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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Stacking of Metal Chelates with Benzene: Can Dispersion‐Corrected DFT Be Used to Calculate Organic–Inorganic Stacking?
|
|---|---|
| Published in |
ChemPhysChem, January 2015
|
| DOI | 10.1002/cphc.201402589 |
| Pubmed ID | |
| Authors |
Dušan P. Malenov, Dragan B. Ninković, Snežana D. Zarić |
| Abstract |
CCSD(T)/CBS energies for stacking of nickel and copper chelates are calculated and used as benchmark data for evaluating the performance of dispersion-corrected density functionals for calculating the interaction energies. The best functionals for modeling the stacking of benzene with the nickel chelate are M06HF-D3 with the def2-TZVP basis set, and B3LYP-D3 with either def2-TZVP or aug-cc-pVDZ basis set, whereas for copper chelate the PBE0-D3 with def2-TZVP basis set yielded the best results. M06L-D3 with aug-cc-pVDZ gives satisfying results for both chelates. Most of the tested dispersion-corrected density functionals do not reproduce the benchmark data for stacking of benzene with both nickel (no unpaired electrons) and copper chelate (one unpaired electron), whereas a number of these functionals perform well for interactions of organic molecules. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 40% |
| Researcher | 4 | 27% |
| Professor | 1 | 7% |
| Unspecified | 1 | 7% |
| Student > Master | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 1 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 7 | 47% |
| Biochemistry, Genetics and Molecular Biology | 2 | 13% |
| Unspecified | 1 | 7% |
| Neuroscience | 1 | 7% |
| Unknown | 4 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 January 2015.
All research outputs
#20,674,485
of 25,394,764 outputs
Outputs from ChemPhysChem
#3,101
of 5,459 outputs
Outputs of similar age
#269,089
of 361,287 outputs
Outputs of similar age from ChemPhysChem
#45
of 106 outputs
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So far Altmetric has tracked 5,459 research outputs from this source. They receive a mean Attention Score of 2.2. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
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