1. A method for fabricating a back-side illuminated image sensor, comprising:
providing a semiconductor substrate having a front surface and a back surface;
forming a plurality of transistors, metal interconnects, and metal pads on the front surface of the substrate;
bonding a supporting layer to the front surface of the substrate;
thinning-down the semiconductor substrate from the back surface;
clearing-out a region of the substrate from the back surface that covers a fine alignment mark by performing registration from the back surface and using a global alignment mark as a reference; and
processing the back surface of the substrate by performing registration from the back surface and using the fine alignment mark as a reference.
2. The method of claim 1, wherein the semiconductor substrate is silicon.
3. The method of claim 1, wherein the semiconductor substrate is a silicon-on-insulator arrangement.
4. The method of claim 1, wherein the semiconductor substrate is an epitaxial silicon arrangement.
5. The method of claim 1, wherein the global alignment mark is formed on the front surface of the substrate by at least a 1X reticle pattern.
6. The method of claim 1, wherein the fine alignment mark is formed on the front surface of the substrate by at least a 4X reticle pattern.
7. The method of claim 1, wherein the fine alignment mark is a mirror-image type alignment or overlay mark.
8. The method of claim 7, wherein the fine alignment mark comprises a structure selected from the group consisting of: metal contact, metal pad, deep trench, and polysilicon.
9. The method of claim 8, wherein providing the substrate includes forming the fine alignment mark with the metal contact and polysilicon structure adjacent to a shallow trench isolation (STI) structure.
10. The method of claim 1, wherein the supporting layer is a transparent glass.
11. The method of claim 10, wherein performing registration from the back surface of the substrate is by using infrared light through the transparent glass and optically aligning the fine alignment mark with a mirror-image type reticle pattern.
12. The method of claim 1, wherein the supporting layer is a silicon wafer.
13. The method of claim 12, wherein performing registration from the back surface of the substrate is by using visible light through the silicon wafer and optically aligning the fine alignment mark with a mirror-image type reticle pattern.
14. The method of claim 1, further comprising filling and leveling the cleared-out region of the substrate with an organic material.
15. The method of claim 14, wherein the organic material is a positive photoresist.
16. The method of claim 14, wherein the organic material is a negative photoresist.
17. The method of claim 1, wherein processing the back surface of the substrate further comprises:
forming a first, second, and third doped regions within an active region of the substrate;
forming a red, green, and blue color filter on the back surface of the substrate and aligned with the first, second, and third doped regions, respectively; and
forming a microlens over the color filter.
18. A method for fabricating a semiconductor device, comprising:
providing a semiconductor substrate having a front side and a backside;
forming a plurality of transistors, metal interconnects, and metal pads at the front side of the substrate;
bonding a supporting layer to the front side of the substrate;
thinning-down the semiconductor substrate from the backside;
performing a first registration from the backside with a global alignment mark disposed at the front side to etch a portion of the substrate from the backside that covers a fine alignment mark disposed at the front side; and
performing a second registration from the backside with the fine alignment mark to process the backside of the substrate.
19. The method of claim 18, further comprising leveling the etched portion of the substrate with a photoresist material.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A computer-readable storage medium embodying computer program instructions for execution by a computer, the computer program instructions adapting a computer to diagnose an adaptive system operatively coupled to external systems wherein the adaptive system is controlled by a state machine, the computer program instructions comprising:
reading a plurality of expected state machine sequences;
recording a state machine sequence from the state machine;
selecting, from the plurality of expected state machine sequences, a selected expected state machine sequence matching the state machine sequence; and
determining the status of the adaptive system based on the selected expected state machine sequence.
2. The computer program instructions according to claim 1, comprising:
normalizing the plurality of expected state machine sequences based on a sample frequency of the state machine sequence.
3. The computer program instructions according to claim 2, comprising:
matching a selected expected state machine sequence to the state machine sequence using an approximate string matching algorithm.
4. The computer program instructions according to claim 3, comprising:
obtaining adaptive data from the adaptive system; and
determining the status of the external systems using the adaptive data.
5. A computer-readable storage medium embodying computer program instructions for execution by a computer, the computer program instructions adapting a computer to diagnose a real-time system controlled by a state machine, the computer program instructions comprising:
reading a plurality of expected state machine sequences;
recording a state machine sequence from the state machine;
selecting from the plurality of expected state machine sequences a selected expected state machine sequence that matches the state machine sequence; and
determining the status of the real-time system based on the selected expected state machine sequence.
6. The computer program instructions according to claim 5, comprising:
normalizing the plurality of expected state machine sequences based on a sample frequency of the state machine sequence.
7. The computer program instructions according to claim 6, comprising:
matching a selected expected state machine sequence to the state machine sequence using an approximate string matching algorithm.
8. A data processing system adapted to diagnose an adaptive system operatively coupled to external systems in which the adaptive system is controlled by a state machine, comprising:
a processor; and
a memory operatively coupled to the processor and having program instructions stored therein, the processor executing the program instructions, the program instructions comprising
reading a plurality of expected state machine sequences,
recording a state machine sequence from the state machine,
selecting from the plurality of expected state machine sequences a selected expected state machine sequence that matches the state machine sequence, and
determining the status of the adaptive system based on the selected expected state machine sequence.
9. The data processing system according to claim 8, wherein the program instructions comprises normalizing the plurality of expected state machine sequences based on a sample frequency of the state machine sequence.
10. The data processing system according to claim 9, wherein the program instructions comprises matching a selected expected state machine sequence to the state machine sequence using an approximate string matching algorithm.
11. The data processing system according to claim 10, wherein the program instructions comprises
obtaining adaptive data from the adaptive system, and
determining the status of the external systems using the adaptive data.
12. A data processing system adapted to diagnose a real-time system controlled by a state machine, comprising:
a processor; and
a memory operatively coupled to the processor and having program instructions stored therein, the processor being operable to execute the program instructions, the program instructions comprising
reading a plurality of expected state machine sequences,
recording a state machine sequence from the state machine,
selecting from the plurality of expected state machine sequences a selected expected state machine sequence that matches the state machine sequence, and
determining the status of the real-time system based on the selected expected state machine sequence.
13. The data processing system according to claim 12, wherein the program instructions comprises normalizing the plurality of expected state machine sequences based on a sample frequency of the state machine sequence.
14. The data processing system according to claim 13, wherein the program instructions comprises matching a selected expected state machine sequence to the state machine sequence using an approximate string matching algorithm.
15. The data processing system according to claim 14, wherein the state machine sequence is recorded by the state machine.