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At least 163 records · Page 9

Estimation Methodology to Evaluate Hypothetical Downwind Impacts from Fusion Plants

The continuing move toward establishing fusion systems for power generation and the associated research to that end is prompting examination of the potential health and safety impacts of such plants to the environment and human health. As many fusion facilities will have tritium inventories on site as part of the fusion fuel, evaluating the potential for downwind impacts from fusion facilities or power plants resulting from accident or routine emissions is a general requirement for assessing location and impacts to workers and the public. As part of siting considerations and permitting, the fusion facilities would be evaluated for potential for downwind concentration and dose impacts. For accident assessment scenarios, the downwind impacts are usually modeled as an instantaneous (or near-instantaneous) release of material transported following the wind. A range of meteorological conditions are usually assessed to determine a bounding case which results in a dose exceeding a specified threshold (e.g., 95 th or 99 th percentile; DOE 2015). This report provides initial estimates of the downwind dose impacts from a potential tritium release at a fusion power plant-relevant facility and identifies potential distances required to limit impacts to nearby population. This effort is meant to provide a bounding analysis and theoretical understanding of impacts of tritium releases for facilities subject to various environmental and atmospheric conditions. Using a Gaussian dispersion model to simulate a brief plume, downwind concentration and dose is projected for tritium oxide. Releases are assumed to consist entirely of tritium oxide due to the increased dose impacts from the oxide form relative to the elemental form of tritium. We also briefly identify how climatological conditions could potentially be used to support risk profile determination.

54 ENVIRONMENTAL SCIENCES↗

The Tianlai Cylinder Pathfinder Array: System Functions and Basic Performance Analysis

The Tianlai Cylinder Pathfinder is a radio interferometer array designed to test techniques for 21 cm intensity mapping in the post-reionization Universe, with the ultimate aim of mapping the large scale structure of the Universe and measuring cosmological parameters such as the dark energy equation of state. Each of its three parallel cylinder reflectors are oriented in the north-south direction, and the array has a large field of view. As the Earth rotates, the northern sky is observed by drift scanning. The array is located in Hongliuxia, a radio quiet site in Xinjiang, and saw its first light in September 2016. In this first paper on the data analysis of the Tianlai cylinder array, we describe the system functions of the array, the commissioning observations during 2016- 2018, and present its basic performance characteristics. We show examples of the interferometric visibility data, then using the observational data, we derive the actual beam profile in the east-west direction, the bandpass response, and calibrate the complex gains for the array elements either with a strong astronomical point source, or with an artificial calibrator source. Based on the preliminary analysis of the data, we derive the system temperature and sensitivity of the array.

79 ASTRONOMY AND ASTROPHYSICS↗

Modeling the effect of wind speed and direction shear on utility‐scale wind turbine power production

Abstract Wind speed and direction variations across the rotor affect power production. As utility‐scale turbines extend higher into the atmospheric boundary layer (ABL) with larger rotor diameters and hub heights, they increasingly encounter more complex wind speed and direction variations. We assess three models for power production that account for wind speed and direction shear. Two are based on actuator disc representations, and the third is a blade element representation. We also evaluate the predictions from a standard power curve model that has no knowledge of wind shear. The predictions from each model, driven by wind profile measurements from a profiling LiDAR, are compared to concurrent power measurements from an adjacent utility‐scale wind turbine. In the field measurements of the utility‐scale turbine, discrete combinations of speed and direction shear induce changes in power production of −19% to +34% relative to the turbine power curve for a given hub height wind speed. Positive speed shear generally corresponds to over‐performance and increasing magnitudes of direction shear to greater under‐performance, relative to the power curve. Overall, the blade element model produces both higher correlation and lower error relative to the other models, but its quantitative accuracy depends on induction and controller sub‐models. To further assess the influence of complex, non‐monotonic wind profiles, we also drive the models with best‐fit power law wind speed profiles and linear wind direction profiles. These idealized inputs produce qualitative and quantitative differences in power predictions from each model, demonstrating that time‐varying, non‐monotonic wind shear affects wind power production.

Energy & Fuels↗

Direct Numerical Simulation of Flow Over a Wall-Mounted Cube with the Nek5000 Spectral Element Code: DNS at Re h = 3900

The direct numerical simulation (DNS) of the canonical wall-mounted unit cube subjected to two distinct incident velocity profiles is performed at a Reynolds number where the bulk flow characteristics are known to become relatively Reynolds number insensitive. The aim of this work is to highlight the sensitivity of such bluff-body flows to mean shear and to provide a representative set of data for such flow scenarios where common turbulence modeling techniques often fail. Simple boundary conditions and a small domain are selected to allow for cost-effective and easy comparisons for model development purposes. In addition to mean velocity profiles, select turbulence statistics are presented in detail. Further, the basic efficacy of eddy viscosity models is evaluated and found to be adequate only for the shear stress components for the bluff-body flows examined here. Other failure mechanisms for RANS are proposed.

42 ENGINEERING↗

Design, Fabrication and Testing of Surveillance Test Articles for MSR Materials Degradation Management

This report details the design, fabrication, and testing of surveillance test articles aimed at assessing material damage in reactor-relevant environments for effective degradation management. Two types of surveillance test articles with reduced sizes were developed based on design algorithms and finite element modeling: welded design and interlocking design. A furnace heating setup was adopted to apply multiple thermal cyclic loading profiles on the test articles with a temperature range of 500°C - 700°C, while the strain response was monitored using a digital image correlation technique. The testing results demonstrated the successful capturing of expected strain range for welded design while machining tolerance should be improved to engage strain coupling in the interlocking design. Mid-term (500 hours) and long-term (1500 hours) cyclic tests were conducted on welded test articles. A constant strain range of ~0.6% was observed at the specimen with testing under 500 hours, while a gradual decrease of strain at specimen was observed after 500 hours. Non-destructive evaluation through X-ray computed tomography confirmed the microcracks in the welds at specimen-driver joints after cyclic test that caused the strain change. Creep testing of the specimen after long-term cyclic test revealed a short creep life than expected. A multi-profile cyclic test was also conducted on a test article and demonstrated consistent strain response under different temperature ramp rates. The report also briefly discussed the challenges and future research efforts to advance test article development for material surveillance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Angle multiplexed metasurfaces

A metasurface is defined by an array of scattering elements having a U shape, where the geometrical dimensions determining the U shape are determined according to the different phase profiles that the metasurface is meant to generate in response to an incident electromagnetic wave. The metasurface, therefore, generates different phase shifts as a function of the incident electromagnetic wave.

36 MATERIALS SCIENCE↗

Trace Actinide Signatures of a Bulk Neptunium Sample

In nuclear forensic analyses, measurements of actinide elements in a sample can assist with identifying interdicted or unknown materials. While these radiochemical signatures have been extensively investigated in uranium materials, less is known about bulk neptunium samples. This paper describes the measurement of trace actinide concentrations and isotopic profiles in a 237 Np oxide sample. Uranium, plutonium, americium, and curium concentrations and isotopic profiles in the sample were determined and deemed potentially useful for distinguishing different sources of 237 Np. Furthermore, several different potential radiochronometry systems were also investigated; discordant results indicate that the Np sample was never completely purified of other actinide elements, or that subsequent contamination of the sample occurred. Few prior studies of neptunium materials have been reported, and these data suggest that trace actinide constituents could provide unique signatures to identify material out of regulatory control.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Review of Basic Energy Reconstruction Techniques in Liquid Xenon and Argon Detectors for Dark Matter and Neutrino Physics Using NEST

Detectors based upon the noble elements, especially liquid xenon as well as liquid argon, as both single- and dual-phase types, require reconstruction of the energies of interacting particles, both in the field of direct detection of dark matter (weakly interacting massive particles WIMPs, axions, etc.) and in neutrino physics. Experimentalists, as well as theorists who reanalyze/reinterpret experimental data, have used a few different techniques over the past few decades. In this paper, we review techniques based on solely the primary scintillation channel, the ionization or secondary channel available at non-zero drift electric fields, and combined techniques that include a simple linear combination and weighted averages, with a brief discussion of the application of profile likelihood, maximum likelihood, and machine learning. Comparing results for electron recoils (beta and gamma interactions) and nuclear recoils (primarily from neutrons) from the Noble Element Simulation Technique (NEST) simulation to available data, we confirm that combining all available information generates higher-precision means, lower widths (energy resolution), and more symmetric shapes (approximately Gaussian) especially at keV-scale energies, with the symmetry even greater when thresholding is addressed. Near thresholds, bias from upward fluctuations matters. For MeV-GeV scales, if only one channel is utilized, an ionization-only-based energy scale outperforms scintillation; channel combination remains beneficial. We discuss here what major collaborations use.

argon↗

A defined medium based on R2A for cultivation and exometabolite profiling of soil bacteria

SummaryExometabolomics is an approach to assess how microorganisms alter their environments through the depletion and secretion of chemical compounds. Comparisons of inoculated with uninoculated media can be used to provide direct biochemical observations on depleted and secreted metabolites which can be used to predict resource competition, cross-feeding and secondary metabolite production in microbial isolates and communities. This approach is most powerful when used with defined media that enable tracking of all depleted metabolites. However, microbial growth media have traditionally been developed for the isolation and growth of microorganisms but not metabolite utilization profiling through LC-MS/MS. Here, we describe the construction of a defined medium, the Northen Lab Defined Medium (NLDM), that not only supports the growth of diverse bacteria but is defined and therefore suited for exometabolomic experiments. Metabolites included in NLDM were selected based on their presence in R2A medium and soil, elemental stoichiometry requirements, as well as knowledge of metabolite usage by different bacteria. We found that NLDM supported the growth of 53 phylogenetically diverse soil bacterial isolates and all of its metabolites were trackable through LC–MS/MS analysis. These results demonstrate the viability and utility of the constructed NLDM medium for cultivating and characterizing diverse microbial isolates and communities.Originality-Significance StatementWe build a defined medium based on the metabolite composition of R2A medium and soil, elemental stoichiometry requirements, and knowledge of metabolite usage by different bacteria. The newly formulated defined medium was evaluated on its ability to support the growth of soil isolates and its application for metabolite utilization profiling. We found that of 53 phylogenetically diverse soil bacterial isolates grew on the defined medium and all of its metabolites were trackable through LC–MS/MS analysis. This demonstrates the viability and utility of the constructed defined medium for cultivating and characterizing diverse microbial isolates and communities.

de Raad, Markus↗

Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution

With advances in DNA sequencing and miniaturized molecular biology workflows, rapid and affordable sequencing of single-cell genomes has become a reality. Compared to 16S rRNA gene surveys and shotgun metagenomics, large-scale application of single-cell genomics to whole microbial communities provides an integrated snapshot of community composition and function, directly links mobile elements to their hosts, and enables analysis of population heterogeneity of the dominant community members. To that end, we sequenced nearly 500 single-cell genomes from a low diversity hot spring sediment sample from Dewar Creek, British Columbia, and compared this approach to 16S rRNA gene amplicon and shotgun metagenomics applied to the same sample. We found that the broad taxonomic profiles were similar across the three sequencing approaches, though several lineages were missing from the 16S rRNA gene amplicon dataset, likely the result of primer mismatches. At the functional level, we detected a large array of mobile genetic elements present in the single-cell genomes but absent from the corresponding same species metagenome-assembled genomes. Moreover, we performed a single-cell population genomic analysis of the three most abundant community members, revealing differences in population structure based on mutation and recombination profiles. While the average pairwise nucleotide identities were similar across the dominant species-level lineages, we observed differences in the extent of recombination between these dominant populations. Most intriguingly, the creek's Hydrogenobacter sp. population appeared to be so recombinogenic that it more closely resembled a sexual species than a clonally evolving microbe. Together, this work demonstrates that a randomized single-cell approach can be useful for the exploration of previously uncultivated microbes from community composition to population structure.

59 BASIC BIOLOGICAL SCIENCES↗

Short-term apartment-level load forecasting using a modified neural network with selected auto-regressive features

Residential electricity load profiles and their diversity have become increasingly important to realize the benefits of Smart or Transactive Energy Networks (TENs). An important element of TENs will be practical, accurate, and implementable residential load forecasting techniques. While there have been many approaches to short-term load forecasting, few have included forecasting for individual households, partly because the high volatility and idiosyncrasies present in individual household load data can pose significant challenges. In this study, we develop a Convolutional Long Short-Term Memory-based neural network with Selected Autoregressive Features (termed a CLSAF model) to improve short-term household electricity load forecasting accuracy by employing three strategies: autoregressive features selection, exogenous features selection, and a “default” state to avoid overfitting at times of high load volatility. We include aggregations of apartments to floor and building level, because utilities may favor transactive approaches that rely on aggregator models, e.g., a cluster of consumers as opposed to an individual. We demonstrate that the CLSAF model, by virtue of its enhanced feature representation and modest computational resources, can accomplish load forecasting in a multi-family residential building across three spatial granularities (individual apartment/household, floor, and building levels), with an accuracy improvement of up to 25% compared to a persistence model. We propose a data screening technique to characterize time-series electricity-load data. This technique is suitable for integration into a TEN ecosystem and allows one to estimate confidence levels of the load forecasts to optimize computational resources and the risks associated with uncertain forecasts.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modeling Intercalation Chemistry with Multiredox Reactions by Sparse Lattice Models in Disordered Rocksalt Cathodes

Modern battery materials can contain many elements with substantial site disorder, and their configurational state has been shown to be critical for their performance. The intercalation voltage profile is a critical parameter to evaluate the performance of energy storage. The application of commonly used cluster expansion techniques to model the intercalation thermodynamics of such systems ab initio is challenged by the combinatorial increase in configurational degrees of freedom as the number of species grows. Such challenges necessitate the efficient generation of lattice models without overfitting and proper sampling of the configurational space under the requirement of charge balance in ionic systems. In this work, we introduce a combined approach that addresses these challenges by (1) constructing a robust cluster expansion Hamiltonian using the sparse regression technique, including -norm regularization and structural hierarchy; and (2) implementing semigrand-canonical Monte Carlo to sample charge-balanced ionic configurations using the table-exchange method and an ensemble average approach. These techniques are applied to a disordered rocksalt oxyfluoride (LMNOF) that is part of a family of promising earth-abundant cathode materials. The simulated voltage profile is found to be in good agreement with experimental data and particularly provides a clear demonstration of the and oxygen contributions to the redox potential as a function of content.

25 ENERGY STORAGE↗

Quantitative Proteome Profiling Reveals Cellobiose-Dependent Protein Processing and Export Pathways for the Lignocellulolytic Response in Neurospora crassa

Filamentous fungi are intensively used for producing industrial enzymes, including lignocellulases. Employing insoluble cellulose to induce the production of lignocellulases causes some drawbacks, e.g., a complex fermentation operation, which can be overcome by using soluble inducers such as cellobiose. Here, a triple β-glucosidase mutant of Neurospora crassa, which prevents rapid turnover of cellobiose and thus allows the disaccharide to induce lignocellulases, was applied to profile the proteome responses to cellobiose and cellulose (Avicel). Our results revealed a shared proteomic response to cellobiose and Avicel, whose elements included lignocellulases and cellulolytic product transporters. While the cellulolytic proteins showed a correlated increase in protein and mRNA levels, only a moderate correlation was observed on a proteomic scale between protein and mRNA levels (R 2 = 0.31). Ribosome biogenesis and rRNA processing were significantly overrepresented in the protein set with increased protein but unchanged mRNA abundances in response to Avicel. Ribosome biogenesis, as well as protein processing and protein export, was also enriched in the protein set that showed increased abundance in response to cellobiose. NCU05895, a homolog of yeast CWH43, is potentially involved in transferring a glycosylphosphatidylinositol (GPI) anchor to nascent proteins. This protein showed increased abundance but no significant change in mRNA levels. Disruption of CWH43 resulted in a significant decrease in cellulase activities and secreted protein levels in cultures grown on Avicel, suggesting a positive regulatory role for CWH43 in cellulase production. The findings should have an impact on a systems engineering approach for strain improvement for the production of lignocellulases.

59 BASIC BIOLOGICAL SCIENCES↗

Prototype Modeling for a Light-Trapping Planar-Cavity Enclosed Particle Solar Receiver

Concentrating solar thermal (CST) systems present a promising avenue for affordable and reliable energy production. Solar receivers are key components that determine the efficiency and longevity of these systems. Particle-based solar receivers have emerged as a compelling alternative to traditional technologies, offering several advantages that address limitations in current CST systems. This is especially true as next-generation CST technologies target applications including electricity generation, thermochemical processes, and industrial process heat, many of which necessitate higher operating temperatures than current commercial molten salt systems. Molten-salt thermal energy storage (TES) systems, commonly used in CSP, face challenges related to freezing and corrosion. Particle-based TES systems, in contrast, do not experience these issues, as particles are stable at high temperatures, exceeding 1000 degrees Celsius. This capability allows for a wider range of applications, including those requiring higher temperatures for industrial processes and efficient electricity generation. A novel innovation in particle-based solar receiver technology is the light-trapping planar cavity receiver (LTPCR) configuration developed by NREL. The LTPCR design consists of small cavity-like structures using opaque planar surfaces, enabling efficient capture and absorption of solar energy. A high incident flux concentration at the cavity aperture is absorbed on the receiver walls, and subsequently transferred to particles on the inside of cavities. The particles flow through the system, forming a fluidized bed inside of the receiver panels, effectively capturing the absorbed solar heat. Air is used as a fluidizing medium in this process to enhance particle heat transfer and mixing. The effectiveness of this design lies in its ability to manage solar flux conditions and ensure high solar-to-thermal receiver efficiency. A 100-kW prototype is currently being tested at the King Saud University in Saudi Arabia to assess the receiver performance. A range of modeling analyses for the optical, thermal, and mechanical effects were conducted to assess the performance of the receiver under on-sun conditions. The solar flux resulting from the KSU heliostat field was modeled using NREL SolTrace software and produced up to 600 kW/m2 at the receiver aperture. The solar flux absorbed on the receiver walls was then used within a computational fluid dynamics (CFD) model to predict wall temperature distributions along with radiation and convection loss. A two-phase CFD model was developed for the fluidized bed of silica sand inside the receiver panels to predict local wall-to-particle heat transfer coefficients, particle temperature distributions, and outlet temperature of the particles. We have also conducted analyses to understand the thermomechanical behavior of these innovative enclosed light-trapping solar receivers optimized for particle heating. We used finite element analysis (FEA) to predict the receiver's performance using temperature distributions obtained from CFD and based on the resulting stress profiles, evaluated creep-fatigue damage with a goal of achieving a 30-year service life. Analysis showed a significant impact of the particle-to-wall heat transfer coefficients (HTCs) on receiver performance, with higher HTCs resulting in reduced stress and increased lifespan. For instance, when using Inconel 740H, increasing the HTC from 800 W/m2 K to 1400 W/m2 K increased the creep life from 4,000 hours to over 100,000 hours. This highlights the importance of understanding and optimizing heat transfer in the design of high-efficiency receivers.

14 SOLAR ENERGY↗

Element Formation in Radiation-hydrodynamics Simulations of Kilonovae

Abstract Understanding the details of r -process nucleosynthesis in binary neutron star merger (BNSM) ejecta is key to interpreting kilonova observations and identifying the role of BNSMs in the origin of heavy elements. We present a self-consistent, two-dimensional, ray-by-ray radiation-hydrodynamic evolution of BNSM ejecta with an online nuclear network (NN) up to a timescale of days. For the first time, an initial numerical relativity ejecta profile composed of the dynamical component and spiral-wave and disk winds is evolved including detailed r -process reactions and nuclear heating effects. A simple model for the jet energy deposition is also included. Our simulation highlights that the common approach of relating in postprocessing the final nucleosynthesis yields to the initial thermodynamic profile of the ejecta can lead to inaccurate predictions. Moreover, we find that neglecting the details of the radiation-hydrodynamic evolution of the ejecta in nuclear calculations can introduce deviations of up to 1 order of magnitude in the final abundances of several elements, including very light and second r -process peak elements. The presence of a jet affects element production only in the innermost part of the polar ejecta, and it does not alter the global nucleosynthesis results. Overall, our analysis shows that employing an online NN improves the reliability of nucleosynthesis and kilonova light-curve predictions.

Magistrelli, Fabio (ORCID:0009000509767851)↗

Lithological controls on soil geochemistry and clay mineralogy across Spodosols in the coastal temperate rainforest of southeast Alaska

The interaction of similar soil forming factors with different parent materials determines soil chemical weathering, influencing soil processes and properties. In the coastal temperate rainforests of southeast Alaska, Spodosols is the dominant soil order in well-drained parent materials regardless of the lithology. Yet, the role of lithology on chemical weathering, base cation depletion, and mineral transformation during pedogenesis remains elusive. Here, we established a lithosequence comprised of soils derived from tonalite, phyllite, slate, and metavolcanic rocks to test the hypothesis that despite the soils in southeast Alaska presenting similar taxonomy and morphology, the influence of lithology in chemical weathering intensity and mineralogy can be detected. We evaluated physicochemical properties, clay mineralogy, Fe-Al oxides, chemical weathering, and elemental mass balance on eleven Spodosols sampled along the lithosequence. We also propose a new weathering index, the Weathering Index for Spodosols (WISP), suitable to evaluate the weathering degree of soils with Al mobility and base-rich parent materials. This index fills a gap in traditional weathering indices that uses Al as an immobile element and/or does not evaluate the leaching of main base cations. We found the pedons across the lithosequence expressed similar physicochemical properties, with predominantly thick profiles, presenting andic properties, relatively thick spodic horizons, and thin E horizons. Podzolization imposed similar mineral transformation trends, mainly dissolution of chlorite, mica alteration to interstratified mica-vermiculite, and formation of smectite in E horizons. Kaolinite was detected in the soils from all lithologies, but only in trace amounts in phyllite soils. Fe oxides depth distribution was similar but with a higher concentration in the slate (44.5 ± 4.2 g/kg), followed by metavolcanic (31.6 ± 4.0 g/kg), phyllite (27.9 ± 3.8 g/kg), and tonalite soils (19.9 ± 5.7 g/kg) and predominantly as organometallic complexes (extracted by Na-pyrophosphate). The stronger weathering of chlorite and mica in the E horizons was reflected in larger losses of Mg and K, while Ca and Na were more depleted in the spodic horizons, suggesting plagioclase weathering. Slate soils were the most depleted in base cations, followed by phyllite, tonalite, and metavolcanic soils. The more depleted status of slate soils was supported by the higher WISP values (WISP = 62), followed by phyllite (WISP = 55), tonalite (WISP = 53), and metavolcanic soils (WISP = 45). Our results demonstrated that lithology controlled elemental depletion intensities, Fe oxide concentrations, and partially the clay fraction mineralogy in addition to podzolization acting as a dominant pedogenic process across all sites. These findings advance our understanding of the role of lithology on soil mineralogy/geochemistry that impacts critical soil functions, such as the soil carbon cycle, elemental fluxes, organo-mineral interactions, and solid-solution reactions.

54 ENVIRONMENTAL SCIENCES↗

Melting and phase relations of Fe-Ni-Si determined by a multi-technique approach

Many studies have suggested silicon as a candidate light element for the cores of Earth and Mercury. However, the effect of silicon on the melting temperatures of core materials and thermal profiles of cores is poorly understood, due to disagreements among melt detection techniques, uncertainties in sample pressure evolution during heating, and sparsity of studies investigating the combined effects of nickel and silicon on the phase diagram of iron. Here, in this study we develop a multi-technique approach for measuring the high-pressure melting and solid phase relations of iron alloys and apply it to Fe 0.8 Ni 0.1 Si 0.1 (Fe-11wt%Ni-5.3wt%Si), a composition compatible with recent estimates for the cores of Earth and Mercury. This approach combines results (20-83 GPa) from two atomic-level techniques: synchrotron Mossbauer spectroscopy (SMS) and synchrotron x-ray diffraction (XRD). Melting is independently detected by the loss of the Mossbauer signal, produced exclusively by solid-bound iron nuclei, and the onset of a liquid diffuse x-ray scattering signal. The use of a burst heating and background updating method for quantifying changes in the reference background during heating facilitates the determination of liquid diffuse signal onsets and leads to strong reproducibility and excellent agreement in melting temperatures determined separately by the two techniques. XRD measurements additionally constrain the hcp-fcc phase boundary and in-situ pressure evolution of the samples during heating. We apply our updated thermal pressure model to published SMS melting data on fcc-Fe and fcc-Fe 0.9 Ni 0.1 to precisely evaluate the effect of silicon on melting temperatures. We find that the addition of 10 mol% Si to Fe 0.9 Ni 0.1 reduces melting temperatures by ~250 K at low pressures (<60 GPa) and flattens the hcp-fcc phase boundary. Extrapolating our results, we constrain the location of the hcp-fcc-liquid quasi-triple point at 147±14 GPa and 3140±90 K, which implies a melting temperature reduction of 500 K compared with Fe 0.9 Ni 0.1 . The results demonstrate the advantages of combining complementary experimental techniques in investigations of melting under extreme conditions.

36 MATERIALS SCIENCE↗