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At least 127 records · Page 7

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↗

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↗

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↗

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↗

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↗

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↗

Quantum Anomalous Hall Crystal at Fractional Filling of Moiré Superlattices

We predict the emergence of a state of matter with intertwined ferromagnetism, charge order, and topology in fractionally filled moiré superlattice bands. Remarkably, these quantum anomalous Hall crystals exhibit a quantized integer Hall conductance that is different than expected from the filling and Chern number of the band. Microscopic calculations show that this phase is robustly favored at half-filling (𝜈 =1/2) at larger twist angles of the twisted semiconductor bilayer 𝑡⁢MoTe 2 .

Exact diagonalization↗

Unlocking New Regimes in Fractional Quantum Hall Effect with Quaternions

We demonstrate that formulating the composite-fermion theory of the fractional quantum Hall (FQH) effect in terms of quaternions greatly expands its reach and opens the door into many interesting issues that were previously not amenable to quantitative theoretical investigation. As an illustration, we explore the possibility of a nematic or a charge-density wave instability of the composite-fermion Fermi sea at half-filled Landau level and of the nearby FQH states by looking for a gap closing instability of the neutral magneto-roton excitation. As a result, our quaternion formulation of the FQH effect has been inspired by mathematical developments in the theoretical analyses of gravitational wave modes and cosmic microwave background radiation, where an important role is played by spin-weighted spherical harmonics that are nothing but monopole harmonics appearing in the spherical geometry for the FQH effect.

Composite fermions↗

Tabulated data for 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. 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. This is the tabulated data for the paper

biorefining↗

Calculation of monomer yields, verification of PG concentration approximation, catalyst comparison for neat aromatic RCF, SEM micrographs for postreaction pulps, yields of aqueous-phase sugar derivatives after PG-H2O RCF, reactor pressure transients, GPC comparing pre- and postreaction organic solvent composition, PG-H2O miscibility testing, GPC probing dimer/oligomer fractionation in PG-H2O mixtures for

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. 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.

biorefining↗

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. 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.

biorefining↗

Assessment of rare earth element fractionation in NIF implosions with radiochemically doped capsules

An ongoing experimental campaign at the National Ignition Facility (NIF) aims to measure neutron induced nuclear reaction cross–sections using radiochemically doped target capsules. Critical to this campaign is the ability to collect a representative sample of the reaction products using Solid Radiochemical Collectors (SRCs) fielded around the NIF chamber. The shot presented in this paper used a doped target capsule with a neopentane gas fill was to investigate the ratio of isotopes collected at three chamber angles. It was found that SRC samples of rare earth elements collected from NIF are representative of the ingoing dopant mix, thereby concluding that fractionation does not occur during a NIF implosion. This validates the doped capsule method for use in measuring neutron induced reaction cross-sections.

Capsule Doping↗

A Region-Growing Segmentation Approach to Delineating Timberline from Satellite-Derived Tree Fractional Cover Products

Timberline marks the transitions from continuous forests to sparse forests and tundra landscapes. As the spatial distribution and dynamics of timberline are closely associated with regional energy and carbon balance, mapping timberline is important to a wide range of environmental and ecological studies. However, current timberline delineation approaches remain under-developed. We proposed an automatic timberline delineation method based on a seeded region-growing segmentation technique and satellite-derived products of tree fractional cover. We applied our approach to the West Siberian Plain and Alaska treeline regions as defined by the Circumpolar Arctic Vegetation Map. The results demonstrate the effectiveness of the proposed method for the accurate delineation of the timberlines that spatially align well with very-high-resolution satellite images. Based on the delineated timberlines, we find regional-scale tree encroachment to be not as substantial as previously reported. The proposed approach can be applied to understanding climate-induced forest responses and inform forest management practices.

Circumpolar Arctic Vegetation Map↗

High Pressure DME-Driven Fractional Crystallizations

Rare Earth Elements (REEs), include the 15 lanthanides plus yttrium and scandium and are crucial for various technologies and applications. Their low concentrations in the earth's crust require alternative sources. This study explores antisolvent fractional crystallization (FC) using dimethyl ether (DME) under high pressures to extract REEs from secondary sources such as mining waste, coal byproducts, and e-waste. DME's properties, including its solubility in water, small molecular size, and high vapor pressure, make it an effective antisolvent that can be easily recovered and reused. The method involves pressurizing DME to 1000-2000 psi in a reaction chamber with the test solution, followed by sample collection and analysis using ICP-MS and ICP-OES. This approach aims to address the limitations of current extraction methods, such as high energy consumption, chemical usage, and waste production, offering a potentially more efficient and sustainable solution for REE extraction.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

Measurement of branching-fraction ratios and CP asymmetries in B± → DCP±K± decays at Belle and Belle II

Abstract We report results from a study ofB ± → DK ± decays followed byDdecaying to theCP-even final stateK + K − and CP-odd final state$$ {K}_S^0{\pi}^0 $$ K S 0 π 0 , whereDis an admixture ofD 0 and$$ {\overline{D}}^0 $$ D ¯ 0 states. These decays are sensitive to the Cabibbo-Kobayashi-Maskawa unitarity-triangle angleϕ 3 . The results are based on a combined analysis of the final data set of 772×10 6 $$ B\overline{B} $$ B B ¯ pairs collected by the Belle experiment and a data set of 198×10 6 $$ B\overline{B} $$ B B ¯ pairs collected by the Belle II experiment, both in electron-positron collisions at the Υ(4S) resonance. We measure the CP asymmetries to be$$ \mathcal{A} $$ A CP+ = (+12.5±5.8±1.4)% and$$ \mathcal{A} $$ A CP− = (−16.7±5.7±0.6)%, and the ratios of branching fractions to be$$ \mathcal{R} $$ R CP+ = 1.164±0.081±0.036 and$$ \mathcal{R} $$ R CP− = 1.151±0.074±0.019. The first contribution to the uncertainties is statistical, and the second is systematic. The asymmetries$$ \mathcal{A} $$ A CP+ and$$ \mathcal{A} $$ A CP− have similar magnitudes and opposite signs; their difference corresponds to 3.5 standard deviations. From these values we calculate 68.3% confidence intervals of (8.5 ° <ϕ 3 < 16.5 ° ) or (84.5 ° <ϕ 3 < 95.5 ° ) or (163.3 ° <ϕ 3 < 171.5 ° ) and 0.321 B< 0.465.

Physics↗

Noncommutative gauge symmetry in the fractional quantum Hall effect

Abstract We show that a system of particles on the lowest Landau level can be coupled to a probe U(1) gauge field$$ \mathcal{A} $$ A μ in such a way that the theory is invariant under a noncommutative U(1) gauge symmetry. While the temporal component$$ \mathcal{A} $$ A 0 of the probe field is coupled to the projected density operator, the spatial components$$ \mathcal{A} $$ A i are best interpreted as quantum displacements, which distort the interaction potential between the particles. We develop a Seiberg-Witten-type map from the noncommutative U(1) gauge symmetry to a simpler version, which we call “baby noncommutative” gauge symmetry, where the Moyal brackets are replaced by the Poisson brackets. The latter symmetry group is isomorphic to the group of volume preserving diffeomorphisms. By using this map, we resolve the apparent contradiction between the noncommutative gauge symmetry, on the one hand, and the particle-hole symmetry of the half-filled Landau level and the presence of the mixed Chern-Simons terms in the effective Lagrangian of the fractional quantum Hall states, on the other hand. We outline the general procedure which can be used to write down effective field theories which respect the noncommutative U(1) symmetry.

Physics↗

Measurement of the W boson decay branching fraction ratio $\mathscr{B}$(W → cq)/$\mathscr{B}$(W →$q\bar{q}'$) in proton-proton collisions at $\sqrt{s}$ = 13 TeV

The most precise measurement to date of the W boson hadronic decay branching fraction ratio $R_{c}^{W} = \mathcal{B}(W \to cq) / \mathcal{B}(W \to q\bar{q}$) is presented. The measurement is based on a sample of proton-proton collision data from the CERN LHC collected by the CMS experiment at a center-of-mass energy of 13 TeV in 2016-2018 with an integrated luminosity of 138 fb$^{-1}$. The large cross section of top quark-antiquark production at the LHC offers a sizable high-purity sample of W bosons suitable for this measurement. Events with one charged lepton (electron or muon) and at least four jets, two tagged as bottom quark jets, are analyzed. Charm jets are tagged using the presence of a muon inside the jet. The result, $R_\mathrm{c}^\mathrm{W}$ = 0.489 $\pm$ 0.020, is consistent with the standard model prediction and is twice as precise as the current world-average value.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗