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DOE OSTI2021

The Tianlai dish pathfinder array: design, operation, and performance of a prototype transit radio interferometer

ABSTRACT The Tianlai Dish Pathfinder Array is a radio interferometer designed to test techniques for 21 cm intensity mapping in the post-reionization universe as a means for measuring large-scale cosmic structure. It performs drift scans of the sky at constant declination. We describe the design, calibration, noise level, and stability of this instrument based on the analysis of about 5% of 6200 h of on-sky observations through 2019 October. Beam pattern determinations using drones and the transit of bright sources are in good agreement, and compatible with electromagnetic simulations. Combining all the baselines, we make maps around bright sources and show that the array behaves as expected. A few hundred hours of observations at different declinations have been used to study the array geometry and pointing imperfections, as well as the instrument noise behaviour. We show that the system temperature is below 80 K for most feed antennas and that noise fluctuations decrease as expected with integration time, at least up to a few hundred seconds. Analysis of long integrations, from 10 nights of observations of the North Celestial Pole (NCP), yielded visibilities with amplitudes of 20–30 mK, consistent with the expected signal from the NCP radio sky with ${\lt}10\,$ mK precision for 1 MHz × 1 min binning. Hi-pass filtering the spectra to remove smooth spectrum signal yields a residual consistent with zero signal at the $0.5\,$ mK level.

(cosmology:) large-scale structure of the Universe↗

DOE OSTI2020

The Role of Dimer Formation in the Nucleation of Superlattice Transformations and Its Impact on Disorder

The formation of defect-free two-dimensional nanocrystal (NC) superstructures remains a challenge as persistent defects hinder charge delocalization and related device performance. Understanding defect formation is an important step toward developing strategies to mitigate their formation. However, specific mechanisms of defect formation are difficult to determine, as superlattice phase transformations that occur during fabrication are quite complex and there are a variety of factors influencing the disorder in the final structure. Here, we use Molecular Dynamics (MD) and electron microscopy in concert to investigate the nucleation of the epitaxial attachment of lead chalcogenide (PbX, where X = S, Se) NC assemblies. We use an updated implementation of an existing reactive force field in an MD framework to investigate how initial orientational (mis)alignment of the constituent building blocks impacts the final structure of the epitaxially connected superlattice. This Simple Molecular Reactive Force Field (SMRFF) captures both short-range covalent forces and long-range electrostatic forces and allows us to follow orientational and translational changes of NCs during superlattice transformation. Our simulations reveal how robust the oriented attachment is with regard to the initial configuration of the NCs, measuring its sensitivity to both in-plane and out-of-plane misorientation. We show that oriented attachment nucleates through the initial formation of dimers, which corroborate experimentally observed structures. We present high-resolution structural analysis of dimers at early stages of the superlattice transformation and rationalize their contribution to the formation of defects in the final superlattice. Collectively, the simulations and experiments presented in this paper provide insights into the nucleation of NC oriented attachment, the impact of the initial configuration of NCs on the structural fidelity of the final epitaxially connected superlattice, and the propensity to form commonly observed defects, such as missing bridges and atomic misalignment in the superlattice due to the formation of dimers. Here, we present potential strategies to mitigate the formation of superlattice defects.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A Statistical Framework for Evaluating Rain Microphysics in Model Simulations and Disdrometer Observations

Abstract Statistical analyses of a large disdrometer data set and a diverse set of model simulations for convection using the Regional Atmospheric Modeling System were conducted, with the mutual goal of providing insights into precipitation formation and microphysical processes. We demonstrate that a two‐moment bulk microphysical model successfully captures the dominant observed modes of variability in rainfall related to rainfall intensity and raindrop size distributions. The model reproduced the general distribution of observed precipitation groups (PGs) derived from Principal Component Analysis. The multi‐variable analysis also uncovered some shortcomings in the model as well as limitations of the disdrometer data. The model solutions were constrained in their predicted drop size distributions (DSDs) due to the fixed DSD parameters assumed in a two‐moment microphysics scheme. A case study from the Mid‐latitude Continental Clouds and Convection Experiment field project demonstrated how model results can be used to contextualize the disdrometer observations which are limited in sample size, spatial coherence, and detection of small drops and low drop concentrations. The case study also showed that the spatial patterns of the statistically derived PGs revealed by the model are consistent with the hypothesized microphysical processes that determine surface rain DSDs. This work demonstrates how leveraging the strengths of observations and models together can improve our understanding and representation of rain microphysical processes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

The influence of irregular terrain on infrasonic propagation in the troposphere

The relations describing the reflection of three-dimensional acoustic ray paths impinging on a non-flat surface are derived and used to approximate the propagation of infrasonic signals over irregular terrain in the geometric limit. The influence of non-flat ground is strongest for those paths that reflect off the surface multiple times, such as those in the tropospheric waveguide; however, notable differences in source and receiver elevations for stratospheric and thermospheric paths can produce notable differences in travel times and arrival amplitudes. The interaction of ray paths with topographical features is investigated using a simple hill to demonstrate the impact of topography on propagation within an azimuthal plane, as well as cases in which the ground surface interaction deflects the path out of the azimuthal plane. Finally, broadband waveform predictions are compared with observations for an event in the western U.S., and a statistical analysis of scattering losses due to interaction with topography in the limit of geometric acoustics is used to improve the agreement between predicted and observed infrasonic signals.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Tropospheric and stratospheric wildfire smoke profiling with lidar: mass, surface area, CCN, and INP retrieval

We present retrievals of tropospheric and stratospheric height profiles of particle mass, volume, surface area, and number concentrations in the case of wildfire smoke layers as well as estimates of smoke-related cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations from backscatter lidar measurements on the ground and in space. Conversion factors used to convert the optical measurements into microphysical properties play a central role in the data analysis, in addition to estimates of the smoke extinction-to-backscatter ratios required to obtain smoke extinction coefficients. The set of needed conversion parameters for wildfire smoke is derived from AERONET observations of major smoke events, e.g., in western Canada in August 2017, California in September 2020, and southeastern Australia in January–February 2020 as well as from AERONET long-term observations of smoke in the Amazon region, southern Africa, and Southeast Asia. The new smoke analysis scheme is applied to CALIPSO observations of tropospheric smoke plumes over the United States in September 2020 and to ground-based lidar observation in Punta Arenas, in southern Chile, in aged Australian smoke layers in the stratosphere in January 2020. These case studies show the potential of spaceborne and ground-based lidars to document large-scale and long-lasting wildfire smoke events in detail and thus to provide valuable information for climate, cloud, and air chemistry modeling efforts performed to investigate the role of wildfire smoke in the atmospheric system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Measurement of single- and double-polarization observables in the photoproduction of 𝜋 + ⁢𝜋 − meson pairs off the proton using CLAS at Jefferson Laboratory

The photoproduction of 𝜋 + ⁢𝜋 − meson pairs off the proton has been studied in the reaction 𝛾⁢𝑝→𝑝⁢𝜋 + ⁢𝜋 − using the CEBAF Large Acceptance Spectrometer (CLAS) and the frozen-spin target (FROST) in Hall B at the Thomas Jefferson National Accelerator Facility. For the first time, the beam and target asymmetries, 𝐼 𝑠,𝑐 and 𝑃 𝑥,𝑦 , have been measured along with the beam-target double-polarization observables, 𝑃$^{𝑠,𝑐}_{𝑥,𝑦}$, using a transversely polarized target with center-of-mass energies ranging from 1.51 GeV up to 2.04 GeV. These data and additional 𝜋⁢𝜋 photoproduction observables from CLAS and experiments elsewhere were included in a partial-wave analysis within the Bonn-Gatchina framework. Significant contributions from 𝑠-channel resonance production are observed in addition to 𝑡-channel exchange processes. The data indicate significant contributions from 𝑁* and Δ* resonances in the third and fourth resonance regions.

QCD phenomenology↗

DOE OSTI2021

Modeling Buried Object Brightness and Visibility for Ground Penetrating Radar

Comparing the observed brightness of various buried objects is a straightforward way to characterize the performance of a ground penetrating radar (GPR) system. However, a limitation arises. A simple comparison of buried object brightness values does not disentangle the effects of the GPR system itself from the system's operating environment and the objects being observed. Therefore, with brightness values exhibiting an unknown synthesis of systemic, environmental, and object factors, GPR system analysis becomes a convoluted affair. In this work, we use an experimentally collected dataset of over 25,000 object observations from five different multistatic radar arrays to develop models of buried object brightness and control for these various effects. Additionally, our modeling efforts provide a means for quantifying the relative brightness of GPR systems, the objects they detect, and the physical properties of those objects that influence observed brightness. To evaluate the models' performance on new object observations, we repeatedly simulate fitting them to half the dataset and predicting the observed brightness values of the unseen half. In addition, we introduce a method for estimating the probability that individual observations constitute a visible object, which aids in failure analysis, performance characterization, and dataset cleaning.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Novel reusable animal model for comparative evaluation of in vivo growth and protein-expression of Escherichia coli O157 strains in the bovine rumen

Previously, we had demonstrated that Escherichia coli O157:H7 (O157) strain 86–24 expresses proteins involved in survival rather than virulence in vitro in rumen fluid from dairy cattle limit fed a maintenance diet. Here, we verified if this observation would be true for different O157 strains grown in vitro in rumen fluid from, and in vivo in the rumen of, animals on contrasting maintenance (high fiber) and lactation (high energy-protein) diets usually limit fed to dairy cattle. For the in vivo studies, an economical, novel, reusable and non-terminal rumen-fistulated animal model permitting simultaneous evaluation of multiple bacterial strains in the bovine rumen was developed. All experiments were conducted in duplicate using different animals to account for host-related variations. The O157 strains included, 86–24, EDL933 and the super shed SS-17. E. coli Nal R (#5735), derived from a bovine intestinal commensal E. coli, was included as a control. As expected, diet influenced ruminal pH and volatile fatty acid (VFA) composition. The pH ranged from 6.2–7.0 and total VFA concentrations from 109–141 μM/ml, in animals fed the maintenance diet. In comparison, animals fed the lactation diet had a ruminal pH ranging between 5.18–6.0, and total VFA of 125–219 μM/ml. Strain dependent differences in O157 recovery from the rumen fluid of cattle fed either diet was observed, both in vitro and in vivo, with O157 strains 86–24 and EDL933 demonstrating similar survival patterns. Analysis of the O157 proteomes expressed in the rumen fluid/rumen verified previous observations of adaptive responses. Any difference in the adaptive response was mainly influenced by the animal’s diet and growth conditions (in vitro and in vivo) and not the O157 strain. These new insights into the O157 responses could help formulate modalities to control O157 across strains in cattle at all stages of husbandry.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

The 3D clustering of Lyman Alpha Emitters measured with DESI

We present a clustering analysis of Lyman-$α$ emitters (LAEs) using spectroscopic observations from the Dark Energy Spectroscopic Instrument (DESI) of candidates selected from the Blanco/DECam Intermediate-Band Imaging Survey (IBIS). We measure the two-point correlation function and the power spectrum, including cross-correlations with DESI quasars. Using both analytical and halo occupation distribution (HOD) simulation-based modeling, we find a linear bias of $b \sim 2.31$--$2.62$ for LAEs over the redshift range $2.26 < z < 3.41$. The analytical modeling also provides constraints on the strength of radiative transfer effects, while the HOD analysis characterizes the LAE-halo connection across multiple models. Finally, we quantify the magnitude of non-perturbative clustering effects such as Fingers of God in the LAE population, providing essential input for the accurate modeling of LAE-based cosmological analyses in forthcoming high-redshift surveys such as DESI-II.

Ebina, H. [UC, Berkeley; LBL, Berkeley] (ORCID:000↗

DOE OSTI2025

Analysis of a Disturbance Event with Inverter-Based Resources Using EMT Simulations

Increasing penetration of inverter-based resources (IBRs) necessitates newer methods of planning and analysis of disturbances. The existing phasor-domain transient stability (TS) analysis may not capture the dynamics of IBRs during fault events. Here, in this paper, electromagnetic transient (EMT) simulations using high-fidelity detailed model of power grid and one of the affected photovoltaic (PV) plants during the Angeles Forest disturbance in 2018 are performed. In these simulations, the processes to develop EMT models of power grid from traditional phasor-domain TS data and PV plant from collected data are described. Thereafter, using these simulations, the response of the PV plant during the fault event in 2018 is replicated and a sensitivity analysis is performed. The sensitivity analysis consists of making changes to the components within the PV plant and in the power grid to evaluate the impact they have on the response observed by the PV plant during the fault event. This analysis provides an understanding of the components that impact the operation of a PV plant during fault events and provide guidance to system planners on the studies that need to be performed to maintain a reliable power grid as new IBR plants are integrated.

42 ENGINEERING↗

DOE OSTI2020

H i asymmetries in LVHIS, VIVA, and HALOGAS galaxies

ABSTRACT We present an analysis of morphological, kinematic, and spectral asymmetries in observations of atomic neutral hydrogen (H i) gas from the Local Volume H i Survey (LVHIS), the VLA Imaging of Virgo in Atomic Gas (VIVA) survey, and the Hydrogen Accretion in Local Galaxies Survey. With the aim of investigating the impact of the local environment density and stellar mass on the measured H i asymmetries in future large H i surveys, we provide recommendations for the most meaningful measures of asymmetry for use in future analysis. After controlling for stellar mass, we find signs of statistically significant trends of increasing asymmetries with local density. The most significant trend we measure is for the normalized flipped spectrum residual (Aspec), with mean LVHIS and VIVA values of 0.204 ± 0.011 and 0.615 ± 0.068 at average weighted 10th nearest-neighbour galaxy number densities of log (ρ10/Mpc−3) = −1.64 and 0.88, respectively. Looking ahead to the Widefield ASKAP L-band Legacy All-sky Blind survey on the Australian Square Kilometre Array Pathfinder, we estimate that the number of detections will be sufficient to provide coverage over 5 orders of magnitude in both local density and stellar mass increasing the dynamic range and accuracy with which we can probe the effect of these properties on the asymmetry in the distribution of atomic gas in galaxies.

Reynolds, T. N.↗

DOE OSTI2023

Experimental Observations of the Topology of Convolutional Neural Network Activations

Topological data analysis (TDA) is a branch of computational mathematics, bridging algebraic topology and data science, that provides compact, noise-robust representations of complex structures. Deep neural networks (DNNs) learn millions of parameters associated with a series of transformations defined by the model architecture resulting in high-dimensional, difficult to interpret internal representations of input data. As DNNs become more ubiquitous across multiple sectors of our society, there is increasing recognition that mathematical methods are needed to aid analysts, researchers, and practitioners in understanding and interpreting how these models' internal representations relate to the final classification. In this paper we apply cutting edge techniques from TDA with the goal of gaining insight towards interpretability of convolutional neural networks used for image classification. We use two common TDA approaches to explore several methods for modeling hidden layer activations as high-dimensional point clouds, and provide experimental evidence that these point clouds capture valuable structural information about the model's process. First, we demonstrate that a distance metric based on persistent homology can be used to quantify meaningful differences between layers and discuss these distances in the broader context of existing representational similarity metrics for neural network interpretability. Second, we show that a mapper graph can provide semantic insight as to how these models organize hierarchical class knowledge at each layer. These observations demonstrate that TDA is a useful tool to help deep learning practitioners unlock the hidden structures of their models.

topological data analysis, deep learning↗

DOE OSTI2026

Characterization of the Polarization Beam Response of SPT-3G Using Point Sources

Precise measurements of cosmic microwave background (CMB) polarization require rigorous control of instrumental systematics. For the South Pole Telescope's third-generation camera (SPT-3G), which observes in three bands centered near 95, 150, and 220 GHz, accurate beam characterization is critical for interpreting the polarized mm-wave sky. We present direct measurements of SPT-3G's polarized beam response from observations of 100 bright extragalactic point sources. Previous SPT-3G power spectrum analyses introduced a phenomenological parameter, $β_{\rm pol}$, to describe the polarization preserved in beam sidelobes, and found evidence for significant depolarization from the requirement of inter-frequency polarization power spectrum consistency. Our direct measurements yield $β_{\rm pol}=0.89\pm0.10$ at 95 GHz, $1.08\pm0.10$ at 150 GHz, and $0.90\pm0.22$ at 220 GHz, indicating minimal sidelobe depolarization. We validate these results with systematic tests of posterior sampling versus bootstrap resampling, real-space versus Fourier-space analysis, temperature-to-polarization leakage handling, covariance determination, and source selection. Compared to values inferred from previous cosmological analyses, our results differ by an effective $1.3σ$. This apparent discrepancy is model dependent, because the point source analysis derives much of its $β_{\rm pol}$ constraining power from higher multipoles than the power spectrum analysis. These measurements therefore admit three explanations for the frequency-dependent residuals observed in the power spectrum analysis: a statistical fluctuation, the need for more sophisticated polarized beam models, or systematics other than beam depolarization.

de Haan, T. [KEK, Tsukuba]↗

DOE OSTI2022

Rapid attribution analysis of the extraordinary heat wave on the Pacific coast of the US and Canada in June 2021

Towards the end of June 2021, temperature records were broken by several degrees Celsius in several cities in the Pacific Northwest areas of the US and Canada, leading to spikes in sudden deaths and sharp increases in emergency calls and hospital visits for heat-related illnesses. Here we present a multi-model, multi-method attribution analysis to investigate the extent to which human-induced climate change has influenced the probability and intensity of extreme heat waves in this region. Based on observations, modelling and a classical statistical approach, the occurrence of a heat wave defined as the maximum daily temperature (TXx) observed in the area 45–52 °N, 119–123 °W, was found to be virtually impossible without human-caused climate change. The observed temperatures were so extreme that they lay far outside the range of historical temperature observations. This makes it hard to state with confidence how rare the event was. Using a statistical analysis that assumes that the heat wave is part of the same distribution as previous heat waves in this region led to a first-order estimation of the event frequency of the order of once in 1000 years under current climate conditions. Using this assumption and combining the results from the analysis of climate models and weather observations, we found that such a heat wave event would be at least 150 times less common without human-induced climate change. Also, this heat wave was about 2 °C hotter than a 1-in-1000-year heat wave would have been in 1850–1900, when global mean temperatures were 1.2 °C cooler than today. Looking into the future, in a world with 2 °C of global warming (0.8 °C warmer than today), a 1000-year event would be another degree hotter. Our results provide a strong warning: our rapidly warming climate is bringing us into uncharted territory with significant consequences for health, well-being and livelihoods. Adaptation and mitigation are urgently needed to prepare societies for a very different future.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

High-resolution rovibrational spectroscopy of trans -formic acid in the v 1 OH stretching fundamental: Dark state coupling and evidence for charge delocalization dynamics

High-resolution infrared (IR) reduced-Doppler absorption spectra of jet-cooled gas phase trans-formic acid in the v 1 OH stretching fundamental region are reported for the first time, obtained by supersonically expanding trans- formic acid/Ar mixtures through a slit jet nozzle source and rotationally cooling to T rot ≈ 10.9(5) K, with ab- sorption signals recorded by high-resolution difference-frequency IR absorption spectroscopy. Two a/b-type rovibrational bands of comparable intensity, one ~10-fold weaker b-type band, and one ~6-fold weaker a-type band are observed, with vibrational band origins at 3570.493(5), 3566.793(5), 3560.032(9), and 3534.6869(2) cm –1 , respectively. Based on previous Raman jet spectroscopic work by Nejad and Sibert [A. Nejad, E.L. Sibert III, The Raman jet spectrum of trans-formic acid and its deuterated isotopologs: Combining theory and experi- ment to extend the vibrational database, J. Chem. Phys. 154(6) (2021) 064301.], these four rovibrational bands have been assigned to v 1 , (v 2 + v 7 ), (v 6 + 2v 7 + 2v 9 ), and 2v 3 , respectively. Specifically, two of the three upper dark states (2 1 7 1 (a') and 6 1 7 2 9 2 (a')) are close enough to the “bright” 1 1 (a') state to facilitate strong anharmonic resonance interactions, which results in intensity mixing into the two zero-order bands that would otherwise be “dark”. Furthermore, our high-resolution spectral analysis reveals that there are local rotational crossings be- tween these zero-order 1 1 and 2 1 7 1 states resulting in extra lines (i.e., some upper levels in the nominally v 1 band have majority zero-order 2 1 7 1 state character). This motivates development of a 3 coupled state (1 1 , 2 1 7 1 , and 6 1 7 2 9 2 ) picture to aid in the spectral analysis, which is able to match all 3 observed band origins and relative band intensities, as well as indicate the necessity of multistate (> 2) coupling. Though limited by range of J and Ka levels (J’ ≤ 9 and K a ’ ≤ 3) populated at supersonic jet temperatures, this work offers first precision spec- troscopic analysis of trans-formic acid in the v 1 OH stretch region, which should aid in assignment of the more complete yet highly congested room temperature FTIR spectra. Lastly, and in sharp contrast to the spectral complexity in the three predominantly b-type bands, the lone a-type 2v 3 rovibrational band at 3534.6869(2) cm –1 is well described by a simple, rigid asymmetric top Hamiltonian.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Nonlinear Ensemble Filtering with Diffusion Models: Application to the Surface Quasigeostrophic Dynamics

The intersection between classical data assimilation methods and novel machine learning techniques has attracted significant interest in recent years. Here, we explore another promising solution in which diffusion models are used to formulate a robust nonlinear ensemble filter for sequential data assimilation. Unlike standard machine learning methods, the proposed ensemble score filter (EnSF) is completely training free and can efficiently generate a set of analysis ensemble members. Here, in this study, we apply the EnSF to a surface quasigeostrophic model and compare its performance against the popular local ensemble transform Kalman filter (LETKF), which makes Gaussian assumptions in the analysis step. Numerical tests demonstrate that EnSF maintains stable performance in the absence of localization and for a variety of experimental settings. We find that while LETKF maintains optimal performance in the case of linear observations of the entire state and a perfect model, EnSF shows improvements over LETKF when nonlinear observations are assimilated and the system is subject to unexpected model errors. A spectral decomposition of the analysis results in this nonlinear observation regime shows that the largest improvements over LETKF occur at large scales (small wavenumbers), where LETKF lacks sufficient ensemble spread. Overall, this initial application of EnSF to a geophysical model of intermediate complexity motivates further development of the algorithm for more realistic problems.

Artificial intelligence↗

DOE OSTI2019

Microstructure Evolution During Controlled Solidification of “Fe{sub 2}O{sub 3}”-CaO-SiO{sub 2} Liquids in Air

The principal chemical components in iron ore sintering are Fe{sub 2}O{sub 3}, CaO, and SiO{sub 2}. This sintering process consists of three key steps: heating, holding at peak temperature, and cooling. During the cooling stage, a liquid oxide solidifies to form the final sinter microstructures. To investigate the fundamental processes taking place during the cooling of sinters, a new experimental technique has been developed that allows the stages of solidification to be determined in isolation, rather than inferred from the final microstructures. Fe{sub 2}O{sub 3}-CaO-SiO{sub 2} oxide samples of a bulk composition having a CaO/SiO{sub 2} mass ratio of 3.46 and 73.2 wt pct Fe{sub 2}O{sub 3} were cooled in air from 1623 K (1350 °C) at 2 K/s, quenched at 5 K temperature intervals from 1533 K to 1453 K (1260 °C to 1180 °C), and analyzed using Electron Probe Micro X-Ray Analysis (EPMA). During cooling, four distinct stages were observed, consisting of the phase assemblages Liquid + Hematite (I), Liquid + Hematite + C{sub 2}S(II), Liquid + C{sub 2}S + CF{sub 2}(III), and C{sub 2}S + CF{sub 2} + CF (IV). This solidification sequence differs from that predicted under equilibrium and Scheil–Gulliver Cooling. Importantly, no Silico-Ferrite of Calcium (SFC) phase was observed to form on solidification of the liquid. Based on the microstructures formed and liquid compositions, measured by EPMA, it was demonstrated that kinetic factors play a major role in determining the phases and microstructures formed under the conditions investigated.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Multisublattice cluster expansion study of short-range ordering in iron-substituted strontium titanate

Owing to the challenges in obtaining realistic atomic configurations in large chemical phase spaces, it is not straightforward to describe structure–property relations in materials exhibiting configurational disorder. One example is iron-substituted strontium titanate (SrTi 1–x Fe x O 3–d , STF), a promising perovskite-derivative cathode material in solid oxide fuel cells that exhibits full solid solubility 0 ≤ x ≤ 1 and a tendency to exhibit short-range order. Here we demonstrate a multisublattice cluster expansion (CE) framework and apply it to STF across the full composition range. The CE approach is distinct from more traditional CE formulations in that clusters are defined explicitly by the chemical species distributed among multiple sublattices, rather than via cluster functions of occupation variables with decoration. The modified CE approach makes it easy to distinguish meaningful chemical interactions that are harder to extract from conventional CE, since for the latter chemical identity in a cluster is expressed as a product of site occupations. The least absolute shrinkage and selection operator (LASSO) is implemented as a regression analysis tool to select key clusters and avoid overfitting. We demonstrate this formulation on STF, and show that it can accurately predict configurational energies in comparison to conventional CE. From the key clusters, we identify that short-range ordering between substitutional Fe and oxygen vacancies (V O ) results in the formation of Fe–VO strings. In addition, we consider the stability of STF through CE-based Monte Carlo (MC) simulations and confirm the presence of superstructures that were previously observed in transmission electron microscopy. In this work, analysis of atomic configurations from MC samples reveals variations in the oxidation state of Fe atoms, which can be explained by the ordering tendency of Fe and V O . The cluster description and selection formalism described here may be applied to other disordered multisublattice systems for accurate and efficient material modeling.

36 MATERIALS SCIENCE↗