Examining the Long-Range Effect in Very Long Graphene Nanoribbons: A First-Principles Study

The role of long-range effect on the modulation of the electronic structure of graphene nanoribbons has been little studied due to the limitations of existing theoretical and computational methods. By splitting a molecule top-down and calculating and jointing the Fock matrix of fragments, we developed a computational method suitable for large-size molecules with random doping and arbitrary geometry. Utilizing this method, we achieved the study of the effects of dopants and curvature on graphene nanoribbons (GNRs). It reveals that both dopants and curvature can change the charge distribution of GNRs, while the influence of dopants is more significant and can extend up to 1–3 nm. The electronic excitation properties of GNRs are also largely modified by the doping state or nonuniform curvature. Our findings provide not only a feasible approach for studying the electronic structure of large-size molecules but also the possibility to improve the properties of graphene-based materials by dopants and local curvature

Quantitatively Verifying the Results' Rationality for Farmland Quality Evaluation with Crop Yield, a Case Study in the Northwest Henan Province, China

<div><p>Evaluating the assessing results’ rationality for farmland quality (FQ) is usually qualitative and based on farmers and experts’ perceptions of soil quality and crop yield. Its quantitative checking still remains difficult and is likely ignored. In this paper, FQ in Xiuwu County, the Northwest Henan Province, China was evaluated by the gray relational analysis (GRA) method and the traditional analytic hierarchy process (AHP) method. The consistency rate of two results was analysed. Research focused on proposing one method of testing the evaluation results’ rationality for FQ based on the crop yield. Firstly generating a grade map of crop yield and overlying it with the FQ evaluation maps. Then analysing their consistency rate for each grade in the same spatial position. Finally examining the consistency effects and allowing for a decision on adopting the results. The results showed that the area rate consistency and matching evaluation unit numbers between the two methods were 84.68% and 87.29%, respectively, and the space distribution was approximately equal. The area consistency rates between crop yield level and FQ evaluation levels by GRA and AHP were 78.15% and 74.29%, respectively. Therefore, the verifying effects of GRA and AHP were near, good and acceptable, and the FQ results from both could reflect the crop yield levels. The evaluation results by GCA, as a whole, were slightly more rational than that by AHP.</p></div

Comparison of the FQ evaluation results based on GCA and yield grades.

<p>According to the comparison, there were some indentify status with different colours. Same indicated that the FQ grade area based on the GCA methods was the same as that of the yield level. Less indicated that the grade of the former was less than that of the latter. More indicated that the former was more than the latter. Abbreviations: FQ, Farmland Quality; GCA, gray correlation analysis.</p

Geographic location of study region and soil sampling sites.

<p>Geographic location of study region and soil sampling sites.</p

Correlation degree and weight of FQ evaluation indexes based on GCA in study site.

<p>Correlation degree and weight of FQ evaluation indexes based on GCA in study site.</p

Comparison of the evaluation results based on AHP and yield grades.

<p>According to the comparison, there were some indentify status with different colours. Same indicated that the FQ grade area based on the AHP methods was the same as that of the yield level. Less indicated that the grade of the former was less than that of the latter. More indicated that the former was more than the latter. Abbreviations: FQ, Farmland Quality; AHP, analytic hierarchy process.</p

Understanding the Phosphorylation Mechanism by Using Quantum Chemical Calculations and Molecular Dynamics Simulations

Phosphorylation is one of the most frequent post-translational modifications on proteins. It regulates many cellular processes by modulation of phosphorylation on protein structure and dynamics. However, the mechanism of phosphorylation-induced conformational changes of proteins is still poorly understood. Here, we report a computational study of three representative groups of tyrosine in ADP-ribosylhydrolase 1, serine in BTG2, and serine in Sp100C by using six molecular dynamics (MD) simulations and quantum chemical calculations. Added phosphorylation was found to disrupt hydrogen bond, and increase new weak interactions (hydrogen bond and hydrophobic interaction) during MD simulations, leading to conformational changes. Quantum chemical calculations further indicate that the phosphorylation on tyrosine, threonine, and serine could decrease the optical band gap energy (<i>E</i>_gap), which can trigger electronic transitions to form or disrupt interactions easily. Our results provide an atomic and electronic description of how phosphorylation facilitates conformational and dynamic changes in proteins, which may be useful for studying protein function and protein design

Level distribution map of FQ evaluations based on GCA in the study site.

<p>The different grades of FQ evaluations were shown with different colours. Abbreviations: FQ, Farmland Quality; GCA, gray correlation analysis.</p

Comparison of FQ results by GCA and AHP in the study site.

<p>According to the comparison, there were two indentify status with different colours. Same indicated that FQ evaluation levels by GCA and AHP method for some unites were coincident. Difference meant that FQ levels by two methods did not well agree. Abbreviations: FQ, Farmland Quality; GCA, gray correlation analysis; AHP, analytic hierarchy process.</p

Comparison of the FQ grades as evaluated by both methods with the crop yield grades.

<p>Comparison of the FQ grades as evaluated by both methods with the crop yield grades.</p