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X Demographics
Mendeley readers
Attention Score in Context
| Title |
1H and 13C NMR scaling factors for the calculation of chemical shifts in commonly used solvents using density functional theory
|
|---|---|
| Published in |
Journal of Computational Chemistry, May 2014
|
| DOI | 10.1002/jcc.23638 |
| Pubmed ID | |
| Authors |
Gregory K Pierens |
| Abstract |
Calculation of NMR chemical shifts and coupling constants using quantum mechanical calculations [density functional theory (DFT)], has become a very popular tool for the determination of conformation and the assignment of stereochemistry within a molecule. We present the scaling factors (linear regression parameters) from 10 DFT methods for 10 commonly used NMR solvents using the same set of reference compounds. The results were compared with the corresponding gas-phase calculations to assess the inclusion of the polarizable continuum model for solvent effects. |
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 % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 110 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | <1% |
| India | 1 | <1% |
| Serbia | 1 | <1% |
| Unknown | 107 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 24% |
| Researcher | 16 | 15% |
| Student > Master | 10 | 9% |
| Student > Bachelor | 9 | 8% |
| Professor | 9 | 8% |
| Other | 19 | 17% |
| Unknown | 21 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 65 | 59% |
| Agricultural and Biological Sciences | 5 | 5% |
| Biochemistry, Genetics and Molecular Biology | 2 | 2% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 2% |
| Physics and Astronomy | 2 | 2% |
| Other | 5 | 5% |
| Unknown | 29 | 26% |
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 23 May 2014.
All research outputs
#22,029,081
of 24,577,646 outputs
Outputs from Journal of Computational Chemistry
#2,008
of 2,153 outputs
Outputs of similar age
#199,394
of 231,203 outputs
Outputs of similar age from Journal of Computational Chemistry
#42
of 42 outputs
Altmetric has tracked 24,577,646 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,153 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 231,203 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.