Zijing Lin

Exploration of tetrahedral structures in silicate cathodes using a motif-network scheme.

Using a motif-network search scheme, we studied the tetrahedral structures of the dilithium/disodium transition metal orthosilicates A2MSiO4 with A = Li or Na and M = Mn, Fe or Co. In addition to finding all previously reported structures, we discovered many other different tetrahedral-network-based crystal structures which are highly degenerate in energy. These structures can be classified into structures with 1D, 2D and 3D M-Si-O frameworks. A clear trend of the structural preference in different systems was revealed and possible indicators that affect the structure stabilities were introduced. For the case of Na systems which have been much less investigated in the literature relative to the Li systems, we predicted their ground state structures and found evidence for the existence of new structural motifs.

First-principles study on core-level spectroscopy of arginine in gas and solid phases.

First-principles simulations have been performed for near-edge X-ray absorption fine-structure (NEXAFS) spectra of neutral arginine at different K-edges in the solid phase as well as X-ray photoelectron spectra (XPS) of neutral, deprotonated, and protonated arginines in the gas phase. Influences of the intra- and intermolecular hydrogen bonds (HBs) and different charge states have been carefully examined to obtain useful structure-property relationships. Our calculations show a noticeable difference in the NEXAFS/XPS spectra of the canonical and zwitterionic species that can be used for unambiguously identifying the dominant form in the gas phase. It is found that the deprotonation/protonation always results in red/blue shifts of several electronvolts for the core binding energies (BEs) at all edges. The normal hydrogen bond Y-H···X (X, Y = N, O) can cause a blue/red shift of ca. 1 eV to the core BEs of the proton acceptor X/donor Y, while the weak C-H···Y hydrogen bond may also lead to a weak red shift (less than 1 eV) of the C1s BEs. Moreover, the influence of intermolecular interactions in the solid state is reflected as a broadening in the σ* region of the NEXAFS spectra at each edge, while in the π* region, these interactions lead to a strengthening or weakening of individual transitions from different carbons, although no evident visual change is found in the resolved total spectra. Our results provide a better understanding of the influences of the intra- and intermolecular forces on the electronic structure of arginine.

Point defect weakened thermal contraction in monolayer graphene

We investigate the thermal expansion behaviors of monolayer graphene and three configurations of graphene with point defects, namely the replacement of one carbon atom with a boron or nitrogen atom, or of two neighboring carbon atoms by boron-nitrogen atoms, based on calculations using first-principles density functional theory. It is found that the thermal contraction of monolayer graphene is significantly decreased by point defects. Moreover, the corresponding temperature for negative linear thermal expansion coefficient with the maximum absolute value is reduced. The cause is determined to be point defects that enhance the mechanical strength of graphene and then reduce the amplitude and phonon frequency of the out-of-plane acoustic vibration mode. Such defect weakening of graphene thermal contraction will be useful in nanotechnology to diminish the mismatching or strain between the graphene and its substrate.

Local Structures and Chemical Properties of Deprotonated Arginine

The potential energy surface of gaseous deprotonated arginine has been systematically investigated by first principles calculations. At the B3LYP/6-31G(d) level, apart from the identification of several stable local structures, a new global minimum is located which is about 6.56 kJ/mol more stable than what has been reported. The deprotonated arginine molecule has two distinct forms with the deprotonation at the carboxylate group (COO−). These two forms are bridged by a very high energy barrier and possess very different IR spectral profiles. Our calculated proton dissociation energy and gas-phase acidity of arginine molecule are found to be in good agreement with the corresponding experimental results. The predicted geometries, dipole moments, rotational constants, vertical ionization energies and IR spectra of low energy conformers will be useful for future experimental measurements.

Gas Phase Conformations of Tetrapeptide Glycine-Phenylalanine-Glycine-Glycine

Systematic search of the potential energy surface of tetrapeptide glycine-phenylalanine-glycine-glycine (GFGG) in gas phase is conducted by a combination of PM3, HF and BHandHLYP methods. The conformational search method is described in detail. The relative electronic energies, zero point vibrational energies, dipole moments, rotational constants, vertical ionization energies and the temperature dependent conformational distributions for a number of important conformers are obtained. The structural characteristics of these conformers are analyzed and it is found that the entropic effect is a dominating factor in determining the relative stabilities of the conformers. The measurements of dipole moments and some characteristic IR mode are shown to be effective approaches to verify the theoretical prediction. The structures of the low energy GFGG conformers are also analyzed in their connection with the secondary structures of proteins. Similarity between the local structures of low energy GFGG conformers and the α-helix is discussed and many β- and γ-turn local structures in GFGG conformers are found.

A genetic algorithm encoded with the structural information of amino acids and dipeptides for efficient conformational searches of oligopeptides

The genetic algorithm (GA) is an intelligent approach for finding minima in a highly dimensional parametric space. However, the success of GA searches for low energy conformations of biomolecules is rather limited so far. Herein an improved GA scheme is proposed for the conformational search of oligopeptides. A systematic analysis of the backbone dihedral angles of conformations of amino acids (AAs) and dipeptides is performed. The structural information is used to design a new encoding scheme to improve the efficiency of GA search. Local geometry optimizations based on the energy calculations by the density functional theory are employed to safeguard the quality and reliability of the GA structures. The GA scheme is applied to the conformational searches of Lys, Arg, Met‐Gly, Lys‐Gly, and Phe‐Gly‐Gly representative of AAs, dipeptides, and tripeptides with complicated side chains. Comparison with the best literature results shows that the new GA method is both highly efficient and reliable by providing the most complete set of the low energy conformations. Moreover, the computational cost of the GA method increases only moderately with the complexity of the molecule. The GA scheme is valuable for the study of the conformations and properties of oligopeptides.

Structural Information-Based Method for the Efficient and Reliable Prediction of Oligopeptide Conformations

Predictions of structures of biomolecules are challenging due to the high dimensionalities of the potential energy surfaces (PESs) involved. Reducing the necessary PES dimensionality is helpful for improving the computational efficiency of all relevant structure prediction methods. For that purpose, a systematic analysis of the backbone dihedral angles (DAs) in the low energy conformations of amino acids, di-, tri-, and tetrapeptides is performed. The analysis reveals that the DAs can be represented by a set of discretized values. Moreover, there are rules limiting the combinations of neighboring DA states. The DA combination rules are used to formulate a path matrix scheme for locating the low energy conformations of peptides. Comparing with the full DA combinations, the PES dimensionality in the path matrix method is reduced by a factor of 2.5n, where n is the number of amino acid residues in a peptide. The path matrix method is validated by applications to find the conformations of representative tri-, tetra-, and pentapeptides and comparison with the best literature results. All the tests show that the path matrix method is very efficient and highly reliable by producing the best search results for the low energy peptide conformations.

A scheme for the generation of Fe–P networks to search for low-energy LiFePO4 crystal structures

Herein we present a network generation scheme to explore the structural diversity of LiFePO4, which is an important cathode material in Li-ion batteries. With our scheme, networks of Fe and P atoms were initially constructed as the backbone structures using structural motifs for the FePx and FePx configurations, obtained from existing structural databases. Then, O atoms were added, resulting in the formation of PO4 tetrahedra and different types of Fe–O polyhedra. Finally, Li atoms were inserted into the vacancies within the generated FePO4 structures. We searched structures with FeO4, FeO5, or FeO6 polyhedra (unit cell with sizes of up to 4 formula units) and obtained ∼8 times more low-energy structures through our database than through existing databases. Furthermore, using our more comprehensive structural database, we unveiled a number of rules for identifying low-energy structures. These improved results complement the existing databases and are valuable for further research on structural transformations in similar materials by changing lithium or sodium cation populations.

Tuning thermal expansions of zinc oxide sheets by varying the layer thickness

Employing density functional theory and Gruneisen formalism, the layer dependence of zinc oxide (ZnO) sheet thermal expansion coefficients (TECs) is investigated. The monolayer ZnO sheet contracts significantly across the entire range of temperatures investigated. The negative TEC with maximum absolute value is determined, which implies that the monolayer ZnO sheets thermal contraction is more remarkable than those of many other 2D atomic layers, such as graphenes negative TEC with maximum absolute value . The bilayer ZnO sheet, similar to the monolayer sheet, contracts with increasing temperature, but its negative TEC absolute value is much smaller. The trilayer ZnO sheet contracts at low temperature, and expands at high temperature, with relatively low absolute values of TECs. The thermal contraction behaviour disappears in four- and five-layer ZnO sheets. These two sheets expand with increasing temperature. The maximum TEC of the five-layer ZnO sheet, , is determined at 1100 K, the maximum temperature investigated.

A random forest learning assisted “divide and conquer” approach for peptide conformation search

Computational determination of peptide conformations is challenging as it is a problem of finding minima in a high-dimensional space. The “divide and conquer” approach is promising for reliably reducing the search space size. A random forest learning model is proposed here to expand the scope of applicability of the “divide and conquer” approach. A random forest classification algorithm is used to characterize the distributions of the backbone φ-ψ units (“words”). A random forest supervised learning model is developed to analyze the combinations of the φ-ψ units (“grammar”). It is found that amino acid residues may be grouped as equivalent “words”, while the φ-ψ combinations in low-energy peptide conformations follow a distinct “grammar”. The finding of equivalent words empowers the “divide and conquer” method with the flexibility of fragment substitution. The learnt grammar is used to improve the efficiency of the “divide and conquer” method by removing unfavorable φ-ψ combinations without the need of dedicated human effort. The machine learning assisted search method is illustrated by efficiently searching the conformations of GGG/AAA/GGGG/AAAA/GGGGG through assembling the structures of GFG/GFGG. Moreover, the computational cost of the new method is shown to increase rather slowly with the peptide length.