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Computationally-efficient synthesis of inversely-designed 3D-printable all-dielectric devices

Maria-Thaleia Passia, Steven A. Cummer

Abstract

We present a systematic, computationally efficient approach for synthesizing 3D-printable all-dielectric devices. Inverse-design optimization methods lead to devices of a continuous dielectric constant profile with complex and conformal shapes. However, stereolithography 3D printers have a limited range of materials; usually, only resin and air are available. As the size and complexity of the devices increase, performing simulations of the entire detailed manufacturable device becomes computationally challenging or even prohibitive. We introduce the LOCABINACONN methodology for transforming an optimized device of a continuous material profile to a manufacturable one while preserving performance as close as possible to the continuous case. The LOCABINACONN is a local and computationally efficient methodology where we identify suitable air/resin configurations that will substitute non-manufacturable material components without simulating the entire manufacturable device. This work paves the way for synthesizing optimized larger-scale 3D-printable devices in a computationally tractable manner.

Computationally-efficient synthesis of inversely-designed 3D-printable all-dielectric devices

Abstract

We present a systematic, computationally efficient approach for synthesizing 3D-printable all-dielectric devices. Inverse-design optimization methods lead to devices of a continuous dielectric constant profile with complex and conformal shapes. However, stereolithography 3D printers have a limited range of materials; usually, only resin and air are available. As the size and complexity of the devices increase, performing simulations of the entire detailed manufacturable device becomes computationally challenging or even prohibitive. We introduce the LOCABINACONN methodology for transforming an optimized device of a continuous material profile to a manufacturable one while preserving performance as close as possible to the continuous case. The LOCABINACONN is a local and computationally efficient methodology where we identify suitable air/resin configurations that will substitute non-manufacturable material components without simulating the entire manufacturable device. This work paves the way for synthesizing optimized larger-scale 3D-printable devices in a computationally tractable manner.
Paper Structure (8 sections, 5 figures)

This paper contains 8 sections, 5 figures.

Table of Contents

  1. Introduction
  2. Overview of the LOCABINACONN methodology
  3. The LOCABINACONN methodology
  4. Inversely designed device of a continuous dielectric constant profile
  5. Transforming a device of a continuous dielectric constant profile to a discrete one
  6. Assigning a resin percentage to each discrete material level
  7. Identifying suitable air-resin structures locally
  8. Validation and Discussion

Figures (5)

  • Figure 1: Overview of the LOCABINACONN methodology
  • Figure 2: (a) The diffraction efficiency of the -1-diffraction order for the baseline device, the optimized device of a continuous material profile, and the optimized device of a discrete but non-manufacturable profile. (b) Baseline metagrating.
  • Figure 3: The dispersion diagram of the air/resin unit cell with 55.6% resin matches that of an effective material of $\epsilon_r$=1.7.
  • Figure 4: (a) The reflection $|S_{11}|$ and (b) transmission $|S_{21}|$ coefficients of ten manufacturable air/resin configurations that try to approach the non-manufacturable material component of Fig. \ref{['fig:overview']} with $\epsilon_r$=1.28.
  • Figure 5: (a) Manufacturable device by LOCABINACONN. (b) The efficiency of the $-1$-diffraction order for the manufacturable device obtained by LOCABINACONN is compared to that of a device obtain by a global approach Passia2024 and the device with seven material levels.