scholarly journals Electronic Structure of AlP Under Pressure Using Semiempirical Method

2010 ◽  
Vol 3 ◽  
pp. 1-7 ◽  
Author(s):  
Hamad R. Jappor ◽  
Mudar A. Abdulsattar ◽  
Ahmed M. Abdul-lettif
Keyword(s):  
Electronic Structure ◽  
Semiempirical Method

scholarly journals Assessing Conformer Energies using Electronic Structure and Machine Learning Methods

2020 ◽  
Author(s):  
Dakota Folmsbee ◽  
Geoffrey Hutchison
Keyword(s):  
Machine Learning ◽  
Electronic Structure ◽  
Density Functional ◽  
Large Scale ◽  
Single Point ◽  
Semiempirical Method ◽  
Coupled Cluster ◽  
Scale Evaluation ◽  
Machine Learning Methods ◽  
Electronic Structure Methods

We have performed a large-scale evaluation of current computational methods, including conventional small-molecule force fields, semiempirical, density functional, ab initio electronic structure methods, and current machine learning (ML) techniques to evaluate relative single-point energies. Using up to 10 local minima geometries across ~700 molecules, each optimized by B3LYP-D3BJ with single-point DLPNO-CCSD(T) triple-zeta energies, we consider over 6,500 single points to compare the correlation between different methods for both relative energies and ordered rankings of minima. We find promise from current ML methods and recommend methods at each tier of the accuracy-time tradeoff, particularly the recent GFN2 semiempirical method, the B97-3c density functional approximation, and RI-MP2 for accurate conformer energies. The ANI family of ML methods shows promise, particularly the ANI-1ccx variant trained in part on coupled-cluster energies. Multiple methods suggest continued improvements should be expected in both performance and accuracy.

scholarly journals Assessing Conformer Energies using Electronic Structure and Machine Learning Methods

2020 ◽  
Author(s):  
Dakota Folmsbee ◽  
Geoffrey Hutchison
Keyword(s):  
Machine Learning ◽  
Electronic Structure ◽  
Density Functional ◽  
Large Scale ◽  
Single Point ◽  
Semiempirical Method ◽  
Coupled Cluster ◽  
Scale Evaluation ◽  
Machine Learning Methods ◽  
Electronic Structure Methods

We have performed a large-scale evaluation of current computational methods, including conventional small-molecule force fields, semiempirical, density functional, ab initio electronic structure methods, and current machine learning (ML) techniques to evaluate relative single-point energies. Using up to 10 local minima geometries across ~700 molecules, each optimized by B3LYP-D3BJ with single-point DLPNO-CCSD(T) triple-zeta energies, we consider over 6,500 single points to compare the correlation between different methods for both relative energies and ordered rankings of minima. We find promise from current ML methods and recommend methods at each tier of the accuracy-time tradeoff, particularly the recent GFN2 semiempirical method, the B97-3c density functional approximation, and RI-MP2 for accurate conformer energies. The ANI family of ML methods shows promise, particularly the ANI-1ccx variant trained in part on coupled-cluster energies. Multiple methods suggest continued improvements should be expected in both performance and accuracy.

scholarly journals DFT-based investigation of the electronic structure of a double-stranded AC B-DNA dim

2013 ◽  
Vol 16 ◽  
pp. 117-122
Author(s):  
Emerson Rengifo ◽  
Gustavo Murillo
Keyword(s):  
Electronic Structure ◽  
Density Functional ◽  
Computational Cost ◽  
Semiempirical Method ◽  
Basis Sets ◽  
Functional Theory ◽  
One Dimensional ◽  
Exchange Correlation ◽  
Dna Dodecamer ◽  
Low Computational Cost

Calculations of the electronic structure of a stacked dimmer sequence from the D(GCAAACGTTTGC)2 B-DNA dodecamer resolved in a PDB file 1HQ7 are performed within density functional theory. Seeking to understand the minimum level of theory that yields a reliable description for these systems, the basis sets 6-31g*, 6-31g*+BSSE, 6-311g*, 6-311g**, 6-311++g** along with the B3LYP and PBE0 exchange-correlation functionals were employed. These results are then used to implement a one dimensional model of long stacked systems to obtain a new semiempirical method that can be employed at low computational cost.

scholarly journals Assessing Conformer Energies using Electronic Structure and Machine Learning Methods

2020 ◽  
Author(s):  
Dakota Folmsbee ◽  
Geoffrey Hutchison
Keyword(s):  
Machine Learning ◽  
Electronic Structure ◽  
Density Functional ◽  
Large Scale ◽  
Single Point ◽  
Semiempirical Method ◽  
Coupled Cluster ◽  
Scale Evaluation ◽  
Machine Learning Methods ◽  
Electronic Structure Methods

We have performed a large-scale evaluation of current computational methods, including conventional small-molecule force fields, semiempirical, density functional, ab initio electronic structure methods, and current machine learning (ML) techniques to evaluate relative single-point energies. Using up to 10 local minima geometries across ~700 molecules, each optimized by B3LYP-D3BJ with single-point DLPNO-CCSD(T) triple-zeta energies, we consider over 6,500 single points to compare the correlation between different methods for both relative energies and ordered rankings of minima. We find promise from current ML methods and recommend methods at each tier of the accuracy-time tradeoff, particularly the recent GFN2 semiempirical method, the B97-3c density functional approximation, and RI-MP2 for accurate conformer energies. The ANI family of ML methods shows promise, particularly the ANI-1ccx variant trained in part on coupled-cluster energies. Multiple methods suggest continued improvements should be expected in both performance and accuracy.

EELS Measurement of the Local Electronic Structure of Copper Atoms Segregated to Aluminum Grain Boundaries

1996 ◽  
Vol 54 ◽  
pp. 342-343
Author(s):  
S.J. Splinter ◽  
J. Bruley ◽  
P.E. Batson ◽  
D.A. Smith ◽  
R. Rosenberg
Keyword(s):  
Electronic Structure ◽  
Grain Boundaries ◽  
Boundary Segregation ◽  
Thin Layers ◽  
Nominal Composition ◽  
Spatially Resolved ◽  
Service Lifetime ◽  
Heat Treated ◽  
Probe Size ◽  
Local Electronic Structure

It has long been known that the addition of Cu to Al interconnects improves the resistance to electromigration failure. It is generally accepted that this improvement is the result of Cu segregation to Al grain boundaries. The exact mechanism by which segregated Cu increases service lifetime is not understood, although it has been suggested that the formation of thin layers of θ-CuA12 (or some metastable substoichiometric precursor, θ’ or θ”) at the boundaries may be necessary. This paper reports measurements of the local electronic structure of Cu atoms segregated to Al grain boundaries using spatially resolved EELS in a UHV STEM. It is shown that segregated Cu exists in a chemical environment similar to that of Cu atoms in bulk θ-phase precipitates.Films of 100 nm thickness and nominal composition Al-2.5wt%Cu were deposited by sputtering from alloy targets onto NaCl substrates. The samples were solution heat treated at 748K for 30 min and aged at 523K for 4 h to promote equilibrium grain boundary segregation. EELS measurements were made using a Gatan 666 PEELS spectrometer interfaced to a VG HB501 STEM operating at 100 keV. The probe size was estimated to be 1 nm FWHM. Grain boundaries with the narrowest projected width were chosen for analysis. EDX measurements of Cu segregation were made using a VG HB603 STEM.

Electronic structure studies of conducting polymers by electron energy-loss spectroscopy

1996 ◽  
Vol 54 ◽  
pp. 160-161
Author(s):  
J. Fink
Keyword(s):  
Electronic Structure ◽  
Conducting Polymers ◽  
Conjugated Polymers ◽  
Electron Acceptors ◽  
Electron Donors ◽  
Light Emitting ◽  
One Dimensional ◽  
New Class ◽  
Electrical Conductivities ◽  
Electron Energy Loss

Conducting polymers comprises a new class of materials achieving electrical conductivities which rival those of the best metals. The parent compounds (conjugated polymers) are quasi-one-dimensional semiconductors. These polymers can be doped by electron acceptors or electron donors. The prototype of these materials is polyacetylene (PA). There are various other conjugated polymers such as polyparaphenylene, polyphenylenevinylene, polypoyrrole or polythiophene. The doped systems, i.e. the conducting polymers, have intersting potential technological applications such as replacement of conventional metals in electronic shielding and antistatic equipment, rechargable batteries, and flexible light emitting diodes.Although these systems have been investigated almost 20 years, the electronic structure of the doped metallic systems is not clear and even the reason for the gap in undoped semiconducting systems is under discussion.

Doping effects on the geometric and electronic structure of tin clusters

2019 ◽  
Vol 21 (44) ◽  
pp. 24478-24488 ◽  
Author(s):  
Martin Gleditzsch ◽  
Marc Jäger ◽  
Lukáš F. Pašteka ◽  
Armin Shayeghi ◽  
Rolf Schäfer
Keyword(s):  
Density Functional Theory ◽  
Electronic Structure ◽  
Density Functional ◽  
Beam Deflection ◽  
Functional Theory ◽  
Doping Effects ◽  
Depth Analysis ◽  
Trajectory Simulations

In depth analysis of doping effects on the geometric and electronic structure of tin clusters via electric beam deflection, numerical trajectory simulations and density functional theory.

A novel ligand with –NH2 and –COOH-decorated Co/Fe-based oxide for an efficient overall water splitting: dual modulation roles of active sites and local electronic structure

2020 ◽  
Vol 10 (18) ◽  
pp. 6266-6273
Author(s):  
Yalan Zhang ◽  
Zebin Yu ◽  
Ronghua Jiang ◽  
Jung Huang ◽  
Yanping Hou ◽  
...  
Keyword(s):  
Electronic Structure ◽  
Water Splitting ◽  
Energy Demand ◽  
Active Sites ◽  
Electrode Materials ◽  
Global Energy ◽  
Overall Water Splitting ◽  
Local Electronic Structure ◽  
Electrochemical Water Splitting

Excellent electrochemical water splitting with remarkable durability can provide a solution to satisfy the increasing global energy demand in which the electrode materials play an important role.

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