Monitoring eutectoid decomposition process of metastable phases in Al-Sm alloy via in-situ X-ray sca
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The transition to hydrogen as a green reductant in metal production is critical for decarbonizing the metallurgical industry, yet atomic-scale mechanisms governing reduction pathways and phase evolution remain unresolved. Using in-situ environmental transmission electron microscopy, we identify a hidden pathway that reveals dynamic formation of amorphous metallic iron (Fe) during the hydrogen-driven reduction of ferrous oxides of Fe 3 O 4 and FeO. Real-time imaging uncovers three coexisting transformation routes: (i) Fe 3 O 4 → FeO, (ii) Fe 3 O 4 → amorphous Fe, and (iii) FeO → amorphous Fe. The resulting amorphous Fe exhibits fluid-like mobility, enabling its rapid aggregation and crystallization into core-shell nanostructures, with a crystalline core enveloped by an amorphous shell. Complementary ab initio molecular dynamics simulations trace the amorphous Fe formation to interfacial strain at the metal/oxide interfaces, where large lattice mismatches destabilize the metal lattice during initial metallization. This interplay between thermodynamics and kinetics governs phase evolution: thermodynamics favors a self-limiting amorphous Fe overlayer, while rapid oxide reduction kinetics drives amorphous overgrowth. Our findings demonstrate that amorphous intermediates bypass rate-limiting crystalline steps, providing mechanistic insights to optimize H 2 -based processes for sustainable steelmaking. In conclusion, these insights bridge the gap between macroscopic process engineering and atomic-scale dynamics, with broader implications for catalysis and nanostructured material synthesis, where oxide reduction pathways critically shape functional phases and microstructures.
Abstract Ocean-based carbon dioxide (CO 2 ) removal (CDR) strategies are an important part of the portfolio of approaches needed to achieve negative greenhouse gas emissions. Many ocean-based CDR strategies rely on injecting CO 2 or organic carbon (that will eventually become CO 2 ) into the ocean interior, or enhancing the ocean’s biological pump. These approaches will not result in permanent sequestration, because ocean currents will eventually return the injected CO 2 back to the surface, where it will be brought into equilibrium with the atmosphere. Here, a model of steady state global ocean circulation and mixing is used to assess the time scales over which CO 2 injected in the ocean interior remains sequestered from the atmosphere. There will be a distribution of sequestration times for any single discharge location due to the infinite number of pathways connecting a location at depth with the sea surface. The resulting probability distribution is highly skewed with a long tail of very long transit times, making mean sequestration times much longer than typical time scales. Deeper discharge locations will sequester purposefully injected CO 2 much longer than shallower ones and median sequestration times are typically decades to centuries, and approach 1000 years in the deep North Pacific. Large differences in sequestration times occur both within and between the major ocean basins, with the Pacific and Indian basins generally having longer sequestration times than the Atlantic and Southern Oceans. Assessments made over a 50 year time horizon illustrates that most of the injected carbon will be retained for injection depths greater than 1000 m, with several geographic exceptions such as the Western North Atlantic. Ocean CDR strategies that increase upper ocean ecosystem productivity with the goal of exporting more carbon to depth will have mainly a short-term influence on atmospheric CO 2 levels because ∼70% will be transported back to the surface ocean within 50 years. The results presented here will help plan appropriate ocean CDR strategies that can help limit climate damage caused by fossil fuel CO 2 emissions.
A circular economy emphasizes the efficient use of all resources (e.g., materials, land, water). Despite anticipated overall benefits to society, the transition to a circular economy is likely to create regional differences in impacts. Current tools are unable to fully evaluate these potential externalities, which will be important for informing research prioritization and regional decision making. The Circular Economy Lifecycle Assessment and VIsualization (CELAVI) framework allows stakeholders to quantify and visualize potential regional and sectoral transfers of impacts that could result from transitioning to a circular economy, with particular focus on energy materials. The framework uses system dynamics to model material flows for multiple circular economy pathways and decisions are based on learning-by-doing and are implemented via cost and strategic value of different circular economy pathways. It uses network theory to track the spatial and sectoral flow of functional units across a graph and discrete event simulation to to step through time and evaluate lifecycle assessment data at each time step. The framework is designed to be flexible and scalable to accommodate multiple energy materials and multiple energy technologies. The primary goal of CELAVI is to help answer questions about how material flows and environmental and economic impacts of energy systems might change if the circularity of energy systems increases.
A circular economy emphasizes the efficient use of all resources (e.g., materials, land, water). Despite anticipated overall benefits to society, the transition to a circular economy is likely to create regional differences in impacts. Current tools are unable to fully evaluate these potential externalities, which will be important for informing research prioritization and regional decision making. The Circular Economy Lifecycle Assessment and VIsualization (CELAVI) framework allows stakeholders to quantify and visualize potential regional and sectoral transfers of impacts that could result from transitioning to a circular economy, with particular focus on energy materials. The framework uses system dynamics to model material flows for multiple circular economy pathways and decisions are based on learning-by-doing and are implemented via cost and strategic value of different circular economy pathways. It uses network theory to track the spatial and sectoral flow of functional units across a graph and discrete event simulation to to step through time and evaluate lifecycle assessment data at each time step. The framework is designed to be flexible and scalable to accommodate multiple energy materials and multiple energy technologies. The primary goal of CELAVI is to help answer questions about how material flows and environmental and economic impacts of energy systems might change if the circularity of energy systems increases.
The martensitic transformation is a fundamental physical phenomenon at the origin of important industrial applications. However, the underlying microscopic mechanism, which is of critical importance to explain the outstanding mechanical properties of martensitic materials, is still not fully understood. This is because for most martensitic materials the transformation is a fast process that makes in situ studies extremely challenging. Noble solids krypton and xenon undergo a progressive pressure-induced face-centered cubic (fcc) to hexagonal close-packed (hcp) martensitic transition with a very wide coexistence domain. Here, we took advantage of this unique feature to study the detailed transformation progress at the atomic level by employing in situ x-ray diffraction and absorption spectroscopy. We evidenced a four-stage pathway and suggest that the lattice mismatch between the fcc and hcp forms plays a key role in the generation of strain. We also determined precisely the effect of the transformation on the compression behavior of these materials.
Sea level rise drives spatial migration of coastal ecosystems and can lead to the accelerated replacement of coastal forests with tidal wetlands. Soil biogeochemical cycles in steady-state upland and wetland ecosystems are well studied, but pathways and rates in rapidly changing ecosystems are largely unconstrained. Wilson and Megonigal (2025) performed a one-time sampling and a subsequent incubation experiment, and characterized the reduction of reactive nitrogen (N) via denitrification and dissimilatory nitrate reduction to ammonia. Sampling was done at four sites where coastal deciduous forest is undergoing ecosystem state change and becoming wetland throughout the Chesapeake Bay, USA. The COMPASS-FME project (http://compass.pnnl.gov) established the sites sampled in this study in 2022–2023.This dataset consists of:* Isotope-labeled incubation results comparing nitrate reduction rates across transects spanning upland, transition, and wetland; and* Ancillary porewater chemistry data.All files in this dataset are plain text, comma-separated value (CSV), and no special software is required to read them.
The present study focuses on investigating the solubility of RuO 2 in a borosilicate-based model high-level waste glass and understanding its impact on the crystallization behavior and electrical conductivity of the resulting vitrified waste forms. The solubility limit of RuO 2 in the investigated glass composition has been determined to be 460 ppm by weight. The higher concentration of RuO 2 results in sub-micron sized Ru-rich inclusions in the glassy matrix, which eventually agglomerate to form needle-like and polyhedral RuO 2 crystals. It is observed that RuO 2 selectively promotes the crystallization of the rare-earth apatite phase over the powellite phase. The as-synthesized RuO 2 -containing glasses exhibit semiconducting behavior with a similar level of electrical conductivity below the glass transition. Here, the percolation of non-uniformly distributed RuO 2 inclusions may result in a formation of short-range low-resistive conduction pathways in the host glass matrix leading to an apparent metallic-like behavior of selected thin samples with the highest ruthenium content.
This study presents a one-pot synthesis route to organometallic nanofibers based on copper thiolate, exhibiting distinctive chemical and physical characteristics. Electron microscopy analysis of morphology and composition revealed 2-10 μm-long, 50-90 nm-diameter hollow and non-hollow fibers composed of copper, sulfur, oxygen, hydrocarbon, and chlorine. Thermogravimetric analysis showed a pronounced mass loss within 120°C-135°C. To elucidate the thermal responsive pathways, the nanofibers were characterized before and after heating. X-ray photoelectron spectroscopy indicates that an initially mixed Cu(I)/Cu(II) oxidation states transition to predominantly Cu(I) upon heating. A layer of nanofiber was coated on battery pouch foil and evaluated as a candidate thermally sensitive coating. At elevated temperature (100-130°C), nanofiber coating released volatile organic compounds, sulfide and sulfur dioxide as detected using multiple gas sensors. This thermally responsive gas release/sensing approach provides a potential large-area temperature monitoring strategy, which is particularly relevant where direct temperature measurements of individual batteries is impractical. The results established proof of concept for nanofiber-coated battery pouch foil as overtemperature warning platform that can provide alerts when surface temperatures exceed a critical threshold. More broadly, the ability to form interconnected fiber networks positions copper thiolate nanofiber coatings as promising materials for advanced applications.
Two-dimensional (2D) ultrathin (~0.5 nm) aluminosilicate bilayer films, consisting of hexagonal prisms (a.k.a. double 6-membered rings D6R) with acidic bridging hydroxyl groups exposed on the surface, have been previously synthesized on a Ru(0001) surface as a zeolite model system. These structures are helpful for mimicking zeolite catalysts with D6R building blocks, such as chabazite. We performed density functional theory calculations to investigate the monomolecular cracking and dehydrogenation of n-butane molecules over the acidic hydroxyl groups of the 2D model system and compared the reaction energetics with that in bulk chabazite. The intrinsic activation energy barrier is the highest for dehydrogenation and lowest for central C–C bond cracking in bulk chabazite. The trend of intrinsic energy barriers for dehydrogenation and terminal and central C–C bond cracking is reproduced on the 2D aluminosilicate film. Overall, the activation barriers are higher on the 2D film than in bulk chabazite due to the lack of confinement in the former. We further explored the effects of the zeolite channel size on the n-butane adsorption and monomolecular cracking using different bulk nanoporous zeolite frameworks (TON, MEL, MEI, and VFI). We found that as the confinement of channels decreases, n-butane adsorption becomes weaker, and the intrinsic energy barrier of terminal C–C cracking increases. The activation energy barriers (dehydrogenation and terminal and central C–C cracking) on the 2D bilayer film surface, which may be considered as zeolite cages at the infinite cage size limit, are close to that in VFI with a relatively large channel size. Comparing the reaction pathway of n-butane terminal C–C cracking in 3D nanocages and on the surface of the 2D aluminosilicate film revealed that stabilizing the transition states in the 3D nanocages is responsible for the decrease in the intrinsic energy barriers for bulk zeolites.
The encapsulation phenomenon associated with strong metal-support interaction (SMSI) has been largely restricted to catalyst systems consisting of group VIII metals with high surface energy and reducible transition metal oxide supports with low surface energy. Here, we demonstrate an encapsulation phenomenon that, while sharing morphological similarities with conventional SMSI, follows a distinctive pathway. This is shown by the encapsulation of CuAu nanoparticles (NPs) supported on highly ordered pyrolytic graphite (HOPG). Through dynamic monitoring of Cu, Au, and Cu 50 Au 50 NPs in an oxidizing atmosphere using ambient-pressure X-ray photoelectron spectroscopy, we show that this spontaneous encapsulation is achieved through the synergistic effect of the alloying elements. Specifically, the surface segregation of Cu promotes dissociative O 2 adsorption, leading to the formation of atomic O species, while the subsurface enrichment of Au hinders O incorporation into the bulk of CuAu NPs. Consequently, O spillover onto the graphite support occurs, resulting in the oxidation of the HOPG surface into graphitic oxide species. The higher affinity of the graphitic oxide species toward the Cu-segregated surface prompts their migration from the HOPG support to encapsulate the CuAu NPs. Finally, these results transcend the conventional SMSI and bear practical implications for the design and development of heterogeneous catalysts, particularly in carbon-supported alloy systems.
Abstract The G protein-coupled metabotropic glutamate receptors form homodimers and heterodimers with highly diverse responses to glutamate and varying physiological functions. We employ molecular dynamics, single-molecule spectroscopy and hydrogen–deuterium exchange to dissect the activation pathway triggered by glutamate. We find that activation entails multiple loosely coupled steps, including formation of an agonist-bound, pre-active intermediate whose transition to active conformations forms dimerization interface contacts that set efficacy. The agonist-bound receptor populates at least two additional intermediates en route to G protein-coupling conformations. Sequential transitions into these states act as ‘gates’, which attenuate the effects of glutamate. Thus, the agonist-bound receptor is remarkably dynamic, with low occupancy of G protein-coupling conformations, providing considerable headroom for modulation by allosteric ligands. Sequence variation within the dimerization interface, as well as altered conformational coupling in receptor heterodimers, may contribute to precise decoding of glutamate signals over broad spatial and temporal scales.
Nonequilibrium hidden states provide a unique window into thermally inaccessible regimes of strong coupling between microscopic degrees of freedom in quantum materials. Understanding the origin of these states allows the exploration of far-from-equilibrium thermodynamics and the development of optoelectronic devices with on-demand photoresponses. However, mapping the ultrafast formation of a long-lived hidden phase remains a longstanding challenge since the initial state is not recovered rapidly. Here, using state-of-the-art single-shot spectroscopy techniques, we present a direct ultrafast visualization of the photoinduced phase transition to both transient and long-lived hidden states in an electronic crystal, 1T-TaS 2 , and demonstrate a commonality in their microscopic pathways, driven by the collapse of charge order. We present a theory of fluctuation-dominated process that helps explain the nature of the metastable state. Our results shed light on the origin of this elusive state and pave the way for the discovery of other exotic phases of matter.
This analysis takes an integrated, innovative approach to develop plausible, high-ambition pathways through 2035 to inform the third U.S. NDC target setting. This approach combines: (1) an extensive consultation and engagement process with a broad set of federal and subnational stakeholders to build a robust U.S. policy platform; and (2) an open-source, field-leading integrated assessment model focused on the U.S. containing subnational details. The modeling tool assesses existing and possible new policies from both federal and subnational levels to assess the overall emissions reduction potential and the policy pathways to deliver the ambition needed for 2035 and leading on to 2050. In addition, we highlight how different actors can contribute to the needed transition in each sector and showcase successful implementation stories by various subnational actors.
Transport accounts for 24% of global CO 2 emissions from fossil fuels. Governments face challenges in developing feasible and equitable mitigation strategies to reduce energy consumption and manage the transition to low-carbon transport systems. To meet the local and global transport emission reduction targets, policymakers need more realistic/sophisticated future projections of transport demand to better understand the speed and depth of the actions required to mitigate greenhouse gas emissions. In this paper, we argue that the lack of access to high-quality data on the current and historical travel demand and interdisciplinary research hinders transport planning and sustainable transitions toward low-carbon transport futures. We call for a greater interdisciplinary collaboration agenda across open data, data science, behaviour modelling, and policy analysis. These advancemets can reduce some of the major uncertainties and contribute to evidence-based solutions toward improving the sustainability performance of future transport systems. The paper also points to some needed efforts and directions to provide robust insights to policymakers. We provide examples of how these efforts could benefit from the International Transport Energy Modeling Open Data project and open science interdisciplinary collaborations.
The broad host range of Fusarium virguliforme represents a unique comparative system to identify and define differentially induced responses between an asymptomatic monocot host, maize (Zea mays), and a symptomatic eudicot host, soybean (Glycine max). Using a temporal, comparative transcriptome-based approach, we observed that early gene expression profiles of root tissue from infected maize suggest that pathogen tolerance coincides with the rapid induction of senescence dampening transcriptional regulators, including ANACs (Arabidopsis thaliana NAM/ATAF/CUC protein) and Ethylene-Responsive Factors. In contrast, the expression of senescence-associated processes in soybean was coincident with the appearance of disease symptom development, suggesting pathogen-induced senescence as a key pathway driving pathogen susceptibility in soybean. Based on the analyses described herein, we posit that root senescence is a primary contributing factor underlying colonization and disease progression in symptomatic versus asymptomatic host–fungal interactions. This process also supports the lifestyle and virulence of F. virguliforme during biotrophy to necrotrophy transitions. Further support for this hypothesis lies in comprehensive co-expression and comparative transcriptome analyses, and in total, supports the emerging concept of necrotrophy-activated senescence. We propose that F. virguliforme conditions an environment within symptomatic hosts, which favors susceptibility through transcriptomic reprogramming, and as described herein, the induction of pathways associated with senescence during the necrotrophic stage of fungal development.
Here, a novel allylic 1,6 hydrogen-atom-transfer mechanism is established through infrared activation of the 2-butenal oxide Criegee intermediate, resulting in very rapid unimolecular decay to hydroxyl (OH) radical products. A new precursor, Z/E -1,3-diiodobut-1-ene, is synthesized and photolyzed in the presence of oxygen to generate anew four-carbon Criegee intermediate with extended conjugation across the vinyl and carbonyl oxide groups that facilitates rapid allylic 1,6 H-atom transfer. A low-energy reaction pathway involving isomerization of 2-butenal oxide from a lower-energy ( tZZ ) conformer to a higher-energy ( cZZ ) conformer followed by 1,6 hydrogen transfer via a seven-membered ring transition state is predicted theoretically and shown experimentally to yield OH products. The low-lying ( tZZ ) conformer of 2-butenaloxide is identified based on computed an harmonic frequencies and intensities of its conformers. Experimental IR action spectra recorded in the fundamental CH stretch region with OH product detection by UV laser-induced fluorescence reveal a distinctive IR transition of the low-lying ( tZZ ) conformer at 2996 cm -1 that results in rapid unimolecular decay to OH products. Statistical RRKM calculations involving a combination of conformational isomerization and unimolecular decay via 1,6 H-transfer yield an effective decay rate k eff ( E ) on the order of 10 8 s -1 at ca. 3000 cm -1 in good accord with the experiment. Unimolecular decay proceeds with significant enhancement due to quantum mechanical tunneling. A rapid thermal decay rate of ca. 10 6 s -1 is predicted by master-equation modeling of 2-butenal oxide at 298 K, 1 bar. This novel unimolecular decay pathway is expected to increase the nonphotolytic production of OH radicals upon alkene ozonolysis in the troposphere.
Abstract. The pathways and timing of drainage from the inundated centers of ice-wedge polygons in a warming climate have important implications for carbon flushing, advective heat transport, and transitions from methane to carbon dioxide dominated emissions. Here, we expand on previous research using a recently developed analytical model of drainage from a low-centered polygon. Specifically, we perform (1) a calibration to field data identifying necessary model refinements and (2) a rigorous model sensitivity analysis that expands on previously published indications of polygon drainage characteristics. This research provides intuition on inundated polygon drainage by presenting the first in-depth analysis of drainage within a polygon based on hydrogeological first principles. We verify a recently developed analytical solution of polygon drainage through a calibration to a season of field measurements. Due to the parsimony of the model, providing the potential that it could fail, we identify the minimum necessary refinements that allow the model to match water levels measured in a low-centered polygon. We find that (1) the measured precipitation must be increased by a factor of around 2.2, and (2) the vertical soil hydraulic conductivity must decrease with increasing thaw depth. Model refinement (1) accounts for runoff from rims into the ice-wedge polygon pond during precipitation events and possible rain gauge undercatch, while refinement (2) accounts for the decreasing permeability of deeper soil layers. The calibration to field measurements supports the validity of the model, indicating that it is able to represent ice-wedge polygon drainage dynamics. We then use the analytical solution in non-dimensional form to provide a baseline for the effects of polygon aspect ratios (radius to thaw depth) and coefficient of hydraulic conductivity anisotropy (horizontal to vertical hydraulic conductivity) on drainage pathways and temporal depletion of ponded water from inundated ice-wedge polygon centers. By varying the polygon aspect ratio, we evaluate the relative effect of polygon size (width), inter-annual increases in active-layer thickness, and seasonal increases in thaw depth on drainage. The results of our sensitivity analysis rigorously confirm a previous analysis indicating that most drainage through the active layer occurs along an annular region of the polygon center near the rims. This has important implications for transport of nutrients (such as dissolved organic carbon) and advection of heat towards ice-wedge tops. We also provide a comprehensive investigation of the effect of polygon aspect ratio and anisotropy on drainage timing and patterns, expanding on previously published research. Our results indicate that polygons with large aspect ratios and high anisotropy will have the most distributed drainage, while polygons with large aspect ratios and low anisotropy will have their drainage most focused near their periphery and will drain most slowly. Polygons with small aspect ratios and high anisotropy will drain most quickly. These results, based on parametric investigation of idealized scenarios, provide a baseline for further research considering the geometric and hydraulic complexities of ice-wedge polygons.