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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Wildfire Smoke PM2.5 per Zipcode

This dataset contains daily aggregated measurements of daily PM2.5 from ambient wildfire smoke in the contiguous United States, spanning from 2006 to 2016. The data is sourced from a study by Childs et al. (2022), titled "Daily Local-Level Estimates of Ambient Wildfire Smoke PM2.5 for the Contiguous US" published in Environmental Science & Technology. To compute the standardized weight across different zip codes, we computed the weight calculation on a 10km grids. To compute the weight, we obtain area-weights that add up to 1 in each polygon of zipcodes. This enabled us to calculate the smoke values per zipcode for the aforementioned period. Those interested in replicating our data processing pipeline can access it at https://github.com/NSAPH-Data-Processing/smoke_aggregation.

PM2.5↗
DOE OSTI2023

DEEPEN 3D PFA Weights for Exploration Datasets in Magmatic Environments

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be developed for use in the weighted sum of the different favorability index models produced from geoscientific exploration datasets. This GDR submission includes those weights. The weighting was done using two different approaches: one based on expert opinions, and one based on statistical learning. The weights are intended to describe how useful a particular exploration method is for imaging each component of each play type. They may be adjusted based on the characteristics of the resource under investigation, knowledge of the quality of the dataset, or simply to reduce the impact a single dataset has on the resulting outputs. Within the DEEPEN PFA, separate sets of weights are produced for each component of each play type, since exploration methods hold different levels of importance for detecting each play component, within each play type. The weights for conventional hydrothermal systems were based on the average of the normalized weights used in the DOE-funded PFA projects that were focused on magmatic plays. This decision was made because conventional hydrothermal plays are already well-studied and understood, and therefore it is logical to use existing weights where possible. In contrast, a true PFA has never been applied to superhot EGS or supercritical plays, meaning that exploration methods have never been weighted in terms of their utility in imaging the components of these plays. To produce weights for superhot EGS and supercritical plays, two different approaches were used: one based on expert opinion and the analytical hierarchy process (AHP), and another using a statistical approach based on principal component analysis (PCA). The weights are intended to provide standardized sets of weights for each play type in all magmatic geothermal systems. Two different approaches were used to investigate whether a more data-centric approach might allow new insights into the datasets, and also to analyze how different weighting approaches impact the outcomes. The expert/AHP approach involved using an online tool (https://bpmsg.com/ahp/) with built-in forms to make pairwise comparisons which are used to rank exploration methods against one-another. The inputs are then combined in a quantitative way, ultimately producing a set of consensus-based weights. To minimize the burden on each individual participant, the forms were completed in group discussions. While the group setting means that there is potential for some opinions to outweigh others, it also provides a venue for conversation to take place, in theory leading the group to a more robust consensus then what can be achieved on an individual basis. This exercise was done with two separate groups: one consisting of U.S.-based experts, and one consisting of Iceland-based experts in magmatic geothermal systems. The two sets of weights were then averaged to produce what we will from here on refer to as the "expert opinion-based weights," or "expert weights" for short. While expert opinions allow us to include more nuanced information in the weights, expert opinions are subject to human bias. Data-centric or statistical approaches help to overcome these potential human biases by focusing on and drawing conclusions from the data alone. More information on this approach along with the dataset used to produce the statistical weights may be found in the linked dataset below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

A New Modeling Approach for a Priori Uncertainties of Laser Tracker Angle Measurements

Methods for modeling the uncertainty in laser tracker angle measurements vary within the metrology industry, leading to confusion and questionable stochastic modeling for survey network adjustments and error propagation analysis. Interpreting the published laser tracker manufacturer performance specifications to determine an a priori sigma value for weighting azimuth and zenith angle measurements can be confusing and has led to differing implementations. Furthermore, this paper proposes a unique way to model survey network a priori laser tracker angular uncertainties based on laser tracker manufacturers’ published maximum permissible error (MPE) values referenced to current standards for weighting survey network measurements. This paper’s proposed model takes into account the disparate effects that pointing errors, target centering errors, and leveling errors have on azimuth and zenith angular uncertainties for measurements with steep sightings and at near ranges.

42 ENGINEERING↗
DOE OSTI2024

Sequential Kalman tuning of the t -preconditioned Crank-Nicolson algorithm: efficient, adaptive and gradient-free inference for Bayesian inverse problems

Ensemble Kalman Inversion (EKI) has been proposed as an efficient method for the approximate solution of Bayesian inverse problems with expensive forward models. However, when applied to the Bayesian inverse problem EKI is only exact in the regime of Gaussian target measures and linear forward models. Here, in this work we propose embedding EKI and Flow Annealed Kalman Inversion, its normalizing flow (NF) preconditioned variant, within a Bayesian annealing scheme as part of an adaptive implementation of the t-preconditioned Crank-Nicolson (tpCN) sampler. The tpCN sampler differs from standard pCN in that its proposal is reversible with respect to the multivariate t-distribution. The more flexible tail behaviour allows for better adaptation to sampling from non-Gaussian targets. Within our Sequential Kalman Tuning (SKT) adaptation scheme, EKI is used to initialize and precondition the tpCN sampler for each annealed target. The subsequent tpCN iterations ensure particles are correctly distributed according to each annealed target, avoiding the accumulation of errors that would otherwise impact EKI. We demonstrate the performance of SKT for tpCN on three challenging numerical benchmarks, showing significant improvements in the rate of convergence compared to adaptation within standard SMC with importance weighted resampling at each temperature level, and compared to similar adaptive implementations of standard pCN. The SKT scheme applied to tpCN offers an efficient, practical solution for solving the Bayesian inverse problem when gradients of the forward model are not available. Code implementing the SKT schemes for tpCN is available at https://github.com/RichardGrumitt/KalmanMC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A standard convention for particle-level Monte Carlo event-variation weights

Streams of event weights in particle-level Monte Carlo event generators are a convenient and immensely CPU-efficient approach to express systematic uncertainties in phenomenology calculations, providing systematic variations on the nominal prediction within a single event sample. But the lack of a common standard for labelling these variation streams across different tools has proven to be a major limitation for event-processing tools and analysers alike. Here we propose a well-defined, extensible community standard for the naming, ordering, and interpretation of weight streams that will serve as the basis for semantically correct parsing and combination of such variations in both theoretical and experimental studies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Quantum-inspired weight-constrained neural network: Reducing variable numbers by 100× compared to standard neural networks

Although quantum machine learning has shown great promise, the practical application of quantum computers remains constrained in the noisy intermediate-scale quantum era. To take advantage of quantum machine learning, we investigate the underlying mathematical principles of these quantum models and find that the quantum neural network with amplitude encoding is equivalent to a weight-constrained neural network. Motivated by this discovery, we develop a classical weight-constrained neural network. We find that this approach can reduce the number of variables in a classical neural network by a factor of 135 while preserving its accuracy. In addition, we develop a dropout method to enhance the robustness of quantum machine learning models, which are highly susceptible to adversarial attacks. This technique can also be applied to improve the adversarial robustness of the classical weight-constrained neural network, which is essential for industry applications, such as self-driving vehicles. Our work offers an approach to reduce the complexity of large classical neural networks, addressing a critical challenge in machine learning.

quantum algorithms & computation↗
DOE OSTI2023

Legacy Analysis of Dark Matter Annihilation from the Milky Way Dwarf Spheroidal Galaxies with 14 Years of Fermi-LAT Data: Data Products

https://arxiv.org/abs/2311.04982This repository contains data products from the 14 year Fermi-LAT analysis of the Milky Way dSphs as described in McDaniel et al (2023) https://arxiv.org/abs/2311.04982. The included data products are the SED fits files and 2D TS profiles in the WIMP mass and cross section space. These are available for dSphs as well as the blank-field analysis, using both the standard likelihood and the weighted likelihood approach (see Appendix A). CSV data files are included containing relevant information about the dSphs (see table 1 of McDaniel+2024) and blank fields (RA & Dec). Also included is a python Jupyter Notebook to show basic usage of the data products. For Example, plotting the SED likelihoods, converting the SED likelihood to DM space, creating a combined TS profile, obtaining upper limits, etc. This is also stored as a static html file for easier viewing. SEDs are stored as fits files in the output format of fermipy (see https://fermipy.readthedocs.io/en/latest/advanced/sed.html) TS profiles are stored as numpy arrays covering 40 logarithmically spaced mass values over the 1 GeV - 1 TeV mass range and 60 logarithmically spaced cross-section values covering the $10^{-28}$ to $10^{-22}$ cm$^3$/s cross section range. TS profiles including the J-factor prior and without are available, and are labeled with "Jprior" or "noprior" respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Large-Volume Injection and Assessment of Reference Standards for n -Alkane δD and δ 13 C Analysis via Gas Chromatography Isotope Ratio Mass Spectrometry

Compound-specific stable isotope analysis of hydrogen (δD) and carbon (δ 13 C) in organic compounds is a valuable tool in biogeochemical research. A key limitation of this method is the relatively large amount of sample required to achieve desirable precision. We developed a large-volume (20 μL) injection method that allows for high throughput analysis of less concentrated samples and tested it for δ 13 C and δD measurements of n-alkanes. We also conducted a comparison of reference standards and assessed several methods to normalize and correct n-alkane δD and δ13C measurements. The mean precision of the δD method based on 233 environmental n-alkane samples (two to three replications per sample) is 4.0‰ (1σ, estimated from the weighted mean of the pooled unbiased standard deviations) and 0.46‰ (1σ) for δ 13 C from 37 environmental samples (two to three replications per sample). The evaluation of reference standards shows that the use of n-alkane standards with large offsets in δD values in adjacent n-alkane chains can lead to biases in measurement correction. The large-volume injection method shows good reproducibility of δ 13 C and δD measurements of n-alkanes and reduces the required sample concentration by about 80%. We propose that for δD measurements, a reference standard set should be used in which each reference standard has a limited range of δD values and no adjacent n-alkane chains, to minimize memory effects.

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

Determination of Constraint-Independent Crack Tip Opening Angle for Stable Crack Growth in High-Strength Ductile Steels

The crack tip opening angle (CTOA) is one of fracture toughness parameters that has been used for decades in describing large stable crack growth in thin-walled aerospace structures under the low-constraint conditions. Recently, the pipeline industry has developed a growing interest in using the CTOA parameter to serve as the minimum required fracture toughness to arrest dynamic crack propagation in modern gas transmission pipelines made of high-strength ductile steel. To meet this industrial need, the CTOA test standard ASTM E3039 was therefore developed for measuring the constant critical CTOA. ASTM E3039 recommends a drop weight tearing test (DWTT) specimen with a shallow crack for standard CTOA testing, but its CTOA may depend on the low constraint condition of the DWTT specimen at the crack tip. Verifying the constraint independence of the DWTT-measured CTOA thus becomes indispensable for applying CTOA toughness to the running fracture control in the pipeline design. For this purpose, the present paper evaluates critical CTOA values in a set of fracture toughness tests on single-edge notched bend (SENB) specimens with shallow and deep cracks, based on four CTOA estimation models. Among these, the Ln(P)-LLD linear fit model is similar to that recommended by ASTM E3039 for CTOA calculation. Fracture test data for X80 pipeline steel and HY80 structural steel were considered in the CTOA evaluation. The results showed that the four CTOA models were able to determine a constraint independent CTOA value for stable crack growth in the SENB specimens. As a result, a single, reliable, constant CTOA value could be determined regardless of the specimen geometry or the crack-tip constraint conditions. Therefore, the CTOA measured using ASTM E3039 is constraint-independent and transferable to use in cases of actual cracks propagating in gas transmission pipelines.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Data driven investigation to understand the influence of total solids on biological biogas upgrading

In situ biogas upgrading achieves CO 2 conversion to CH 4 via hydrogenotrophic methanogenesis; however, gas-liquid mass transfer constraints limit the upgrading performance. Recognizing that optimization studies often underrepresent the effects of total solids (TS) and organic loading rate (OLR), this study undertook a holistic, statistics driven assessment of operating conditions for in situ H 2 assisted biogas upgrading, centering the analysis on TS and OLR. A dataset of 31 studies was compiled and comprised 99 observations. A rigorous analytical framework was employed, combining data standardization, fixed- and random-effects (REML) weighted regressions with cluster-robust errors, stratified analyses, and machine learning. Mixed-effects meta regression indicated that TS was the main factor explaining differences of methane fraction (CH 4 %) when considering the between studies heterogeneity. Focusing on a near-stoichiometric subset (H 2 /CO 2 ≈ 4:1), TS remained significant. Stratified results showed a stronger negative relationship between TS and CH 4 % in UASB reactors than in CSTRs, with a negative effect under mesophilic conditions and no significant effect under thermophilic conditions. A Random Forest model corroborated the statistical findings, consistently ranking H 2 /CO 2 ratio, OLR, TS, and hydrogen injection rate (HIR) as the most influential predictors. These findings delineate trends across increasing TS levels, particularly between 1% and 10%, and provide preliminary insights for TS above 15% in in situ biogas upgrading. They further provide insights for the influence of TS by reactor type and temperature, thereby advancing the evidence base for implementing biological CO 2 conversion to CH 4 in practice.

In situ biogas upgrading↗
DOE OSTI2024

Cellulose molecular weight of corn stover with cotreatment

Here we present a dataset of cellulose molecular weights from corn stover after a cotreatment process. The corn stover sample was subjected to a combination of mechanical disruption (ball milling) and consolidated bioprocessing (CBP) process using the bacterium C. thermocellum at 60 grams/L solids loadings. Cellulose was isolated from control, no cotreatment control, and cotreatment corn stover. Cellulose was then derivatized using anhydrous pyridine and phenyl isocyanate over 48 h at 70 ºC. The reaction was quenched by anhydrous methanol. Methanol and water mixture (7:3, v/v) was added dropwise to promote precipitation of the cellulose derivative. The solids were collected by filtration and thoroughly washed with the methanol and water mixture followed by water. The cellulose derivative was dried overnight under vacuum at 40°C. The obtained cellulose tricarbanilates was then dissolved in tetrahydrofuran (THF) at 1.0 mg/mL and the solution was filtered through a 0.45 µm PTFE filter and placed in an auto-sampler vial. The molecular weight of cellulose was measured by Agilent GPC SECurity 1200 system equipped with four Waters Styragel columns (i.e., HR0.5, HR2, HR4, and HR6) and a UV detector (270 nm). THF was used as the mobile phase. Data collection and processing was performed by Polymer Standards Service WinGPC Unity software (Build 6807). The molecular weight was calculated relative to the polystyrene calibration curve. The data on molecular weights provided information about the effects of cotreatment on corn stover cellulose molecular changes.

Cellulose, molecular weights, corn stover, cotreat↗
DOE OSTI2023

Poly(oxymethylene) Ethers as a High Cetane, Low Sooting Biofuel Blendstock for Use in Medium to Heavy Duty Mixing Controlled Compression Ignition Engines

Compression ignition (CI) engines are currently the most common prime mover for medium and heavy duty vehicles; these engines contribute roughly a quarter of US greenhouse gas emissions from transportation, and even higher percentages of particulate and nitrogen oxide emissions. As a result, there have been significant efforts made to reduce these emissions, particularly through selection of low-emissions alternative fuels. Oxymethylene ethers (OMEs) are a class of molecule, typically structured R-O-(CH2O)n-R', which have been considered as a possible blendstock in CI fuels for the goal of soot reduction. Generally, past work has focused on methyl-terminated OMEs, CH3-O-(CH2O)n-CH3, which by virtue of containing no C--C bonds, produce negligible soot. These molecules show significant reductions in soot emission from engines when blended in moderate to high ratios with traditional diesels, however, they have been shown to have inferior physical properties and poor compatibility with some legacy systems. Recent theoretical work has shown that OMEs with non-methyl alkyl groups may have superior performance, albeit at the cost of increased soot formation. In this work, a variety of OMEs with terminating alkyl groups from methyl to butyl are considered for their suitability as CI fuels. The synthesis of these extended OMEs is studied, including formation of n=1 OMEs from common chemical sources, and extension of the chain length to heavier molecules, via reactions over acidic ion exchange resins. Following the synthesis, the properties of these OMEs are studied with respect to their engine applicability. It is found that heavier (propyl- and butyl-terminated) OMEs have superior properties for diesel compatibility, particularly in reactivity, volatility, and water solubility. Extended-alkyl OMEs are found to have higher soot production than methyl-terminated OMEs, but remain superior to diesel soot production on a per-unit-energy basis. A sample of a butyl-terminated OME mixture, n=2-4, is selected as the ideal OME blend for close compatibility with legacy diesel systems. This mixture is blended with certified diesel and tested for ASTM D975 compatibility, passing all required tests but lubricity; decreased heat of combustion is observed but not governed by the diesel standard. Fundamental combustion tests of various mid-weight OMEs are performed in a rapid compression machine, where it is shown that low-temperature chemistry causes a region of decreased dependence of ignition delay on temperature, consistent with methyl-terminated OME behavior. An isopropyl-terminated OME is observed to have low reactivity compared to other OMEs; this fuel is investigated via further rapid compression machine testing and CFR engine testing. It is found that this OME has strong negative-temperature-coefficient ignition behavior - a first for OMEs - and has reactivity lower than other OMEs, but insufficient for direct spark ignition engine testing.

09 BIOMASS FUELS↗
DOE OSTI2023

Fractionated and purified hybrid poplar lignins as a polyol replacement in rigid polyurethane/polyisocyanurate foams

This study introduces fractionated lignin as an innovative component in the formulation of rigid polyurethane/polyisocyanurate (PUR/PIR) foams. Low-density PUR/PIR rigid foams were prepared by replacing 80% of the petrochemical-based polyol with a hybrid poplar (HP) lignin, recovered via alkaline pretreatment, and also with a fraction of this lignin, isolated via the Aqueous Lignin Purification with Hot Agents (ALPHA) process. The as-recovered HP and ALPHA-fractionated HP lignins were characterized to determine hydroxyl content, molecular weight (Mw) distribution, and pH. Both lignin-based foams met minimum standard requirements in terms of closed cell content, compression strength, and thermal conductivity. Notably, the foams made with ALPHA-based lignin outperformed the as-recovered lignin-based foams in all measured foam properties. Moreover, the ALPHA-based foam had comparable performance to the control foam (without lignin) except for density and even surpassed the control foam in closed cell content and compressive strength. This investigation of the molecular properties of lignin suggests that significant reductions in lignin average molecular weight and polydispersity (PDI) can positively impact the properties of lignin-based rigid foams.

09 BIOMASS FUELS↗
DOE OSTI2025

Accurate Dehydrogenation Enthalpies Dataset for Liquid Organic Hydrogen Carriers

This contribution presents a comprehensive extension of the QM9 dataset (originally at 133 K molecules) with the calculation of G4MP2 enthalpies for 9,841 molecules, featuring up to nine heavy atoms. We present QM9-LOHC, a (de)hydrogenation dataset of 10,373 reactions, including a minimum of 5.5% weight hydrogen storage capacity in line with the Department of Energy standards for Liquid Organic Hydrogen Carriers (LOHC). By utilizing the accurate quantum chemical method G4MP2 we expand the QM9 database and explore new avenues for the exploration of hydrogen storage technologies (electrochemical LOHCs, alkali metal-LOHCs, and mixtures of LOHCs). The QM9-LOHC dataset, with its focus on reactions that vary only by hydrogen saturation levels, provides a needed data resource for advancing the design and optimization of both conventional and innovative LOHC systems, and high-fidelity data for molecular discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Godiva IV Simulated Radiation Field Characterization and Variance Reduction

Godiva IV is a system comprised of highly enriched uranium alloyed with molybdenum in the form of fuel plate rings. The reactor, along with its predecessors, was designed with the unique ability to satisfy interests in the super-prompt-critical reactor operation space. Originally, the reactor was part of the Los Alamos Critical Experiments Facility (LACEF) at Technical Area-18 (TA-18). The radiation field around Godiva at this facility was well characterized and understood. As a fast neutron system, the neutron spectrum in and around Godiva was close to a Watt Fission spectrum. The Kiva where Godiva IV was located at LACEF was made of thin, sheet metal walls which did not contribute significantly to the neutron spectrum. Following the transition of LACEF to the National Critical Experiments and Research Center (NCERC) in Nevada, Godiva-IV was moved from TA-18 to the Device Assembly Facility (DAF) at the Nevada National Security Site (NNSS). Part of this move brought renewed interest in radiation field characterization. The new facility introduced significant changes to the environment surrounding Godiva, and preliminary foil irradiation results suggested that the room contribution to the neutron spectrum was significant. Unlike at TA-18, a large thermal neutron signature was added to the fast spectrum from Godiva due to significant room return. A primary goal due to the additional complexity that the room return adds to the Godiva IV radiation emission spectrum was the development of an efficient Monte Carlo N-Particle (MCNP) calculation capable of characterizing the neutron spectrum anywhere in the room around Godiva. A campaign of activation foil irradiations and analysis were completed to support the validation of the MCNP model. The modeling of these foils in MCNP can be easily done with a standard volumetric neutron flux tally. However, given the multitude of locations and reaction rates to be modeled, further steps must be taken to increase the efficiency of these calculations in MCNP. During this study, a benchmark model currently under development for Godiva IV was used. A qualitative assessment of the thermal neutron contributors was performed using spatial neutron distribution plots. Additional detail was added to the model based on the qualitative results showing the thermal spectrum’s large sensitivity to hydrogenous material. Neutron energy spectra was evaluated at discrete locations in the room around Godiva to quantify the relative contribution of various components. It was discovered that the concrete walls are the largest contributor to the thermal signature, with minor contributions from plastic components surrounding Godiva. Following these results, two different variance reduction techniques were implemented to improve the problem efficiency in these calculations. In the first approach, an F5 point detector tally was implemented in the standard Godiva IV criticality problem. The second approach involved a weight-window generator implementation with an F5 point detector tally in a fixed source problem. The weight window implementation reduced the runtime from 42739.55 minutes to 1803.34 minutes (computer time), compared to the F5 KCODE implementation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Novel 3D Force Sensors for a Cost-Effective 3D Force Plate for Biomechanical Analysis

Three-dimensional force plates are important tools for biomechanics discovery and sports performance practice. However, currently, available 3D force plates lack portability and are often cost-prohibitive. To address this, a recently discovered 3D force sensor technology was used in the fabrication of a prototype force plate. Thirteen participants performed bodyweight and weighted lunges and squats on the prototype force plate and a standard 3D force plate positioned in series to compare forces measured by both force plates and validate the technology. For the lunges, there was excellent agreement between the experimental force plate and the standard force plate in the X-, Y-, and Z-axes (r = 0.950–0.999, p < 0.001). For the squats, there was excellent agreement between the force plates in the Z-axis (r = 0.996, p < 0.001). Across axes and movements, root mean square error (RMSE) ranged from 1.17% to 5.36% between force plates. Although the current prototype force plate is limited in sampling rate, the low RMSEs and extremely high agreement in peak forces provide confidence the novel force sensors have utility in constructing cost-effective and versatile use-case 3D force plates.

42 ENGINEERING↗
DOE OSTI2024

Lignin molecular weights of Populus trichocarpa residues after CELF pretreatment

Here we present a dataset of molecular weights of lignin from a woody energy crop (Populus trichocarpa) residues after a series of co-solvent enhanced lignocellulosic fractionation (CELF) pretreatment. The natural poplar variant GW-9947 from the Center for Bioenergy Innovation (CBI) was used. The poplar was knife milled and passed through a 1 mm sieve and CELF pretreatment was performed in a Parr autoclave reactor with 7.5 wt % solids loading, 0.5 wt% H2SO4 as catalyst at 150°C with various time. Tetrahydrofuran was added in a 1:1 mass ratio with water as the pretreatment solvent. Lignin was isolated from the pretreated samples after ball-milling in a porcelain jar with ceramic balls via Retsch PM 200 at 580 rpm for 2.5 h followed by enzymatic hydrolysis in acetate buffer (pH 4.8, 50 °C) for 48 h. The solid residue was isolated by centrifugation and hydrolyzed again with freshly added buffer and enzymes for another 48 h. After filtration, the solid residue was extracted twice with 96% (v/v) 1,4-dioxane/water mixture at room temperature overnight. The extracts were combined, rotary evaporated, and freeze-dried to recover lignin. The lignin samples were then derivatized in an acetic anhydride/pyridine (1:1, v/v) mixture and stirred at room temperature for 24 h. Ethanol was added to the reaction mixture, left for 30 min and then removed with a rotary evaporator. The addition and removal of ethanol was repeated at least 3 times until all traces of acetic acid were removed. Acetylated lignin samples were then dissolved in tetrahydrofuran (THF) at a concentration of 1.0 mg/mL. The molecular weight of acetylated lignin was measured by a gel permeation chromatography (GPC) on a PSS-Polymer Standards Service (Warwick, RI, USA) GPC SECurity 1200 system featuring Agilent HPLC 1200 components equipped with four Waters Styragel columns (HR1, HR2, HR4 and HR6) and an UV detector (270 nm). Tetrahydrofuran was used as the mobile phase and flow rate was 0.3 mL/min. The Polymer Standards Service WinGPC Unity software (Build 6807) was used for data processing for all the samples. The data provides information about the effects of CELF pretreatment time at 150 ºC on lignin molecular weights.

09 BIOMASS FUELS↗
DOE OSTI2024

Early Diagnosis of Fibromyalgia Using Surface-Enhanced Raman Spectroscopy Combined with Chemometrics

Fibromyalgia (FM) is a chronic muscle pain disorder that shares several clinical features with other related rheumatologic disorders. This study investigates the feasibility of using surface-enhanced Raman spectroscopy (SERS) with gold nanoparticles (AuNPs) as a fingerprinting approach to diagnose FM and other rheumatic diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), osteoarthritis (OA), and chronic low back pain (CLBP). Blood samples were obtained on protein saver cards from FM (n = 83), non-FM (n = 54), and healthy (NC, n = 9) subjects. A semi-permeable membrane filtration method was used to obtain low-molecular-weight fraction (LMF) serum of the blood samples. SERS measurement conditions were standardized to enhance the LMF signal. An OPLS-DA algorithm created using the spectral region 750 to 1720 cm -1 enabled the classification of the spectra into their corresponding FM and non-FM classes (Rcv > 0.99) with 100% accuracy, sensitivity, and specificity. The OPLS-DA regression plot indicated that spectral regions associated with amino acids were responsible for discrimination patterns and can be potentially used as spectral biomarkers to differentiate FM and other rheumatic diseases. This exploratory work suggests that the AuNP SERS method in combination with OPLS-DA analysis has great potential for the label-free diagnosis of FM.

60 APPLIED LIFE SCIENCES↗