Measuring method and measuring device
According to one embodiment, a measuring method includes forming a partition including a lower portion arranged on a first surface side of a base and an upper portion protruding from a side surface of the lower portion, acquiring a first image including the partition observed from a second surface side opposed to the first surface of the base by an optical microscope, analyzing the acquired first image, and measuring an amount of protrusion by which an end portion of the upper portion protrudes from the side surface of the lower portion, based on the analysis result.
1 . A measuring method comprising:
forming a partition including a lower portion arranged on a first surface side of a base and an upper portion protruding from a side surface of the lower portion;
acquiring a first image including the partition observed from a second surface side opposed to the first surface of the base by an optical microscope;
analyzing the acquired first image; and
measuring an amount of protrusion by which an end portion of the upper portion protrudes from the side surface of the lower portion, based on the analysis result.
2 . The measuring method of claim 1 , wherein
the analyzing includes identifying a first pixel corresponding to the side surface of the lower portion, and a second pixel corresponding to the end portion of the upper portion, based on luminance values of a plurality of pixels constituting the first image, and
the measuring includes measuring the amount of protrusion, based on the number of pixels arranged between the identified first and second pixels.
3 . The measuring method of claim 2 , wherein
the measuring includes converting the number of pixels into the amount of protrusion, based on conversion information indicating a length corresponding to one pixel, and
the conversion information is prepared in advance, based on a second image including a sample whose size observed by the optical microscope is already known.
4 . The measuring method of claim 2 , wherein
the measuring includes acquiring the amount of protrusion output from a machine learning model by inputting the number of pixels arranged between the identified first and second pixels to the machine learning model, the machine learning model being generated by learning a data set prepared in advance, and
the data set includes the number of pixels arranged between the first and second pixels identified from a third image including the partition in which the amount of protrusion observed by the optical microscope is known, and the known amount of protrusion.
5 . A measuring method comprising:
forming an insulating layer arranged on a first surface side of a base;
forming a lower electrode arranged on the insulating layer;
forming a rib which covers a part of the lower electrode and which includes an aperture overlapping with the lower electrode;
forming a partition including a lower portion arranged on the rib and an upper portion protruding from a side surface of the lower portion;
acquiring a first image including the partition observed from a second surface side opposed to the first surface of the base by an optical microscope;
analyzing the acquired first image; and
measuring an amount of protrusion at which an end portion of the upper portion protrudes from the side surface of the lower portion, based on the analysis result.
6 . The measuring method of claim 5 , wherein
the lower portion is formed of a first metal material, and
the upper portion is formed of a second metal material different from the first metal material.
7 . The measuring method of claim 6 , wherein
the first metal material includes aluminum or an aluminum alloy, and
the second metal material includes titanium.
8 . The measuring method of claim 6 , wherein
the lower portion includes a barrier layer arranged on the rib, and a metal layer arranged on the barrier layer,
the barrier layer is formed of a third metal material different from the first metal material, and
the metal layer is formed of the first metal material.
9 . The measuring method of claim 8 , wherein
the first metal material includes aluminum or an aluminum alloy,
the second metal material includes titanium, and
the third metal material includes molybdenum.
10 . The measuring method of claim 5 , wherein
the side surface of the lower portion is inclined to a direction perpendicular to the base such that a width of the lower portion becomes smaller toward the upper portion.
11 . The measuring method of claim 5 , wherein
the analyzing includes identifying a first pixel corresponding to an end portion on a side opposite to the side surface of the lower portion, and a second pixel corresponding to the end portion of the upper portion, based on luminance values of a plurality of pixels constituting the first image, and
the measuring includes measuring the amount of protrusion, based on the number of pixels arranged between the identified first and second pixels.
12 . The measuring method of claim 11 , wherein
the measuring includes converting the number of pixels into the amount of protrusion, based on conversion information indicating a length corresponding to one pixel, and
the conversion information is prepared in advance, based on a second image including a sample whose size is already known by the optical microscope.
13 . The measuring method of claim 11 , wherein
the measuring includes acquiring the amount of protrusion output from a machine learning model by inputting the number of pixels arranged between the identified first and second pixels to the machine learning model, the machine learning model being generated by learning a data set prepared in advance, and
the data set includes the number of pixels arranged between the first and second pixels identified from a third image including the partition in which the amount of protrusion observed by the optical microscope is known, and the known amount of protrusion.
14 . The measuring method of claim 5 , further comprising:
forming an organic layer which is in contact with the lower electrode through the aperture after measuring the amount of protrusion; and
forming an upper electrode arranged on the organic layer.
15 . The measuring method of claim 14 , further comprising:
forming a cap layer arranged on the upper electrode; and
forming a sealing layer arranged on the cap layer.
16 . The measuring method of claim 5 , wherein
the insulating layer is formed of an organic material, and
the rib is formed of an inorganic material.
17 . A measuring device comprising:
an acquisition unit configured to acquire a first image including a partition observed by an optical microscope from a second surface side opposed to a first surface of a base in which the partition including a lower portion and an upper portion protruding from a side surface of the lower portion is formed on the first surface side;
an analysis unit configured to analyze the acquired first image; and
a measurement unit configured to measure an amount of protrusion by which the end portion of the upper portion protrudes from the side surface of the lower portion, based on the analysis result.
18 . The measuring device of claim 17 , wherein
the analysis unit is configured to identify a first pixel corresponding to the side surface of the lower portion, and a second pixel corresponding to the end portion of the upper portion, based on luminance values of a plurality of pixels constituting the first image, and
the measurement unit is configured to measure the amount of protrusion, based on the number of pixels arranged between the identified first and second pixels.
19 . The measuring device of claim 18 , wherein
the measurement unit is configured to convert the number of pixels into the amount of protrusion, based on conversion information indicating a length corresponding to one pixel, and
the conversion information is prepared in advance, based on a second image including a sample whose size observed by the optical microscope is already known.
20 . The measuring device of claim 18 , wherein
the measurement unit is configured to acquire the amount of protrusion output from a machine learning model by inputting the number of pixels arranged between the identified first and second pixels to the machine learning model, the machine learning model being generated by learning a data set prepared in advance, and
the data set includes the number of pixels arranged between the first and second pixels identified from a third image including the partition in which the amount of protrusion observed by the optical microscope is already known, and the known amount of protrusion.