Graphene is attracting much attention in condensed matter physics and material science in the two-dimensional(2D) system due to its special structure, and mechanical and electronic properties. However, the lack of electronic bandgap and uncontrollable phase structure greatly limit its application in semiconductors, such as power conversion devices, optoelectronic devices, transistors, etc. During the past few decades, 2D transition metal dichalcogenides (TMDs) with much more phase structures have attracted intensive research interest in fundamental studies and practical applications for energy storage, as catalysts, and in piezoelectricity, energy harvesting, electronics, optoelectronic, and spintronics. The controllable phase transition also provides another degree of freedom to pave the way for more novel devices. In this review, we introduce the abundant phase structures of 2D-TMDs, including 2H, 1T, 1T’ and charge density waves, and highlight the corresponding attractive properties and applications of each phase. In addition, all the possible methods to trigger the phase transition in TMDs are systematically introduced, including strain engineering, electron doping, alloying, thermal, electric field, and chemical absorption. Finally, the outlook of future opportunities in TMD phase transitions and the corresponding challenges, including both the synthesis and applications, are also addressed.

Efficient navigation in complex flows is of crucial importance for robotic applications. This work presents a numerical study of the point-to-point navigation of a fish-like swimmer in a time-varying vortical flow with a hybrid method of deep reinforcement learning (DRL) and immersed boundary–lattice Boltzmann method (IB-LBM). The vortical flow is generated by placing four stationary cylinders in a uniform flow. The swimmer is trained to discover effective navigation strategies that could help itself to reach a given destination point in the flow field, utilizing only the time-sequential information of position, orientation, velocity and angular velocity. After training, the fish can reach its destination from random positions and orientations, demonstrating the effectiveness and robustness of the method. A detailed analysis shows that the fish utilizes highly subtle tail flapping to control its swimming orientation and take advantage of the reduced streamwise flow area to reach it destination, and in the same time avoiding entering the high flow velocity area.

This work presents a numerical study of the collective motion of two freely-swimming swimmers by a hybrid method of the deep reinforcement learning method (DRL) and the immersed boundary-lattice Boltzmann method (IB-LBM). An active control policy is developed by training a fish-like swimmer to swim at an average speed of 0.4 $L/T$ and an average orientation angle of 0${}^{\circ }$. After training, the swimmer is able to restore the desired swimming speed and orientation from moderate external perturbation. Then the control policy is adopted by two identical swimmers in the collective swimming. Stable side-by-side, in-line and staggered formations are achieved according to the initial positions. The stable side-by-side swimming area of the follower is concentrated to a small area left or right to the leader with an average distance of 1.35 L. The stable in-line area is concentrated to a small area about 0.25 L behind the leader. A detailed analysis shows that both the active control and passive self-organization play an important role in the emergence of the stable schooling formations, while the active control works for maintaining the speed and orientation in case the swimmers collide or depart from each other and the passive self-organization works for emerging a stable schooling configuration. The result supports the Lighthill conjecture and also highlights the importance of the active control.

For a long time, fish school swimming has attracted a great deal of attention in biological systems, as fish schools can have complex hydrodynamic effects on individuals. This work adopted a non-iterative, immersed boundary–lattice Boltzmann method (IB–LBM). A numerical simulation of two-dimensional three-degree-of-freedom self-propelled fish, in side-by-side, staggered, and triangle formations, was conducted by adjusting spacing and motion parameters. A comprehensive analysis of individual speed gains and energy efficiencies in these formations was carried out. Furthermore, an analysis of the hydrodynamic characteristics of fish schools was performed, using instantaneous vorticity profiles and pressure fields. Certain studies have shown that passive interactions between individuals cannot always bring hydrodynamic benefits. The swimming efficiency of side-by-side formations in the same phase gradually increases as the distance decreases, but it also brings certain burdens to individuals when the phases are different. This paper also shows that the roles of passive interactions, spacing, and deflections affect fish school subsystems differently. When the low-pressure areas created by a wake vortex act on one side of an individual’s body, the tail-end fish are good at gaining hydrodynamic benefits from it. This effect is not universal, and the degree to which individuals benefit from changes in exercise parameters varies. This study provides a theoretical basis for bioinspired robots, as well as providing certain insights into the mechanism of collective biological movement.

Using first-principles theory, we investigated the stability and feasibility on Mn-doped SnTe monolayer and the interactions of Mn-doped SnTe monolayer (Mn-SnTe) for the adsorption of toxic gases H₂S, SO₂, NO, NO₂ and Cl₂. The results show that the Mn-SnTe monolayer has a weak interaction for H₂S and strong adsorption energies of −1.840, −4.123, −2.954 and −3.578 eV for SO₂, NO, NO₂ and Cl₂, respectively. In addition, due to the high sensitivity of Mn-SnTe monolayer to adsorb SO₂ and Cl₂, the bandgaps of the developed systems are reduced by about 79.96% and 100%, respectively. The results indicate that the Mn-SnTe monolayer has a high sensitivity for the detection of SO₂ and Cl₂ gases. Our calculations provide a theoretical basis for the development of Mn-SnTe monolayer for potential applications as sensors or scavengers for toxic gases.

The adsorption behaviors of gas molecules such as Cl₂, CO, NO, NO₂ and SO₂ on MoSSe/GaN, as well as their adsorption energies, charge transfer and adsorption distances are investigated based on the first-principles calculation. The large adsorption energies of Cl₂, NO, NO₂ and SO₂ on MoSSe/GaN indicate that the gas molecules have strong interaction forces with MoSSe/GaN. Probing the changes in the electronic structure, the adsorption of NO and NO₂ on MoSSe/GaN introduces magnetism into their systems and reduces the band gaps. The magnetism mainly originates from the O atoms in NO and NO₂, while the decrease of the band gap is due to the hybridization of orbitals near the bottom of the conduction band and the top of the valence band with the p orbitals of Ga atoms in MoSSe/GaN. This suggests that MoSSe/GaN can be applied to detect NO and NO₂ gas molecules and has potential as a semiconductor gas sensor for these gases.