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RESEARCH PAPER · Light Science & Applications · 2019

Emerging role of machine learning in light-matter interaction

Jiajia Zhou, Bolong Huang, Zheng Yan, Jean‐Claude G. Bünzli

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Emerging role of machine learning in light-matter interactionOriginalLanthanide Photonics: Shaping the Nanoworld166Ce doping TiO2/halloysite nanotubes photocatalyst for enhanced electrons transfer and photocatalytic degradation of Tetracycline35Optimization of an H0 photonic crystal nanocavity using machine learning22Deep learning: a new tool for photonic nanostructure design145Single-particle spectroscopy for functional nanomaterials253Inverse design of all-dielectric parallel-plane mirror optical resonator4High‐contrast optical microscopy of graphene sheets1Nanophotonic Structural Colors348Artificial intelligence for photonics and photonic materials63Advances and challenges for fluorescence nanothermometry656Optical microscopy to study single nanoparticles electrochemistry: From reaction to motion22Machine learning and applications in ultrafast photonics418Decoding Optical Data with Machine Learning35Foundations of a Fast, Data-Driven, Machine-Learned Simulator15Plasmonic Mid-Infrared Filter Array-Detector Array Chemical Classifier Based on Machine Learning58Playing optical tweezers with deep reinforcement learning: in virtual, physical and augmented environments16A free-running dual-comb spectrometer with intelligent temporal alignment algorithm12Block Copolymer Directed Metamaterials and Metasurfaces for Novel Optical Devices82Highlighting photonics: looking into the next decade320Perspective paper: Can machine learning become a universal method of laser photonics?7The principles of machine learning algorithms: Applications to biophotonics and disease3Intelligent designs in nanophotonics: from optimization towards inverse creation121Nanophotonics-enabled optical data storage in the age of machine learning24Quantum computing enhanced machine learning for physico-chemical applications2General Inverse Design of Layered Thin-Film Materials with Convolutional Neural Networks66A learning based approach for designing extended unit cell metagratings19A Review and Perspective on the Main Machine Learning Methods Applied to Physical Sciences11Performance Analysis of Optical Arithmetic Circuit Using Artificial Neural Network0Towards integrated mode-division demultiplexing spectrometer by deep learning40Artificial Neural Network Modelling for Optimizing the Optical Parameters of Plasmonic Paired Nanostructures24Rare-Earth Doping in Nanostructured Inorganic Materials1204Prediction of nature of band gap of perovskite oxides (ABO3) using a machine learning approach72Chirality in Light–Matter Interaction223Learning to simulate high energy particle collisions from unlabeled data40Flexible modulations on selectivity of syngas formation via CO2 reduction on atomic catalysts16Ultraspectral Imaging Based on Metasurfaces with Freeform Shaped Meta‐Atoms164Predicting Laser-Induced Colors of Random Plasmonic Metasurfaces and Optimizing Image Multiplexing Using Deep Learning26Luminescent lanthanide coordination compounds as potential mitochondria-targeting probes: Molecular engineering to bioimaging20Improving Teacher Competence in Designing Project-Based Learning Models Through Workshops in The First Semester of the 2018/2019 Academic Year (Madrasah Tsanawiyah Negeri Analysis Study 06 Kerinci)0Machine learning-based discovery of vibrationally stable materials13Optical Encoding Model Based on Orbital Angular Momentum Powered by Machine Learning15Review: 2D material property characterizations by machine-learning-assisted microscopies16Learning and Predicting Photonic Responses of Plasmonic Nanoparticle Assemblies via Dual Variational Autoencoders24Luminescent lanthanide molecular materials as potential probes for the recognition of toxic and biologically important cations14Lithium-ion battery thermal management via advanced cooling parameters: State-of-the-art review on application of machine learning with exergy, economic and environmental analysis48Phase transitions of the anisotropic Dicke model22Machine learning reduces soft costs for residential solar photovoltaics15Where are the outcrops? Automatic delineation of bedrock from sediments using Deep-Learning techniques9Nanostructured surface plasmon resonance sensors: Toward narrow linewidths37Performance Optimization Engineering of Multicomponent Absorbing Materials Based on Machine Learning19A Deep Learning Method for Predicting Low-Cost and High-Accuracy Designing of Anticipatory Layered Nanostructures10Deep learning-based inverse design optimization of efficient multilayer thermal emitters in the near-infrared broad spectrum20Recent developments in Chalcogenide phase change material-based nanophotonics32Machine Learning‐Accelerated Development of Perovskite Optoelectronics Toward Efficient Energy Harvesting and Conversion3Multi-scale optimization of selectively magnetized isotropic carbon fiber fabrics for microwave absorption using machine learning12Towards accurate real-time luminescence thermometry: An automated machine learning approach34Self-Adjusting Optical Systems Based on Reinforcement Learning7Prediction of Quantum Yields of Monolayer WS2 by Machine Learning7Smart control of nonlinear effects in guided optics : Numerical and experimental studies towards novel imaging applications0A newcomer’s guide to deep learning for inverse design in nano‐photonics69Overview: Photovoltaic Solar Cells, Science, Materials, Artificial Intelligence, Nanotechnology and State of the Art12Sigmoid activation function generation by photonic artificial neuron (PAN)6PERFORMANCE ANALYSIS OF OPTICAL PARALLEL FULL ADDER USING ARTIFICIAL NEURAL NETWORK0Lanthanide-based nanomaterials for temperature sensing in the near-infrared spectral region: illuminating progress and challenges55Neuromorphic Optical Data Storage Enabled by Nanophotonics: A Perspective23Autoencoders for compressive sampling in a high-dimensional ultra-fast optical system0Machine Learning Prediction of Quantum Yields and Wavelengths of Aggregation-Induced Emission Molecules14An on-chip programmable diffractive deep neural network based on Sb2Se3-incorporated silicon metalines1Review—Quantum Biosensors: Principles and Applications in Medical Diagnostics743D Laser Writing of Low‐Loss Cross‐Section‐Variable Type‐I Optical Waveguide Passive/Active Integrated Devices in Single Crystals28Optimized higher-order photon state classification by machine learning6Machine Learning for Custom-Designed Light Emitters in Biomedicine15Photonics Meets AI: Driving the Future of Technological Advancement0Utilizing quantum fingerprints in plant cells to evaluate plant productivity0Using optical-electronic neural network for demultiplexing OAM-coded signals0Advanced Microwave Absorption in Woven Structures: The Role of Conductivity-Polarization Loss Synergy1Bio-inspired synergistic imaging for concealed targets0Hierarchic superradiant phases in anisotropic Dicke model0613 Modern extraction techniques: unlocking potential1Investigating the Radial Photonic Band Structure of Second-Order Circular Gratings Using FDTD and Hankel Transform0Integrated Machine Learning and Molecular Dynamics for Functional Nanoparticle Design: Synthesis, Characterization, Force-Field Development, and Property Prediction2Beyond detection: Reprogramming chemiluminescence for spatiotemporal control and intelligent sensing4Role of nuclear quantum effects on hydrogen isotope diffusion in α-U revealed by machine-learning potential and path-integral methods0

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  1. Lanthanide Photonics: Shaping the Nanoworld

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  2. Ce doping TiO2/halloysite nanotubes photocatalyst for enhanced electrons transfer and photocatalytic degradation of Tetracycline

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  3. Optimization of an H0 photonic crystal nanocavity using machine learning

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  4. Deep learning: a new tool for photonic nanostructure design

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  5. Single-particle spectroscopy for functional nanomaterials

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  6. Inverse design of all-dielectric parallel-plane mirror optical resonator

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  7. High‐contrast optical microscopy of graphene sheets

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  8. Nanophotonic Structural Colors

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  10. Advances and challenges for fluorescence nanothermometry

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  11. Optical microscopy to study single nanoparticles electrochemistry: From reaction to motion

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  12. Machine learning and applications in ultrafast photonics

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  14. Foundations of a Fast, Data-Driven, Machine-Learned Simulator

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  15. Plasmonic Mid-Infrared Filter Array-Detector Array Chemical Classifier Based on Machine Learning

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  17. A free-running dual-comb spectrometer with intelligent temporal alignment algorithm

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  19. Highlighting photonics: looking into the next decade

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  20. Perspective paper: Can machine learning become a universal method of laser photonics?

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  21. The principles of machine learning algorithms: Applications to biophotonics and disease

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  22. Intelligent designs in nanophotonics: from optimization towards inverse creation

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  23. Nanophotonics-enabled optical data storage in the age of machine learning

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  24. Quantum computing enhanced machine learning for physico-chemical applications

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  25. General Inverse Design of Layered Thin-Film Materials with Convolutional Neural Networks

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  30. Artificial Neural Network Modelling for Optimizing the Optical Parameters of Plasmonic Paired Nanostructures

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  44. Luminescent lanthanide molecular materials as potential probes for the recognition of toxic and biologically important cations

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