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376 records · Page 5

Lepto-axiogenesis with light right-handed neutrinos

We study lepto-axiogenesis in theories where the right-handed neutrino is light enough that its dynamics affect the determination of the baryon asymmetry. When compared with theories of high-scale lepto-axiogenesis where the Majorana neutrino mass may be treated as an effective dimension-five operator, we find that the predicted saxion mass is lower. Two distinct scenarios emerge. In the first, processes that generate the baryon asymmetry are in equilibrium down to the mass of the right-handed neutrino. In the second, the relevant processes never reach equilibrium; the baryon number freezes in. We comment on implications for supersymmetric spectra and discuss constraints on late decays of supersymmetric relics and from dark radiation. In contrast to high-scale lepto-axiogenesis, which predicts superpartners with masses of 10–100 TeV or more, we find this scenario is consistent with a wider range of superpartner masses, all the way down to current direct search bounds.

Axions and ALPs

Dynamic Diketoenamine Crosslinking Unlocks Vinyl Polymer Vitrimers From β ‐Triketone Chemistry

Covalent adaptable networks (CANs) offer a compelling strategy to unite the mechanical robustness of thermosets with the reprocessability of thermoplastics, yet achieving simultaneous durability, processability, and true recyclability remains challenging. We introduce diketoenamine (DKE) vitrimers derived from β-triketone methacrylate monomers and demonstrate how rational monomer design dictates network processability, viscoelasticity, and recyclability. By systematically varying the spacer length between the β-triketone (TK) moiety and the polymer backbone, we identify a key structure–property relationship that dictates vitrimer behavior. Networks bearing TK pendants minimally displaced from the backbone suppress creep but exhibit limited stress relaxation, whereas extended spacers yield lower glass transition temperatures, higher effective crosslink densities, and efficient stress dissipation, enabling optical transparency and reprocessability. Extending this platform to ultra-high molecular-weight prepolymers introduces physical entanglements as secondary crosslinks, further enhancing dimensional stability without compromising processability. Both mechanical and chemical recycling validate the closed-loop circularity of these materials. Furthermore, these results establish TK methacrylates as a versatile platform for designing high-performance vitrimers that integrate durability, reprocessability, and true closed-loop recyclability.

closed-loop recyclability

Coalition for Community-Supported Affordable Geothermal Energy Systems (C2SAGES)

The C2SAGES project evaluated the feasibility of a community geothermal system for the planned Windy Ridge affordable housing development in Hinesburg, Vermont. Led by GTI Energy with Vermont Gas Systems, LN Consulting, NREL, and Frontier Energy, the work assessed technical design, energy performance, costs, business models, community engagement, maintenance, workforce development, and permitting. The proposed system was designed to serve 100% of the development’s heating, cooling, and domestic hot water loads. Compared with a baseline using air-source heat pumps and natural gas water heating, the geothermal system was estimated to reduce HVAC and domestic hot water energy use by about 45% to 48%, lower operating and maintenance costs, and reduce 30-year life-cycle costs by 37% for Phase 1 and 10% for Phase 2. Technical testing and modeling indicated that the Windy Ridge site is suitable for a community-scale geothermal system. The project also developed borehole field layouts, piping concepts, pump house designs, controls, maintenance plans, and supporting engineering drawings. The business model analysis found that first cost, ownership structure, and customer affordability remain major deployment challenges. Utility-led maintenance and operation were viewed favorably, but traditional utility cost-recovery models may require subsidy or revised financing structures to be practical for affordable housing. Community engagement highlighted the need for clear public education, transparent financing, reliable long-term maintenance, trained technicians, and the potential to pair geothermal systems with weatherization. Overall, the report concludes that community geothermal is technically feasible and offers meaningful energy, emissions, and life-cycle cost benefits, but broader deployment will depend on workable financing models and workforce readiness.

15 GEOTHERMAL ENERGY

From zonal to nodal capacity expansion planning: Spatial aggregation impacts on a realistic test-case

Solving power system capacity expansion planning (CEP) problems at realistic spatial resolutions is computationally challenging. Thus, a common practice is to solve CEP over zonal models with low spatial resolution rather than over full-scale nodal power networks. Due to improvements in solving large-scale stochastic mixed integer programs, these computational limitations are becoming less relevant, and the assumption that zonal models are realistic and useful approximations of nodal CEP is worth revisiting. Here, this work is the first to conduct a systematic computational study on the assumption that spatial aggregation can reasonably be used for ISO-scale CEP. By considering a realistic, large-scale test network based on the state of California with over 8000 buses, we find that well-designed small spatial aggregations can yield good approximations but that coarser zonal models may result in large distortions of investment decisions, e.g., capacity under-investment of up to 41% for the lowest resolution model considered.

24 POWER TRANSMISSION AND DISTRIBUTION

Frontier Job-Centric Telemetry Dataset

Comprehensive analysis of high-performance computing (HPC) systems requires linking workload execution to system behavior. This kind of analysis is vital for diagnosing performance issues, managing capacity, detecting anomalous workloads, and understanding how applications interact with system hardware. This job-centric telemetry dataset unifies scheduler job records with node-level measurements, enabling direct association between workloads and their corresponding power, thermal, and performance characteristics. It contains sanitized, scheduler related metadata for 152,400 individual jobs that ran on the Frontier supercomputer and ended on selected days throughout 2024 and 2025, a subpopulation of ~6.8% of the total number of allocated jobs with non-zero run time on the system over that same period. Each is linked with files that contain telemetry time series records of the power utilization and temperature behavior of its allocated nodes and their processors during the run time of the job. Where available, a portion of the job files also contain network performance time series. Jobs are sampled from select days that reflect normal levels of user activity and possess job size distributions with large numbers of leadership class jobs (>20% of Frontier nodes). Jobs in this dataset attempt to best represent successful user workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

The phase diagram of quantum chromodynamics in one dimension on a quantum computer

The quantum chromodynamics (QCD) phase diagram, which reveals the state of strongly interacting matter at different temperatures and densities, is key to answering open questions in physics, ranging from the behaviour of particles in neutron stars to the conditions of the early universe. However, classical simulations of QCD face significant computational barriers, such as the sign problem at finite matter densities. Quantum computing offers a promising solution to overcome these challenges. Here, we take an important step toward exploring the QCD phase diagram with quantum devices by preparing thermal states in one-dimensional non-Abelian gauge theories. We experimentally simulate the thermal states of SU(2) and SU(3) gauge theories at finite densities on a trapped-ion quantum computer using a variational method. This is achieved by introducing two features: Firstly, we add motional ancillae to the existing qubit register to efficiently prepare thermal probability distributions. Secondly, we introduce charge-singlet measurements to enforce colour-neutrality constraints. This work pioneers the quantum simulation of QCD at finite density and temperature for two and three colours, laying the foundation to explore QCD phenomena on quantum platforms.

Quantum information

Effects of Composition and Oxidation States on the Structures of Chromium-Containing Sodium Silicate Glasses: Molecular Dynamics Simulations using Machine Learning Interatomic Potentials

Chromium represents a significant challenge for the vitrification of high-level nuclear waste into silicate and borosilicate glasses due to its low solubility and variable oxidation states, which can limit the waste loading due to promotion of crystallization or phase separation during processing. In this study, we modeled chromium containing silicate glasses using molecular dynamics simulations with three machine learning interatomic potentials (MLIPs), MACE, CHGNet, and PFP were employed, to gain insights on glass composition and oxidation states on the structures of these glasses. One of the goals is to evaluate their ability of these MLIPs to accurately represent the general structure of silicate glasses and chromium local environments as a function of chromium oxidation states. Density Functional Theory (DFT) based calculations and experimental data such as neutron structure factors were used to validate the structural models. It was found that the foundation models of all three MLIPs are able to reproduce general structural features of the sodium silicate glass structure consistent with experimental and DFT data, but only CHGNet and PFP can accurately capture the oxidation states and local environment of chromium: tetrahedral for Cr6+ and octahedral for Cr3+. Furthermore, we studied the effect of varying Cr3+/ Cr6+ (Cr3+/Crtotal) ratio and total chromium content using PFP. Our results show that Cr6+ enhances network polymerization by reducing non-bridging oxygens through Na? charge compensation required due to the formation of chromate (CrO42-) species, while Cr³? acts as a network modifier that disrupts connectivity. System size effects on the structural characteristics and chromium environments were also tested using the PFP potential. This work highlights the importance of careful validation on the precision, transferability, and potential of MLIPs for modeling glasses containing transition metal elements that can exist in multiple oxidation states. It is also encouraging to see the foundational models are all three MLFFs are able to reproduce the basic sodium silicate glass structures, while suggesting additional training or refining is needed to improve the description of more complex systems containing transition metals.

Puga, Christina L.

Nuclear Safety [Vol. 32, No. 1, January-March 1991]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 1 The Safety Review and Approval Process for Space Nuclear Power Sources, G. L. Bennett; 19 Report on the American Nuclear Society International Topical Meeting: "The Safety, Status, and Future of Non-Commercial Reactors and Irradiation Facilities", E. G. Silver; 35 Book Review: Fission Product Transport Processes in Reactor Accidents, Proceedings to the International Centre tor Heat and Mass Processes T. S. Kress; 38 Fast Reactor Technology in the 1990s: A Summary of the 1990 International Fast Reactor Safety Meeting, A. E. Levin; ACCIDENT ANALYSIS: 56 Effects of Chemical Phenomena on LWR Severe Accident Fission Product Behavior, A. P. Malinauskas and T. S. Kress; CONTROL AND INSTRUMENTATION: 65 Technical Note: Safety Parameter Display Systems—10 Years Later, R. J. Eckenrode; 68 Potential Application of Neural Networks to the Operation of Nuclear Power Plants, R. E. Uhrig; DESIGN FEATURES: 80 Twenty-First DOE/NRC Nuclear Air-Cleaning Conference, R. R. Bellamy, D. W. Moeller, and M. W. First; 91 Impact of an Apparent Radiation Embrittlement Rate on the Life Expectancy of PWR Vessel Supports, R. D. Cheverton, G. C. Robinson, W. E. Pennell, and R. K. Nanstad; ENVIRONMENTAL EFFECTS: 103 Technical Note: The Impact of Offsite Factors on the Safety Performance of Small Nuclear Power Plants, Yu. D. Baranaev and A. N. Viktorov; WASTE AND SPENT FUEL MANAGEMENT: 109 Activities Related to Waste Management, Compiled by E. G. Silver; OPERATING EXPERIENCES: 118 Reactor Shutdown Experience, Compiled by J. W. Cletcher; 121 Selected Safety-Related Events, Compiled by G. A. Murphy; 123 Operating U.S. Power Reactors, Compiled by E. G. Silver; RECENT DEVELOPMENTS: 140 General Administrative Activities, Compiled by E. G. Silver; 150 Reports, Standards, and Safety Guides, D. S. Queener; 155 Status of Power-Reactor Licensing Activities, Compiled by E. G. Silver; 157 Proposed Rule Changes as of Sept. 30, 1990; ANNOUNCEMENTS: 79 MIT Offers Summer Program on Nuclear Power Reactor Safety; 108 Harvard School of Public Health Offers Several Short Courses; 139 Short Course and Workshop on Nuclear Criticality Safety at University of New Mexico; 160 SCK/CEN Announces Training Course on Emergency Planning and Response; 161 The Authors; 164 Indexes to Nuclear Safety, Volume 31

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Photophysical and Time‐resolved Infrared Properties of Long‐Lived Rhenium(I) 4,5‐Diazafluorene Tricarbonyl Chromophores

This report investigates the synthesis, structural characterization, fundamental molecular photophysics, electrochemistry, UV-Vis spectroelectrochemistry, and time-resolved infrared spectroscopic properties of eight [fac-Re(dafR)(CO) 3 L] 0/+ complexes, where R=ethyl [(dedaf); 1, 3, 5, 7] or H [(dafH); 2, 4, 6, 8] and L=Cl− (1, 2), imidazole [(Im); 3, 4], 4-ethylpyridine [(4-Etpy); 5, 6], or pyridine [(py); 7, 8]. Universally, 1–8 yield higher energy photoluminescence (PL) emission bands and higher PL quantum yields (up to 53 %) than the classic 2,2’-bipyridine (bpy) and 1,10-phenanthroline (phen) ligated Re(I) tricarbonyl complexes. The excited state lifetimes of 1–8 lie between those corresponding to the bpy and phen derivatives, ranging from 120 and 1300 ns at room temperature. Combinations of reductive UV-Vis spectroelectrochemistry, transient absorption spectroscopy, and time-resolved infrared spectroscopy consistently assigned the lowest excited states in 1–8 being of metal-to-ligand charge transfer (MLCT) character. These new ReI MLCT chromophores follow classic energy gap law behavior and possess the characteristics necessary for serving as valuable photosensitizers suitable to energize excited state electron and energy transfer photochemistry.

Charge transfer

DESI Strong Lens Foundry. III. Keck Spectroscopy for Strong Lenses Discovered Using Residual Neural Networks

We present spectroscopic data of strong lenses and their source galaxies using the Keck Near-Infrared Echellette Spectrometer (NIRES) and the Dark Energy Spectroscopic Instrument (DESI), providing redshifts necessary for nearly all strong-lensing applications with these systems, especially the extraction of physical parameters from lensing modeling. These strong lenses were found in the DESI Legacy Imaging Surveys using residual neural networks and followed up by our Hubble Space Telescope program, with all systems displaying unambiguous lensed arcs. With NIRES, we target eight lensed sources at redshifts difficult to measure in the optical range and determine the source redshifts for six, between z s = 1.675 and 3.332. DESI observed one of the remaining source redshifts, as well as an additional source redshift within the six systems. The two systems with nondetections by NIRES were observed for a considerably shorter 600 s at high airmass. Combining NIRES infrared spectroscopy with optical spectroscopy from our DESI Strong Lensing Secondary Target Program, these results provide the complete lens and source redshifts for six systems, a resource for refining automated strong lens searches in future deep- and wide-field imaging surveys and addressing a range of questions in astrophysics and cosmology.

Agarwal, Shrihan [University of Chicago, IL (Unite

An attention-based neural ordinary differential equation framework for modeling inelastic processes

To preserve strictly conservative behavior as well as model the variety of dissipative behavior displayed by solid materials, we propose a significant enhancement to the internal state variable-neural ordinary differential equation (ISV-NODE) framework. In this data-driven, physics-constrained modeling framework internal states are inferred rather than prescribed. The ISV-NODE consists of: (a) a stress model dependent on observable deformation and inferred internal state, and (b) a model of the evolution of the internal states. The enhancements to ISV-NODE proposed in this work are multifold: (a) a partially input convex neural network stress potential provides polyconvexity in terms of observed strain while leaving the inferred state unconstrained, and (b) an internal state flow model uses common latent features to inform novel attention-based gating and drives the flow of internal state only in dissipative regimes. We demonstrated that this architecture can accurately model dissipative and conservative behavior across an isotropic, isothermal elastic-viscoelastic-elastoplastic spectrum with three exemplars, while maintaining fundamental principles by design.

97 MATHEMATICS AND COMPUTING

Generative learning of densities on manifolds

A generative modeling framework is proposed that combines diffusion models and manifold learning to efficiently sample data densities on manifolds. The approach utilizes Diffusion Maps to uncover possible low-dimensional underlying (latent) spaces in the high-dimensional data (ambient) space. Two approaches for sampling from the latent data density are described. The first is a score-based diffusion model, which is trained to map a standard normal distribution to the latent data distribution using a neural network. The second one involves solving an Itô stochastic differential equation in the latent space. Additional realizations of the data are generated by lifting the samples back to the ambient space using Double Diffusion Maps , a recently introduced technique typically employed in studying dynamical system reduction; here the focus lies in sampling densities rather than system dynamics. The proposed approaches enable sampling high dimensional data densities restricted to low-dimensional, a priori unknown manifolds. The efficacy of the proposed framework is demonstrated through a benchmark problem and a material with multiscale structure.

Double diffusion maps

Thermal Reservoir Networks for Modularly Expandable Thermal Microgrids

The Department of Defense (DoD) faces the substantial challenge of cost-effectively retrofitting one to two installations per month, each comprising approximately 1,000 buildings, to improve resilience, reduce energy consumption, and enhance energy supply security. Achieving these objectives requires optimal system selection and effective risk mitigation during system integration. To address this need, we introduce Platform-Based Design (PBD), a structured, hierarchical methodology adapted from other industrial sectors to the domain of energy system retrofits. We demonstrate the effectiveness of PBD through a techno-economic feasibility study comparing geothermal-coupled thermal energy networks (TENs) with conventional energy systems for heating, cooling, and powering 17 buildings at Joint Base Andrews (JBA) in Maryland. Our analysis illustrates that the PBD approach enables rigorous, data-driven, sequential decision making, resulting in a family of Pareto-optimal systems, among which the TEN emerged as the most promising solution. The selected TEN design integrates geothermal borefields, heat recovery heat pumps, photovoltaic (PV) arrays, and battery storage. Compared to the baseline system – gas heating combined with air-source chillers – the proposed TEN reduces annual imported energy by 74% and peak electricity demand by 45%, achieves a levelized cost of energy of $\$0.210$/kWh, and substantially enhances resilience. Life-cycle costs increase by approximately 6%, and initial investment costs are about 2.5 times higher than the baseline. However, if central plant infrastructure, district loops, and utility-scale PV and battery systems are privately funded and operated, the initial investment would fall below the baseline system cost. Critical to achieving these significant performance improvements were detailed nonlinear dynamic simulations coupling geothermal heat transfer, energy system operation, and realistic feedback control logic. These simulations identified essential design modifications and control strategy refinements that substantially reduced energy use, peak demand, and compressor shortcycling, thereby improving durability and reliability—issues that would have been significantly more expensive to resolve during operation. Additionally, the verification step highlighted sensitivities to key design parameters that could reduce initial investment by approximately $\$2$ million and reduce annual life-cycle costs more than $\$300,000$. We recommend adopting the PBD methodology for future feasibility studies and TEN pilot projects to gain valuable operational experience. Furthermore, we recommend that DoD invest in transferring and scaling the PBD methodology to other installations. This entails developing standardized computational frameworks and component libraries as well as training industry in conducting PBD. Such investments would enable rapid, robust, reliable, and cost-effective retrofits, supporting DoD’s ambitious energy system modernization goals.

Wetter, Michael [Lawrence Berkeley National Labora

Lunar accelerometer network gravitational observatory (LANGO)

With ground-based interferometers detecting hundreds of gravitational-wave (GW) events, GW astronomy has continued to blossom. U.S. and European scientists are developing plans to construct third-generation ground-based interferometers. ESA has proceeded through the mission formulation phase of space-based interferometer in a lower-frequency band, 10 –4 –0.1 Hz. Despite all these exciting developments, there is still a missing frequency band, 0.1–10 Hz. This mid-frequency band is rich with interesting astrophysical events. Coalescence and merger of intermediate-mass black holes (IMBHs) will occur in this frequency band. Coalescing stellar-mass BHs will pass through this frequency band days before they reach the frequency band of LIGO and Virgo. Detection of such signals would enable a mid-frequency detector to issue an advance notice to the high-frequency GW detectors, as well as to optical, x-ray and γ-ray telescopes. We propose Lunar Accelerometer Network Gravitational Observatory (LANGO) to detect GWs in this frequency band. In the first phase (LANGO 1), we propose to deploy four ambient-temperature (250 K) accelerometers in the tetrahedral or in a square configuration on the hemisphere facing the Earth. After successful operation at 250 K, LANGO would be upgraded to a cryogenic (4 K) version with over two orders of magnitude increased sensitivity (LANGO 2), with coherent rejection of seismic noise implemented. LANGO is a full-tensor detector, capable of determining the source direction and wave polarization. Each test mass (TM) is suspended as a pendulum with resonance frequency ∼ 0.01 Hz, thus is only weakly coupled to the lunar surface horizontally. LANGO is designed to detect the relative motion of globally separated, nearly free, TMs by using the Moon as a large quiet platform. LANGO 1 and 2 accelerometers aim at sensitivities ⩽ 10 –11 m s –2 Hz –1/2 and ⩽ 10 –13 m s –2 Hz –1/2 in the horizontal axes over the frequency band of 1 mHz–10 Hz, which yield GW sensitivities 1.1 x 10 -21 Hz -1/2 and 3.8 x 10 -24 Hz -1/2 at 1 Hz, respectively. The LANGO accelerometers will be 10 3 –10 5 times more sensitive than Apollo seismometers. With such sensitivity, LANGO will also make great contribution to the advancement of lunar geophysics.

79 ASTRONOMY AND ASTROPHYSICS

Correlated Ion Transport Governed by Dynamic Local Structure in High Concentration and Localized High Concentration Electrolytes

Understanding the dynamics of cluster formation and network percolation provides the mechanistic link between microscopic solvation structure and transport in concentrated electrolytes, including localized high-concentration electrolytes (LHCEs). Although recent studies have shown LHCEs to form micelle-like aggregates at specific compositions, a quantitative understanding of how solvation structures and transport properties depend on salt–solvent–diluent ratios remains limited. Here, we integrate molecular dynamics with Onsager transport analyses to chart the evolution of solvation microstructure and associated ionic transport in LiFSI/DMC/TTE, achieving good agreement with experimental conductivities across composition. We show that micelle formation arises from a dynamic instability of the cation–anion network, and that network percolation is the primary determinant of conductivity. Two compositional thresholds emerge: A critical network concentration (CNC) and a critical micelle concentration (CMC) that delineate transitions from extended percolating networks to micelle-like clusters and then to fragments. These structural transitions rationalize the nonintuitive conductivity decrease at intermediate dilution despite monotonically decreasing viscosity and provide composition-level design rules for LHCEs.

Mohanakrishnan, Rohith Srinivaas [University of Ca

Visualizing Crystallization Dynamics and Transformation Pathways of Disordered Rocksalt Oxides During Thermally Activated Sol–Gel Synthesis

Sol–gel synthesis is a wet-chemical processing route for fabricating functional materials with control over composition and microstructure at relatively low temperatures compared to conventional solid-state synthesis. While sol–gel process initiates with intermixed molecular precursors, the early-stage nucleation pathways are insufficiently understood. Here, in this study, the chemical and structural transformation of ion disordered rocksalt (DRX) Li 1.2 Mn 0.4 Ti 0.4 O 2 (LMTO), a promising cathode material for lithium batteries, is studied by multiscale characterizations. In situ heating transmission electron microscopy (TEM) using a liquid cell visualizes and identifies crystallization pathways at the nanoscale. While some regions follow a classical multi-step transition through thermodynamically stable intermediates, others exhibit a kinetic shortcut via a localized amorphous matrix to directly form the DRX structure. Macroscale Fourier transform infrared spectroscopy corroborates the findings and reveals that transition metal ions are more strongly incorporated into the acetate-coordinated network than lithium. Although in situ heating TEM captures diverse local transformation pathways, in situ synchrotron X-ray diffraction indicates that the macroscopic transformation proceeds predominantly through spinel LMTO and lithium titanates toward DRX-LMTO. The findings uncover the spatiotemporal chemical and structural transformations in sol–gel derived DRX-LMTO materials, and call for fine-tuning of such sol–gel chemistries to manipulate the crystallization pathways and achieve target material homogeneity more efficiently.

cathode material

The impact of metastability on the high-pressure behavior of cerium

The structures adopted by solids under pressure are often assumed to reflect thermodynamic equilibrium, yet in many materials phase selection is strongly influenced by kinetic pathways and microstructural inheritance. Elemental cerium (Ce) exemplifies this challenge, with decades of conflicting reports describing different high-pressure crystal structures emerging under nominally identical conditions. Here we use neutron diffraction from large ( ~ 60 mm 3 ) sample volumes to follow the structural evolution in ultra-high-purity Ce during controlled pressure-temperature cycling between 85 and 295 K and up to 8 GPa. We find that the crystal structure formed at high pressure depends on the compression pathway: slow compression ( ~ 0.25 GPa hr −1 ) at room temperature favors an orthorhombic phase (α'), whereas slow ( ~ 0.25 GPa hr −1 ) and also moderately faster ( ~ 0.5 GPa hr −1 ) compression at low temperature stabilizes a pure monoclinic phase (α"). The low-temperature phase persists metastably over a wide temperature range but transforms irreversibly upon heating above ~ 280 K, or modest pressure cycling. Remarkably, the lower-pressure γ phase remains trapped far beyond the expected stability field, persisting to the highest pressures studied. These observations show that phase selection in Ce is governed by kinetics and microstructural memory rather than equilibrium thermodynamics or sample morphology alone, establishing path dependence as a defining feature of its high-pressure behavior.

Ridley, Christopher J. [Oak Ridge National Laborat