Optimizing Biofuel Production: Integrating NIR Imaging and Machine Learning for Corn Stover Characterization
This talk with deals with NIR imaging and Machine Learning methods for characterization of corn stover.
09 BIOMASS FUELS↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Multimodal Defect Imaging of Pure Tungsten Components Fabricated via Electron Beam Powder Bed Fusion
The utilization of additive manufacturing (AM) techniques for refractory materials in high-temperature environments has significantly expanded because of the ability to fabricate geometrically complex components. Electron beam powder bed fusion (EB-PBF), which provides lower residual stress, a cleaner vacuum environment, and better efficiency for high melting point, is one of the best-suited AM methods to produce advanced refractory components. However, the property variation attributed to the heterogeneous microstructure and process-induced defects has hindered the widespread adoption of EB-PBF-produced material like tungsten. While numerous in-situ monitoring and defect detection methods have been demonstrated for EB-PBF, a workflow that compares and evaluates process-induced abnormalities from different imaging perspectives is still limited. This study examines a feature-embedded tungsten component manufactured via the EB-PBF process to demonstrate the defect detection capabilities of a multimodal defect imaging workflow. The predefined and process-induced defects are evaluated by harnessing various imaging techniques, including in-situ electron imaging, layerwise near-infrared (NIR) imaging, post-build high-energy x-ray computed tomography (CT), and conventional destructive metallography. The results highlight the strengths and limitations of distinctive defect imaging techniques concerning specific defect types, sizes, and conditions. It was found that electron imaging can provide more abnormal detection capabilities while maintaining a higher measuring accuracy, against the conventional metallography in this case study, compared with NIR and CT imaging techniques.
36 MATERIALS SCIENCE↗
Demonstrating Advanced Sensors for In-Situ Monitoring Towards Qualification of Nuclear Relevant Components
The U.S. Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing qualification of laser powder bed fusion (LPBF) components for nuclear applications. A major focus of this effort is the use of in situ process monitoring and machine learning–based tools to establish real-time quality assurance. The primary objective of this report is to identify and evaluate the most relevant in situ sensor systems for LPBF, and to document the deployment of these systems across platforms critical to the AMMT program. This work demonstrates how in situ monitoring can detect process anomalies, track geometry-dependent flaws, and identify limiting combinations of processing parameters—particularly those related to energy density and complex geometries (e.g., overhanging structures). To support this goal, a diverse suite of sensor modalities was evaluated across LPBF platforms, including visible and near-infrared (NIR) imaging, fringe projection profilometry, long-wavelength infrared (LWIR) thermography, and high-speed photodiode/pyrometry systems. These sensor streams were integrated with Peregrine, a machine-agnostic software platform that, among other capabilities, can generate real-time process anomaly classification. This report documents sensor deployments on multiple AMMT flagship platforms, including the Concept Laser M2 and Renishaw AM400/AM250 systems. Calibration builds with complex, flaw-prone geometries such as unsupported overhangs, stepped features, and thin walls, were used to evaluate how well Peregrine and its associated sensors could detect process anomalies and other instabilities under varied energy densities. It will be shown how Peregrine reliably identifies common process anomalies such as recoater streaking, superelevation, etc., and can be used in post-build analysis for anomaly spatial distributions throughout the build height to better understand the impact of geometry and processing parameter choice on the build. This work demonstrates measurable progress toward the vision that components can be born-qualified by establishing a real-time monitoring framework, identifying limiting process conditions, and laying the foundation for sensor fusion–enabled prediction pipelines that are scalable across platforms and applicable to nuclear-relevant components.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Superconducting nanowire single-photon detector enhanced near-infrared II portable confocal microscopy for tissue imaging with indocyanine green
In this Letter a novel, to our knowledge, approach for near-infrared (NIR) fluorescence portable confocal microscopy is introduced, aiming to enhance fluorescence imaging of biological samples in the NIR-II window. By integrating a superconducting nanowire single-photon detector (SNSPD) into a confocal microscopy, we have significantly leveraged the detection efficiency of the NIR-II fluorescence signal from indocyanine green (ICG), an FDA-approved dye known for its NIR-II fluorescence capabilities. The SNSPD, characterized by its extremely low dark count rate and optimized NIR system detection efficiency, enables the excitation of ICG with 1 mW and the capture of low-light fluorescence signals from deep regions (up to 512 µm). Consequently, our technique was able to produce high-resolution images of bio samples with a superior signal-to-noise ratio, making a substantial advancement in the field of fluorescence microscopy and offering a promising opportunity for future clinical study.
Liu, Yifan (ORCID:0000000328877704)↗
Strong NIR II Chiroptical Response and Magnetic Anisotropy via Modular Installation of Chiral Capping Ligands on a Light-Emitting Diradicaloid Scaffold
Low-energy molecular lumiphores have seen increased interest due to potential imaging and communications applications. Specifically, molecules that emit in the near-infrared (NIR, 700–1700 nm) or telecom (∼1260–1625 nm) regions, where attenuation is minimized in biological tissue and optical fibers, respectively, can drastically improve image resolution and depth penetration; however, bright low-energy emission is rare due to exponentially decreasing quantum yields in this region. Chiral molecules exhibiting strong NIR or telecom absorption/emission would be of particular interest due to advanced security and spintronics applications, but these compounds remain scarce and are currently restricted to lanthanide or nanoparticle-based systems. Here, we report the synthesis of a chiral organic-based NIR emitter, enabled by simple peripheral installation of chiral capping ligands. These ligands twist the achiral NIR-emissive core, breaking inversion symmetry. Furthermore, this twisting enables strong chiroptical responses observed via static and transient circular dichroism and increased magnetic anisotropy through electron paramagnetic resonance (EPR) measurements, establishing this strategy as a promising method for the development of new chiral emitters and sensors.
Electron paramagnetic resonance spectroscopy↗
Infrared quantum ghost imaging of living and undisturbed plants
Quantum ghost imaging (QGI) is a method that measures absorption at extremely low light intensities. Nondegenerate QGI probes a sample at one wavelength while forming an image with correlated photons at a different wavelength. This spectral separation alleviates the need for imaging detectors with high sensitivity in the near-infrared (NIR) region, thereby reducing the required illumination intensity. Using NCam, a single-photon detector, we demonstrated nondegenerate QGI with unprecedented sensitivity and contrast, obtaining images of living plants with less than 1% light transmission. The plants experienced 3aW/cm 2 of light during imaging, orders of magnitude below starlight. This realization of QGI expands the method to extremely low-light bioimaging and imaging of light-sensitive samples, where minimizing illumination intensity is crucial to prevent phototoxicity or sample degradation.
47 OTHER INSTRUMENTATION↗
NDVI and Multispectral Images, UAS Flights, Council Road Site, Seward Peninsula, Alaska, June 2022
The dataset contains Normalized Difference Vegetation Index (NDVI) and multispectral images collected on June 18, 2022 using an UAS (Unmanned Aerial System) Yuneec H520, Mapir Survey 3, and Parrot Sequoia cameras. This data was created to accompany the following datasets:- NGEE Arctic CO2, CH4 and Energy Eddy-Covariance (EC) Flux Tower Auxiliary Measurements, Council Road Mile Marker 71, Seward Peninsula, Alaska (https://doi.org/10.5440/1526749)- Sun-induced chlorophyll fluorescence/eddy covariance measurements at NGEE Arctic Council site, Seward Peninsula, Alaska, 2022 (https://doi.org/10.15485/2466175)- NGEE Arctic Meteorological Data from Instrumented PCDC Stations, Council Site, Seward Peninsula, Alaska, 2018 - 2023 (https://doi.org/10.5440/1529604)Survey 3 is RGN (Red, Greeen, Near Infra Red) camera with 87° Horizontal Field of View (HFOV) (19mm) f/2.8 Aperture, 550nm/660nm/850nm (Red+Green+NIR) filter transmission and produced geo referenced jpg and raw format images. Parrot Sequoia is a camera with 16 megapixel RGB (Red, Green, Blue) sensor and 1.2 megapixel monochrome sensors in discrete spectral bands: Green (550nm - 40Nm Bandwidth), Red (660nm - 40nm Bandwidth), Red Edge (735nm - 10nm Bandwidth) and Near Infrared (790nm - 40nm Bandwidth).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
54 ENVIRONMENTAL SCIENCES↗
Combined TDLAS and chemiluminescence imaging in a flat flame burner operated with NH3/H2 blends
Ammonia is viewed as a viable hydrogen carrier due to favorable storage and transport characteristics. While it can be re-converted to hydrogen at point-of-use via thermal catalytic cracking, direct utilization in combustion systems can result in reduced costs and improved efficiency. A major barrier to this approach is the low flammability and potential for high nitrogen oxide emissions, driven by fuel-bound nitrogen and complex kinetic pathways. While a number of kinetic mechanisms currently exist for simulating ammonia combustion, a major need continues to be direct information about species profiles in easy-to-model systems capable of isolating chemical kinetics from multi-dimensional fluid dynamic effects. This paper reports on recent species measurements made in a flat flame burner using a combined tunable-diode-laser-absorption-spectroscopy (TDLAS) and chemiluminescence imaging approach. Three flame conditions were included representative of NH3/H2 blends, partially cracked NH3 (inc. N2), and 100% NH3 with enhanced air (30% oxygen). Two NIR distributed feedback (DFB) laser diodes were used to determine H2O concentration and temperature (via ratio thermometry) at various radial and axial positions, after which an inverse Abel transform was used to infer centerline values. Companion images were collected using a Princeton Instrument PI-MAX intensified camera equipped with a 105mm UV lens and multiple filter sets targeting OH*, NH*, and NH2* emission. Results were compared to companion Cantera burner-stabilized flame simulations using various kinetic mechanisms. A recent mechanism including excited species chemistry was also included, to investigate whether excited and ground state profiles exhibit significant differences.
ammonia combustion↗
Above the Energy Gap Law: Heavy Chalcogenide Substitution in NIR II-Emissive Diradicaloid Qubits
Near-infrared (NIR, 700–1700 nm)- and telecom (∼1260–1625 nm)-emissive molecules are good candidates for biological imaging and quantum sensing applications, respectively; however, bright low energy emission is rare due to exponentially increasing nonradiative decay rates in these regions, a phenomenon known as the energy gap law. Recent literature has emphasized the importance of minimizing skeletal modes to prevent increased nonradiative decay rates, but most organic lumiphores in these regions utilize large, conjugated scaffolds containing many C═C modes. Here we report a compact, telecom-emissive scaffold, tetrathiafulvalene-2,3,6,7-tetraselenate, or TTFts, that displays remarkable air, water, and acid stability, exhibits record quantum yields and brightness values, and retains quantum coherence under ambient conditions. These properties are enabled through methodical selenium substitution, which bathochromically shifts emission while shifting skeletal vibrations to lower energies. This new scaffold validates heavy heteroatom substitution strategies and establishes a new class of bright telecom emitters and robust qubits.
biological imaging↗
In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems
Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.
36 MATERIALS SCIENCE↗
In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems
Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.
36 MATERIALS SCIENCE↗
Photothermal Properties of Nanostructured Black Titanium Dioxide for Targeted Cellular and Microbial Elimination
Heterophase black titanium dioxide (hB-TiO 2 ), characterized by broadened near-infrared (NIR) absorption, has emerged as a promising photothermally active nanomaterial. This study focused on the synthesis of nanoscale hB-TiO 2 and its evaluation as a multifunctional agent for photothermal therapy (PTT). The purity and composition of the mixed-phase nanoscale hB-TiO 2 were demonstrated by X-ray diffraction, and the morphology of nanoparticles was imaged by transmission electron microscopy. Extensive additional characterization was conducted to validate the optoelectronic properties. The material was further evaluated in biological systems using NIH 3T3-GFP fibroblasts and the fungus Candida albicans. Nanoscale hB-TiO 2 exhibited good biocompatibility in the absence of laser irradiation and effectively ablated both NIH 3T3-GFP cells and C. albicans following 20 min of laser exposure. This noninvasive treatment strategy leverages NIR-responsive materials to induce localized hyperthermia. The findings provide grounds for the use of selectively induced hyperthermia, which could be employed for the targeted destruction of cells or fungi with minimal impact on surrounding tissue if the material is functionalized with specific targeting groups and delivered to cells or fungal infections.
Irradiation↗
Deep drilling in the time domain with DECam – II: characterizing the light curves of candidates in the extragalactic fields
ABSTRACT In this second paper on the DECam deep-drilling field (DDF) program, we release 2020 optical $gri$-band light curves for transients and variables in the extragalactic COSMOS and ELAIS fields based on time series observations with a 3-d cadence from semester 2021A through 2023A. In order to demonstrate the wide variety of time domain events detected by the program and encourage others to use the data set, we characterize the sample by presenting a brief analysis of the light-curve parameters such as time span, amplitude, and peak brightness. We also present preliminary light-curve categorizations, and identify potential stellar variables, active galactic nuclei, tidal disruption events, supernovae (SNe) (such as Type Ia, Type IIP, superluminous, and gravitationally lensed SNe), and fast transients. Where relevant, the number of identified transients is compared to the predictions of the original proposal. We also discuss the challenges of analyzing DDF data in the context of the upcoming Vera C. Rubin Observatory and its Legacy Survey of Space and Time, which will include DDFs. Images from the Dark Energy Camera DDF program are available without proprietary period and the light curves presented in this work are publicly available for analysis.
Graham, Melissa L. (ORCID:0000000291543136)↗
Synergistic Alignment of Low Aspect‐Ratio π‐Conjugated Molecules Enables Exceptional UV–vis–NIR Polarization Detection
Abstract Polarization detection enhances signal contrast and is widely utilized in diverse advanced applications. An ongoing challenge is the development of high‐performance polarization‐sensitive photodetectors based on optically anisotropic organic semiconductors, particularly in the near‐infrared (NIR) region. While uniaxially aligned π‐conjugated polymers with high aspect ratios exhibit strong linear dichroism and have shown promise, their limited NIR performance and heavy reliance on polymer material now represent critical limitations. Here, a breakthrough is reported in achieving giant linear dichroism and exceptional polarization detection with low aspect‐ratios (AR) non‐fullerene small‐molecule (NFSM) acceptors, extending polarization sensitivity from the UV–vis to the NIR range. An impressive dichroic ratio of 27.1 at 605 nm and 12.0 at 780 nm is demonstrated. The maximum polarization photocurrent ratio is 11.2 at 780 nm under parallel versus perpendicular polarized light. This unprecedented performance originates from synergistic molecular alignment, wherein NFSMs significantly enhance the uniaxial orientation of both the polymer matrix and the NFSMs themselves during self‐assembly and thermal annealing. Besides, such a linear‐polarization‐sensitive photodetectors (LPS‐PDs) are showcased in generating degree‐of‐linear‐polarization imaging. The work establishes NFSMs as a viable material system for next‐generation of organic LPS‐PDs and provides fundamental insights into structural origins of polarization sensitivity in low AR organic semiconductors.
Xue, Yingying↗
A Solvatochromic Near Infrared Fluorophore Sensitive to the Full Amyloid Beta Aggregation Pathway
Alzheimer's disease has long been associated with the aggregation of amyloid beta peptides (Aβ42) into macroscale plaques, although specific neurodegenerative agents have not been definitively identified. Much evidence has pointed to the soluble nanoscale oligomers that form early in the Aβ42 aggregation pathway, but there is little understanding of these structures, their mechanisms of formation, or how they grow into plaques. Here, we show that a solvatochromic fluorophore with near-infrared (NIR) emission can track synthetic Aβ42 aggregation through environment-sensitive spectral shifts from the earliest time points through plaque formation. This azide-functionalized phosphine oxide azetidine rhodol (Phazr-N3) shows large polarity-dependent changes in fluorescence emission, with maxima shifting from 630 nm in toluene to 703 nm in aqueous buffer, and a maximum quantum yield of 62%. Upon induction of Aβ42 aggregation, we observe immediate solvatochromic changes in Phazr-N3 fluorescence, with multiple apparent phases over 12 h, and which culminate before the onset of any major fluorescence changes of conformation-specific aggregation fluorophore thioflavin T. Solution anisotropy measurements show a low micromolar affinity of Phazr-N3 for disordered, free Aβ42 in solution, and real-time measurements are consistent with rapid liquid-liquid phase separation and slow dehydration of the growing aggregate. Spectral imaging of synthetic plaques stained in the presence of live cells and lipid-binding protein albumin shows over 4000-fold Phazr-N3 fluorescence intensity above background under no-wash conditions, and over 100-fold intensity above coplated microglial cells or a large excess of albumin. This use of a solvatochromic probe with structure-independent binding to free Aβ42 offers real-time, minimally invasive insight into the full Aβ42 aggregation pathway.
Wang, Zeming↗
Quantum Imaging of Ferromagnetic van der Waals Magnetic Domain Structures at Ambient Conditions
Recently discovered 2D van der Waals magnetic materials, and specifically iron–germanium–telluride (Fe5GeTe2), have attracted significant attention both from a fundamental perspective and for potential applications. Key open questions concern their domain structure and magnetic phase transition temperature as a function of sample thickness and external field, as well as implications for integration into devices such as magnetic memories and logic. Here we address key questions using a nitrogen-vacancy center based quantum magnetic microscope, enabling direct imaging of the magnetization of Fe5GeTe2 at submicrometer spatial resolution as a function of temperature, magnetic field, and thickness. This quantum imaging technique provides noninvasive, high-sensitivity measurements with high spatial resolution under ambient conditions, making it particularly well suited for probing 2D magnets. We employ spatially resolved measures, including magnetization variance and cross-correlation, and find a significant spread in transition temperature yet with no clear dependence on thickness down to 15 nm. We also identify previously unknown stripe features in the optical as well as magnetic images, which we attribute to modulations of the constituting elements during crystal synthesis and subsequent oxidation. Our results suggest that the magnetic anisotropy in this material does not play a crucial role in their magnetic properties, leading to a magnetic phase transition of Fe5GeTe2 which is largely thickness-independent down to 15 nm. Our findings could be significant in designing future spintronic devices, magnetic memories, and logic with 2D van der Waals magnetic materials.
Bindu, Bindu [Hebrew University of Jerusalem, Isra↗