OPTIMAL | Automated Maskless Laser Lithography Platform for First Time Right Mixed Scale Patterning

Summary

Laser-based technologies for creating structures in the range from nanometer up to millimeter 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 know 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

  1. high depth (150 micrometer)
  2. dimensions in the range from 100 nm to sub-mm in XYZ,
  3. 2D&3D shape on flat surface,
  4. combining parallel & serial patterning,
  5. no need for external treatments on samples;
  6. increased speed (1 cm2/min) and large area (up to 2000 cm2),
  7. > 40% of reduction in the consumption of resources for the whole manufacturing process.

 

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.

By accelerating and upscaling the structuring process, the OPTIMAL project will increase the process efficiency and yield, which will reduce the energy consumption, avoid material waste, decrease costs, and lead time in many applications. The platform will potentiate the possibilities in the sustainable making of high quality, versatile, less costly masters for industrial manufacturing, as demonstrated in 4 use cases (optical lenses, multifunctional riblet structures, virtual reality lens, microfluidic chips).

Results, demos, etc. Show all and search (6)
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Demonstrators, pilots, prototypes
Comment:

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.

More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101057029
https://www.optimal-project.eu/
Start date: 01-10-2022
End date: 30-09-2026
Total budget - Public funding: 5 616 876,00 Euro - 5 616 875,00 Euro
Cordis data

Original description

Laser-based technologies for creating structures in the range from nanometer up to millimeter 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 know 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 (i) high depth (150 micrometer), ii) dimensions in the range from 100 nm to sub-mm in XYZ, iii) 2D&3D shape on flat surface, (iv) combining parallel & serial patterning, (v) no need for external treatments on samples; vi) increased speed (1 cm2/min) and large area (up to 2000 cm2), vii) > 40% of reduction in the consumption of resources for the whole manufacturing process. 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.
By accelerating and upscaling the structuring process, the OPTIMAL project will increase the process efficiency and yield, which will reduce the energy consumption, avoid material waste, decrease costs, and lead time in many applications. The platform will potentiate the possibilities in the sustainable making of high quality, versatile, less costly masters for industrial manufacturing, as demonstrated in 4 use cases (optical lenses, multifunctional riblet structures, virtual reality lens, microfluidic chips).

Status

SIGNED

Call topic

HORIZON-CL4-2021-TWIN-TRANSITION-01-03

Update Date

27-10-2022
Geographical location(s)
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Result items:

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. 

Result items:

By accelerating and upscaling the structuring process, the OPTIMAL project will increase the process efficiency and yield, which will allow for “first time right” fabrication of the required structures, lower consumption of resources, waste reduction, lower CO2 emissions, increase of productivity, and cost reduction. 

Result items:

By accelerating and upscaling the structuring process, the OPTIMAL project will increase the process efficiency and yield, which will allow for “first time right” fabrication of the required structures, lower consumption of resources, waste reduction, lower CO2 emissions, increase of productivity, and cost reduction. 

Result items:

The OPTIMAL approach involves various disciplines, which interact with each other in order to achieve the project objectives. Material research and photochemistry is needed to develop the suitable photoresists (MRT). Laser technology knowledge (JOR, ISE) is required for developing novel laser lithography methods, machines, and processes. The electronics finds its application in the optical based sensors for in-line monitoring, controlling the laser sources and patterning (ILC, DPX). The software engineering expertise (UPR) completes the required skills for the development of self-learning algorithms for generating the virtual photomasks. Mechanical and environmental engineering deal with the equipment and manufacturing processes and their life cycle assessment (JOR). Experts in training and communication science (ILC, UPR) will design workshops and training materials to explain and promote the developed technologies to broad public and stakeholders. 

Result items:

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 consortium consists of three research institutes (JOR, ISE, ILC), one university (UPR), member of the Italian Photonics Association, three Small Medium Enterprises (MRT, DPX, HYP), two big industries, leaders in their corresponding market (SDA and BCD).

Result items:

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 consortium consists of three research institutes (JOR, ISE, ILC), one university (UPR), member of the Italian Photonics Association, three Small Medium Enterprises (MRT, DPX, HYP), two big industries, leaders in their corresponding market (SDA and BCD).

Result items:

By accelerating and upscaling the structuring process, the OPTIMAL project will increase the process efficiency and yield, which will allow for “first time right” fabrication of the required structures, lower consumption of resources, waste reduction, lower CO2 emissions, increase of productivity, and cost reduction. 

Result items:

By accelerating and upscaling the structuring process, the OPTIMAL project will increase the process efficiency and yield, which will allow for “first time right” fabrication of the required structures, lower consumption of resources, waste reduction, lower CO2 emissions, increase of productivity, and cost reduction. 

Result items:

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.

Result items:

By accelerating and upscaling the structuring process, the OPTIMAL project will increase the process efficiency and yield, which will allow for “first time right” fabrication of the required structures, lower consumption of resources, waste reduction, lower CO2 emissions, increase of productivity, and cost reduction. 

Result items:

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.

Result items:

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.

Comment:

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.