)n perovskite superlattices that have N type and P type interfaces using the first-principles electronic structure calculations.

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

scholarly journals Scaling up electronic structure calculations on quantum computers: The frozen natural orbital based method of increments

2021 ◽  
Vol 155 (3) ◽  
pp. 034110
Author(s):  
Prakash Verma ◽  
Lee Huntington ◽  
Marc P. Coons ◽  
Yukio Kawashima ◽  
Takeshi Yamazaki ◽  
...  
Keyword(s):  
Electronic Structure ◽  
Electronic Structure Calculations ◽  
Scaling Up ◽  
Quantum Computers ◽  
Natural Orbital ◽  
Structure Calculations
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