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DOE OSTI2025

First-Principles Studies on Sc 2 RuZ (Z = Si, Ge, Sn) Inverse Heusler Alloys: Structural, Electronic, and Transport Properties

The continuous demand for efficient, nontoxic, and thermally stable materials for room-temperature energy conversion motivates the exploration of novel thermoelectric systems beyond the traditional magnetic Heusler alloys. While full and half-Heusler compounds, especially Co-, Ni-, and Mn-based systems, have demonstrated promising thermoelectric properties, their typically high operating temperatures and magnetic complexities limit their applicability in ambient thermal management. In this context, we investigate whether Sc-based inverse Heusler alloys can offer a viable nonmagnetic alternative with competitive thermoelectric performance. In this work, we perform a systematic first-principles study of the inverse Heusler compounds Sc 2 RuZ (Z = Si, Ge, Sn), focusing on their structural, electronic, mechanical, and thermodynamic-thermoelectric properties. Density Functional Theory (DFT) was employed to compute optimized lattice structures and band dispersion, while dynamical stability was assessed via phonon calculations. Thermoelectric transport coefficients, including Seebeck coefficient, electrical conductivity, and thermal conductivity, were estimated using the semiclassical Boltzmann transport theory within the constant relaxation time approximation. Our results show that all Sc 2 RuZ compounds are thermodynamically stable semiconductors with indirect band gaps of 0.12–0.16 eV and exhibit high elastic moduli, especially Sc 2 RuSn, which demonstrates superior stiffness and incompressibility. Importantly, all compounds display promising room-temperature thermoelectric characteristics, including high Seebeck coefficients and power factors. These findings reveal that Sc 2 RuZ alloys represent a rare class of stable, nonmagnetic inverse Heusler semiconductors with intrinsic thermoelectric potential at room temperature, unlike many existing Heusler systems optimized for spintronics or high-temperature operation. This work expands the known design space for Heusler-based thermoelectrics and offers a theoretical basis for experimental realization of efficient, low-temperature, nonmagnetic thermoelectric materials.

alloys↗

DOE OSTI2026

Crystal generation using the fully differentiable pipeline and latent space optimization

We present a materials generation framework that couples a symmetry-conditioned variational autoencoder with a differentiable SO(3) power spectrum objective to steer candidates toward a specified local environment under the crystallographic constraints. In particular, we implement a fully differentiable pipeline that performs batch-wise optimization on both direct and latent crystallographic representations. Using the GPU acceleration, the implementation achieves about fivefold speed compared to our previous CPU workflow, while yielding comparable outcomes. In addition, we introduce the optimization strategy that alternatively performs optimization on the direct and latent crystal representations. This dual-level relaxation approach can effectively escape local minima defined by different objective gradients, thus increasing the success rate of generating complex structures satisfying the target local environments. This framework can be extended to systems consisting of multi-components and multi-environments, providing a scalable route to generate material structures with the target local environment.

conditional VAE↗

DOE OSTI2025

Structural, magnetic, optical, dielectric and electronic properties of R 2 NiIrO 6 (R = Pr and Nd): A comprehensive experimental and theoretical investigation

Double perovskites are highly promising materials capable of exhibiting a wide variety of phenomena. In this work, we perform a comprehensive experimental and theoretical study of polycrystalline R 2 NiIrO 6 (R = Pr and Nd) compounds. Both compounds were synthesised using the solid-state reaction method. Rietveld refinement confirmed a monoclinic structure with the P2 1 /n space group for both compounds. The scanning electron images showed the average grain sizes of 0.55 μm for R = Pr and 0.46 μm for R = Nd. Fourier transform infrared ra- diation spectra of the two compounds presented two intense bands at 470 cm -1 and 540 cm -1 . The optical measurements revealed that the band gaps of the compounds were in the visible absorption range. The field- cooled magnetisation - field hysteresis measurements indicated exchange bias properties in the synthesised compounds at low temperatures. Both temperature and frequency variation of dielectric constant and loss tangent measurements were conducted. The frequency-dependent ac conductivity measurements indicated that the conductivity increases with the increase of frequency as well as temperature. The Nd 2 NiIrO 6 compound showed lower ac conductivities compared to its isostructural Pr 2 NiIrO 6 compound. The atomic and electronic structures of Nd 2 NiIrO 6 and Pr 2 NiIrO 6 were explored using the spin-polarised calculations performed within the DFT+U method. Our results suggested that the inclusion of on-site correlations and repulsions for the d-states of atoms was necessary in order to obtain finite band gaps of Nd 2 NiIrO 6 and Pr 2 NiIrO 6 systems.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Long-term calibration and validation of stability of the Auger Engineering Radio Array using the diffuse Galactic radio emission

The Auger Engineering Radio Array (AERA) measures radio emission from high-energy extensive air showers. Consisting of 153 autonomous radio-detector stations spread over 17 km^2, it detects radio waves in the frequency range of 30 to 80 MHz. Accurate characterization of the detector response is crucial for proper interpretation of the collected data. Previously, this was achieved through laboratory measurements of the analog chain and simulations and measurements of the antenna's directional response. In this paper, we perform an absolute calibration using the continuously monitored sidereal modulation of the diffuse Galactic radio emission. Calibration is done by comparing the average frequency spectra recorded by the stations with predictions from seven different models of the full radio sky, accounting for the system response, which includes the antenna, filters, and amplifiers. The analysis of the calibration constants over a period of seven years shows no relevant and no significant ageing effect in the AERA antennas. This result confirms the long-term stability of the detector stations and demonstrates the possibility for a radio detector to effectively monitor ageing effects of other detectors operating over extended periods.

Antennas↗

DOE OSTI2025

ExINP NSA Ice Nucleating Particle Concentrations

This data set comprises cumulative ambient ice-nucleating particle (INP) concentrations measured at the National Oceanic and Atmospheric Administration's (NOAA’s) Barrow Atmospheric Baseline Observatory (71.3230° N, 156.6114° W, “BRW” hereafter), next to the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site and ~ 6 km northeast of the town of Utqiaġvik. Our INP abundance data were generated using a combination of online instrument, the Portable Ice Nucleation Experiment chamber ver. 3 (PINE-03), and an offline cold stage, the West Texas Cryogenic Refrigerator Applied to Freezing Test system (WT-CRAFT). Our online INP data are all from the Examining the Ice-Nucleating Particles from NSA (ExINP-NSA) campaign conducted from October 19, 2021 to May 24, 2024. The offline INP concentration analysis was performed at West Texas A&M University for aerosol particle samples collected on polycarbonate filters (with 0.2-micron diameter pores). The PINE-03 measurements, as well as sampling activities for offline INP measurements, were conducted using the BRW site. An inset laminar sampling stack was mounted to the instrument platform, allowing PINE-03 to intake particle-laden air. For most of the campaign period, the semi-autonomous PINE-03 chamber was remotely controlled from West Texas A&M University using the LabView interface through the BeyondTrust remote-access console. PINE-03 was set to conduct an immersion freezing expansion experiment (i.e., simulated adiabatic cooling along with RHw at or above 100%). Except during the scheduled maintenance periods, the time resolution of each expansion experiment was approximately 12 minutes. PINE-03 continuously measured INP concentrations during the entire campaign without any substantial breaks. For most of the campaign period, PINE scanned its set-point vessel air temperatures from -14 °C to -31 °C and back to -14 °C about every 120 minutes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

ExINP NSA Ice Nucleating Particle Concentrations

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Invariant discovery of features across multiple length scales: Applications in microscopy and autonomous materials characterization

Physical imaging is a foundational characterization method in areas from condensed matter physics and chemistry to astronomy and spans length scales from atomic to universe. Images encapsulate crucial data regarding atomic bonding, materials microstructures, and dynamic phenomena such as microstructural evolution and turbulence, among other phenomena. The challenge lies in effectively extracting and interpreting this information. Variational Autoencoders (VAEs) have emerged as powerful tools for identifying the underlying factors of variation in image data, providing a systematic approach to distilling meaningful patterns from complex data sets. However, a significant hurdle in their application is the definition and selection of appropriate descriptors reflecting local structures. Here, we introduce the scale-invariant VAE approach (SI-VAE) based on the progressive training of the VAE with the descriptors sampled at different length scales. The SI-VAE allows the discovery of the length scale-dependent factors of variation in the system. Here, we illustrate this approach using the ferroelectric domain images and generalize it to the movies of the electron-beam induced phenomena in graphene and topography evolution across combinatorial libraries. This approach can further be used to initialize the decision making in automated experiments including structure–property discovery and can be applied across a broad range of imaging methods. This approach is universal and can be applied to any spatially resolved data including both experimental imaging studies and simulations, and can be particularly useful for exploration of phenomena such as turbulence and scale-invariant transformation fronts.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Approaches for Autonomous Peer to Peer Communication: For Resilient Community Microgrids

The final phase of the Islandable Communications task of the SECURE project consisted of integrating the islandable communications network into a microgrid simulation at NREL. Initially integration was planned for a microgrid implemented as a mix of simulation and physical hardware. As the project evolved, the microgrid became fully simulated. The simulation environment was structured to break out the communication paths that would pass over a communication network in a field demonstration. The Islandable Communication network was integrated into the simulation environment, allowing both a commercial cellular carrier and a Private LTE network to be evaluated. The microgrid simulation showed differences in performance and behavior when operating over the wireless networks (compared to operating over wired Ethernet in the lab). These differences point to further research opportunities to better understand how microgrid communication carried over real-world or impaired networks affects the microgrid system behavior.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Experimental Analysis of Distribution Network Voltage Regulation Using Smart Inverters

Smart inverters (SIs) have demonstrated their potential to provide grid services for both transmission and distribution systems. One of these grid services, distribution network voltage regulation by SIs, has the potential to improve network voltage regulation through controlling the reactive and active power output of the SIs. Voltage regulation by SIs will be distributed and might be better suited to controlling local conditions to complement traditional voltage-regulating assets, e.g., tap-changing transformers, capacitor banks, and line voltage regulators. There is a gap in the literature on comparing the SI response characteristics when the SIs are controlled by a local controller or external control signals. This paper presents an experimental study to characterize SI reactive power regulation responses to two different control methods: autonomous control and remote dispatch. We found that SI reactive power regulation responses exhibit important differences between these methods in terms of delays and ramp rate. Finally, power-hardware-in-the-loop (PHIL) tests were conducted to evaluate the performance of these two methods. The PHIL test results show that the SI response characteristics for autonomous control and remote dispatch need to be considered when planning for distribution network voltage regulation using SIs.

autonomous control↗

DOE OSTI2025

Ligand-induced self-assembly of twisted two-dimensional halide perovskites

Two-dimensional (2D) halide perovskites (HPs) exhibit intriguing optoelectronic functionalities. Conventionally, 2D HPs have been synthesized with linear and planar molecular spacers, resulting in nominal modifications of their optoelectronic properties. In contrast, lower-dimensional HPs (0D and 1D) have proved accommodating to the incorporation of bulky molecular spacers. Fundamental insights into the incorporation of bulky molecular spacers in 2D HP structures remains elusive. Here, in this study, by implementing a high-throughput autonomous exploration workflow, the crystallization behaviours of 2D HPs based on a bulky 3,3-diphenylpropylammonium (DPA) spacer are comprehensively explored. Counterintuitive to conventional HP chemistry, synthesis of 2D DPA 2 PbI 4 HPs is indeed feasible when the steric hindrance is mediated by minute incorporation of 3D HP precursors. Furthermore, a moiré superlattice is observed from the DPA 2 PbI 4 flakes, indicating the spontaneous formation of twisted stacks of 2D HPs.We hypothesize that the unconventional van der Waals surface of DPA 2 PbI 4 facilitates the self-assembly of the twisted stacks of 2D HPs. This work exemplifies how high-throughput experimentation can discover unconventional material systems in which the synthetic principle lies beyond conventional chemical intuition. Furthermore, these findings provide hints for how to chemically manipulate the twist stacking in 2D HPs, thus rendering a straightforward way for bespoke realization of functionalities in exotic materials systems via a bottom-up approach.

materials chemistry↗

DOE OSTI2024

Beyond Human Vision: Exploring Materials with Machine Intelligence

Machine intelligence has the potential to revolutionize materials science, enabling autonomous synthesis, self-driving characterization, and accelerated modeling. However, despite the promise, successful implementation of these methods in day-to-day research remains a challenge. This talk will delve into the reasons behind this, exploring how truly intelligent experiments are hindered by opaque experiment control, a lack of domain-specific models, and human-centric design. Through a focus on the characterization of next-generation microelectronics and energy storage materials, I will share insights from both successful and failed attempts to implement machine intelligence. We will then explore the next steps necessary to unlock the full potential of machine intelligence in materials science, creating a future where intelligent systems work seamlessly alongside researchers to drive innovation and discovery.

artificial intelligence↗

DOE OSTI2024

FORCE Regression Testing

Via programs including the Light Water Reactor Sustainability and Integrated Energy Systems, the U.S. Department of Energy has invested in the Framework for Optimization of ResourCes and Economics (FORCE) software framework (Idaho National Laboratory 2024a) for the technical and economic analysis of nuclear-integrated energy systems (IES). Nuclear IES expand the use of nuclear from traditional baseload electricity generation to a flexible and adaptive source of combined heat and power. Nuclear heat can be used in the production of a variety of energy currencies such as hydrogen and ammonia as well as other heat applications including water desalination and district heating. FORCE is designed with the intent to provide interconnected analysis tools that enable the accurate technical and economic assessment of specific nuclear IES configurations for individual energy markets. FORCE consists of three main analysis pathways: HYBRID (Idaho National Laboratory 2024b), which contains high-resolution physical models for IES; Holistic Energy Resource Optimization Network (HERON) (Idaho National Laboratory 2024c), which analyzes IES long-term economic viability; and Optimization of Real-time Capacity Allocation (ORCA) (Idaho National Laboratory 2024d), designed for real-time control of IES via digital twins and optimal decision making, including autonomous and remote operation research. Development of the FORCE ecosystem is guided by three pillars: capability, which assures that the computational requirements of IES analysis are met by the software tools; reliability, which provides for consistent code performance and expected behaviors; and accessibility, which lowers the barrier to entry for using the software and accelerates analysis by users beyond the FORCE primary developers. Reliability of the FORCE ecosystem is established according to the American Nuclear Society?s Nuclear Quality Assurance (NQA-1) program [American Society of Mechanical Engineers 1982], with specific levels of software quality assurance (SQA) within NQA-1 applied to each software tool in FORCE. As the tools within FORCE have matured, some integration algorithms to accurately connect the software tools for holistic analysis have been developed and deployed within the FORCE software repository. In accordance with NQA-1 standards, regression tests are required to guarantee the software performs consistently even when new capabilities are added to the software. In this report, we document the deployment of both unit tests, which test the consistent behavior of small pieces of the FORCE code base, as well as integration tests, which test the consistent performance of full use cases for the FORCE integration algorithms. We further document the encapsulation of these tests within a test harness, which collectively checks for each successful test completion on demand. Finally, we document the automation of the test harness using GitHub Actions [GitHub 2024], which require all tests succeed before any new capability or other changes can be added to the FORCE integration software

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Regional surrogates for predictive control of digital twins

Digital twins of complex systems must involve a model that is fast, generalizable, and usable for real-time control. For example, high-fidelity nonlinear multiphysics simulations can capture laser-material interactions, but are too slow for optimization or model predictive control (MPC). Reduced-order models, used to accelerate such computation, frequently fail to generalize to unseen inputs or control states. We show theoretically that this failure is intrinsic, i.e., that a learned model is non-unique outside the sampled subspace when its low-rank structure arises from limited excitation and clustered eigenvalues, rather than from a user-imposed truncation alone. Motivated by this result, we propose a control-ready regional surrogate-construction framework for both autonomous and nonautonomous dynamics; it employs Koopman lifting to represent nonlinearities, while preserving spatial locality. We illustrate our approach by constructing a control-ready surrogate for the digital twin of a thermal component of additive-manufacturing process. Our surrogate, localized in space through a von Neumann stencil, is learned from noisy high-fidelity simulations that emulate thermal-camera images collected during the manufacturing. It is linear in thermo-physically augmented states so that MPC reduces to a convex quadratic program. The surrogate requires no online correction, generalizes to unseen scan paths and power profiles of the laser, and is more than three orders of magnitude faster than a finite-difference solver. Furthermore, when the MPC sequence computed on the digital twin is applied to this solver, closed-loop temperature regulation is recovered, showing that the surrogate preserves control-relevant input-output behavior.

Data-driven model↗

DOE OSTI2025

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency

Many workflows in high-energy-physics (HEP) stand to benefit from recent advances in transformer-based large language models (LLMs). While early applications of LLMs focused on text generation and code completion, modern LLMs now support orchestrated agency: the coordinated execution of complex, multi-step tasks through tool use, structured context, and iterative reasoning. We introduce the HEP Toolkit for Agentic Planning, Orchestration, and Deployment (HEPTAPOD), an orchestration framework designed to bring this emerging paradigm to HEP pipelines. The framework enables LLMs to interface with domain-specific tools, construct and manage simulation workflows, and assist in common utility and data analysis tasks through schema-validated operations and run-card-driven configuration. To demonstrate these capabilities, we consider a representative Beyond the Standard Model (BSM) Monte Carlo validation pipeline that spans model generation, event simulation, and downstream analysis within a unified, reproducible workflow. HEPTAPOD provides a structured and auditable layer between human researchers, LLMs, and computational infrastructure, establishing a foundation for transparent, human-in-the-loop systems.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗

DOE OSTI2024

Controlled patterning of crystalline domains by frontal polymerization

Materials with hierarchical architectures that combine soft and hard material domains with coalesced interfaces possess superior properties compared with their homogeneous counterparts. These architectures in synthetic materials have been achieved through deterministic manufacturing strategies such as 3D printing, which require an a priori design and active intervention throughout the process to achieve architectures spanning multiple length scales. Here we harness frontal polymerization spin mode dynamics to autonomously fabricate patterned crystalline domains in poly(cyclooctadiene) with multiscale organization. This rapid, dissipative processing method leads to the formation of amorphous and semi-crystalline domains emerging from the internal interfaces generated between the solid polymer and the propagating cure front. The size, spacing and arrangement of the domains are controlled by the interplay between the reaction kinetics, thermochemistry and boundary conditions. Small perturbations in the fabrication conditions reproducibly lead to remarkable changes in the patterned microstructure and the resulting strength, elastic modulus and toughness of the polymer. Furthermore, this ability to control mechanical properties and performance solely through the initial conditions and the mode of front propagation represents a marked advancement in the design and manufacturing of advanced multiscale materials. Drawing inspiration from biological systems in which structural complexity develops through dissipative reaction–diffusion processes, this study explores a transformative synthetic manufacturing strategy aimed at harnessing the principles underpinning morphogenic growth, unlocking new avenues for advanced materials design and fabrication. Synthetic coupled reaction-transport processes offer a versatile yet relatively underexplored method to manipulate the spatial attributes of synthetic materials10. Here we introduce an innovative manufacturing approach based on frontal ring-opening metathesis polymerization (FROMP) that draws parallels with morphogenic growth and development, enabling the formation of patterned microstructures within polymeric materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Web-based wide-area monitoring platform for ringdown and clustering analytics in power systems

This paper introduces an open-source research platform for monitoring the Mexican interconnected power grid, allowing real-time processing and information extraction of the grid’s dynamic condition. Moreover, the platform is a Python-based development that embeds different ringdown and clustering analytics tools. In the case of ringdown analysis, the modal information can be extracted using some of the most known algorithms, i.e., Prony analysis, eigensystem realization algorithm (ERA), and matrix pencil (MP). For clustering analysis, the coherent behaviour of generator and non-generator buses is provided by applying recent state-of-the-art techniques such as affinity propagation, K-means, hierarchical agglomerative clustering, and typicality data analysis. The results of up to 93 PMUs show that this open-source platform suits researchers’ and engineers’ power system dynamic analysis requirements.

Clustering↗

DOE OSTI2025

Observations of surface energy fluxes and meteorology in the seasonally snow-covered high-elevation East River watershed during SPLASH, 2021–2023

Abstract. From autumn 2021 through summer 2023, scientists from the National Oceanic and Atmospheric Administration (NOAA) and partners conducted the Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH) campaign in the East River watershed of Colorado. One objective of SPLASH was to observe the transfer of energy between the atmosphere and the surface, which was done at several locations. Two remote sites were chosen that did not have access to power utilities. These were along the valley floor near the East River in the vicinity of the unincorporated town of Gothic, Colorado. Energy balance measurements were made at these locations using autonomous, single-level flux towers referred to as atmospheric surface flux stations (ASFSs). The ASFSs were deployed on 28 September 2021 at the Kettle Ponds Annex site and on 12 October 2021 at the Avery Picnic site and operated until 19 July and 21 June 2023, respectively. Measurements included basic meteorology; upward and downward longwave and shortwave radiative fluxes and subsurface conductive flux, each at 1 min resolution; 3-D winds from a sonic anemometer and H2O/CO2 from an open-path gas analyzer, both at 20 Hz from which sensible, latent heat, and CO2 fluxes were derived; and profiles of soil properties in the upper 0.5 m (both sites) and temperature profiles through the snow (at Avery Picnic), each reported between 10 min and 6 h. The system uptime was 97 % (Kettle Ponds) and 90 % (Avery Picnic), and collectively 1184 d of data was obtained between the stations. The purpose of this article is to document the ASFS deployment at SPLASH, to document the data acquisition and post-processing of measurements, and to serve as a guide for interested users of the data sets, which are archived at Zenodo (https://doi.org/10.5281/zenodo.10313363, Cox et al., 2023b; https://doi.org/10.5281/zenodo.10327409, Cox et al., 2023c; https://doi.org/10.5281/zenodo.10313894, Cox et al., 2023d; https://doi.org/10.5281/zenodo.10307825, Cox et al., 2023e; https://doi.org/10.5281/zenodo.10310520, Cox et al., 2023f) with the Creative Commons Attribution 4.0 International license.

Cox, Christopher J. (ORCID:0000000322037173)↗

DOE OSTI2025

Differential equations for cosmological correlators

Cosmological fluctuations retain a memory of the physics that generated them in their spatial correlations. The strength of correlations varies smoothly as a function of external kinematics, which is encoded in differential equations satisfied by cosmological correlation functions. In this work, we provide a broader perspective on the origin and structure of these differential equations. As a concrete example, we study conformally coupled scalar fields in a power-law cosmology. The wavefunction coefficients in this model have integral representations, with the integrands being the product of the corresponding flat-space results and “twist factors” that depend on the cosmological evolution. Similar twisted integrals arise for loop amplitudes in dimensional regularization, and their recent study has led to the discovery of rich mathematical structures and powerful new tools for computing multi-loop Feynman integrals in quantum field theory. The integrals of interest in cosmology are also part of a finite-dimensional basis of master integrals, which satisfy a system of first-order differential equations. We develop a formalism to derive these differential equations for arbitrary tree graphs. The results can be represented in graphical form by associating the singularities of the differential equations with a set of graph tubings. Upon differentiation, these tubings grow in a local and predictive fashion. In fact, a few remarkably simple rules allow us to predict — by hand — the equations for all tree graphs. While the rules of this “kinematic flow” are defined purely in terms of data on the boundary of the spacetime, they reflect the physics of bulk time evolution. We also study the analogous structures in tr ϕ 3 theory, and see some glimpses of hidden structure in the sum over planar graphs. This suggests that there is an autonomous combinatorial or geometric construction from which cosmological correlations, and the associated spacetime, emerge.

Cosmological models↗