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At least 307 records · Page 17

Imaging from Macro to Nanoscale: Multimodal Advances in Chemical and Biomedical Imaging

Imaging increasingly serves as a multiscale framework for linking molecular mechanisms to cellular behavior, tissue architecture, and organ phenotypes in biology and unraveling fundamental processes in chemistry, physics and materials science. This Perspective highlights recent advances in chemical and biomedical imaging across macro-, micro-, and nanoscales, using representative examples published in Chemical and Biomedical Imaging (CBMI). At the macroscale, we discuss chemically selective MRI, including endogenous and exogenous CEST strategies, together with photoacoustic imaging as a hybrid modality with functional and chemical contrast. At the microscale, we consider fluorescence, label-free optical and vibrational imaging, and selected X-ray approaches that expand sensitivity, specificity, and temporal resolution in biological and materials systems. At the nanoscale, we highlight super-resolution fluorescence microscopy, single-molecule methods, tip-enhanced Raman spectroscopy, and correlative imaging strategies that resolve local heterogeneity and molecular organization. Across scales, a common theme emerges that advances in probes, contrast mechanisms, instrumentation, and sample handling are enabling chemically informed imaging that connects molecular specificity with biological context.

multiscale imaging↗

Vibrational sum frequency generation spectroscopy reveals the inertness of chromium oxide (001) surfaces

Nanoengineered metal oxides such as Cr(III)-oxide (chromia) films have diverse potential applications in corrosion inhibition, remediation, energy generation, catalysis, data storage, and biological and environmental systems. Concerns about material degradation or oxidation to toxic chromate necessitate an understanding of chromia/aqueous interfaces, beginning with their hydroxylation and hydration behavior. Vibrational sum-frequency generation spectroscopy (vSFG) provides specific molecular-level information about water at the oxide/aqueous junction with high surface selectivity. To overcome the strong absorber problem typical of certain metal oxides in the UV–visible range during nonlinear optical studies, we employed molecular beam epitaxy to deposit transparent, epitaxial nanofilms of Cr 2 O 3 with (001) crystalline orientation on sapphire (Al 2 O 3 (001)) substrates, as confirmed by atomic force microscopy and X-ray diffraction. vSFG spectra of the air and water interfaces of the Cr 2 O 3 (001) films reveal hydroxyl features corresponding to both dissociated and molecular water on the surface. In contrast to the dangling hydroxyls found on the bare Al 2 O 3 (001) substrate, the hydroxyl groups on the deposited Cr 2 O 3 (001) nanofilm do not readily undergo isotopic H/D exchange when exposed to varying forms of D 2 O under ambient conditions. When considering the chemistries of the corresponding trivalent cations in aqueous solution, the finding is at variance with their similar acidities and proton exchange dynamics but consistent with markedly slower inner-sphere water ligand exchange of hexaquo Cr 3+ . This finding challenges the idea that proton and water exchange at the water/Cr₂O₃(001) interface are solely correlated, driven by the strength of metal-bridging oxygen bonds and surface hydroxyl distribution, without direct causation.

Boamah-Agyemang, Mavis D. [Pacific Northwest Natio↗

Quantitative measurement of pebble fuel anisotropy using generalized ellipsometry

The renewed development of high-temperature gas-cooled reactors has created a need to modernize pebble fuel quality control methods. One important specification in these methods is the coefficient of thermal expansion (CTE) anisotropy, which reflects graphite grain alignment and affects fuel performance. This study investigates the feasibility of using two-modulator generalized ellipsometry microscopy (2-MGEM) as a potential surrogate metric for CTE anisotropy. Graphite matrix compacts with controlled levels of anisotropy were fabricated by varying pre-pressures during forming and were subsequently characterized using both optical dilatometry and 2-MGEM. Measured responses were compared to an isotropic reference pebble produced using an industrial manufacturing process to provide a practical baseline. The resulting measurements revealed a strong quantitative correlation between the CTE anisotropy ratio and the corresponding diattenuation ratio. However, propagated measurement uncertainties in the optical method were found to limit definitive pass/fail discrimination, highlighting the need for improved precision before qualification as a quality control tool. Still, the results establish a quantitative relationship between optical and CTE anisotropy and support further development of 2-MGEM as a potential surrogate method for evaluating graphite matrix anisotropy in pebble fuel manufacturing.

Raftery, Alicia [ORNL] (ORCID:0000000259076427)↗

Feeling the Strain: Quantifying Ligand Deformation in Photosynthesis

Structural distortion of protein-bound ligands can play a critical role in enzyme function by tuning the electronic and chemical properties of the ligand molecule. However, quantifying these effects is difficult due to the limited resolution of protein structures and the difficulty of generating accurate structural restrains for non-protein ligands. Here, we seek to quantify these effects through a statistical analysis of ligand distortion in Chlorophyll (Chl) proteins (CP), where ring deformation is thought to play a role in energy and electron transfer. To assess the accuracy of ring-deformation estimates from available structural data, we take advantage of the C 2 symmetry of Photosystem II (PSII), comparing ring-deformation estimates for equivalent sites both within and between 113 distinct X-ray and Cryogenic electron microscopy (CryoEM) PSII structures. Significantly, we find that several deformation modes exhibit considerable variability in predictions, even for equivalent monomers, down to 2 Å resolution, to an extent that probably prevents their utilization in optical calculations. We further find that refinement restrains play a critical role in determining deformation values to resolution as low as 2 Å. However, for those modes that are well-resolved in the structural data, ring deformation in PSII is strongly conserved across all species tested, from cyanobacteria to algae. Furthermore, these results highlight both the opportunities and limitations inherent in the structure-based analysis of the bioenergetic and optical properties of CPs and other protein-ligand complexes.

14 SOLAR ENERGY↗

DONUT: physics-aware machine learning for real-time X-ray nanodiffraction analysis

Coherent X-ray scattering techniques are critical for investigating the fundamental structural properties of materials at the nanoscale. While advancements have made these experiments more accessible, real-time analysis remains a significant bottleneck, often hindered by artifacts and computational demands. In scanning X-ray nanodiffraction microscopy, which is widely used to spatially resolve structural heterogeneities, this challenge is compounded by the convolution of the divergent beam with the sample’s local structure. To address this, we introduce DONUT (Diffraction with Optics for Nanobeam by Unsupervised Training), a physics-aware neural network designed for the rapid and automated analysis of nanobeam diffraction data. By incorporating a differentiable geometric diffraction model directly into its architecture, DONUT learns to predict crystal lattice strain and orientation in real-time. Crucially, this is achieved without reliance on labeled datasets or pre-training, overcoming a fundamental limitation for supervised machine learning in X-ray science. We demonstrate experimentally that DONUT accurately extracts all features within the data over 200 times more efficiently than conventional fitting methods.

Materials science↗

DONUT: Physics-aware Machine Learning for Real-time X-ray Nanodiffraction Analysis

SF-25-088 Coherent X-ray scattering techniques are critical for investigating the fundamental structural properties of materials at the nanoscale. While advancements have made these experiments more accessible, real-time analysis remains a significant bottleneck, often hindered by artifacts and computational demands. In scanning X-ray nanodiffraction microscopy, which is widely used to spatially resolve structural heterogeneities, this challenge is compounded by the convolution of the divergent beam with the sample’s local structure. To address this, we introduce DONUT (Diffraction with Optics for Nanobeam by Unsupervised Training), a physics-aware neural network designed for the rapid and automated analysis of nanobeam diffraction data. By incorporating a differentiable geometric diffraction model directly into its architecture, DONUT learns to predict crystal lattice strain and orientation in real-time. Crucially, this is achieved without reliance on labeled datasets or pre-training, overcoming a fundamental limitation for supervised machine learning in X-ray science. We demonstrate experimentally that DONUT accurately extracts all features within the data over 200 times more efficiently than conventional fitting methods.

Zhou, Tao [Argonne National Laboratory (ANL), Argo↗

Giant Modulation of Refractive Index from Picoscale Atomic Displacements

Abstract It is shown that structural disorder—in the form of anisotropic, picoscale atomic displacements—modulates the refractive index tensor and results in the giant optical anisotropy observed in BaTiS 3 , a quasi‐1D hexagonal chalcogenide. Single‐crystal X‐ray diffraction studies reveal the presence of antipolar displacements of Ti atoms within adjacent TiS 6 chains along the c ‐axis, and threefold degenerate Ti displacements in the a – b plane. 47/49 Ti solid‐state NMR provides additional evidence for those Ti displacements in the form of a three‐horned NMR lineshape resulting from a low symmetry local environment around Ti atoms. Scanning transmission electron microscopy is used to directly observe the globally disordered Ti a–b plane displacements and find them to be ordered locally over a few unit cells. First‐principles calculations show that the Ti a – b plane displacements selectively reduce the refractive index along the ab ‐plane, while having minimal impact on the refractive index along the chain direction, thus resulting in a giant enhancement in the optical anisotropy. By showing a strong connection between structural disorder with picoscale displacements and the optical response in BaTiS 3 , this study opens a pathway for designing optical materials with high refractive index and functionalities such as large optical anisotropy and nonlinearity.

36 MATERIALS SCIENCE↗

Editorial overview: Unlocking the secrets of nongenetic plasticity, one cell at a time

Cellular noise, the non-genetic variability observed among isogenic cells, arises from factors such as growth conditions, aging, and stochastic gene expression, influencing cell stress-response, metabolism, morphology, and size. Here, such plasticity, while critical for adaptation, often goes unnoticed with traditional population-averaging biotechnologies that inevitably mask cell-specific variations and prompting the question, "What else might we be missing". However, recent breakthroughs in optical imaging, microfluidics, and omics, are beginning to uncover the complexity of cellular plasticity. This special is-sue highlights some of these breakthroughs, with key contributions including innovations in multimodal chemical imaging, label-free microscopy, spatial and temporal omics, and droplet-based microfluidics. Collectively, these cutting-edge tools provide unprecedent-ed insights into non-genetic cell-to-cell variability, enhancing our understanding of cellu-lar plasticity and its implications for health, energy, and ecology.

59 BASIC BIOLOGICAL SCIENCES↗

Tracking Dendritic Growth in Hydrogen-Based Hematite Reduction via Computer Vision

The reduction of hematite to metallic iron using hydrogen (H2) as a reducing agent presents a promising pathway for decarbonizing steel production. In this study, we employ a combination of in situ confocal scanning laser microscopy (CSLM) and advanced computer vision techniques to quantitatively analyze dendritic growth of ferrite during H2-based reduction of iron oxide at high temperatures. A workflow integrating Watershed Image Segmentation (WIS) and Lucas-Kanade Optical Flow (LKOF) is developed to extract both global and local kinetic information from time-resolved micrograph sequences. H2 reduction experiments conducted at 1400 degrees C and 1500 degrees C demonstrate a clear correlation between temperature and reduction rate, as evidenced by accuracy of fitted Johnson-Mehl-Avrami-Kolmogorov (JMAK) parameters. Optical flow analysis further elucidates the anisotropic and branched nature of dendritic growth, providing spatially resolved velocity fields that correlate well with global transformation kinetics. The proposed methodology demonstrates strong agreement with experimental measurements and literature values, offering a robust framework for automated image-based analysis to study kinetics through microstructural evolution in the reduction of iron ore, and likely other reaction-diffusion phenomena.

08 HYDROGEN↗

Novel white light-emitting CdSe:Mn 2+ synthesized by photo-assisted chemical bath deposition

Nowadays, white light-emitting materials have attracted extensive research due to their potential applications in lighting devices and displaying images. Several semiconductor nanoparticles have been explored to achieve efficient white light emission. In this work, we report on novel white light-emitting CdSe:Mn 2+ thin films synthesized by photo-assisted chemical bath deposition. The effect of varying the Mn 2+ ion concentrations on the thin film structure, morphology, and optical properties was investigated. X-ray powder diffraction results indicated that all the films annealed at 250 degrees C possessed a cubic structure, with crystallite sizes in the range of 1-130 nm. Scanning electron microscopy demonstrated spherical nanoparticles with no significant changes with varying Mn 2+ doping concentrations. Energy dispersive X-ray spectroscopy confirmed the presence of the anticipated elements. The atomic force microscope revealed that the surface roughness has decreased with an increase in Mn 2+ ion concentrations but decreased for 0.7 %Mn 2+ . The UV-Vis absorption spectra showed absorption edges around 600-650 nm. Photoluminescence emission spectra excited at 3.8 eV (325 nm) showed emission bands at around 1.75 eV (709 nm), and 1.88 eV (659 nm), which were attributed to the band-to-band emission, and 4 T 1 ( 4 G)-> 6 A 1 ( 6 S) transitions of Mn 2+ ions, respectively, while emission bands at 2.35 eV (528 nm), and prominent at 3.17 eV (391 nm) were due to the glass substrate. The temperature-dependent luminescence showed a decrease in relative emission intensity with the increase in the operating temperature. The chromaticity colour coordinates showed white light-emitting thin films. These present findings open a new door to developing white light using CdSe thin films.

36 MATERIALS SCIENCE↗

Probing Plasmonic Near-Fields in Oxide-Modified Aluminum Nanocubes Using Photon-Induced Near-Field Electron Microscopy

Plasmonic nanoparticles generate strong electric fields near their surface upon photoexcitation, enabling applications in sensing, spectroscopy, and photocatalysis. Electron microscopy techniques – such as cathodoluminescence and electron energy loss spectroscopy – have been leveraged to produce nanoscale maps of localized surface plasmon (LSP) modes. More recently, photon-induced near-field electron microscopy (PINEM) has emerged as a powerful technique for imaging evanescent near-fields generated by ultrafast laser excitation. In this work, we employ PINEM within an ultrafast electron microscope, complemented by numerical calculations to investigate how optical polarization, surface modification, and light intensity affect the evanescent fields associated with LSPs on oxide-modified aluminum nanocubes. Polarization control of the incident light field enables spatial mapping of the nanocube’s LSPs at the single particle level. Systematic variation of the oxide layer thickness reveals that increased coating thickness correlates with a stronger PINEM signal and a greater energy gain of probing electrons. Additionally, higher light intensities at fixed polarization and oxide coating further amplify the PINEM signal. These findings demonstrate the utility of PINEM as a high-resolution technique for optical near-field imaging and spectroscopy of single plasmonic nanoparticles. The ability to probe single particle behavior offers new opportunities for advancing the design and characterization of nanophotonic and plasmonic materials.

PINEM↗

Charge state-dependent symmetry breaking of atomic defects in transition metal dichalcogenides

Abstract The functionality of atomic quantum emitters is intrinsically linked to their host lattice coordination. Structural distortions that spontaneously break the lattice symmetry strongly impact their optical emission properties and spin-photon interface. Here we report on the direct imaging of charge state-dependent symmetry breaking of two prototypical atomic quantum emitters in mono- and bilayer MoS 2 by scanning tunneling microscopy (STM) and non-contact atomic force microscopy (nc-AFM). By changing the built-in substrate chemical potential, different charge states of sulfur vacancies (Vac S ) and substitutional rhenium dopants (Re Mo ) can be stabilized. $${\mathrm{Vac}}_{{{{{{{{\rm{S}}}}}}}}}^{-1}$$ Vac S − 1 as well as $${{\mathrm{Re}}}_{{{{{{{{\rm{Mo}}}}}}}}}^{0}$$ Re Mo 0 and $${\mathrm{Re}}_{{\rm{Mo}}}^{-1}$$ Re Mo − 1 exhibit local lattice distortions and symmetry-broken defect orbitals attributed to a Jahn-Teller effect (JTE) and pseudo-JTE, respectively. By mapping the electronic and geometric structure of single point defects, we disentangle the effects of spatial averaging, charge multistability, configurational dynamics, and external perturbations that often mask the presence of local symmetry breaking.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Wafer-scale waveguide sidewall roughness scattering loss characterization by image processing

Photonic integrated circuits (PICs) are vital for developing affordable, high-performance optoelectronic devices that can be manufactured at an industrial scale, driving innovation and efficiency in various applications. Optical loss of modes in thin film waveguides and devices is a critical measure of their performance. Thin film growth, lithography, masking, and etching processes are imperfect processes that introduce significant sidewall and top-surface roughness and cause dominating optical losses in waveguides and photonic structures. This roughness, as perturbations couple light from guided to far-field radiation modes, leads to scattering losses that can be estimated from theoretical models. Typically, with UV-based lithography, sidewall roughness is significantly larger than wafer-top surface roughness. Atomic force microscopy (AFM) imaging measurement gives a 3D and high-resolution roughness profile, but the measurement is inconvenient, costly, and unscalable for large-scale PICs and at wafer-scale. Here, we evaluate the sidewall roughness profile based on 2D high-resolution scanning electron microscope (SEM) imaging. We characterized the loss on two homemade nitride and oxide films on 3-inch silicon wafers with 12 waveguide devices on each and correlated the scattering loss estimated from a 2D image-based sidewall profile and theoretical Payne model. The lowest loss of guided fundamental transverse electric (TE 0 ) mode is found at 0.075 dB/cm at 633 nm across 24 devices, a record at visible wavelength. Our work shows 100% success (edge continuity span exceeding 95% of image width/height) in edge detection in image processing of all images to estimate autocorrelation function and optical mode loss. These demonstrations offer valuable insights into waveguide sidewall roughness and a comparison of experimental and 2D SEM image processing based loss estimations with applications in loss characterization at wafer-scale PICs.

Khurana, Mohit (ORCID:0000000207898672)↗

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗

Functionalization of nitrogen vacancy-containing nanodiamonds with a metal-organic framework for quantum sensing applications

Nitrogen vacancy (NV)-containing nanodiamonds (NDs) are an important material in applications such as biological imaging, catalysis, and, in particular, quantum sensing. Careful manipulation of the surface coating on NV NDs is essential for both enhancing quantum sensor performance and for tuning selectivity towards specific sensing targets. Here, we demonstrate a simple synthetic approach for functionalizing NV NDs with the zeolitic imidazole framework-8 (ZIF-8) metal–organic framework (MOF), providing a well-ordered, porous scaffold for immobilizing target analytes near the NV ND surface. The composites were structurally characterized by x-ray diffraction, electron microscopy, and X-ray photoelectron spectroscopy, and these results were all consistent with NV NDs fully encapsulated by ZIF-8. Critically, the luminescent properties of the NV NDs, which are vital for quantum sensing experiments such as optically detected magnetic resonance (ODMR), are unchanged by the MOF coating. Moreover, spin relaxometry experiments indicate that the ZIF-8 coating significantly enhances the NV ND spin longitudinal relaxation time T1, a critical quantum parameter for sensing applications. Given the tremendous structural diversity of MOFs, the NV ND@MOF composites are an exciting material class with exciting implications for the development of high-performance quantum sensors.

Crawford, Scott↗

Tunable chiral and nematic states in the triple-Q antiferromagnet Co 1/3 TaS 2

Complex spin configurations in magnetic materials, ranging from collinear single-Q to non-coplanar multi-Q states, exhibit rich symmetry and chiral properties. However, their detailed characterization is often hindered by the limited spatial resolution of neutron diffraction techniques. Here we employ magnetic circular dichroism and magnetic linear dichroism to investigate the triangular lattice antiferromagnet Co 1/3 TaS 2 , revealing three-state (Z 3 ) nematicity and also spin chirality across its multi-Q magnetic phases. At intermediate temperatures, the presence of linear dichroism identifies nematicity arising from a single-Q stripe phase, while at high magnetic fields and low temperatures, a phase characterized solely by circular dichroism emerges, signifying a purely chiral non-coplanar triple-Q state. Notably, at low temperatures and small fields, we discover a unique phase where both chirality and nematicity coexist. A theoretical analysis based on a continuous multi-Q manifold captures the emergence of these distinct magnetic phases, as a result of the interplay between four-spin interactions and weak magnetic anisotropy. Additionally, both circular and linear dichroism microscopy spatially resolves the chiral and nematic domains. Our findings establish Co 1/3 TaS 2 as a rare platform hosting diverse multi-Q states with distinct combinations of spin chirality and nematicity while demonstrating the effectiveness of polarized optical techniques in characterizing complex magnetic textures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Metal ion dopant-induced famatinite to chalcostibite phase transformation of copper antimony sulphide colloidal nanostructures: effect on photophysical and pseudocapacitance properties

Here, the strategic doping of transition metal ions into copper antimony sulphide (CAS) semiconducting nanostructures can significantly influence their photophysical and pseudocapacitive properties, for which there are few reports and therefore is the focus of this study. Accordingly, highly crystalline metal ion (Mn 2+ , Fe 2+ , Co 2+ , Ni 2+ and Zn 2+ ) doped off-stoichiometric copper rich/poor, antimony-rich/poor, and sulphur-poor CAS nanostructures (10–23 nm) were grown via colloidal (hot-injection) synthesis using metal diethyldithiocarbamate precursors. Importantly, metal ion doping significantly influences the structure and composition of the off-stoichiometric CAS nanostructures. Data from powder X-ray diffraction, Raman spectroscopy, high-resolution scanning/transmission electron microscopy, and energy dispersive X-ray spectroscopy confirm that the heavier metal ion dopants induce a novel phase transformation from famatinite (fCAS) to chalcostibite (cCAS) nanostructures. The influence of the metal ion dopants is also observed in the optical properties of as-synthesized nanostructures. This involves blue-shifted ultraviolet-visible absorption, reduced Urbach tailing, and tunable bandgaps between 2.17 and 2.38 eV. Also, the doped nanostructures display broad visible-near infrared photoluminescence via a triple radiative pathway with relatively short decay lifetimes between 0.2 and 6.1 ns. This is mediated by electronic transitions involving intrinsic (copper/antimony/sulphur interstitial) and extrinsic (metal ion interstitial) defect states. Additionally, electrodes prepared from Mn 2+ -doped fCAS nanostructures show enhanced pseudocapacitance via Na+ surface adsorption and intercalation relative to undoped fCAS electrodes, while Zn 2+ -doped cCAS electrodes exhibit pseudocapacitance via a combination of Na+ surface adsorption, intercalation, and redox reactions. These electrodes exhibit reduced charge transfer resistance, improved electronic conductivity and notably enhanced specific capacitance (∼222 F g −1 ), and charge transport, as measured in 1 M Na 2 SO 4 electrolyte via cyclic voltammetry and electrochemical impedance spectroscopy. To this end, the discovery of the metal ion-induced phase transformation presents a new avenue for optimizing the functional properties of fCAS and cCAS nanostructures, highlighting the critical role of metal ion-related defects in controlling the optical and electrochemical properties, towards potential solar absorption and energy storage applications.

25 ENERGY STORAGE↗

Deep-ultraviolet ptychographic pocket-scope (DART): mesoscale lensless molecular imaging with label-free spectroscopic contrast

The mesoscale characterization of biological specimens has traditionally required compromises between resolution, field-of-view, depth-of-field, and molecular specificity, with most approaches relying on external labels. Here we present the Deep-ultrAviolet ptychogRaphic pockeT-scope (DART), a handheld platform that transforms label-free molecular imaging through intrinsic deep-ultraviolet spectroscopic contrast. By leveraging biomolecules’ natural absorption fingerprints and combining them with lensless ptychographic microscopy, DART resolves down to 308-nm linewidths across centimeter-scale areas while maintaining millimeter-scale depth-of-field. The system’s virtual error-bin methodology effectively eliminates artifacts from limited temporal coherence and other optical imperfections, enabling high-fidelity molecular imaging without lenses. Through differential spectroscopic imaging at deep-ultraviolet wavelengths, DART quantitatively maps nucleic acid and protein distributions with femtogram sensitivity, providing an intrinsic basis for explainable virtual staining. We demonstrate DART’s capabilities through imaging of tissue sections, cytopathology specimens, blood cells, and neural populations, revealing detailed molecular contrast without external labels. The combination of high-resolution molecular mapping and broad mesoscale imaging in a portable platform opens new possibilities from rapid clinical diagnostics, tissue analysis, to biological characterization in space exploration.

60 APPLIED LIFE SCIENCES↗