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Pushing the limits of optical information storage using deep learning

Nature nanotechnology, 2019-03, Vol.14 (3), p.237-244

2019

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Origin of second-harmonic generation from individual silicon nanowires

Physical review. B, 2016-03, Vol.93 (12), Article 125421

2016

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Deep Learning Meets Nanophotonics: A Generalized Accurate Predictor for Near Fields and Far Fields of Arbitrary 3D Nanostructures

Nano letters, 2020-01, Vol.20 (1), p.329-338

2020

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Enhancement of electric and magnetic dipole transition of rare-earth-doped thin films tailored by high-index dielectric nanostructures

Applied optics (2004), 2019-03, Vol.58 (7), p.1682

2019

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Challenges in nanofabrication for efficient optical metasurfaces

Scientific reports, 2021-03, Vol.11 (1), p.5620-12, Article 5620

2021

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Strongly Directional Scattering from Dielectric Nanowires

ACS photonics, 2017-08, Vol.4 (8), p.2036-2046

2017

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A newcomer’s guide to deep learning for inverse design in nano-photonics

Nanophotonics (Berlin, Germany), 2023-12, Vol.12 (24), p.4387-4414

2023

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Deep learning enabled real time speckle recognition and hyperspectral imaging using a multimode fiber array

Optics express, 2019-07, Vol.27 (15), p.20965-20979

2019

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Evolutionary multi-objective optimization of colour pixels based on dielectric nanoantennas

Nature nanotechnology, 2017-02, Vol.12 (2), p.163-169

2017

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Unveiling the Optical Emission Channels of Monolayer Semiconductors Coupled to Silicon Nanoantennas

ACS photonics, 2020-11, Vol.7 (11), p.3106-3115

2020

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Advancing materials science through next-generation machine learning

Current opinion in solid state & materials science, 2024-06, Vol.30, p.101157, Article 101157

2024

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Generalizing the exact multipole expansion: density of multipole modes in complex photonic nanostructures

Nanophotonics (Berlin, Germany), 2022-09, Vol.11 (16), p.3663-3678

2022

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Probing the optical near-field interaction of Mie nanoresonators with atomically thin semiconductors

Communications physics, 2023-05, Vol.6 (1), p.102-7, Article 102

2023

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Decay rate of magnetic dipoles near nonmagnetic nanostructures

Physical review. B, 2018-02, Vol.97 (8), Article 085411

2018

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Design of plasmonic directional antennas via evolutionary optimization

Optics express, 2019-09, Vol.27 (20), p.29069-29081

2019

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Infrared nanoplasmonic properties of hyperdoped embedded Si nanocrystals in the few electrons regime

Nanophotonics (Berlin, Germany), 2022-07, Vol.11 (15), p.3485-3493

2022

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Deep Learning Enabled Strategies for Modeling of Complex Aperiodic Plasmonic Metasurfaces of Arbitrary Size

ACS photonics, 2022-02, Vol.9 (2), p.575-585

2022

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Deep Learning Enabled Design of Complex Transmission Matrices for Universal Optical Components

ACS photonics, 2021-01, Vol.8 (1), p.283-295

2021

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Polarization conversion in plasmonic nanoantennas for metasurfaces using structural asymmetry and mode hybridization

Scientific reports, 2017-01, Vol.7 (1), p.40906-40906, Article 40906

2017

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pyGDM—A python toolkit for full-field electro-dynamical simulations and evolutionary optimization of nanostructures

Computer physics communications, 2018-12, Vol.233, p.167-192

Wiecha, Peter R.

2018

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Local field enhancement and thermoplasmonics in multimodal aluminum structures

Physical review. B, 2017-07, Vol.96 (3), Article 035440

2017

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Wafer‐Scale 200 mm Metal Oxide Infrared Metasurface with Tailored Differential Emissivity Response in the Atmospheric Windows

Advanced optical materials, 2022-09, Vol.10 (17), p.n/a

2022

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Tailoring Second-Harmonic Generation in Single L‑Shaped Plasmonic Nanoantennas from the Capacitive to Conductive Coupling Regime

ACS photonics, 2015-11, Vol.2 (11), p.1592-1601

2015

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Hyper-Doped Silicon Nanoantennas and Metasurfaces for Tunable Infrared Plasmonics

ACS photonics, 2021-05, Vol.8 (5), p.1393-1399

2021

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Deep learning for nano-photonic materials – The solution to everything!?

Current opinion in solid state & materials science, 2024-02, Vol.28, p.101129, Article 101129

Wiecha, Peter R.

2024

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Pushing the limits of optical information storage using deep learning

Origin of second-harmonic generation from individual silicon nanowires

Deep Learning Meets Nanophotonics: A Generalized Accurate Predictor for Near Fields and Far Fields of Arbitrary 3D Nanostructures

Enhancement of electric and magnetic dipole transition of rare-earth-doped thin films tailored by high-index dielectric nanostructures

Challenges in nanofabrication for efficient optical metasurfaces

Strongly Directional Scattering from Dielectric Nanowires

A newcomer’s guide to deep learning for inverse design in nano-photonics

Deep learning enabled real time speckle recognition and hyperspectral imaging using a multimode fiber array

Evolutionary multi-objective optimization of colour pixels based on dielectric nanoantennas

Unveiling the Optical Emission Channels of Monolayer Semiconductors Coupled to Silicon Nanoantennas

Advancing materials science through next-generation machine learning

Generalizing the exact multipole expansion: density of multipole modes in complex photonic nanostructures

Probing the optical near-field interaction of Mie nanoresonators with atomically thin semiconductors

Decay rate of magnetic dipoles near nonmagnetic nanostructures

Design of plasmonic directional antennas via evolutionary optimization

Infrared nanoplasmonic properties of hyperdoped embedded Si nanocrystals in the few electrons regime

Deep Learning Enabled Strategies for Modeling of Complex Aperiodic Plasmonic Metasurfaces of Arbitrary Size

Deep Learning Enabled Design of Complex Transmission Matrices for Universal Optical Components

Polarization conversion in plasmonic nanoantennas for metasurfaces using structural asymmetry and mode hybridization

pyGDM—A python toolkit for full-field electro-dynamical simulations and evolutionary optimization of nanostructures

Local field enhancement and thermoplasmonics in multimodal aluminum structures

Wafer‐Scale 200 mm Metal Oxide Infrared Metasurface with Tailored Differential Emissivity Response in the Atmospheric Windows

Tailoring Second-Harmonic Generation in Single L‑Shaped Plasmonic Nanoantennas from the Capacitive to Conductive Coupling Regime

Hyper-Doped Silicon Nanoantennas and Metasurfaces for Tunable Infrared Plasmonics

Deep learning for nano-photonic materials – The solution to everything!?

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