17 research outputs found
Clean BN encapsulated 2D FETs with lithography compatible contacts
Device passivation through ultraclean hexagonal BN encapsulation is proven
one of the most effective ways for constructing high-quality devices with
atomically thin semiconductors that preserves the ultraclean interface quality
and intrinsic charge transport behavior. However, it remains challenging to
integrate lithography compatible contact electrodes with flexible distributions
and patterns. Here, we report the feasibility in straightforwardly integrating
lithography defined contacts into BN encapsulated 2D FETs, giving rise to
overall device quality comparable to the state-of-the-art results from the
painstaking pure dry transfer processing. Electronic characterization on FETs
consisting of WSe and MoS channels reveals an extremely low scanning
hysteresis of ca. 2 mV on average, a low density of interfacial charged
impurity of ca. cm, and generally high charge mobilities over
cmVs at low temperatures. The overall
high device qualities verify the viability in directly integrating lithography
defined contacts into BN encapsulated devices to exploit their intrinsic charge
transport properties for advanced electronics.Comment: 17 pages, 4 figure
Investigation on Internal Short Circuit Identification of Lithium-Ion Battery Based on Mean-Difference Model and Recursive Least Square Algorithm
Electric vehicles powered by lithium-ion batteries take advantages for urban transportation. However, the safety of lithium-ion battery needs to be improved. Self-induced internal short circuit of lithium-ion batteries is a serious problem which may cause battery thermal runaway. Accurate and fast identification of internal short circuit is critical, while difficult for lithium-ion battery management system. In this study, the influences of the parameters of significance test on the performance of an algorithm for internal short circuit identification are evaluated experimentally. The designed identification is based on the mean-difference model and the recursive least square algorithm. First, the identification method is presented. Then, two characteristic parameters are determined. Subsequently, the parameters of the significance calculation are optimized based on the measured data. Finally, the effectiveness of the method for the early stage internal short circuit detection is studied by an equivalent experiment. The results indicate that the detection time can be shortened significantly via a proper configuration of the parameters for the significance test
Transcriptome profiling of the initial segment and proximal caput of mouse epididymis
BackgroundThe proximal region of the mouse epididymis plays a pivotal role in sperm transport, sperm maturation, and male fertility. Several studies have focused on segment-dependent gene expression of the mouse epididymis through high-throughput sequencing without the precision of the microdissection.Methods and resultsHerein, we isolated the initial segment (IS) and proximal caput (P-caput) by physical microdissection using an Lcn9-cre; Rosa26tdTomato mouse model. We defined the transcriptome changes of caput epididymis by RNA sequencing (RNA-seq), which identified 1,961 genes that were abundantly expressed in the IS and 1,739 genes that were prominently expressed in the P-caput. In addition, we found that many differentially expressed genes (DEGs) were predominantly or uniquely expressed in the epididymis and region-specific genes were highly associated with transport, secretion, sperm motility, fertilization, and male fertility.ConclusionThus, this study provides an RNA-seq resource to identify region-specific genes in the caput epididymis. The epididymal-selective/specific genes are potential targets for male contraception and may provide new insights into understanding segment-specific epididymal microenvironment-mediated sperm transport, maturation, and male fertility
Rotor Temperature Safety Prediction Method of PMSM for Electric Vehicle on Real-Time Energy Equivalence
The load capacity of the permanent magnet synchronous motor is limited by the rotor temperature, and the excessive temperature of the rotor will bring potential thermal safety problems of the system. Therefore, the accurate prediction of the rotor temperature of the permanent magnet synchronous motor for the electric vehicle is crucial to improve the motor performance and system operation safety. This paper studied the heating mechanism and the energy flow path of the motor and built the heat energy conversion model of the stator and rotor. The real-time algorithm to predict the rotor temperature was constructed based on the dissipative energy conservation of the stator of the motor rotor temperature. And the prediction method of the initial rotor temperature is fitted using the experimental results when the system is powered on. Finally, the test platform was set up to validate the rotor temperature accuracy. The results show that the motor rotor temperature estimation error under the dynamic operating condition is within ±5. The research provides a solution to improve the performance and thermal safety of the permanent magnet synchronous motor for electric vehicles
ROTOR STRENGTH ANALYSIS AND LIFE CALCULATION OF HEV MOTOR
The interference fit between HEV motor rotor shaft and dynamo sheets was discussed in this paper. Assembly stress was analyzed and fatigue life was predicted by CAE method to study the motor rotor’s structural reliability. Comparison with the Von Mises stress results under different assembling methods shows,proper use of interference fit can reduce the stress fluctuation of matching components in deferent rotational speeds. Deeply research proves that interference fit in rotational part’s radial direction can obviously improve the fatigue performance if high stress fluctuation caused by centrifugal force exists
Experimental Study on Storage and Maintenance Method of Ni-MH Battery Modules for Hybrid Electric Vehicles
This paper investigates the performance changes of nickel−metal hydride (Ni-MH) battery modules for hybrid electric vehicles (HEVs) using different storage and maintenance methods. The effects of charge−discharge mode, maintenance period, rest time, charge rate, and storage state of charge (SOC) on the storage performance of Ni-MH battery modules are studied. Based on the experimental results and engineering application requirements, this paper proposes some important recommendations and methods for storage and maintenance of Ni-MH battery modules for HEVs. The experimental results show that, compared with the six benchmark methods, the proposed storage and maintenance method provides superior storage and maintenance outcomes and significantly saves maintenance time