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At least 487 records · Page 27

Complete resolution across the neodymium/samarium isotopic envelope with a liquid sampling‐atmospheric pressure glow discharge — Orbitrap mass spectrometer

Rationale Nd and Sm isotope ratios play an important role in geological dating and as nuclear forensic signatures; however, the overlap of the respective 144, 148, 150 Nd/Sm isobars requires prior separations to be performed before analysis on typical MS platforms. The work presented here overcomes these isobaric interferences using ultrahigh‐mass resolution to alleviate interference without prior chemical separations. Methods A liquid sampling‐atmospheric pressure glow discharge ion source was coupled to a standard, QExactive Focus Orbitrap mass spectrometer, providing a mass resolution of ~80 k. A Spectroswiss FTMS booster X2 data acquisition package was used to collect extended transients, providing much higher mass resolution; ~230 k and ~600 k are employed here for Nd and Sm isotopes. Results While the standard Orbitrap resolution is far greater than typical “atomic” MS platforms, it was insufficient to alleviate all isobars. The use of a resolution of ~230 k resulted in baseline separation across the entire isotopic envelope for both Nd and Sm. Isotope ratios obtained from Nd:Sm mixtures using high‐resolution were equivalent to those found for individual‐element solutions, while isotope ratios obtained at a resolution of ~80 k (standard for the OEM data system) showed large deviations. Conclusions Use of ultrahigh‐resolution is an attractive alternative to extensive chemical separations to alleviate severe isobaric interferences. Sufficient mass resolution greatly reduces/eliminates the need for sample manipulations (separations) before analysis while reducing costs and total analysis times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

No–till establishment improves the climate benefit of bioenergy crops on marginal grasslands

Expanding biofuel production is expected to accelerate the conversion of unmanaged marginal lands to meet biomass feedstock needs. Greenhouse gas production during conversion jeopardizes the ensuing climate benefits, but most research to date has focused only on conversion to annual crops and only following tillage. Here we report the global warming impact of converting USDA Conservation Reserve Program (CRP) grasslands to three types of bioenergy crops using no–till (NT) vs. conventional tillage (CT). We established replicated NT and CT plots in three CRP fields planted to continuous corn, switchgrass, or restored prairie. For the 2 yr following an initial soybean year in all fields, we found that, on average, NT conversion reduced nitrous oxide (N 2 O) emissions by 50% and CO 2 emissions by 20% compared with CT conversion. Differences were higher in Year 1 than in Year 2 in the continuous corn field, and in the two perennial systems the differences disappeared after Year 1. In all fields net CO 2 emissions (as measured by eddy covariance) were positive for the first 2 yr following CT establishment, but following NT establishment net CO 2 emissions were close to zero or negative, indicating net C sequestration. Overall, NT improved the global warming impact of biofuel crop establishment following CRP conversion by over 20–fold compared with CT (–6.01 Mg CO 2 e ha –1 yr –1 for NT vs. –0.25 Mg CO 2 e ha –1 yr –1 for CT, on average). We also found that Intergovernmental Panel on Climate Change estimates of N 2 O emissions (as measured by static chambers) greatly underestimated actual emissions for converted fields regardless of tillage. Policies should encourage adoption of NT for converting marginal grasslands to perennial bioenergy crops to reduce C debt and maximize climate benefits.

54 ENVIRONMENTAL SCIENCES↗

Putting the soil health principles to the test in Iowa

One of the most popular soil conservation campaigns is based on the USDA Natural Resource Conservation Service's Soil Health Principles (NRCS-SHPs). The NRCS-SHP program identifies four principles—maximize presence of living roots, minimize disturbance, maximize soil cover, and maximize biodiversity—with the underlying assumption that the more principles one follows, the greater improvements in soil health. Despite the popularity of the NRCS-SHPs, this underlying assumption has not been rigorously tested. To do so, we used nine long-term experiments all located in central Iowa, but with varying degree of NRCS-SHP adoption, to determine if greater adoption increases three slow-changing (maximum water holding capacity, bulk density [BD], and soil organic carbon) and three dynamic (microbial biomass carbon [MBC], potentially mineralizable carbon [PMC], and permanganate oxidizable carbon [POXC]) soil health indicators. We regressed these indicators with a soil health principle score that can scale soil management based on adoption of the NRCS-SHPs. Of the slow-changing soil properties, increased adoption of NRCS-SHPs only decreased soil BD (R2 = 0.22, p = 0.024). On the other hand, increased adoption of NRCS-SHPs strongly predicted increases in both MBC and PMC and across two sampling dates (R2 > 0.23, p < 0.015); POXC, however, did not increase with greater adoption. The consistent increases in MBC and PMC with greater adoption of NRCS-SHPs supports their usefulness as sensitive indicators of positive soil health change. Our study provides scientific evidence to support the NRCS-SHPs concept, improving its usefulness as an extension campaign, and stands as a step toward evidence-based soil conservation.

60 APPLIED LIFE SCIENCES↗

Enhancement of Magneto‐Mechanical Actuation of Micropillar Arrays by Anisotropic Stress Distribution

Abstract Magnetically active shape‐reconfigurable microarrays undergo programmed actuation according to the arrangement of magnetic dipoles within the structures, achieving complex twisting and bending deformations. Cylindrical micropillars have been widely used to date, whose circular cross‐sections lead to identical actuation regardless of the actuating direction. In this study, micropillars with triangular or rectangular cross‐sections are designed and fabricated to introduce preferential actuation directions and explore the limits of their actuation. Using such structures, controlled liquid wetting is demonstrated on micropillar surfaces. Liquid droplets pinned on magnetic micropillar arrays undergo directional spreading when the pillars are actuated as depinning of the droplets is enabled only in certain directions. The enhanced deformation due to direction dependent magneto‐mechanical actuation suggests that micropillar arrays can be fundamentally tailored to possess application specific responses and opens up opportunities to exploit more complex designs such as micropillars with polygonal cross sections. Such tunable wetting of liquids on microarray surfaces has potential to improve printing technologies via contactless reconfiguration of stamp geometry by magnetic field manipulation.

Park, Jeong Eun↗

The Rule of Thirds: Controlling Junction Chirality and Polarity in 3D DNA Tiles

The successful self-assembly of tensegrity triangle DNA crystals heralded the ability to programmably construct macroscopic crystalline nanomaterials from rationally-designed, nanoscale components. This 3D DNA tile owes its “tensegrity” nature to its three rotationally-stacked double helices locked together by the tensile winding of a center strand segmented into 7 base pair (bp) inter-junction regions, corresponding to two thirds of a helical turn of DNA. All reported tensegrity triangles to date have employed [Z + 2/3] turn inter-junction segments, yielding right-handed, antiparallel, “J1” junctions. Here, we report here a minimal DNA triangle motif consisting of 3-bp inter-junction segments, or one third of a helical turn. Here, we find that the minimal motif exhibits a reversed morphology with a left-handed tertiary structure mediated by a locally-parallel Holliday junction—the L1 junction. This parallel junction yields a predicted helical groove matching pattern that breaks the pseudosymmetry between tile faces, and the junction morphology further suggests a folding mechanism. We identify a Rule of Thirds by which supramolecular chirality can be programmed through inter-junction DNA segment length. These results underscore the role that global topological forces play in determining local DNA architecture and ultimately point to an under-explored class of self-assembling, chiral nanomaterials for topological processes in biological systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Single Crystalline GeSe Van Der Waals Ribbons With Uniform Layer Stacking, High Carrier Mobility, and Adjustable Edge Morphology

Abstract Performance of the group IV monochalcogenide GeSe in solar cells, electronic, and optoelectronic devices is expected to improve when high‐quality single crystalline material is used rather than polycrystalline films. Crystalline flakes represent an attractive alternative to bulk single crystals as their synthesis may be developed to be scalable, faster, and with higher overall yield. However, large – and especially large and thin – single crystal flakes are notoriously hard to synthesize. Here it is demonstrated that vapor‐liquid‐solid growth combined with direct lateral vapor‐solid incorporation produces high‐quality single crystalline GeSe ribbons with tens of micrometers size and controllable thickness. Electron microscopy shows that the ribbons exhibit perfect equilibrium (AB) van der Waals stacking order without extended defects across the entire thickness, in contrast to the conventional case of substrate‐supported flakes where material is added via layer‐by‐layer nucleation and growth on the basal plane. Electrical measurements show anisotropic transport and a high Hall mobility of 85 cm 2 V −1 s −1 , on par with the best single crystals to date. Growth from mixed GeSe and SnSe vapors, finally, yields ribbons with unchanged structure and composition but with jagged edges, promising for applications that rely on ample chemically active edge sites, such as catalysis or photocatalysis.

99 GENERAL AND MISCELLANEOUS↗

Evidence of Directional Structural Superlubricity and Lévy Flights in a van der Waals Heterostructure

Abstract Structural superlubricity is a special frictionless contact in which two crystals are in incommensurate arrangement such that relative in‐plane translation is associated with vanishing energy barrier crossing. So far, it has been realized in multilayer graphene and other van der Waals (2D crystals with hexagonal or triangular crystalline symmetries, leading to isotropic frictionless contacts. Directional structural superlubricity, to date unrealized in 2D systems, is possible when the reciprocal lattices of the two crystals coincide in one direction only. Here, directional structural superlubricity a α‐bismuthene/graphite van der Waals system is evidenced, manifested by spontaneous hopping of the islands over hundreds of nanometers at room temperature, resolved by low‐energy electron microscopy and supported by registry simulations. Statistical analysis of individual and collective α‐bismuthene islands populations reveal a heavy‐tailed distribution of the hopping lengths and sticking times indicative of Lévy flight dynamics, largely unobserved in condensed‐matter systems.

Le Ster, Maxime↗

Preserving the Josephson Coupling of Twisted Cuprate Junctions via Tailored Silicon Nitride Circuits Boards

Controlled fabrication of twisted van der Waals heterostructures is essential to unlock the full potential of moiré materials. However, achieving reproducibility remains a major challenge, particularly for air-sensitive materials such as Bi 2 Sr 2 CaCu 2 O 8 + δ (BSCCO), where it is crucial to preserve the intrinsic and delicate superconducting properties of the interface throughout the entire fabrication process. Here, a dry, inert and cryogenic assembly method is presented that combines silicon nitride nanomembranes (NMBs) with pre-patterned electrodes and the cryogenic stacking technique (CST) to fabricate high-quality twisted BSCCO Josephson junctions (JJs). This protocol prevents thermal and chemical degradation during both interface formation and electrical contact integration. It is also found that asymmetric membrane designs, such as a double cantilever, effectively suppress vibration-induced disorder due to wire bonding, resulting in sharp and hysteretic current–voltage characteristics. The junctions exhibit a twist-angle-dependent Josephson coupling with magnitudes comparable to the highest-performing devices reported to date, but achieved through a straightforward and versatile contact method, offering a scalable and adaptable platform for future applications. These findings highlight the importance of both interface and contact engineering in addressing reproducibility in superconducting van der Waals heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

An Oxygen‐Scavenger Sulfide Coating Enabling Long‐Term Stable Nickel‐Rich Cathodes

Oxygen release is a major issue associated with layer-structured metal oxide cathodes in lithium batteries, which can further cause a series of problems, such as irreversible phase transition, microcracking, and electrolyte decomposition. Eventually, these issues jointly result in cell performance degradation and safety hazards. Thus, it is very significant to tackle oxygen release for achieving long-term stable cyclability, but very challenging. Although intensive efforts have been invested to date, there still lacks a feasible solution. In this study, nanoscale ZrS 2 coatings are applied on prefabricated LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathodes directly via atomic layer deposition (ALD). Very encouragingly, we reveal that this ALD-deposited conformal ZrS 2 nanocoating can serve as an exceptional oxygen scavenger and then convert into a stable sulfate (Zr(SO 4 ) 2 ) coating. Such an in situ conversion is very beneficial and effective for protecting the electrolyte from decomposition. In addition, the resultant Zr(SO 4 ) 2 coating further inhibits undesirable reactions, stabilizes the interface between NMC811 and the electrolyte, suppresses microcracking, mitigates transition metal dissolution, and maintains the structural stability of the NMC811 cathode. Consequently, the ZrS 2 -coated NMC811 cathode has demonstrated extraordinary performance. Thus, this study advances the understanding of interface engineering while paving a new technical pathway for commercializing NMC811 cathodes.

Nickel-rich cathodes↗

Metalloborophenes: Structural Diversity and Emerging Properties of Metal–Boron Two‐Dimensional Frameworks

Metalloborophenes, an emerging subclass of 2D materials, have attracted growing attention owing to their exceptional structural diversity and highly tunable electronic and magnetic properties. Constructed from vacancy‐rich borophene frameworks stabilized by electron donation from incorporated metal atoms, metalloborophenes merge the chemical versatility of boron with the functional richness of metal dopants. The first experimental realization of Cu–borophene nanoribbons in 2024 marked a pivotal advance, confirming long‐standing theoretical predictions and revitalizing interest in this new frontier of boron‐based 2D chemistry. Despite this progress, most studies to date remain conceptual and theoretical, constrained by challenges in scalable synthesis, dopant precision, and substrate control. Computational investigations have revealed a broad landscape of stable metalloborophene structures, exhibiting metallic, semiconducting, and magnetic behavior across diverse dopant families, including alkali, alkaline‐earth, transition, and lanthanide elements. These tunable characteristics open promising avenues for applications in spintronics, catalysis, and hydrogen storage. This review provides a comprehensive overview of metalloborophenes, emphasizing the interplay between structure, stability, and functionality, and outlining future directions toward bridging predictive modeling with experimental realization of this rapidly evolving class of 2D materials.

2D materials↗

Exploring Charged Defects in Ferroelectrics by the Switching Spectroscopy Piezoresponse Force Microscopy

Monitoring the charged defect concentration at the nanoscale is of critical importance for both the fundamental science and applications of ferroelectrics. However, up-to-date, high-resolution study methods for the investigation of structural defects, such as transmission electron microscopy, X-ray tomography, etc., are expensive and demand complicated sample preparation. Here, with an example of the lanthanum-doped bismuth ferrite ceramics, a novel method is proposed based on the switching spectroscopy piezoresponse force microscopy (SSPFM) that allows probing the electric potential from buried subsurface charged defects in the ferroelectric materials with a nanometer-scale spatial resolution. When compared with the composition-sensitive methods, such as neutron diffraction, X-ray photoelectron spectroscopy, and local time-of-flight secondary ion mass spectrometry, the SSPFM sensitivity to the variation of the electric potential from the charged defects is shown to be equivalent to less than 0.3 at% of the defect concentration. Additionally, the possibility to locally evaluate dynamics of the polarization screening caused by the charged defects is demonstrated, which is of significant interest for further understanding defect-mediated processes in ferroelectrics.

42 ENGINEERING↗

Subsampling and DNA pooling can increase gains through genomic selection in switchgrass

Genomic selection (GS) can accelerate breeding cycles in perennial crops such as the bioenergy grass switchgrass (Panicum virgatum L.). The sequencing costs of GS can be reduced by pooling DNA samples in the training population (TP), only sequencing TP phenotypic outliers, or pooling candidate population (CP) samples. These strategies were simulated for two traits (spring vigor and anthesis date) in three breeding populations. Sequencing only the outlier 50% of the TP phenotype distribution resulted in a penalty of <5% of the predictive ability, measured using cross-validation. Predictive ability also decreased when sequencing progressively fewer TP DNA pools, but TPs constructed from only two phenotypically contrasting DNA samples retained a mean of >80% predictive ability relative to individual TP sequencing. Novel group testing methods allowed greater than one CP individual to be screened per sequenced DNA sample but resulted in a predictive ability penalty. To determine the impact of reduced sequencing, genetic gain was calculated for seven GS scenarios with variable sequencing budgets. Reduced TP sequencing and most CP pooling methods were superior to individual sequence-based GS when sequencing resources were restricted (2,000 DNA samples per 5-yr cycle). Only one scenario was superior to individual sequencing when sequencing budgets were large (8,000 DNA samples per 5-yr cycle). This study highlights multiple routes for reduced sequencing costs in GS.

59 BASIC BIOLOGICAL SCIENCES↗

Influence of tower shadow on downwind flexible rotors: Field tests and simulations

Abstract As wind turbine rotors become larger, the blades become more flexible, requiring extra stiffness and cost to avoid the risk of tower strike. Wind turbines in a downwind configuration have a reduced risk of tower strike because the rotor thrust acts away from the tower. However, downwind blades pass through the wake of the tower, and the resulting load variation may contribute to blade fatigue. To date, there have been no field tests to quantify this tower shadow effect on unsteady blade moments. The present study reports on the first field testing of a flexible, downwind, coned rotor and compares the experimental data against simulations run in OpenFAST. The tower shadow effect is simulated using the conventional Powles model and a new Eames model (developed herein), which includes the influence of upstream turbulence. Both models reasonably predict the blade root out‐of‐plane bending moment data and the tower shadow dip magnitude when compared to field test data in Region 3. Tower shadow was found to increase the short‐term Damage Equivalent Loads (DELs) by less than 10% compared to other effects (gravity, shear, and turbulence), and the predictions were consistent with experiments. These results indicate that the tower shadow effect can be reasonably modeled with the simpler Powles model and that the tower shadow effect can be small compared to the effect of turbulence. However, long‐term fatigue due to tower shadow should be included in detailed structural analysis and design of the rotor and the tower.

Simpson, Juliet G.↗

Using observational mean-flow data to drive large-eddy simulations of a diurnal cycle at the SWiFT site

Reproducing realistic date- and site-specific unsteady wind conditions in large-eddy simulations is becoming increasingly useful in wind energy. How to run a large-eddy simulation to match observed conditions, however, remains an open research question. One approach that has received considerable attention is mesoscale-to-microscale coupling, in which information about the mesoscale weather, most commonly acquired from a mesoscale numerical weather model, is passed on to a microscale model. In this paper, we demonstrate how the recently developed profile-assimilation technique, a form of mesoscale-to-microscale coupling, can be used to drive large-eddy simulations solely based on observed mean-flow profiles at a single location, bypassing the need for auxiliary mesoscale simulations. The new approach is evaluated for a diurnal cycle at the Scaled Wind Farm Technology site. Observed mean-flow profiles from the ground up to a height of 2 km are reconstructed by aggregating measurements from multiple instruments, and gaps in the data are infilled with natural neighbor interpolation. We perform nine simulations using various forcing approaches to deal with data limitations. The results show that it is indeed possible to drive microscale large-eddy simulation with observations using the profile-assimilation technique, notwithstanding large gaps in virtual potential temperature measurements. However, profile assimilation with vertical smoothing of the error between the desired and actual profiles is required. Without that smoothing, the microscale simulations develop unrealistically high turbulence levels under many situations. Finally, we show that simulated mesoscale data can account for missing observations, although care is needed as both data sources are not necessarily compatible.

17 WIND ENERGY↗

Valence-to-core X-ray emission spectroscopy of titanium compounds using energy dispersive detectors

X-ray emission spectroscopy (XES) of transition metal compounds is a powerful tool for investigating the spin and oxidation state of the metal centers. Valence-to-core (vtc) XES is of special interest, as it contains information on the ligand nature, hybridization, and protonation. To date, most vtc-XES studies have been performed with high-brightness sources, such as synchrotrons, due to the weak fluorescence lines from vtc transitions. Here, we present a systematic study of the vtc-XES for different titanium compounds in a laboratory setting using an X-ray tube source and energy dispersive microcalorimeter sensors. With a full-width at half-maximum energy resolution of approximately 4 eV at the Ti Kβ lines, we measure the XES features of different titanium compounds and compare our results for the vtc line shapes and energies to previously published and newly acquired synchrotron data as well as to new theoretical calculations. Finally, we report simulations of the feasibility of performing time-resolved vtc-XES studies with a laser-based plasma source in a laboratory setting. Our results show that microcalorimeter sensors can already perform high-quality measurements of vtc-XES features in a laboratory setting under static conditions and that dynamic measurements will be possible in the future after reasonable technological developments.

36 MATERIALS SCIENCE↗

The Efficacy of Replacing Metallic Cerium in Aluminum–Cerium Alloys with LREE Mischmetal

The ongoing development of aluminum–cerium alloys has produced materials exhibiting elevated temperature mechanical property retention, long term microstructural stability, and flexible processability compared to traditional aluminum alloys, accommodating the growing demand for high temperature aluminum alloys not requiring the use of high-cost elements like scandium. To date, reported Al–Ce alloy compositions contain large amounts of elemental cerium. Mischmetal (MM), a mixture of lanthanum, cerium, and other light rare earth elements (LREE) is less expensive and more available than pure cerium. The chemical similarity of the LREEs means there is possibility to use MM as the primary alloy addition, lowering alloy cost. This talk will report the effect of using MM instead of cerium in a 12 wt% binary alloy on mechanical properties, phase constituency, thermal stability, and load sharing. Results will show that MM can be substituted completely for cerium with a mostly positive impact on alloy performance.

Sims, Zachary↗

Machine-Learning Accelerated Studies of Materials with High Performance and Edge Computing

In the studies of materials, experimental measurements often serve as the reference to verify physics theory and modeling; while theory and modeling provide a fundamental understanding of the physics and principles behind. However, the interactions and cross validation between them have long been a challenge even to-date. Not only that inferring a physics model from experimental data is itself a difficult inverse problem, another major challenge is the orders-of-magnitude longer wall-clock time required to carry out high-fidelity computer modeling to match the timescale of experiments. We envisage that by combining high performance computing, data science, and edge computing technology, the current predicament can be alleviated, and a new paradigm of data-driven physics research will open up. For example, we can accelerate computer simulations by first performing the large-scale modeling on high performance computers and train a machine-learned surrogate model. This computationally inexpensive surrogate model can then be transferred to the computing units residing closely to the experimental facilities to perform high-fidelity simulations at a much higher throughout. The model will also be more amenable to analyzing and validating experimental observations in comparable time scales at a much lower computational cost. Further integration of these accelerated computer simulations with an outer machine learning loop can also inform and direct future experiments, while making the inverse problem of physics model inference more tractable. We will demonstrate a proof-of-concept by using a quantum Monte Carlo application, Dynamical Cluster Approximation (DCA++), to machine-learn a surrogate model and accelerate the study of quantum correlated materials.

Li, Ying Wai↗

LC-MEMENTO: A Memory Model for Accelerated Architectures

With the advent of heterogeneous architectures, in particular, with the ubiquity of multi-GPU systems, it is becoming increasingly important to manage device memory efficiently in order to reap the benefits of the additional core count. To date, such responsibility mainly falls on the programmer where device-to-host data communication (and vice versa), if not done properly, may incur costly memory transfer operations and synchronization. The problem may be compounded by additional requirement to maintain system-wide memory consistency that may involve expensive synchronization overhead. In this paper, we present Location Consistency Memory Model for Enhanced Transfer Operations (LC-MEMENTO). This framework considers incorporating runtime techniques for multi-GPU memory management to support relaxed synchronization semantics and memory transfer operations automatically. Specifically, we implement a relaxed form of a memory consistency model based on the Location Consistency (LC) in an Asynchronous Many-Task Runtime (ARTS) and demonstrate that, this memory model enables additional optimization opportunities for the three representative applications encompassing different computational patterns (scientific computation, graphs, data streaming, etc.).

Memory Models, Accelerators, Adaptive Optimization↗