Characterization of electrostatic discharge threshold voltage of phase-shift mask reticle

A reticle is a stencil used in lithography process for forming integrated circuit (IC) on silicon substrate. It consists of a thin (100 nm) coating of masking metallic patterned (features) with critical dimension (CD) of nanometers on a thicker quartz substrate. The features can be damaged by electrostatic discharge (ESD) when exposed to the environment electrostatic charge and caused deformed IC and eventually device difunctional. Semiconductor equipment materials industry (SEMI) standard established the allowable electrostatic charge on reticle based on the characterization of ESD threshold voltage on binary reticle. However, there is another type of reticle which is phase-shift mask (PSM), has not been characterized for its ESD threshold voltage. A direct current (DC) voltage is applied directly to the structures with CD of 80 nm, 110 nm, and 160 nm. The surface current is recorded at all levels of stress from 1 to 100 V. The current–voltage (IV) curve and physical inspection results for each cell are then reviewed and classified. The results yielded which no electric field induced migration (EFM) defect and breakdown voltage occurred at any of the structures. The cathode’s metal work function has been identified as the factor that influences the PSM reticle ESD threshold voltage.

Fully Isolated Quad-Port Electric Energy Routing Converter with Medium- and High-Voltage Grid Connection Capability

Aiming at the demand for medium- and high-voltage port access capability in energy router, this study proposes a quad-port DC/DC converter topology scheme based on modular multilevel converter (QP-M2DC). Compared with the traditional multiterminal energy routing converter, it has the advantages of high modularity, strong flexibility, and high power density. In addition, for the modular structure on the medium- and high-voltage sides, this study proposes a narrow phase-shift cyclic modulation strategy, which reduces the system need for voltage balance control and simplifies the overall system control. This study comprehensively introduces and analyses the QP-M2DC topology, working principle, high-frequency link equivalent, and power characteristics, then establishes an equivalent model of system control, and proposes a control scheme for a multiterminal energy routing converter. Finally, a simulation model of the system is established through PLECS, and the simulation results show that in such a narrow phase-shift modulation strategy, the proposed topology can have stable operation in a variety of patterns, reduce the capacitance, and achieve better voltage balance at the same time. The experimental results show the converter efficiency of up to 97.8%. It further shows the superiority of the proposed topology structure and the correctness and effectiveness of the proposed control schemes.

Interaction between photoperiod and variation in circadian rhythms in tomato

Many biological processes follow circadian rhythmicity and are controlled by the circadian clock. Predictable environmental changes such as seasonal variation in photoperiod can modulate circadian rhythms, allowing organisms to adjust to the time of the year. Modification of circadian clocks is especially relevant in crops to enhance their cultivability in specific regions by changing their sensibility to photoperiod. In tomato, the appearance of mutations in EMPFINDLICHER IM DUNKELROTEN LICHT 1 (EID1, Solyc09g075080) and NIGHT LIGHT-INDUCIBLE AND CLOCK-REGULATED GENE 2 (LNK2, Solyc01g068560) during domestication delayed its circadian rhythms, and allowed its expansion outside its equatorial origin. Here we study how variation in circadian rhythms in tomato affects its perception of photoperiod. To do this, we create near isogenic lines carrying combinations of wild alleles of EID1 and LNK2 and perform transcriptomic profiling under two different photoperiods. We observe that EID1, but not LNK2, has a large effect on the tomato transcriptome and its response to photoperiod. This large effect of EID1 is likely a consequence of the global phase shift elicited by this gene in tomato's circadian rhythms.

A simple mass oscillator metasurface design with linear phase shift

In this paper, a simple mass oscillator metasurface is designed, which can regulate the phase shift of flexural wave covering 0-2π by adjusting the number of mass oscillators on the connecting bar. Based on the forced vibration theory, there is a simple approximately linear relationship between the number and phase shift of mass oscillators, which can more intuitively and accurately predict the phase of different number of mass oscillators, and then realize the metasurface design of mass oscillators with different requirements. Therefore, arbitrary regulation of flexural waves, such as abnormal refraction, beam focusing, and self-acceleration, can be realized by reasonably arranging the number of mass oscillators. The results show that the proposed metasurface can be greatly simplified both in the establishment of phase shift relation and in the fabrication of structure configuration, and will have broad application potential in the engineering field.

A Deep Reinforcement Learning Approach to IRS-assisted MU-MIMO Communication Systems

<div>The deep reinforcement learning (DRL)-based deep deterministic policy gradient (DDPG) framework is proposed to solve the joint optimization of the IRS phase-shift matrix and the precoding matrix in an IRS-assisted multi-stream multi-user MIMO communication.<br></div><div><br></div><div>The combination of multiple-input multiple-output(MIMO) communications and intelligent reflecting surfaces(IRSs) is foreseen as a key enabler of beyond 5G (B5G) and 6Gsystems. In this work, we develop an innovative deep reinforcement learning (DRL)-based approach to the joint optimization of the MIMO precoders and the IRS phase-shift matrices that is proved to be efficient in high dimensional systems. The proposed approach is termed deep deterministic policy gradient (DDPG)and maximizes the sum rate of an IRS-assisted multi-stream(MS) multi-user MIMO (MU-MIMO) system by learning the best matrix configuration through online trial-and-error interactions. The proposed approach is formulated in terms of continuous state and action spaces, and a sum-rate-based reward function. The computational complexity is reduced by using artificial neural networks (ANNs) for function approximations and it is shown that the proposed solution scales better than other state-of-the-art methods, while reaching a competitive performance.<br></div>