Naozumi Fujiwara’s research while affiliated with SCREEN Holdings Co., Ltd. and other places

In the semiconductor manufacturing process, the miniaturization of patterns has led to increased structural fragility, making pattern collapse a critical issue during the drying step in wet cleaning processes. Such collapse can lead to device defects, which must be avoided. One method to prevent pattern collapse is surface modification treatment (SMT), which substitutes hydrophilic surface OH groups with hydrophobic functional groups such as trimethylsilanol (TMS) groups. In this study, we modeled the FinFET structure of Si/SiO2 with TMS groups and investigated its behavior of the structures under the wet and dry conditions. The results revealed that collapse dynamics varied with the TMS coverage ratio, demonstrating the suppressive effect of SMT on collapse. Notably, focusing on the structural dynamics of the fins, we found that collapse occurs when the fins deform into a cantilever shape, highlighting a collapse mechanism distinct from the previously reported S-shaped beam deformation. In this paper, we discuss the collapse and recovery behavior by evaluating the adhesion energy and elastic energy of the fins. These findings provide valuable insights into the mechanisms of pattern collapse and offer potential strategies for enhancing semiconductor manufacturing processes.

Since the pattern collapse was reported for the first time it has been getting more critical issue in wet cleaning process along with semiconductor scaling. The model of the pattern collapse is that structures such as fins deform due to capillary force during drying step, then they contact and stick each other due to surface tension. One technique to prevent pattern collapse involves lowering the surface tension by modifying the surface’s silanol groups with functional groups[1]. The expected mechanism is that the adhesive force becomes smaller than the elastic force of the pattern due to the reduced surface tension. However, the details, including the dynamics, are still unclear. In particular, how functional groups affect fin contact from a molecular perspective remains unknown. Clarifying these issues is crucial because it will lead to a better understanding of the pattern collapse, subsequently enhancing semiconductor fabrication efficiency. Molecular dynamics (MD) simulation is a useful tool to elucidate these phenomena, as it can obtain physical properties and forces of the system from statistical thermodynamics and visualize nanoscale dynamics[2]. In this study, we prepared models of fins modified with trimethyl silanol (TMS) and calculated the adhesive forces between them by using MD techniques. We utilized the MD solver Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and the visualizer Open Visualization Tool (OVITO) [3, 4]. The fin model utilized in these calculations is depicted in Figure 1. The size of the simulation box was 15.360×2.304×42.000 nm. Periodic boundary conditions were applied in the x and y directions, while specular boundary condition was applied in the z direction. This model primarily consisted of Si atoms. The height of fins was 30 nm, with the top 10 nm terminated by OH groups (912 in total) and the remaining terminated by H atoms. Here we introduced TMS substitutions for randomly selected OH groups. The numbers of substitutions were 0, 91, 228, and 365, resulting in 0%, 10%, 25%, and 40% TMS models, respectively. To reduce bias arising from the random placement of TMS groups, five TMS models were created for each level of TMS substitution. The first step in the calculation process involved placing water between the fins to simulate a wet condition and induce pattern collapse, followed by conducting a 2.0 ns MD calculation. As a result, in every model, the fins came into contact each other (Figure 1b). Subsequently, all water molecules were removed to simulate a dried condition, followed by a 2.0 ns MD calculation. In all models, under the dry condition, the fin contact established during the wet condition was kept (Figure 1c, d). The average adhesive forces between 1.0 ns and 2.0 ns of the MD trajectory after water removal were analyzed, revealing that the forces in the 10%, 25%, and 40% TMS models were less than 1/3 of those in the 0% TMS models. We interpret that, despite the persistence of pattern collapse in the dry condition, restoring the initially separated fins appears more feasible in TMS-modified surface models. The details will be reported in an oral presentation. [1] T. Koide et al. , "Effect of Surface Energy Reduction for Nano-Structure Stiction," ECS Transactions, vol. 69, no. 8, p. 131, 2015, doi: 10.1149/06908.0131ecst. [2] R. Seki et al. , "Insights into FinFET Structure Collapse: A Reactive Force Field-Based Molecular Dynamics Investigation," Solid State Phenomena, vol. 346, p. 123, 2023, doi: 10.4028/p-mUO0Oa. [3] A. P. Thompson et al. , "LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales," Computer Physics Communications, vol. 271, p. 108171, 2022, doi: 10.1016/j.cpc.2021.108171. [4] A. Stukowski, "Visualization and analysis of atomistic simulation data with OVITO–the Open Visualization Tool," Modelling and Simulation in Materials Science and Engineering, vol. 18, no. 1, p. 015012, 2010, doi: 10.1088/0965-0393/18/1/015012. Figure 1: (a) The wet Fin model with inter-fin water molecules for MD simulations. The top 10 nm of the fins were terminated with OH groups, while the remaining were terminated with H atoms. Through the introduction of TMS substitutions for randomly selected OH groups, we prepared 10%, 25%, and 40% TMS models. (b) The snapshot of MD simulation after 2.0 ns from the initial configuration of (a). (c) The dry model prepared by removing water molecules from the configuration of (b). (d) The snapshot of MD simulation after 2.0 ns from the configuration of (c). Figure 1

Evaluations of adhesion energies between materials in contact have been important topics for wet-cleaning process developments. For instance, the balance of adhesion energies among polymers, particles, and a substrate was investigated to elucidate a particle removal mechanism for a polymer-based cleaning process [1] for the purpose of optimizing polymer solution formulations and so on. However, it would be difficult to experimentally evaluate only a targeted adhesion energy when multiple materials interact with each other. We thought using numerical simulation methods would be effective to calculate adhesion energies between targeted materials. The molecular dynamics (MD) simulation is one of the most powerful tools because it enables to easily calculate the intermolecular interactions between arbitrary materials under various conditions. Thus, we conducted MD simulations to calculate adhesion energies between materials related to the wet-cleaning process in semiconductor production. To calculate adhesion energies in MD simulations, we used a thermodynamic integration (TI) method [2]. Although this method is originally used to calculate the free energy difference between two equilibrium states, it also enables us to calculate properties regarding an adhesion energy between materials such as a work of adhesion between a liquid film and a solid substrate [3]. In the TI method, two equilibrium states have to be quasi-statically transitioned for the calculation of the free energy difference between those two states. In particular, to calculate an adhesion energy from the free energy difference, the two equilibrium states are desired. One is a state where materials are in contact and the other is a state where they are separated, as shown in States 1 and 2 in Fig. 1a. Thus, as the method to quasi-statically transition between those states, a phantom wall such that only repulsive interaction works with an arbitrary material is often introduced in the TI method [3, 4]. When the phantom wall interacts only with Material B shown in Fig. 1a, State 1 can be transitioned to State 2 by gradually raising the position of the phantom wall. Figure 1b shows the force exerted on Material B by the phantom wall at each wall position. By numerically integrating this result, the free energy difference between the two states and the corresponding adhesion energy can be calculated [3, 5]. As a verification of the TI method implemented in our MD calculation systems, we calculated the work of adhesion between the water film and the solid substrate using the TI method with the phantom wall, and we obtained values of the work of adhesion comparable to those reported in the previous MD study [3]. From the above, we conclude that the properties regarding adhesion energies between materials in contact with can be calculated using the TI method with the phantom wall in our MD calculation systems. In the presentation at the conference, we will present detailed results of MD analysis on adhesion energies between materials used in wet-cleaning processes, such as H-terminated Si, OH-terminated SiO 2 , PTFE, and so on. References [1] Yu, Seong Hoon, et al., Chemical Engineering Journal 470 (2023): 144102. [2] Leroy, Frédéric, et al., Macromolecular rapid communications 30.9‐10 (2009): 864-870. [3] Bistafa, Carlos, et al., The Journal of Chemical Physics 155.6 (2021). [4] Leroy, Frédéric, and Florian Müller-Plathe, The Journal of chemical physics 133.4 (2010). [5] Yamaguchi, Yasutaka, et al., ECS Transactions 108.4 (2022): 93. Figure 1: (a) State 1 in which Materials A and B are in contact and State 2 in which they are separated. Material B can be pulled away from Material A by raising the position of the phantom wall. (b) The force exerted on Material B by the phantom wall at each wall position. Figure 1

As miniaturization progresses, pattern collapse during the drying step of wet cleaning processes has become a critical issue in the semiconductor industry. In this study, we used reactive molecular dynamics simulations to analyze pattern collapse, with a focus on bondings and reactions. To simulate pattern deformation during the drying process of wet cleaning, we created a FinFET model as a HAR structure. The surface of this model was terminated with hydrogen atoms. The widths between the patterns were changed in order to create a Laplace pressure difference when water molecules were placed on the surface. The model was simulated by placing water molecules up to half the height of the pattern. As a result, the pattern was deformed. Furthermore, by removing water molecules and changing the Laplace pressure balance, it was found that the pattern contacted each other at the tip. The pattern remained in contact when water molecules were removed from the model. In the contact area, the covalent bonds, such as Si-Si and Si-O-Si, were not formed, but instead, hydrogen-to-hydrogen van der Waals bonds were formed between patterns. We calculated the total van der Waals forces between hydrogen atoms at the contact surfaces using the Hamaker equation and calculated the elastic force of the patterns using the beam deflection formula. Our calculations showed that the total van der Waals forces between hydrogen atoms at the contact surfaces were larger than the elastic force of the patterns, indicating that van der Waals forces could be a factor in maintaining the contact of the patterns.

As the semiconductor industry relentlessly reduces device sizes, efficient and precise cleaning processes have become increasingly critical to address challenges such as nanostructure stiction. Gaining insight into the molecular behavior of water and isopropyl alcohol (IPA) on silicon dioxide (SiO2) surfaces is essential for controlling semiconductor wet cleaning processes. This study investigated the interactions between these liquids and SiO2 surfaces. Using molecular dynamics (MD) simulations, we examined the adsorption behavior of water and IPA molecules on both amorphous and crystalline SiO2 (a-SiO2 and c-SiO2) surfaces. Our findings reveal a preferential adsorption of water molecules on a-SiO2 surfaces compared to c-SiO2. This preference can be ascribed to the irregularity of the a-SiO2 surface, which results in the presence of silanol groups that remain inaccessible to the liquid molecules. In contrast, the c-SiO2 surface exhibits a more uniform and accessible structure. This study not only imparts crucial insights into the molecular behavior of water and IPA on SiO2 surfaces but also provides valuable information for future enhancements and optimization of semiconductor wet surface preparation, cleaning, etching and drying.