Abstract3D printing has the promising capability to fabricate engineered lattice structures with broadly tunable surface area and optimal geometries for maximizing structural and functional properties. This study characterizes the electrical conductivity of 3D lattices of varying size, structure, and porosity to guide additively manufactured electrode design in energy storage devices. Graph theory‐based calculations and experiments comparing the conductivity of multiple strut lattice structures and illustrating the scaling laws governing architectures with either coated or solid conductive struts are presented. The lightweight lattices explored here show higher conductivity than random foams that lack a periodic mesostructure. It is experimentally demonstrated that the 3D lattice type influences the specific capacity when employed in supercapacitors, outperforming 2D supercapacitor counterparts, and other 3D printed electrodes while allowing for optimization of the design for different energy storage applications. Additionally, it is shown that tuning the physical structure of the lattices allows for precise control over the electrical response to mechanical loading, as confirmed through experimental measurements. The lattice structure programs the electrodes’ mechanical stiffness, with higher relative density samples showing higher Young's modulus. These results can serve to guide the design of 3D printed electrodes in a variety of electrochemical and electromechanical device applications.

The movement of Cu in a HfO 2 -based resistive random access memory (RRAM) device is investigated in depth by first-principle calculations. Thermodynamics analysis shows that the dominant motion of Cu tends to be along the [001] orientation with a faster speed. The migration barriers along different routes are compared and reveal that the [001] orientation is the optimal migration route of Cu in HfO 2 , which is more favorable for Cu transportation. Furthermore, the preferable HfO 2 growth orientation along [100], corresponding to Cu migration along [001], is also observed. Therefore, it is proposed that the HfO 2 material should grow along [100] and the operating voltage should be applied along [001], which will contribute to the improvement of the response speed and the reduction of power consumption of RRAM.

In this paper, based on first‐principles calculations, we have carried out a comprehensive study of substitutional oxygen defects in hexagonal silicon nitride (β‐Si3N4). First of all, it is found that substitutional oxygens tend to form clusters at three different sites due to the intensive attractive interaction. By analyzing modified Bader charge and trap energy, we next discuss retention characteristic of the three clusters. The results manifest that all of the clusters are amphoteric defects with the ability to trap both electrons and holes. Moreover, every cluster is more powerful to trap holes, which indicates that oxygen clusters have a higher stability to hold holes than electrons. With regard to endurance characteristic, our studies reveal that the three clusters present differences after program/erase cycles, and then we explore the mechanism of endurance degeneration by nudged elastic band method (NEB). Taking full account of retention and endurance, we deem holes rather than electrons to be optimal to act as operational charge carriers for oxygen defects in Si3N4‐based charge trapping memories.

Based on density functional theory, the mechanisms for oxygen-driven unzipping of carbon nanotubes under electric field are presented. Under the control of external electric field, O adatoms will diffuse along the single-walled carbon nanotube from low potential to the high potential sites. The energy barrier of O adatoms diffusion gets lower while increasing the electric potential, thus enabling the O adatoms to diffuse to the higher potential sites more easily. And with quantities of O adatoms diffusing to the high potential sites, a linear epoxy chain is formed and the single-walled carbon nanotube will be unzipped into graphene nanoribbons automatically.

Based on first principle calculations, a comprehensive study of substitutional oxygen defects in hexagonal silicon nitride (ˇ-Si 3 N 4 / has been carried out. Firstly, it is found that substitutional oxygen is most likely to form clusters at three sites in Si 3 N 4 due to the intense attractive interaction between oxygen defects. Then, by using three analytical tools (trap energy, modified Bader analysis and charge density difference), we discuss the trap abilities of the three clusters. The result shows that each kind of cluster at the three specific sites presents very different abilities to trap charge carriers (electrons or holes): two of the three clusters can trap both kinds of charge carriers, confirming their amphoteric property; While the last remaining one is only able to trap hole carriers. Moreover, our studies reveal that the three clusters differ from each other in terms of endurance during the program/erase progress. Taking full account of capturing properties for the three oxygen clusters, including trap ability and endurance, we deem holes rather than electrons to be optimal to act as operational charge carriers for the oxygen defects in Si 3 N 4 -based charge trapping memories.