Periodic Reporting for period 2 - OPTIMAL (Automated Maskless Laser Lithography Platform for First Time Right Mixed Scale Patterning)
Période du rapport: 2024-04-01 au 2025-09-30
Laser-based technologies for creating structures in the range from nanometre up to millimetre size find many applications such as free form optics, photonics, multifunctional surfaces, lab-on-chip, etc. with a global market volume of > 200 billion euros. The original structures, known as masters, are the first step in the making of tools for key-enabling technologies like injection molding or nanoimprinting. Some of the current limitations in the laser lithography processes are the limited depth of the structures, small area and low speed at process level, high-power consumption in the laser interference lithography, and multiple and expensive processes required for the development of hierarchical multifunctional structures at industrial level.
The OPTIMAL project will integrate for the first-time different laser lithography technologies, quality monitoring systems and processes in one platform for the development of structures with high depth, dimensions in the range from 100 nm to sub-mm, 2D&3D shape on flat surface, combining parallel & serial patterning, no need for external treatments on samples, increased speed and large area. The OPTIMAL project uses self-learning algorithms to optimize the virtual photomask as well as integrates methods for an inline control of the laser patterning. The OPTIMAL platform will be validated through the manufacturing of master tools for four different use cases: a) full-polymer micro lenses for industrial optics, b) hierarchical multifunctional drag reduction riblet structures for aviation, c) free-form lens arrays for high-end virtual reality displays and d) microfluidic hierarchical structures for lab on chip medical devices.
The OPTIMAL project will integrate for the first-time different laser lithography technologies, quality monitoring systems and processes in one platform for the development of structures with high depth, dimensions in the range from 100 nm to sub-mm, 2D&3D shape on flat surface, combining parallel & serial patterning, no need for external treatments on samples, increased speed and large area. The OPTIMAL project uses self-learning algorithms to optimize the virtual photomask as well as integrates methods for an inline control of the laser patterning. The OPTIMAL platform will be validated through the manufacturing of master tools for four different use cases: a) full-polymer micro lenses for industrial optics, b) hierarchical multifunctional drag reduction riblet structures for aviation, c) free-form lens arrays for high-end virtual reality displays and d) microfluidic hierarchical structures for lab on chip medical devices.
The newly developed positive tone mr-P 22G_XP and the negative mr-DWL_100_HT_XP resists are associated to the corresponding use cases. These resists were reproducibly manufactured, their physical and lithographic parameters were determined, and their aging behaviour were investigated.
For the 1PL parallel writing subsystem, a solution based on single long-focal length lens utilization was selected. Various conditions for the patterning using two-photon lithography with a fs laser (780 nm) were investigated. A novel version of the fully automated LIL module was developed and mounted on a translational linear stage with a precision < 2 µm that allows the sub-nanometre adjustment of the grating period. The electroforming equipment was upgraded and the nickel deposition process was tested at various temperatures to find the ideal conditions.
An imaging system for quantitative measurement of the surface flatness with the addition of structured lighting for the focus variation microscopy was developed. A specialized software tool - “Vision Motion”, was also developed integrating the control of motion platforms and digital imaging hardware. The hardware modules for in-line optical monitoring and point-of-focus determination in both the 1PL parallel writing scenario and the 1PL/2PL serial writing scenario were installed at OPTIMAL platform. For the off-line measurement system for quality control the first prototype of optics, mechanics, electronics and software was finalized. The modules for dark-field and diffractive imaging approaches for large-area surface testing were also finalized, tested and installed at OPTIMAL platform.
The self-learning algorithm was optimized and compiled as a standalone application using the MATLAB App Designer, allowing implementation within the OPTIMAL platform. The software was employed to optimize photomasks for production of benchmark artefacts and a micro-optical element, proving its effectiveness.
All the 4 laser writing modules and 7 different hardware modules for inline quality monitoring were integrated into the OPTIMAL platform, together with their respective software control and signal processing electronics for all sensors. Several replacement/upgrade parts together with software upgrades for the vision and alignment systems had been performed. Two software tools for the inverse 3D-printing process were developed. Several methods and strategies for processing the photoresist were tested in order to create the structures with the sub-mm depth.
The use case partners provided structural data for the masters and structures to be developed as a 3D-CAD-file. The writing tests started with the aim to test the possible combination of writing technologies.
The environmental impact of the OPTIMAL photoresist materials was assessed. The environmental impacts of the OPTIMAL platform in comparison with the reference system was estimated and expected environmental benefits of the “First-time-right” production concept were identified. The LCA was focused on estimations of global warming potential (GWP), cumulated energy demand (CED) and abiotic resource depletion. The impacts are assessed in a cradle-to-gate LCA and calculated per 2000 cm² size metal shim produced.
For the 1PL parallel writing subsystem, a solution based on single long-focal length lens utilization was selected. Various conditions for the patterning using two-photon lithography with a fs laser (780 nm) were investigated. A novel version of the fully automated LIL module was developed and mounted on a translational linear stage with a precision < 2 µm that allows the sub-nanometre adjustment of the grating period. The electroforming equipment was upgraded and the nickel deposition process was tested at various temperatures to find the ideal conditions.
An imaging system for quantitative measurement of the surface flatness with the addition of structured lighting for the focus variation microscopy was developed. A specialized software tool - “Vision Motion”, was also developed integrating the control of motion platforms and digital imaging hardware. The hardware modules for in-line optical monitoring and point-of-focus determination in both the 1PL parallel writing scenario and the 1PL/2PL serial writing scenario were installed at OPTIMAL platform. For the off-line measurement system for quality control the first prototype of optics, mechanics, electronics and software was finalized. The modules for dark-field and diffractive imaging approaches for large-area surface testing were also finalized, tested and installed at OPTIMAL platform.
The self-learning algorithm was optimized and compiled as a standalone application using the MATLAB App Designer, allowing implementation within the OPTIMAL platform. The software was employed to optimize photomasks for production of benchmark artefacts and a micro-optical element, proving its effectiveness.
All the 4 laser writing modules and 7 different hardware modules for inline quality monitoring were integrated into the OPTIMAL platform, together with their respective software control and signal processing electronics for all sensors. Several replacement/upgrade parts together with software upgrades for the vision and alignment systems had been performed. Two software tools for the inverse 3D-printing process were developed. Several methods and strategies for processing the photoresist were tested in order to create the structures with the sub-mm depth.
The use case partners provided structural data for the masters and structures to be developed as a 3D-CAD-file. The writing tests started with the aim to test the possible combination of writing technologies.
The environmental impact of the OPTIMAL photoresist materials was assessed. The environmental impacts of the OPTIMAL platform in comparison with the reference system was estimated and expected environmental benefits of the “First-time-right” production concept were identified. The LCA was focused on estimations of global warming potential (GWP), cumulated energy demand (CED) and abiotic resource depletion. The impacts are assessed in a cradle-to-gate LCA and calculated per 2000 cm² size metal shim produced.
New breakthroughs in the field of photoresists were achieved with increased thickness and area while keeping homogeneity. This opened up new market potential.
The possibility to create 1D, 2D and 2.5D structures via 1PL in the serial and parallel writing was demonstrated. The possibility to create 1D, 2D, 2.5D and 3D structures via 2PL module was also demonstrated. The electroplating process was optimized for large area (70 x 30 cm²) substrates, including seed layer application via ELESS plating and the subsequent low temperature electroforming. It was also possible to replace the toxic nickel chloride with the more environmentally friendly nickel sulfamate as a nickel source.
The OPTIMAL “Vision Motion” system allows real-time focus search and monitoring and various alignment tasks needed for fabrication process. Thanks to the installed inline monitoring tools, the scanning speed was improved and the faults number were decreased. The precision of the captured 3D images is improved whereas the stage levelling increases the speed of scanning, due to optimization of the used Z-range. The final implementation of streamed 3D scan in combination with analysis tool is not existing on other systems and expected to be patentable.
The self-learning algorithm developed within the project yielded major improvements in terms of build accuracy. The average build error decreased from 3.6 µm to 1.2 µm in a single build for test cases including benchmark artefacts and a micro-optical element, demonstrating clear improvements compared to standard approaches to virtual photomask optimization.
The laser lithography, inline monitoring and self-learning algorithms modules were successfully tested on the OPTIMAL platform.
During the LCA study on the reference system for the OPTIMAL platform it was noticed the main contribution to GWP, CED and abiotic resource depletion is electricity consumed for clean room conditioning (40 m² size) and the manufacturing processes. It was estimated that the overall processing time of the OPTIMAL system will decrease by 54% compared to the reference system with corresponding reduction of environmental impact.
The possibility to create 1D, 2D and 2.5D structures via 1PL in the serial and parallel writing was demonstrated. The possibility to create 1D, 2D, 2.5D and 3D structures via 2PL module was also demonstrated. The electroplating process was optimized for large area (70 x 30 cm²) substrates, including seed layer application via ELESS plating and the subsequent low temperature electroforming. It was also possible to replace the toxic nickel chloride with the more environmentally friendly nickel sulfamate as a nickel source.
The OPTIMAL “Vision Motion” system allows real-time focus search and monitoring and various alignment tasks needed for fabrication process. Thanks to the installed inline monitoring tools, the scanning speed was improved and the faults number were decreased. The precision of the captured 3D images is improved whereas the stage levelling increases the speed of scanning, due to optimization of the used Z-range. The final implementation of streamed 3D scan in combination with analysis tool is not existing on other systems and expected to be patentable.
The self-learning algorithm developed within the project yielded major improvements in terms of build accuracy. The average build error decreased from 3.6 µm to 1.2 µm in a single build for test cases including benchmark artefacts and a micro-optical element, demonstrating clear improvements compared to standard approaches to virtual photomask optimization.
The laser lithography, inline monitoring and self-learning algorithms modules were successfully tested on the OPTIMAL platform.
During the LCA study on the reference system for the OPTIMAL platform it was noticed the main contribution to GWP, CED and abiotic resource depletion is electricity consumed for clean room conditioning (40 m² size) and the manufacturing processes. It was estimated that the overall processing time of the OPTIMAL system will decrease by 54% compared to the reference system with corresponding reduction of environmental impact.