| Title |
The octet rule in chemical space: generating virtual molecules
|
|---|---|
| Published in |
Molecular Diversity, August 2017
|
| DOI | 10.1007/s11030-017-9775-2 |
| Pubmed ID | |
| Authors |
Rafel Israels, Astrid Maaß, Jan Hamaekers |
| Abstract |
We present a generator of virtual molecules that selects valid chemistry on the basis of the octet rule. Also, we introduce a mesomer group key that allows a fast detection of duplicates in the generated structures. Compared to existing approaches, our model is simpler and faster, generates new chemistry and avoids invalid chemistry. Its versatility is illustrated by the correct generation of molecules containing third-row elements and a surprisingly adept handling of complex boron chemistry. Without any empirical parameters, our model is designed to be valid also in unexplored regions of chemical space. One first unexpected finding is the high prevalence of dipolar structures among generated molecules. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 20% |
| United States | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 26% |
| Student > Ph. D. Student | 5 | 26% |
| Professor > Associate Professor | 2 | 11% |
| Student > Master | 2 | 11% |
| Student > Bachelor | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 3 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 7 | 37% |
| Physics and Astronomy | 3 | 16% |
| Mathematics | 2 | 11% |
| Engineering | 2 | 11% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 4 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 21 September 2017.
All research outputs
#13,364,855
of 23,881,329 outputs
Outputs from Molecular Diversity
#249
of 492 outputs
Outputs of similar age
#148,923
of 319,331 outputs
Outputs of similar age from Molecular Diversity
#2
of 7 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 492 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 49th percentile – i.e., 49% 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 319,331 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.