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At least 1,531 records · Page 85

Propagation method and planting density influence canopy developmental transition and biomass productivity in Miscanthus × giganteus

Understanding how establishment practices influence the mechanisms underlying Miscanthus × giganteus (miscanthus) productivity and canopy development is critical for optimizing management. Data was collected during the juvenile (2011–2013) and mature (2024) phases of a long-term field experiment established in Urbana, Illinois, to evaluate the effects of propagation method (plug propagation [PP] and rhizome propagation [RP]), planting density (1.0, 0.75, and 0.25 plants m⁻²), and nitrogen application (0 and 67 kg N ha⁻¹) on end-of-season biomass yield, tiller mass, tiller density, and tiller height. Linear regression models identified the dominant predictors of yield across stand ages and management regimes. Planting density, nitrogen (N) application, and propagation method significantly influenced early yield and canopy development. During the juvenile phase, biomass yield was driven by tiller density due to canopy expansion; in the mature phase, yield became driven by tiller mass. The PP plots produced higher tiller density than the RP plots, resulting in faster canopy closure and higher juvenile-phase yields. Rhizome-propagated (RP) plots produced lower tiller density, but individual tillers were 3.3–6.4 g tiller −1 heavier than PP tillers. After the canopy reached equilibrium, the PP and RP yields were similar because greater RP tiller mass compensated for its lower tiller density. Higher planting density resulted in greater yield and tiller density during the second year (2012), but this effect was absent from the third year (2013) onward. In the juvenile phase, N fertilization enhanced yield by 1.6–3.4 Mg ha −1 . Initiating fertilization in 2013 on unfertilized plots produced biomass similar to that in fertilized plots, suggesting yield recovery in the mature phase. These findings revealed that establishment strategies, including propagation method and planting density, influence juvenile miscanthus canopy development and productivity, transitioning from tiller-density- to mass-dominated yields, but not mature phase productivity.

09 BIOMASS FUELS↗

Identification and evolution of active sites in isomorphously substituted Fe-ZSM-5 catalysts for methane dehydroaromatization (MDA)

Methane dehydroaromatization (MDA) enables the catalytic conversion of methane into aromatics, mainly benzene, along with hydrogen, in a single-step process under non-oxidative conditions. In this study, we prepared a series of isomorphously substituted Fe-ZSM-5 catalysts with exclusively isolated or low-oligomerized sites up to 3.2% Fe weight loading by adding ethylenediaminetetraacetic acid (EDTA) to the crystallization gel. These catalysts exhibit no induction/activation period and a significantly higher maximum product yield compared to Fe/ZSM-5 catalysts prepared by the incipient wetness impregnation method and containing extensively aggregated FeOx. This investigation focuses on the evolution of Fe sites during the post-synthetic treatments. Most importantly, we demonstrate the quantitative relation between Fe site isolation and catalytic activity, proving that isolated or low-oligomerized Fe species at the exchange sites formed during post-synthetic retreatment are the active sites for methane activation.

02 PETROLEUM↗

Multi-frequency progressive refinement for learned inverse scattering

Interpreting scattered acoustic and electromagnetic wave patterns is a computational task that enables remote imaging in a number of important applications, including medical imaging, geophysical exploration, sonar and radar detection, and nondestructive testing of materials. However, accurately and stably recovering an inhomogeneous medium from far-field scattered wave measurements is a computationally difficult problem, due to the nonlinear and non-local nature of the forward scattering process. We design a neural network, called Multi-Frequency Inverse Scattering Network (MFISNet), and a training method to approximate the inverse map from far-field scattered wave measurements at multiple frequencies. We consider three variants of MFISNet, with the strongest performing variant inspired by the recursive linearization method — a commonly used technique for stably inverting scattered wavefield data — that progressively refines the estimate with higher frequency content. MFISNet outperforms past methods in regimes with high-contrast, heterogeneous large objects, and inhomogeneous unknown backgrounds.

97 MATHEMATICS AND COMPUTING↗

Metallic fuel transient fuel-cladding interface liquefaction model assessment platform enabled by integrating BISON with databases

A novel platform has been developed within the BISON fuel performance code to assess models of fuel-cladding interface liquefaction for sodium-cooled fast reactor (SFR) metallic fuels. Here, this platform is crucial because liquefaction at the fuel-cladding interface significantly impacts fuel performance and may compromise fuel pin integrity during transient events. To ensure accurate predictions, the platform integrates data collected during the Integral Fast Reactor (IFR) program, now archived in metallic fuel databases. This integration supports verification and validation (V&V) of the models in BISON. Leveraging the extensive US experience with metallic fuel liquefaction and the collections of preserved legacy data, the platform serves as a powerful tool for evaluating existing models and advancing the development of new ones.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A dynamically bare metal interface enables reversible magnesium electrodeposition at 50 mAh cm −2

Understanding and facilitating pure magnesium nucleation/growth electrodeposition behavior with ultrahigh Coulombic efficiency is complicated by the phenomenon of solid electrolyte interphase (SEI) formation in state-of-the-art, halogen-free magnesium electrolytes. Defining the electrolyte properties necessary to achieve ideal electrodeposition/stripping (E/S) thus remains elusive. Here, in this work, we reveal for the first time, rapid magnesium electrodeposition behavior that forms densely aligned, micron-sized thin platelets by establishing a dynamic bare magnesium/electrolyte interface during high-rate net plating. This effectively “SEI-free” interface allows facile magnesium diffusion and migration in stripping with near-unity E/S efficiency under demanding conditions over long-term cycling. The intrinsic electrolyte stability of the salt/solvent at the molecular level is the key to forming such an interface. The efficacy of the dynamic bare interface and an electrodeposited, free-standing magnesium anode is demonstrated in a high-areal-capacity full cell. These findings provide new design principles and fundamental understanding of interfacial chemistry in multivalent metal batteries.

Mg full cell↗

Understanding ion-selective Li/Na metal plating behavior in hybrid Li-Na battery

This study investigates ion-selective Li/Na metal plating behavior in hybrid Li-Na battery systems, revealing the critical role of electrolyte solvents in these processes. Using a hybrid battery design with a LiFePO 4 cathode, Na metal anode, and NaPF 6 -based electrolytes, we observed contrasting effects of carbonate- and ether-based electrolyte solvents. While ether-based electrolytes showed expected Na plating/stripping, carbonate-based electrolytes surprisingly favored a Li-dominant plating/stripping reaction despite the Na-rich environment. X-ray photoelectron spectroscopy revealed that this selectivity is linked to the composition of the solid electrolyte interphase (SEI) layer, with carbonate electrolytes forming Li-based inorganic-rich SEI layers that facilitate Li-ion diffusion while screening Na ions. In conclusion, these findings challenge the conventional understanding of metal plating in multi-ion environments and offer insights for designing future hybrid battery systems.

25 ENERGY STORAGE↗

Bayesian optimization of entropy-stabilized metal fluoride conversion cathodes and their synthesis

Fluoride-based conversion cathodes are promising for next-generation Li ion batteries because of their high voltage and energy densities. High entropy earth abundant fluoride cathodes are attractive for sustainable battery because of the potentially higher cycling stability. While Ni and Co containing equimolar alloys stabilized by high entropy were considered previously, Ni and Co free non-equimolar metal alloy compositions might offer new opportunities to increase materials stability and average voltage. This opportunity was pursued using Bayesian optimization of average voltage for the computational prediction of (Fe x1 Cu x2 Zn x3 Mn x4 Mg x5 )F 2 cathode chemistries. Theoretical voltage, room temperature free energy, and electronic structure of potentially high voltage compositions were computed using density functional theory calculations. Here, the experimental realization of non-equimolar quinary Co and Ni free fluorides with stable rutile single phase and improved conversion reaction voltage by up to 28 % compared to the equimolar alloy demonstrated the power of Bayesian optimization methods for the computationally guided experimental synthesis of fluoride cathodes. Finally, non-equimolar cathode chemistries were found with cycling stability superior to known multi-element fluorides.

25 ENERGY STORAGE↗

High tensile alloy of copper to mitigate current collector deformation in silicon electrodes for lithium-ion batteries

The volumetric changes of silicon electrodes, along with the strong adhesive properties of certain binders, can lead to plastic deformation of the current collector and create damage in the electrode coating. Here, in this study, we report a detailed study of silicon coatings on a high-tensile alloy (HTA) foil of copper with strength over twice that of conventional copper foils. The HTA current collectors with high mechanical strength can mitigate plastic deformation upon continuous cycling. At moderate areal capacities (2.5–3 mAh cm −2 ), conventional copper foils show significant wrinkling after only a few electrochemical cycles, whereas the HTA foils remain intact. We demonstrate viability of the HTA foils in large format xx6395 pouch cells, in which the HTA current collectors remain intact even at an areal capacity of 4.5 mAh cm −2 ; in contrast, wrinkles form in conventional copper current collectors increasing the likelihood of lithium plating. Computational studies show that stresses generated during cycling of silicon electrodes are very high in the current collector and at the current collector-coating interface, explaining the wrinkling of conventional Cu foils. Our studies highlight importance of current collector to solve the electrochemical and chemo-mechanical performance challenges associated with high-loading silicon electrodes.

Chemo-mechanical degradation↗

Unravelling fast-charging degradation in NMC/Gr pouch cells: Lithium plating and SEI properties

As fast-charging technology expands across the electric vehicle and emerging energy-storage applications, understanding its impact on battery performance and longevity is critical. In this study, 1.8 Ah LiNi 0.6 Mn 0.2 Co 0.2 O 2 /graphite pouch cells were charged at various charging rates (0.5C, 2C, 4C, and 6C) to investigate the degradation mechanisms. Our results showed that well-designed NMC/Gr pouch cells could reach over 1000 cycles with a 2C charging rate, while only reaching around 500 cycles with 4C and 6C charging rates. Fast-charging effects on NMC and graphite electrodes were obtained through a series of post-mortem characterizations, including electrochemical impedance spectroscopy (EIS), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS). Although higher charging rates cause pulverization of NMC secondary particles, the dominant degradation mechanism driving the fading of fast-charging-related performance lies in the graphite anode, where lithium plating and LiF-rich solid electrolyte interphase (SEI) formation result in Li inventory loss and impedance growth. The postmortem results suggest that the formation of a LiF-rich SEI, which exacerbates anode impedance and some irreversible Li + ion loss, is likely driven by the substantial decomposition of PF 6 − during fast charging, an effect often overlooked in smaller laboratory-scale studies.

Luo, Mei [Argonne National Laboratory (ANL), Argon↗

Super-resolution model for overlapping peak detection and improved spatial resolution in high-energy diffraction microscopy

Reconstruction quality in Far-field High-Energy Diffraction Microscopy (FF-HEDM) is limited by the spatial resolution of area detectors and the frequent occurrence of overlapping diffraction spots. To address these challenges, we developed a super-resolution (SR) framework using convolutional neural networks (CNNs) to recreate 2D diffraction peaks at up to ×8 resolution from raw detector data. A specialized simulation tool was created to generate synthetic training datasets with varying degrees of peak overlap. Integrated into the Microstructural Imaging using Diffraction Analysis Software (MIDAS), the SR model improves the spatial accuracy and precision of 3D grain reconstruction by an order of magnitude. This approach provides a robust solution for investigation of complex micromechanical states and material classes where the analysis is limited by the presence of overlapping peaks. Furthermore, the methodology developed here can potentially be extended to other techniques that require sub-pixel accuracy for high-fidelity data analysis.

High-energy diffraction microscopy↗

Compositional effect on pressure-induced polymorphism in high-entropy alloys

Recently, pressure-induced polymorphic phase transitions were discovered in several fragmented high-entropy alloys (HEAs), offering a valuable opportunity to deepen our understanding of these materials. However, the chemical and physical factors that govern these transitions are still unclear. Here, in this work, we combined in situ high-pressure synchrotron X-ray diffraction, X-ray emission spectroscopy (XES), and high-resolution transmission electron microscopy (HRTEM) to systematically study the evolution of the atomic and electronic structures in the Cantor alloy and its face-centered-cubic ( fcc ) subset alloys (CoCrFeMnNi, CoCrFeNi, CoCrMnNi, CoFeMnNi, CoCrNi, CoFeNi, CoMnNi, CrFeNi, and FeMnNi). Surprisingly, diverse behavior was observed among these closely related alloys during compression and decompression, which includes irreversible, reversible fcc to hexagonal close-packed (hcp) phase transitions, or even no detectable phase transitions up to ∼40 GPa. HRTEM measurements confirmed that the fcc and hcp phases abided by the classic Shoji-Nishiyama orientation relationship during the transitions. XES data indicated that high-pressure suppresses the local magnetic moments in all the studied alloys, suggesting that magnetic states do not significantly influence the polymorphic transitions. By comparing the effects of the atomic size difference, entropy, valence electron concentration, and stacking fault energy across all the compositions studied, only the stacking fault energy shows a strong correlation with the phase transitions, indicating it plays a key role in inducing polymorphism in HEAs.

36 MATERIALS SCIENCE↗

AstroPix: A pixelated HVCMOS sensor for space-based gamma-ray measurement

A next-generation medium-energy gamma-ray telescope targeting the MeV range would address open questions in astrophysics regarding how extreme conditions accelerate cosmic-ray particles, produce relativistic jet outflows, and more. One concept, AMEGO-X, relies upon the mission-enabling CMOS Monolithic Active Pixel Sensor silicon chip AstroPix. AstroPix is designed for space-based use, featuring low noise, low power consumption, and high scalability. Desired performance of the device include an energy resolution of 5 keV (or 10% FWHM) at 122 keV and a dynamic range per-pixel of 25–700 keV, enabled by the addition of a high-voltage bias to each pixel which supports a depletion depth of 500 μ m. This work reports on the status of the AstroPix development process with emphasis on the current version under test, version three (v3), and highlights of version two (v2). Version 3 achieves energy resolution of 10.4 ± 3.2% at 59.5 keV and 94 ± 6 μ m depletion in a low-resistivity test silicon substrate.

Astrophysics instrumentation↗

Design of a SiC-Si moving packed-bed particle-to-sCO 2 heat exchanger for high temperature concentrating solar power applications

Particle-based concentrating solar power systems integrated with sCO 2 power cycles offer high thermal efficiencies but require durable heat exchangers to transfer heat from high-temperature particles to the sCO 2 working fluid. Here, this study presents the design and optimization of a silicon carbide-silicon moving packed-bed heat exchanger for fabrication via binder jetting additive manufacturing. The heat exchanger was designed to withstand a 20 MPa sCO 2 pressure and operate at particle inlet temperatures up to 750 °C. The final design features 152 sCO 2 channels distributed across 19 plates, with elliptical corners and a minimum wall thickness of 3 mm. Flow restrictors at the sCO 2 channel inlets significantly improved flow uniformity, reducing thermal stresses and achieving a structural reliability of 99 % under representative operating conditions. The heat exchanger delivers a thermal duty of 9 kW and a volumetric power density of approximately 1 MW/m 3 in the channel region. Sensitivity studies confirmed the heat exchanger’s robustness under varying operating conditions, demonstrating its viability as a high-performance alternative to metallic heat exchangers for particle-based high-temperature concentrating solar power applications.

Barua, Bipul [Argonne National Laboratory (ANL), A↗

Boosting Noise2Inverse via enhanced model selection for denoising computed tomography data

Synchrotron-based x-ray tomographic imaging enables the examination of the internal structure of materials at high spatial and temporal resolution. Experimental constraints can impose dose and time limits on the measurements, introducing a higher level of noise and artifacts in the reconstructed images. Deep learning has emerged as a powerful tool to remove noise from reconstructed images. Recently, the Noise2Inverse method was designed specifically for denoising reconstructed images without requiring paired noisy and clean images. This method creates multiple statistically independent reconstructions used to pair the data in which training involves transforming one reconstruction into the other, and vice versa. Originally designed to be used after a fixed number of epochs, we see in practice that this approach may not produce the optimal model and may unnecessarily waste computational resources. Therefore, we propose an alternative method of identifying the best model during training that aligns with the Noise2Inverse method. During validation, we compare the model output of the multiple reconstructions among each other. We hypothesize that the best model is the one that produces images with the highest similarity, implying a convergence in the predicted material properties and absorption values. To compare model outputs, we consider the absolute error, square error, structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and cosine similarity. We evaluate our method on two simulated tomography datasets and two, real-world, low-contrast, high-energy x-ray tomography datasets. We show our approach is more effective at determining the best model, up to an increase of 12.50% and 12.53% in SSIM and PSNR, respectively, while only requiring a fifth of the training time compared to the original approach.

CT↗

Development, optimization, and application of an episomal plasmid system for Rhodotorula toruloides

Rhodotorula toruloides is an emerging oleaginous yeast with strong potential as a microbial cell factory for the production of acetyl-CoA-derived bioproducts. However, engineering of this organism has been limited by the absence of a functional episomal plasmid system, a foundational genetic tool for rapid gene expression, pathway testing, and CRISPR-based genome engineering. Here, we report the first episomal plasmid system for R. toruloides . Through systematic screening of candidate autonomously replicating sequences (ARSs) from diverse sources, we identified multiple functional ARS elements and selected C63F4, a fragment derived from Contig 63 of R. toruloides CBS14, because of its stable performance. The resulting pC63F4 plasmid was maintained episomally, supported GFP reporter expression, exhibited a copy number of 2.39 ± 0.13, and showed good stability during long term cultivation. To overcome poor transformation efficiency, we developed a Cre- loxP -mediated in vivo re-circularization strategy that enabled reliable delivery of the episomal plasmid. Using this improved system, we demonstrated functional episomal expression of metabolic engineering genes and multi-gene pathways for the production of triacetic acid lactone, fatty alcohols, and limonene. Finally, we leveraged this platform to establish a redesigned CRISPR system that enables seamless genome editing in R. toruloides for the first time, while also simplifying marker recycling. Together, this work establishes a long-needed episomal plasmid platform and associated CRISPR toolkit that will accelerate metabolic engineering, synthetic biology, and fundamental studies in R. toruloides .

CRISPR-Cas9↗

Developing and Implementing Risk-Based Research Safety at Argonne National Laboratory

Facilities operated by the US Department of Energy (DOE) are required to have extensive worker safety and health programs by regulation. Here we describe how Argonne National Laboratory (ANL) has implemented the DOE requirements to bring the Laboratory’s multidisciplinary research risk to an acceptable level to safely execute ANL’s mission to perform cutting-edge research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Polymorphism and Phase Control in Dion–Jacobson 2D 3-(Aminomethyl)piperidinium-Based Metal Iodide Perovskites

Two-dimensional halide perovskites exhibit rich structural diversity and tunable optoelectronic properties, making them promising materials for energy, sensing, and photonic applications. In this work, we report the structural mapping of four distinct polymorphs, γ (P2 1 /c), β (P4/mbm), α (P4/mmm), and δ (Cmcm) in the two-dimensional iodoplumbate, iodostannate, and iodogermanate perovskite so-called Dion-Jacobson series (3AMP)MI4 (M = Sn, Pb, Ge), where 3AMP is 3-(aminomethyl)piperidinium. The phases exhibit systematic evolution in octahedral distortion, lattice symmetry, and metal–halide geometry, enabling structural control over optoelectronic properties. Notably, the α-phase of (3AMP)SnI 4 represents a rare, ambient-stable, high-symmetry structure for Sn-based perovskites, without a phase transition down to 100 K. Variable-temperature single-crystal diffraction, powder x-ray diffraction (PXRD), and calorimetry reveal metal- and temperature-dependent polymorph interconversions, including the emergence of long range supercell reflections in Pb-rich compositions at low temperature. Optical spectroscopy and photoelectron yield spectroscopy confirm band gap tunability and band alignment trends, highlighting symmetry-dependent shifts and anomalous band gap bowing in mixed-metal systems, verified by electronic structure calculations. Calculations additionally indicate that the higher symmetry phases have reduced electron and hole effective masses compared to the lower symmetry phases.

36 MATERIALS SCIENCE↗

Data-Driven Discovery and Experimental Validation of Solvent Polarity Effects on Conjugated Polymer Solution-to-Film Assembly Pathways

Understanding how solvent properties influence the solution-to-film assembly of conjugated polymers remains a critical challenge due to the complex and intertwined nature of polymer–solvent interactions. In this study, we integrate a data-driven framework with experimental validation to identify key parameters influencing the assembly and performance of poly[2,5-(2-octyldodecyl)-3,6-diketopyrrolopyrrole-alt-5,5-(2,5-di(thien-2-yl)thieno[3,2-b]thiophene)] (DPP-DTT) in organic field-effect transistors (OFETs). A machine learning (ML) approach identified the normalized Reichardt polarity parameter (E T N ) as a significant descriptor correlated with DPP-DTT hole mobility (μ). Systematic DPP-DTT devices fabricated using solvents across a wide E T N range revealed that higher E T N solvents yield enhanced μ. To elucidate the structural origins of high μ, we conducted comprehensive analyses using UV–vis–NIR spectroscopy and grazing incidence wide angle X-ray scattering (GIWAXS) measurements. The results revealed that films processed from high E T N solvents exhibit reduced paracrystallinity. By analyzing the solution-state behavior using optical microscopy and solution WAXS, we revealed polymer solubility differences in the various solvents and associated distinct polymer assembly pathways, elucidating why the high E T N solvent produces long-range ordered films. Notably, the high E T N solvent shows a pronounced preference for liquid-crystal (LC)-mediated assembly, providing a mechanistic explanation for the enhanced structural order. Therefore, these results demonstrate that solvent polarity, as evaluated by E T N , serves as an important parameter that plays a significant role in the DPP-DTT assembly pathway and resultant solid-state morphology. This work provides a strategy for integrating data science with experiments to identify critical parameters associated with complex polymer systems and helps guide rational process design for high-performance organic electronics.

36 MATERIALS SCIENCE↗