Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “FRACTIONATION”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Sensitivity of Cloud-Radiative Effects to Cloud Fraction Parametrizations in Tropical, Mid-Latitude and Arctic Kilometre-Scale Simulations

The Regional Atmosphere (RA) configuration of the Met Office Unified Model currently requires different cloud fraction parametrizations (CFP) for tropical and midlatitude simulations. To explore the scope for unification of these two RA configurations, this paper presents a detailed evaluation of simulations over tropical, midlatitude and arctic domains, with two different diagnostic CFPs, a prognostic CFP, and no CFP at all. Furthermore, a novel, hybrid approach was used that treats liquid cloud diagnostically and ice cloud prognostically. Using observations from three U.S. Department of Energy Atmospheric Radiation Measurement supersites, it is shown that none of these CFPs stands out as superior over all domains. Over the frequently overcast Arctic, the all-or-nothing approach best captures the cloud radiative properties. Conversely, CFPs are of benefit in regions with frequent partial cloudiness, such as the midlatitudes and the tropics. However, their improved cloud radiative properties often hide an error compensation. All models underestimate overcast, low-base cloud with small water paths in convective environments. In addition, mid-latitude overcast, low-base, optically thick clouds in the morning, possibly associated with overnight convection, are frequently too broken. Diagnostic schemes compensate for these errors by producing spurious, scattered afternoon cloud, which could be due to a correct cloud response to too eager convective initiation. Winter clouds over the midlatitudes are improved when liquid cloud is represented diagnostically with a bimodal saturation-departure PDF, without error compensation. While it is difficult to unify the RA across the globe around a single CFP scheme, the newly proposed Hybrid scheme performs reasonably well for cloud cover across all regions. It also exhibits SW biases that are smaller than most other configurations and is less affected by excessive liquid water paths and compensating errors than fully diagnostic schemes. Surface precipitation is fairly insensitive to the CFP in the simulations shown here.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Measurement of CP asymmetries and branching fraction ratios of B – decays to two charm mesons

The CP asymmetries of seven B – decays to two charm mesons are measured using data corresponding to an integrated luminosity of 9 fb –1 of proton-proton collisions collected by the LHCb experiment. Decays involving a D *0 or ${D}_s^{\ast -}$ meson are analysed by reconstructing only the D 0 or ${D}_s^{-}$ decay products. This paper presents the first measurement of $\mathcal{A}$ CP (B – → ${D}_s^{\ast -}$ D 0 ) and $\mathcal{A}$ CP (B – → ${D}_s^{-}$D $\ast$0 ), and the most precise measurement of the other five CP asymmetries. There is no evidence of CP violation in any of the analysed decays. Additionally, two ratios between branching fractions of selected decays are measured.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

An efficient second-order adaptive procedure for inserting CAD geometries into hexahedral meshes using volume fractions

Here, this paper is concerned with inserting three-dimensional computer-aided design (CAD) geometries into meshes composed of hexahedral elements using a volume fraction representation. An adaptive procedure for doing so is presented. The procedure consists of two steps. The first step performs spatial acceleration using a k-d tree. The second step involves subdividing individual hexahedra in an adaptive mesh refinement (AMR)-like fashion and approximating the CAD geometry linearly (as a plane) at the finest subdivision. The procedure requires only two geometric queries from a CAD kernel: determining whether or not a queried spatial coordinate is inside or outside the CAD geometry and determining the closest point on the CAD geometry’s surface from a given spatial coordinate. We prove that the procedure is second-order accurate for sufficiently smooth geometries and sufficiently refined background meshes. We demonstrate the expected order of accuracy is achieved with several verification tests and illustrate the procedure’s effectiveness for several exemplar CAD geometries.

Adaptive↗
DOE OSTI2024

Reductive catalytic fractionation of cotton stalks: catalytic strategy for tuning the selectivity of phenolic monomers

Pretreatment of lignocellulosic biomass is a primary step to delink lignin from the lignin-carbohydrate complex for bioethanol production and other value-added products. Presently, these processes yield lignin (technical) with significant structural changes compared to native lignin and make it difficult to valorize. Reductive catalytic fractionation (RCF) is an advanced pretreatment process to valorize native lignin to selective phenolic monomers before capitalizing on carbohydrates. Herein, cotton stalks (CS) were pretreated with ethanol: water mixture catalyzed by bimetallic, Ru-Ni/HY (RNY) and Ru-Fe/HY (RFY), and trimetallic, Ru-Fe-Ni/HY (RFNY), catalysts using the endogenously produced H 2 . The favorable catalytic properties of the RFNY catalyst, including high reducibility, acidity, metal dispersion, the synergistic effect of all the metals, and appropriate pore and particle size resulted in the highest catalytic activity. Maximum 92% delignification efficiency was achieved with 91% holocellulose retention. The extracted lignin after depolymerization in the same step produced a 19 wt.% yield of phenolic monomers. Increasing the duration of the reaction from 2 to 6 h increased the selectivity to saturated alkyl chain phenolics (1 to 16 wt.%) at the expense of hemicellulose (50 to 9%). The fate of carbohydrates left behind after the RCF (CS-RCF) process was analyzed through enzymatic saccharification and compared with raw CS and acid-pretreated CS. In conclusion, CS-RCF yielded maximum glucose yield (45 g/L) within an incubation period of 72 h.

09 BIOMASS FUELS↗
DOE OSTI2023

Control of Fractional Diffusion Problems via Dynamic Programming Equations

In this study, we explore the approximation of feedback control of integro-differential equations containing a fractional Laplacian term. To obtain feedback control for the state variable of this nonlocal equation, we use the Hamilton–Jacobi–Bellman equation. It is well known that this approach suffers from the curse of dimensionality, and to mitigate this problem we couple semi-Lagrangian schemes for the discretization of the dynamic programming principle with the use of Shepard approximation. This coupling enables approximation of high-dimensional problems. Numerical convergence toward the solution of the continuous problem is provided together with linear and nonlinear examples. The robustness of the method with respect to disturbances of the system is illustrated by comparisons with an open-loop control approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Harnessing dimethyl ether with ultra-low-grade heat for scaling-resistant brine concentration and fractional crystallization

Solvent-driven separations may enable scalable concentration of hypersaline brines, supporting a circular resource economy from the extraction of lithium and rare earth elements from spent battery and magnet leachates. This work analyses a novel solvent-driven water extraction (SDWE) system employing dimethyl ether (DME) and ultra-low-grade heat for brine concentration and fractional crystallization. SDWE exploits DME’s unique properties: (1) a low dielectric constant that promotes water solubility over charged solutes by a factor of 10 3 , and (2) a high volatility that facilitate efficient DME reconcentration with ultra-low-grade heat. The techno-economic viability of SDWE is assessed with a computational framework that encompasses a liquid–liquid separator and a solvent concentrator. We integrate the extended universal quasichemical model with the virial equation of state to predict the compositions of the complex three-phase DME-water mixture at vapor–liquid and liquid–liquid equilibrium. Subsequently, we optimize the thermodynamic and economic performance of SDWE, by controlling the interstage flash pressure, heat source temperature, and the number of concentrating stages. DME-based SDWE concentrates an input saline feed to 5.5 M and regenerates over 99 % of the DME using ultra-low-grade heat below 50 °C, with a DME/water selectivity ratio of 125. Here our calculations reveal that optimal performance is achieved at interstage flash pressures of 0.4 – 0.5 bar for heat source temperatures between 323–373 K, with improved exergetic efficiencies at lower temperatures. At a heat source temperature of 323 K and an interstage pressure of 0.489 bar, DME-driven SDWE achieves an optimal thermodynamic efficiency of 20.5 % and a projected specific cost of US$ 1.93 m -3 . These specific costs suggest that SDWE is competitive with commercialized thermal distillation technologies, while mitigating the traditional risks associated with scaling in heat and mass exchangers with hypersaline brines.

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

An empirical calibration of the serpentine-water oxygen isotope fractionation at T = 25–100°C

The ability to precisely constrain the physical–chemical conditions of serpentinization, such as temperature and fluid source, is limited by the accuracy of calibrations for oxygen isotope fractionation between serpentine and water – i.e., 1000 lnα( serpentine-water ) – which disagree by up to 20‰ when extrapolated to T<200°C. In this study, we present a new empirical calibration of 1000 lnα( serpentine-water ) aiming to improve applications of oxygen isotope geochemistry to very low-T serpentinization (T<100°C). We used the high-spatial resolution capabilities of Secondary Ion Mass Spectrometry (SIMS) to analyze oxygen isotope ratios in mineral pairs of calcite + serpentine, quartz + serpentine and talc + serpentine co-crystallized at scales≤50μm in six serpentinite samples from the Samail ophiolite (Oman). SIMS analysis shows that the mineral pairs are relatively homogenous in oxygen isotope ratios with variability in δ 18 O values ≤2‰ (2s). Clumped isotope thermometry and petrological constraints indicate crystallization temperatures from 25 to 100°C for the investigated samples. These independent constraints on temperature allowed us to derive 1000 lnα( serpentine-water ) by combining Δ 18 O( quartz-serpentine ), Δ 18 O( talc-serpentine ) and Δ 18 O( calcite-serpentine ) measured by SIMS in the investigated samples with Δ 18 O( quartz-water ), Δ 18 O( talc-water ) and Δ 18 O( calcite-water ) calibrations available in the literature. Our empirical calibration of 1000 lnα( serpentine-water ) = 1.04±0.20 (2SE) × 10 6 /T 2 (T in K), from T = 25 to 100°C, is within uncertainty of former high-temperature empirical calibrations extrapolated to T<100°C and matches experimental calibrations when extrapolated to T=250°C. In conclusion, the new serpentine-water calibration enables more accurate reconstructions of fluid-rock interactions occurring during low-temperature serpentinization processes in various tectonic settings.

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

Mapping wall-to-wall fractional cover of Arctic tundra plant functional types in Alaska using 20-m spatial resolution satellite imagery and harmonized plot observations

Estimates of fractional cover (fCover) across given land surfaces are used to assess, and often model, vegetation composition and diversity, which are crucial for understanding the health and functioning of terrestrial ecosystems. Remote sensing provides a useful means for scaling local, plot-measured fCover estimates to regional scales. Leveraging a recently synthesized and harmonized plot database, this study generated wall-to-wall maps of fCover for six Alaskan-Arctic plant functional types (PFT), including non-vascular plants, forbs, graminoids, and deciduous and evergreen shrubs, using 20-m satellite data (Sentinel-1, Sentinel-2, ArcticDEM) using a machine learning regression approach, specifically the random forest (RF) algorithm, which is well-suited for handling nonlinear relationships and high-dimensional satellite datasets. This study additionally addressed the spatio-temporal inconsistencies e.g., sampling scale, plot size, and collection year in plot measured fCover by adopting a multivariate outlier detection approach—Cook’s distance—to identify high-quality plots for model training and validation. Our approach achieves high accuracy (R 2 = 0.59–0.93, root mean squared errors = 0.02–0.10 for all PFTs) between plot-observed and satellite-derived fCover when using high-quality plot samples. The mapped fCover characterizes the spatial patterns of different PFTs across the tundra biome at a 20-m resolution, providing key information needed for improved representation of Arctic tundra vegetation in terrestrial biosphere models to better understand climate-vegetation feedback across the Arctic tundra.

Arctic tundra↗
DOE OSTI2024

Effects of processing temperature, pressure, and fiber volume fraction on mechanical and morphological behaviors of fully-recyclable uni-directional thermoplastic polymer-fiber-reinforced polymers

This work explores a type of composite called thermoplastic polymer-fiber-reinforced polymers (PFRPs), often referred to as self-reinforced composites (SRCs). A representative PFRP was exemplified using unidirectional (UD) ultra-high-molecular-weight polyethylene (UHMWPE) fibers embedded in a high-density polyethylene (HDPE) matrix. The effects of compression molding temperature and pressure on the mechanical and morphological behaviors of the filament-wound PFRPs with various fiber volume fractions (V f ) were experimentally investigated. The results elucidate the evolution of morphologies and tensile properties of the PFRPs due to thermal melting, fiber misalignment from pressure, and (V f )-induced structural variance, which has not been comprehensively reported yet. The highest specific tensile strength and modulus of the PFRP laminae reach 600 MPa/(g/cm 3 ) and 31 GPa/(g/cm 3 ), respectively. These properties are comparable to glass-/aramid-fiber-reinforced polymers (GFRPs, GFRTPs, AFRPs, and AFRTPs), with PFRPs exhibiting better ductility (specific strain at peak load ≈ 4%/(g/cm 3 )) than other common polymer composites. The motivation for this work was the high recyclability of PFRPs, which can be recycled by melting both the fibers and the matrix, and then reshaped them for re-manufacturing composites to maximize the efficiency in material reuse. This process simplifies the implementation of closed-loop recycling, re-manufacturing, and reuse to support sustainability in composites. This work aims to contribute to advancing thermoplastic PFRPs for their potential applications in various industries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Multi-pass flow-through reductive catalytic fractionation

Reductive catalytic fractionation (RCF) is a promising lignin-first biorefining strategy that selectively extracts and depolymerizes lignin from whole biomass. Flow-through (FT)-RCF enables physical separation of the biomass and catalyst, but this process configuration typically operates at high solvent-to-biomass ratios. Here, we demonstrate multi-pass FT-RCF, wherein the lignin-enriched solvent obtained after an initial FT-RCF step is recycled and used in subsequent FT-RCF without intermediate lignin recovery. Multi-pass FT-RCF reduces the solvent-to-biomass ratio from 48 to 1.9 L/kg, which is a lower solvent loading than is accessible in batch reactors, without negative impacts on delignification and monomer yield with up to 12 wt % lignin in the solvent. Overall, this work demonstrates that solvent demand in RCF processes, which is a key cost and energy driver to enable this process at scale, can be reduced by recycling lignin oil between RCF reactions.

09 BIOMASS FUELS↗
DOE OSTI2021

Revisiting group contribution theory for estimating fractional free volume of microporous polymer membranes

Fractional free volume (FFV) is a commonly used metric for the development of structure–property relationships for polymer membranes. The most common method to calculate FFV uses Bondi's group contribution method, first introduced in 1964. While updated in 1997, there has not been a significant compilation of new structural motifs since the advent of linear microporous polymers. Here, in this study, we critically examined the assumptions in Bondi's original method and provide four recommendations to streamline and improve the accuracy of calculating van der Waals volume (V W ) for any group. Using these recommendations, we created an updated list of (V W ) values for structural groups commonly present in microporous polymers. The (V W ) and FFV values were then calculated for a database of 123 microporous and high free volume polymers from the literature, showing an average 7% decrease in (V W ) and corresponding increase in FFV by a factor of 24% when compared to prior group contribution correlations in the literature. The significant apparent increase in estimated FFV provides a new perspective to understand and interpret the role of free volume on the separation performance of linear microporous polymers. Additionally, standardization of the group contribution method allows for the direct comparison of FFV values across studies.

42 ENGINEERING↗
DOE OSTI2022

Implications of styrenic triblock copolymer gel mechanics on midblock bridging fraction

Triblock copolymer gels have garnered considerable scientific interest over the past few decades and are used in a variety of applications including consumer cushioning, pressure-sensitive adhesives, and ballistics gels. While many of their applications rely upon understanding mechanical properties, mechanical studies of block copolymer gels are relatively disjointed with each focusing on specific copolymers, which inherently have a fixed molecular weight and composition. Here, the present study examines the quasistatic mechanical response of styrenic triblock copolymer gels composed of seven unique triblock copolymers at various concentrations. Resultant stress-extension data is fitted with the slip-tube network (STN) theory that describes gel mechanics based upon crosslinked network (G c ) and chain entanglement (G e ) modulus contributions. Collectively, modulus contributions imply that midblock bridging is independent of copolymer identity (i.e., molecular weight and block fraction) and dependent on triblock copolymer concentration via F b ∝ φ ABA 0.91±0.39 over the concentration range examined (φ ABA = 0.05–0.39). Gels composed of a complementary diblock-triblock copolymer pair were subsequently analyzed to explore the influence of interlocking loop-loop and loop-bridge pairs within the effective midblock bridging population. These results point to the presence of a physically significant quantity of interlocked loops, but quantitative analysis was inconclusive.

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

Multivariable degradation modeling and life prediction using multivariate fractional Brownian motion

In system prognostics and health management, multivariable degradation models have been widely developed to predict the life of complex systems using degradation data of multiple Performance Characteristics (PCs). Recent studies have detected a Long-Term Memory (LTM) effect among the degradation process of various PCs, implying a strong coupling phenomenon between the future degradation behavior and historical degradation trajectory. Although the LTM has been widely integrated into single-PC-based degradation modeling, it has not been considered in multi-PC-based scenarios. To capture LTM among multiple PCs, this article proposes a novel LTM-integrated Multivariate Degradation Model (MDM) for system life prediction based on multivariate fractional Brownian motion, which simultaneously incorporates the cross-correlation among different PCs. To estimate parameters of the LTM-integrated MDM, a maximum likelihood method is developed. Here, two likelihood-ratio hypothesis tests are developed to test the existence of the overall and individual LTM effect among multiple PCs. Both simulation studies and physical experiments on the performance degradation of solar energy conversion and storage devices are conducted to validate the proposed model. Results reveal that the proposed LTM-integrated MDM significantly outperforms existing MDMs in life prediction, while the lifetime uncertainty is heavily underestimated by those traditional approaches that neglect the LTM.

42 ENGINEERING↗
DOE OSTI2026

Integrating very-high-resolution imagery, Sentinel-2 time-series data, and machine learning to map shrub fractional abundance across arid and semi-arid ecosystems in China

Shrub fractional abundance (SFA), the proportion of shrub cover per unit area, serves as a critical indicator of environmental aridity and ecosystem health in arid and semi-arid regions, particularly across the Mongolian steppe. However, large-scale SFA mapping in Mongolian steppe ecosystems remains challenging due to the small crown size of shrubs, their sparse distribution, and spectral overlap with coexisting low vegetation (e.g., grasses and herbs), which hinders accurate detection using coarser-resolution satellite data or traditional field surveys. To address these challenges, we developed a two-step approach that integrates very-high-resolution (VHR) imagery, time-series Sentinel-2 data, and deep learning techniques. First, we generated high-accuracy benchmark maps of individual shrub crowns from 0.5 m VHR imagery by combining manual segmentation with a hybrid deep learning framework (Dino V2 and convolutional neural networks). Second, we used these shrub crown maps as training data to build an XGBoost model for predicting SFA from 20 m Sentinel-2 time-series data, leveraging phenological information to improve estimation. We validated our approach across 70 sites (1km 2 each) in the Inner Mongolia Autonomous Region, which is representative of Mongolian steppe ecosystems. From VHR imagery, we mapped 1.31 million shrub crowns with an accuracy of R 2 = 0.92. Scaling up with Sentinel-2 data yielded regional SFA maps with an R 2 = 0.60. Further SHAP (SHapley Additive exPlanations) analysis on the developed XGBoost model revealed that phenological metrics (particularly observations in early-May, mid-July, and late-September), which distinguish shrub phenology from that of other land cover types (e.g., grasses and bare soil), were the most influential predictors of SFA. Finally, our regional SFA maps uncovered unimodal relationships between shrub distribution and climate variables, peaking at mean annual minimum temperatures near 0 °C and annual precipitation around 200 mm. Collectively, these findings demonstrate how the integration of multi-source remote sensing and machine learning can overcome historical limitations in SFA mapping, enabling accurate, spatially continuous assessments across vast Inner-Mongolian steppe ecosystems. Our framework has the potential to be applied to other steppe ecosystems and dryland ecosystems across the Mongolian steppe and beyond, offering a foundation for improved monitoring and ecological impact assessments in the face of global climate changes.

Arid and semi-arid landscapes↗
DOE OSTI2024

Coupling Microdroplet-Based Sample Preparation, Multiplexed Isobaric Labeling, and Nanoflow Peptide Fractionation for Deep Proteome Profiling of the Tissue Microenvironment

There is increasing interest in developing in-depth proteomic approaches for mapping tissue heterogeneity in a cell-type-specific manner to better understand and predict the function of complex biological systems such as human organs. Existing spatially resolved proteomics technologies cannot provide deep proteome coverage due to limited sensitivity and poor sample recovery. Herein, we seamlessly combined laser capture microdissection with a low-volume sample processing technology that includes a microfluidic device named microPOTS (microdroplet processing in one pot for trace samples), multiplexed isobaric labeling, and a nanoflow peptide fractionation approach. The integrated workflow allowed us to maximize proteome coverage of laser-isolated tissue samples containing nanogram levels of proteins. We demonstrated that the deep spatial proteomics platform can quantify more than 5000 unique proteins from a small-sized human pancreatic tissue pixel (∼60,000 μm2) and differentiate unique protein abundance patterns in pancreas. Furthermore, the use of the microPOTS chip eliminated the requirement for advanced microfabrication capabilities and specialized nanoliter liquid handling equipment, making it more accessible to proteomic laboratories.

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

Lignin-Derived Phenolic Compounds and Water Are Effective Cosolvents for Reductive Catalytic Fractionation

Reductive catalytic fractionation (RCF) is an effective lignin-first biorefining method to extract lignin as a stabilized oil from lignocellulosic biomass. To realize RCF at scale, process modeling has shown that minimizing the use of exogenous organic solvents is critical. To this end, here we investigate the ability of lignin-derived monomers to act as either solvents or cosolvents for RCF. We begin by examining the influence of lignin-derived aromatic compounds (4-propylguaiacol, 4-propylphenol, and propylbenzene) on RCF monomer yields and subsequently extend our analysis to mixtures of 4-propylguaiacol and either methanol or water. Here, we demonstrate that 4-propylguaiacol is an effective solvent for lignin extraction and depolymerization during RCF, especially when used in combination with water as a cosolvent. Cosolvent mixtures of 4-propylguaiacol and water enable up to 81% lignin extraction, monomer yields up to 25 wt %, and postreaction phase separation. However, unlike methanol, water as a cosolvent fails to inhibit aromatic ring hydrogenation when conducted over Ru/C as a catalyst, potentially leading to excess hydrogen consumption in a process utilizing this approach. Nonetheless, these results suggest a promising strategy for eliminating external organic solvents from RCF by utilizing mixtures of lignin-derived compounds and water as alternative extraction solvents.

09 BIOMASS FUELS↗
DOE OSTI2022

Solvent-driven fractional crystallization for atom-efficient separation of metal salts from permanent magnet leachates

Abstract This work reports a dimethyl ether-driven fractional crystallization process for separating rare earth elements and transition metals. The process has been successfully applied in the treatment of rare earth element-bearing permanent magnet leachates as an atom-efficient, reagent-free separation method. Using ~5 bar pressure, the solvent was dissolved into the aqueous system to displace the contained metal salts as solid precipitates. Treatments at distinct temperatures ranging from 20–31 °C enable crystallization of either lanthanide-rich or transition metal-rich products, with single-stage solute recovery of up to 95.9% and a separation factor as high as 704. Separation factors increase with solution purity, suggesting feasibility for eco-friendly solution treatments in series and parallel to purify aqueous material streams. Staged treatments are demonstrated as capable of further improving the separation factor and purity of crystallized products. Upon completion of a crystallization, the solvent can be recovered with high efficiency at ambient pressure. This separation process involves low energy and reagent requirements and does not contribute to waste generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗