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At least 919 records · Page 51

Time‐Lapse Image Classification Using a Diffractive Neural Network

Diffractive deep neural networks (D 2 NNs), comprised of spatially engineered passive surfaces, collectively process optical input information at the speed of light propagation through a thin diffractive volume, without any external computing power. Diffractive networks were demonstrated to achieve all‐optical object classification and perform universal linear transformations. Herein, a “time‐lapse” image classification scheme using a diffractive network is demonstrated for the first time, significantly advancing its classification accuracy and generalization performance on complex input objects by using the lateral movements of the input objects and/or the diffractive network, relative to each other. In a different context, such relative movements of the objects and/or the camera are routinely being used for image super‐resolution applications; inspired by their success, a time‐lapse diffractive network is designed to benefit from the complementary information content created by controlled or random lateral shifts. The design space and performance limits of time‐lapse diffractive networks are numerically explored, revealing a blind testing accuracy of 62.03% on the optical classification of objects from the CIFAR‐10 dataset. This constitutes the highest inference accuracy achieved so far using a single diffractive network on the CIFAR‐10 dataset. Time‐lapse diffractive networks will be broadly useful for the spatiotemporal analysis of input signals using all‐optical processors.

36 MATERIALS SCIENCE↗

High Cooperativity Using a Confocal-Cavity–QED Microscope

Cavity quantum electrodynamics (QED) with cooperativity far greater than unity enables high-fidelity quantum sensing and information processing. The high-cooperativity regime is often reached through the use of short single-mode resonators. More complicated multimode resonators, such as the near-confocal optical Fabry-Pérot cavity, can provide intracavity atomic imaging in addition to high cooperativity. This capability has recently proved important for exploring quantum many-body physics in the driven-dissipative setting. In this work, we show that a confocal-cavity–QED microscope can realize cooperativity in excess of 110. This cooperativity is on par with the very best single-mode cavities (which are far shorter) and 21 times greater than single-mode resonators of similar length and mirror radii. The 1.7-µm imaging resolution is naturally identical to the photon-mediated interaction range. We measure these quantities by determining the threshold of cavity superradiance when small optically tweezed BoseEinstein condensates are pumped at various intracavity locations. Transmission measurements of an ex situ cavity corroborate these results. We provide a theoretical description that shows how cooperativity enhancement arises from the dispersive coupling to the atoms of many near-degenerate modes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Spectroscopic Fourth-order Coronagraph for the Characterization of Terrestrial Planets at Small Angular Separations from Host Stars

We propose a new approach for high-contrast imaging at the diffraction limit using segmented telescopes in a modest observation bandwidth. This concept, named “spectroscopic fourth-order coronagraphy,” is based on a fourth-order coronagraph with a focal-plane mask that modulates the complex amplitude of the Airy disk along one direction. While coronagraphs applying the complex amplitude mask can achieve the theoretical limit performance for any arbitrary pupils, the focal-plane mask severely limits the bandwidth. Here, focusing on the fact that the focal-plane mask modulates the complex amplitude along one direction, we noticed that the mask can be optimized for each spectral element generated by a spectrograph. We combine the fourth-order coronagraph with two spectrographs to produce a stellar spectrum on the focal plane and reconstruct a white pupil on the Lyot stop. Based on the wave-front analysis of an optical design applying an Offner-type imaging spectrograph, we found that the achievable contrast of this concept is 10{sup −10} at 1.2–1.5 times the diffraction limit over the wavelength range of 650–750 nm for the entrance pupil of the LUVOIR telescope. Thus, this coronagraph concept could bring new habitable planet candidates not only around G- and K-type stars beyond 20–30 pc but also around very nearby M-type stars. This approach potentially promotes the characterization of the atmospheres of nearby terrestrial planets with future on- and off-axis segmented large telescopes.

47 OTHER INSTRUMENTATION↗

Pre-Ionization Controlled Laser Plasma Formation for Ignition Applications (Final Scientific/Technical Report)

This report consists of three grand funded papers. Abstracts for each follow. 1) In this work, we present experimental and modeling studies of air pre-ionization using ultraviolet (UV) laser pulses and its effect on laser breakdown of an overlapped near-infrared (NIR) pulse. Experimental studies are conducted with a 266 nm beam (fourth harmonic of Nd:YAG) for UV pre-ionization and an overlapped 1064 nm NIR beam (fundamental of Nd:YAG), both having pulse duration of 10 ns. Results show that the UV beam produces a pre-ionized volume which assists in breakdown of the NIR beam, leading to reduction in NIR breakdown threshold by factor of >2. Numerical modeling is performed to examine the ionization and breakdown of both beams. The modeled breakdown threshold of the NIR, including assist by pre-ionization, is in reasonable agreement with the experimental results. 2) The present contribution compares the energy absorption, optical emission, temperature, and fluid dynamics of ultraviolet (UV) λ = 266 nm and near infrared (NIR) λ = 1064 nm nanosecond laser induced plasmas in ambient air. For UV pulses at the conditions studied, energy absorption by the plasmas increases relatively gradually with laser pulse energy starting at delivered energy of E~8 mJ. Corresponding measurements of plasma luminosity show that the absorption of UV radiation does not necessarily result in visible plasma emission. For the NIR induced plasmas, the energy absorption profile is far more abrupt and begins at ~55 mJ. In contrast with UV, the absorption of NIR radiation is always accompanied by intense optical emission. The temperatures of both types of plasma have been measured with Rayleigh scattering thermometry (at times after the Thomson signal sufficiently diminishes). The UV plasmas can attain a wider range of temperatures, including lower temperatures, depending on the pulse energy (e.g., T ~400–2000K for E ~7–35 mJ at Δt = 10 μs after the pulse) while the NIR plasmas show only hotter temperatures (e.g., T ~ 12 000 K for E = 75 mJ at Δt = 10 μs after the pulse) as is consistent with the literature. Differences in the fluid dynamics for UV versus NIR pulses are shown with Schlieren imaging. In this work, the contrast in the UV and NIR plasma threshold behavior is attributed to differing roles of avalanche ionization and multiphoton ionization as is also illustrated by a simple numerical model. 3) The present contribution examines the impact of plasma dynamics and plasma-driven fluid dynamics on the flame growth of laser ignited mixtures and shows that a new dual-pulse scheme can be used to control the kernel formation process in ways that extend the lean ignition limit. We perform a comparative study between (conventional) single-pulse laser ignition (λ = 1064 nm) and a novel dual-pulse method based on combining an ultraviolet (UV) pre-ionization pulse (λ = 266 nm) with an overlapped near-infrared (NIR) energy addition pulse (λ = 1064 nm). We employ OH* chemiluminescence to visualize the evolution of the early flame kernel. For single-pulse laser ignition at lean conditions, the flame kernel separates through third lobe detachment, corresponding to high strain rates that extinguish the flame. In this work, we investigate the capabilities of the dual-pulse to control the plasma-driven fluid dynamics by adjusting the axial offset of the two focal points. In particular, we find there exists a beam waist offset whereby the resulting vorticity suppresses formation of the third lobe, consequently reducing flame stretch. With this approach, we demonstrate that the dual-pulse method enables reduced flame speeds (at early times), an extended lean limit, increased combustion efficiency, and decreased laser energy requirements.

Mechanical engineering↗

In situ Detection of Plasma Induced Surface Interaction based on Deep Learning based Visual Diagnostics (Technical Report)

It is characteristic for many plasma devices to undergo plasma-material interaction leading to surface erosion. These processes, often not easily detectable, lead to changes in device performance and lifespan. State-of-the-art lifetime tests and wear experiments require over 1000s hours. A self-consistent model for accurately predicting the erosion's effects is not available. In situ detection of these processes is not a trivial task since the surface variations at the early stages have a micron scale. Such limitations not only restrict testing and prediction capabilities but also slow the development of new thrusters and limit mission duration. To address these challenges, an in-situ diagnostic for real-time erosion assessment has been developed, aiming to expedite lifetime testing and broaden experimental campaigns. Several works were dedicated to real-time and in situ monitoring of material erosion during plasma exposure using laser holography, microscopy, and with telemicroscopes. However, the applicability of these approaches is limited due to complexity, cost and less flexibility as they often require placing diagnostic equipment inside the vacuum chamber. In collaboration with Princeton Collaborative Research Facility (PCRF), Princeton Plasma Physics Laboratory (PPPL), a new diagnostic approach is developed, where geometry modifications to the ceramic channel walls were introduced that would result in accelerated channel erosion. We employed Long-distance microscope (LDM) imagery, combined with Deep-Learning based Shape from focus or depth from focus (DFF or SFF) approach, that provides an accessible and cost-effective solution. LDM employs focus variation techniques to continuously capture multiple images of the target object at distinct focal planes. DFF, an optical focus variation method, generates a 3D topographical surface depth map from a sequence of variably focused images. Combined with the developed diagnostic, this approach offers a controllable means to study erosion under accelerated conditions. In this work, we develop Neural Network-based DFF algorithm applicable for LDM data to quantitatively evaluate plasma induced surface modification from LDM data. Next, we develop Deep Learning-based super-resolution depth map image reconstruction technique to increase the resolution of depth maps obtained from DFF algorithm to improve the accuracy of erosion measurements. Thirdly, we develop several image processing techniques to remove noise and improve the quality of depth map image. Here we report the results of initial tests for this approach. An experimental setup designed and built in PPPL was employed that consists of a 3-cm gridded ion source that produces a neutralized argon beam with energies up to 600 eV. A hexagonal boron nitride (h-BN) ceramic target, designed based on computational predictions, was used. Tests were conducted to reconstruct the complex geometry of the target under the lighting conditions of the operated ion source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

System and method for remote detection and location of gas leaks

A system for monitoring for a gas leak from a gas containing structure is disclosed. The system includes a lens that directs an image of a scene of interest through an optical filter onto a detector. The filter is associated with the lens and the filter has one or more passbands that passes wavelengths which match one or more emission or reflectively wavelengths of the gas being monitored. A detector receives the image after the image passes through the lens and the filter. The detector generates image data representing the scene including the gas containing structure. A processor is configured to process the image data by executing machine executable code stored on a memory. The machine executable code processes the image data to identify turbulence flows in the image data such that turbulence flow indicates a gas leak, and generate and send an alert in response to the identification of a turbulence flow.

O'Neill, Mary D.↗

Time-resolved spray characterization via unified optical flow and binarization technique

This work leverages an unsupervised machine learning and advanced image processing techniques to characterize the breakup of fuel sprays in a small-scale combustor under reacting conditions, providing valuable insights into near-nozzle flow phenomenology. The proposed methodology integrates an improved optical flow model on a convolutional neural network to extract flow vectors with a binarization technique to assess droplets’ size and shape across the region of interest. The velocimetry approach demonstrates superior performance compared to a state-of-the-art optical flow model when applied to high-speed X-ray phase contrast spray images, achieving more accurate and reliable flow predictions. Moreover, breakup processes are quantified by breakup length and sphericity in accordance with velocity estimations, allowing a more complete characterization of the flow. This study establishes a robust methodology for analyzing spray morphology and primary breakup in compact combustors, contributing valuable means of understanding and optimizing fuel spray behavior in advanced combustion systems.

42 ENGINEERING↗

Direct Observation of Circularly Polarized Nonlinear Optical Activities in Chiral Hybrid Lead Halides

Circularly polarized light emission is a crucial application in imaging, sensing, and photonics. However, utilizing low-energy photons to excite materials, as opposed to high-energy light excitation, can facilitate deep-tissue imaging and sensing applications. The challenge lies in finding materials capable of directly generating circularly polarized nonlinear optical effects. In this study, we introduce a chiral hybrid lead halide (CHLH) material system, R/S-DPEDPb 3 Br 8 ·H 2 O (DPED = 1,2-diphenylethylenediammonium), which can directly produce circularly polarized second harmonic generation (CP-SHG) through linearly polarized infrared light excitation, exhibiting a polarization efficiency as high as 37% at room temperature. To understand the spin relaxation mechanisms behind the high polarization efficiency, we utilized two models, so-called D’yakonov–Perel’ (DP) and Bir–Aronov–Pikus (BAP) mechanisms. The unique zigzag inorganic frameworks within the hybrid structure are believed to reduce the dielectric confinement and exciton binding energy, thus enhancing spin polarization, especially in regions with a high excitation pump fluence based on the DP mechanism. In the case of low excitation pump fluence, the BAP mechanism dominates, as evidenced by the observed decrease in the polarization ratio from CP-SHG measurement. Using density functional theory analysis, we elucidate how the distinctive 8-coordination environment of lead bromide building blocks effectively suppresses spin–orbit coupling at the conduction band minimum. This suppression significantly diminishes spin-splitting, thereby slowing the spin relaxation rate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Airy light-sheet Raman imaging

Light-sheet fluorescence microscopy has greatly improved the speed and overall photostability of optically sectioning cellular and multi-cellular specimens. Similar gains have also been conferred by light-sheet Raman imaging; these schemes, however, rely on diffraction limited Gaussian beams that hinder the uniformity and size of the imaging field-of-view, and, as such, the resulting throughput rates. Here, we demonstrate that a digitally scanned Airy beam increases the Raman imaging throughput rates by more than an order of magnitude than conventional diffraction-limited beams. Overall, this, spectrometer-less, approach enabled 3D imaging of microparticles with high contrast and 1 µm axial resolution at 300 msec integration times per plane and orders of magnitude lower irradiation density than coherent Raman imaging schemes. We detail the apparatus and its performance, as well as its compatibility with fluorescence light-sheet and quantitative-phase imaging towards rapid and low phototoxicity multimodal imaging.

47 OTHER INSTRUMENTATION↗

Characterization of a Low-Temperature Plasma (LTP) Ambient Ionization Source Using Temporally Resolved Monochromatic Imaging Spectrometry

The low-temperature plasma (LTP) probe is a common plasma-based source used for ambient desorption–ionization mass spectrometry (MS). While the LTP probe has been characterized in detail with MS, relatively few studies have used optical spectroscopy. In this paper, two-dimensional (2D) imaging at selected wavelengths is used to visualize important species in the LTP plasma jet. First, 2D steady-state images of the LTP plume for N 2 + (391.2 nm), He I (706.5 nm), and N 2 (337.1 nm) emissions were recorded under selected plasma conditions. Second, time-resolved 2D emission maps of radiative species in the LTP plasma jet were recorded through the use of a 200 ns detection gate and varying gate delays with respect to the LTP trigger pulse. Emission from He I, N 2 + , and N 2 in the plasma jet region was found to show a transient behavior (often referred to as plasma bullets) lasting only a few microseconds. The N 2 + and He I maps were highly correlated in spatial and temporal structure. Further, emission from N 2 showed two maxima in time, one before and one after the maximum emission for N 2 + and He I, due to an initial electronic excitation wave and ion–electron recombination, respectively. Third, the interaction of the LTP probe with a sample substrate and an electrically grounded metallic needle was studied. Emission from a fluorophore on the sample substrate showed an initial photon-induced excitation from plasma-generated photons followed by electronic excitation by other plasma species. The presence of a grounded needle near the plasma jet significantly extended the plasma jet lifetime and also generated a long-lived corona discharge on the needle. The effect of LTP operating parameters on emission spectra was correlated with mass-spectral results including reagent-ion signals. Lastly, five movies provide a side-by-side comparison of the temporal behavior of emitting species and insights into the interactions of the emission clouds with a sample surface as well as an external needle. Temporally and spatially resolved imaging provided insights into important processes in the LTP plasma jet, which will help improve analyte ion sampling in LTP–MS.

Chan, George C. -Y.↗

End–to–End Metasurface Design for Temperature Imaging via Broadband Planck‐Radiation Regression

A theoretical framework is presented for temperature imaging from long-wavelength infrared (LWIR) thermal radiation (e.g., 8–12 µm) through the end-to-end design of a metasurface-optics frontend and a computational-reconstruction backend. A new nonlinear reconstruction algorithm, “Planck regression”, is introduced to reconstruct the temperature map from a gray scale sensor image, even in the presence of severe chromatic aberration, by exploiting black body and optical physics particular to thermal imaging. This algorithm is combined with an end-to-end approach that optimizes manufacturable, single-layer metasurfaces to yield the most accurate reconstruction. The designs demonstrate high-quality, noise-robust reconstructions of arbitrary temperature maps (including completely random images) in simulations of an ultra-compact thermal-imaging device. Here, it is also shown that Planck regression is much more generalizable to arbitrary images than a straightforward neural-network reconstruction, which requires a large training set of domain-specific images.

36 MATERIALS SCIENCE↗

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

This review explores magnetic field-driven emergent phenomena across various material systems, emphasizing the pivotal roles of magneto-optical and nanoscopy techniques. We examine fundamental aspects of Landau electrodynamics in both 2D and 3D systems, including quantum Hall and topological magnetoelectric effects in graphene and topological insulators. Particularly attention is given to magnetic excitations and magnetopolaritons, such as surface magnon polaritons, magnetoplasmons, and magnetoexcitons in novel quantum materials, including quantum magnets and hybrid heterostructures. Advanced imaging techniques, such as scattering-type scanning near-field optical microscopy (SNOM) and microwave impedance microscopy, are showcased for their capability to resolve these phenomena with microscopic and nanoscopic resolution. These insights are complemented by discussions of advanced experimental approaches, including cryogenic environments, ultrafast pump-probe techniques, and the integration of magnetic fields into near-field optical methodologies. We further investigate the potential of these imaging techniques for unraveling complex magnetic orders, quantum phases, and correlated electronic behaviors. Finally, we offer perspectives on future research directions and highlight emerging opportunities in the evolving field of optical magneto-nanoscopy.

36 MATERIALS SCIENCE↗

Spectrometer-free quantitative vapor sensing and classification via spatiotemporal imaging of porous silicon metasurfaces

Metasurfaces offer a compact platform for optical vapor sensing, but their practical deployment has been limited by weak evanescent light–matter interactions and reliance on spectrally resolved instrumentation. Here, we report porous silicon (pSi) metasurfaces for spectrometer-free quantitative detection of volatile organic compounds (VOCs) with strongly enhanced light–matter interaction. The engineered porosity increases sensitivity by >100× relative to non-porous dielectric metasurfaces, enabling limits of detection of 1.65 ppm for methanol and 9.1 ppm for ethanol across a broad dynamic range (<10 ppm to >103 ppm). Imaging-based readout provides a lightweight, spectrometer-free pathway for real-time quantitative sensing. Beyond quantitative detection, the mesoporous architecture introduces adsorption–desorption kinetics as an additional information channel. Analysis of the resulting spatiotemporal signatures enables kinetic fingerprinting without reliance on infrared spectral features or surface functionalization, and a lightweight machine-learning classifier differentiates acetone, methanol, ethanol, and isopropanol with 91.6% accuracy. These results establish porous metasurfaces as spatiotemporal sensing elements that couple quantitative vapor detection with kinetic fingerprinting through real-time dynamical responses, enabling low-cost, high-performance optical sensors.

Dash, Tomoshree [Clemson University]↗

Microscale drivers and mechanisms of fracture in post-processed additively manufactured Ti–6Al– 4 V

Herein, we focus on understanding the microstructure-fracture correlations in a Ti–6Al– 4 V alloy additively manufactured via electron beam melting (EBM) and subjected to various post-process heat-treatments. Specifically, the as fabricated material is subjected to a sub-transus heat-treatment followed by air-cooling and a super-transus heat-treatment followed by either air- or furnace-cooling. Next, a series of in-situ single edge notch tension (SENT) tests are carried out under a high-resolution digital optical microscope. The panoramic high-resolution images captured during the in-situ tests are then used to characterize the planar deformation on the specimen surface using microstructure-based digital image correlation (DIC). Additionally, the results of the in-situ SENT tests together with DIC and post-mortem fractographic analyses provided us with a better understanding of the microstructure-fracture correlations in these materials. Our results show that the fracture mechanism of the as fabricated and sub-transus heat-treated materials is essentially the same, while the changes in the microstructure following the super-transus heat-treatments significantly affects the fracture mechanism. In this case, several microcracks of hundreds of microns in length first nucleate away from the deformed notch following extreme plastic deformation at discrete locations. Furthermore, the location of these microcracks in the super-transus heat-treated materials is extremely sensitive to the details of the underlying microstructure.

36 MATERIALS SCIENCE↗

New insights into the mechanism of ultrasonic atomization for the production of metal powders in additive manufacturing

Ultrasonic atomization is one of the promising technologies for producing metal powders for additive manufacturing, where precise control of particle size and morphology is essential. In this study, we coupled an ultrasonic transducer with a carbon fiber plate and atomized liquid droplets and films under different vibration amplitudes. Water, glycerol, and pure aluminum melt were used to study the atomization mechanism and the resulting droplet/powder characteristics, respectively. High-speed optical and ultrafast synchrotron X-ray imaging were used to study in situ the ultrasonic atomization dynamics, including pulsation and clustering of cavities inside the liquid layer/films, development of capillary waves, and formation of liquid droplets. For the first time, we observed and captured the occurrence of cavitation during the atomization of resting drops, films and impact droplets. The inertial cavitation events interfered with the capillary waves across the interphase boundary, puncturing and breaking the boundary to produce atomized mist. The in situ observation revealed the intricate dynamics of ultrasonic atomization and underscored the pivotal role of cavitation events throughout the entire atomization process. We also conducted experiments on ultrasonic atomization of liquid aluminum, producing particles of perfectly spherical shape. The particle size tended to decrease with reduced vibration amplitude Our work has demonstrated the important processing strategies on how to tailor the particle size while ensuring consistent particle shape and morphology, which is the key processing capability for producing high quality powders for additive manufacturing applications.

36 MATERIALS SCIENCE↗

The effects of field history on magnetic skyrmion formation in [Pt/Co/Ir] 3 multilayers

Here, we report on the formation of Néel-type magnetic bubble skyrmions at room temperature in [Pt/Co/Ir] 3 multilayered thin films after an in-plane magnetic field treatment. Polar magneto-optical Kerr Effect (p-MOKE) microscopy images show that the dendritic magnetic configurations observed after AC demagnetization evolve into magnetic bubble skyrmions after the application and subsequent removal of an in-plane magnetic field. Micromagnetic simulations were used to systematically investigate the role of the in-plane magnetic field magnitude, misalignment of the sample, and the Dzyaloshinskii-Moriya interactions (DMI) in generating bubble skyrmions during the field treatment. The simulations show that in-plane fields slightly below the saturation field are the most effective at producing skyrmions, and, furthermore, a small field angle away from the sample plane not only leads to improved skyrmion formation but also provides a means to select the skyrmion polarity where the direction of the out-of-plane component of the field is opposite to the direction of the skyrmion cores. This field treatment scheme leads to a simple and reliable way to create magnetic bubble skyrmions in multilayered thin films with DMI.

36 MATERIALS SCIENCE↗

Measurement of flow properties coupled to experimental and numerical analyses of dense, granular flows for solar thermal energy storage

Granular flows of sintered bauxite proppants were researched along an inclined plane for solar thermal energy storage applications. Granular flow properties needed to drive numeric granular models were measured for improved numerical model predictions for Carbobead CP 50/140, 40/100, and 30/60 particles. Particle shape and size distributions were determined by coupling optical microscopy to an in-house image processing algorithm. The impulse excitation technique was used to measure elastic and shear moduli, and compute Poisson’s ratio. The coefficient of static sliding friction was measured using the slip-stick method, and the static rolling friction was determined from measured shear on particles positioned between two hot-pressed plates. The coefficient of restitution was measured by dropping particles on a surface and determining the kinetic energy before and after impact with the surface using high resolution particle tracking velocimetry. Particle size did not significantly impact the coefficients of restitution and static rolling friction, however, particle shape distribution resulted in a large variation in measurements. An inclined flow experiment was performed to characterize granular flows of Carbobead CP 30/60 particles using particle image velocimetry. Numerical models of the experiment using discrete element method were generated with the measured mechanical properties as inputs for comparison with experimental results. A constant directional torque rolling friction model best predicted bulk granular flow behavior. Furthermore, good agreement between the model and experiment was achieved at ambient, steady state conditions, with average velocity differences <10%.

14 SOLAR ENERGY↗

Smart Scattering Scanning Near-Field Optical Microscopy

Scattering scanning near-field optical microscopy (s-SNOM) provides spectroscopic imaging from molecular to quantum materials with few nanometer deep subdiffraction limited spatial resolution. However, in its conventional implementation s-SNOM is slow to effectively acquire a series of spatio-spectral images, especially with large fields of view. This problem is further exacerbated for weak resonance contrast or when using light sources with limited spectral irradiance. Indeed, the generally limited signal-to-noise ratio prevents sampling a weak signal at the Nyquist sampling rate. Here, we demonstrate how acquisition time and sampling rate can be significantly reduced by using compressed sampling, matrix completion, and adaptive random sampling, while maintaining or even enhancing the physical or chemical image content. We use fully sampled real data sets of molecular, biological, and quantum materials as ground-truth physical data and show how deep under-sampling with a corresponding reduction of acquisition time by 1 order of magnitude or more retains the core s-SNOM image information. We demonstrate that a sampling rate of up to 6× smaller than the Nyquist criterion can be applied, which would provide a 30-fold reduction in the data required under typical experimental conditions. Furthermore, our smart s-SNOM approach is generally applicable and provides systematic full spatio-spectral s-SNOM imaging with a large field of view at high spectral resolution and reduced acquisition time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗