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Mendeley readers
Attention Score in Context
| Title |
An improved approach for evaluating the semicrystalline lamellae of starch granules by synchrotron SAXS
|
|---|---|
| Published in |
Carbohydrate Polymers, December 2016
|
| DOI | 10.1016/j.carbpol.2016.12.002 |
| Pubmed ID | |
| Authors |
Binjia Zhang, Fengwei Xie, David K. Wang, Siming Zhao, Meng Niu, Dongling Qiao, Shanbai Xiong, Fatang Jiang, Jie Zhu, Long Yu |
| Abstract |
A fitting method combined with a linear correlation function was developed as an improved approach for the SAXS analysis of the semicrystalline lamellae of starch granules. Using a power-law function with two Gaussian plus Lorentz functions, the SAXS pattern was resolved into sub-patterns of the net lamellar peak and the power-law scattering plus scattering background (PL+B). The ratio of the net lamellar peak area (Apeak) to the total scattering area (Atotal) was proposed equal to the proportion of the lamellae within the starch granule (PSL). Along with this fitting method, we obtained a better profile of linear correlation function, with the elimination of the interference of non-lamellar amorphous starch (i.e., amorphous growth rings). Then, we could accurately calculate the lamellar parameters, e.g., PSL, the thicknesses of semicrystalline (d), crystalline (dc) and amorphous (da) lamellae, and the volume fraction (φc) of crystalline lamellae within semicrystalline lamellae. Quantitative analysis revealed that PSL was positively correlated with the crystallinity (Xc) of starch. It was confirmed that the distribution of lamellar thickness was more important than the starch botanical origin in affecting the validity of the developed fitting method. We also proposed a criterion to test the validity of the proposed method. Specifically, the total SAXS pattern should be mostly tangent to the profile of PL+B at a high q tail (close to 0.2Å(-1)). |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 42 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 33% |
| Researcher | 7 | 17% |
| Unspecified | 3 | 7% |
| Student > Doctoral Student | 2 | 5% |
| Student > Bachelor | 2 | 5% |
| Other | 5 | 12% |
| Unknown | 9 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 17% |
| Chemical Engineering | 6 | 14% |
| Materials Science | 5 | 12% |
| Chemistry | 4 | 10% |
| Unspecified | 3 | 7% |
| Other | 5 | 12% |
| Unknown | 12 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 12 December 2016.
All research outputs
#16,048,318
of 25,374,917 outputs
Outputs from Carbohydrate Polymers
#3,241
of 5,157 outputs
Outputs of similar age
#237,040
of 416,046 outputs
Outputs of similar age from Carbohydrate Polymers
#36
of 56 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,157 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 35th percentile – i.e., 35% 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 416,046 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.