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DOE OSTI2025

Current-based metrology with two-terminal mesoscopic conductors

The traditional approach to quantum parameter estimation focuses on the quantum state, deriving fundamental bounds on precision through the quantum Fisher information. In most experimental settings, however, performing arbitrary quantum measurements is highly unfeasible. In open quantum systems, an alternative approach to metrology involves the measurement of stochastic currents flowing from the system to its environment. However, the present understanding of current-based metrology is mostly limited to Markovian master equations. Considering a parameter estimation problem in a two-terminal mesoscopic conductor, we identify the key elements that determine estimation precision within the Landauer-Büttiker formalism. Crucially, this approach allows us to address arbitrary coupling and temperature regimes. Furthermore, we obtain analytical results for the precision in linear-response and zero-temperature regimes. For the specific parameter estimation task that we consider, we demonstrate that the boxcar transmission function is optimal for current-based metrology in all parameter regimes.

Landauer formula↗

DOE OSTI2022

Proton Scattering in NOvA Test Beam

The NuMI Off-axis $\nu_e$ Appearance (NOvA) experiment is a two-detector, long baseline, neutrino oscillation experiment, which aims to make a determination of the neutrino mass ordering, the octant of $\theta_{23}$, and measure possible charge-parity (CP) violation. Determining these parameters is a step towards answering some of the fundamental questions about neutrinos. Are neutrinos their own antiparticle? Could neutrinos be responsible for the matter-antimatter asymmetry of the universe? How do neutrinos get their mass? Answering these questions requires precise measurements of the parameters that govern how neutrinos behave, namely the mass squared splittings, mixing angles, and possible CP-violating phase factor in the PNMS matrix. Reaching high precision requires minimizing both statistical and systematic errors. As NOvA continues to accumulate data, the sizes of our statistical errors continue to shrink such that in a couple of years they will be comparable to our systematic errors. NOvA's current systematic errors are dominated by energy and calibration uncertainties. The Test Beam program was initiated to address these uncertainties by assessing the detector response in an environment where more parameters of the incoming particles are known. One of the main goals of the Test Beam program is to garner a better understanding of our systematic errors, particularly in energy measurement and detector response, so that the modeling of these parameters can be improved. I studied protons in the Test Beam Detector with momenta around \unit[1]{GeV/c}, the high end of the momentum range relevant to quasielastic neutrino interactions in NOvA. One question this sample can help to answer is if we correctly simulate the fraction of protons that have an inelastic scattering interaction versus ranging out. If protons inelastically scatter at different rates in our simulation and data, the correction applied to the hadronic system when reconstructing neutrino energy could be inaccurate, since events with inelastic scattering will have less visible energy in the detector. This is particularly important for quasielastic $\nu_\mu$ events, which have the lowest hadronic energy resolution, and therefore give us our best measurements of $\Delta m_{32}^2$ and $\theta_{23}$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Intrinsic correlations among characteristics of neutron-rich matter imposed by the unbound nature of pure neutron matter

The unbound nature of pure neutron matter (PNM) requires intrinsic correlations between the symmetric nuclear matter (SNM) EOS parameters (incompressibility K 0 , skewness J 0 and kurtosis I 0 ) and those (slope L, curvature K sym and skewness J sym ) characterizing the symmetry energy independent of any nuclear many-body theory. We investigate these intrinsic correlations and their applications in better constraining the poorly known high-density behavior of nuclear symmetry energy. Several novel correlations connecting the characteristics of SNM EOS with those of nuclear symmetry energy are found. In particular, at the lowest-order of approximations, the bulk parts of the slope L, curvature K sym and skewness J sym of the symmetry energy are found to be L ≈ K 0 /3, K sym ≈ LJ 0 /2K 0 and J sym ≈ I 0 L/3K 0 , respectively. High-order corrections to these simple relations can be written in terms of the small ratios of high-order EOS parameters. The resulting intrinsic correlations among some of the EOS parameters reproduce very nicely their relations predicted by various microscopic nuclear many-body theories and phenomenological models constrained by available data of terrestrial experiments and astrophysical observations in the literature. Here, the unbound nature of PNM is fundamental and the required intrinsic correlations among the EOS parameters characterizing both the SNM EOS and symmetry energy are universal. These intrinsic correlations provide a novel and model-independent tool not only for consistency checks but also for investigating the poorly known high-density properties of neutron-rich matter by using those with smaller uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Activated relaxation in supercooled monodisperse atomic and polymeric WCA fluids: Simulation and ECNLE theory

Here, we combine simulation and Elastically Collective Nonlinear Langevin Equation (ECNLE) theory to study the activated relaxation in monodisperse atomic and polymeric Weeks–Chandler–Andersen (WCA) liquids over a wide range of temperatures and densities in the supercooled regime under isochoric conditions. By employing novel crystal-avoiding simulations, metastable equilibrium dynamics is probed in the absence of complications associated with size polydispersity. Based on a highly accurate structural input from integral equation theory, ECNLE theory is found to describe well the simulated density and temperature dependences of the alpha relaxation time of atomic fluids using a single system-specific parameter, a c , that reflects the nonuniversal relative importance of local cage and collective elastic barriers. For polymer fluids, the explicit dynamical effect of local chain connectivity is modeled at the fundamental dynamic free energy trajectory level based on a different parameter, N c , that quantifies the degree of intramolecular correlation of bonded segment activated barrier hopping. For the flexible chain model studied, a physically intuitive value of N c ≈ 2 results in good agreement between simulation and theory. A direct comparison between atomic and polymeric systems reveals that chain connectivity can speed up activated segmental relaxation due to weakening of equilibrium packing correlations but can slow down relaxation due to local bonding constraints. The empirical thermodynamic scaling idea for the alpha time is found to work well at high densities or temperatures but fails when both density and temperature are low. The rich and subtle behaviors revealed from simulation for atomic and polymeric WCA fluids are all well captured by ECNLE theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Quasinormal modes of naked singularities in presence of nonlinear scalar fields

We study linear perturbations against static spherically symmetric background configurations of general relativity with a real scalar field (SF), which is minimally coupled with gravity; it is nonlinear due to the presence of the self-action potential. The background solutions have a naked singularity at the center of the configuration. The focus is on the stability of the background and fundamental frequencies of the quasinormal modes (QNM) of the axial perturbations in the Regge-Wheeler gauge. The problem is reduced to one hyperbolic master equation with an effective potential 𝑊eff, which turns out to be positive for a general non-negative SF potential; this ensures the linear stability with respect to this kind of perturbations. For numerical simulations, the SF potential was chosen in the power-law form 𝑉⁡(𝜙) ∼ 𝜙 2⁢𝑛 with 2 < 𝑛 ≤40. We extracted the fundamental frequencies of QNM for different 𝑛 and various sets of the background configuration parameters. The results show that even for a small background SF, there is a significant difference between the fundamental frequencies and ones in case of the Schwarzschild background. Furthermore, the results are also compared with the case of the Fisher-Janis-Newman-Winicour background dealing with a massless linear scalar field.

General relativity↗

DOE OSTI2021

Role of Surface Termination in the Metal–Insulator Transition of V 2 O 3 (0001) Ultrathin Films

Surface termination is known to play an important role in determining the physical properties of materials. It is crucial to know how surface termination affects the metal–insulator transition (MIT) of V 2 O 3 films for both fundamental understanding and its applications. By changing growth parameters, we achieved a variety of surface terminations in V 2 O 3 films that are characterized by low-energy electron diffraction (LEED) and photoemission spectroscopy techniques. Depending upon the terminations, our results show that MIT can be partially or fully suppressed near the surface region due to the different fillings of the electrons at the surface and subsurface layers and the change of screening length compared to the bulk. Across MIT, a strong redistribution of spectral weight and its transfer from a high-to-low-binding energy regime is observed in a wide energy scale. Our results show that the total spectral weight in the low-energy regime is not conserved across MIT, indicating a breakdown of the “sum rules of spectral weight”, signature of a strongly correlated system. Such a change in spectral weight is possibly linked to the change in hybridization, lattice volume (i.e., effective carrier density), and the spin degree of freedom in the system that occurs across MIT. We find that MIT in this system is strongly correlation-driven, where the electron–electron interactions play a pivotal role. Furthermore, our results provide better insight into the understanding of the electronic structure of strongly correlated systems and highlight the importance of accounting for surface effects during interpretation of the physical property data mainly using surface-sensitive probes, such as surface resistivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Tuning the Charge Transport Property and Photocatalytic Activity of Anthracene-Based 1D π–d Conjugated Coordination Polymers by Interlayer Stacking

One-dimensional (1D) π–d-conjugated coordination polymers (CCPs) with charge delocalization have attracted significant attention due to their potential application in energy conversion and storage. However, the fundamental understanding of the correlation of their structural parameters with photophysical and photocatalytic properties remains underexplored. Herein, we report three novel Cu-node anthracene-based 1D π–d CCPs with systematic variation of steric groups (Ph > Me > H) at the 9 and 10 position of anthracene (denoted as An Ph , An Me , and An H ), which is aimed at altering the stacking of the polymer chains and its impact on the inter-chain charge transport property. Here, by using the combination of steady-state X-ray absorption spectroscopy, optical transient absorption spectroscopy, X-ray transient absorption spectroscopy, and electrochemical impedance spectroscopy, we show that the linear ligands (An Ph , An Me , and An H ) with different degrees of steric groups (Ph > Me > H) introduced at the 9 and 10 position of anthracene can alter the stacking of the polymer chains and thus impact their crystallinity, charge separation, and charge transport property, which in turn impacts their photocatalytic performance for hydrogen evolution reaction.

1-D-polymer↗

DOE OSTI2022

Computational studies of structural, energetic, and electronic properties of pure Pt and Mo and mixed Pt/Mo clusters: Comparative analysis of characteristics and trends

The added technological potential of bimetallic clusters and nanoparticles, as compared to their pure (i.e., one-component) counterparts, stems from the ability to further fine-tune their properties and, consequently, functionalities through a simultaneous use of the “knobs” of size and composition. The practical realization of this potential can be greatly advanced by the knowledge of the correlations and relationships between the various characteristics of bimetallic nanosystems on the one hand and those of their pure counterparts as well as pure constituent components on the other hand. Here, in this study, we present results of a density functional theory based study of pure Pt n and Mo n clusters aimed at revisiting and exploring further their structural, electronic, and energetic properties. These are then used as a basis for analysis and characterization of the results of calculations on two-component Pt n-m Mo m clusters. The analysis also includes establishing relationships between the properties of the Pt n-m Mo m clusters and those of their Pt n-m and Mo m components. One of the particularly intriguing findings suggested by the calculated data is a linear dependence of the average binding energy per atom in sets of Pt n-m Mo m clusters that have the same fixed number m of Mo atoms and different number n-m of Pt atoms on the fractional content (n-m)/n of Pt atoms. We derive an analytical model that establishes the fundamental basis for this linearity and expresses its parameters—the m-dependent slope and intercept—in terms of characteristic properties of the constituent components, such as the average binding energy per atom of Mo m and the average per-atom adsorption energy of the Pt atoms on Mo m . The conditions of validity and degree of robustness of this model and of the linear relationship predicted by it are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Many-body electronic structure of LaScO 3 by real-space quantum Monte Carlo

We present real space quantum Monte Carlo (QMC) calculations of the scandate LaSc0 3 that proved to be challenging for traditional electronic structure approaches due to strong correlation effects resulting in inaccurate band gaps from DFT and GW methods when compared with existing experimental data. Besides calculating an accurate QMC band gap corrected for supercell size biases and in agreement with numerous experiments, we also predict the cohesive energy of the crystal using the standard fixed-node QMC without any empirical or non-variational parameters. We show that promotion (optical) gap and fundamental gap agree with each other illustrating a clear absence of significant excitonic effects in the ideal crystal. We obtained these results in perfect consistency in two independent tracks that employ different basis sets (plane wave vs. localized gaussians), different codes for generating orbitals (QUANTUM ESPRESSO vs. CRYSTAL), different QMC codes (QMCPACK vs. QWALK) and different high-accuracy pseudopotentials (ccECPs vs. Troullier-Martins) presenting the maturity and consistency of QMC methodology and tools for studies of strongly correlated problems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Fission with Exotic Nuclei (Abbreviated Report)

Nuclear fission is a key mechanism involved in the synthesis of heavy elements in the Cosmos and is the primary explanation for the stability of superheavy elements. Nevertheless, our knowledge of fission remains extremely fragmented. Most experiments have been conducted only on a tiny number of stable actinide nuclei and are often incomplete, leading to gaps in our basic understanding of the process. For many radioactive isotopes, basic fission data such as the charge or mass distribution of the fragments is unknown. These gaps cannot always be filled by simulation alone. Common fission models contain too many free parameters and lack predictive power. In contrast, the fundamental theory of fission under development at LLNL is much more predictive, but its current computational cost is too high to be used extensively for data evaluations. A unique window of opportunity to resolve these limitations has recently opened: the U.S. nuclear science community is ramping up major experimental programs at the Facility for Rare Isotope Beams (FRIB, the DOE flagship facility in low-energy nuclear science), and techniques from machine learning have shown great potential to simplify the use of a fundamental, quantum-mechanical theory of fission. This project has two components. On the experimental side, we acquired and deployed at the HIGS facility a new dual Frisch-Grid ionization chamber to measure correlated fragment-mass, kinetic energy, and angular distributions of fission fragments from induced fission. This new device was used to perform measurements of charge, mass and total kinetic energy of fission fragments in the photofission of 238 U and eight gamma-ray beam energies between 6.2 and 13 MeV, which allowed extracting high-precision independent yields for this reaction. The device was also used to perform measurements of the same quantities in the neutron-induced fission of 234 U with monoenergetic beams of energy between 5 and 8 MeV. In parallel, we collaborated with a team at Commissariat à l’énergie atomique et aux énergies alternatives (CEA) to perform a series of measurements of fission yields in inverse kinematics for the two isotopes of 236 U and 240 Pu. The experiment took place at the Grand Accélérateur National d’Ions Lourds in France in June 2023. The deployment of the VAMOS spectrometer with a new array called PISTA allowed determining the excitation energy of the fissioning system within 1 Mega-electronvolts. The second component of the project involved using deep neural networks to build fast and reliable emulators of our current fission models. In an invited paper published in Frontier in Physics, we showed that autoencoders could successfully compress nuclear wavefunctions in nuclear density functional theory. We achieved a dimensionality reduction of the order of two orders of magnitude while keeping the error in the total energy to less than 0.01%. In a second paper submitted to Physical Review Letters in June 2023 with our collaborators at CEA, we showed that variational autoencoders can learn the collective degrees of freedom driving the fission process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Closed Loop Time and the Topology of Totality

The author suggests a cosmology based on just two principles: (1) no boundaries to spacetime and (2) no physical infinities. On the hypothesis that these are exactly true, and that charge conjugation, parity and time reversal invariance (CPT) is a perfect symmetry at the big bang, answers are provided to many puzzles, such as what happened to the antimatter, what happened before the big bang, and what will happen in the far future? Consequences are that our universe U is closed (with positive curvature) and so the total energy, angular momentum and charge of the universe must be zero. At the big bang a universe-antiuniverse pair, UU¯ is created as a virtual fluctuation in what we may call Outer SpaceTime, along with a vast number of other disconnected universes—the multiverse. The CPT-conjugate U¯ has identical physics (and matter content) to U; other UU¯ pairs in the multiverse have different physics parameters. A consequence is that time at the fundamental particle level à la Feynman must be distinct from thermodynamic time. The UU¯ forms a closed loop.

Albrow, Michael G.↗

DOE OSTI2022

Convective Parameters Derived from Radiosonde Data (SONDEPARAM) Value-Added Product Report

Radiosondes provide fundamental observations of the vertical profile of atmospheric state (pressure, temperature, humidity, and winds), with important implications for subsequent studies on environmental controls on cloud conditions. Within convective cloud environments, there is an increasing demand for additional value-added products (VAPs) to facilitate the use of U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility radiosonde data sets. Such VAPs should provide quick and reliable estimates for several standard radiosonde parameters or quantities of interest using common assumptions, as well as open, flexible code for visualization and user interaction. The Convective Parameters Derived from Radiosonde Data (SONDEPARAM) VAP will apply several robust algorithms used in Wang et al. (2020) for the calculation of useful radiosonde convective cloud parameters, including the convective available potential energy (CAPE), convective inhibition (CIN), and other convective parameters, for several different assumptions regarding the initial parcel characteristics (i.e., surface-based, most unstable, mixed layer). These ARM VAP codes are developed in open, flexible Python formats, with the intention that these parameters/calculations will be incorporated into traditional ARM quick-look radiosonde plotting, yet associated with user-available codes for ease in user reproduction and assumption modification.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

The Impact of Crop Rotation and Spatially Varying Crop Parameters in the E3SM Land Model (ELMv2)

Abstract Earth System Models (ESMs) are increasingly representing agriculture due to its impact on biogeochemical cycles, local and regional climate, and fundamental importance for human society. Realistic large scale simulations may require spatially varying crop parameters that capture crop growth at various scales and among different cultivars, as well as common crop management practices, but their importance is uncertain, and they are often not represented in ESMs. In this study, we examine the impact of using constant versus spatially varying crop parameters using a novel, realistic crop rotation scenario in the Energy Exascale Earth System Model (E3SM) Land Model version 2 (ELMv2). We implemented crop rotation by using ELMv2's dynamic land unit capability, and then calibrated and validated the model against observations collected at three AmeriFlux sites in the US Midwest with corn soybean rotation. The calibrated model closely captured the magnitude and observed seasonality of carbon and energy fluxes across crops and sites. We performed regional simulations for the US Midwest using the calibrated model and found that spatially varying only a few crop parameters across the region, as opposed to using constant parameters, had a large impact, with the carbon fluxes and energy fluxes both varying by up to 40%. These results imply that large scale ESM simulations using spatially invariant crop parameters may result in biased energy and carbon fluxes estimation from agricultural land, and underline the importance of improving human‐earth systems interactions in ESMs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Automatically generated model for light alkene combustion

Light alkenes are common combustion intermediates for a variety of fuels. Therefore, understanding their oxidation and pyrolysis chemistry is key to building detailed mechanisms for heavier fuels. This work was focused on the development and evaluation of a detailed kinetic mechanism suitable for the combustion of light alkenes up to C 4 without the use of tuned parameters, instead, the parameter values come from first principles or direct measurements. The generated mechanism accurately estimates the laminar burning velocity (S u ) and ignition delay time (IDT) of light alkenes available in the literature, which represent fundamental combustion properties at a wide range of conditions. Because each parameter is thought to have a physically realistic value, not tuned to these measurements, the new model could be used as a sub-mechanism in models for other applications. The reaction network was generated with the open-source Reaction Mechanism Generator (RMG) software. Sensitivity analyses were performed under wide ranges of temperatures and pressures, allowing for the identification of the most impactful species and reactions. Based on these, a comprehensive thermochemistry database, including calculations on 550 molecules performed in this work at the CBS-QB3 level of theory, and a kinetic library, including theoretically-derived reaction rates retrieved from the literature, were built and used in the mechanism generation. The developed mechanism was compared against several existing detailed kinetic mechanisms for ethene, propene, 1-butene, 2-butene, and isobutene. Here, the newly generated model is the most accurate among the ones analyzed, in terms of fractional bias and normalized mean square error. Hence, this new model was used to analyze the chemistry of alkene combustion. Key rate coefficients were compared, to identify the cause of deviations between the models and possible areas for further improvements.

09 BIOMASS FUELS↗

DOE OSTI2020

CMB distance priors revisited: effects of dark energy dynamics, spatial curvature, primordial power spectrum, and neutrino parameters

As a physical and sufficient compression of the full CMB data, the CMB distance priors, or shift parameters, have been widely used and provide a convenient way to include CMB data when obtaining cosmological constraints. In this paper, we revisit this data vector and examine its stability under different cosmological models. We find that the CMB distance priors are an accurate substitute for the full CMB data when probing dark energy dynamics. This is true when the primordial power spectrum model is directly generalized from the power spectrum of the model used in the derivation of the distance priors from the CMB data. We discover a difference when a non-flat model with the untilted primordial inflation power spectrum is used to measure the distance priors. This power spectrum is a radical change from the more conventional tilted primordial power spectrum and violates fundamental assumptions for the reliability of the CMB shift parameters. We also investigate the performance of CMB distance priors when the sum of neutrino masses Σm ν and the effective number of relativistic species N eff are allowed to vary. Our findings are consistent with earlier results: the neutrino parameters can change the measurement of the sound horizon from CMB data, and thus the CMB distance priors. We find that when the neutrino model is allowed to vary, the cold dark matter density ω c and N eff need to be included in the set of parameters that summarize CMB data, in order to reproduce the constraints from the full CMB data. As a result, we present an updated and expanded set of CMB distance priors which can reproduce constraints from the full CMB data within 1σ, and are applicable to models with massive neutrinos, as well as non-standard cosmologies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

A novel methodology for gamma-ray spectra dataset procurement over varying standoff distances and source activities

The adoption of machine learning approaches for gamma-ray spectroscopy has received considerable attention in the literature. Many studies have investigated the deployment of various algorithm architectures to a specific task. However, little attention has been afforded to the development of the datasets leveraged to train the models. Such training datasets typically span a set of environmental or detector parameters to encompass a problem space of interest to a user. Variations in these measurement parameters will also induce fluctuations in the detector response, including expected pile-up and ground scatter effects. Fundamental to this work is the understanding that 1) the underlying spectral shape varies as the measurement parameters change and 2) the statistical uncertainties associated with two spectra impact their level of similarity. While previous studies attribute some arbitrary discretization to the measurement parameters for the generation of their synthetic training data, this work introduces a principled methodology for efficient spectral-based discretization of a problem space. A signal-to-noise ratio (SNR) respective spectral comparison measure and a Gaussian Process Regression (GPR) model are used to predict the spectral similarity across a range of measurement parameters. This innovative approach effectively showcased its capability by dividing a problem space, ranging from 5 cm to 100 cm standoff distances and 5 μCi–100 μCi of 137 Cs, into three unique combinations of measurement parameters. The findings from this work will aid in creating more robust datasets, which incorporate many possible measurement scenarios, reduce the number of required experimental test set measurements, and possibly enable experimental training data collection for gamma-ray spectroscopy.

data science↗

DOE OSTI2020

Two-color-driven enhanced high-order harmonic generation in solids

We theoretically investigate the emission of high-harmonic (HH) radiation in model crystals by bichromatic few-cycle driving pulses that are composed as the phase-coherent superposition of a mid-infrared fundamental pulse and its second harmonic. Adjusting the model-crystal parameters to reproduce the lowest band gap of MgO, we examine the extent to which distinct domains of the HH spectrum can be controlled and enhanced by tuning the temporal profile of the bichromatic driving laser electric field. We change the driving-pulse shape by varying its fundamental-versus-second-harmonic pulse amplitude ratio and delay, while keeping the energy of the driving laser pulse fixed. For suitable amplitude ratios and delays, we find an up to fivefold enhancement of the spectral HH yield and significant shifts of the HH cutoff frequency.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2021

In situ synchrotron diffraction and modeling of non-equilibrium solidification of a MnFeCoNiCu alloy

The solidification mechanism and segregation behavior of laser-melted Mn 35 Fe 5 Co 20 Ni 20 Cu 20 was firstly investigated via in situ synchrotron x-ray diffraction at millisecond temporal resolution. The transient composition evolution of the random solid solution during sequential solidification of dendritic and interdendritic regions complicates the analysis of synchrotron diffraction data via any single conventional tool, such as Rietveld refinement. Therefore, a novel approach combining a hard-sphere approximation model, thermodynamic simulation, thermal expansion measurement and microstructural characterization was developed to assist in a fundamental understanding of the evolution of local composition, lattice parameter, and dendrite volume fraction corresponding to the diffraction data. This methodology yields self-consistent results across different methods. Via this approach, four distinct stages were identified, including: (I) FCC dendrite solidification, (II) solidification of FCC interdendritic region, (III) solid-state interdiffusion and (IV) final cooling with marginal diffusion. It was found out that in Stage I, Cu and Mn were rejected into liquid as Mn 35 Fe 5 Co 20 Ni 20 Cu 20 solidified dendritically. During Stage II, the lattice parameter disparity between dendrite and interdendritic region escalated as Cu and Mn continued segregating into the interdendritic region. After complete solidification, during Stage III, the lattice parameter disparity gradually decreases, demonstrating a degree of composition homogenization. The volume fraction of dendrites slightly grew from 58.3 to 65.5%, based on the evolving composition profile across a dendrite/interdendritic interface in diffusion calculations. Postmortem metallography further confirmed that dendrites have a volume fraction of 64.7 ± 5.3% in the final microstructure.

36 MATERIALS SCIENCE↗