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214 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multigeneration Pedigrees to Monitor Hatchery Broodstock Composition and Genetic Variation of Spring/Summer Chinook Salmon in the Columbia River Basin

Abstract Hatchery production of Chinook Salmon Oncorhynchus tshawytscha in the Columbia River basin comprises most of the anadromous salmonid production in this region. Hatchery facilities and programs serve to mitigate for impacts to salmonids due to the construction and operation of hydropower dams and habitat impacts from development in addition to the conservation and restoration of natural populations. A genetic method referred to as parentage-based tagging (PBT) enables highly reliable detection of hatchery-origin fish and inference of multigeneration pedigrees. This study compiles 11 years of PBT data from nearly 125,000 interior stream-type Chinook Salmon from 24 spawning hatcheries located on tributaries of the mid- and upper Columbia River and in the Salmon, Clearwater, and Grande Ronde River subbasins. Multigenerational pedigrees allowed for investigation of the proportions of natural- and hatchery-origin broodstock (pNOB and pHOB, respectively) for each hatchery and enumeration of the scale of production between segregated and integrated programs. We then compared how pHOB and the scale of production influenced the number of stray fish observed, genetic diversity, relatedness, and age-class compositions within broodstocks. Over 91.0% of hatchery broodstock could be assigned back to their parents, and overall less than 1.0% of broodstock consisted of fish that were unintentionally incorporated into nonnatal hatchery programs. We evaluated 11 segregated programs with 0.0–10.0% pNOB, 9 intermediate programs (10.1–50.0% pNOB), and 3 integrated programs (>50.0% pNOB). There was no correlation between the scale of production or pNOB with the level of genetic diversity, but as production size increased, so did the effective number of breeders. This study demonstrates the utility of PBT as a monitoring tool for hatchery broodstocks, and results suggest that segregated and integrated programs have tradeoffs that generally align with their intended broodstock management purpose of providing fish for harvest and/or fish for supplementation or reintroduction.

Horn, Rebekah L.↗
DOE OSTI2022

Retracted: Monitoring Hatchery Broodstock Composition and Genetic Variation of Spring/Summer Chinook Salmon in the Columbia River Basin with Multigeneration Pedigrees

Abstract Hatchery production of Chinook Salmon Oncorhynchus tshawytscha in the Columbia River basin comprises most of the anadromous salmonid production in this region. Hatchery facilities and programs serve to mitigate for impacts to salmonids due to the construction and operation of hydropower dams and habitat impacts from development in addition to the conservation and restoration of natural populations. A genetic method referred to as parentage-based tagging (PBT) enables highly reliable detection of hatchery-origin fish and inference of multigeneration pedigrees. This study compiles 11 years of PBT data from nearly 125,000 interior stream-type Chinook Salmon from 24 spawning hatcheries located in tributaries of the mid- and upper Columbia River as well as the Salmon, Clearwater, and Grande Ronde River subbasins. Multigenerational pedigrees allowed investigation of the proportion of natural- and hatchery-origin broodstock (pNOB and pHOB, respectively) for each hatchery and enumeration of the scale of production between segregated and integrated programs. We then compared how pHOB and the scale of production influenced the number of stray fish observed, genetic diversity, relatedness, and age-class compositions within broodstocks. Over 91.0% of hatchery broodstock could be assigned back to their parents, and there was an overall rate of less than 1.0% of broodstock that were unintentionally incorporated into nonnatal hatchery programs. We evaluated 14 segregated programs with 0.0–10.0% pNOB, 7 intermediate programs (10.1–50.0% pNOB), and 3 integrated programs (>50.0% pNOB). There was no correlation between the scale of production or pNOB with the level of genetic diversity, but as production size increased, so did the effective number of breeders. This study demonstrates the utility of PBT as a monitoring tool for hatchery broodstocks, and results suggest that segregated and integrated programs have tradeoffs that generally align with their intended broodstock management purpose of providing fish for harvest and/or fish for supplementation or reintroduction.

Horn, Rebekah L.↗
DOE OSTI2020

Osteoporosis Treatments Affect Bone Matrix Maturation in a Rat Model of Induced Cortical Remodeling

ABSTRACT To test how osteoporosis drugs affect bone matrix maturation during cortical bone remodeling, 72 pregnant rats were switched from a 0.4% to a 0.01% calcium diet at parturition for a 23‐day lactation period. At weaning, eight dams were sacrificed to establish baseline values, while the remaining dams were returned to 0.4% calcium and treated with vehicle (saline), sodium fluoride (NaF), zoledronic acid (ZA), or sclerostin antibody (Scl‐Ab) for either 7 or 28 days (eight animals per group per time point). Femora were examined by μCT, dynamic histomorphometry, Fourier transform infrared imaging, and three‐point bending of notched specimens. Cortical porosity decreased in all groups from baseline to day 28. Intracortical mineralizing surface (MS/BS) and mineral apposition rate (MAR), as well as the mineral‐to‐matrix ratio were unaffected by treatment, but intracortical crystallinity was increased in the ZA group at day 10 compared with vehicle. Cortical area increased in all groups over 28 days mainly because of an addition of bone at the endocortical surface. Endocortical MS/BS did not vary among the groups, but endocortical MAR was suppressed in the NaF group at day 2 and elevated in the Scl‐Ab group at day 4 compared with vehicle. Endocortical mineral‐to‐matrix ratio was increased at days 5 and 10 following NaF treatment and endocortical crystallinity was increased at day 5 following ZA treatment compared with vehicle. Fracture toughness did not differ among the groups. Thus, the treatments affected matrix maturation more strongly at the endocortical then intracortical envelope. In this model of induced remodeling, the bone formation phase is synchronized at multiple sites, facilitating study of the effects of drugs or other bone‐targeting agents on matrix maturation independent of their effects on the initiation of remodeling. © 2020 The Authors. JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Coupling between collective modes in the deformed 98 Zr nucleus: Insights from consistent HFB + QRPA calculations with the Gogny interaction

The zirconium isotopes exhibit structural properties that present multiple challenges to nuclear theory. Investigations of the coupling present within isoscalar modes and within isovector modes are scarce but important for advancing our understanding of the microscopic picture of nuclei. To explore some of these underlying coupling features, and to test the predictive power of a state-of-the-art nuclear structure approach, we provide a detailed analysis of the properties of 90,96,98 Zr . This region includes a benchmarking case and offers insights into nuclear deformation phenomena. Here, to investigate the coupling between collective modes in deformed nuclei, we focused our analysis on the ground and excited-state properties of these isotopes, employing a consistent approach with the axially symmetric deformed Hartree-Fock-Bogoliubov (HFB) and the quasiparticle random phase approximation (QRPA) framework, both using the Gogny D1M force. This approach effectively describes both low-lying and giant-resonance states. We devoted special attention to the deformed 98 Zr nucleus, where we confirm the existence of coupling between monopole and quadrupole excitations through the 𝐾 𝜋 = 0 + QRPA components and demonstrate an analogous dipole-octupole coupling through the 𝐾 𝜋 = 0 − and 𝐾 𝜋 = 1 − components. Intrinsic transition densities and associated radial projections illustrate the coupling. Our work complements and extends earlier studies carried out using density-functional-based methods and notably, we included the complete Coulomb interaction also in the pairing fields, i.e., we treat terms exactly that are approximated in typical calculations that use the Gogny D1 and D2 interaction families.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2012

Assimilation of GRACE Terrestrial Water Storage into a Land Surface Model: Evaluation 1 and Potential Value for Drought Monitoring in Western and Central Europe

A land surface model s ability to simulate states (e.g., soil moisture) and fluxes (e.g., runoff) is limited by uncertainties in meteorological forcing and parameter inputs as well as inadequacies in model physics. In this study, anomalies of terrestrial water storage (TWS) observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission were assimilated into the NASA Catchment land surface model in western and central Europe for a 7-year period, using a previously developed ensemble Kalman smoother. GRACE data assimilation led to improved runoff correlations with gauge data in 17 out of 18 hydrological basins, even in basins smaller than the effective resolution of GRACE. Improvements in root zone soil moisture were less conclusive, partly due to the shortness of the in situ data record. In addition to improving temporal correlations, GRACE data assimilation also reduced increasing trends in simulated monthly TWS and runoff associated with increasing rates of precipitation. GRACE assimilated root zone soil moisture and TWS fields exhibited significant changes in their dryness rankings relative to those without data assimilation, suggesting that GRACE data assimilation could have a substantial impact on drought monitoring. Signals of drought in GRACE TWS correlated well with MODIS Normalized Difference Vegetation Index (NDVI) data in most areas. Although they detected the same droughts during warm seasons, drought signatures in GRACE derived TWS exhibited greater persistence than those in NDVI throughout all seasons, in part due to limitations associated with the seasonality of vegetation.

Li, Bailing↗
DOE OSTI2023

Balloon Tag Manufacturing Technique for Sensor Fish and Live Fish Recovery

Fish may experience injuries and mortality when they pass through hydraulic conveyances at hydropower dams, even if these conveyances are designed to be fish-friendly, such as downstream bypass systems, modified spillways and turbines. The main methods used to study fish passage conditions in hydraulic structures involve direct, in situ testing using Sensor Fish technology and live fish. Sensor Fish data helps identify physical stressors and their locations in the fish passage environment, while live fish are assessed for injuries and mortality. Balloon tags, which are self-inflating balloons attached externally to Sensor Fish and live fish, aid in their recovery after passing through hydraulic structures. This article focuses on the development of balloon tags with varying numbers of dissolvable, vegetable-based capsules containing a mixture of oxalic acid, sodium bicarbonate powders, and water at two different temperatures. Our research determined that balloon tags with three capsules, injected with 5 mL of water at 18.3 °C, consistently achieved the desired balloon volume. These tags had a mean inflation volume of 114 cm 3 with a standard deviation of 1.2 cm 3 . Among the balloon tags injected with water at 18.3 °C, it was observed that the two-capsule balloon tags took the longest time to reach full inflation. In addition, the four-capsule balloon tags demonstrated a faster inflation start time, while the three-capsule balloon tags demonstrated a faster deflation start time. Overall, this approach proves to be effective for validating the performance of new technologies, improving turbine design, and making operational decisions to enhance fish passage conditions. Importantly, it serves as a valuable tool for research and field evaluations, aiding in the refinement of both the design and operation of hydraulic structures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15–90. The effects of dementia, mild cognitive impairment, Parkinson’s disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p < 0.001), while neither depression nor ADHD showed consistent associations with VLM scores (p > 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders.

Neurosciences & Neurology↗
DOE OSTI2021

The BEST framework for the search for the QCD critical point and the chiral magnetic effect

The Beam Energy Scan Theory (BEST) Collaboration was formed with the goal of providing a theoretical framework for analyzing data from the Beam Energy Scan (BES) program at the relativistic heavy ion collider (RHIC) at Brookhaven National Laboratory. The physics goal of the BES program is the search for a conjectured QCD critical point as well as for manifestations of the chiral magnetic effect. We describe progress that has been made over the previous five years. This includes studies of the equation of state and equilibrium susceptibilities, the development of suitable initial state models, progress in constructing a hydrodynamic framework that includes fluctuations and anomalous transport effects, as well as the development of freezeout prescriptions and hadronic transport models. Lastly, we address the challenge of integrating these components into a complete analysis framework. This document describes the collective effort of the BEST Collaboration and its collaborators around the world.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Biological Response Models: Predicting Injury and Mortality of Fish During Downstream Passage through Hydropower Facilities

This report describes the U.S. Department of Energy’s HydroPASSAGE project efforts to develop and collect biological response models for integration into the Biological Performance Assessment (BioPA) toolset and the Hydropower Biological Evaluation Toolset (HBET). These models help understand how fish are likely to respond during dam passage when exposed to hydraulic and physical stressors associated with turbines and other hydropower structures. When fish pass through hydropower facilities, they may encounter several stressors, of which the three most common are collision, rapid decompression, and fluid shear. Specialized equipment has been used to develop 99 biological response models for exposure to blade strike, rapid decompression, or fluid shear. The models were gathered from the literature or developed as part of this effort and include models for 31 different species of fish that have various predicted endpoints (i.e., injury or mortality). Among these models, considerable variation in susceptibility to the stressors has been observed from one species to another, and a species’ susceptibility to one stressor does not necessarily indicate similar susceptibility to another. Although several species have been examined, it is still unclear how many other species, which may have different morphological traits, may respond to these stressors, so further examination of the different species is needed. These models can and have been applied in several different cases, often using the BioPA toolset and HBET, to better understand the potential for injury and mortality that may occur during fish passage at hydropower facilities, including specific applications, such as turbine replacement, the installation of new turbines, or changing operations of currently installed turbines. As hydropower is continually developed to meet the electricity needs of society, tools such as HBET and BioPA, used with the integrated biological response models, will aid in the development of technologies and strategies that avoid, minimize, mitigate, or manage environmental effects.

13 HYDRO ENERGY↗
DOE OSTI2022

Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning

Stream temperature (Ts) is an important water quality parameter that affects ecosystem health and human water use for beneficial purposes. Accurate Ts predictions at different spatial and temporal scales can inform water management decisions that account for the effects of changing climate and extreme events. In particular, widespread predictions of Ts in unmonitored stream reaches can enable decision makers to be responsive to changes caused by unforeseen disturbances. In this study, we demonstrate the use of classical machine learning (ML) models, support vector regression and gradient boosted trees (XGBoost), for monthly Ts predictions in 78 pristine and human-impacted catchments of the Mid-Atlantic and Pacific Northwest hydrologic regions spanning different geologies, climate, and land use. The ML models were trained using long-term monitoring data from 1980–2020 for three scenarios: (1) temporal predictions at a single site, (2) temporal predictions for multiple sites within a region, and (3) spatiotemporal predictions in unmonitored basins (PUB). In the first two scenarios, the ML models predicted Ts with median root mean squared errors (RMSE) of 0.69–0.84 °C and 0.92–1.02 °C across different model types for the temporal predictions at single and multiple sites respectively. For the PUB scenario, we used a bootstrap aggregation approach using models trained with different subsets of data, for which an ensemble XGBoost implementation outperformed all other modeling configurations (median RMSE 0.62 °C).The ML models improved median monthly Ts estimates compared to baseline statistical multi-linear regression models by 15–48% depending on the site and scenario. Air temperature was found to be the primary driver of monthly Ts for all sites, with secondary influence of month of the year (seasonality) and solar radiation, while discharge was a significant predictor at only 10 sites. The predictive performance of the ML models was robust to configuration changes in model setup and inputs, but was influenced by the distance to the nearest dam with RMSE <1 °C at sites situated greater than 16 and 44 km from a dam for the temporal single site and regional scenarios, and over 1.4 km from a dam for the PUB scenario. Our results show that classical ML models with solely meteorological inputs can be used for spatial and temporal predictions of monthly Ts in pristine and managed basins with reasonable (<1 °C) accuracy for most locations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Displacements of the earth's surface due to atmospheric loading - Effects of gravity and baseline measurements

Atmospheric mass loads and deforms the earth's crust. By performing a convolution sum between daily, global barometric pressure data and mass loading Green's functions, the time dependent effects of atmospheric loading, including those associated with short-term synoptic storms, on surface point positioning measurements and surface gravity observations are estimated. The response for both an oceanless earth and an earth with an inverted barometer ocean is calculated. Load responses for near-coastal stations are significantly affected by the inclusion of an inverted barometer ocean. Peak-to-peak vertical displacements are frequently 15-20 mm with accompanying gravity perturbations of 3-6 micro Gal. Baseline changes can be as large as 20 mm or more. The perturbations are largest at higher latitudes and during winter months. These amplitudes are consistent with the results of Rabbel and Zschau (1985), who modeled synoptic pressure disturbances as Gaussian functions of radius around a central point. Deformation can be adequately computed using real pressure data from points within about 1000 km of the station. Knowledge of local pressure, alone, is not sufficient. Rabbel and Zschau's hypothesized corrections for these displacements, which use local pressure and the regionally averaged pressure, prove accurate at points well inland but are, in general, inadequate within a few hundred kilometers of the coast.

Van Dam, T. M.↗
DOE OSTI2024

An Operations and Maintenance Roadmap for U.S. Offshore Wind: Enabling a Cost-Effective and Sustainable U.S. Offshore Wind Energy Industry Through Innovative Operations and Maintenance

The United States is currently targeting 30GW of offshore wind to be installed by 2030, and 150GW by 2050. Even considering future turbine sizes, this represents thousands of new turbines installed in a diverse set of environments, each with their unique design, installation, and maintenance challenges. While much can be learned from European and Asian experience with offshore wind over the past two decades, it is important to understand the unique circumstances of the U.S. This document explores operations and maintenance of offshore wind energy, specific to the U.S. and attempts to lay out a roadmap for needed activities to ensure reliability of future installations. The roadmap was informed through dozens of interviews with a wide cross-section of the industry, including representatives from OEMs, owner/operators, service companies, certification agencies, service providers, and researchers. The roadmap first describes the problem by component - blades, drivetrain and nacelle, structures and foundations, and electrical systems - through a look at current practices and opportunities for improvement in the areas of Failure Mode Analysis and Mitigation; Monitoring, Sensing, and Inspection; and Maintenance Execution. Crosscutting areas of Digitalization, Robotics and Automation, Prognostics and Health Management and O&M Optimization, Experimentation and Demonstration, Standardization, and Design Optimization Considering Reliability and O&M are then discussed. Finally, the roadmap summarizes all of these topics with recommendations for short (1-3 years), medium (4-7 years), and long term (8-12 years) activities, with a description of needed public and private sector contributions.

17 WIND ENERGY↗
DOE OSTI2023

Artificial Neural Network Models for Octane Number and Octane Sensitivity: A Quantitative Structure Property Relationship Approach to Fuel Design

Octane sensitivity (OS), defined as the research octane number (RON) minus the motor octane number (MON) of a fuel, has gained interest among researchers due to its effect on knocking conditions in internal combustion engines. Compounds with a high OS enable higher efficiencies, especially within advanced compression ignition engines. RON/MON must be experimentally tested to determine OS, requiring time, funding, and specialized equipment. Thus, predictive models trained with existing experimental data and molecular descriptors (via quantitative structure-property relationships (QSPRs)) would allow for the preemptive screening of compounds prior to performing these experiments. Here, the present work proposes two methods for predicting the OS of a given compound: using artificial neural networks (ANNs) trained with QSPR descriptors to predict RON and MON individually to compute OS (derived octane sensitivity (dOS)), and using ANNs trained with QSPR descriptors to directly predict OS. Twenty-five ANNs were trained for both RON and MON and their test sets achieved an overall 6.4% and 5.2% error, respectively. Twenty-five additional ANNs were trained for both dOS and OS; dOS calculations were found to have 15.3% error while predicting OS directly resulted in 9.9% error. A chemical analysis of the top QSPR descriptors for RON/MON and OS is conducted, highlighting desirable structural features for high-performing molecules and offering insight into the inner mathematical workings of ANNs; such chemical interpretations study the interconnections between structural features, descriptors, and fuel performance showing that connectivity, structural diversity, and atomic hybridization consistently drive fuel performance.

09 BIOMASS FUELS↗
DOE OSTI2023

PluginPlay: Enabling exascale scientific software one module at a time

For many computational chemistry packages, being able to efficiently and effectively scale across an exascale cluster is a heroic feat. Collective experience from the Department of Energy’s Exascale Computing Project suggests that achieving exascale performance requires far more planning, design, and optimization than scaling to petascale. In many cases, entire rewrites of software are necessary to address fundamental algorithmic bottlenecks. This in turn requires a tremendous amount of resources and development time, resources that cannot reasonably be afforded by every computational science project. It thus becomes imperative that computational science transition to a more sustainable paradigm. Key to such a paradigm is modular software. While the importance of modular software is widely recognized, what is perhaps not so widely appreciated is the effort still required to leverage modular software in a sustainable manner. The present manuscript introduces PluginPlay, https://github.com/NWChemEx-Project/PluginPlay, an inversion-of-control framework designed to facilitate developing, maintaining, and sustaining modular scientific software packages. Here this manuscript focuses on the design aspects of PluginPlay and how they specifically influence the performance of the resulting package. Although, PluginPlay serves as the framework for the NWChemEx package, PluginPlay is not tied to NWChemEx or even computational chemistry. We thus anticipate PluginPlay to prove to be a generally useful tool for a number of computational science packages looking to transition to the exascale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Evidence-based indicator approach to guide preliminary environmental impact assessments of hydropower development

Global expansion of hydropower resources has increased in recent years to meet growing energy demands and fill worldwide gaps in electricity supply. However, hydropower induces significant environmental impacts on river ecosystems - impacts that are addressed through environmental impact assessment (EIA) processes. The need for effective EIA processes is increasing as environmental regulations are either stressed in developing countries undertaking rapid expansion of hydropower capacity or time- and resource-intensive in developed countries. Part of the challenge in implementing EIAs lies in reaching a consensus among stakeholders regarding the most important environmental factors as the focus of impact studies. To help address this gap, we developed a weight-of-evidence approach (and toolkit) as a preliminary and coarse assessment of the most relevant impacts of hydropower on primary components of the river ecosystem, as identified using river function indicators. Through a science-based questionnaire and predictive model, users identify which environmental indicators may be impacted during hydropower development as well as those indicators that have the highest levels of uncertainty and require further investigation. Furthermore, an assessment tool visualizes inter-dependent indicator relationships, which help formulate hypotheses about causal relationships explored through environmental studies. We apply these tools to four existing hydropower projects and one hypothetical new hydropower project of varying sizes and environmental contexts. We observed consistencies between the output of our tools and the Federal Energy Regulatory Commission licensing process (inclusive of EIAs) but also important differences arising from holistic scientific evaluations (our toolkit) versus regulatory policies. The tools presented herein are aimed at increasing the efficiency of the EIA processes that engender environmental studies without loss of rigor or transparency of rationale necessary for understanding, considering, and mitigating the environmental consequences of hydropower.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Metrology for femtosecond pulsed x-ray heating in diamond anvil cell experiments at the European XFEL: Revisiting the iron phase diagram up to 150 GPa

The development of pulsed intense x-ray sources, such as free electron laser, offers new avenues for high pressure experiments. Here, we study the feasibility and metrology of x-ray heating in diamond anvil cells at the European x-ray free electron laser. This method enables one to volumetrically heat the sample while inhibiting chemical migration and probing the crystallographic structure of the sample throughout the heating with a high repetition rate. We focus our study on iron, whose phase diagram is well established up to 100 GPa, to explore the possibilities and limitations of this technique. We volumetrically heat iron samples at starting pressures ranging from 10 to 138 GPa, using the x-ray beam pulsed at 4.5 MHz in a serial pump-and-probe experimental design. Experimental challenges arise from temperature gradients within the sample, changes in temperature at the 100 ns timescale, the difficulty of direct temperature estimates, the effect of thermal pressure, and the presence of metastable crystallites due to rapid cycles of heating and cooling. Hence, we develop a multi-crystal-like data processing method that allows us to account for sample heterogeneity in probed conditions. We then calibrate our measurements using known physical properties of iron under pressure. Thermal pressure in our experiments increases from 4% of the isochoric prediction at 10 GPa to 23% at 138 GPa, and we show that our data are in agreement with most previous observations of iron in this pressure range. The method can now be implemented at higher pressures and temperatures and on materials with unknown phase diagrams.

Materials science↗