• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.11 s.353
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• pp.48-57
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• 2006

This work describes a 12b 200KHz 0.52mA $0.47mm^2$ algorithmic ADC for sensor applications such as motor controls, 3-phase power controls, and CMOS image sensors simultaneously requiring ultra-low power and small size. The proposed ADC is based on the conventional algorithmic architecture with recycling techniques to optimize sampling rate, resolution, chip area, and power consumption. The input SHA with eight input channels for high integration employs a folded-cascode architecture to achieve a required DC gain and a sufficient phase margin. A signal insensitive 3-D fully symmetrical layout with critical signal lines shielded reduces the capacitor and device mismatch of the MDAC. The improved switched bias power-reduction techniques reduce the power consumption of analog amplifiers. Current and voltage references are integrated on the chip with optional off-chip voltage references for low glitch noise. The employed down-sampling clock signal selects the sampling rate of 200KS/s or 10KS/s with a reduced power depending on applications. The prototype ADC in a 0.18um n-well 1P6M CMOS technology demonstrates the measured DNL and INL within 0.76LSB and 2.47LSB. The ADC shows a maximum SNDR and SFDR of 55dB and 70dB at all sampling frequencies up to 200KS/s, respectively. The active die area is $0.47mm^2$ and the chip consumes 0.94mW at 200KS/s and 0.63mW at 10KS/s at a 1.8V supply.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.5
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• pp.80-88
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• 2020

With the issuance of one-week fine dust emergency reduction measures in March 2019, the public's anxiety about fine dust is increasingly growing. In order to assess the application of air purifying plant-based bio-filters to public facilities, this study presented a method for measuring pollutant reduction effects by creating an indoor environment for continuous discharge of particle pollutants and conducted basic studies to verify whether indoor air quality has improved through the system. In this study conducted in a lecture room in spring, the background concentration was created by using mosquito repellent incense as a pollutant one hour before monitoring. Then, according to the schedule, the fine dust reduction capacity was monitored by irrigating for two hours and venting air for one hour. PM₁₀, PM_2.5, and temperature & humidity sensors were installed two meters front of the bio-filters, and velocity probes were installed at the center of the three air vents to conduct time-series monitoring. The average face velocity of three air vents set up in the bio-filter was 0.38±0.16 m/s. Total air-conditioning air volume was calculated at 776.89±320.16㎥/h by applying an air vent area of 0.29m×0.65m after deducing damper area. With the system in operation, average temperature and average relative humidity were maintained at 21.5-22.3℃, and 63.79-73.6%, respectively, which indicates that it satisfies temperature and humidity range of various conditions of preceding studies. When the effects of raising relatively humidity rapidly by operating system's air-conditioning function are used efficiently, it would be possible to reduce indoor fine dust and maintain appropriate relative humidity seasonally. Concentration of fine dust increased the same in all cycles before operating the bio-filter system. After operating the system, in cycle 1 blast section (C-1, β=-3.83, β=-2.45), particulate matters (PM₁₀) were lowered by up to 28.8% or 560.3㎍/㎥ and fine particulate matters (PM_2.5) were reduced by up to 28.0% or 350.0㎍/㎥. Then, the concentration of find dust (PM₁₀, PM_2.5) was reduced by up to 32.6% or 647.0㎍/㎥ and 32.4% or 401.3㎍/㎥ respectively through reduction in cycle 2 blast section (C-2, β=-5.50, β=-3.30) and up to 30.8% or 732.7㎍/㎥ and 31.0% or 459.3㎍/㎥ respectively through reduction in cycle 3 blast section (C-3, β=5.48, β=-3.51). By referring to standards and regulations related to the installation of vegetation bio-filters in public facilities, this study provided plans on how to set up objective performance evaluation environment. By doing so, it was possible to create monitoring infrastructure more objective than a regular lecture room environment and secure relatively reliable data.