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Lung Capacity01:47

Lung Capacity

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The air in the lungs is measured in volumes and capacities. Lung volume measures reflect the amount of air taken in, released, or left over after a lung function, like a single inhalation. Lung capacity measures are sums of two or more lung volume measures.
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State Space Representation01:27

State Space Representation

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The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
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A space truss is a three-dimensional counterpart of a planar truss. These structures consist of members connected at their ends, often utilizing ball-and-socket joints to create a stable and versatile framework. The space truss is widely used in various construction projects due to its adaptability and capacity to withstand complex loads.
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Respiratory Capacities01:24

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Respiratory capacities are crucial indicators of lung function, representing the maximum amount of air an individual's respiratory system can handle during various breathing phases.
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Transfer Function to State Space01:23

Transfer Function to State Space

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State-space representation is a powerful tool for simulating physical systems on digital computers, necessitating the conversion of the transfer function into state-space form. Consider an nth-order linear differential equation with constant coefficients, like those encountered in an RLC circuit. The state variables are selected as the output and its n−1 derivatives. Differentiating these variables and substituting them back into the original equation produces the state equations.
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State Space to Transfer Function01:21

State Space to Transfer Function

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The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
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Related Experiment Video

Updated: Jan 27, 2026

Synthesis, Cellular Delivery and In vivo Application of Dendrimer-based pH Sensors
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A High Full Well Capacity CMOS Image Sensor for Space Applications.

Woo-Tae Kim1, Cheonwi Park2, Hyunkeun Lee3

  • 1School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju 61005, Korea. wtkim@gist.ac.kr.

Sensors (Basel, Switzerland)
|March 31, 2019
PubMed
Summary

This study introduces a novel CMOS image sensor (CIS) pixel design that significantly boosts full well capacity (FWC) for space applications. The enhanced design achieves a high FWC and improved modulation transfer function (MTF) without compromising pixel area.

Keywords:
CMOS image sensorsmultiple charge transferradiation damage effectsspace applicationswide dynamic range

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Area of Science:

  • Electronics
  • Semiconductor Devices
  • Space Technology

Background:

  • CMOS image sensors (CIS) are crucial for space applications, but require high full well capacity (FWC) to handle varying light intensities.
  • Existing pixel designs often face limitations in FWC within constrained pixel areas, impacting performance in demanding environments.

Purpose of the Study:

  • To present a novel CIS pixel design that enhances FWC for space applications.
  • To analyze the impact of the new design on modulation transfer function (MTF) and radiation effects.
  • To demonstrate the feasibility of the proposed techniques through fabrication and testing.

Main Methods:

  • Integration of a Metal-Oxide-Semiconductor (MOS) capacitor within the pixel architecture.
  • Multiple charge transfer mechanism from photodiode to in-pixel capacitor based on light intensity.
  • Fabrication of the CIS using a 0.11 μm 1-poly 4-metal CIS process.
  • Evaluation of FWC, MTF, and radiation damage effects.

Main Results:

  • Achieved a high measured FWC of 103,448 electrons.
  • Demonstrated a 300% improvement in Modulation Transfer Function (MTF).
  • Successfully fabricated and tested the CIS with a 6.5 μm pixel pitch.

Conclusions:

  • The proposed pixel design effectively increases FWC in a limited area for space CIS.
  • The integration of an MOS capacitor and multiple charge transfer enhances light intensity handling.
  • The fabricated CIS shows significant improvements in FWC and MTF, suitable for space missions.