In this paper, the electronic structure and stability of the intrinsic, B-, N-, Si-, S-doped graphene are studied based on first-principles calculations of density functional theory. Firstly, the intrinsic, B-, N-, Si-, S-doped graphene structures are optimized, and then the forming energy, band structure, density of states, differential charge density are analyzed and calculated. The results show that B- and Si-doped systems are p-type doping, while N is n-type doping. By comparing the forming energy, it is found that N atoms are more easily doped in graphene. In addition, for B-, N-, Si-doped systems, it is found that the doping atoms will open the band gap, leading to a great change in the band structure of the doping system. Finally, we systematically study the optical properties of the different configurations. By comparison, it is found that the order of light sensitivity in the visible region is as follows: S-doped> Si-doped> pure > B-doped > N-doped. Our results will provide theoretical guidance for the stability and electronic structure of non-metallic doped graphene.

Blends of cyanate ester and phthalonitrile–polyhedral oligomeric silsesquioxane copolymers were prepared, and their cure behavior and properties were compared via differential scanning calorimetry (DSC) analysis, thermogravimetric (TG) analysis, dynamic mechanical analysis, Fourier-transform far-infrared (FTIR) spectroscopy, and rheometric studies. The copolymer blends showed high chemical reactivity, low viscosity, and good thermal stability (TG temperatures were above 400 °C). The glass-transition temperature of the blends increased by at least 140 °C compared to cyanate ester resin. The blends are suitable for preparing carbon-fiber-reinforced composite materials via a winding process and a prepreg lay-up process with a molding technique. The FTIR data showed that the polymerization products contained triazine-ring structures that were responsible for the superior thermal properties.

Monolayer transition metal dichalcogenides (mTMDs) possess a direct band gap and strong PL emission that is highly sensitive to doping level and interfaces, laying the foundation for investigating the contact between mTMD and metal via PL spectroscopy. Currently, electrical methods have been utilized to measure the contact resistance (R_C), but they are complicated, time-consuming, high-cost and suffer from inevitable chemical disorders and Fermi level pinning. In addition, previously reported contact resistances comprise both Schottky barrier and tunnel barrier components. Here, we report a simple, rapid and low-cost method to study the tunnel barrier dominated contact resistance of mTMD based junctions through PL spectroscopy. These junctions are free from chemical disorders and Fermi level pinning. Excluding the Schottky barrier component, solely tunnel barrier dominated contact resistances of 1 L MoSe₂/Au and 1 L MoSe₂/graphene junctions were estimated to be 147.8 Ω μm and 54.9 Ω μm, respectively. Density functional theory (DFT) simulations revealed that the larger R_C of the former was possibly due to the existence of intrinsic effective potential difference (Φ_barrier) between mTMD and metal. Both junctions exhibit an increasing tendency of R_C as temperature decreases, which is probably attributed to the thermal expansion coefficient (TEC) mismatch-triggered interlayer spacing (d) increase and temperature-induced doping. Remarkably, a significant change of R_C was observed in 1 L MoSe₂/Au junctions, which is possibly ascribed to the changes of their orbital overlaps. Our results open new avenues for exploring fundamental metal–semiconductor contact principles and constructing high-performance devices.

Graphene has attracted significant interest due to its unique properties. Herein, we built an adsorption structure selection workflow based on a density functional theory (DFT) calculation and machine learning to provide a guide for the interfacial properties of graphene. There are two main parts in our workflow. One main part is a DFT calculation routine to generate a dataset automatically. This part includes adatom random selection, modeling adsorption structures automatically, and a calculation of adsorption properties. It provides the dataset for the second main part in our workflow, which is a machine learning model. The inputs are atomic characteristics selected by feature engineering, and the network features are optimized by a genetic algorithm. The mean percentage error of our model was below 35%. Our routine is a general DFT calculation accelerating routine, which could be applied to many other problems. An attempt on graphene/magnesium composites design was carried out. Our predicting results match well with the interfacial properties calculated by DFT. This indicated that our routine presents an option for quick-design graphene-reinforced metal matrix composites.

Dilute magnetic semiconductors (DMSs), such as (In, Mn)As and (Ga, Mn)As prototypes, are limited to III–V semiconductors with Curie temperatures ( T _c ) far from room temperature, thereby hindering their wide application. Here, one kind of DMS based on perovskite niobates is reported. BaM _x Nb _{(1− x )} O _{3− δ} ( M = Fe, Co) powders are prepared by the composite-hydroxide-mediated method. The addition of M elements endows BaM _x Nb _{(1− x )} O _{3− δ} with local ferromagnetism. The tetragonal BaCo _x Nb _{(1− x )} O _{3− δ} nanocrystals can be obtained by Co doping, which shows strong saturation magnetization ( M _sat ) of 2.22 emu g ⁻¹ , a remnant magnetization ( M _r ) of 0.084 emu g ⁻¹ and a small coercive field ( H _c ) of 167.02 Oe at room temperature. The ab initio calculations indicate that Co doping could lead to a 64% local spin polarization at the Fermi level ( E _F ) with net spin DOS of 0.89 electrons eV ⁻¹ , this result shows the possibility of maintaining strong ferromagnetism at room temperature. In addition, the trade-off effect between the defect band absorption and ferromagnetic properties of BaM _x Nb _{(1− x )} O _{3− δ} is verified experimentally and theoretically.

We study the spin-orbit interaction of two-dimensional electron/hole gas (2DEGs/2DHGs) on quasi-2D potassium niobates (KNs) via first-principles calculations. The strong surface polarity changes the free surface states from 2DEGs to 2DHGs. The in-plane dipole maintained on 2D models leads to giant Zeeman-type spin splitting, as high as 566 meV for the (001)_c facet KN and 1.21 eV for the (111)_c facet KN. The thickness-dependent Zeeman-type spin splitting shows a linear relation with respect to 1/r, while the corresponding in-plane polarization quantum has a linear relation of 1/(2^0.5)with respect to a decrease in thickness. Interestingly, the 2DHGs with molecular-like orbital character is solely constituted by O 2p states, showing logic switchable behavior at extremely thin samples with enormous Zeeman-type splitting that can switch between insulator and conductor by opposite spin polarization.