US 12,347,707 B2
Semiconductor analysis system
Yudai Kubo, Tokyo (JP); Tsunenori Nomaguchi, Tokyo (JP); and Hiroyuki Chiba, Tokyo (JP)
Assigned to Hitachi High-Tech Corporation, Tokyo (JP)
Appl. No. 17/797,225
Filed by Hitachi High-Tech Corporation, Tokyo (JP)
PCT Filed Feb. 27, 2020, PCT No. PCT/JP2020/008056
§ 371(c)(1), (2) Date Aug. 3, 2022,
PCT Pub. No. WO2021/171490, PCT Pub. Date Sep. 2, 2021.
Prior Publication US 2023/0063192 A1, Mar. 2, 2023
Int. Cl. H01L 21/67 (2006.01); G05B 19/418 (2006.01); H01J 37/20 (2006.01); H01J 37/244 (2006.01); H01J 37/26 (2006.01); H01J 37/28 (2006.01); H01J 37/305 (2006.01)
CPC H01L 21/67276 (2013.01) [G05B 19/41875 (2013.01); H01J 37/20 (2013.01); H01J 37/244 (2013.01); H01J 37/265 (2013.01); H01J 37/28 (2013.01); H01J 37/305 (2013.01); G05B 2219/32368 (2013.01); H01J 2237/0473 (2013.01); H01J 2237/221 (2013.01); H01J 2237/24578 (2013.01); H01J 2237/2802 (2013.01); H01J 2237/31749 (2013.01)] 9 Claims
OG exemplary drawing
 
1. A semiconductor analysis system comprising:
a machining device that machines a semiconductor wafer to prepare a thin film sample for observation;
a transmission electron microscope device that acquires a transmission electron microscope image of the thin film sample;
a host control device that controls the machining device and the transmission electron microscope device, wherein the host control device evaluates the thin film sample based on the transmission electron microscope image, updates machining conditions based on an evaluation result of the thin film sample, and outputs the updated machining conditions to the machining device; and
wherein:
the machining device includes a scanning electron microscope device that acquires a scanning electron microscope image;
the host control device includes a determination unit that performs a first pass or fail determination process of machining end point detection for the thin film sample based on the transmission electron microscope image, a learning device that generates a learning model for performing the machining end point detection by comparing a first pass or fail determination result of the machining end point detection in the determination unit with the scanning electron microscope image, and a machining control unit;
the learning device uses the learning model to perform a second pass or fail determination process of the machining end point detection for the thin film sample based on the scanning electron microscope image; and
the machining control unit gives an instruction to the machining device to continue machining or end machining based on the second pass or fail determination result of the machining end point detection in the learning device.