As semiconductor devices continue to introduce new materials and structures, not only the dimensions but the material properties are becoming important in determining the device properties. Properties of insulator films used in transistors and memory devices, such as breakdown voltage and damage, are of particular interest as they determine the characteristics as well as the reliability of the devices. To ensure efficient production of these devices, an inline tool for metrology and inspection of material properties is desirable. One way to evaluate the material properties is to measure the material’s response to application of voltage. For this purpose, we have developed laser-assisted SEM; an SEM with laser irradiation capability to control the electrical state of the material under SEM observation. The laser can be used to inject carriers into insulators and neutralize insulator charging caused by the electron beam. By evaluating the energy of secondary electrons, we measured the charging voltage of insulators, defined as the difference in the surface potential between when the laser is irradiated and not irradiated. Similarly to breakdown voltage, we verified that the charging voltage increases with the insulator thickness. Furthermore, charging voltage was shown to be dependent on damage due to plasma in an etcher. Therefore, charging voltage measurements assisted by a laser is a unique way to evaluate the material property of insulators. We believe our laser assisted SEM will open the door to new types of electrical and material characterizations and go beyond the traditional role of SEMs in metrology and inspection.
In addition to the conventional process control method like dimensional metrology, there is a growing need to measure the electrical characteristics of device structures. Detection of defective electrical characteristics during device fabrication is important to improve device yield and shorten the ramp-up time of the manufacturing process. Voltage contrast of traditional scanning electron microscopes can be used to measure some of the electrical characteristics but is limited in its sensitivity and, hence, its applicable processes. We have developed a Laser-assisted SEM (LA-SEM) with (1) laser irradiation function and (2) electron beam modulation function to control and enhance the voltage contrast (VC) for in-line electrical inspection and measurement. In this report, for samples with high-impedance components obstructing the view of defect of interest, we confirmed that ultraviolet laser irradiation provides defect contrast that cannot be obtained with electron-beam-only VC. For Not-Open defects on a PN junction, the VC was improved by a factor of 1.19 by using a laser in the near-infrared region. Furthermore, to extract electrical properties of defects and monitor their changes during the manufacturing flow, a VC circuit simulation function was developed to quantitatively estimate VC transients obtained by modulated electron beam irradiation. As an example, a quantitative estimation of RC by transient voltage contrast analysis was performed on floating plugs with varying resistance using metal film deposition on its side walls. A decent correlation between the estimated electrical properties and the sheet resistance of the metallic film was demonstrated.
In scanning electron microscope (SEM) image simulation, it is necessary to consider the charging of electron beam irradiation, which can be computationally intensive. Therefore, we have developed a neural network-based algorithm to generate SEM images by inputting the shape and material properties of semiconductor devices, after which various preprocesses are applied to the physical parameters to improve the accuracy. The contrast and visibility of the generated images are then compared with simulation results that are not included in the training dataset. As a preliminary result, we found that the physical parameters that affect charging, such as the relative permittivity and electron mobility of the material, can be predicted. The effect of acceptance is also considered in the training process to reproduce the changes in image quality depending on the type and arrangement of detectors.
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