First-principles studies on the electronic and contact properties of monolayer Ga2STe-metal contacts.

Monolayer (ML) Janus III-VI compounds have attracted the use of multiple competitive platforms for future-generation functional electronics, including non-volatile memories, field effect transistors, and sensors. In this work, the electronic and interfacial properties of ML Ga2STe-metal (Au, Ag, Cu, and Al) contacts are systematically investigated using first-principles calculations combined with the non-equilibrium Green's function method. The ML Ga2STe-Au/Ag/Al contacts exhibit weak electronic orbital hybridization at the interface, while the ML Ga2STe-Cu contact exhibits strong electronic orbital hybridization. The Te surface is more conducive to electron injection than the S surface in ML Ga2STe-metal contact. Quantum transport calculations revealed that when the Te side of the ML Ga2STe is in contact with Au, Ag and Cu electrodes, p-type Schottky contacts are formed. When in contact with the Al electrode, an n-type Schottky contact is formed with an electron SBH of 0.079 eV. When the S side of ML Ga2STe is in contact with Au and Al electrodes, p-type Schottky contacts are formed, and when it is in contact with Ag and Cu electrodes, n-type Schottky contacts are formed. Our study will guide the selection of appropriate metal electrodes for constructing ML Ga2STe devices.

Optimizing ultrashort pulse in fiber laser based on artificial intelligence algorithm.

Ultrashort pulses, characterized by their short pulse duration, diverse spectral content, and high peak power, are widely used in fields including laser processing, optical storage, biomedical sciences, and laser imaging. The complex, highly-nonlinear process of ultrashort pulse evolution within fiber lasers is influenced by numerous aspects such as dispersion, loss, gain, and nonlinear effects. Traditionally, the split-step Fourier transforms method is employed for simulating ultrashort pulses in fiber lasers, which involves traversing multiple parameters within the fiber to attain the pulse's optimal state. The simulation is a significantly time-consuming process. Here, we use a neural network model to fit and predict the impact of multiple parameters on the pulse characteristics within fiber lasers, enabling parameter optimization through genetic algorithms to determine the optimal pulse duration, pulse energy, and peak power. Integrating artificial intelligence algorithms simplifies the acquisition of optimal pulse parameters and enhances our understanding of multiple parameters' impact on the pulse characteristics. The investigation of ultrashort pulse optimization based on artificial intelligence holds immense potential for laser design.

Mutations influence the conformational dynamics of the GDP/KRAS complex.

Mutations near allosteric sites can have a significant impact on the function of KRAS. Three specific mutations, K104Q, G12D/K104Q, and G12D/G75A, which are located near allosteric positions, were selected to investigate the molecular mechanisms behind mutation-induced influences on the activity of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations followed by the principal component analysis (PCA) were performed to improve the sampling of conformational states. The results revealed that these mutations significantly alter the structural flexibility, correlated motions, and dynamic behavior of the switch regions that are essential for KRAS binding to effectors or regulators. Furthermore, the mutations have a significant impact on the hydrogen bonding interactions between GDP and the switch regions, as well as on the electrostatic interactions of magnesium ions (Mg2+) with these regions. Our results verified that these mutations strongly influence the binding of KRAS to its effectors or regulators and allosterically regulate the activity. We believe that this work can provide valuable theoretical insights into a deeper understanding of KRAS function.Communicated by Ramaswamy H. Sarma.