Computational technologies are still in the course of development for nanoimprint lithography (NIL). Only a few simulators are applicable to the nanoimprint process, and these simulators are desired by device manufacturers as part of their daily toolbox. The most challenging issue in NIL process simulation is the scale difference of each component of the system. The template pattern depth and the residual resist film thickness are generally of the order of a few tens of nanometers, while the process needs to work over the entire shot size, which is typically of the order of 10 mm square. This amounts to a scale difference of the order of 106. Therefore, in order to calculate the nanoimprint process with conventional fluid structure interaction (FSI) simulators, an enormous number of meshes is required, which results in computation times that are unacceptable. To support all lithographic systems, Canon has introduced “Lithography Plus”, a software solution capable of anomaly detection, automatic recovery, trouble flow prediction and remote support. The software is now under development specifically for NIL. Because NIL is a rheological process, to software must address a completely new work flow. In this paper, we introduce the methods used to create drop patterns and refinements to the NIL process simulator which can be applied to predict resist filling and, in the future, be used to make corrections to the drop pattern virtually, thereby eliminating time consuming on-tool verification. Finally, we discuss the development of virtual metrology software that incorporates artificial intelligence to provide fast feedback on key tool outputs such as overlay.
Computational technologies are still in the course of development for nanoimprint lithography (NIL). Only a few simulators are applicable to the nanoimprint process, and these simulators are desired by device manufacturers as part of their daily toolbox. The most challenging issue in NIL process simulation is the scale difference of each component of the system. The template pattern depth and the residual resist film thickness are generally of the order of a few tens of nanometers, while the process needs to work over the entire shot size, which is typically of the order of 10 mm square. This amounts to a scale difference of the order of 106 . Therefore, in order to calculate the nanoimprint process with conventional fluid structure interaction (FSI) simulators, an enormous number of meshes is required, which results in computation times that are unacceptable. To support all lithographic systems, Canon has introduced “Lithography Plus”, a software solution capable of anomaly detection, automatic recovery, trouble flow prediction and remote support. The software is now under development specifically for NIL. Because NIL is a rheological process, to software must address a completely new work flow. In this paper, we introduce the methods used to create drop patterns and refinements to the NIL process simulator which can be applied to predict resist filling and, in the future, be used to make corrections to the drop pattern virtually, thereby eliminating time consuming on-tool verification. Finally, we discuss the development of virtual metrology software that incorporates artificial intelligence to provide fast feedback on key tool outputs such as overlay.
For nanoimprint lithography (NIL), computational technologies are still being developed. Only a few simulators are applicable to the nanoimprint process, and these simulators are desired by device manufacturers as part of their everyday toolbox. In this paper, we introduce a new NIL process simulator which simulates the whole imprinting process, and evaluates the quality of the resulting resist film. To overcome the scale difference of each component of the system, which makes it difficult to calculate the process with conventional fluid structure interaction simulators, our simulator utilizes analytically integrated expressions which reduce the dimensions of the calculation region.
Computational technologies are still in the course of development for nanoimprint lithography (NIL). Only a few simulators are applicable to the nanoimprint process, and these simulators are desired by device manufacturers as part of their daily toolbox. The most challenging issue in NIL process simulation is the scale difference of each component of the system. The template pattern depth and the residual resist film thickness are generally of the order of a few tens of nanometers, whereas the process needs to work over the entire shot size, which is typically of the order of several hundred square millimeters. This amounts to a scale difference of the order of 106. Therefore, in order to calculate the nanoimprint process with conventional fluid structure interaction simulators, an enormous number of meshes is required, which results in computation times that are unacceptable. We introduce a process simulator which directly inputs the process parameters, simulates the whole imprinting process, and evaluates the quality of the resulting resist film for jet and flash imprint lithography process. To overcome the scale differences, our simulator utilizes analytically integrated expressions which reduce the dimensions of the calculation region. In addition, the simulator can independently consider the resist droplet configurations and calculate the droplet coalescence, thereby predicting the distribution of the non-fill areas which originate from the trapped gas between the droplets. The simulator has been applied to the actual NIL system and some examples of its applications are presented here.
Imprint lithography is an effective and well-known technique for replication of nano-scale features. Nanoimprint lithography (NIL) manufacturing equipment utilizes a patterning technology that involves the field-by-field deposition and exposure of a low viscosity resist deposited by jetting technology onto the substrate. The patterned mask is lowered into the fluid which then quickly flows into the relief patterns in the mask by capillary action. Following this filling step, the resist is crosslinked under UV radiation, and then the mask is removed, leaving a patterned resist on the substrate. The technology faithfully reproduces patterns with a higher resolution and greater uniformity compared to those produced by photolithography equipment. Additionally, as this technology does not require an array of wide-diameter lenses and the expensive light sources necessary for advanced photolithography equipment, NIL equipment achieves a simpler, more compact design, allowing for multiple units to be clustered together for increased productivity. Previous studies have demonstrated NIL resolution better than 10nm, making the technology suitable for the printing of several generations of critical memory levels with a single mask. In addition, resist is applied only where necessary, thereby eliminating material waste. Computational technologies are still in the course of development for NIL. Only a few simulators are applicable to the nanoimprint process, and these simulators are desired by device manufacturers as part of their daily toolbox. The most challenging issue in NIL process simulation is the scale difference of each component of the system. The template pattern depth and the residual resist film thickness are generally of the order of a few tens of nanometers, while the process needs to work over the entire shot size, which is typically of the order of 10 mm square. This amounts to a scale difference of the order of 106. Therefore, in order to calculate the nanoimprint process with conventional fluid structure interaction (FSI) simulators, an enormous number of meshes is required, which results in computation times that are unacceptable. In this paper, we introduce a new process simulator which directly inputs the process parameters, simulates the whole imprinting process, and evaluates the quality of the resulting resist film. To overcome the scale differences, our simulator utilizes analytically integrated expressions which reduce the dimensions of the calculation region. In addition, the simulator can independently consider the positions of the droplets and calculate the droplet coalescence, thereby predicting the distribution of the non-fill areas which originate from the trapped gas between the droplets. The simulator has been applied to the actual NIL system and some examples of its applications are presented in this work.
Imprint lithography is an effective and well-known technique for replication of nano-scale features. Nanoimprint lithography (NIL) manufacturing equipment utilizes a patterning technology that involves the field-by-field deposition and exposure of a low viscosity resist deposited by jetting technology onto the substrate. The patterned mask is lowered into the fluid which then quickly flows into the relief patterns in the mask by capillary action. Following this filling step, the resist is crosslinked under UV radiation, and then the mask is removed, leaving a patterned resist on the substrate. The technology faithfully reproduces patterns with a higher resolution and greater uniformity compared to those produced by photolithography equipment. Additionally, as this technology does not require an array of wide-diameter lenses and the expensive light sources necessary for advanced photolithography equipment, NIL equipment achieves a simpler, more compact design, allowing for multiple units to be clustered together for increased productivity. Previous studies have demonstrated NIL resolution better than 10nm, making the technology suitable for the printing of several generations of critical memory levels with a single mask. In addition, resist is applied only where necessary, thereby eliminating material waste. Given that there are no complicated optics in the imprint system, the reduction in the cost of the tool, when combined with simple single level processing and zero waste leads to a cost model that is very compelling for semiconductor memory applications. All lithographic approaches must establish an ecosystem in order to meet the stringent demands for device manufacturing. The table below shows the performance requirements for each category. Throughput is a basic requirement for cost of ownership. Defectivity addresses device yield. Overlay is also needed to enhance device yield. Each device generation places stricter demands on the overlay budget. An infrastructure is required in order to successfully yield advanced devices. In addition, today’s solutions require computational methods and machine learning to meet the requirements described above. The purpose of this paper is to describe the NIL integration requirements, review some of the key solutions for total integration.
For nanoimprint lithography, computational technologies are still being developed. In this paper, we introduce a new NIL process simulator which simulates the whole imprinting process, and evaluates the quality of the resulting resist film. To overcome the scale difference of each component of the system, which makes it difficult to calculate the process with conventional fluid structure interaction simulators, our simulator utilizes analytically integrated expressions which reduce the dimensions of the calculation region. Additionally, we report on the critical dimension uniformity of sub-20nm contact holes as a demonstration of pattern robustness and discuss advancements made in defectivity, throughput and overlay.
Computational technologies are still in the course of development for nanoimprint lithography (NIL). Only a few simulators are applicable to the nanoimprint process, and these simulators are desired by device manufacturers as part of their daily toolbox. The most challenging issue in NIL process simulation is the scale difference of each component of the system. The template pattern depth and the residual resist film thickness are generally of the order of a few tens of nanometers, while the process needs to work over the entire shot size, which is typically of the order of 10 mm square. This amounts to a scale difference of the order of 106. Therefore, in order to calculate the nanoimprint process with conventional fluid structure interaction (FSI) simulators, an enormous number of meshes is required, which results in computation times that are unacceptable. In this paper, we introduce a new process simulator which directly inputs the process parameters, simulates the whole imprinting process, and evaluates the quality of the resulting resist film. To overcome the scale differences, our simulator utilizes analytically integrated expressions which reduce the dimensions of the calculation region. In addition, the simulator can independently consider the positions of the droplets and calculate the droplet coalescence, thereby predicting the distribution of the non-fill areas which originate from the trapped gas between the droplets. The simulator has been applied to the actual NIL system and some examples of its applications are presented here.
Nanoimprint lithography manufacturing equipment utilizes a patterning technology that involves the field-by-field deposition and exposure of a low viscosity resist deposited by jetting technology onto the substrate. The patterned mask is lowered into the fluid which then quickly flows into the relief patterns in the mask by capillary action. Following this filling step, the resist is crosslinked under UV radiation, and then the mask is removed, leaving a patterned resist on the substrate. The technology faithfully reproduces patterns with a higher resolution and greater uniformity compared to those produced by photolithography equipment. Additionally, as this technology does not require an array of widediameter lenses and the expensive light sources necessary for advanced photolithography equipment, NIL equipment achieves a simpler, more compact design, allowing for multiple units to be clustered together for increased productivity. In this paper, we review the progress and status of the FPA-1200NZ2C wafer imprint system and FPA-1100NR2 mask replication system. To address high volume manufacturing concerns, an FPA-1200NZ2C four-station cluster tool is used in order to meet throughput and cost of ownership requirements (CoO). Throughputs of up to 90 wafers per hour were achieved by applying a multi-field dispense method. Mask life of up to 125 lots, using a contact hole test mask were demonstrated. A mix and match overlay of 3.4 nm has also been achieved and a single machine overlay across the wafer of 2.1nm in X, 1.9nm in Y was also demonstrated. In addition, data is also presented on mask replication. Critical elements of a replication platform include image placement (IP) accuracy and critical dimension uniformity (CDU). Data is presented on both of these subjects. With respect to image placement, an IP accuracy (after removing correctables) of 0.8nm in X, 1.0nm in Y has been demonstrated.
Imprint lithography has been shown to be an effective technique for replication of nano-scale features. Jet and
Flash* Imprint Lithography (J-FIL*) involves the field-by-field deposition and exposure of a low viscosity resist
deposited by jetting technology onto the substrate. The patterned mask is lowered into the fluid which then quickly flows
into the relief patterns in the mask by capillary action. Following this filling step, the resist is crosslinked under UV
radiation, and then the mask is removed, leaving a patterned resist on the substrate.
There are many criteria that determine whether a particular technology is ready for wafer manufacturing. Defectivity
and mask life play a significant role relative to meeting the cost of ownership (CoO) requirements in the production of
semiconductor devices. Hard particles on a wafer or mask create the possibility of inducing a permanent defect on the
mask that can impact device yield and mask life. By using material methods to reduce particle shedding and by
introducing an air curtain system, the lifetime of both the master mask and the replica mask can be extended. In this
work, we report results that demonstrate a path towards achieving mask lifetimes of better than 1000 wafers.
On the mask side, a new replication tool, the FPA-1100 NR2 is introduced. Mask replication is required for
nanoimprint lithography (NIL), and criteria that are crucial to the success of a replication platform include both particle
control, resolution and image placement accuracy. In this paper we discuss the progress made in both feature resolution
and in meeting the image placement specification for replica masks.
In nanoimprint with UV curable resin, a mold fabricated by etching quartz by using Cr as a hard mask is
generally used. For fine pattern fabrication, Cr fine pattern etching technology is very important. Usually, the
realization of enough resolution needs a resist thickness reduction, which, however, makes it difficult to etch
extremely fine Cr features with vertical sidewalls.
Here, we propose a brand-new method called "reverse EB process". In this method, an electron-beam (EB)
resist pattern is first reversed by a plasma-robust material, with which as a mask, the Cr is then etched to form
a hard mask for the mold etching. By this process, we have realized a quartz mold with patterns of 16nm in
half pitch at minimum.
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