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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Feature review of photovoltaic modeling software utilizing blind performance assessment

While confidence in photovoltaic (PV) modeling software has always been essential, the rapid pace of new PV plant developments makes accuracy and credibility more critical than ever. Independent assessments, particularly through blind modeling comparisons, are therefore necessary to ensure unbiased benchmarking across PV modeling software. Previous studies have been limited by a narrow range of models compared, anonymized results, or system size. This study presents results from the first-ever onymous blind modeling comparison, evaluated using both lab- and utility-scale fixed-tilt, monofacial, south-facing systems at sub-hourly time intervals. Seven commercially used PV software tools were compared: 3E SynaptiQ, PlantPredict, PVsyst, RatedPower, SAM, SolarFarmer, and Solargis Evaluate. Predictions were submitted directly by software representatives, providing unique insights into each software’s implementation and resulting prediction behavior. Notable features, including plane-of-array (POA) transposition model, module temperature model, shading model, and performance model were analyzed and compared. Four summary tables compile these features of the software, serving as a resource to help users understand the methodological differences and select the most suitable software for their applications. The software tools show deviations from mean error in annual yield up to 2.5 % in the lab-scale system, increasing to 6.0 % for the utility-scale system. These differences arise from a combination of user decisions and the inherent behavior of the software, indicating the need for continuous and rigorous validation of modeling methods using these software tools against complex, real-world systems.

14 SOLAR ENERGY↗
DOE OSTI2026

Evaluation and optimization of flow boiling frictional pressure drop correlations using the data from traditional and next-generation refrigerants in a micro-fin tube

This study presents an experimental evaluation and optimization of flow boiling frictional pressure drop correlations for conventional and next-generation refrigerants in a horizontal micro-fin tube, with particular emphasis on the newly emerging refrigerant blends R-454C and R-455A, for which pressure-drop data in enhanced tubes remain limited. Experiments were conducted with R-410A, R-454C, R-455A, R-134a, R-1234yf, and R-1234ze(E) in a copper micro-fin tube with an inner diameter of 8.468 mm, over mass fluxes ranging from 100 to 300 kg/(m²·s) depending on the refrigerant, and evaporation temperatures of 7, 12, and 14 °C. Frictional pressure gradients were determined from measured total pressure drops after subtracting acceleration pressure drop, and the resulting database was used to assess four existing models: Kuo and Wang (1996), Cavallini et al. (1997), Goto et al. (2001), and Diani et al. (2014). The measured frictional pressure gradient increased with vapor quality and mass flux for all refrigerants and increased further at lower evaporation temperatures, with the overall trend strongly related to liquid viscosity. Among the four correlations, the Goto et al. (2001) model provided the best overall agreement with the measured data before optimization. To further improve prediction accuracy, the Kuo and Wang (1996) and Goto et al. (2001) models were optimized using the complete experimental database. After optimization, both models reduced the overall mean absolute deviation to below 15%, while the optimized Goto et al. (2001) model maintained the best and most consistent overall performance. The results provide new pressure-drop data for next-generation refrigerants and demonstrate that parameter optimization can significantly enhance the applicability of existing micro-fin-tube correlations.

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗
DOE OSTI2024

Interactions in misaligned layered materials

The deliberate introduction of stacking faults has been found to induce properties markedly distinct from those of perfectly stacked particles or sheets, with even minute deviations leading to significant alterations in material characteristics. In this review article, we discuss the effects of stacking faults – both linear and rotational – on surface structures influencing ion adsorption, particle–particle affinity governing crystal growth, friction, and electronic properties. In conclusion, our comprehensive overview sheds light on the multifaceted impact of stacking faults on these phenomena, offering insights that bridge multiple disciplines, and provides numerous interdisciplinary research questions, paving the way for future innovations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A versatile machine learning workflow for high-throughput analysis of supported metal catalyst particles

Accurate and efficient characterization of nanoparticles (NPs), particularly regarding particle size distribution, is essential for advancing our understanding of their structure-property relationship and facilitating their design for various applications. In this study, we introduce a novel two-stage artificial intelligence (AI)-driven workflow for NP analysis that leverages prompt engineering techniques from state-of-the-art single-stage object detection and large-scale vision transformer (ViT) architectures. This methodology is applied to transmission electron microscopy (TEM) and scanning TEM (STEM) images of heterogeneous catalysts, enabling high-resolution, high-throughput analysis of particle size distributions for supported metal catalyst NPs. The model's performance in detecting and segmenting NPs is validated across diverse heterogeneous catalyst systems, including various metals (Ru, Cu, PtCo, and Pt), supports (silica (SiO 2 ), γ-alumina (γ-Al 2 O 3 ), and carbon black), and particle diameter size distributions with mean and standard deviations ranging from 1.6 ± 0.2 nm to 9.7 ± 4.6 nm. The proposed machine learning (ML) methodology achieved an average F1 overlap score of 0.91 ± 0.01 and demonstrated the ability to disentangle overlapping NPs anchored on catalytic support materials. The segmentation accuracy is further validated using the Hausdorff distance and robust Hausdorff distance metrics, with the 90th percent of the robust Hausdorff distance showing errors within 0.4 ± 0.1 nm to 1.4 ± 0.6 nm. In conclusion, our AI-assisted NP analysis workflow demonstrates robust generalization across diverse datasets and can be readily applied to similar NP segmentation tasks without requiring costly model retraining.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Active control of laser beam pointing for the Zettawatt-Equivalent Ultrashort pulse laser System: a proof-of-principle study with 16-inch optics

We present a proof-of-principle study of active beam-pointing control for the Zettawatt-Equivalent Ultrashort pulse laser System (ZEUS) using a piezo-actuated 16-inch mirror. To the best of our knowledge, this is the largest actively controlled mirror reported in a high-power laser system. A simple proportional feedback control was implemented based on a field-programmable gate array, which reduced the standard deviation of beam-pointing fluctuations by 91% to 0.075 μrad in the horizontal direction and by 78% to 0.25 μrad in the vertical direction. We also demonstrated the elimination of long-term pointing jitter caused by temperature drift using the same apparatus.

laser pointing control↗
DOE OSTI2024

Kinetic stability of Chapman–Enskog plasmas

In this paper, we investigate the kinetic stability of classical, collisional plasma – that is, plasma in which the mean-free-path $\lambda$ of constituent particles is short compared with the length scale $L$ over which fields and bulk motions in the plasma vary macroscopically, and the collision time is short compared with the evolution time. Fluid equations are typically used to describe such plasmas, since their distribution functions are close to being Maxwellian. The small deviations from the Maxwellian distribution are calculated via the Chapman–Enskog (CE) expansion in $\lambda /L \ll 1$ , and determine macroscopic momentum and heat fluxes in the plasma. Such a calculation is only valid if the underlying CE distribution function is stable at collisionless length scales and/or time scales. We find that at sufficiently high plasma $\beta$ , the CE distribution function can be subject to numerous microinstabilities across a wide range of scales. For a particular form of the CE distribution function arising in strongly magnetised plasma ( viz. plasma in which the Larmor periods of particles are much smaller than collision times), we provide a detailed analytic characterisation of all significant microinstabilities, including peak growth rates and their associated wavenumbers. Of specific note is the discovery of several new microinstabilities, including one at sub-electron-Larmor scales (the ‘whisper instability’) whose growth rate in certain parameter regimes is large compared with other instabilities. Our approach enables us to construct the kinetic stability maps of classical, two-species collisional plasma in terms of $\lambda$ , the electron inertial scale $d_e$ and the plasma $\beta$ . This work is of general consequence in emphasising the fact that high- $\beta$ collisional plasmas can be kinetically unstable; for strongly magnetised CE plasmas, the condition for instability is $\beta \gtrsim L/\lambda$ . In this situation, the determination of transport coefficients via the standard CE approach is not valid.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Self-organization in collisionless, high- β turbulence

The magnetohydrodynamic (MHD) equations, as a collisional fluid model that remains in local thermodynamic equilibrium (LTE), have long been used to describe turbulence in myriad space and astrophysical plasmas. Yet, the vast majority of these plasmas, from the solar wind to the intracluster medium (ICM) of galaxy clusters, are only weakly collisional at best, meaning that significant deviations from LTE are not only possible but common. Recent studies have demonstrated that the kinetic physics inherent to this weakly collisional regime can fundamentally transform the evolution of such plasmas across a wide range of scales. Here, we explore the consequences of pressure anisotropy and Larmor-scale instabilities for collisionless, β $\gg$ 1, turbulence, focusing on the role of a self-organizational effect known as ‘magneto-immutability’. We describe this self-organization analytically through a high-β, reduced ordering of the Chew–Goldberger–Low-MHD (CGL-MHD) equations, finding that it is a robust inertial-range effect that dynamically suppresses magnetic-field-strength fluctuations, anisotropic-pressure stresses and dissipation due to heat fluxes. As a result, the turbulent cascade of Alfvénic fluctuations continues below the putative viscous scale to form a robust, nearly conservative, MHD-like inertial range. These findings are confirmed numerically via Landau-fluid CGL-MHD turbulence simulations that employ a collisional closure to mimic the effects of microinstabilities. We find that microinstabilities occupy a small (~5%) volume-filling fraction of the plasma, even when the pressure anisotropy is driven strongly towards its instability thresholds. We discuss these results in the context of recent predictions for ion-vs-electron heating in low-luminosity accretion flows and observations implying suppressed viscosity in ICM turbulence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Lectures on statistical mechanics

Presented here is a transcription of the lecture notes from Professor Allan N. Kaufman’s graduate statistical mechanics course Physics 212A and 212B at the University of California Berkeley from the 1972–1973 academic year. 212A addressed equilibrium statistical mechanics with topics: fundamentals (micro-canonical and sub-canonical ensembles, adiabatic law and action conservation, fluctuations, pressure, and virial theorem), classical fluids and other systems (equation of state, deviations from ideality, virial coefficients and van der Waals potential, canonical ensemble and partition function, quasistatic evolution, grand-canonical ensemble and partition function, chemical potential, simple model of a phase transition, quantum virial expansion, numerical simulation of equations of state, and phase transition), chemical equilibrium (systems with multiple species and chemical reactions, law of mass action, Saha equation, chemical equilibrium including ionization and excited states), and long-range interactions (including Coulomb, dipole, and gravitational interactions, Debye–Hückel theory, and shielding). 212B addressed nonequilibrium statistical mechanics with topics: fundamentals (definitions: realizations, moments, characteristic function, and discrete variables), Brownian motion (Langevin equation, fluctuation–dissipation theorem, spatial diffusion, Boltzmann’s H-theorem), Liouville and Klimontovich equations, Landau equation (derivation, elaboration, and H-theorem, and irreversibility), Markov processes and Fokker–Planck equation (derivations of the Fokker–Planck equation and a master equation), linear response and transport theory (linear Boltzmann equation, linear response theory of Kubo and Mori, relation of entropy production to electrical conductivity, transport relations and coefficients, normal mode solutions of the transport equations, sketch of a generalized Langevin equation method for transport theory), and an introduction to nonequilibrium quantum statistical mechanics.

plasma dynamics↗
DOE OSTI2025

Bootstrap current modeling in M3D-C1

Bootstrap current plays a crucial role in the equilibrium of magnetically confined plasmas, particularly in quasi-symmetric stellarators and in tokamaks, where it can represent bulk of the electric current density. Accurate modeling of this current is essential for understanding the magnetohydrodynamic (MHD) equilibrium and stability of these configurations. This study expands the modeling capabilities of M3D-C1, an extended-MHD code, by implementing self-consistent physics models for bootstrap current. It employs two analytical frameworks: a generalized Sauter model (Sauter et al. 1999 Phys. Plasmas vol. 6, no. 7, pp. 2834–2839), and a revised Sauter-like model (Redl et al. 2021 Phys. Plasmas vol. 28, no. 2, pp. 022502). The isomorphism described by Landreman et al. (2022 Phys. Rev. Lett. vol. 128, pp. 035001) is employed to apply these models to quasi-symmetric stellarators. The implementation in M3D-C1 is benchmarked against neoclassical codes, including NEO, XGCa and SFINCS, showing excellent agreement. These improvements allow M3D-C1 to self-consistently calculate the neoclassical contributions to plasma current in axisymmetric and quasi-symmetric configurations, providing a more accurate representation of the plasma behavior in these configurations. A workflow for evaluating the neoclassical transport using SFINCS with arbitrary toroidal equilibria calculated using M3D-C1 is also presented. This workflow enables a quantitative evaluation of the error in the Sauter-like model in cases that deviate from axi- or quasi-symmetry (e.g. through the development of an MHD instability).

fusion plasma↗
DOE OSTI2024

Distinct evolutionary lineages of Schistocephalus parasites infecting co-occurring sculpin and stickleback fishes in Alaska

Sculpins (coastrange and slimy) and sticklebacks (ninespine and threespine) are widely distributed fishes cohabiting 2 south-central Alaskan lakes (Aleknagik and Iliamna), and all these species are parasitized by cryptic diphyllobothriidean cestodes in the genus Schistocephalus. The goal of this investigation was to test for host-specific parasitic relationships between sculpins and sticklebacks based upon morphological traits (segment counts) and sequence variation across the NADH1 gene. A total of 446 plerocercoids was examined. Large, significant differences in mean segment counts were found between cestodes in sculpin (mean = 112; standard deviation [S.D.] = 15) and stickleback (mean = 86; S.D. = 9) hosts within and between lakes. Nucleotide sequence divergence between parasites from sculpin and stickleback hosts was 20.5%, and Bayesian phylogenetic analysis recovered 2 well-supported clades of cestodes reflecting intermediate host family (i.e. sculpin, Cottidae vs stickleback, Gasterosteidae). Our findings point to the presence of a distinct lineage of cryptic Schistocephalus in sculpins from Aleknagik and Iliamna lakes that warrants further investigation to determine appropriate evolutionary and taxonomic recognition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Data Set Analysis to Reduce Uncertainty in Formula Assignments of Ultrahigh Resolution Mass Spectra

Environmental samples contain a vast array of organic compounds with diverse elemental compositions and heteroatom content. Molecular formula assignments of ultrahigh resolution mass spectra (HRMS) hold promise for elucidating the molecular composition of these compounds. However, the need to account for an assortment of heteroatoms increases the uncertainty associated with individual assignments – and ultimately the ecological, biological, and biogeochemical insights gleaned from the assignments. To address this challenge, we introduce a formula assignment strategy that leverages HRMS data sets to improve assignment confidence, filter false assignments, and mitigate bias in assignment routines. The strategy, implemented using CoreMS, first identifies the highest confidence assignment for a recurring ion in a data set by assessing the mass accuracy and isotopologue similarity of all assignments to the ion across the data set. The second component of the strategy examines the consistency of mass errors for an assigned ion throughout a data set and flags formulas with statistically unlikely deviations in mass error. Here, we illustrate the application and utility of the strategy by comparing its results against documented misassignment patterns within a set of oceanographic samples that were measured with 21 T Fourier Transform Ion Cyclotron Resonance Mass Spectrometry. Because the efficacy of our strategy improves with data set size, it is particularly useful for enhancing assignment confidence in large HRMS data sets common in studies of environmental systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Open Specy 1.0: Automated (Hyper)spectroscopy for Microplastics

Microplastic spectral analysis is one of the most time-consuming processes in studying microplastic pollution, often requiring days per sample. Researchers are transitioning to automated batch and hyperspectral image analysis techniques to enhance efficiency. Open Specy, initially aimed at manual single-spectrum analysis, has now integrated automated methods. This updated version, Open Specy 1.0, introduces several new features, including two algorithms for automated processing (smoothing and particle compression), an extensive library containing over 40,000 open-source Raman and FTIR spectra, and two machine learning classifiers (logistic regression and k medoids) developed from this library. Furthermore, it includes a revamped user interface, an R package, and a benchmark data set for testing future advancements in automated techniques. Researchers evaluated various configurations for hyperspectral smoothing, particle identification, compression, and splitting, to achieve combined recovery rates between 50 and 150% particle counts, identities, and sizes with a coefficient of variation (CV) of less than 40% (the accredited standard). Mean absorbance times the standard deviation provided a consistent particle identification. Hyperspectral smoothing led to a 96% combined recovery rate and reduced variability (CV = 38%) compared to the 86% recovery (CV = 83%) of nonsmoothed controls. Additionally, compressing spectra for particles was significantly faster (>3x) and showed similar accuracy but with reduced variability than processing each pixel individually. Key challenges persist in automating spectral analysis, particularly in refining particle splitting algorithms, and improving identification routines to minimize false positives and negatives. In conclusion, new methods in sample preparation for better stabilization and dispersion of particles could overcome some of these issues.

13 HYDRO ENERGY↗
DOE OSTI2026

Integrating Flow Imaging Analysis and Single-Particle ICP-TOFMS for Comprehensive Micro- and Nanoplastic Characterization

Flow imaging analysis (FIA), provides composition-agnostic morphological characterization. These measurements of particle size and shape are valuable to mass-based analysis, such as single particle inductively coupled plasma time-of-flight mass spectrometry (sp-ICP-TOFMS), which provides quantitative data on elements within particles. Using these two methods together enables informed use of geometric assumptions required by sp-ICP-TOFMS, as particle mass is typically converted to a particle diameter using assumed-spherical geometry. To validate this concept, parallel measurements to determine particle diameters were performed by FIA and sp-ICP-TOFMS on four particle suspensions: 300 nm polystyrene Eu-doped nanoparticles, 1 μm Fe-rich beads, 3 μm four element calibration polystyrene beads and 5 μm polystyrene beads. The Fe-particles obtained the highest percent difference from the manufacturer’s nominal diameter, as the mean diameter obtained by FIA was overestimated by 21% and sp-ICP-TOFMS underestimated the mean diameter by 20.7%. Two types of particles were selected to test the effect of varying the particle number concentrations (PNC) on sizing accuracy, and both methods accurately sized each particle population at the PNC expected. Single particle analysis of carbon has continued to be a popular research topic, with direct applications to environmental pollutants in terms of nano- and micro- plastics. Real-world plastic particles were studied, and FIA’s measured circularity values demonstrated that the particles deviated from spherical geometries, therefore sp-ICP-TOFMS data should be interpreted as mass-based rather than size-based. Combining these techniques enables improved interpretation of particle populations and evaluation of particle sizes.

Szakas, Sarah [ORNL] (ORCID:0000000241332197)↗
DOE OSTI2025

Double-Crucible Vertical Bridgman Technique for Stoichiometry-Controlled Chalcogenide Crystal Growth

Precise stoichiometry control in single-crystal growth is essential for both technological applications and fundamental research. However, conventional growth methods often face challenges such as non-stoichiometry, compositional gradients, and phase impurities, particularly in non-congruent melting systems. Even in congruent melting systems like Bi₂Se₃, deviations from the ideal stoichiometric composition can lead to significant property degradation, such as excessive bulk conductivity, which limits its topological applications. In this study, we introduce the double-crucible vertical Bridgman (DCVB) method, a novel approach that enhances stoichiometry control through the combined use of continuous source material feeding, traveling-solvent growth, and liquid encapsulation, which suppresses volatile element loss under high pressure. Using Bi₂Se₃ as a model system, we demonstrate that crystals grown via DCVB exhibit enhanced stoichiometric control, significantly reducing defect density and achieving much lower carrier concentrations compared to those produced by conventional Bridgman techniques. Moreover, the continuous feeding of source material enables the growth of large crystals. As a result, this approach presents a promising strategy for synthesizing high-quality, large-scale crystals, particularly for metal chalcogenides and pnictides that exhibit challenging non-congruent melting behaviors.

Crystal structure↗
DOE OSTI2025

High-Pressure Phase Transition of Metastable Wurtzite-Like CuInSe 2 Nanocrystals

Ternary I–III–VI 2 semiconductors, such as CuInSe 2 , exhibit diverse polymorphs with unique structural characteristics and optoelectronic properties. This study investigates the pressure-induced phase transitions of metastable wurtzite-like CuInSe 2 nanocrystals. Using a combination of synchrotron X-ray diffraction, pair distribution function analysis, and density functional theory calculations, we reveal a transition from cation-ordered wurtzite-like (Pmc2 1 ) to cation-disordered NaCl-like (Fm3̅m) structures at 7.7 GPa. The cation-disordered NaCl-like phase persists upon decompression. Bulk modulus calculations highlight size-dependent deviations from bulk material behavior. These findings deepen our understanding of phase stability in colloidal I–III–VI 2 semiconductor nanocrystals, with implications for tailoring functional materials under extreme conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Encapsulation of Ba in InSb Framework Introduces Chirality in Clathrate-Like BaIn 4 Sb 4

The discovery of Zintl compounds remains a powerful strategy for identifying materials with tunable electronic and thermal transport properties. During a concerted search for new inorganic clathrates with In–Sb frameworks, we discovered BaIn 4 Sb 4 . The composition of this phase deviates from that expected for a type-I clathrate with tetrahedral coordination of all In and Sb atoms (Ba 8 In 31 Sb 15 ). Instead, in the chiral structure of BaIn 4 Sb 4 (space group P 3 1 21, No. 152), a part of the In atoms have a trigonal planar coordination of 1In + 2Sb, forming Sb 2 –In–In–Sb 2 nonplanar fragments isostructural to diborane(4) B 2 H 4 with D 2 d symmetry. Ba atoms are located inside 16-vertex In 8 Sb 8 polyhedra, which share vertices and edges to form a chiral framework around the 3 1 screw axes. The title compound is electron-balanced, [Ba 2+ ][In 2+ ] 2 [In 3+ ] 2 [Sb3–] 4 , which was confirmed by characterization of the charge and heat transport properties. BaIn 4 Sb 4 exhibits a low thermal conductivity and high Seebeck coefficient, suggesting its untapped potential for thermoelectric applications. Finally, density functional theory (DFT) calculations indicate that chemical doping may enhance carrier concentration and improve the originally low electrical conductivity, thus enhancing thermoelectric performance.

electrical properties↗
DOE OSTI2026

Dissecting Disorder: Defect-Driven Structural Complexity in Layered Li3InCl6 Solid Electrolyte

Halide solid electrolytes have emerged as promising candidates for solid-state batteries owing to their high oxidative stability and ionic conductivity. Among them, Li3InCl6 (LIC) has attracted significant attention. However, diffraction patterns of LIC synthesized via different methods exhibit distinct differences particularly at low-angle reflectionsindicative of underlying structural disorder. These variations are attributed to deviations from ideal crystallographic order, especially stacking faults, whose impact on structure and ion transport remains poorly understood. Here, we identify and quantify stacking faults in LIC samples prepared under different synthetic conditions. Using X-ray diffraction and time-of-flight neutron diffraction, we construct and refine stacking fault models that accurately reproduce the experimental diffraction features. LIC samples with higher degrees of stacking faults exhibit only negligible differences in ionic conductivities and activation energies. This indicates that stacking faults have a limited impact on altering the Li+ diffusion pathway along the c-axis, likely due to the high concentration of vacancies in the In layers, while Li+ diffusion remains nearly unchanged in the ab-plane. Our results account for the observed differences in diffraction patterns across samples and provide a quantitative assessment of faulting probabilities and stacking sequences. The insights gained from this study are expected to be broadly applicable to other layered halide solid electrolytes and contribute to a deeper understanding of the role of structural disorder in ion transport.

Liu, Jue [ORNL] (ORCID:000000024453910X)↗
DOE OSTI2025

Structurally Frustrated Remeika Phases: Tolerance Factor and Non-Kramers’ Ion Effects

Quantum materials that are found on the verge of structural, magnetic, and electronic instabilities are deep reservoirs for exotic phenomena. Our criteria to study the reported Ln 5 Ru 6 Sn 18 (Ln = Gd, Tb) are guided by the tolerance factor for Remeika phases─a class of intermetallic compounds with the general formula A 3 M 4 X 13 (where A = rare-earth element, M = transition metal, and X = tetrel), which can be viewed as structural analogues of pseudoperovskites (4 × ABX 3 ), with one of the tetrel atoms occupying the A-site. We have grown single crystals, up to 0.5 cm on the largest facet, of Gd 5 Ru 6 Sn 18 (a = 13.8052(12) Å) and Tb 5 Ru 6 Sn 18 (a = 13.7825(9) Å), which we expect to be on the verge of a formation instability. Bulk magnetic, heat capacity, and electrical transport measurements reveal unusual behavior that originates from the trivalent Gd and Tb ions, with deviations from typical metallic behavior and magnetic ordering that is short-range or disrupted in some other way. Furthermore, to better understand these phenomena, single-crystal neutron diffraction is investigated, which reveals short-range correlations among the partially occupied Tb and Sn sublattices, with 3D-ΔPDF analysis supporting direction-dependent local order. Taken together, these measurements show the utility of using tolerance factors in identifying materials that are likely to exhibit complex phenomena and uncover environments where a formation instability may strongly impact emergent bulk magnetic and electronic phenomena.

36 MATERIALS SCIENCE↗