Charged particle ray device and cross-sectional shape estimation program

1. A charged particle ray device for irradiating a sample with a charged particle ray, comprising:

a charged particle source that emits the charged particle ray;

a detector that detects a charged particle generated by irradiating the charged particle ray on the sample and outputs a detection signal indicating an intensity of the charged particle;

an energy discriminator that discriminates the charged particle according to the energy of the charged particle before the detector detects the charged particle;

a storage unit that stores the detection signal output by the detector for a reference sample as a reference pattern,

wherein the charged particle ray device is configured to:

estimate a cross-sectional shape of the sample using the detection signal output by the detector;

acquire the detection signal for each of different discrimination conditions of the energy discriminator, and

estimate the cross-sectional shape of the sample by comparing the detection signal acquired for each of the discrimination conditions and the reference pattern.

2. The charged particle ray device according to claim 1 ,

wherein the reference pattern describes, for each position in a depth direction of the reference sample, a position of an edge portion of a cross-sectional shape of the reference sample,

wherein the energy discriminator is configured to selectively discriminate the charged particle obtained from a specific position in the depth direction of the sample according to the discrimination conditions,

wherein the charged particle ray device acquires the detection signal for each of the different discrimination conditions, thereby acquiring the position of the edge portion of the cross-sectional shape of the sample for each position in the depth direction of the sample corresponding to the discrimination conditions, and

wherein the charged particle ray device compares the position of the edge portion of the cross-sectional shape of the reference sample with the position of the edge portion of the cross-sectional shape of the sample for each position in the depth direction of the sample, thereby estimating the cross-sectional shape of the sample.

3. The charged particle ray device according to claim 1 ,

wherein the charged particle ray device:

acquires, as the reference pattern, a change amount in which a deflection amount of the charged particle ray changes by changing an acceleration voltage of the charged particle ray for each position in a depth direction of the sample,

for each different acceleration voltage of the charged particle ray, acquires the position of the edge portion of the cross-sectional shape of the sample for each position in the depth direction of the sample, and

compares, for each position in the depth direction of the sample, the change amount described by the reference pattern with the position of the edge portion of the cross-sectional shape of the sample obtained for each of the different acceleration voltages, thereby estimating the cross-sectional shape of the sample.

4. The charged particle ray device according to claim 1 ,

wherein the reference pattern describes a potential distribution of a surface of the reference sample when the reference sample having no cavity therein is charged,

wherein the energy discriminator is configured to selectively discriminate the charged particle generated from a position having a specific potential on the surface of the sample according to the discrimination conditions, and

wherein the charged particle ray device estimates, on the surface of the sample, the position of the cavity existing inside the sample by comparing the potential distribution described by the reference pattern with the detection signal for each of the discrimination conditions.

5. The charged particle ray device according to claim 4 ,

wherein the storage unit stores a difference between a potential at a position where the cavity is projected on the surface of the sample and a potential at a position other than the projected position on the surface of the sample as cavity size data described for each size in a depth direction of the cavity, and

wherein the charged particle ray device estimates the size in the depth direction of the cavity existing inside the sample by comparing the difference described by the cavity size data with the detection signal for each of the discrimination conditions.

6. The charged particle ray device according to claim 4 ,

wherein the sample has a hole,

wherein the charged particle ray device further includes a deflector that deflects the charged particle ray, and

wherein the deflector irradiates the charged particle ray to the bottom of the hole by deflecting the charged particle ray and tilting an incident angle at which the charged particle ray enters the sample.

7. The charged particle ray device according to claim 1 ,

wherein the charged particle source irradiates the sample with the charged particle ray to generate a potential difference in a depth direction of the sample,

wherein the reference pattern describes a deflection amount by which the charged particle ray is deflected by a potential difference between the surface and the bottom of the reference sample, and

wherein the charged particle ray device estimates the cross-sectional shape of the sample by comparing the amount of deflection of the charged particle beam with the amount of deflection described by the reference pattern.

8. The charged particle ray device according to claim 1 ,

wherein the charged particle ray device generates an image representing the cross-sectional shape of the sample, and

wherein the charged particle ray device further includes a display unit that displays an image of the cross-sectional shape of the sample.

9. The charged particle ray device according to claim 8 ,

wherein the charged particle ray device calculates a deflection amount of the charged particle ray using an acceleration voltage of the charged particle ray,

wherein the charged particle ray device calculates a range of the acceleration voltage at which the charged particle ray can reach the bottom of the sample using the deflection amount and the size of the sample in a depth direction, and

wherein the display unit displays a range of the acceleration voltage calculated by the charged particle ray device.

10. The charged particle ray device according to claim 8 ,

wherein the charged particle ray device estimates a three-dimensional shape of the sample by estimating the cross-sectional shape of the sample for each position in a depth direction of the sample, and

wherein the display unit displays a three-dimensional shape of the sample estimated by the charged particle ray device.

11. The charged particle ray device according to claim 8 ,

wherein the charged particle ray device classifies the cross-sectional shape of the sample into one of a tapered shape, an reverse taper shape, a bowing shape, an inclined shape, or a shape defined by a user of the charged particle ray device, and displays a result of the classification of the charged particle ray device.

12. A non-transitory computer readable storing thereon a cross-sectional shape estimation program for causing a computer to execute a process of estimating a cross-sectional shape of a sample, wherein the program when executed by the computer, configures the computer to:

acquire detection signal data describing a detection signal representing an intensity of a charged particle generated by irradiating the sample with a charged particle ray,

read a reference pattern describing a detection signal representing the intensity of the charged particle generated by irradiating a reference sample with the charged particle ray, and

estimate a cross-sectional shape of the sample using the detection signal data and the reference pattern,

wherein the detection signal data is acquired by discriminating the charged particle according to energy of the charged particle before the charged particle is detected by a detector, and

wherein, in estimating a cross-sectional shape of the sample using the detection signal data and the reference pattern, the computer is configured to compare the reference pattern with the detection signal acquired for each different discrimination condition to estimate the cross-sectional shape of the sample.