Improving print accuracy and eliminating striations in volumetric additive manufacturing: a novel approach to tomographic optimization, and a latent image printing method

Rackson, Charles M.; McLeod, Robert R.

doi:10.1117/12.2623008

Cited by 2 publications

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“…These can alter the optical properties on a local or global scale, and can arise from the basic photo-induced polymerization process [36] as well as modifications during development. Such modifications include shrinking [37,38], thermal diffusion [39], striation [40] and undesired photo-polymerization of areas with low degree of polymerization [41]. It is important to point out that the recently demonstrated two-colour fabrication method can potentially increase fabrication speed substantially, while also offering a moderate improvement in terms of minimal feature size [42].…”

Section: Basics Aspects and Challenges Of Additive Fabricationmentioning

confidence: 99%

Additive 3D photonic integration that is CMOS compatible

et al. 2023

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Today, continued miniaturization in electronic integrated circuits (ICs) appears to have reached its fundamental limit at ∼2 nm feature-sizes, from originally ∼1 cm. At the same time, energy consumption due by communication becomes the dominant limitation in high performance electronic ICs for computing, and modern computing concepts such a neural networks further amplify the challenge. Communication based on co-integrated photonic circuits is a promising strategy to address the second. As feature size has leveled out, adding a third dimension to the predominantly two dimensional integrated circuits appears the most promising future strategy for further IC architecture improvement. Crucial for efficient electronic-photonic co-integration is CMOS compatibility of the associated photonic integration fabrication process. Here, we review our latest results obtained in the FEMTO-ST RENATECH facilities on using additive photo-induced polymerization of a standard photo-resin for truly 3D photonic integration according to these principles. Based on one- and two-photon polymerization and combined with direct-laser writing, we 3D-printed air and polymercladded photonic waveguides. An important application of such circuits are the interconnects of optical neural networks, where 3D integration enables scalability in terms of network size versus its geometric dimensions. In particular via flashTPP, a fabrication process combining blanket one- and high-resolution two-photon polymerization, we demonstrated polymer-cladded step-index waveguides with up to 6 mmlength, low insertion (∼0.26 dB) and propagation (∼1.3 dB/mm) losses, realized broadband and low loss (∼0.06 dB splitting losses) adiabatic 1 to M couplers as well as tightly confining air-cladded waveguides for denser integration. By stably printing such integrated photonic circuits on standard semiconductor samples, we show the concept’s CMOS compatibility. With this, we lay out a promising, future avenue for scalable integration of hybrid photonic and electronic components.

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Section: Basics Aspects and Challenges Of Additive Fabricationmentioning

confidence: 99%

Additive 3D photonic integration that is CMOS compatible

et al. 2023

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Machine learning to optimize additive manufacturing for visible photonics

et al. 2023

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Additive manufacturing has become an important tool for fabricating advanced systems and devices for visible nanophotonics. However, the lack of simulation and optimization methods taking into account the essential physics of the optimization process leads to barriers for greater adoption. This issue can often result in sub-optimal optical responses in fabricated devices on both local and global scales. We propose that physics-informed design and optimization methods, and in particular physics-informed machine learning, are particularly well-suited to overcome these challenges by incorporating known physics, constraints, and fabrication knowledge directly into the design framework.

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Improving print accuracy and eliminating striations in volumetric additive manufacturing: a novel approach to tomographic optimization, and a latent image printing method

Cited by 2 publications

References 0 publications

Additive 3D photonic integration that is CMOS compatible

Additive 3D photonic integration that is CMOS compatible

Machine learning to optimize additive manufacturing for visible photonics

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