Structure, stability, charge transfer, chemical bonding, and spectroscopic properties of Ga atom-doped neutral Mg_n (n=2-12) clusters have been systematically investigated by CALYPSO and density functional theory. All cluster structures are based on "tetrahedral" and "yurt-like" growth except for GaMg2. The ground state isomer of GaMg with high symmetry strcture is predicted to be the best-fit candidate for the "magic" cluster because of its excellent stability. Natural bond orbital calculations reveal that Ga and Mg atoms play the role of electron acceptor and donor in all ground state isomers, while the orbitals in both Ga and Mg are sp-hybridized. Most importantly, chemical bonding studies based on atom-in-mole ular theory have shown that the lowest-energy state of GaMg₄ is so special in that it is not only the critical size for the appearance of Mg-Mg covalent bonds but also the only cluster that has both Ga-Mg covalent and non-covalent bonds. Finally, theoretical calculations of IR and Raman spectra of all ground state isomers indicate that the spectra of these clusters are observable in the low-frequency band, and thus they can be identified by spectroscopic experiments. Furthermore, the bond heterogeneity of the Ga-Mg in the GaMg₄ ground state isomer has also been specically investigated, includingfixed GaMg₄ structure with Mg atoms added in different directions as well as ab initio molecular dynamics sampling at different temperatures.

Stronger hydrophobic interactions result in more compact single-chain structures, elevating the tendency as well as the critical temperature of phase separation.

Using CALYPSO crystal search software, the structural growth mechanism, relative stability, charge transfer, chemical bonding and optical properties of AuMg_n (n = 2–12) nanoclusters were extensively investigated based on DFT. The shape development uncovers two interesting properties of AuMg_n nanoclusters contrasted with other doped Mg-based clusters, in particular, the planar design of AuMg₃ and the highly symmetrical cage-like of AuMg₉. The relative stability study shows that AuMg₁₀ has the robust local stability, followed by AuMg₉. In all nanoclusters, the charge is transferred from the Mg atoms to the Au atoms. Chemical bonding properties were confirmed by ELF analysis that Mg-Mg formed covalent bonds in nanoclusters larger than AuMg₃. Static polarizability and hyperpolarizability calculations strongly suggest that AuMg₉ nanocluster possesses interesting nonlinear optical properties. Boltzmann distribution weighted average IR and Raman spectroscopy studies at room temperature verify that these nanoclusters are identifiable by spectroscopic experiments. Finally, the average bond distance and average nearest neighbor distance were fully investigated.

基于第一性原理计算方法, 设计出了一种新型二维半导体材料TiO₂, 并进一步研究了其结构稳定性, 电子结构, 载流子迁移率和光学性质等. 二维TiO₂的形成能、声子谱、分子动力学、弹性常数表明, 二维TiO₂具有较好的动力学, 热力学和机械稳定性, 具备实验制备的条件, 且能够稳定存在于常温条件下. 电子结构分析表明, 二维TiO₂是一种间接带隙半导体, 在GGA+PBE和HSE06算法下的能隙分别为1.19 eV和2.76 eV, 其价带顶和导带底能级分别由Ti-3d和Ti-4s态电子构成, O原子的电子态在费米能级附近贡献很小, 主要分布在深处能级. 载流子迁移率显示, 二维TiO₂的迁移率比单层MoS₂要小, 其电子和空穴迁移率分别为31.09和36.29 cm²·V^–1·s^–1. 由于空穴迁移率和电子迁移率的各向异性, 电子-空穴复合率较低, 使得单层TiO₂的使用寿命更长, 光催化活性更好. 在应变调控下, 二维TiO₂的能隙发生明显响应, 以适用于各种半导体器件的需要. 半导体的带边势和光学性质显示, 在–5%—2%单/双轴应变下, 二维TiO₂能够光裂水制H₂, 在–5%—5%单/双轴应变下, 能够光裂水制O₂, H₂O₂和O₃等. 此外, 二维TiO₂对可见光和紫外光具有较高的吸收系数, 说明其在未来光电子器件和光催化材料领域有着潜在的应用前景.

采用基于密度泛函理论的第一性原理平面波赝势方法, 计算了单层GeTe、表面氢化及氟化单层GeTe的晶体结构、稳定性、电子结构和光学性质. 计算结果表明, 经过修饰后, GeTe的晶格常数、键角、键长增大, 且均具有较好的稳定性. 电子结构分析表明, 单层GeTe为间接带隙半导体, 全氢化修饰、全氟化修饰以及氢氟共修饰(F, Ge同侧; H, Te同侧)则转变为直接带隙半导体, 且修饰后的能隙均不同程度减小. 载流子有效质量表明, 全氢化、全氟化以及氢氟共修饰GeTe (F, Ge同侧; H, Te同侧)的有效质量减小, 其载流子迁移率增强. 带边势分析结果显示, 单层GeTe能够光裂解水制氢和析氧, 而修饰后的GeTe的价带带边势明显下移, 其氧化性明显增强, 能够光裂解水析O₂, H₂O₂, O₃以及OH·等产物. 光学性质表明, 修饰后的GeTe对可见光区和红、紫外区的光谱吸收效果明显增强, 表明其在光催化领域有着广阔的应用前景.

Liquid-liquid phase separation (LLPS) of proteins is an emerging field in the research of biophysics. Many intrinsically disordered proteins (IDPs) are known to have the ability to assemble via LLPS and to organize into protein-rich and dilute phases both in vivo and in vitro. Such a kind of phase separation of proteins plays an important role in a wide range of cellular processes, such as the formation of membraneless organelles (MLOs), signaling transduction, intracellular organization, chromatin organization, etc. In recent years, there appeared a great number of theoretical analysis, computational simulation and experimental research focusing on the physical principles of LLPS. In this article, the theoretical and computational simulation methods for the LLPS are briefly reviewed. To elucidate the physical principle of LLPS and to understand the phase behaviors of the proteins, biophysicists have introduced the concepts and theories from statistical mechanics and polymer sciences. Flory-Huggins theory and its extensions, such as mean-field model, random phase approximation (RPA) and field theory simulations, can conduce to understanding the phase diagram of the LLPS. To reveal the hidden principles in the sequence-dependent phase behaviors of different biomolecular condensates, different simulation methods including lattice models, off-lattice coarse-grained models, and all-atom simulations are introduced to perform computer simulations. By reducing the conformational space of the proteins, lattice models can capture the key points in LLPS and simplify the computations. In the off-lattice models, a polypeptide can be coarse-grained as connected particles representing repeated short peptide fragments. All-atom simulations can describe the structure of proteins at a higher resolution but consume higher computation-power. Multi-scale simulation may provide the key to understanding LLPS at both high computational efficiency and high accuracy. With these methods, we can elucidate the sequence-dependent phase behaviors of proteins at different resolutions. To sum up, it is necessary to choose the appropriate method to model LLPS processes according to the interactions within the molecules and the specific phase behaviors of the system. The simulations of LLPS can facilitate the comprehensive understanding of the key features which regulate the membraneless compartmentalization in cell biology and shed light on the design of artificial cells and the control of neurodegeneration.