A 4H-SiC trench MOSFET structure with wrap N-type pillar for low oxide field and enhanced switching performance

An optimized silicon carbide(SiC)trench metal-oxide-semiconductor field-effect transistor(MOSFET)structure with side-wall p-type pillar(p-pillar)and wrap n-type pillar(n-pillar)in the n-drain was investigated by utilizing Silvaco TCAD simulations.The optimized structure mainly includes a p+buried region,a light n-type current spreading layer(CSL),a p-type pillar region,and a wrapping n-type pillar region at the right and bottom of the p-pillar.The improved structure is named as SNPPT-MOS.The side-wall p-pillar region could better relieve the high electric field around the p+shielding region and the gate oxide in the off-state mode.The wrapping n-pillar region and CSL can also effectively reduce the specific on-resistance(Ron,sp).As a result,the SNPPT-MOS structure exhibits that the figure of merit(Fo M)related to the breakdown voltage(V_(BR))and Ron,sp(V_(BR)^2R_(on,sp))of the SNPPT-MOS is improved by 44.5%,in comparison to that of the conventional trench gate SJ MOSFET(full-SJ-MOS).In addition,the SNPPT-MOS structure achieves a much fasterwitching speed than the full-SJ-MOS,and the result indicates an appreciable reduction in the switching energy loss.

Improved 4H-SiC UMOSFET with super-junction shield region

This article investigates an improved 4H-SiC trench gate metal–oxide–semiconductor field-effect transistor(MOSFET)(UMOSFET)fitted with a super-junction(SJ)shielded region.The modified structure is composed of two n-type conductive pillars,three p-type conductive pillars,an oxide trench under the gate,and a light n-type current spreading layer(NCSL)under the p-body.The n-type conductive pillars and the light n-type current spreading layer provide two paths to and promote the diffusion of a transverse current in the epitaxial layer,thus improving the specific on-resistance(R_(on,sp)).There are three p-type pillars in the modified structure,with the p-type pillars on both sides playing the same role.The p-type conductive pillars relieve the electric field(E-field)in the corner of the trench bottom.Two-dimensional simulation(silvaco TCAD)indicates that Ron,sp of the modified structure,and breakdown voltage(V_(BR))are improved by 22.2%and 21.1%respectively,while the maximum figure of merit(FOM=V_(BR)^(2)/R_(on,sp)) is improved by 79.0%.Furthermore,the improved structure achieves a light smaller low gate-to-drain charge(Q_(gd))and when compared with the conventional UMOSFET(conventional-UMOS),it displays great advantages for reducing the switching energy loss.These advantages are due to the fact that the p-type conductive pillars and n-type conductive pillars configured under the gate provide a substantial charge balance,which also enables the charge carriers to be extracted quickly.In the end,under the condition of the same total charge quantity,the simulation comparison of gate charge and OFF-state characteristics between Gaussdoped structure and uniform-doped structure shows that Gauss-doped structure increases the V_(BR)of the device without degradation of dynamic performance.

Spatial learning and memory deficits in young adult mice exposed to a brief intense noise at postnatal age

Noise pollution is a major hazardous factor to human health and is likely harmful for vulnerable groups such as pre-term infants under lifesupport system in an intensive care unit. Previous studies have suggested that noise exposure impairs children’s learning ability and cognitive performance and cognitive functions in animal models in which the effect is mainly attributed to the oxidant stress of noise on the cognitive brain. The potential role of noise induced hearing loss(NIHL), rather than the oxidant stress, has also been indicated by a depression of neurogenesis in the hippocampus long after a brief noise exposure, which produces only a tentative oxidant stress. It is not clear if noise exposure and NIHL during early development exerts a long term impact on cognitive function and neurogenesis towards adulthood. In the present study, a brief noise exposure at high sound level was performed in neonatal C57BL/6J mice(15 days after birth) to produce a significant amount of permanent hearing loss as proved 2 months after the noise. At this age, the noise-exposed animals showed deteriorated spatial learning and memory abilities and a reduction of hippocampal neurogenesis as compared with the control. The averaged hearing threshold was found to be strongly correlated with the scores for spatial learning and memory. We consider the effects observed are largely due to the loss of hearing sensitivity, rather than the oxidant stress, due to the long interval between noise exposure and the observations.

Low switching loss and increased short-circuit capability split-gate SiC trench MOSFET with p-type pillar

A split-gate SiC trench gate MOSFET with stepped thick oxide, source-connected split-gate(SG), and p-type pillar(ppillar) surrounded thick oxide shielding region(GSDP-TMOS) is investigated by Silvaco TCAD simulations. The sourceconnected SG region and p-pillar shielding region are introduced to form an effective two-level shielding, which reduces the specific gate–drain charge(Q_(gd,sp)) and the saturation current, thus reducing the switching loss and increasing the short-circuit capability. The thick oxide that surrounds a p-pillar shielding region efficiently protects gate oxide from being damaged by peaked electric field, thereby increasing the breakdown voltage(BV). Additionally, because of the high concentration in the n-type drift region, the electrons diffuse rapidly and the specific on-resistance(Ron,sp) becomes smaller.In the end, comparing with the bottom p~+ shielded trench MOSFET(GP-TMOS), the Baliga figure of merit(BFOM,BV~2/R_(on,sp)) is increased by 169.6%, and the high-frequency figure of merit(HF-FOM, R_(on,sp) × Q_(gd,sp)) is improved by310%, respectively.

Model design and structure research for integration system of energy, information and transportation networks based on ANP-fuzzy comprehensive evaluation

For lack of deep research on model, system structure and top-level design, the integrated system concept of energy, information and transportation networks fails to provide effective guidance for transferring the theory to practice. In this paper, with dispatching of energy flow and information flow as a focus, clean energy of wind power and solar power as carrier, battery charging & swapping station as medium and all kinds of transportation flows as entity, a five-in-one threenetwork integrated system model is built by full use of technologies of Internet of Vehicles(IOV) and Internet of things(IOT) to promote the innovative concept of three-network integration into practice, and provide a reference for future researches.

Vision Enhanced Generative Pre-trained Language Model for Multimodal Sentence Summarization

Multimodal sentence summarization(MMSS)is a new yet challenging task that aims to generate a concise summary of a long sentence and its corresponding image.Although existing methods have gained promising success in MMSS,they overlook the powerful generation ability of generative pre-trained language models(GPLMs),which have shown to be effective in many text generation tasks.To fill this research gap,we propose to using GPLMs to promote the performance of MMSS.Notably,adopting GPLMs to solve MMSS inevitably faces two challenges:1)What fusion strategy should we use to inject visual information into GPLMs properly?2)How to keep the GPLM′s generation ability intact to the utmost extent when the visual feature is injected into the GPLM.To address these two challenges,we propose a vision enhanced generative pre-trained language model for MMSS,dubbed as Vision-GPLM.In Vision-GPLM,we obtain features of visual and textual modalities with two separate encoders and utilize a text decoder to produce a summary.In particular,we utilize multi-head attention to fuse the features extracted from visual and textual modalities to inject the visual feature into the GPLM.Meanwhile,we train Vision-GPLM in two stages:the vision-oriented pre-training stage and fine-tuning stage.In the vision-oriented pre-training stage,we particularly train the visual encoder by the masked language model task while the other components are frozen,aiming to obtain homogeneous representations of text and image.In the fine-tuning stage,we train all the components of Vision-GPLM by the MMSS task.Extensive experiments on a public MMSS dataset verify the superiority of our model over existing baselines.