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A Machine Learning Approach for the Prediction of Formability and Thermodynamic Stability of Single and Double Perovskite Oxides
Perovskite oxides continue to attract huge interest due to their fascinating and wide-ranging properties for diverse applications. The tunability of these properties may be further enhanced by increasing their compositional complexity via double perovskite-ordered configurations containing multiple cations. In this work, we focus on an exhaustive chemical space of single and double oxide perovskites and optimally explore this space to identify novel compositions that are likely to form stable compounds. Critically, we examine the relationship between formability, the practical ability to synthesize a compound, and stability, the thermodynamic preference to form the structure. Our formability and stability training data sets were enumerated from the available experimental literature and in-house density functional theory computations and contained 1505 and 3469 examples, respectively, representing state-of-the-art in the current open literature in perovskite and double perovskite compounds. Subsequently, cross-validated and highly accurate machine learning classification models are built using these training data sets and employed to screen for novel stable oxide perovskites. The study identifies (1) atomic features relevant to prediction of formability and stability in perovskite and double perovskite compounds, (2) the importance of including energy contributions due to local structural relaxations going beyond the high symmetry perovskite phase, and (3) 437,828 double perovskite compounds that are likely to be stable and 891,188 compounds that are likely to be formable. From the intersection of this large chemical space of formable and stable oxide perovskites, 414 compositions are identified as the most promising candidates for future experimental synthesis of novel oxide perovskites. The developed models may be generalized and have implications beyond perovskite discovery if applied to other families of compounds.
Understanding the electromagnetic topology during the ohmic breakdown in tokamaks considering self-generated electric fields
We report that the physical mechanisms of the ohmic breakdown in a tokamak have been understood based on the classical Townsend avalanche theory. However, a new systematic theory (Yoo et al 2018 Nat. Commun.9 3523) recently demonstrated that electron avalanches during the ohmic breakdown are completely different from the Townsend avalanche due to strong self-generated electric fields. In this study, we elucidate the multi-dimensional effects of the self-generated electric field on plasma dynamics during the ohmic breakdown. We also propose a novel electromagnetic topology analysis method that can easily predict the overall plasma behavior and where the main plasma is generated. The topology analysis method is validated by a state-of-art particle simulation for various magnetic configurations. New physical insights into the complex electromagnetic topology would facilitate designing more reliable and optimized ohmic breakdown scenarios in future tokamaks, such as ITER and beyond.
Radial Spin Texture of the Weyl Fermions in Chiral Tellurium
Trigonal tellurium, a small-gap semiconductor with pronounced magneto-electric and magneto-optical responses, is among the simplest realizations of a chiral crystal. We have studied by spin- and angle-resolved photoelectron spectroscopy its unconventional electronic structure and unique spin texture. We identify Kramers-Weyl, composite, and accordionlike Weyl fermions, so far only predicted by theory, and show that the spin polarization is parallel to the wave vector along the lines in k space connecting high-symmetry points. Our results clarify the symmetries that enforce such spin texture in a chiral crystal, thus bringing new insight in the formation of a spin vectorial field more complex than the previously proposed hedgehog configuration. Our findings thus pave the way to a classification scheme for these exotic spin textures and their search in chiral crystals.
Cooling Strategies for an Electric Motor with Additively Manufactured Hollow Conductors and Distributed Power Electronics Integrated with Heat Pipes
This paper discusses design tradeoffs and thermal modeling explored in cooling strategies for an aircraft propulsion electric motor with additively manufactured coils and distributed power electronics integrated with heat pipes. Design tradeoffs include heat pipe Qmax performance related to inclination, condenser configuration, coolant type, coolant flow path complexity, and ease of access to modular power electronics. Three cooling strategies were selected and realized into CAD models. These models were further evaluated using 3D thermal FEA and optimization tools to explore cooling geometry details that include fin thickness, spacing and count with the objective to minimize fin mass under a set of constraints. Lastly, motorette test data is presented comparing air versus liquid cooling of heat pipes.
Asterocladon ednae sp. nov. (Asterocladales, Phaeophyceae) from the Philippines
SUMMARY Members of the brown algal order Asterocladales are characterized by stellate arrangement of its chloroplasts, in which a stellate configuration has a protruding central pyrenoid complex. The order is represented by the genus Asterocladon , which consists of only three species so far. Similar to other small and filamentous seaweeds, studies on Asterocladon remain scant and their diversity poorly understood. To fill this gap, we conducted molecular‐assisted taxonomic studies on Asterocladon based on seven culture isolates collected from Okinawa Prefecture, Japan and Cebu, the Philippines. One culture isolate from the Philippines was revealed to be a new species of Asterocladon based on morpho‐anatomical and molecular analyses using rbc L and psa A genes and is described here as Asterocladon ednae . The other isolates were attributed to A. rhodochortonoides . A. ednae was most closely related to A. rhodochortonoides in morphology and molecular phylogeny but was distinguished from the latter by its elongately ellipsoid plurilocular sporangia. This is the first report of the genus and species A. ednae in the Philippines, further increasing the diversity of seaweeds in the country.
AFUE Analysis Software Tool
The Annual Fuel Utilization Efficiency (AFUE) analysis of residential and light commercial furnaces follows ANSI/ASHRAE Standard 103-2017 (i.e., Method of Testing for Annual Fuel Utilization Efficiency of Residential Central Furnaces and Boilers) . The analysis is a complex, comprehensive method based on furnace configuration and specific components equipped, requiring detailed furnace testing and measurement data. For this reason, an AFUE Analysis Tool using Microsoft Excel enabled with Visual Basic for Applications (VBA) was developed with a user-friendly interface and comprehensive coverage. The tool consists of three worksheets: unit and configuration selection, geometry and measurement data input, and AFUE plus key results. This tool can be used to estimate the AFUE of both condensing and noncondensing furnaces with single-stage, two-stage, and step-modulating functions. The tool was validated with experimental data from Oak Ridge National Laboratory’s natural gas furnace projects that are commercially available. The results indicate the tool is reasonably accurate in the evaluation of a new R&D modified furnace unit.
Center for Tokamak Transient Simulations (RPI Unstructured Mesh Developments for FES SciDAC4 Partnerships) (Final Report)
The goal of this project was the development of unstructured mesh technologies for fusion simulation codes” for FES SciDAC partnerships and to integrate those technologies into the simulation workflows of those partnerships. Specific developments were executed in support of the following FES SciDAC4 partnerships: Partnership Center for High‐fidelity Boundary Plasma Simulation (HBPS), Center for Integrated Simulation of Fusion Relevant RF (RF‐SciDAC), Center for Plasma Surface Interactions: Predicting the Performance and Impact of Dynamic PFC Surfaces (PSI2), and Center for Tokamak Transient Simulations (CTTS). The key unstructured mesh development areas addressed in this project include (i) methods to most effectively perform PIC calculations on unstructured meshes; (ii) creating meshes for fusion systems accounting for any desired level of geometric complexity and providing physics aware mesh configurations, (iii) adapting unstructured meshes to control the discretization errors, (iv) executing unstructured mesh calculations on GPU accelerated systems, (v) supporting physics/application‐specific PIC operations including surface/wall interactions of particles, (vi) providing infrastructure tools to support the interactions of solvers with unstructured meshes, and (vii) providing advanced methods for coupling plasma physics codes.
A Fast, Accurate Prediction for System-Wide Damage Due to Dynamic Wind Loading
The complex relationship between photovoltaic (PV) hardware configurations, overall system dynamics, and turbulent aerodynamic phenomena generates highly unsteady, non-uniform loads that can lead to damaging instabilities. These effects may result in glass breakage, cell cracking, and structural failures in frames and mounting systems, even under moderate wind conditions. Addressing industry concerns about premature system failures in field conditions deemed survivable, our research aims to develop a fast and accurate predictive model for system damage. This model integrates configurable hardware choices with advanced simulation tools to represent the overall system-specific dynamics effectively. Using this model, we predict responses under varying weather conditions and hardware setups, translating these predictions into pre-trained surrogate models capable of accurately identifying failure risks and rapidly testing new system hardening measures. In this presentation, we will showcase preliminary results in capturing system dynamics through our customizable library of PV hardware configurations. Additionally, we will highlight how these new tools build upon PVade's established wind load modeling capabilities and foster the development of advanced AI/ML surrogates for improving system robustness.
ACDC (Automated Campbell Diagram Code) [SWR-26-042]
This application provides a web-based graphical user interface to generating Campbell Diagrams and visualizing mode shapes for OpenFAST turbine models. Determining the aeroelastic stability and dynamic characteristics of wind turbines is a critical step in turbine design and analysis. Historically, extracting natural frequencies and mode shapes from OpenFAST—the industry-standard whole-turbine simulation code—has been a fragmented and tedious process. It required manual model configuration, command-line linearization execution, and complex post-processing via proprietary scripts to handle rotating-frame dynamics. To address these workflow bottlenecks, we present the Automated Campbell Diagram Code (ACDC), an open-source graphical software tool developed by the National Laboratory of the Rockies (NLR) under the DOE-funded Distributed Wind Aeroelastic Modeling (dWAM) project. ACDC streamlines the end-to-end linearization and stability analysis workflow into a single, intuitive cross-platform application. The software guides users through OpenFAST model configuration, definition of operating points, and the automated execution of steady-state trim and linearization simulations. Under the hood, ACDC automates the complex mathematical post-processing steps required for rotating systems, including Multi-Blade Coordinate (MBC) transformations, eigenanalysis, and advanced modal tracking utilizing the Modal Assurance Criterion (MAC) and spectral clustering. Finally, ACDC processes these results to automatically generate Campbell diagrams and features a robust 3D visualization engine to animate full-system mode shapes. By eliminating the reliance on external post-processing environments and manual data manipulation, ACDC significantly accelerates dynamic analysis and lowers the barrier to entry for wind energy researchers and engineers.
Apparatus and method for optimizing quantifiable behavior in configurable devices and systems
An apparatus and method are provided to perform constrained optimization of a constrained property of an apparatus, which is complex due to having several components, and these components are configurable in real-time. The optimization is achieved by detecting values of the constrained property and a plurality of other properties of the apparatus when the apparatus is configured in a first subset of the plurality of configurations. A model is learned using the detected values of the constrained property. The model represents the constrained property and can also represent other properties as a function of the configurations. The model can also include estimated uncertainties of the constrained property in the model. Then, using the d model and the estimated uncertainties, the optimal configuration can be selected to minimize an error value (e.g., the difference between a desired value and an observed value of the at least one constrained property).
Ending the Energy-Poverty Nexus: An Ethical Imperative for Just Transitions
Arguments for a just transition are integral to debates about climate change and the drive to create a carbon-neutral economy. There are currently two broad approaches rooted in ethics and justice for framing just energy transitions. The first can be described as internal to the transition and emphasizes the anticipation, assessment, and redressing of harms created by the transition itself and the inclusion in transition governance of groups or communities potentially harmed by its disruptions. In this article, we propose a second approach to ethics and justice in an energy transition, which we describe as systemic or societal in scope. This approach complements attention to the proximate dynamics and impacts of the transition process with a focus on the distant societal and economic outcomes the transition brings into being and how they compare to conditions prior to the transition. It poses the question: do the transformative social, economic, and technological changes wrought by energy systems create more just societies and economies, or do they instead reinforce or recreate long-standing injustices and inequalities? We illustrate this approach with an assessment of one of the most significant existing forms of energy injustice: the energy-poverty nexus. We argue that the energy-poverty nexus reflects configurations of socio-energy systems that create complex, extractive feedbacks between energy insecurity and economic insecurity and, over time, reinforce or exacerbate poverty. We further argue that just energy transitions should work to disentangle these configurations and re-design them so as to create generative rather than extractive feedbacks, thus ending the energy-poverty nexus and creating long-term outcomes that are more just, equitable, and fair.
Load balancing for multi-beam additive manufacturing systems
As powder bed fusion (PBF) additive manufacturing (AM) becomes a more mature field, system configurations are gradually moving away from the classic single heat source, layer-by-layer system configurations towards unconventional system configurations that offer higher throughput. Higher throughput systems allow PBF systems to be considered for a larger variety of industrial applications. However, the inclusion of multiple heat sources, or beams, also increases the complexity of the control schemes needed. For multi-beam systems with overlapping fields of view, the distribution of workload, or load balancing, across these beams directly affects the total print time for a build. Additionally, the probability of any beam failing in a multi-beam system increases with the number of beams. While manual methods of load balancing and dealing with beam failures are reasonable for current generation multi-beam systems, as system configurations become more complex, manual methods will become prohibitively inefficient. Here, this paper introduces two different ways to load balance multi-beam systems of various configuration types, regardless of their complexity, which are highly performant. A consequence of this performance is the enablement of on-the-fly load balancing in the event a beam fails, thus improving system robustness.
Designing lithium halide solid electrolytes
All-solid-state lithium batteries have attracted widespread attention for next-generation energy storage, potentially providing enhanced safety and cycling stability. The performance of such batteries relies on solid electrolyte materials; hence many structures/phases are being investigated with increasing compositional complexity. Among the various solid electrolytes, lithium halides show promising ionic conductivity and cathode compatibility, however, there are no effective guidelines when moving toward complex compositions that go beyond ab -initio modeling. Here, we show that ionic potential, the ratio of charge number and ion radius, can effectively capture the key interactions within halide materials, making it possible to guide the design of the representative crystal structures. This is demonstrated by the preparation of a family of complex layered halides that combine an enhanced conductivity with a favorable isometric morphology, induced by the high configurational entropy. This work provides insights into the characteristics of complex halide phases and presents a methodology for designing solid materials.
C–H Bond Activation via U(II) in the Reduction of Heteroleptic Bis(trimethylsilyl)amide U(III) Complexes
Reduction of (C 5 Me 5 ) 2 U III (NR 2 ) and (C 5 Me 5 )U III (NR 2 ) 2 (R = SiMe 3 ) with potassium graphite in the presence of 2.2.2-cryptand (crypt) generates dark solutions that have UV-visible spectra consistent with time-dependent density functional theory (TDDFT) calculations on the U(II) products, [(C 5 Me 5 ) 2 U II (NR 2 )] - and [(C 5 Me 5 )U II (NR 2 ) 2 ] - . However, the solutions quickly change color and form the U(III) C–H bond activation products [K(crypt)][(C 5 Me 5 ) 2 U III (CH 2 SiMe 2 NSiMe 3 –κC,κN)], 1, and [K(crypt)][(C 5 Me 5 )U III (NR 2 )(CH 2 SiMe 2 NSiMe 3 –κC,κN)], 2, that were identified by X-ray crystallography. DFT calculations on the putative [(C 5 Me 5 ) 2 U II (NR 2 )] - and [(C 5 Me 5 )U II (NR 2 ) 2 ] - complexes revealed 5f 3 6d 1 ground state electron configurations as previously found in isolable [(C 5 H 4 SiMe 3 ) 3 U II ] - , which indicated that these low symmetry heteroleptic complexes are reasonable precursors for new U(II) complexes.
Magnetic tunability in tetragonal Mn–Rh–Ir–Sn inverse Heusler compounds
Abstract Gaining control over magnetic structure has been an ongoing challenge in materials that form complex, nanoscale, and non-collinear magnetic configurations. Recently, it was predicted that tuning the ratio of the Dzyaloshinskii–Moriya interaction to the uniaxial magnetic anisotropy in tetragonal inverse Heuslers through changes in composition could allow a range of interesting magnetic states to be accessed, from simple ferrimagnetism, to helical and antiskyrmionic phases. Here, we show tunability of the magnetic phase behavior in the Mn–Rh–Sn system through Ir substitution on the Rh substructure. Iridium substitution correlates to an increase in the strength of ferromagnetic exchange couplings, at the expense of antiferromagnetic exchange couplings. However, we do not observe the complex non-collinear magnetic phases proposed previously, likely due to the extremely narrow composition window where these phases are predicted to form in a bulk sample. This work highlights the sensitivity of complex magnetic structures to stoichiometry, which makes them difficult to discover empirically.
Modeling Snowflake Divertors in MAST-U Tokamak
We report that in a snowflake (SF) divertor, two magnetic field nulls are placed close to each other, creating four strike points (SPs) compared to two in a standard X-point divertor. In preparation for MAST-U experiments, magnetic configurations with the standard and SF divertors with various locations and separation distances of the nulls were modeled using the two-dimensional multi-fluid code UEDGE with a full plasma transport model featuring charge-state-resolved sputtered carbon impurities. The complex interplay of the plasma transport and magnetic configurations was comprehensively studied using a simple model for the theoretically predicted fast plasma mixing driven by the 'churning' mode instability in the two-null SF region. The modeling results show that (1) all SF-plus configurations and SF-minus configuration with closely located nulls produce the same plasma parameters and heat fluxes at the same SPs; (2) SF divertors approach the outer and inner SP detachment conditions at lower upstream density w.r.t. the standard divertor; (3) heat flux profiles at primary SPs are substantially broadened and peak values are reduced in SF configurations w.r.t. SN divertors; this broadening becomes more pronounced with the fast plasma mixing increase.
Multistability of isolated and hydrogenated Ga–O divacancies in β–Ga 2 O 3
This work systematically explores 19 unique configurations of the close-associate Ga–O divacancies (V Ga V O ) in β–Ga 2 O 3 , including their complexes with H impurities, using hybrid functional calculations. Interestingly, most configurations are found to retain the negative-U behavior of V O , as they exhibit a thermodynamic (–/3–) charge-state transition level energetically located in the upper part of the band gap, where the 3– charge state is associated with the formation of a Ga–Ga dimer. The energy positions of the thermodynamic (–/3–) charge-state transition levels divide the divacancy configurations into three different groups, which can be understood from the three possible Ga–Ga dimerizations resulting from the tetrahedral and octahedral Ga sites. The relative formation energies of the different divacancy configurations, and hence the electrical activity of the divacancies, is found to depend on the Fermi-level position, and the energy barriers for transformation between different divacancy configurations are explored from nudged elastic band calculations. Hydrogenation of the divacancies is found to either passivate their negative-U charge-state transition levels or shift them down in Fermi level position, depending on whether the H resides at V O or forms an O–H bond at V Ga , respectively. Finally, the divacancy is discussed as a potential origin of the so-called E$^{*}_{2}$ center previously observed by deep-level transient spectroscopy.