Mr. Devdutt Tripathi Profile

Devdutt Tripathi

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SPIE Journal Paper | 31 July 2023

Deep learning aids simultaneous structure–material design discovery: a case study on designing phase change material metasurfaces

Soumyashree Panda, Sushil Kumar, Devdutt Tripathi, Ravi Hegde

JNP, Vol. 17, Issue 03, 036006, (July 2023) https://doi.org/10.1117/12.10.1117/1.JNP.17.036006

KEYWORDS: Design and modelling, Education and training, Deep learning, Crystals, Mathematical optimization, Data modeling, Optical filters, Nanophotonics, Performance modeling, Evolutionary optimization

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The capabilities of modern precision nanofabrication and the wide choice of materials [plasmonic metals, high-index dielectrics, phase change materials (PCM), and 2D materials] make the inverse design of nanophotonic structures such as metasurfaces increasingly difficult. Deep learning is becoming increasingly relevant for nanophotonics inverse design. Although deep learning design methodologies are becoming increasingly sophisticated, the problem of the simultaneous inverse design of structure and material has not received much attention. In this contribution, we propose a deep learning-based inverse design methodology for simultaneous material choice and device geometry optimization. To demonstrate the utility of the proposed method, we consider the topical problem of active metasurface design using PCMs. We consider a set of four commonly used PCMs in both fully amorphous and crystalline material phases for the material choice and an arbitrarily specifiable polygonal meta-atom shape for the geometry part, which leads to a vast structure/material design space. We find that a suitably designed deep neural network can achieve good optical spectrum prediction capability in an ample design space. Furthermore, we show that this forward model has a sufficiently high predictive ability to be used in a surrogate-optimization setup resulting in the inverse design of active metasurfaces of switchable functionality.

SPIE Journal Paper | 21 January 2023

Optimally designed tunable phase change material-based narrowband perfect absorber

Devdutt Tripathi, Ravi Hegde

JNP, Vol. 17, Issue 01, 016004, (January 2023) https://doi.org/10.1117/12.10.1117/1.JNP.17.016004

KEYWORDS: Reflection, Absorption, Crystals, Silica, Crystallization, Silver, Thermography, Chalcogenides, Switching, Resonators

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In recent years, there has been a growing interest in active metasurfaces. In particular, phase change material-based metasurfaces offering all-optical reconfigurability are being explored. Despite recent progress, further improvement in device reconfiguration energies and optical contrast achievable between the amorphous and crystalline states is desirable. In this work, we demonstrate that using a mirror-backed chalcogenide-based narrowband perfect absorber metasurface can significantly improve the device’s reflection contrast at much lower energies than its mirrorless case. By considering a GST225 metasurface operating in the near IR, our systematic numerical study finds improved reflection contrast (up to −32 dB, Q-factor 19.22 compared with 9.59 dB, Q-factor 11 for the mirrorless case). For the mirrored case, the thermal study finds faster crystallization (up to 6 times) at reduced reconfiguration thresholds (72 times lower) compared with the mirrorless case. This results in a more than 2 orders of magnitude higher device figure of merit [defined as the change in reflection contrast (in dB) to a corresponding change in optical energy (in nJ)] compared with the mirrorless case. The results are promising for high-performance metasurfaces at reduced switching energies.

Proceedings Article | 9 October 2021 Presentation + Paper

A numerical study of optical reconfiguration dynamics of phase change material metasurfaces

Hardik Shyam Vyas, Devdutt Tripathi, Ravi Sadananda Hegde

Proceedings Volume 11903, 119030B (2021) https://doi.org/10.1117/12.2601343

KEYWORDS: Crystals, Reflectivity, Switching, Refractive index

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Tunability is a highly desirable feature for nanophotonic devices and metasurfaces that can enable a plethora of exciting applications like dynamic color filtering and displays, motionless beam scanning, and fast focal length tuning compact imagers. Among several alternatives being explored for realizing tunable nanophotonics, phase change materials have been receiving much attention. In particular, chalcogenide glasses like GeSeTe alloys possess several advantages like large refractive index contrast and rapid phase switching properties which enable non-volatile reconfigurable metasurfaces. While previous workers have reported high reflection contrast changes ensuing from laser-induced amorphous-to-crystalline phase changes, detailed studies of the reconfiguration dynamics and optimization of switching processes have not been adequately considered. In this work, we consider simple and dimerized one-dimensional gratings of GST225 and numerically study phase switching as a function of reconfiguration pulse intensity with the objective of minimizing reconfiguration threshold and maximizing the figure of merit (defined as the rate of change of reflection contrast in % to change in pulse intensity beyond the reconfiguration threshold). The numerical study employs coupled electromagnetic and thermal solvers to ascertain the temperature profile and material phase profile for a particular reconfiguration pulse (assumed to be rectangular shaped). This work hopes to provide insights into the reconfiguration dynamics of PCM gratings while scaling down the reconfiguration threshold intensity requirements which can guide experimental activity in PCM based active metasurfaces.

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