Machine Learning for Optical Scanning Probe Nanoscopy

Chen, Xinzhong; Xu, Suheng; Shabani, Sara; Zhao, Yueqi; Fu, Matthew; Millis, Andrew J.; Fogler, Michael M.; Pasupathy, Abhay N.; Liu, Mengkun; Basov, D. N.

doi:10.1002/adma.202109171

Machine Learning for Optical Scanning Probe Nanoscopy

Journal Article · Fri Nov 04 00:00:00 EDT 2022 · Advanced Materials

DOI:https://doi.org/10.1002/adma.202109171· OSTI ID:1995866

^[1]; Xu, Suheng ^[2]; Shabani, Sara ^[2]; Zhao, Yueqi ^[3]; Fu, Matthew ^[2]; Millis, Andrew J. ^[2]; Fogler, Michael M. ^[3]; Pasupathy, Abhay N. ^[2]; Liu, Mengkun ^[4]; Basov, D. N. ^[2]

Department of Physics and Astronomy Stony Brook University Stony Brook NY 11794 USA
Department of Physics Columbia University New York NY 10027 USA
Department of Physics University of California at San Diego La Jolla CA 92093‐0319 USA
Department of Physics and Astronomy Stony Brook University Stony Brook NY 11794 USA, National Synchrotron Light Source II Brookhaven National Laboratory Upton NY 11973 USA

Abstract

The ability to perform nanometer‐scale optical imaging and spectroscopy is key to deciphering the low‐energy effects in quantum materials, as well as vibrational fingerprints in planetary and extraterrestrial particles, catalytic substances, and aqueous biological samples. These tasks can be accomplished by the scattering‐type scanning near‐field optical microscopy (s‐SNOM) technique that has recently spread to many research fields and enabled notable discoveries. Herein, it is shown that the s‐SNOM, together with scanning probe research in general, can benefit in many ways from artificial‐intelligence (AI) and machine‐learning (ML) algorithms. Augmented with AI‐ and ML‐enhanced data acquisition and analysis, scanning probe optical nanoscopy is poised to become more efficient, accurate, and intelligent.

View Accepted Manuscript (Publisher)

Sponsoring Organization:: USDOE

Grant/Contract Number:: SC0012704; SC0019443

OSTI ID:: 1995866

Journal Information:: Advanced Materials, Journal Name: Advanced Materials; ISSN 0935-9648

Publisher:: Wiley Blackwell (John Wiley & Sons)Copyright Statement

Country of Publication:: Germany

Language:: English

References (208)

Inducing and Probing Localized Excitons in Atomically Thin Semiconductors via Tip‐Enhanced Cavity‐Spectroscopy Lee, Hyeongwoo; Kim, Inki; Park, Chulho Advanced Functional Materials, Vol. 31, Issue 33 https://doi.org/10.1002/adfm.202102893	journal	June 2021
Modern Scattering‐Type Scanning Near‐Field Optical Microscopy for Advanced Material Research Chen, Xinzhong; Hu, Debo; Mescall, Ryan Advanced Materials https://doi.org/10.1002/adma.201804774	journal	April 2019
Visualizing Atomically Layered Magnetism in CrSBr Rizzo, Daniel J.; McLeod, Alexander S.; Carnahan, Caitlin Advanced Materials, Vol. 34, Issue 27 https://doi.org/10.1002/adma.202201000	journal	May 2022
Hypothesis Learning in Automated Experiment: Application to Combinatorial Materials Libraries Ziatdinov, Maxim A.; Liu, Yongtao; Morozovska, Anna N. Advanced Materials, Vol. 34, Issue 20 https://doi.org/10.1002/adma.202201345	journal	April 2022
Tip-enhanced Raman spectroscopy - an interlaboratory reproducibility and comparison study: TERS interlaboratory comparison Blum, Carolin; Opilik, Lothar; Atkin, Joanna M. Journal of Raman Spectroscopy, Vol. 45, Issue 1 https://doi.org/10.1002/jrs.4423	journal	January 2014
Terahertz spectroscopy and imaging - Modern techniques and applications Jepsen, P. U.; Cooke, D. G.; Koch, M. Laser & Photonics Reviews, Vol. 5, Issue 1 https://doi.org/10.1002/lpor.201000011	journal	October 2010
Rapid Classification of Quantum Sources Enabled by Machine Learning Kudyshev, Zhaxylyk A.; Bogdanov, Simeon I.; Isacsson, Theodor Advanced Quantum Technologies, Vol. 3, Issue 10 https://doi.org/10.1002/qute.202000067	journal	September 2020
Fast Scanning Probe Microscopy via Machine Learning: Non‐Rectangular Scans with Compressed Sensing and Gaussian Process Optimization Kelley, Kyle P.; Ziatdinov, Maxim; Collins, Liam Small, Vol. 16, Issue 37 https://doi.org/10.1002/smll.202002878	journal	August 2020
ImageNet Large Scale Visual Recognition Challenge Russakovsky, Olga; Deng, Jia; Su, Hao International Journal of Computer Vision, Vol. 115, Issue 3 https://doi.org/10.1007/s11263-015-0816-y	journal	April 2015
Enhanced dielectric contrast in scattering-type scanning near-field optical microscopy Knoll, Bernhard; Keilmann, Fritz Optics Communications, Vol. 182, Issue 4-6 https://doi.org/10.1016/S0030-4018(00)00826-9	journal	August 2000
Artificial intelligence and pattern recognition techniques in microscope image processing and analysis Bonnet, Noël Advances in Imaging and Electron Physics https://doi.org/10.1016/S1076-5670(00)80020-8	book	January 2000
Machine learning based on holographic scattering spectrum for mixed pollutants analysis Duan, Qiannan; Xu, Zhaoyi; Zheng, Shourong Analytica Chimica Acta, Vol. 1143 https://doi.org/10.1016/j.aca.2020.10.060	journal	January 2021
Probing the local dielectric function of WS2 on an Au substrate by near field optical microscopy operating in the visible spectral range Garrity, Oisín; Rodriguez, Alvaro; Mueller, Niclas S. Applied Surface Science, Vol. 574 https://doi.org/10.1016/j.apsusc.2021.151672	journal	February 2022
PPINN: Parareal physics-informed neural network for time-dependent PDEs Meng, Xuhui; Li, Zhen; Zhang, Dongkun Computer Methods in Applied Mechanics and Engineering, Vol. 370 https://doi.org/10.1016/j.cma.2020.113250	journal	October 2020
Automated tip functionalization via machine learning in scanning probe microscopy Alldritt, Benjamin; Urtev, Fedor; Oinonen, Niko Computer Physics Communications, Vol. 273 https://doi.org/10.1016/j.cpc.2021.108258	journal	April 2022
Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations Raissi, M.; Perdikaris, P.; Karniadakis, G. E. Journal of Computational Physics, Vol. 378 https://doi.org/10.1016/j.jcp.2018.10.045	journal	February 2019
Some trends in microscope image processing Bonnet, Noël Micron, Vol. 35, Issue 8 https://doi.org/10.1016/j.micron.2004.04.006	journal	December 2004
Space-filling scan paths and Gaussian process-aided adaptive sampling for efficient surface measurements Yang, Chengfei; Peng, Chaoyang; Chen, Yuhang Precision Engineering, Vol. 54 https://doi.org/10.1016/j.precisioneng.2018.07.011	journal	October 2018
Fast and Accurate Uncertainty Estimation in Chemical Machine Learning Musil, Félix; Willatt, Michael J.; Langovoy, Mikhail A. Journal of Chemical Theory and Computation, Vol. 15, Issue 2 https://doi.org/10.1021/acs.jctc.8b00959	journal	November 2018
Combined Tip-Enhanced Raman Spectroscopy and Scattering-Type Scanning Near-Field Optical Microscopy Kusch, Patryk; Morquillas Azpiazu, Nieves; Mueller, Niclas S. The Journal of Physical Chemistry C, Vol. 122, Issue 28 https://doi.org/10.1021/acs.jpcc.8b03637	journal	June 2018
Deep Learning Enabled Strain Mapping of Single-Atom Defects in Two-Dimensional Transition Metal Dichalcogenides with Sub-Picometer Precision Lee, Chia-Hao; Khan, Abid; Luo, Di Nano Letters, Vol. 20, Issue 5 https://doi.org/10.1021/acs.nanolett.0c00269	journal	April 2020
Phonon Polaritons in Twisted Double-Layers of Hyperbolic van der Waals Crystals Zheng, Zebo; Sun, Fengsheng; Huang, Wuchao Nano Letters, Vol. 20, Issue 7 https://doi.org/10.1021/acs.nanolett.0c01627	journal	June 2020
Quantitative Nanoinfrared Spectroscopy of Anisotropic van der Waals Materials Ruta, Francesco L.; Sternbach, Aaron J.; Dieng, Adji B. Nano Letters, Vol. 20, Issue 11 https://doi.org/10.1021/acs.nanolett.0c02671	journal	September 2020
Automated Searching and Identification of Self-Organized Nanostructures Gordon, Oliver M.; Hodgkinson, Jo E. A.; Farley, Steff M. Nano Letters, Vol. 20, Issue 10 https://doi.org/10.1021/acs.nanolett.0c03213	journal	August 2020
Charge-Transfer Plasmon Polaritons at Graphene/α-RuCl ₃ Interfaces Rizzo, Daniel J.; Jessen, Bjarke S.; Sun, Zhiyuan Nano Letters, Vol. 20, Issue 12 https://doi.org/10.1021/acs.nanolett.0c03466	journal	November 2020
Amplitude- and Phase-Resolved Infrared Nanoimaging and Nanospectroscopy of Polaritons in a Liquid Environment Virmani, Divya; Bylinkin, Andrei; Dolado, Irene Nano Letters, Vol. 21, Issue 3 https://doi.org/10.1021/acs.nanolett.0c04108	journal	January 2021
Long-Lived Phonon Polaritons in Hyperbolic Materials Ni, Guangxin; McLeod, Alexander S.; Sun, Zhiyuan Nano Letters, Vol. 21, Issue 13 https://doi.org/10.1021/acs.nanolett.1c01562	journal	June 2021
Hybrid Tip-Enhanced Nanospectroscopy and Nanoimaging of Monolayer WSe ₂ with Local Strain Control Park, Kyoung-Duck; Khatib, Omar; Kravtsov, Vasily Nano Letters, Vol. 16, Issue 4 https://doi.org/10.1021/acs.nanolett.6b00238	journal	March 2016
Nanoscale Near-Field Tomography of Surface States on (Bi _0.5 Sb _0.5 ) ₂ Te ₃ Mooshammer, Fabian; Sandner, Fabian; Huber, Markus A. Nano Letters, Vol. 18, Issue 12 https://doi.org/10.1021/acs.nanolett.8b03008	journal	November 2018
Logarithm Diameter Scaling and Carrier Density Independence of One-Dimensional Luttinger Liquid Plasmon Wang, Sheng; Wu, Fanqi; Zhao, Sihan Nano Letters, Vol. 19, Issue 4 https://doi.org/10.1021/acs.nanolett.8b05031	journal	March 2019
Global Optimization of Dielectric Metasurfaces Using a Physics-Driven Neural Network Jiang, Jiaqi; Fan, Jonathan A. Nano Letters, Vol. 19, Issue 8 https://doi.org/10.1021/acs.nanolett.9b01857	journal	July 2019
Refractive Index-Based Control of Hyperbolic Phonon-Polariton Propagation Fali, Alireza; White, Samuel T.; Folland, Thomas G. Nano Letters, Vol. 19, Issue 11 https://doi.org/10.1021/acs.nanolett.9b02651	journal	September 2019
Photodegradation Protection in 2D In-Plane Heterostructures Revealed by Hyperspectral Nanoimaging: The Role of Nanointerface 2D Alloys Fali, Alireza; Zhang, Tianyi; Terry, Jason Patrick ACS Nano, Vol. 15, Issue 2 https://doi.org/10.1021/acsnano.0c06148	journal	January 2021
Bayesian Learning of Adatom Interactions from Atomically Resolved Imaging Data Valleti, Sai Mani Prudhvi; Zou, Qiang; Xue, Rui ACS Nano, Vol. 15, Issue 6 https://doi.org/10.1021/acsnano.0c10851	journal	June 2021
Automated and Autonomous Experiments in Electron and Scanning Probe Microscopy Kalinin, Sergei V.; Ziatdinov, Maxim; Hinkle, Jacob ACS Nano, Vol. 15, Issue 8 https://doi.org/10.1021/acsnano.1c02104	journal	July 2021
Revealing the Chemical Bonding in Adatom Arrays via Machine Learning of Hyperspectral Scanning Tunneling Spectroscopy Data Roccapriore, Kevin M.; Zou, Qiang; Zhang, Lizhi ACS Nano, Vol. 15, Issue 7 https://doi.org/10.1021/acsnano.1c02902	journal	June 2021
Deep Learning Analysis of Polaritonic Wave Images Xu, Suheng; McLeod, Alexander. S.; Chen, Xinzhong ACS Nano, Vol. 15, Issue 11 https://doi.org/10.1021/acsnano.1c07011	journal	October 2021
Exploring Causal Physical Mechanisms via Non-Gaussian Linear Models and Deep Kernel Learning: Applications for Ferroelectric Domain Structures Liu, Yongtao; Ziatdinov, Maxim; Kalinin, Sergei V. ACS Nano, Vol. 16, Issue 1 https://doi.org/10.1021/acsnano.1c09059	journal	December 2021
Autonomous Scanning Probe Microscopy in Situ Tip Conditioning through Machine Learning Rashidi, Mohammad; Wolkow, Robert A. ACS Nano, Vol. 12, Issue 6 https://doi.org/10.1021/acsnano.8b02208	journal	May 2018
Physics-Based Approach for a Neural Networks Enabled Design of All-Dielectric Metasurfaces Tanriover, Ibrahim; Hadibrata, Wisnu; Aydin, Koray ACS Photonics, Vol. 7, Issue 8 https://doi.org/10.1021/acsphotonics.0c00663	journal	July 2020
Machine Learning for Integrated Quantum Photonics Kudyshev, Zhaxylyk A.; Shalaev, Vladimir M.; Boltasseva, Alexandra ACS Photonics, Vol. 8, Issue 1 https://doi.org/10.1021/acsphotonics.0c00960	journal	December 2020
Elucidating the Behavior of Nanophotonic Structures through Explainable Machine Learning Algorithms Yeung, Christopher; Tsai, Ju-Ming; King, Brian ACS Photonics, Vol. 7, Issue 8 https://doi.org/10.1021/acsphotonics.0c01067	journal	July 2020
Machine Learning-Based Diffractive Image Analysis with Subwavelength Resolution Ghosh, Abantika; Roth, Diane J.; Nicholls, Luke H. ACS Photonics, Vol. 8, Issue 5 https://doi.org/10.1021/acsphotonics.1c00205	journal	April 2021
Hybrid Machine Learning for Scanning Near-Field Optical Spectroscopy Chen, Xinzhong; Yao, Ziheng; Xu, Suheng ACS Photonics, Vol. 8, Issue 10 https://doi.org/10.1021/acsphotonics.1c00915	journal	September 2021
Nonlocal Time-Resolved Terahertz Spectroscopy in the Near Field Pizzuto, Angela; Castro-Camus, Enrique; Wilson, William ACS Photonics, Vol. 8, Issue 10 https://doi.org/10.1021/acsphotonics.1c01367	journal	October 2021
Deep Learning Enhanced Mobile-Phone Microscopy Rivenson, Yair; Ceylan Koydemir, Hatice; Wang, Hongda ACS Photonics, Vol. 5, Issue 6 https://doi.org/10.1021/acsphotonics.8b00146	journal	March 2018
Far Infrared Synchrotron Near-Field Nanoimaging and Nanospectroscopy Khatib, Omar; Bechtel, Hans A.; Martin, Michael C. ACS Photonics, Vol. 5, Issue 7 https://doi.org/10.1021/acsphotonics.8b00565	journal	December 2017
A Deep Learning Approach for Objective-Driven All-Dielectric Metasurface Design An, Sensong; Fowler, Clayton; Zheng, Bowen ACS Photonics, Vol. 6, Issue 12 https://doi.org/10.1021/acsphotonics.9b00966	journal	November 2019
Quantifying Nanoscale Electromagnetic Fields in Near-Field Microscopy by Fourier Demodulation Analysis Mooshammer, Fabian; Huber, Markus A.; Sandner, Fabian ACS Photonics, Vol. 7, Issue 2 https://doi.org/10.1021/acsphotonics.9b01533	journal	January 2020
THz Near-Field Imaging of Extreme Subwavelength Metal Structures Chen, Xinzhong; Liu, Xiao; Guo, Xiangdong ACS Photonics, Vol. 7, Issue 3 https://doi.org/10.1021/acsphotonics.9b01534	journal	January 2020
Adiabatic Tip-Plasmon Focusing for Nano-Raman Spectroscopy Berweger, Samuel; Atkin, Joanna M.; Olmon, Robert L. The Journal of Physical Chemistry Letters, Vol. 1, Issue 24 https://doi.org/10.1021/jz101289z	journal	November 2010
Quantitative Measurement of Local Infrared Absorption and Dielectric Function with Tip-Enhanced Near-Field Microscopy Govyadinov, Alexander A.; Amenabar, Iban; Huth, Florian The Journal of Physical Chemistry Letters, Vol. 4, Issue 9 https://doi.org/10.1021/jz400453r	journal	April 2013
Infrared Nanoscopy of Dirac Plasmons at the Graphene–SiO ₂ Interface Fei, Zhe; Andreev, Gregory O.; Bao, Wenzhong Nano Letters, Vol. 11, Issue 11 https://doi.org/10.1021/nl202362d	journal	October 2011
Ultrafast and Nanoscale Plasmonic Phenomena in Exfoliated Graphene Revealed by Infrared Pump–Probe Nanoscopy Wagner, Martin; Fei, Zhe; McLeod, Alexander S. Nano Letters, Vol. 14, Issue 2 https://doi.org/10.1021/nl4042577	journal	January 2014
Recovery of Permittivity and Depth from Near-Field Data as a Step toward Infrared Nanotomography Govyadinov, Alexander A.; Mastel, Stefan; Golmar, Federico ACS Nano, Vol. 8, Issue 7 https://doi.org/10.1021/nn5016314	journal	June 2014
Mid-infrared Polaritonic Coupling between Boron Nitride Nanotubes and Graphene Xu, Xiaoji G.; Jiang, Jian-Hua; Gilburd, Leonid ACS Nano, Vol. 8, Issue 11 https://doi.org/10.1021/nn504093g	journal	November 2014
Near-field probing of vibrational absorption for chemical microscopy Knoll, B.; Keilmann, F. Nature, Vol. 399, Issue 6732 https://doi.org/10.1038/20154	journal	May 1999
Phonon-enhanced light–matter interaction at the nanometre scale Hillenbrand, R.; Taubner, T.; Keilmann, F. Nature, Vol. 418, Issue 6894 https://doi.org/10.1038/nature00899	journal	July 2002
Gate-tuning of graphene plasmons revealed by infrared nano-imaging Fei, Z.; Rodin, A. S.; Andreev, G. O. Nature, Vol. 487, Issue 7405 https://doi.org/10.1038/nature11253	journal	June 2012
Optical nano-imaging of gate-tunable graphene plasmons Chen, Jianing; Badioli, Michela; Alonso-González, Pablo Nature, Vol. 487, Issue 7405 https://doi.org/10.1038/nature11254	journal	June 2012
Fast automated analysis of strong gravitational lenses with convolutional neural networks Hezaveh, Yashar D.; Levasseur, Laurence Perreault; Marshall, Philip J. Nature, Vol. 548, Issue 7669 https://doi.org/10.1038/nature23463	journal	August 2017
Correlated insulator behaviour at half-filling in magic-angle graphene superlattices Cao, Yuan; Fatemi, Valla; Demir, Ahmet Nature, Vol. 556, Issue 7699 https://doi.org/10.1038/nature26154	journal	March 2018
Unconventional superconductivity in magic-angle graphene superlattices Cao, Yuan; Fatemi, Valla; Fang, Shiang Nature, Vol. 556, Issue 7699 https://doi.org/10.1038/nature26160	journal	March 2018
Deep learning massively accelerates super-resolution localization microscopy Ouyang, Wei; Aristov, Andrey; Lelek, Mickaël Nature Biotechnology, Vol. 36, Issue 5 https://doi.org/10.1038/nbt.4106	journal	April 2018
Organic structure determination using atomic-resolution scanning probe microscopy Gross, Leo; Mohn, Fabian; Moll, Nikolaj Nature Chemistry, Vol. 2, Issue 10 https://doi.org/10.1038/nchem.765	journal	August 2010
Atomic-scale observation of structural and electronic orders in the layered compound α-RuCl3 Ziatdinov, M.; Banerjee, A.; Maksov, A. Nature Communications, Vol. 7, Issue 1 https://doi.org/10.1038/ncomms13774	journal	December 2016
Spatial complexity due to bulk electronic nematicity in a superconducting underdoped cuprate Phillabaum, B.; Carlson, E. W.; Dahmen, K. A. Nature Communications, Vol. 3, Issue 1 https://doi.org/10.1038/ncomms1920	journal	January 2012
Searching for exotic particles in high-energy physics with deep learning Baldi, P.; Sadowski, P.; Whiteson, D. Nature Communications, Vol. 5, Issue 1 https://doi.org/10.1038/ncomms5308	journal	July 2014
Highly confined low-loss plasmons in graphene–boron nitride heterostructures Woessner, Achim; Lundeberg, Mark B.; Gao, Yuanda Nature Materials, Vol. 14, Issue 4 https://doi.org/10.1038/nmat4169	journal	December 2014
Polaritons in layered two-dimensional materials Low, Tony; Chaves, Andrey; Caldwell, Joshua D. Nature Materials, Vol. 16, Issue 2 https://doi.org/10.1038/nmat4792	journal	November 2016
Ultrafast multi-terahertz nano-spectroscopy with sub-cycle temporal resolution Eisele, M.; Cocker, T. L.; Huber, M. A. Nature Photonics, Vol. 8, Issue 11 https://doi.org/10.1038/nphoton.2014.225	journal	October 2014
Ultrafast optical switching of infrared plasmon polaritons in high-mobility graphene Ni, G. X.; Wang, L.; Goldflam, M. D. Nature Photonics, Vol. 10, Issue 4 https://doi.org/10.1038/nphoton.2016.45	journal	March 2016
Temporal correlations of superconductivity above the transition temperature in La2−xSrxCuO4 probed by terahertz spectroscopy Bilbro, L. S.; Aguilar, R. Valdés; Logvenov, G. Nature Physics, Vol. 7, Issue 4 https://doi.org/10.1038/nphys1912	journal	February 2011
Visualization of electron nematicity and unidirectional antiferroic fluctuations at high temperatures in NaFeAs Rosenthal, E. P.; Andrade, E. F.; Arguello, C. J. Nature Physics, Vol. 10, Issue 3 https://doi.org/10.1038/nphys2870	journal	February 2014
Nanotextured phase coexistence in the correlated insulator V2O3 McLeod, A. S.; van Heumen, E.; Ramirez, J. G. Nature Physics, Vol. 13, Issue 1 https://doi.org/10.1038/nphys3882	journal	September 2016
Machine learning phases of matter Carrasquilla, Juan; Melko, Roger G. Nature Physics, Vol. 13, Issue 5 https://doi.org/10.1038/nphys4035	journal	February 2017
Imaging the nanoscale phase separation in vanadium dioxide thin films at terahertz frequencies Stinson, H. T.; Sternbach, A.; Najera, O. Nature Communications, Vol. 9, Issue 1 https://doi.org/10.1038/s41467-018-05998-5	journal	September 2018
Scale-invariant magnetic textures in the strongly correlated oxide NdNiO3 Li, Jiarui; Pelliciari, Jonathan; Mazzoli, Claudio Nature Communications, Vol. 10, Issue 1 https://doi.org/10.1038/s41467-019-12502-0	journal	October 2019
Dictionary learning in Fourier-transform scanning tunneling spectroscopy Cheung, Sky C.; Shin, John Y.; Lau, Yenson Nature Communications, Vol. 11, Issue 1 https://doi.org/10.1038/s41467-020-14633-1	journal	February 2020
Femtosecond exciton dynamics in WSe2 optical waveguides Sternbach, Aaron J.; Latini, Simone; Chae, Sanghoon Nature Communications, Vol. 11, Issue 1 https://doi.org/10.1038/s41467-020-17335-w	journal	July 2020
Moiré metrology of energy landscapes in van der Waals heterostructures Halbertal, Dorri; Finney, Nathan R.; Sunku, Sai S. Nature Communications, Vol. 12, Issue 1 https://doi.org/10.1038/s41467-020-20428-1	journal	January 2021
Adaptive tip-enhanced nano-spectroscopy Lee, Dong Yun; Park, Chulho; Choi, Jinseong Nature Communications, Vol. 12, Issue 1 https://doi.org/10.1038/s41467-021-23818-1	journal	June 2021
Correlator convolutional neural networks as an interpretable architecture for image-like quantum matter data Miles, Cole; Bohrdt, Annabelle; Wu, Ruihan Nature Communications, Vol. 12, Issue 1 https://doi.org/10.1038/s41467-021-23952-w	journal	June 2021
Gate-tunable plasmons in mixed-dimensional van der Waals heterostructures Wang, Sheng; Yoo, SeokJae; Zhao, Sihan Nature Communications, Vol. 12, Issue 1 https://doi.org/10.1038/s41467-021-25269-0	journal	August 2021
Nanoscale lattice dynamics in hexagonal boron nitride moiré superlattices Moore, S. L.; Ciccarino, C. J.; Halbertal, D. Nature Communications, Vol. 12, Issue 1 https://doi.org/10.1038/s41467-021-26072-7	journal	September 2021
Deep neural networks for understanding noisy data applied to physical property extraction in scanning probe microscopy Borodinov, Nikolay; Neumayer, Sabine; Kalinin, Sergei V. npj Computational Materials, Vol. 5, Issue 1 https://doi.org/10.1038/s41524-019-0148-5	journal	February 2019
Imaging mechanism for hyperspectral scanning probe microscopy via Gaussian process modelling Ziatdinov, Maxim; Kim, Dohyung; Neumayer, Sabine npj Computational Materials, Vol. 6, Issue 1 https://doi.org/10.1038/s41524-020-0289-6	journal	March 2020
Ensemble learning-iterative training machine learning for uncertainty quantification and automated experiment in atom-resolved microscopy Ghosh, Ayana; Sumpter, Bobby G.; Dyck, Ondrej npj Computational Materials, Vol. 7, Issue 1 https://doi.org/10.1038/s41524-021-00569-7	journal	July 2021
Nano-imaging of strain-tuned stripe textures in a Mott crystal McLeod, A. S.; Wieteska, A.; Chiriaco, G. npj Quantum Materials, Vol. 6, Issue 1 https://doi.org/10.1038/s41535-021-00339-0	journal	May 2021
Multi-messenger nanoprobes of hidden magnetism in a strained manganite McLeod, A. S.; Zhang, Jingdi; Gu, M. Q. Nature Materials, Vol. 19, Issue 4 https://doi.org/10.1038/s41563-019-0533-y	journal	December 2019
Towards data-driven next-generation transmission electron microscopy Spurgeon, Steven R.; Ophus, Colin; Jones, Lewys Nature Materials https://doi.org/10.1038/s41563-020-00833-z	journal	October 2020
Broad spectral tuning of ultra-low-loss polaritons in a van der Waals crystal by intercalation Taboada-Gutiérrez, Javier; Álvarez-Pérez, Gonzalo; Duan, Jiahua Nature Materials, Vol. 19, Issue 9 https://doi.org/10.1038/s41563-020-0665-0	journal	April 2020
Configurable phonon polaritons in twisted α-MoO3 Chen, Mingyuan; Lin, Xiao; Dinh, Thao H. Nature Materials, Vol. 19, Issue 12 https://doi.org/10.1038/s41563-020-0732-6	journal	July 2020
Radiative control of dark excitons at room temperature by nano-optical antenna-tip Purcell effect Park, Kyoung-Duck; Jiang, Tao; Clark, Genevieve Nature Nanotechnology, Vol. 13, Issue 1 https://doi.org/10.1038/s41565-017-0003-0	journal	November 2017
Single-molecule resonance Raman effect in a plasmonic nanocavity Jaculbia, Rafael B.; Imada, Hiroshi; Miwa, Kuniyuki Nature Nanotechnology, Vol. 15, Issue 2 https://doi.org/10.1038/s41565-019-0614-8	journal	January 2020
Visualization of moiré superlattices McGilly, Leo J.; Kerelsky, Alexander; Finney, Nathan R. Nature Nanotechnology, Vol. 15, Issue 7 https://doi.org/10.1038/s41565-020-0708-3	journal	June 2020
Sub-nanometre resolution in single-molecule photoluminescence imaging Yang, Ben; Chen, Gong; Ghafoor, Atif Nature Photonics, Vol. 14, Issue 11 https://doi.org/10.1038/s41566-020-0677-y	journal	August 2020
Deep learning for the design of photonic structures Ma, Wei; Liu, Zhaocheng; Kudyshev, Zhaxylyk A. Nature Photonics, Vol. 15, Issue 2 https://doi.org/10.1038/s41566-020-0685-y	journal	October 2020
Coexisting first- and second-order electronic phase transitions in a correlated oxide Post, K. W.; McLeod, A. S.; Hepting, M. Nature Physics, Vol. 14, Issue 10 https://doi.org/10.1038/s41567-018-0201-1	journal	July 2018
Moiré engineering of electronic phenomena in correlated oxides Chen, Xinzhong; Fan, Xiaodong; Li, Lin Nature Physics, Vol. 16, Issue 6 https://doi.org/10.1038/s41567-020-0865-1	journal	April 2020
Deep moiré potentials in twisted transition metal dichalcogenide bilayers Shabani, Sara; Halbertal, Dorri; Wu, Wenjing Nature Physics https://doi.org/10.1038/s41567-021-01174-7	journal	February 2021
Fundamental limits to graphene plasmonics Ni, G. X.; McLeod, A. S.; Sun, Z. Nature, Vol. 557, Issue 7706 https://doi.org/10.1038/s41586-018-0136-9	journal	May 2018
In-plane anisotropic and ultra-low-loss polaritons in a natural van der Waals crystal Ma, Weiliang; Alonso-González, Pablo; Li, Shaojuan Nature, Vol. 562, Issue 7728 https://doi.org/10.1038/s41586-018-0618-9	journal	October 2018
Machine learning in electronic-quantum-matter imaging experiments Zhang, Yi; Mesaros, A.; Fujita, K. Nature, Vol. 570, Issue 7762 https://doi.org/10.1038/s41586-019-1319-8	journal	June 2019
Origins of structural and electronic transitions in disordered silicon Deringer, Volker L.; Bernstein, Noam; Csányi, Gábor Nature, Vol. 589, Issue 7840 https://doi.org/10.1038/s41586-020-03072-z	journal	January 2021
Topological polaritons and photonic magic angles in twisted α-MoO3 bilayers Hu, Guangwei; Ou, Qingdong; Si, Guangyuan Nature, Vol. 582, Issue 7811 https://doi.org/10.1038/s41586-020-2359-9	journal	June 2020
Efficient Fizeau drag from Dirac electrons in monolayer graphene Zhao, Wenyu; Zhao, Sihan; Li, Hongyuan Nature, Vol. 594, Issue 7864 https://doi.org/10.1038/s41586-021-03574-4	journal	June 2021
Interface nano-optics with van der Waals polaritons Zhang, Qing; Hu, Guangwei; Ma, Weiliang Nature, Vol. 597, Issue 7875 https://doi.org/10.1038/s41586-021-03581-5	journal	September 2021
Fizeau drag in graphene plasmonics Dong, Y.; Xiong, L.; Phinney, I. Y. Nature, Vol. 594, Issue 7864 https://doi.org/10.1038/s41586-021-03640-x	journal	June 2021
Deep learning enables cross-modality super-resolution in fluorescence microscopy Wang, Hongda; Rivenson, Yair; Jin, Yiyin Nature Methods, Vol. 16, Issue 1 https://doi.org/10.1038/s41592-018-0239-0	journal	December 2018
Differentiable biology: using deep learning for biophysics-based and data-driven modeling of molecular mechanisms AlQuraishi, Mohammed; Sorger, Peter K. Nature Methods, Vol. 18, Issue 10 https://doi.org/10.1038/s41592-021-01283-4	journal	October 2021
Computed terahertz near-field mapping of molecular resonances of lactose stereo-isomer impurities with sub-attomole sensitivity Moon, Kiwon; Do, Youngwoong; Park, Hongkyu Scientific Reports, Vol. 9, Issue 1 https://doi.org/10.1038/s41598-019-53366-0	journal	November 2019
Artificial-intelligence-driven scanning probe microscopy Krull, A.; Hirsch, P.; Rother, C. Communications Physics, Vol. 3, Issue 1 https://doi.org/10.1038/s42005-020-0317-3	journal	March 2020
Neural network-based order parameter for phase transitions and its applications in high-entropy alloys Yin, Junqi; Pei, Zongrui; Gao, Michael C. Nature Computational Science, Vol. 1, Issue 10 https://doi.org/10.1038/s43588-021-00139-3	journal	October 2021
High-resolution quantitative determination of dielectric function by using scattering scanning near-field optical microscopy Tranca, D. E.; Stanciu, S. G.; Hristu, R. Scientific Reports, Vol. 5, Issue 1 https://doi.org/10.1038/srep11876	journal	July 2015
The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics Yao, Kun; Herr, John E.; Toth, David W. Chemical Science, Vol. 9, Issue 8 https://doi.org/10.1039/C7SC04934J	journal	January 2018
An artificial intelligence atomic force microscope enabled by machine learning Huang, Boyuan; Li, Zhenghao; Li, Jiangyu Nanoscale, Vol. 10, Issue 45 https://doi.org/10.1039/C8NR06734A	journal	January 2018
Tip-enhanced Raman scattering Bailo, Elena; Deckert, Volker Chemical Society Reviews, Vol. 37, Issue 5 https://doi.org/10.1039/b705967c	journal	January 2008
Pure optical contrast in scattering-type scanning near-field microscopy HillenbRand, R.; Knoll, B.; Keilmann, F. Journal of Microscopy, Vol. 202, Issue 1 https://doi.org/10.1046/j.1365-2818.2001.00794.x	journal	April 2001
Characterization of optically dense, doped semiconductors by reflection THz time domain spectroscopy Jeon, Tae-In; Grischkowsky, D. Applied Physics Letters, Vol. 72, Issue 23 https://doi.org/10.1063/1.121531	journal	June 1998
Origin of low dielectric constant of carbon-incorporated silicon oxide film deposited by plasma enhanced chemical vapor deposition Kim, Jin Yong; Hwang, Moo Sung; Kim, Yoon-Hae Journal of Applied Physics, Vol. 90, Issue 5 https://doi.org/10.1063/1.1388861	journal	September 2001
Generalized spectral method for near-field optical microscopy Jiang, B. -Y.; Zhang, L. M.; Castro Neto, A. H. Journal of Applied Physics, Vol. 119, Issue 5 https://doi.org/10.1063/1.4941343	journal	February 2016
Narrow-band near-field nanoscopy in the spectral range from 1.3 to 8.5 THz Kuschewski, F.; von Ribbeck, H. -G.; Döring, J. Applied Physics Letters, Vol. 108, Issue 11 https://doi.org/10.1063/1.4943793	journal	March 2016
Tutorial: An introduction to terahertz time domain spectroscopy (THz-TDS) Neu, Jens; Schmuttenmaer, Charles A. Journal of Applied Physics, Vol. 124, Issue 23 https://doi.org/10.1063/1.5047659	journal	December 2018
Scanning tunneling state recognition with multi-class neural network ensembles Gordon, O.; D’Hondt, P.; Knijff, L. Review of Scientific Instruments, Vol. 90, Issue 10 https://doi.org/10.1063/1.5099590	journal	October 2019
Machine-learning-assisted metasurface design for high-efficiency thermal emitter optimization Kudyshev, Zhaxylyk A.; Kildishev, Alexander V.; Shalaev, Vladimir M. Applied Physics Reviews, Vol. 7, Issue 2 https://doi.org/10.1063/1.5134792	journal	June 2020
Machine learning-based multidomain processing for texture-based image segmentation and analysis Borodinov, Nikolay; Tsai, Wan-Yu; Korolkov, Vladimir V. Applied Physics Letters, Vol. 116, Issue 4 https://doi.org/10.1063/1.5135328	journal	January 2020
The Raspberry Pi auto-aligner: Machine learning for automated alignment of laser beams Mathew, Renju S.; O’Donnell, Roshan; Pizzey, Danielle Review of Scientific Instruments, Vol. 92, Issue 1 https://doi.org/10.1063/5.0032588	journal	January 2021
Optical constants from scattering-type scanning near-field optical microscope Guo, Xiao; Bertling, Karl; Rakić, Aleksandar D. Applied Physics Letters, Vol. 118, Issue 4 https://doi.org/10.1063/5.0036872	journal	January 2021
Ultrabroadband infrared nanospectroscopic imaging Bechtel, H. A.; Muller, E. A.; Olmon, R. L. Proceedings of the National Academy of Sciences, Vol. 111, Issue 20 https://doi.org/10.1073/pnas.1400502111	journal	May 2014
Machine learning for quantum matter Carrasquilla, Juan Advances in Physics: X, Vol. 5, Issue 1 https://doi.org/10.1080/23746149.2020.1797528	journal	January 2020
Artificial intelligence for photonics and photonic materials Piccinotti, Davide; MacDonald, Kevin F.; A. Gregory, Simon Reports on Progress in Physics, Vol. 84, Issue 1 https://doi.org/10.1088/1361-6633/abb4c7	journal	December 2020
Embedding human heuristics in machine-learning-enabled probe microscopy Gordon, Oliver M.; Junqueira, Filipe L. Q.; Moriarty, Philip J. Machine Learning: Science and Technology, Vol. 1, Issue 1 https://doi.org/10.1088/2632-2153/ab42ec	journal	February 2020
Machine learning at the (sub)atomic scale: next generation scanning probe microscopy Gordon, Oliver M.; Moriarty, Philip J. Machine Learning: Science and Technology, Vol. 1, Issue 2 https://doi.org/10.1088/2632-2153/ab7d2f	journal	May 2020
Improving the segmentation of scanning probe microscope images using convolutional neural networks Farley, Steff; Hodgkinson, Jo E. A.; Gordon, Oliver M. Machine Learning: Science and Technology, Vol. 2, Issue 1 https://doi.org/10.1088/2632-2153/abc81c	journal	December 2020
SSNOMBACTER: A collection of scattering-type scanning near-field optical microscopy and atomic force microscopy images of bacterial cells Lucidi, Massimiliano; Tranca, Denis E.; Nichele, Lorenzo GigaScience, Vol. 9, Issue 11 https://doi.org/10.1093/gigascience/giaa129	journal	November 2020
Microscopy Hacks: development of various techniques to assist quantitative nanoanalysis and advanced electron microscopy Watanabe, Masashi Microscopy, Vol. 62, Issue 2 https://doi.org/10.1093/jmicro/dfs085	journal	March 2013
Near-field microscopy by elastic light scattering from a tip Keilmann, Fritz; Hillenbrand, Rainer Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, Vol. 362, Issue 1817 https://doi.org/10.1098/rsta.2003.1347	journal	April 2004
Visualizing strange metallic correlations in the two-dimensional Fermi-Hubbard model with artificial intelligence Khatami, Ehsan; Guardado-Sanchez, Elmer; Spar, Benjamin M. Physical Review A, Vol. 102, Issue 3 https://doi.org/10.1103/PhysRevA.102.033326	journal	September 2020
Validity of Machine Learning in the Quantitative Analysis of Complex Scanning Near-Field Optical Microscopy Signals Using Simulated Data Chen, Xinzhong; Ren, Richard; Liu, Mengkun Physical Review Applied, Vol. 15, Issue 1 https://doi.org/10.1103/PhysRevApplied.15.014001	journal	January 2021
Structural phase transitions in a MoWSe 2 monolayer: Molecular dynamics simulations and variational autoencoder analysis Rajak, Pankaj; Krishnamoorthy, Aravind; Nakano, Aiichiro Physical Review B, Vol. 100, Issue 1 https://doi.org/10.1103/PhysRevB.100.014108	journal	July 2019
Dynamics of electronically phase-separated states in the double exchange model Luo, Jing; Chern, Gia-Wei Physical Review B, Vol. 103, Issue 11 https://doi.org/10.1103/PhysRevB.103.115137	journal	March 2021
Phase diagram study of a two-dimensional frustrated antiferromagnet via unsupervised machine learning Acevedo, S.; Arlego, M.; Lamas, C. A. Physical Review B, Vol. 103, Issue 13 https://doi.org/10.1103/PhysRevB.103.134422	journal	April 2021
Nanoscale chemical phase separation in FeTe 0.55 Se 0.45 as seen via scanning tunneling spectroscopy He, Xiaobo; Li, Guorong; Zhang, Jiandi Physical Review B, Vol. 83, Issue 22 https://doi.org/10.1103/PhysRevB.83.220502	journal	June 2011
Visualizing the charge density wave transition in 2 H - NbSe 2 in real space Arguello, C. J.; Chockalingam, S. P.; Rosenthal, E. P. Physical Review B, Vol. 89, Issue 23 https://doi.org/10.1103/PhysRevB.89.235115	journal	June 2014
Model for quantitative tip-enhanced spectroscopy and the extraction of nanoscale-resolved optical constants McLeod, Alexander S.; Kelly, P.; Goldflam, M. D. Physical Review B, Vol. 90, Issue 8 https://doi.org/10.1103/PhysRevB.90.085136	journal	August 2014
Phase transition in bulk single crystals and thin films of V O 2 by nanoscale infrared spectroscopy and imaging Liu, Mengkun; Sternbach, Aaron J.; Wagner, Martin Physical Review B, Vol. 91, Issue 24 https://doi.org/10.1103/PhysRevB.91.245155	journal	June 2015
Discovering phase transitions with unsupervised learning Wang, Lei Physical Review B, Vol. 94, Issue 19 https://doi.org/10.1103/PhysRevB.94.195105	journal	November 2016
Dielectric properties of amorphous phase-change materials Chen, C.; Jost, P.; Volker, H. Physical Review B, Vol. 95, Issue 9 https://doi.org/10.1103/PhysRevB.95.094111	journal	March 2017
Scattering of electromagnetic waves from a cone with conformal mapping: Application to scanning near-field optical microscope Chui, S. T.; Chen, Xinzhong; Liu, Mengkun Physical Review B, Vol. 97, Issue 8 https://doi.org/10.1103/PhysRevB.97.081406	journal	February 2018
Uncertainty-aware machine learning for high energy physics Ghosh, Aishik; Nachman, Benjamin; Whiteson, Daniel Physical Review D, Vol. 104, Issue 5 https://doi.org/10.1103/PhysRevD.104.056026	journal	September 2021
Jet substructure classification in high-energy physics with deep neural networks Baldi, Pierre; Bauer, Kevin; Eng, Clara Physical Review D, Vol. 93, Issue 9 https://doi.org/10.1103/PhysRevD.93.094034	journal	May 2016
Jet flavor classification in high-energy physics with deep neural networks Guest, Daniel; Collado, Julian; Baldi, Pierre Physical Review D, Vol. 94, Issue 11 https://doi.org/10.1103/PhysRevD.94.112002	journal	December 2016
Unsupervised learning of phase transitions: From principal component analysis to variational autoencoders Wetzel, Sebastian J. Physical Review E, Vol. 96, Issue 2 https://doi.org/10.1103/PhysRevE.96.022140	journal	August 2017
Physics-informed machine learning approach for reconstructing Reynolds stress modeling discrepancies based on DNS data Wang, Jian-Xun; Wu, Jin-Long; Xiao, Heng Physical Review Fluids, Vol. 2, Issue 3 https://doi.org/10.1103/PhysRevFluids.2.034603	journal	March 2017
Electronic Phase Separation in the Slightly Underdoped Iron Pnictide Superconductor Ba 1 − x K x Fe 2 As 2 Park, J. T.; Inosov, D. S.; Niedermayer, Ch. Physical Review Letters, Vol. 102, Issue 11 https://doi.org/10.1103/PhysRevLett.102.117006	journal	March 2009
Nanoscale Proximity Effect in the High-Temperature Superconductor Bi 2 Sr 2 CaCu 2 O 8 + δ Using a Scanning Tunneling Microscope Parker, Colin V.; Pushp, Aakash; Pasupathy, Abhay N. Physical Review Letters, Vol. 104, Issue 11 https://doi.org/10.1103/PhysRevLett.104.117001	journal	March 2010
Long-Wavelength Local Density of States Oscillations Near Graphene Step Edges Xue, Jiamin; Sanchez-Yamagishi, Javier; Watanabe, K. Physical Review Letters, Vol. 108, Issue 1 https://doi.org/10.1103/PhysRevLett.108.016801	journal	January 2012
KFe 2 Se 2 is the Parent Compound of K-Doped Iron Selenide Superconductors Li, Wei; Ding, Hao; Li, Zhi Physical Review Letters, Vol. 109, Issue 5 https://doi.org/10.1103/PhysRevLett.109.057003	journal	July 2012
Anisotropic Electronic State via Spontaneous Phase Separation in Strained Vanadium Dioxide Films Liu, M. K.; Wagner, M.; Abreu, E. Physical Review Letters, Vol. 111, Issue 9 https://doi.org/10.1103/PhysRevLett.111.096602	journal	August 2013
Quasiparticle Interference, Quasiparticle Interactions, and the Origin of the Charge Density Wave in 2 H − NbSe 2 Arguello, C. J.; Rosenthal, E. P.; Andrade, E. F. Physical Review Letters, Vol. 114, Issue 3 https://doi.org/10.1103/PhysRevLett.114.037001	journal	January 2015
Random Field Driven Spatial Complexity at the Mott Transition in VO 2 Liu, Shuo; Phillabaum, B.; Carlson, E. W. Physical Review Letters, Vol. 116, Issue 3 https://doi.org/10.1103/PhysRevLett.116.036401	journal	January 2016
Discovering Physical Concepts with Neural Networks Iten, Raban; Metger, Tony; Wilming, Henrik Physical Review Letters, Vol. 124, Issue 1 https://doi.org/10.1103/PhysRevLett.124.010508	journal	January 2020
Unsupervised Phase Discovery with Deep Anomaly Detection Kottmann, Korbinian; Huembeli, Patrick; Lewenstein, Maciej Physical Review Letters, Vol. 125, Issue 17 https://doi.org/10.1103/PhysRevLett.125.170603	journal	October 2020
Arrested Phase Separation in Double-Exchange Models: Large-Scale Simulation Enabled by Machine Learning Zhang, Puhan; Chern, Gia-Wei Physical Review Letters, Vol. 127, Issue 14 https://doi.org/10.1103/PhysRevLett.127.146401	journal	September 2021
Classifying surface probe images in strongly correlated electronic systems via machine learning Burzawa, L.; Liu, S.; Carlson, E. W. Physical Review Materials, Vol. 3, Issue 3 https://doi.org/10.1103/PhysRevMaterials.3.033805	journal	March 2019
Sparse sampling for fast quasiparticle-interference mapping Oppliger, Jens; Natterer, Fabian Donat Physical Review Research, Vol. 2, Issue 2 https://doi.org/10.1103/PhysRevResearch.2.023117	journal	May 2020
Machine learning holographic mapping by neural network renormalization group Hu, Hong-Ye; Li, Shuo-Hui; Wang, Lei Physical Review Research, Vol. 2, Issue 2 https://doi.org/10.1103/PhysRevResearch.2.023369	journal	June 2020
Electrodynamics of high- T c superconductors Basov, D. N.; Timusk, T. Reviews of Modern Physics, Vol. 77, Issue 2 https://doi.org/10.1103/RevModPhys.77.721	journal	August 2005
Electrodynamics of correlated electron materials Basov, D. N.; Averitt, Richard D.; van der Marel, Dirk Reviews of Modern Physics, Vol. 83, Issue 2 https://doi.org/10.1103/RevModPhys.83.471	journal	June 2011
Machine learning and the physical sciences Carleo, Giuseppe; Cirac, Ignacio; Cranmer, Kyle Reviews of Modern Physics, Vol. 91, Issue 4 https://doi.org/10.1103/RevModPhys.91.045002	journal	December 2019
Face recognition: a convolutional neural-network approach Lawrence, S.; Giles, C. L. IEEE Transactions on Neural Networks, Vol. 8, Issue 1 https://doi.org/10.1109/72.554195	journal	January 1997
Thermal Tuning of High-$T_{c}$ Superconducting Bi$_{2}$Sr $_{2}$CaCu$_{2}$ O$_{8+\delta }$ Terahertz Metamaterial Kalhor, S.; Ghanaatshoar, M.; Kashiwagi, T. IEEE Photonics Journal, Vol. 9, Issue 5 https://doi.org/10.1109/JPHOT.2017.2754465	journal	October 2017
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches Bioucas-Dias, José M.; Plaza, Antonio; Dobigeon, Nicolas IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 5, Issue 2 https://doi.org/10.1109/JSTARS.2012.2194696	journal	April 2012
Multi-Fidelity Physics-Constrained Neural Network and Its Application in Materials Modeling Liu, Dehao; Wang, Yan Journal of Mechanical Design, Vol. 141, Issue 12 https://doi.org/10.1115/1.4044400	journal	September 2019
Electrodynamics of Solids: Optical Properties of Electrons in Matter Dressel, Martin; Gruener, George; Bertsch, George F. American Journal of Physics, Vol. 70, Issue 12 https://doi.org/10.1119/1.1516200	journal	December 2002
Nanophotonic particle simulation and inverse design using artificial neural networks Peurifoy, John; Shen, Yichen; Jing, Li Science Advances, Vol. 4, Issue 6 https://doi.org/10.1126/sciadv.aar4206	journal	June 2018
Transient exciton-polariton dynamics in WSe ₂ by ultrafast near-field imaging Mrejen, M.; Yadgarov, L.; Levanon, A. Science Advances, Vol. 5, Issue 2 https://doi.org/10.1126/sciadv.aat9618	journal	February 2019
Ultrafast nonlocal collective dynamics of Kane plasmon-polaritons in a narrow-gap semiconductor Charnukha, A.; Sternbach, A.; Stinson, H. T. Science Advances, Vol. 5, Issue 8 https://doi.org/10.1126/sciadv.aau9956	journal	August 2019
Tip-enhanced strong coupling spectroscopy, imaging, and control of a single quantum emitter Park, Kyoung-Duck; May, Molly A.; Leng, Haixu Science Advances, Vol. 5, Issue 7 https://doi.org/10.1126/sciadv.aav5931	journal	July 2019
Automated structure discovery in atomic force microscopy Alldritt, Benjamin; Hapala, Prokop; Oinonen, Niko Science Advances, Vol. 6, Issue 9 https://doi.org/10.1126/sciadv.aay6913	journal	February 2020
Ultrahigh-resolution scanning microwave impedance microscopy of moiré lattices and superstructures Lee, Kyunghoon; Utama, M. Iqbal Bakti; Kahn, Salman Science Advances, Vol. 6, Issue 50 https://doi.org/10.1126/sciadv.abd1919	journal	December 2020
Exploring order parameters and dynamic processes in disordered systems via variational autoencoders Kalinin, Sergei V.; Dyck, Ondrej; Jesse, Stephen Science Advances, Vol. 7, Issue 17 https://doi.org/10.1126/sciadv.abd5084	journal	April 2021
Imaging Quasiparticle Interference in Bi₂Sr₂CaCu₂O_8+δ Hoffman, J. E.; McElroy, K.; Lee, D.-H. Science, Vol. 297, Issue 5584, p. 1148-1151 https://doi.org/10.1126/science.1072640	journal	July 2002
Mott Transition in VO2 Revealed by Infrared Spectroscopy and Nano-Imaging Qazilbash, M. M.; Brehm, M.; Chae, B. -G. Science, Vol. 318, Issue 5857 https://doi.org/10.1126/science.1150124	journal	December 2007
Tunable Phonon Polaritons in Atomically Thin van der Waals Crystals of Boron Nitride Dai, S.; Fei, Z.; Ma, Q. Science, Vol. 343, Issue 6175 https://doi.org/10.1126/science.1246833	journal	March 2014
Polaritons in van der Waals materials Basov, D. N.; Fogler, M. M.; Garcia de Abajo, F. J. Science, Vol. 354, Issue 6309 https://doi.org/10.1126/science.aag1992	journal	October 2016
Photonic crystals for nano-light in moiré graphene superlattices Sunku, S. S.; Ni, G. X.; Jiang, B. Y. Science, Vol. 362, Issue 6419 https://doi.org/10.1126/science.aau5144	journal	December 2018
Programmable hyperbolic polaritons in van der Waals semiconductors Sternbach, A. J.; Chae, S. H.; Latini, S. Science, Vol. 371, Issue 6529 https://doi.org/10.1126/science.abe9163	journal	February 2021
Review of recent progress on THz spectroscopy of quantum materials: superconductors, magnetic and topological materials Bera, Arnab; Bera, Satyabrata; Kalimuddin, Sk The European Physical Journal Special Topics, Vol. 230, Issue 23 https://doi.org/10.1140/epjs/s11734-021-00216-8	journal	July 2021
Analytical model for quantitative prediction of material contrasts in scattering-type near-field optical microscopy Cvitkovic, A.; Ocelic, N.; Hillenbrand, R. Optics Express, Vol. 15, Issue 14 https://doi.org/10.1364/OE.15.008550	journal	January 2007
Substrate-enhanced infrared near-field spectroscopy Aizpurua, Javier; Taubner, Thomas; García de Abajo, F. Javier Optics Express, Vol. 16, Issue 3 https://doi.org/10.1364/OE.16.001529	journal	January 2008
Quasi-analytical model for scattering infrared near-field microscopy on layered systems Hauer, Benedikt; Engelhardt, Andreas P.; Taubner, Thomas Optics Express, Vol. 20, Issue 12 https://doi.org/10.1364/OE.20.013173	journal	January 2012
Machine-learning techniques for fast and accurate feature localization in holograms of colloidal particles Hannel, Mark D.; Abdulali, Aidan; O’Brien, Michael Optics Express, Vol. 26, Issue 12 https://doi.org/10.1364/OE.26.015221	journal	January 2018
Photo-induced terahertz near-field dynamics of graphene/InAs heterostructures Yao, Ziheng; Semenenko, Vyacheslav; Zhang, Jiawei Optics Express, Vol. 27, Issue 10 https://doi.org/10.1364/OE.27.013611	journal	January 2019
Hyperspectral time-domain terahertz nano-imaging Aghamiri, Neda Alsadat; Huth, Florian; Huber, Andreas J. Optics Express, Vol. 27, Issue 17 https://doi.org/10.1364/OE.27.024231	journal	January 2019
Deep learning for accelerated all-dielectric metasurface design Nadell, Christian C.; Huang, Bohao; Malof, Jordan M. Optics Express, Vol. 27, Issue 20 https://doi.org/10.1364/OE.27.027523	journal	January 2019
Machine learning approach for computing optical properties of a photonic crystal fiber Chugh, Sunny; Gulistan, Aamir; Ghosh, Souvik Optics Express, Vol. 27, Issue 25 https://doi.org/10.1364/OE.27.036414	journal	January 2019
Physics-informed neural networks for inverse problems in nano-optics and metamaterials Chen, Yuyao; Lu, Lu; Karniadakis, George Em Optics Express, Vol. 28, Issue 8 https://doi.org/10.1364/OE.384875	journal	January 2020
Machine learning and evolutionary algorithm studies of graphene metamaterials for optimized plasmon-induced transparency Zhang, Tian; Liu, Qi; Dan, Yihang Optics Express, Vol. 28, Issue 13 https://doi.org/10.1364/OE.389231	journal	January 2020
Mono-crystalline gold platelets: a high-quality platform for surface plasmon polaritons Kaltenecker, Korbinian J.; Krauss, Enno; Casses, Laura Nanophotonics, Vol. 9, Issue 2 https://doi.org/10.1515/nanoph-2019-0362	journal	February 2020
Tip-enhanced photoluminescence nano-spectroscopy and nano-imaging Lee, Hyeongwoo; Lee, Dong Yun; Kang, Min Gu Nanophotonics, Vol. 9, Issue 10 https://doi.org/10.1515/nanoph-2020-0079	journal	May 2020
Polariton panorama Basov, D. N.; Asenjo-Garcia, Ana; Schuck, P. James Nanophotonics, Vol. 10, Issue 1 https://doi.org/10.1515/nanoph-2020-0449	journal	November 2020
An Introduction to Variational Autoencoders Kingma, Diederik P.; Welling, Max Foundations and Trends® in Machine Learning, Vol. 12, Issue 4 https://doi.org/10.1561/2200000056	journal	January 2019
Detecting nematic order in STM/STS data with artificial intelligence Goetz, Jeremy B.; Zhang, Yi; Lawler, Michael SciPost Physics, Vol. 8, Issue 6 https://doi.org/10.21468/SciPostPhys.8.6.087	journal	June 2020
Variational Autoencoder Reconstruction of Complex Many-Body Physics Luchnikov, Ilia A.; Ryzhov, Alexander; Stas, Pieter-Jan Entropy, Vol. 21, Issue 11 https://doi.org/10.3390/e21111091	journal	November 2019
Basic Reinforcement Learning Techniques to Control the Intensity of a Seeded Free-Electron Laser Bruchon, Niky; Fenu, Gianfranco; Gaio, Giulio Electronics, Vol. 9, Issue 5 https://doi.org/10.3390/electronics9050781	journal	May 2020
Complex Deep Learning with Quantum Optics Manzalini, Antonio Quantum Reports, Vol. 1, Issue 1 https://doi.org/10.3390/quantum1010011	journal	July 2019

Similar Records

Bolometric Superconducting Optical Nanoscopy (BOSON)

Journal Article · Thu Jul 24 20:00:00 EDT 2025 · Physical Review. X · OSTI ID:3009085

Ultrasensitive Tip- and Antenna-Enhanced Infrared Nanoscopy of Protein Complexes

Journal Article · Thu Jul 18 00:00:00 EDT 2019 · Journal of Physical Chemistry C · OSTI ID:1571484

Magnetic field driven emergent phenomena: Insights from magneto-optics and nanoscopy

Journal Article · Thu Sep 11 20:00:00 EDT 2025 · Progress in Quantum Electronics · OSTI ID:2589351

Machine Learning for Optical Scanning Probe Nanoscopy

Citation Formats

References (208)

Similar Records

Related Subjects