Si-Micromachined Knudsen Pumps for High Compression Ratio and High Flow Rate.

This dissertation focuses on Si-micromachined Knudsen pumps. Knudsen pumps exploit thermal transpiration that results from the free-molecular flow in non-isothermal channels. The absence of moving parts, without frictional loss and mechanical failure, provides significantly higher reliability. For a high compression ratio, 48 stages are cascaded in series in a single chip of 10.35 × 11.45 mm2 area. A five-mask, single-wafer process is used for monolithic integration of the designed Knudsen pump. The pressure levels of each stage are measured by integrated Pirani gauges. Using 1.35 W, the fabricated pumps evacuates the encapsulated cavities from 760 to 50 Torr and from 250 to 5 Torr. Multistage Knudsen pumps are further explored using a two-part architecture. To increase the compression ratio, 162 stages are serially cascaded. The two-part architecture uses 54 stages designed for the pressure range of 760-50 Torr, and 108 stages designed for lower pressures. This approach provides greater compression ratio and speed than using a uniform design for each stage in the 48-stage Knudsen pump. The design has a footprint of 12 × 15 mm2. Using 0.39 W, the evacuated chamber is reduced from 760 to 0.9 Torr, resulting in a compression ratio of 844. The vacuum levels were sustained beyond 37 days of continuous operation. The dynamic calibration of microfabricated Pirani gauges is explored for increasing pressure measurement accuracy in the 162-stage Knudsen pump. Test results demonstrated that dynamic calibration can be significantly more accurate than conventional static calibration when Pirani gauges are embedded deep within a microfluidic pathway. Si-micromachined single-stage Knudsen pumps are explored for generating high-flow rates. A high density of thermal transpiration flow channels is arrayed in parallel for combined pumping operation. A design with 0.4 × 106 parallel channels in a footprint of 16 × 20 mm2 generates a measured 211 sccm air flow at a pressure difference of 92 Pa, using 37.2 W. The low-temperature atomic layer deposition (ALD) of Al2O3 is investigated for vacuum seals in wafer-level vacuum packaging applications. The conformal coverage provided by ALD Al2O3 is shown to seal micromachined cavities. Lifetime tests extending out to 19 months are reported.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/102498/1/sdan_1.pd

A Si-micromachined 48-stage Knudsen pump for on-chip vacuum

This paper describes a thermal transpiration-driven multistage Knudsen pump for vacuum pumping applications. This type of pump relies upon the motion of gas molecules from the cold end to the hot end of a channel in which the flow is restricted to the free molecular or transitional regimes. To achieve a high compression ratio, 48 stages are cascaded in series in a single chip. A five-mask, single silicon wafer process is used for monolithic integration of the designed Knudsen pump. The pump has several monolithically integrated Pirani gauges to experimentally measure the vacuum pumping characteristics of the pump. It has a footprint of 10.35 × 11.45 mm 2 . For an input power of 1350 mW, the fabricated pump self-evacuates the encapsulated cavities from 760 to ≈50 Torr, resulting in a compression ratio of 15. It also pumps down from 250 to ≈5 Torr, resulting in a compression ratio of 50. Each integrated Pirani gauge requires ≈3.9 mW of power consumption, and its response is sufficiently sensitive in the operating pressure range of 760–1 Torr.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98610/1/0960-1317_22_10_105026.pd

Development on Deaf Support Application Based on Daily Sound Classification Using Image-based Deep Learning

According to statistics, the number of hearing-impaired persons among the disabled in Korea accounts for 27% of all persons with disabilities. However, there is insufficient support for the deaf and hard of hearing's protective devices and life aids compared to the large number. In particular, the hearing impaired misses much information obtained through sound and causes inconvenience in daily life. Therefore, in this paper, we propose a method to relieve the discomfort in the daily life of the hearing impaired. It analyzes sounds that can occur frequently and must be recognized in daily life and guide them to the hearing impaired through applications and vibration bracelets. Sound analysis was learned by using deep learning by converting sounds that often occur in daily life into the Mel-Spectrogram. The sound that actually occurs is recorded through the application, and then it is identified based on the learning result. According to the identification result, predefined alarms and vibrations are provided differently so that the hearing impaired can easily recognize it. As a result of the recognition of the four major sounds occurring in real life in the experiment, the performance showed an average of 85% and an average of 80% of the classification rate for mixed sounds. It was confirmed that the proposed method can be applied to real-life through experiments. Through the proposed method, the quality of life can be improved by allowing the hearing impaired to recognize and respond to sounds that are essential in daily life