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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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At least 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Quantifying Interannual Variability for Photovoltaic Systems in PVWatts

The National Renewable Energy Laboratory's (NREL's) PVWatts is a relatively simple tool used by industry and individuals alike to easily estimate the amount of energy a photovoltaic (PV) system will produce throughout the course of a typical year. PVWatts Version 5 has previously been shown to be able to reasonably represent an operating system's output when provided with concurrent weather data, however this type of data is not available when estimating system output during future time frames. For this purpose PVWatts uses weather data from typical meteorological year (TMY) datasets which are available on the NREL website. The TMY files represent a statistically 'typical' year which by definition excludes anomalous weather patterns and as a result may not provide sufficient quantification of project risk to the financial community. It was therefore desired to quantify the interannual variability associated with TMY files in order to improve the understanding of risk associated with these projects. To begin to understand the interannual variability of a PV project, we simulated two archetypal PV system designs, which are common in the PV industry, in PVWatts using the NSRDB's 1961-1990 historical dataset. This dataset contains measured hourly weather data and spans the thirty years from 1961-1990 for 239 locations in the United States. To note, this historical dataset was used to compose the TMY2 dataset. Using the results of these simulations we computed several statistical metrics which may be of interest to the financial community and normalized the results with respect to the TMY energy prediction at each location, so that these results could be easily translated to similar systems. This report briefly describes the simulation process used and the statistical methodology employed for this project, but otherwise focuses mainly on a sample of our results. A short discussion of these results is also provided. It is our hope that this quantification of the interannual variability of PV systems will provide a starting point for variability considerations in future PV system designs and investigations. however this type of data is not available when estimating system output during future time frames.

14 SOLAR ENERGY↗
DOE OSTI2013

A novel Whole Air Sample Profiler (WASP) for the quantification of volatile organic compounds in the boundary layer

The emission and fate of reactive VOCs is of inherent interest to those studying chemical biosphere-atmosphere interactions. In-canopy VOC observations are obtainable using tower-based samplers, but the lack of suitable sampling systems for the full boundary 5 layer has limited the data characterizing the vertical structure of such gases above the canopy height and still in the boundary layer. This is the important region where many reactive VOCs are oxidized or otherwise removed. Here we describe an airborne sampling system designed to collect a vertical profile of air into a 3/800 OD tube 150m in length. The inlet ram air pressure is used to flow sampled air through the 10 tube, which results in a varying flow rate based on aircraft speed and altitude. Since aircraft velocity decreases during ascent, it is necessary to account for the variable flow rate into the tube. This is accomplished using a reference gas that is pulsed into the air stream so that the precise altitude of the collected air can be reconstructed post-collection. The pulsed injections are also used to determine any significant effect 15 from diffusion/mixing within the sampling tube, either during collection or subsequent extraction for gas analysis. This system has been successfully deployed, and we show some measured vertical profiles of isoprene and its oxidation products methacrolein and methyl vinyl ketone from a mixed canopy near Columbia, Missouri.

Mak, J. E.↗
DOE OSTI2023

Carbon-Assisted, Continuous Syngas Production in a Chemical Looping Scheme

In the current energy and environment scenario, it is imperative to develop energy efficient routes for chemical manufacturing that also pave the way for mitigation of greenhouse gas emissions. This work presents an efficient pathway for continuous syngas production via a chemical looping conversion of the two most potent greenhouse gases—CH 4 , and CO 2 . The well-known dry-reforming process of converting CH 4 , and CO 2 to syngas is energy-intensive and suffers from catalyst deactivation. The chemical looping approach, on the other hand, provides avenues for mitigating catalyst deactivation and enabling improved energy efficiency. The key to such process enhancements lies in the intricate structure–function relationships of the catalyst and its correlation to the process variables. We present the reduction and oxidation characteristics of 5 wt.% Ni/Ce 1-x Zr x O 2 -based catalysts (x = 0, 0.4, and 0.625). We demonstrate low temperature CH4 activation over Ni-promoted samples as opposed to pure Ce 1-x Zr x O 2 . Moreover, our results depict an optimum regeneration of these catalysts when oxidized by CO 2 , and H 2 O, which allows for chemical looping operation of steam reforming of methane as well. Process variables were tuned to optimize the CH 4 conversion (over 80%), and H 2 /CO ratio at 650 °C. The critical surface reactions—carbon accumulation and gasification, and thermocatalytic CO 2 splitting were investigated to elucidate the dynamic nature of the catalyst surface. In conclusion, the impact of this work lies in showcasing the opportunities to design chemical looping reactors for energy efficient syngas production from waste greenhouse gases.

25 ENERGY STORAGE↗
DOE OSTI2015

SUN-LIKE MAGNETIC CYCLES IN THE RAPIDLY ROTATING YOUNG SOLAR ANALOG HD 30495

A growing body of evidence suggests that multiple dynamo mechanisms can drive magnetic variability on different timescales, not only in the Sun but also in other stars. Many solar activity proxies exhibit a quasi-biennial (∼2 year) variation, which is superimposed upon the dominant 11 year cycle. A well-characterized stellar sample suggests at least two different relationships between rotation period and cycle period, with some stars exhibiting long and short cycles simultaneously. Within this sample, the solar cycle periods are typical of a more rapidly rotating star, implying that the Sun might be in a transitional state or that it has an unusual evolutionary history. In this work, we present new and archival observations of dual magnetic cycles in the young solar analog HD 30495, a ∼1 Gyr old G1.5 V star with a rotation period near 11 days. This star falls squarely on the relationships established by the broader stellar sample, with short-period variations at ∼1.7 years and a long cycle of ∼12 years. We measure three individual long-period cycles and find durations ranging from 9.6 to 15.5 years. We find the short-term variability to be intermittent, but present throughout the majority of the time series, though its occurrence and amplitude are uncorrelated with the longer cycle. These essentially solar-like variations occur in a Sun-like star with more rapid rotation, though surface differential rotation measurements leave open the possibility of a solar equivalence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

CENSUS OF BLUE STARS IN SDSS DR8

We present a census of the 12,060 spectra of blue objects ((g – r){sub 0} < –0.25) in the Sloan Digital Sky Survey (SDSS) Data Release 8 (DR8). As part of the data release, all of the spectra were cross-correlated with 48 template spectra of stars, galaxies, and QSOs to determine the best match. We compared the blue spectra by eye to the templates assigned in SDSS DR8. 10,856 of the objects matched their assigned template, 170 could not be classified due to low signal-to-noise ratio, and 1034 were given new classifications. We identify 7458 DA white dwarfs, 1145 DB white dwarfs, 273 rarer white dwarfs (including carbon, DZ, DQ, and magnetic), 294 subdwarf O stars, 648 subdwarf B stars, 679 blue horizontal branch stars, 1026 blue stragglers, 13 cataclysmic variables, 129 white dwarf-M dwarf binaries, 36 objects with spectra similar to DO white dwarfs, 179, quasi-stellar objects (QSOs), and 10 galaxies. We provide two tables of these objects, sample spectra that match the templates, figures showing all of the spectra that were grouped by eye, and diagnostic plots that show the positions, colors, apparent magnitudes, proper motions, etc., for each classification. Future surveys will be able to use templates similar to stars in each of the classes we identify to automatically classify blue stars, including rare types.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Diversity of Eastern North American Ant Communities along Environmental Gradients

Studies of species diversity patterns across regional environmental gradients seldom consider the impact of habitat type on within-site (alpha) and between-site (beta) diversity. This study is designed to identify the influence of habitat type across geographic and environmental space, on local patterns of species richness and regional turnover patterns of ant diversity in the northeastern United States. Specifically, I aim to 1) compare local species richness in paired open and forested transects and identify the environmental variables that best correlate with richness; and 2) document patterns of beta diversity throughout the region in both open and forested habitat. I systematically sampled ants at 67 sites from May to August 2010, spanning 10 degrees of latitude, and 1000 meters of elevation. Patterns of alpha and beta diversity across the region and along environmental gradients differed between forested and open habitats. Local species richness was higher in the low elevation and warmest sites and was always higher in open habitat than in forest habitat transects. Richness decreased as temperature decreased or elevation increased. Forested transects show strong patterns of decreasing dissimilarity in species composition between sites along the temperature gradient but open habitat transects did not. Maximum temperature of the warmest month better predicted species richness than either latitude or elevation. I find that using environmental variables as key predictors of richness yields more biologically relevant results, and produces simpler macroecological models than commonly used models which use only latitude and elevation as predictors of richness and diversity patterns. This study contributes to the understanding of mechanisms that structure the communities of important terrestrial arthropods which are likely to be influenced by climatic change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Synthesis and Observation of Emergent Phenomena in Epitaxial Heusler Compound Heterostructures

The proposal was on the synthesis and observation of emergent phenomena in epitaxial Heusler compound heterostructures. The large range of properties and number of Heusler compounds opens up a wide number of potential compounds that will exhibit emergent phenomena. The similarity, large range of relatively inexpensive, large area, high crystal quality, III-V bulk substrates, lattice parameters and the ability to tune the lattice parameters through ternary or quaternary III-V compound semiconductor epitaxial growth, makes III-V semiconductors an ideal choice for substrates for epitaxial growth of Heusler compounds. A number of half Heusler compounds have been predicted to exhibit band inversion, making them topological and are therefore expected to exhibit spin-momentum locked topological surface states with linear dispersion. Others are predicted to be semimetals with Weyl points and others semiconducting and magnetic. During the course of this grant, emphasis has been on investigating Heusler compounds with emergent phenomena and demonstrating the ability to tune their properties through alloying and strain. We have grown toplogical semimetal (PtLuSb, PtMnBi), Weyl (Co 2 MnAl, Co 2 TiGe), half metal (PtMnSb, Co 2 MnSi, Co 2 MnAl x Si 1-x , Co2FeAl), and semiconducting (CoTiSb, NiTiSn) and tuned their properties through alloying and epitaxial strain. We also investigated the closely related materials of rare-earth monopnictide, some of which have also been predicted to be topological. During the attempts to grow the PtMnBi, it was discovered that Bi, another predicted topological material when ultrathin, could be grown epitaxially on InSb, results for which are also reported here. The main focus for this effort has been on using variable photon energy and spin-dependent angle resolved photoemission (ARPES) to determine bulk band structure and surface states of pristine epitaxial films grown on III-V semiconductor and MgO substrates and correlate results with theory and transport measurements. Theory has been critical to interpretation of experimental results and has been essential in guiding experiments. The research benefited from several strong collaborations between the PIs and the beamline scientists at the Advanced Light Source at Lawrence Berkeley Laboratory, the Stanford Linear Accelerator Center (SLAC) at Stanford and at the Max Lab at Lund University in Sweden. The strong experiment - theory collaboration between the PI’s groups, the Palmstrøm group at UCSB and the Janotti group at the University of Delaware, has been critical for interpreting the experimental ARPES and magnetotransport measurements results and making predictions to guide experiments. Weekly interactive Zoom meetings made this work well. A collaboration between the Palmstrøm group and Dr. Alexei Fedorov at the Advanced Light Source (ALS) resulted in significant modifications to his end chamber to accommodate the vacuum suitcase that was designed and constructed in the Palmstrøm group at UCSB. In collaboration with beamline scientists, Drs. Makoto Hashimoto and Donghui Lu at SLAC, Palmstrøm made modifications to the vacuum suitcase and developed special sample holders that allowed samples to be grown in the Palmstrøm MBE systems at UCSB and transported in the UHV vacuum suitcase to SLAC for ARPES measurements. The development of the vacuum suitcase was essential for this grant as it has allowed variable photon energies to be used to identify surface versus bulk states on samples that could not be capped and decapped using As- or Sb-capping layers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Resampling and data augmentation for short-term PV output prediction based on an imbalanced sky images dataset using convolutional neural networks

Integrating photovoltaics (PV) into electricity grids is challenged by potentially large fluctuations in power generation. In recent years, sky image-based PV output prediction using convolutional neural networks (CNNs) has emerged as a promising approach to forecasting fluctuations. A key challenge is imbalanced sky image datasets: because of the geography of solar PV system installations, sky image datasets are often rich in sunny condition data but deficient in cloudy condition data. This imbalance contrasts with the fact that model errors are dominated by cloudy condition performance. In this study, we attempt to remedy this by exploring the enrichment and augmentation of an imbalanced sky images dataset for two PV output prediction tasks: nowcasting (predicting concurrent PV output) and forecasting (predicting 15-minute-ahead future PV output). We empirically examine the efficacy of using different resampling and data augmentation approaches to create a rebalanced dataset for model development. A three-stage greedy search is used to determine the optimal resampling approach, data augmentation techniques and over-sampling rate. The results show that for the nowcast problem, resampling and data augmentation can effectively enhance the model performance, reducing overall root mean squared error (RMSE) by an average of 4%, or a 15 std. (standard deviation) of improvement compared to the variability of the baseline model. In contrast, the treatment RMSE for the forecast problem nearly always overlaps the baseline performance at the ± 2 std. level. The optimal resampling approach expands on the original dataset by over-sampling the minority cloudy data, with the best results from large over-sampling rate (e.g., 4 ~ 6 times over-sampling of cloudy images).

14 SOLAR ENERGY↗
DOE OSTI2016

Insights into the variability of nucleated amyloid polymerization by a minimalistic model of stochastic protein assembly

Self-assembly of proteins into amyloid aggregates is an important biological phenomenon associated with human diseases such as Alzheimer’s disease. Amyloid fibrils also have potential applications in nano-engineering of biomaterials. The kinetics of amyloid assembly show an exponential growth phase preceded by a lag phase, variable in duration as seen in bulk experiments and experiments that mimic the small volumes of cells. Here, to investigate the origins and the properties of the observed variability in the lag phase of amyloid assembly currently not accounted for by deterministic nucleation dependent mechanisms, we formulate a new stochastic minimal model that is capable of describing the characteristics of amyloid growth curves despite its simplicity. We then solve the stochastic differential equations of our model and give mathematical proof of a central limit theorem for the sample growth trajectories of the nucleated aggregation process. These results give an asymptotic description for our simple model, from which closed form analytical results capable of describing and predicting the variability of nucleated amyloid assembly were derived. We also demonstrate the application of our results to inform experiments in a conceptually friendly and clear fashion. Our model offers a new perspective and paves the way for a new and efficient approach on extracting vital information regarding the key initial events of amyloid formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

A variance-based decomposition and global sensitivity index method for uncertainty quantification: Application to retrieved ice cloud properties

This study develops a novel uncertainty quantification (UQ) method for cloud microphysical property retrievals using variance-based decomposition and global sensitivity index. In this UQ framework, empirical orthogonal function (EOF) analysis is applied to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) ground-based observations, which are the inputs for the cloud retrieval studied here. The principal components (PCs) in the EOF expansion are parameterized as random input variables, and hence, the input dimension is greatly reduced (up to a factor of 50), allowing large ensemble of random samplings. The EOF expansion improves the accuracy of the uncertainty estimation by taking into account the cross correlations in the input data profiles. Here, this method enables a probabilistic representation of a retrieval process by adding normally distributed perturbations into PCs of sample means of input data profiles within a time window. Therefore, it effectively facilitates objective validation of climate models against cloud retrievals under a probabilistic framework for rigorous statistical inferences. Moreover, the variance-based global sensitivity index analysis, part of this method, attributes the output uncertainties to each individual source, thus providing directions for improving retrieval algorithms and observation strategies. For demonstration, we apply this method to quantify the uncertainties of the ARM program's baseline cloud retrieval algorithm for an ice cloud case observed at the Southern Great Plains site on 9 March 2000.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Effects of the microstructure and porosity on properties of Ti-6Al-4V ELI alloy fabricated by electron beam melting (EBM)

Electron Beam Melting (EBM) is a metal powder bed-based Additive Manufacturing (AM) technology that makes possible the fabrication of three dimensional near-net-shaped parts directly from computer models. EBM technology has been in continuously updating, obtaining optimized properties of the processed alloys. Ti-6Al-4V titanium alloy is the most widely used and studied alloy for this technology and is the focus of this work. Several research works have been completed to study the mechanisms of microstructure formation as well as its influence on mechanical properties. However, the relationship is not completely understood, and more systematic research work is necessary in order to attain a better understanding of these features. In this work, samples fabricated at different locations, orientations, and distances from the build platform have been characterized, studying the relationship of these variables with the resulting material intrinsic characteristics and properties (surface topography, microstructure, porosity, micro-hardness and static mechanical properties). This study has revealed that porosity is the main factor controlling mechanical properties relative to the other studied variables. Therefore, in future process developments, decreasing of the porosity should be considered as the primary goal in order to improve mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Predicting critical heat flux with uncertainty quantification and domain generalization using conditional variational autoencoders and deep neural networks

Deep generative models (DGMs) can generate synthetic data samples that closely resemble the original dataset, addressing data scarcity. In this work, we developed a conditional variational autoencoder (CVAE) to augment critical heat flux (CHF) data used for the 2006 Groeneveld lookup table. To compare with traditional methods, a fine-tuned deep neural network (DNN) regression model was evaluated on the same dataset. Both models achieved small mean absolute relative errors, with the CVAE showing more favorable results. Uncertainty quantification (UQ) was performed using repeated CVAE sampling and DNN ensembling. The DNN ensemble improved performance over the baseline, while the CVAE maintained consistent results with less variability and higher confidence. Both models achieved small errors inside and outside the training domain, with slightly larger errors outside. Altogether, the CVAE performed better than the DNN in predicting CHF and exhibited better uncertainty behavior.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Sources of Li isotope bias during SIMS analysis of standard glasses

The 7 Li/ 6 Li ratios in fourteen USGS, MPI-DING, and NIST glass reference materials (RMs) were analyzed by LG-SIMS to assess compositional matrix effects, evaluate RM δ 7 Li homogeneity, and calculate the useful yield of lithium in silicate glasses. The analyzed RMs cover a range of SiO 2 contents from 45.5 to 75.6% (komatiite to rhyolite), the largest compositional range yet evaluated for δ 7 Li matrix effects. We observe a matrix-induced bias (matrix effect) of up to 18‰ over the studied range that linearly correlates with SiO 2 content, demonstrating that SiO 2 content is a critical factor that must be considered when using silicate glasses to standardize for silicate samples of unknown δ 7 Li composition. All RMs were found to be sufficiently reproducible to aid in standardization of variable SiO 2 contents and appear isotopically homogeneous at the precision of our measurements. Lithium ionizes very efficiently in these RMs, with measurable yields >5% in all fused-rock RMs and >15% in low SiO 2 fused-rock RMs measured at high beam intensities. Finally, fused-rock RMs ionize lithium 2-3x more efficiently than synthetic glass RMs, which may be related to differences in major oxide chemistry and the reduced nature of the synthetic glasses relative to their fused counterparts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A theoretical kinetic study of ĊH 3 + ṄH 2 : From electronic structure to NH 3 /CH 4 combustion modelling implications

Carbon–nitrogen interaction reactions play an important role in governing the reactivity of ammonia blended fuels. However, there remains uncertainties regarding their detailed reaction pathways and rate constants, hampering the development of high-fidelity chemical kinetic models. In this study, the kinetics of ĊH 3 + ṄH 2 , a key C–N interaction reaction in ammonia/methane blend combustion have been investigated. The potential energy surface has been explored using the high-level ANL0F method, yielding highly accurate stationary point energies that agree with ATcT values within 0.1 kcal mol –1 . Variable reaction coordinate transition state theory is used to treat the barrierless association and decomposition reaction channels, based on directly sampled radical-radical interaction energies at the CASPT2-F12(2e,2o)/cc-pVTZ-F12 level of theory. The minimum transitional mode numbers of states obtained are then coupled with the RRKM/master equation to calculate temperature- and pressure-dependent rate constants. Our a priori calculations capture available experimental measurements from the literature very well. The calculated rate constants have been incorporated into an NH 3 /CH 4 chemical kinetic model currently under development at the University of Galway. The effect of the updated kinetic data for ĊH 3 + ṄH 2 on model predicted NH 3 /CH 4 fuel reactivity is elucidated.

ab initio↗
DOE OSTI2018

Effect of compositional changes on microstructure in additively manufactured aluminum alloy 2139

Highlights: • Volatile elements preferentially vaporize during additive manufacturing. • Vapor losses affect precipitate habit plane in aluminum alloy 2139. • Above 0.2 wt% Mg the precipitate forms on the preferred {111} habit plane. • Higher strength is associated with precipitates on the {111} habit planes. - Abstract: A matrix of nine experiments was conducted on aluminum alloy 2139 samples made by an electron beam directed energy deposition additive manufacturing process to characterize the effect of magnesium vaporization loss on microstructure and properties. The nine-sample matrix included three different magnesium levels deposited onto material at three different temperatures. The goal was to quantify the variability in the deposited material as a function of allowable magnesium content and the local temperature of the substrate or previous layer. The results show that temperature variations in the substrate up to 100 K have no significant effect on the amount of magnesium loss; however, relatively large variations in Mg content, up to a ±0.25 wt%, can significantly affect the microstructure and mechanical properties. This is due to a change in how the precipitate phase forms, which influences the mechanism by which the alloy is strengthened.

36 MATERIALS SCIENCE↗
DOE OSTI2024

TDCOSMO - XVI. Measurement of the Hubble constant from the lensed quasar WGD 2038–4008

Time-delay cosmography is a powerful technique to constrain cosmological parameters, particularly the Hubble constant (H0). The TDCOSMO Collaboration is performing an ongoing analysis of lensed quasars to constrain cosmology using this method. In this work, we obtain constraints from the lensed quasar WGD 2038−4008 using new time-delay measurements and previous mass models by TDCOSMO. This is the first TDCOSMO lens to incorporate multiple lens modeling codes and the full time-delay covariance matrix into the cosmological inference. The models are fixed before the time delay is measured, and the analysis is performed blinded with respect to the cosmological parameters to prevent unconscious experimenter bias. We obtain DΔ t = 1.68−0.38+0.40 Gpc using two families of mass models, a power-law describing the total mass distribution, and a composite model of baryons and dark matter, although the composite model is disfavored due to kinematics constraints. In a flat ΛCDM cosmology, we constrain the Hubble constant to be H0 = 65−14+23 km s−1 Mpc−1. The dominant source of uncertainty comes from the time delays, due to the low variability of the quasar. Future long-term monitoring, especially in the era of the Vera C. Rubin Observatory’s Legacy Survey of Space and Time, could catch stronger quasar variability and further reduce the uncertainties. This system will be incorporated into an upcoming hierarchical analysis of the entire TDCOSMO sample, and improved time delays and spatially-resolved stellar kinematics could strengthen the constraints from this system in the future.Key words: gravitational lensing: strong / cosmological parameters / distance scale⋆ Corresponding author; kcwong19@gmail.com.⋆⋆ NHFP Einstein fellow.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Phase behavior of the 38-atom Lennard-Jones cluster

We have developed a coarse-grained description of the phase behavior of the isolated 38-atom Lennard-Jones cluster (LJ{sub 38}). The model captures both the solid-solid polymorphic transitions at low temperatures and the complex cluster breakup and melting transitions at higher temperatures. For this coarse model development, we employ the manifold learning technique of diffusion mapping. The outcome of the diffusion mapping analysis over a broad temperature range indicates that two order parameters are sufficient to describe the cluster's phase behavior; we have chosen two such appropriate order parameters that are metrics of condensation and overall crystallinity. In this well-justified coarse-variable space, we calculate the cluster's free energy landscape (FEL) as a function of temperature, employing Monte Carlo umbrella sampling. These FELs are used to quantify the phase behavior and onsets of phase transitions of the LJ{sub 38} cluster.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Video-rate Raman-based metabolic imaging by Airy light-sheet illumination and photon-sparse detection

Despite its massive potential, Raman imaging represents just a modest fraction of all research and clinical microscopy to date. This is due to the ultralow Raman scattering cross-sections of most biomolecules that impose low-light or photon-sparse conditions. Bioimaging under such conditions is suboptimal, as it either results in ultralow frame rates or requires increased levels of irradiance. Here, we overcome this tradeoff by introducing Raman imaging that operates at both video rates and 1,000-fold lower irradiance than state-of-the-art methods. To accomplish this, we deployed a judicially designed Airy light-sheet microscope to efficiently image large specimen regions. Further, we implemented subphoton per pixel image acquisition and reconstruction to confront issues arising from photon sparsity at just millisecond integrations. We demonstrate the versatility of our approach by imaging a variety of samples, including the three-dimensional (3D) metabolic activity of single microbial cells and the underlying cell-to-cell variability. To image such small-scale targets, we again harnessed photon sparsity to increase magnification without a field-of-view penalty, thus, overcoming another key limitation in modern light-sheet microscopy.

60 APPLIED LIFE SCIENCES↗