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726 records · Page 17

Large moiré superstructure of stacked incommensurate charge density waves

This article reports how two different charge density waves with slightly different wavevectors can exist in the same crystal and create moiré superstructure. Advances in heterostructure fabrication have opened new frontiers in moiré physics. Here we extend moiré engineering from artificially assembled thin flakes with mismatched lattice parameters to materials that host incommensurate orders, presenting a long-period moiré superlattice in a layered charge-density-wave compound, EuTe 4 . Using high-momentum-resolution X-ray diffraction, we found two coexisting incommensurate charge density waves with slightly mismatched in-plane wavevectors. The interaction between these two charge density waves leads to joint commensuration with the lattice and a moiré superstructure with a period of ~13.6 nm, offering key insights into the unique properties of EuTe4, such as the temperature-invariant incommensurate wavevectors and unconventional in-gap states. Owing to interlayer phase shifts, the moiré superstructure exhibits a clear thermal hysteresis, accounting for the large hysteresis in electrical resistivity and numerous metastable states. Our findings open new directions for moiré engineering based on incommensurate lattices and highlight the important role of interlayer ordering in stacked structures.

36 MATERIALS SCIENCE

Toward Trustworthy Autonomous Science: A Two-Year Community Roadmap

One year ago, the AISLE roadmap argued that autonomous laboratories operated as isolated islands and proposed a grassroots network organized around five critical dimensions. The field has since moved faster than that roadmap anticipated: multi-agent systems have produced experimentally validated hypotheses, self-driving laboratories have grown more interoperable and orchestrated, reasoning-trained and domain foundation models have raised the capability ceiling, and the Genesis Mission has placed autonomous experimentation at the center of U.S. federal science strategy, with industry emerging as a primary actor. Progress has met a sobering counter-current, including a corrected flagship discovery result, benchmarks showing that agents which rival experts on closed-ended questions still complete only a fraction of open-ended research, and fabricated citations surfacing at leading venues. We read this as the defining tension of the field: producing a candidate discovery is no longer the hard part, but verifying it is, and this asymmetry now limits autonomous science more than raw model capability. Accordingly, we update the roadmap around seven dimensions, revisiting the original five and elevating two former cross-cutting concerns, trust, verification, and reproducibility, and safety, security, and governance, to first-class status. We assess the original milestones (M1 through M14) as achieved, partially achieved, reframed, or open, add four new milestones (M15 through M18) for the elevated dimensions, and scope the path forward to a two-year horizon, with the first year concentrating on interfaces, protocol adoption, and the scaffolding of verification, and the second targeting federation, zero-trust coordination, and governance. Throughout, we position the grassroots network as the interoperability fabric that lets national programs, international initiatives, and commercial platforms connect rather than re-silo.

99 GENERAL AND MISCELLANEOUS

Interleaved bond frustration in a triangular lattice antiferromagnet

Frustration of long-range order via lattice geometry amplifies fluctuations and generates ground states that are highly sensitive to perturbations. Traditionally, geometric frustration is used to engineer unconventional magnetic states; however, the charge degree of freedom and bond order can be similarly frustrated. Finding materials that host both frustrated magnetic and bond networks holds promise for engineering structural and magnetic states with the potential of coupling to one another via either magnetic or strain fields. Here we identify an unusual instance of this coexistence in the triangular lattice antiferromagnets LnCd 3 P 3 (Ln = lanthanides). These compounds feature two-dimensional planes of unique trigonal planar CdP 3 units with an underlying bond instability that is frustrated via emergent kagome ice correlations. This bond instability is interleaved in between layers of frustrated magnetic moments. Furthermore, our results establish LnCd 3 P 3 as a rare materials class in which frustrated magnetism is embedded within a dopable semiconductor with a frustrated bond order instability.

Gomez Alvarado, S. J. [University of California, S

Probing the role of local tunnel variations in early-stage lithiation of α-MnO₂ nanowires via in situ TEM

Understanding lithium-ion transport in tunnel-structured manganese oxides is essential for designing high-performance lithium-ion battery electrode materials. Here, we elucidate the early-stage lithiation mechanism of potassium-stabilized α-MnO 2 nanowires using in situ transmission electron microscopy (TEM) coupled with electron energy-loss spectroscopy (EELS), high-resolution TEM (HRTEM), and geometric phase analysis (GPA). Real-time TEM imaging reveals clear volume expansion at the reaction front, while EELS analysis uncovers lithium-ion diffusion far beyond this region, where no visible expansion is observed, indicating fast, defect-assisted transport. GPA and HRTEM analyses show that localized tensile and compressive strain fields, originating from pre-existing local tunnel structural variations, persist after lithiation. The tensile-strained regions enable lithium-ion insertion with minimal lattice distortion, offering additional free volume that facilitates rapid lithium-ion accommodation ahead of the structural transformation. Our results demonstrate a local tunnel variation-mediated fast diffusion pathway that precedes bulk reaction, underscoring the critical role of local strain in enabling early-stage lithium transport. Given the structural versatility of MnO 2 and its ability to accommodate diverse atomic arrangements beyond the well-known tunnel phases (β-, γ-, δ-, λ-, R-phases), our findings highlight the importance of understanding and engineering local structural environments. This work provides fundamental insights into the interplay between defects, strain, and ion dynamics, and presents defect engineering as a promising approach to enhance both rate performance and structural stability in manganese-based cathodes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Deep Learning and Photogrammetric Reconstruction for Automated Crack Detection and Dimensional Measurement in Mining Operations

Surface crack detection and dimensional measurement at active mining sites present significant safety and operational challenges. Manual inspection methods are labor-intensive, spatially incomplete, and expose personnel to hazardous environments, while existing automated approaches have been developed primarily for concrete civil infrastructure and have not been validated on the complex, variable surfaces characteristic of mining environments. This dissertation presents an automated pipeline that integrates deep learning semantic segmentation with Structure-from-Motion photogrammetry to detect surface cracks and measure their aperture, length, and vertical displacement from standard RGB imagery acquired during routine Uncrewed Aerial Vehicle (UAV) survey operations, without requiring additional sensor hardware or manual measurement. The pipeline combines a U-Net architecture with an EfficientNet-B0 encoder, pretrained on the SDNET2018 concrete crack dataset and fine-tuned on a mining-specific dataset spanning laboratory concrete specimens, coal refuse impoundment embankments, and post-blast limestone quarry benches. Photogrammetric reconstruction is performed using COLMAP Structure-from-Motion and Multi-View Stereo, with crack segmentation masks projected into the reconstructed point cloud to enable three-dimensional vertical displacement measurement through local plane fitting and bimodal surface detection. The pipeline was validated across 36 controlled laboratory specimens at three imaging distances and four vertical displacement levels, achieving aperture measurement RMSE of 0.047 cm and R² of 0.954, and vertical displacement RMSE of 0.140 cm and R² of 0.966, against independent caliper measurements. Field application at a coal refuse impoundment in southwestern Pennsylvania detected 71 crack components across the embankment crest, with a dominant longitudinal crack exhibiting aperture values reaching 28 cm and a 95th percentile vertical displacement of 35.53 cm, consistent in magnitude and spatial distribution with simultaneously acquired LiDAR-derived estimates. Application across four post-blast limestone quarry bench datasets in California successfully characterized blast-induced fracture networks at ground sampling distances ranging from 0.59 to 1.23 cm/pixel, with detected crack geometries physically consistent with observable surface conditions at each site. The results demonstrate that deep learning-based crack detection and photogrammetric measurement can be integrated into routine UAV inspection workflows at mining sites, providing repeatable, scalable, and quantitative crack characterization across surface types, crack scales, and displacement magnitudes not previously addressed in the literature. The pipeline requires no dedicated surveying equipment beyond the UAV platforms already deployed at mine sites for survey and monitoring purposes, supporting practical adoption within existing operational workflows.

Crack detection, Dimensional Measurement

Temperature-dependent spin dynamics in Cr 2 O 3

Cr 2 ⁢O 3 emerges as a prominent candidate material for spintronics and magnetoelectronic applications. However, a comprehensive understanding of its temperature-dependent spin dynamics remains elusive, impeding the engineering of novel spintronics based on this material. Here, we delve into this through a combination of inelastic neutron scattering experiments and atomistic simulations. Our results unveiled the emergence of paramagnons above and below 𝑇 𝑁 . We demonstrated a significant softening of linear magnons upon heating in the antiferromagnetic state. Further analysis revealed that this softening primarily originated from four-magnon interactions, while thermal expansion played a minor role.

antiferromagnetism

Modeling Radiolysis and Chemical Reactions during Dry Storage of Aluminum-clad Spent Nuclear Fuel

After aluminum-clad spent nuclear fuel (ASNF) is removed from the reactor, it is initially stored in spent fuel pools, which are specially designed water-filled basins that provide temporary cooling to reduce the temperature of the fuel assemblies and provide radiation shielding. ASNF continues to generate heat due to the radioactive decay of elements within the fuel, which persists for many years post-shutdown as the residual radioactive products decay into more stable elements. During the wet storage period, an oxyhydroxide layer composed of boehmite/bayerite forms on the surfaces of the aluminum cladding from exposure to water in the pools. Road-ready packaging for long-term disposition of the ASNF involves dry storage in helium backfilled DOE standard canisters (DSCs). When the ASNF is removed from water storage and dried, most of the water is removed, but some physisorbed and chemisorbed water remains in the oxyhydroxide layers. This residual water can produce hydrogen when exposed to radiation from the ASNF during dry storage. Predicting hydrogen accumulation over time in the DSCs is critical for long-term storage considerations. Previous modeling efforts have developed coupled computational fluid dynamics (CFD)-chemical models to simulate temperature, pressure, and gas phase concentrations within the DSCs. These models use the thermal field predicted by CFD as input to a radiolysis model for the gas phase and the surface oxyhydroxide layer chemistry. Given the long storage period of the DSCs and the impracticality of long-term experiments, a simulation-based approach is necessary to assess chemical evolution within the canisters. This study advances the development of a modeling framework designed to simulate the chemical evolution of spent fuel canisters. Both thermal and radiation-driven reactions are considered, with radiation kinetics quantified using G-values. Sensitivity analysis identifies key parameters influencing species composition. Reaction pathway diagrams offer insight into dominant species formation routes, enabling more effective comparisons between model predictions and experimental observations, particularly regarding the production of hydrogen. Results show that the model predicts significant hydrogen gas production with minimal oxygen generation, primarily due to hydrogen formation via boehmite pathways. These findings underscore the importance of accurately characterizing surface-bound species and radiolysis kinetics. A deeper understanding of these mechanisms is critical for evaluating the long-term safety of nuclear waste storage.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE

Final Report: Process Intensification of Hydrogen Production through Sorption-Enhanced Gasification of Biomass

The University of Utah, in partnership with Idaho National Laboratory (INL), evaluated Sorption-Enhanced Gasification (SEG) as a transformative pathway for producing hydrogen with the potential for negative CO 2 emissions. SEG integrates gasification, water-gas shift, and in-situ carbon capture within a dual fluidized bed reactor to enable efficient clean hydrogen production. Key challenges related to biomass variability and process complexity were addressed through feedstock engineering, reaction optimization, and process validation. A co-pelletized biomass–limestone feedstock was developed to simplify feeding and introduction of makeup limestone. Kinetic and sorbent studies identified optimal operating conditions and confirmed the suitability of low-cost limestone, while catalysts were developed to reduce tar formation. Reactor modeling and techno-economic analysis indicated that SEG can achieve competitive hydrogen production costs, particularly when combined with carbon incentives, supporting its potential for scale-up and carbon-negative operation.

08 HYDROGEN

Atomic Evolution of Hydrogen Intercalation Wave Dynamics in Palladium Nanocrystals Revealed by Liquid-Phase Transmission Electron Microscopy

Solute-intercalation-induced phase separation creates spatial heterogeneities in host materials, a phenomenon ubiquitous in batteries, hydrogen storage, and other energy devices. Despite many efforts, probing intercalation processes at the atomic scale has been a significant challenge. By utilizing liquid-phase transmission electron microscopy (TEM), we study hydrogen (de)intercalation in palladium nanocrystals as a model system and have achieved unprecedented atomic-resolution imaging of hydrogen intercalation wave dynamics. Our observations reveal that intercalation wave mechanisms, instead of shrinking-core mechanisms, prevail at ambient temperature for palladium nanocubes ranging from ∼60 nm down to ∼10 nm. Systematic image analysis uncovers the atomic evolution of the hydrogen intercalation wave, transitioning from nonplanar and inclined boundaries to those closely aligned with {100} planes. Our kinetic Monte Carlo simulations demonstrate that the observed intercalation wave dynamics correspond to sorption pathways minimizing the lattice mismatch strain at the phase boundary. In conclusion, unveiling the atomic intercalation pathways holds profound implications for engineering intercalation-mediated devices and advancements in energy sciences.

Lee, Daewon [Lawrence Berkeley National Laboratory

Ultrafast Nanoimaging of Carrier Funneling in Composition-Graded Semiconductor Nanowires

Recent advances in bandgap engineering of low-dimensional semiconductors have enabled high-efficiency carrier transport in miniaturized electronic and optoelectronic devices. The physical properties and functionalities of these materials are governed by complex carrier dynamics coupled with multiple transport mechanisms in tailored band structures. Here, we report ultrafast nanoimaging of carrier funneling and recombination in composition-grade CdSxSe1-x nanowires using pump-probe near-field nanoscopy. Leveraging the high resolution of this technique in both space and time, we resolve nanoscale local carrier dynamics along composition-graded nanowires, revealing the local variation of composition-dependent carrier mobilities and lifetimes that significantly differ from their uniform composition counterparts. Furthermore, we demonstrate a length-dependent behavior wherein shorter nanowires exhibit enhanced funneling effects, accelerating carrier transport by up to 33%. Our findings provide direct visualization of nanoscale carrier transport while supporting an effective approach for investigating complex carrier interactions in inhomogeneous semiconductor nanostructures, with implications for optimizing next-generation optoelectronic devices.

Yang, Rundi

Enhancing NO Reduction by CO Over NiO/CeO 2 Catalyst by Optimizing the Metal Oxide–Support Interaction

Noble metal catalysts are widely used in three-way catalysts (TWCs) due to their high efficiency, but their scarcity and high cost drive the need for effective, low-cost alternatives. Here, in this work, a series of NiO/CeO 2 catalysts were engineered by modulating the OH content and crystallite size of the CeO 2 support. This approach yielded Ni species ranging from isolated single atoms to small clusters and larger aggregates, with varied NiO/CeO 2 interaction strengths. Evaluation of their performance in NO reduction by CO, CO oxidation, and the water–gas shift reaction revealed that the NiO/CeO 2 -300 catalyst, featuring small CeO 2 crystallites and highly dispersed NiO clusters, delivered superior activity for NO reduction and CO oxidation. It was demonstrated that small NiO clusters, due to their efficient CO adsorption and activation, were more active than Ni single atoms. Furthermore, the presence of water was found to influence the catalyst stability, with NiO clusters less stable than single atoms likely due to the hydroxylation effect leading to the formation of Ni(OH) 2 . Oxygen storage capacity measurements revealed that performance was governed by a combination of CeO 2 crystallite size and the abundance of NiO/CeO 2 interfaces. These findings demonstrated that the catalytic performance of Ni/CeO 2 systems could be maximized by optimizing the Ni nanostructure and its interaction with CeO 2 support, positioning them as a promising, multifunctional nonprecious alternative for three-way catalysis application.

36 MATERIALS SCIENCE

Learning Nonlinear Reduced Models from Data with Operator Inference

This review discusses Operator Inference, a nonintrusive reduced modeling approach that incorporates physical governing equations by defining a structured polynomial form for the reduced model, and then learns the corresponding reduced operators from simulated training data. The polynomial model form of Operator Inference is sufficiently expressive to cover a wide range of nonlinear dynamics found in fluid mechanics and other fields of science and engineering, while still providing efficient reduced model computations. The learning steps of Operator Inference are rooted in classical projection-based model reduction; thus, some of the rich theory of model reduction can be applied to models learned with Operator Inference. This connection to projection-based model reduction theory offers a pathway toward deriving error estimates and gaining insights to improve predictions. Furthermore, through formulations of Operator Inference that preserve Hamiltonian and other structures, important physical properties such as energy conservation can be guaranteed in the predictions of the reduced model beyond the training horizon. This review illustrates key computational steps of Operator Inference through a large-scale combustion example.

Mechanics

Breaking the Energy Barrier of Heavy Metal Ion Diffusion in Micropores with Mesoporous 3D Graphene for Fast and Efficient Cu2+ Removal

Efficient removal of heavy metals from water critically depends not only on adsorption capacity but also on ion diffusion kinetics and the associated energy barriers. In conventional carbon adsorbents, severe diffusion confinement within micropores restricts ion transport, resulting in sluggish adsorption kinetics and large apparent activation energies despite high specific surface areas. Here, we demonstrate that this fundamental limitation is overcome by engineering meso/macroporous architectures in the 3D graphene materials synthesized via our discovered alkali-metal reactions with\\\\r\\\\n2\\\\r\\\\nCO. The unique 3D graphene materials possess defect-rich graphene frameworks with interconnected meso/macroporous networks, exhibiting simultaneously high surface area and greatly enhanced meso/macropore volume that enable efficient access to adsorption sites. As a result, the Cu2+ adsorption on 3D graphene proceeds with very low activation energies (4.98 kJ mol–1), which is almost 4 times smaller than on activated carbon (23.1 kJ mol–1). This finding offers a promising platform for efficient and sustainable water purification.

25 ENERGY STORAGE

A topological superconductor tuned by electronic correlations

A topological superconductor, characterized by either a chiral order parameter or a topological surface state in proximity to bulk superconductivity, is foundational to topological quantum computing. A key open challenge is whether electron-electron interactions can tune such topological superconducting phases. Here, we provide experimental signatures of a unique topological superconducting phase in competition with electronic correlations in 10-unit-cell thick FeTe x Se 1-x films grown on SrTiO 3 substrates. When the Te content x exceeds 0.7, we observe a topological transition marked by the emergence of a superconducting surface state. Near the FeTe limit, the system undergoes another transition where the surface state disappears, and superconductivity is suppressed. Theory suggests that electron-electron interactions in the odd-parity xy− band drives this second topological transition. The flattening and eventual decoherence of d xy -derived bands track the superconducting dome, linking correlation effects directly to superconducting coherent transport. Our work establishes many-body electronic correlations as a sensitive knob for tuning topology and superconductivity, offering a pathway to engineer new topological phases in correlated materials.

36 MATERIALS SCIENCE

Additive‐Free Oxidized Spiro‐MeOTAD Hole Transport Layer Significantly Improves Thermal Solar Cell Stability

Perovskite solar cells are among the most promising new solar technologies, already surpassing polycrystalline silicon solar cell efficiencies. The stability of the highest efficiency devices at elevated temperature is, however, poor. These cells typically use Spiro-MeOTAD as the hole transporting layer. It is generally believed that additives, required for enhancing electrical conductivity and optimizing energy level alignment, are responsible for the reduced stability—inferring that Spiro-MeOTAD based hole transporting layers are intrinsically unstable. Here, a reliable noble metal free synthesis of Spiro-MeOTAD (bis(trifluoromethane)sulfonimide) 4 is presented which is used as the oxidizing agent. No additives are added to the partially oxidized Spiro-MeOTAD hole-transporting layer. Device efficiencies up to 24.2% are achieved. Electrical conductivity is largely developed by the first 1% oxidation. Further oxidation shifts the energy levels away from the vacuum level, which allows tuning of the energy level alignment without the use of additives—contradicting the current understanding of this system. Without additives, devices demonstrate significant improvement in stability at elevated temperatures up to 85 °C under one sun over 1400 h continuous illumination. The remaining degradation is pinpointed to ion migration and reactions in the perovskite layer which may be further suppressed with compositional engineering and adequate ion barrier layers.

14 SOLAR ENERGY

Software Validation Work With The ZPPR-15 Data

The analysis activities for fast reactors involve using many different pieces of software that are relied upon for their predictive capabilities. For this software to be considered reliable, documented proof that the predictions of the software are accurate is required. In this manuscript, the validation work that covers some of the Argonne software used in fast reactor design activities is discussed and displayed. This validation work includes neutron and gamma flux distributions, reaction rate distributions, and reactivity worth. In an ideal world, a reactor development program would have access to a comprehensive set of experimental facilities to help inform the design aspects of the reactor itself. While thermal-hydraulics experiments, and to a limited degree mechanical experiments, can be carried out today for validation needs, neutronics related experimental facilities are rather impractical because of the lack of experimental facilities. Given the desired time table for construction of new reactors, the reconstitution or creation of new neutronic experimental facilities is untenable and thus those reactor development programs must rely upon any available experimental measurements that are qualitatively similar to the design. While a methodology has been proposed to assess the similarity between the past experimental measurements and the reactor itself, that aspect is beyond the scope of this manuscript. In this manuscript, the focus is entirely placed on the analysis results for a series of experiments carried out at the ZPPR facility in Idaho in the mid-1980s. In this regard, this manuscript only shows the validation of the stated neutronics software for specific loadings of the ZPPR reactor. Because of the fuel form, its proposed enrichment, and the material content of the reactor core, the ZPPR-15 experiments were identified as potential validation data for the reactor. The ZPPR-15 experiments were intended as mockups of a 330 MWe Integral Fast Reactor program which was a follow on program to the Clinch River Breeder Reactor. In the ZPPR-15 series of experiments, measurements of the neutron spectrum, control rod worth, sodium void worth, foil reaction rate distributions, Doppler worth of heated samples, gamma dose, and axial expansion worth were all carried out and published. In many cases, these reactivity coefficients are good candidates to validate the reactivity coefficient calculation scheme used by the analysis software and included in the safety analysis activities of fast reactor development projects today. This manuscript discusses the modeling methodology and accuracy of the calculated experimental results using the LANL software MCNP and the ANL software package ARC (Argonne Reactor Codes). As will be shown, for many of the experimental measurements, the two software packages are found to be good predictive analysis tools for those experiments. In other cases, problems with the analysis methodology or underlying cross section data are exposed which indicates where predictive analysis is not as reliable. Finally, in some of the measurements the conclusion is reached that the experimental measurement cannot be reproduced with the analysis software as it is simply too difficult.

Aliberti, Gerardo

Nitrene generation and transfer for unnatural biosynthesis in living cells

Abstract Synthetic biology has enabled the production of natural and unnatural products from inexpensive sustainable feedstocks. Yet, the scope of available products has been limited largely to compounds accessible from nature’s chemical reactions. Evolved enzymes can catalyse reactions of unnatural substrates or reactions not found in nature but often require the addition of synthetic reagents to purified enzymes or to resting cells containing those enzymes. Here we show that chemical reactions of metabolic intermediates produced intracellularly in living cells can include intermolecular nitrene transfers. The biosynthesis of N -acetoxyanilines, in combination with the generation and transfer of N -aryl nitrene intermediates from them catalysed by a cytochrome P450, generates amino alcohols, diamines, diarylamines and aminoalkyl arenes from simple carbon feedstocks. These products—common substructures of pharmaceuticals and agrochemicals—are challenging to synthesize by standard organic chemistry and were produced from inexpensive, renewable feedstocks. Evolution of the enzymes in this pathway showed that titres can be increased by engineering and that the products can be synthesized with high enantioselectivity.

Donnell, Isaac

Impact of hydrogenation on the stability and mechanical properties of amorphous boron nitride

Abstract Interconnect materials with ultralow dielectric constant, and good thermal and mechanical properties are crucial for the further miniaturization of electronic devices. Recently, it has been demonstrated that ultrathin amorphous boron nitride (aBN) films have a very low dielectric constant, high density (above 2.1 g cm −3 ), high thermal stability, and mechanical properties. The excellent properties of aBN derive from the nature and degree of disorder, which can be controlled at fabrication, allowing tuning of the physical properties for desired applications. Here, we report an improvement in the stability and mechanical properties of aBN upon hydrogen doping. With the introduction of a Gaussian approximation potential for atomistic simulations, we investigate the changing morphology of aBN with varying H doping concentrations. We found that for 8 at% of H doping, the concentration ofsp 3 -hybridized atoms reaches to a maximum which leads to an improvement of thermal stability and mechanical properties by 20%. These results will be a guideline for experimentalists and process engineers to tune the growth conditions of aBN films for numerous applications.

Materials Science