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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Extrapolation of Type Ia Supernova Spectra into the Near-infrared Using Principal Component Analysis

Abstract We present a method of extrapolating the spectroscopic behavior of Type Ia supernovae (SNe Ia) in the near-infrared (NIR) wavelength regime up to 2.30 μ m using optical spectroscopy. Such a process is useful for accurately estimating K-corrections and other photometric quantities of SNe Ia in the NIR. A principal component analysis is performed on data consisting of Carnegie Supernova Project I & II optical and NIR FIRE spectra to produce models capable of making these extrapolations. This method differs from previous spectral template methods by not parameterizing models strictly by photometric light-curve properties of SNe Ia, allowing for more flexibility of the resulting extrapolated NIR flux. A difference of around −3.1% to −2.7% in the total integrated NIR flux between these extrapolations and the observations is seen here for most test cases including Branch core-normal and shallow-silicon subtypes. However, larger deviations from the observation are found for other tests, likely due to the limited high-velocity and broad-line SNe Ia in the training sample. Maximum-light principal components are shown to allow for spectroscopic predictions of the color-stretch light-curve parameter, s BV , within approximately ±0.1 units of the value measured with photometry. We also show these results compare well with NIR templates, although in most cases the templates are marginally more fitting to observations, illustrating a need for more concurrent optical+NIR spectroscopic observations to truly understand the diversity of SNe Ia in the NIR.

Astronomy & Astrophysics↗
DOE OSTI2026

Self-supervised and multi-fidelity learning for extended predictive soil spectroscopy

Infrared spectroscopy is a cost-effective, non-destructive, and environmentally benign technology that is increasingly recognized as an important solution for meeting the global demand for soil data. While both near-infrared (NIR) and mid-infrared (MIR) diffuse reflectance spectroscopy enable rapid estimation of soil properties, they present a significant trade-off: NIR offers superior scalability and lower operational costs, whereas MIR provides higher analytical fidelity by capturing fundamental molecular vibrations. In this study, we propose a self-supervised, multi-fidelity learning framework designed to bridge this gap. Our approach leverages large-scale MIR spectral libraries to learn a compact, transferable latent representation, into which NIR spectra are subsequently aligned for downstream prediction. The workflow consists of pretraining a latent model on a large MIR library, adapting the representation using a smaller paired NIR–MIR dataset, and evaluating generalization on an independent external test set. Across a range of chemical and physical soil properties, we found that MIR-derived embeddings improved prediction accuracy relative to baseline models that used raw MIR inputs. Predictions derived from the spectrum conversion (NIR to MIR) task did not match the performance of the original MIR spectra but were similar or superior to predictive performance of NIR-only models, suggesting the unified spectral latent space can effectively leverage the larger and more diverse MIR dataset for prediction of soil properties not well represented in current NIR libraries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing

Abstract Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine Learning. Despite a well-established mathematical foundation for neural dynamics, there exists numerous software and hardware solutions and stacks whose variability makes it difficult to reproduce findings. Here, we establish a common reference frame for computations in digital neuromorphic systems, titled Neuromorphic Intermediate Representation (NIR). NIR defines a set of computational and composable model primitives as hybrid systems combining continuous-time dynamics and discrete events. By abstracting away assumptions around discretization and hardware constraints, NIR faithfully captures the computational model, while bridging differences between the evaluated implementation and the underlying mathematical formalism. NIR supports an unprecedented number of neuromorphic systems, which we demonstrate by reproducing three spiking neural network models of different complexity across 7 neuromorphic simulators and 4 digital hardware platforms. NIR decouples the development of neuromorphic hardware and software, enabling interoperability between platforms and improving accessibility to multiple neuromorphic technologies. We believe that NIR is a key next step in brain-inspired hardware-software co-evolution, enabling research towards the implementation of energy efficient computational principles of nervous systems. NIR is available atneuroir.org

Science & Technology - Other Topics↗
DOE OSTI2011

NEAR-INFRARED REVERBERATION BY DUSTY CLUMPY TORI IN ACTIVE GALACTIC NUCLEI

According to recent models, the accretion disk and black hole in active galactic nuclei (AGNs) are surrounded by a clumpy torus. We investigate the NIR flux variation of the torus in response to a UV flash for various geometries. Anisotropic illumination by the disk and the torus self-occultation contrast our study with earlier works. Both the waning effect of each clump and the torus self-occultation selectively reduce the emission from the region with a short delay. Therefore, the NIR delay depends on the viewing angle (where a more inclined angle leads to a longer delay), and the time response shows an asymmetric profile with negative skewness, opposing the results for optically thin tori. The range of the computed delay coincides with the observed one, suggesting that the viewing angle is primarily responsible for the scatter of the observed delay. We also propose that the red NIR-to-optical color of type 1.8/1.9 objects is caused not only by the dust extinction but also the intrinsically red color. Compared with the modest torus thickness, both a thick and a thin tori display weaker NIR emission. A selection bias is thus expected such that NIR-selected AGNs tend to possess moderately thick tori. A thicker torus shows a narrower and more heavily skewed time profile, while a thin torus produces a rapid response. A super-Eddington accretion rate leads to much weaker NIR emission due to the disk self-occultation and the disk truncation by self-gravity. A long delay is expected from an optically thin and/or a largely misaligned torus. Very weak NIR emission, such as in hot-dust-poor active nuclei, can arise from a geometrically thin torus, a super-Eddington accretion rate, or a slightly misaligned torus.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Probing reionization with the cross-power spectrum of 21 cm and near-infrared radiation backgrounds

The cross-correlation between the 21 cm emission from the high-redshift intergalactic medium and the near-infrared (NIR) background light from high-redshift galaxies promises to be a powerful probe of cosmic reionization. In this paper, we investigate the cross-power spectrum during the epoch of reionization. We employ an improved halo approach to derive the distribution of the density field and consider two stellar populations in the star formation model: metal-free stars and metal-poor stars. The reionization history is further generated to be consistent with the electron-scattering optical depth from cosmic microwave background measurements. Then, the intensity of the NIR background is estimated by collecting emission from stars in first-light galaxies. On large scales, we find that the 21 cm and NIR radiation backgrounds are positively correlated during the very early stages of reionization. However, these two radiation backgrounds quickly become anti-correlated as reionization proceeds. The maximum absolute value of the cross-power spectrum is |Δ{sub 21,NIR}{sup 2}|∼10{sup −4} mK nW m{sup –2} sr{sup –1}, reached at ℓ ∼ 1000 when the mean fraction of ionized hydrogen is x-bar{sub i}∼0.9. We find that Square Kilometer Array can measure the 21 cm-NIR cross-power spectrum in conjunction with mild extensions to the existing CIBER survey, provided that the integration time independently adds up to 1000 and 1 hr for 21 cm and NIR observations, and that the sky coverage fraction of the CIBER survey is extended from 4 × 10{sup –4} to 0.1. Measuring the cross-correlation signal as a function of redshift provides valuable information on reionization and helps confirm the origin of the 'missing' NIR background.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

An infrared and optical analysis of a sample of XBONGs and optically elusive AGNs

We present near-infrared (NIR) spectra of four optically elusive active galactic nuclei (AGNs) and four X-ray bright, optically normal galaxies (XBONGs) from the Swift-BAT survey. With archival observations from the Sloan Digital Sky Survey, the Two Micron All Sky Survey, Spitzer, and the Wide-field Infrared Survey Explorer (WISE), we test a number of AGN indicators in the NIR and mid-infrared; namely, NIR emission line diagnostic ratios, the presence of coronal high-ionization lines, and infrared photometry. Of our eight hard X-ray selected AGNs, we find that optical normalcy has a variety of causes from object to object, and no one explanation applies. Our objects have normal Eddington ratios and so are unlikely to host radiatively inefficient accretion flows. It is unlikely that star formation in the host or starlight dilution is contributing to their failure of optical diagnostics, except perhaps in two cases. The NIR continua are well fit by two blackbodies: one at the stellar temperature, and a hot dust component near the dust sublimation temperature. The XBONGs are more likely to have significant hot dust components, while these components are small relative to starlight in the optically elusive AGN. Some of our sample have NIR line ratios typical of AGNs, but NIR diagnostics are unsuccessful in distinguishing H II regions from AGNs in general. In one object, we discover a hidden broad-line region in the NIR. These results have strong relevance to the origin of optically normal AGNs in deep X-ray surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

ON THE DISTANCE OF THE GLOBULAR CLUSTER M4 (NGC 6121) USING RR LYRAE STARS. I. OPTICAL AND NEAR-INFRARED PERIOD-LUMINOSITY AND PERIOD-WESENHEIT RELATIONS

We present new distance determinations to the nearby globular M4 (NGC 6121) based on accurate optical and near-infrared (NIR) mean magnitudes for fundamental (FU) and first overtone (FO) RR Lyrae variables (RRLs), and new empirical optical and NIR period-luminosity (PL) and period-Wesenheit (PW) relations. We have found that optical-NIR and NIR PL and PW relations are affected by smaller standard deviations than optical relations. The difference is the consequence of a steady decrease in the intrinsic spread of cluster RRL apparent magnitudes at fixed period as longer wavelengths are considered. The weighted mean visual apparent magnitude of 44 cluster RRLs is =13.329 ± 0.001 (standard error of the mean) ±0.177 (weighted standard deviation) mag. Distances were estimated using RR Lyr itself to fix the zero-point of the empirical PL and PW relations. Using the entire sample (FU+FO) we found weighted mean true distance moduli of 11.35 ± 0.03 ± 0.05 mag and 11.32 ± 0.02 ± 0.07 mag. Distances were also evaluated using predicted metallicity dependent PLZ and PWZ relations. We found weighted mean true distance moduli of 11.283 ± 0.010 ± 0.018 mag (NIR PLZ) and 11.272 ± 0.005 ± 0.019 mag (optical-NIR and NIR PWZ). The above weighted mean true distance moduli agree within 1σ. The same result is found from distances based on PWZ relations in which the color index is independent of the adopted magnitude (11.272 ± 0.004 ± 0.013 mag). These distances agree quite well with the geometric distance provided by Kaluzny et al. based on three eclipsing binaries. The available evidence indicates that this approach can provide distances to globulars hosting RRLs with a precision better than 2%-3%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Utilization of Synthetic Near-Infrared Spectra via Generative Adversarial Network to Improve Wood Stiffness Prediction

Near-infrared (NIR) spectroscopy is widely used as a nondestructive evaluation (NDE) tool for predicting wood properties. When deploying NIR models, one faces challenges in ensuring representative training data, which large datasets can mitigate but often at a significant cost. Machine learning and deep learning NIR models are at an even greater disadvantage because they typically require higher sample sizes for training. In this study, NIR spectra were collected to predict the modulus of elasticity (MOE) of southern pine lumber (training set = 573 samples, testing set = 145 samples). To account for the limited size of the training data, this study employed a generative adversarial network (GAN) to generate synthetic NIR spectra. The training dataset was fed into a GAN to generate 313, 573, and 1000 synthetic spectra. The original and enhanced datasets were used to train artificial neural networks (ANNs), convolutional neural networks (CNNs), and light gradient boosting machines (LGBMs) for MOE prediction. Overall, results showed that data augmentation using GAN improved the coefficient of determination (R 2 ) by up to 7.02% and reduced the error of predictions by up to 4.29%. ANNs and CNNs benefited more from synthetic spectra than LGBMs, which only yielded slight improvement. All models showed optimal performance when 313 synthetic spectra were added to the original training data; further additions did not improve model performance because the quality of the datapoints generated by GAN beyond a certain threshold is poor, and one of the main reasons for this can be the size of the initial training data fed into the GAN. LGBMs showed superior performances than ANNs and CNNs on both the original and enhanced training datasets, which highlights the significance of selecting an appropriate machine learning or deep learning model for NIR spectral-data analysis. The results highlighted the positive impact of GAN on the predictive performance of models utilizing NIR spectroscopy as an NDE technique and monitoring tool for wood mechanical-property evaluation. Further studies should investigate the impact of the initial size of training data, the optimal number of generated synthetic spectra, and machine learning or deep learning models that could benefit more from data augmentation using GANs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

PROXIMA CENTAURI AS A BENCHMARK FOR STELLAR ACTIVITY INDICATORS IN THE NEAR-INFRARED

A new generation of dedicated Doppler spectrographs will attempt to detect low-mass exoplanets around mid- to late M stars at near-infrared (NIR) wavelengths, where those stars are brightest and have the most Doppler information content. A central requirement for the success of these instruments is to properly measure the component of radial velocity (RV) variability contributed by stellar magnetic activity and to account for it in exoplanet models of RV data. The wavelength coverage for many of these new instruments will not include the Ca ii H and K or H α lines, the most frequently used absorption-line tracers of magnetic activity. Thus, it is necessary to define and characterize NIR activity indicators for mid- to late M stars in order to provide simultaneous activity metrics for NIR RV data. We have used the high-cadence UVES observations of the M5.5 dwarf Proxima Centauri from Fuhrmeister et al. to compare the activity sensitivity of eight NIR atomic lines to that of H α . We find that equivalent-width-type measurements of the NIR K i doublet and the Ca ii NIR triplet are excellent proxies for the canonical optical tracers. The Ca ii triplet will be acquired by most of the new and upcoming NIR Doppler spectrographs, offering a common, reliable indicator of activity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A Differential Measurement of Circumstellar Extinction for AA Tau’s 2011 Dimming Event

AA Tau is a classical T Tauri star with a highly inclined, warped circumstellar disk. For decades, AA Tau exhibited photometric and spectroscopic variabilities that were successfully modeled as occultations of the primary star by circumstellar material. In 2011, AA Tau entered an extended faint state, presumably due to enhanced levels of circumstellar dust. We use two sets of contemporaneous optical–near-IR (NIR) spectra of AA Tau, obtained in 2008 and 2014 December, to directly measure the wavelength-dependent extinction associated with the dust enhancement driving AA Tau’s 2011 optical fade. Taken alone, AA Tau’s apparent optical–NIR increased extinction curve cannot be fit well with standard extinction laws. At optical wavelengths, AA Tau’s dimming event is consistent with predictions of common extinction models for an increase of A {sub V} = 2, but no such model reproduces AA Tau’s color–color excess at NIR wavelengths. We show that veiling emission accounts for the apparent anomalous NIR extinction: after including this veiling flux, AA Tau’s dimming event is consistent with a standard A {sub V} = 2 extinction law across the full optical–NIR range. We also report an increase in AA Tau’s mid-IR flux since its 2011 fade and suggest that an increase in the height of AA Tau’s inner disk is the most likely explanation for both the IR brightening and the additional extinction along the line of sight. In addition to informing our understanding of AA Tau, this analysis demonstrates that caution should be exercised when inferring extinction (and stellar parameters) from the NIR color–color excess of young stars with measurable NIR veiling fluxes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

THE MAGNETIC FIELD OF L1544. I. NEAR-INFRARED POLARIMETRY AND THE NON-UNIFORM ENVELOPE

The magnetic field ( B -field) of the starless dark cloud L1544 has been studied using near-infrared (NIR) background starlight polarimetry (BSP) and archival data in order to characterize the properties of the plane-of-sky B -field. NIR linear polarization measurements of over 1700 stars were obtained in the H band and 201 of these were also measured in the K band. The NIR BSP properties are correlated with reddening, as traced using the Rayleigh–Jeans color excess ( H – M ) method, and with thermal dust emission from the L1544 cloud and envelope seen in Herschel maps. The NIR polarization position angles change at the location of the cloud and exhibit their lowest dispersion there, offering strong evidence that NIR polarization traces the plane-of-sky B -field of L1544. In this paper, the uniformity of the plane-of-sky B -field in the envelope region of L1544 is quantitatively assessed. This allows evaluation of the approach of assuming uniform field geometry when measuring relative mass-to-flux ratios in the cloud envelope and core based on averaging of the radio Zeeman observations in the envelope, as done by Crutcher et al. In L1544, the NIR BSP shows the envelope B -field to be significantly non-uniform and likely not suitable for averaging Zeeman properties without treating intrinsic variations. Deeper analyses of the NIR BSP and related data sets, including estimates of the B -field strength and testing how it varies with position and gas density, are the subjects of later papers in this series.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Evaluating the Consistency of Cosmological Distances Using Supernova Siblings in the Near-infrared

Abstract The study of supernova (SN) siblings, supernovae with the same host galaxy, is an important avenue for understanding and measuring the properties of Type Ia SN Ia light curves (LCs). Thus far, sibling analyses have mainly focused on optical LC data. Considering that LCs in the near-infrared (NIR) are expected to be better standard candles than those in the optical, we carry out the first analysis compiling SN siblings with only NIR data. We perform an extensive literature search of all SN siblings and find six sets of siblings with published NIR photometry. We calibrate each set of siblings ensuring they are on homogeneous photometric systems, fit the LCs with the SALT3-NIR and SNooPy models, and find median absolute differences inμvalues between siblings of 0.248 and 0.186 mag, respectively. To evaluate the significance of these differences beyond measurement noise, we run simulations that mimic these LCs and provide an estimate for uncertainty on these median absolute differences of ∼0.052 mag, and we find that, statistically, our analysis rules out the nonexistence of intrinsic scatter in the NIR at the 99% level. When comparing the same sets of SN siblings, we observe a median absolute difference inμvalues between siblings of 0.177 mag when using optical data alone as compared to 0.186 mag when using NIR data alone. It is unclear if these results may be due to limited statistics or poor quality NIR data, all of which will be improved with the Nancy Grace Roman Space Telescope.

Astronomy & Astrophysics↗
DOE OSTI2018

Mesoporous Carbon Nanospheres as a Multifunctional Carrier for Cancer Theranostics

Optical nanomaterials with intense absorption in near-infrared (NIR) region hold great promise for biomedical applications such as photothermal therapy (PTT) and photoacoustic imaging (PAI). In this work, we report mesoporous carbon nanospheres (Meso-CNs) with broadband and intense absorption in the UV–Vis–NIR region (300–1400 nm) and explore their potential as a multifunctional platform for photoacoustic imaging and chemo-photothermal therapy. Methods: Meso-CNs were prepared by a “silica-assisted” synthesis strategy and characterized by transmission electron microscope and optical spectroscopy. We investigated the photothermal conversion and photoacoustic imaging of Meso-CNs in comparison with single-walled carbon nanotubes (SWCNTs), graphene and gold nanorods (GNRs). In vitro cellular assays and in vivo chemo-photothermal combination therapy were performed. Results: The absorption coefficients of Meso-CNs are 1.5–2 times higher than those of SWCNTs and graphene and are comparable to those of GNRs in both the first and the second near-infrared optical windows (NIR-I and NIR-II) of tissues. When exposed to an NIR laser, the photothermal and photoacoustic signal generation of Meso-CNs are also stronger than those of SWCNTs, graphene, and GNRs. DOX was loaded into Meso-CNs with a high efficiency (35 wt%) owing to the unique mesoporous structure. Particularly, the drug release from Meso-CNs is sensitive to both pH and NIR light stimulation. In vivo chemo-photothermal combination therapy demonstrates a remarkable inhibition effect on tumor growth under NIR laser treatment. Conclusions: We have developed Meso-CNs for photothermal conversion and photoacoustic imaging. The porous structure also serves as a drug carrier and the drug release can be controlled by pH and external light. The high drug loading capacity, superior photothermal and photoacoustic generation, together with the apparent chemo-photothermal therapeutic effect, make Meso-CNs a promising platform for cancer theranostics.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1993

Near-infrared spectra of the Martian surface: Reading between the lines

Moderate-resolution near-infrared (NIR) spectra of Mars have been widely used in studies of the Martian surface because many candidate surface materials have distinctive absorption features at these wavelengths. Recent advances in NIR detector technology and instrumentation have also encouraged studies in this spectral region. The use of moderate spectral resolution has often been justified for NIR surface observations because the spectral features produced by most surface materials are relatively broad, and easily discriminated at this resolution. In spite of this, NIR spectra of Mars are usually very difficult to interpret quantitatively. One problem is that NIR surface absorption features are often only a few percent deep, requiring observations with great signal-to-noise ratios. A more significant problem is that gases in the Martian atmosphere contribute numerous absorption features at these wavelengths. Ground-based observers must also contend with variable absorption by several gases in the Earth's atmosphere (H2O, CO2, O3, N2O, CH4, O2). The strong CO2 bands near 1.4, 1.6, 2.0, 2.7, 4.3, and 4.8 micrometers largely preclude the analysis of surface spectral features at these wavelengths. Martian atmospheric water vapor also contributes significant absorption near 1.33, 1.88, and 2.7 micrometers, but water vapor in the Earth's atmosphere poses a much larger problem to ground-based studies of these spectral regions. The third most important NIR absorber in the Martian atmosphere is CO. This gas absorbs most strongly in the relatively-transparent spectral windows near 4.6 and 2.3 micrometers. It also produces 1-10 percent absorption in the solar spectrum at these NIR wavelengths. This solar CO absorption cannot be adequately removed by dividing the Martian spectrum by that of a star, as is commonly done to calibrate ground-based spectroscopic observations, because most stars do not have identical amounts of CO absorption in their spectra. Here, we describe tow effective methods for eliminating contamination of Martian surface spectra by absorption in the solar, terrestrial, and Martian atmospheres. Both methods involve the use of very-high-resolution spectra that completely resolve the narrow atmospheric absorption lines.

Crisp, D.↗
NASA NTRS2004

Ground-Based VIS/NIR Reflectance Spectra of 25143 Itokawa: What Hayabusa will See and How Ground-Based Data can Augment Analyses

Planning for the arrival of the Hayabusa spacecraft at asteroid 25143 Itokawa includes consideration of the expected spectral information to be obtained using the AMICA and NIRS instruments. The rotationally-resolved spatial coverage the asteroid we have obtained with ground-based telescopic spectrophotometry in the visible and near-infrared can be utilized here to address expected spacecraft data. We use spectrophotometry to simulate the types of data that Hayabusa will receive with the NIRS and AMICA instruments, and will demonstrate them here. The NIRS will cover a wavelength range from 0.85 m, and have a dispersion per element of 250 Angstroms. Thus, we are limited in coverage of the 1.0 micrometer and 2.0 micrometer mafic silicate absorption features. The ground-based reflectance spectra of Itokawa show a large component of olivine in its surface material, and the 2.0 micrometer feature is shallow. Determining the olivine to pyroxene abundance ratio is critically dependent on the attributes of the 1.0- and 2.0 micrometer features. With a cut-off near 2,1 micrometer the longer edge of the 2.0- feature will not be obtained by NIRS. Reflectance spectra obtained using ground-based telescopes can be used to determine the regional composition around space-based spectral observations, and possibly augment the longer wavelength spectral attributes. Similarly, the shorter wavelength end of the 1.0 micrometer absorption feature will be partially lost to the NIRS. The AMICA filters mimic the ECAS filters, and have wavelength coverage overlapping with the NIRS spectral range. We demonstrate how merging photometry from AMICA will extend the spectral coverage of the NIRS. Lessons learned from earlier spacecraft to asteroids should be considered.

Vilas, Faith↗
DOE OSTI2025

Rapid monitoring of fermentations: a feasibility study on biological 2,3-butanediol production

2,3-butanediol (2,3-BDO) is an economically important platform chemical that can be produced by the fermentation of sugars using an engineered strain of Zymomonas mobilis . These fermentations require continuous monitoring and modification of fermentation conditions to maximize 2,3-BDO yields and minimize the production of the undesired coproducts glycerol and acetoin. Because of the time required for sampling and off-line chromatographic measurement of fermentation samples, the ability of fermentation scientists to modify fermentation conditions in a timely manner is limited. The goal of this study was to test if near-infrared spectroscopy (NIRS) along with multivariate statistics could reduce the time needed for this analysis and enable real-time monitoring and control of the fermentation. In this work we developed partial least squares (PLS) calibration models to predict the concentrations of glucose, xylose, 2,3-BDO, acetoin, and glycerol in fermentations via NIRS using two different spectrometers and two different spectroscopy modalities. We first evaluated the feasibility of rapid NIRS monitoring through experiments where we measured the signals from each analyte of interest and built NIRS-based PLS models using spectra from synthetic samples containing uncorrelated concentrations of these analytes. All analytes showed unique spectral signatures, and this initial modeling showed that all analytes could be detected simultaneously. We then began work with samples from laboratory fermentation experiments and tested the feasibility of regression model development across two spectral collection modalities (at-line and on-line) and two instruments: a laboratory-grade instrument and a low-cost instrument with a more limited spectral range. All modalities showed promise in the ability to monitor Z. mobilis fermentations of glucose and xylose to 2,3-BDO. The low-cost instrument displayed a lower signal-to-noise ratio than the laboratory-grade instrument, which led to comparatively lower performance overall, but still provided sufficient accuracy to monitor fermentation trends. While the ease of use of on-line monitoring systems was favored as compared to at-line systems due to the lack of sampling required and potential for automated process control, we observed some decrease in performance due to the additional complexity of the sample matrix. We have demonstrated that NIRS combined with multivariate analysis can be used for at-line and on-line monitoring of the concentrations of glucose, xylose, 2,3-BDO, acetoin, and glycerol during Z. mobilis fermentations. The decrease in signal-to-noise ratio when using a low-cost spectrometer led to greater prediction error than the laboratory-grade spectrometer for at-line monitoring. The on-line monitoring modality showed great promise for real time process control via NIRS.

09 BIOMASS FUELS↗
DOE OSTI2016

Synthesis, structure, and luminescence property of a series of Ag–Ln coordination polymers with the N-heterocyclic carboxylato ligand

Six Ln–Ag coordination polymers {[LnAg_2(IN)_4(H_2O)_5]·NO_3·2H_2O}{sub n} (Ln=Ho (1) and Tb (2), HIN=isonicotinic acid), {[PrAg_2(IN)_4(H_2O)_2]·NO_3·H_2O}{sub n} (3), [LnAg(pdc){sub 2}]{sub n} (Ln=Eu(4) and Pr (5), H{sub 2}pdc=3,4-pyridine-dicarboxylic acid) and [NdAg(bidc){sub 2}(H{sub 2}O){sub 4}]{sub n} (6) (H{sub 2}bidc=benzimidazole-5,6-dicarboxylic acid) have been hydrothermally synthesized and characterized by single crystal X-ray diffraction, elemental analysis, IR, UV–vis-NIR absorption spectra, fluorescence spectra and thermogravimetric analysis. Structural analyses reveal that the six polymers exhibit 0D (polymer (1)), 1D (polymer (2)), 2D (polymers (3) and (5)) and 3D (polymers (4) and (6)) infinite structures, respectively. Polymers (1)–(6) exhibit the Ln(III) characteristic emission in the near-infrared (NIR) region or in the visible region. Especially, the NIR emission bands of polymers 1, 5 and 6 evidently present shift or splitting due to formation of the Ln–Ag coordination polymers. This can be attributed to the tune of inner levels in Ln–Ag system caused by the interact and influence between the 4d orbital of the Ag(I) ion and the 4f orbital of the Ln(III) ion, which can be confirmed by the UV–vis-NIR absorption spectra of the polymers. In addition, the distortion of coordination geometry as well as difference of the coordination number around the Ag(I) ion affect the structure framework. - Graphical abstract: Six Ag–Ln coordination polymers have been hydrothermally synthesized and characterized. The photoluminescence properties were studied. The distortion of coordination geometry of Ag(I) ion affect structure framework. Introduction of Ag(I) cause wonderful changes to the NIR emission of Ln(III) ions. - Highlights: • Six Ln–Ag polymers have been synthesized and characterized. • The distortion of coordination geometry of Ag(I) ion affect structure framework. • Introduction of Ag(I) cause wonderful changes to the NIR emission of Ln(III) ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Bright, Modular, and Switchable Near-Infrared II Emission from Compact Tetrathiafulvalene-Based Diradicaloid Complexes

Near-infrared (NIR)-emitting molecules are promising candidates for biological sensing and imaging applications; however, many NIR dyes are large conjugated systems which frequently have issues with stability, solubility, and tunability. Here, we report a novel class of compact and tunable fluorescent diradicaloid complexes which are air-, water-, light-, and temperature-stable. These properties arise from a compressed pi manifold which promotes an intense ligand-centered π-π transition in the NIR II (1000-1700 nm) region and which subsequently emits at similar to ~1200 nm. This emission is among the brightest known for monomolecular lumiphores with deep NIR II (>1100 nm) emission, nearly an order of magnitude brighter than the commercially available NIR II dye IR 26. Additionally, this fluorescence is electrochemically sensitive, with efficient switching upon addition of redox agents. The brightness, stability, and modularity of this system distinguish it as a promising candidate for the development of new technologies built around NIR emission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗