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Results for “NIR spectroscopy”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Rapid measurement of soluble xylo-oligomers using near-infrared spectroscopy (NIRS) and multivariate statistics: calibration model development and practical approaches to model optimization

Rapid monitoring of biomass conversion processes using techniques such as near-infrared (NIR) spectroscopy can be substantially quicker and less labor-, resource-, and energy-intensive than conventional measurement techniques such as gas or liquid chromatography (GC or LC) due to the lack of solvents and preparation methods, as well as removing the need to transfer samples to an external lab for analytical evaluation. The purpose of this study was to determine the feasibility of rapid monitoring of a biomass conversion process using NIR spectroscopy combined with multivariate statistical modeling, and to examine the impact of (1) subsetting the samples in the original dataset by process location and (2) reducing the spectral range used in the calibration model on model performance. We develop multivariate calibration models for the concentrations of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids at multiple points in a biomass conversion process which produces and then purifies XOS compounds from sugar cane bagasse. A single model using samples from multiple locations in the process stream showed acceptable performance as measured by standard statistical measures. However, compared to the single model, we show that separate models built by segregating the calibration samples according to process location show improved performance. We also show that combining an understanding of the sample spectra with simple multivariate analysis tools can result in a calibration model with a substantially smaller spectral range that provides essentially equal performance to the full-range model. We demonstrate that real-time monitoring of soluble xylo-oligosaccharides (XOS), monomeric xylose, and total solids concentration at multiple points in a process stream using NIR spectroscopy coupled with multivariate statistics is feasible. Segregation of sample populations by process location improves model performance. Models using a reduced spectral range containing the most relevant spectral signatures show very similar performance to the full-range model, reinforcing the importance of performing robust exploratory data analysis before beginning multivariate modeling.

09 BIOMASS FUELS↗
DOE OSTI2020

Investigating the Curing Process of Epoxy Thermosets by Near-Infrared (nIR) Spectroscopy

Near-Infrared (nIR) Spectroscopy is a type of absorption spectroscopy that may be used to study the curing process of thermosetting epoxy-based resins like Eccostock FFP. This is accomplished by monitoring the absorption bands of the epoxy oxirane ring, which decrease in intensity with increasing degree of cure. Relative to epoxy absorption bands in the mid-IR region, those in the nIR range exhibit less overlap, allowing for a more accurate analysis of cure kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Quantification of Carbon Nanotube Doses in Adherent Cell Culture Assays Using UV-VIS-NIR Spectroscopy

The overt hazard of carbon nanotubes (CNTs) is often assessed using in vitro methods, but determining a dose–response relationship is still a challenge due to the analytical difficulty of quantifying the dose delivered to cells. An approach to accurately quantify CNT doses for submerged in vitro adherent cell culture systems using UV-VIS-near-infrared (NIR) spectroscopy is provided here. Two types of multi-walled CNTs (MWCNTs), Mitsui-7 and Nanocyl, which are dispersed in protein rich cell culture media, are studied as tested materials. Post 48 h of CNT incubation, the cellular fractions are subjected to microwave-assisted acid digestion/oxidation treatment, which eliminates biological matrix interference and improves CNT colloidal stability. The retrieved oxidized CNTs are analyzed and quantified using UV-VIS-NIR spectroscopy. In vitro imaging and quantification data in the presence of human lung epithelial cells (A549) confirm that up to 85% of Mitsui-7 and 48% for Nanocyl sediment interact (either through internalization or adherence) with cells during the 48 h of incubation. This finding is further confirmed using a sedimentation approach to estimate the delivered dose by measuring the depletion profile of the CNTs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Near-Real-Time Material Tracking: Combining Vis–NIR Spectroscopy with Flow Sensing for Accurate Nd(III) Quantification

A fiber-optic visible–near-infrared (vis–NIR) absorption spectroscopy and flow sensor system has been developed for near-real-time tracking of Nd mass in the effluent stream from a column in a fume hood. The approach leverages two unique data streams and a partial least-squares regression (PLSR) model trained on vis–NIR absorption spectra of Nd(III) (0–1.5 M) in 1 M HNO 3 . In-line volumetric flow rate and vis–NIR spectra are measured in sequence after a chromatography column. The time stamps from each data stream are then synchronized, which allows integrated volumes to be combined with Nd(III) molarities predicted by a PLSR model to accurately calculate the Nd mass flowing through the column. This integrated measurement provides instantaneous mass flow and accumulates these data over time to obtain the total mass processed. The methodology developed in this study contributes critical technical infrastructure to improve monitoring capabilities to support chemical separations and the production of strategic materials and isotopes.

Irvine, Sawyer B. [Oak Ridge National Laboratory (↗
DOE OSTI2022

Non-destructive measurement and real-time monitoring of apple hardness during ultrasonic contact drying via portable NIR spectroscopy and machine learning

Portable near-infrared spectrometer in the spectral range of 900–1700 nm was evaluated for the first time to assess and monitor apple hardness in real-time during ultrasonic drying. Calibration models were developed using PLS and ANN, and their performances were evaluated by internal leave-one-out cross-validation and an external dataset. Several pre-treatments including standard normal variate (SNV), multiplicative scatter correction (MSC), Savitzky–Golay first and second derivatives were employed to examine the effects of spectral variations in hardness prediction. Seven important wavelengths were selected using weighted regression coefficients to develop a simple MLR model to facilitate the model interpretation and circumvent noise. The models using PLS, MLR, and ANN with selected wavelengths predicted the apple hardness with R 2 p of 0.91, 0.91, 0.95, and RMSEP of 14.78, 14.85, and 12.46 N, respectively. Finally, the results indicate that portable NIR spectrometers are quite promising for real-time monitoring of apple hardness during ultrasonic drying.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Identifying hydroxylated copper dimers in SSZ-13 via UV-vis-NIR spectroscopy

Cu-Exchanged zeolites are promising materials for the selective conversion of methane to methanol. Their activity is attributed to the presence of small Cu-oxo and Cu-hydroxy clusters, but the nature of active centers in various zeolite structures is still under debate. In this contribution, we combine time dependent density functional theory with spin–orbit coupling to predict the optical spectra of various Cu monomers and dimers in SSZ-13. As a result, we furthermore compare theoretical results to experimental measurements and find that the presence of Cu-hydroxy dimers and Cu monomers could potentially explain the experimentally observed UV-vis-NIR spectra.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1993

Measuring and distinguishing compositional and maturity properties of lunar soils by remote VIS-NIR spectroscopy

Space weathering on the lunar surface affects the spectra/optical character of an exposed lunar soil in three ways: the reflectance is reduced, absorption band depths are reduced, and a red-sloped continuum is created and increased with exposure. As a result, the spectrum of a lunar soil is dependent upon both the degree of exposure at the lunar surface and the original composition. It is critical to the remote analysis of lunar soils to differentiate between the optical effects of maturity and the effects of composition. In the laboratory, it is possible to determine and consequently distinguish the degree of exposure, or soil maturity, as measured by parameters such as I(sub s)/FeO (e.g., 1; mature defined as I(sub s)/FeO greater than or equal to 60), and the composition, as measured by various chemical and petrographical techniques. Lunar soils returned by the Apollo missions provide important ground truth for developing methods for remotely measuring the maturity and the concentration of Fe-bearing minerals in lunar soil. The ground truth spectral data analyzed are from the John Adams lunar soil spectra collection. Soils collected from or near highland terrains are emphasized in the discussion. The mineralogical makeup of mare soils results in behavior somewhat different from highland soils.

Fischer, Erich M.↗
DOE OSTI2026

UV–Vis–NIR Reflectance Spectroscopy and Chemometrics for Monitoring Pu Directly on an Ion Exchange Column

Here, we present a fiber-optic UV–vis–NIR reflectance spectroscopy method for direct, noninvasive monitoring of Pu(IV) in a glass ion exchange column during dynamic loading and elution in a glovebox. A movable probe enables spatially resolved spectral acquisition along the column axis, capturing distinct features associated with Pu(IV) nitrate complexes during loading and free ions during elution. Principal component analysis was applied to extract the dominant spectral variance and resolve relative concentration profiles without requiring precise knowledge of optical penetration depth or species identity. This in situ approach reveals spatial gradients and speciation dynamics in real time, which provides actionable insight into Pu(IV) ion migration, resin saturation, and breakthrough behavior under evolving flow conditions. The method offers a practical, fiber-compatible strategy to monitor glass column–based separations for Pu and other lanthanides or actinides and to characterize metal–resin interactions in flow-through systems.

actinide↗
DOE OSTI2024

Rapid and high-throughput determination of sorghum ( Sorghum bicolor ) biomass composition using near infrared spectroscopy and chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum (Sorghum bicolor) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

09 BIOMASS FUELS↗
DOE OSTI2025

Near-infrared spectroscopy as a green analytical tool for sustainable biomass characterization for biofuels and bioproducts: An overview

Biomass, a widely used renewable energy source, requires characterization to optimize biofuel and bioproduct processes, customize feedstocks, and ensure economic and environmental sustainability. Conventional wet-chemistry methods for biomass analysis are slow, expensive, and require significant reagents and skilled personnel. In contrast, near-infrared (NIR) spectroscopy, a faster, cost-effective, and reagent-free green technology, enables non-destructive biomass analysis with minimal sample preparation. This study provides an overview of the fundamentals of NIR spectroscopy and explores its recent applications for analyzing various biomass properties important to the biofuel and bioproduct industry. The study also critically evaluates the challenges and opportunities of using NIR spectroscopy for biomass analysis. This review aims to guide future research for rapid and high throughput characterization of biomass in the biomass industry, supporting the United Nations’ sustainable development goal (SDG) 7: producing affordable and sustainable energy.

Biofuels↗
DOE OSTI2024

Data for Rapid and High-Throughput Determination of Sorghum ( Sorghum bicolor ) Biomass Composition using Near Infrared Spectroscopy and Chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum ( Sorghum bicolor ) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

Biomass Analytics↗
DOE OSTI2022

Pilot-Scale Pelleting Tests on High-Moisture Pine, Switchgrass, and Their Blends: Impact on Pellet Physical Properties, Chemical Composition, and Heating Values

In this study, we evaluated the pelleting characteristics of southern yellow pine (SYP), switchgrass (SG), and their blends for thermochemical conversion processes, such as pyrolysis and gasification. Using a pilot-scale ring-die pellet mill, we specifically assessed the impact of blend moisture, length-to-diameter (L/D) ratio in the pellet die, and ratio of pine to SG on the physico-chemical properties of the resulting pellets. We found that an increase in pine content by 25–50% marginally affected the bulk density; however, it also led to an increase in calorific value by 7% and a decrease in ash content by 72%. A moisture content of 25% (wet basis) and an L/D ratio of 5 resulted in poor pellet durability at <90% and bulk density values of <500 kg/m 3 , but increasing the L/D ratio to 9 and lowering the moisture content to 20% (w.b.) improved the pellet durability to >90% and the bulk density to >500 kg/m 3 . Blends with ≥50% pine content resulted in lower energy consumption, while a lower L/D ratio resulted in higher pelleting energy. Based on these findings, we successfully demonstrated the high-moisture pelleting of 2.5 ton of pine top residues blended with SG at 60:40 and 50:50 ratios. The quality of the pellets was monitored off-line and at-line by near infrared (NIR) spectroscopy. Multivariate models constructed by combining the NIR data and the pelleting process variables could successfully predict the pine content (R 2 = 0.99), higher heating value (R 2 = 0.98), ash (R 2 = 0.95), durability (R 2 = 0.94), and bulk density (R 2 = 0.86) of the pellets. Thus, we established how blending and densification of SYP and SG biomass could improve feedstock specifications and that NIR spectroscopy can effectively monitor the pellet properties during the high-moisture pelleting process.

09 BIOMASS FUELS↗
NASA NTRS2012

Near-Infrared (NIR) Raman Spectroscopy of Precambrian Carbonate Stromatolites with Post-Depositional Organic Inclusions

Raman spectroscopy has promising potential for future Mars missions as a non-contact detection technique for characterizing organic material and mineralogy. Such a capability will be useful for selecting samples for detailed analysis on a rover and for selecting samples for return to Earth. Stromatolites are important evidence for the earliest life on Earth and are promising targets for Mars investigations. Although constructed by microorganisms, stromatolites are organo-sedimentary structures that can be large enough to be discovered and investigated by a Mars rover. In this paper, we report the Raman spectroscopic investigations of the carbonate mineralogy and organic layering in a Precambrian (;1.5 Gyr old) stromatolite from the Crystal Spring Formation of Southern California. Ultraviolet (UV: 266 nm), visible (514 nm, 633 nm), and near-infrared (NIR: 785 nm, 1064 nm) Raman spectra are presented. We conclude that 1064 nm excitation is the optimal excitation wavelength for avoiding intrinsic fluorescence and detecting organic carbon within the carbonate matrix. Our results confirm that NIR Raman spectroscopy has important applications for future Mars missions.

Tanaka, Zuki↗
NASA NTRS1994

Noninvasive Intracranial Pressure and Tissue Oxygen Measurements for Space and Earth

The paper discusses the following: Increasing intracranial pressure in humans during simulated microgravity. and near-infrared monitoring of model chronic compartment syndrome in exercising skeletal muscle. Compared to upright-seated posture, 0 deg. supine, 6 deg. HDT, and 15 deg. HDT produced TMD changes of 317 +/- 112, 403 +/- 114, and 474 +/- 112 n1 (means +/- S.E.), respectively. Furthermore, postural transitions from 0 deg. supine to 6 deg. HDT and from 6 deg. to 15 deg. HDT generated significant TMD changes (p less than 0.05). There was no hysteresis when postural transitions to HDT were compared to reciprocal transitions toward upright seated posture. Currently, diagnosis of chronic compartment syndrome (CCS) depends on measurement of intramuscular pressure by invasive catheterization. We hypothesized that this syndrome can be detected noninvasively by near-infrared (NIR) spectroscopy, which tracks variations in muscle hemoglobin/myoglobin oxygen saturation. CCS was simulated in the tibialis anterior muscle of 7 male and 3 female subjects by gradual inflation of a cuff placed around the leg to 40 mmHg during 14 minutes of cyclic isokinetic dorsiflexion exercise. On a separate day, subjects underwent the identical exercise protocol with no external compression. In both cases, tissue oxygenation (T(sub O2) was measured in the tibialis anterior by NIR spectroscopy and normalized to a percentage scale between baseline and a T(sub O2) nadir reached during exercise to ischemic exhaustion. Over the course of exercise, T(sub O2) declined at a rate of 1.4 +/- 0.3% per minute with model CCS, yet did not decrease during control exercise. Post-exercise recovery of T(sub O2) was slower with model CCS (2.5 +/- 0.6 min) than in control (1.3 +/- 0.2 min). These results demonstrate that NIR spectroscopy can detect muscle deoxygenation caused by pathologically elevated intramuscular pressure in exercising skeletal muscle. Consequently, this technique shows promise as a noninvasive diagnostic tool for CCS.

Hargens, A. R.↗