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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Detecting thermodynamic phase transition via explainable machine learning of photoemission spectroscopy

Identifying thermodynamic signatures of electronic phases, such as superconductivity, is challenging in low-dimensional materials due to strong fluctuations and low probing volume. Spectroscopic methods are often used to identify new bulk phases, but their main measurable quantity—electronic energy gaps—is no longer an effective order parameter in low-dimensional and fluctuating systems. Combining angle-resolved photoemission with a domain-adversarial neural network, we report a data-driven method to identify thermodynamic phase transitions solely based on single-particle spectra. We demonstrate 97.6% accuracy in cuprate superconductor Bi 2 Sr 2 CaCu 2 O 8+δ with strong superconducting fluctuations. This model notably compensates for the scarcity of experimental data by leveraging virtually inexhaustible simulated data. Further, its explainability reveals the crucial role of in-gap spectral weight in detecting phase fluctuations and thermodynamic transitions. Our work pinpoints the spectroscopic signatures of fluctuating orders and enables using spectroscopy for machine-learning-assisted material discovery for low-dimensional and strong coupling systems.

2D materials↗
DOE OSTI2026

MoNbTi-based Refractory Multi-principal Element Alloy System: A Review of the Thermodynamic Phase Predictions, Formed Microstructures, and Mechanical Properties as a Function of the Fabrication Methods (AM versus SPS versus VAM)

Abstract Multi-principal element alloys, particularly of refractory compositions, are an increasingly popular candidate for extreme-environment applications, including for next-generation nuclear reactors and in other industries, such as biomedical and aerospace, due to their high strength. The ability to achieve solid-solution microstructures provides these alloys with improved mechanical properties; however, these microstructures are heavily composition- and processing-dependent. In this review, the multi-principal element alloy MoNbTi-based system (with Zr, V, and Cr additions) was selected to compare the effects of elemental composition and processing route on the resulting microstructures and mechanical properties. The review provides insight into identifying the optimal alloy composition and processing route for a balance of desired microstructure and mechanical properties.

Krogh, Kara↗
DOE OSTI2025

Thermodynamic phase transitions of nematic order in magnetic helices

A nematic phase lacks translation order but has orientational order. Nematic phases have been discovered in a variety of systems, including liquid crystals, correlated materials, and superconductors. Here, we report on a magnetic nematic phase, where the basis components are composed of magnetic helices. We directly probed the order parameters associated with the magnetic helices using resonant soft x-ray scattering and find two distinct nematic phases with complex spatiotemporal signatures. Using x-ray correlation spectroscopy, we find that near the phase boundary between the two nematic phases, fluctuations coexist on multiple disparate timescales. Our micromagnetic simulations and density functional theory calculations show that the fluctuations occur concomitantly with a reorientation of the magnetic helices, indicating spontaneous symmetry breaking and the emergence of additional degrees of freedom. Our results provide a framework for characterizing exotic phases that can be extended to a broad class of physical systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Classifying thermodynamic cloud phase using machine learning models

Vertically resolved thermodynamic cloud-phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave-radiometer-derived liquid water path, and radiosonde temperature measurements. The measured pixels are classified as ice, snow, mixed phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1 score, and mean intersection over union (IOU). Analysis of ML confidence scores shows that ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. The ML models' generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗
DOE OSTI2025

Thermodynamic Cloud Phase Classifications Using Machine Learning at NSA and ANX

Vertically resolved thermodynamic cloud phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) THERMOCLDPHASE Value-Added Product (VAP) uses a multi-sensor approach to classify thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave radiometer-derived liquid water path, and radiosonde temperature measurements. The measured voxels are classified as ice, snow, mixed-phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multilayer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with one year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1-score, and mean Intersection over Union (IOU). Analysis of ML confidence scores shows ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential datastreams for ML thermodynamic cloud phase predictions. The ML models’ generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. Finally, we evaluate the ML models’ response to simulated instrument outages and signal degradation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

ARM Thermodynamic Cloud Phase (THERMOCLDPHASE) Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s Thermodynamic Cloud Phase (THERMOCLDPHASE) Value-Added Product (VAP) provides vertically resolved thermodynamic cloud phase classifications (Zhang and Levin 2024). This VAP applies the multi-sensor methodology introduced by Shupe (2007) to identify cloud phase at the pixel level as liquid, drizzle, liquid + drizzle, rain, ice, snow, or mixed-phase. In addition, the VAP determines the overall cloud layer phase—classified as liquid, mixed-phase, or ice—based on the fraction of ice-containing pixels within the entire layer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Bromine Incorporation Affects Phase Transformations and Thermal Stability of Lead Halide Perovskites

Mixed-cation and mixed-halide lead halide perovskites show great potential for their application in photovoltaics. Many of the high-performance compositions are made of cesium, formamidinium, lead, iodine, and bromine. However, incorporating bromine in iodine-rich compositions and its effects on the thermal stability of the perovskite structure has not been thoroughly studied. In this work, we study how replacing iodine with bromine in the state-of-the-art Cs 0.17 FA 0.83 PbI 3 perovskite composition leads to different dynamics in the phase transformations as a function of temperature. Through a combination of structural characterization, cathodoluminescence mapping, X-ray photoelectron spectroscopy, and first-principles calculations, we reveal that the incorporation of bromine reduces the thermodynamic phase stability of the films and shifts the products of phase transformations. Our results suggest that bromine-driven vacancy formation during high temperature exposure leads to irreversible transformations into PbI 2 , whereas materials with only iodine go through transformations into hexagonal polytypes, such as the 4H-FAPbI 3 phase. This work sheds light on the structural impacts of adding bromine on thermodynamic phase stability and provides new insights into the importance of understanding the complexity of phase transformations and secondary phases in mixed-cation and mixed-halide systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

thermocldphase

ARM VAP deriving the thermodynamic phase of water in clouds.

cloud↗
DOE OSTI2024

Partition between supercooled liquid droplets and ice crystals in mixed-phase clouds based on airborne in situ observations

Abstract. The onset of ice nucleation in mixed-phase clouds determines the lifetime and microphysical properties of ice clouds. In this work, we develop a novel method that differentiates between various phases of mixed-phase clouds, such as clouds dominated by pure liquid or pure ice segments, compared with those having ice crystals surrounded by supercooled liquid water droplets or vice versa. Using this method, we examine the relationship between the macrophysical and microphysical properties of Southern Ocean mixed-phase clouds at −40 to 0 °C (e.g. stratiform and cumuliform clouds) based on the in situ aircraft-based observations during the US National Science Foundation Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES) flight campaign. The results show that the exchange between supercooled liquid water and ice crystals from a macrophysical perspective, represented by the increasing spatial ratio of regions containing ice crystals relative to the total in-cloud region (defined as ice spatial ratio), is positively correlated with the phase exchange from a microphysical perspective, represented by the increasing ice water content (IWC), decreasing liquid water content (LWC), increasing ice mass fraction, and increasing ice particle number fraction (IPNF). The mass exchange between liquid and ice becomes more significant during phase 3 when pure ice cloud regions (ICRs) start to appear. Occurrence frequencies of cloud thermodynamic phases show a significant phase change from liquid to ice at a similar temperature (i.e. −17.5 °C) among three types of definitions of mixed-phase clouds based on ice spatial ratio, ice mass fraction, or IPNF. Aerosol indirect effects are quantified for different phases using number concentrations of aerosols greater than 100 or 500 nm (N>100 and N>500, respectively). N>500 shows stronger positive correlations with ice spatial ratios compared with N>100. This result indicates that larger aerosols potentially contain ice-nucleating particles (INPs), which facilitate the formation of ice crystals in mixed-phase clouds. The impact of N>500 is also more significant in phase 2 when ice crystals just start to appear in the mixed phase compared with phase 3 when pure ICRs have formed, possibly due to the competing aerosol indirect effects on primary and secondary ice production in phase 3. The thermodynamic and dynamic conditions are quantified for each phase. The results show stronger in-cloud turbulence and higher updraughts in phases 2 and 3 when liquid and ice coexist compared with pure liquid or ice (phases 1 and 4, respectively). The highest updraughts and turbulence are seen in phase 3 when supercooled liquid droplets are surrounded by ice crystals. These results indicate both updraughts and turbulence support the maintenance of supercooled liquid water amongst ice crystals. Overall, these results illustrate the varying effects of aerosols, thermodynamics, and dynamics through various stages of mixed-phase cloud evolution based on this new method that categorizes cloud phases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Jacobian-free pseudo-arclength continuation method for phase transitions in inhomogeneous thermodynamic systems

Developing phase diagrams for inhomogeneous systems in thermodynamics is difficult, in part, due to the large phase space and the possibility of unstable and metastable solutions arising from first-order phase transitions. Pseudo-arclength continuation (PAC) is a method that allows one to trace out stable and unstable solutions of nonlinear systems. Typically, PAC utilizes the Jacobian in order to implement Newton (or quasi-Newton) steps. In this work, we present a Jacobian-free PAC method that is amenable to the usual workflows in inhomogeneous thermodynamics. We demonstrate our method in systems that have first-order phase transitions, including a novel example of polyelectrolyte complex coacervation in confinement, where multiple surface phase transitions occur and can overlap with one another.

Chemistry↗
DOE OSTI2025

Kinetic Understanding of Field-Induced Phase Transition from Tetragonal to Ferroelectric Orthorhombic Phase in Ferroelectric CeO 2 –HfO 2 –ZrO 2 Films

The ferroelectric properties and structural phase transition behaviors of fluorite-type CeO 2 −HfO 2 −ZrO 2 films were investigated. The epitaxial films on indium tin oxide (ITO) (111)/yttria-stabilized zirconia (YSZ) (111) substrates were grown through pulsed laser deposition at room temperature and subsequently heat-treated at 1000 °C under a N 2 gas flow. The crystalline phases and Curie temperatures of the films were investigated by X-ray diffraction. An increase in the Ce or Zr content in the films led to a higher crystallographic symmetry, such as orthorhombic or tetragonal. In addition, electrical characterization revealed that the orthorhombic films and some of the tetragonal films displayed ferroelectricity. This was due to the field-induced phase transition from the tetragonal to ferroelectric orthorhombic phase in the films, where the Curie temperatures were relatively low. The tetragonal metastable phase was kinetically frozen and could not change into the stable orthorhombic phase at such a low temperature. The critical electric field where the field-induced phase transition occurred was below 0.8 MV/cm, which was sufficiently small compared to the coercive field. These results evidence the kinetic driving force that causes a field-induced phase transition from the paraelectric tetragonal phase to the ferroelectric orthorhombic phase in HfO 2 -based ferroelectrics. They also enhance our understanding of the thermodynamic phase stabilities of HfO 2 -based material polymorphs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Observation of stacking engineered magnetic phase transitions within moiré supercells of twisted van der Waals magnets

Abstract Recent demonstrations of moiré magnetism, featuring exotic phases with noncollinear spin order in the twisted van der Waals (vdW) magnet chromium triiodide CrI 3 , have highlighted the potential of twist engineering of magnetic (vdW) materials. However, the local magnetic interactions, spin dynamics, and magnetic phase transitions within and across individual moiré supercells remain elusive. Taking advantage of a scanning single-spin magnetometry platform, here we report observation of two distinct magnetic phase transitions with separate critical temperatures within a moiré supercell of small-angle twisted double trilayer CrI 3 . By measuring temperature-dependent spin fluctuations at the coexisting ferromagnetic and antiferromagnetic regions in twisted CrI 3 , we explicitly show that the Curie temperature of the ferromagnetic state is higher than the Néel temperature of the antiferromagnetic one by ~10 K. Our mean-field calculations attribute such a spatial and thermodynamic phase separation to the stacking order modulated interlayer exchange coupling at the twisted interface of moiré superlattices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

KBKit: A Python Toolkit for Kirkwood–Buff Theory from Molecular Dynamics

Thermodynamic properties of liquid mixtures govern processes that range from drug delivery to energy storage, yet extracting these properties from molecular simulations remains challenging. Kirkwood–Buff (KB) theory offers a rigorous route by linking microscopic pair distribution functions to macroscopic free energies, but practical use of the theory has been hindered by two obstacles: (i) the long simulations needed to obtain well-converged Kirkwood-Buff integrals (KBIs) and (ii) the specialized corrections required to translate finite-size data to the thermodynamic limit. $\texttt{KBKit}$ is an open-source Python package that removes these barriers. It automatically computes KBIs and derived thermodynamic quantities from GROMACS input files, applies state-of-the-art finite-size corrections, and provides built-in diagnostic tools to quantify statistical uncertainty. Written with modern software-engineering practices—continuous integration, extensive unit testing, and thorough documentation—$\texttt{KBKit}$ is both reliable and easy to extend. By condensing complex KBI analysis into a few intuitive commands, $\texttt{KBKit}$ enables researchers to incorporate KB theory into routine simulation workflows and accelerate the discovery of solution-phase thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Exploring Cr and molten salt interfacial interactions for molten salt applications

Molten salts play an important role in various energy-related applications such as high-temperature heat transfer fluids and reaction media. However, the extreme molten salt environment causes the degradation of materials, raising safety and sustainability challenges. A fundamental understanding of material–molten salt interfacial evolution is needed. This work studies the transformation of metallic Cr in molten 50/50 mol% KCl–MgCl 2 via multi-modal in situ synchrotron X-ray nano-tomography, diffraction and spectroscopy combined with density functional theory (DFT) and ab initio molecular dynamics (AIMD) simulations. Notably, in addition to the dissolution of Cr in the molten salt to form porous structures, a δ-A15 Cr phase was found to gradually form as a result of the metal–salt interaction. This phase change of Cr is associated with a change in the coordination environment of Cr at the interface. DFT and AIMD simulations provide a basis for understanding the enhanced stability of δ-A15 Cr vs. bcc Cr, by revealing their competitive phase thermodynamics at elevated temperatures and probing the interfacial behavior of the molten salt at relevant facets. This study provides critical insights into the morphological and chemical evolution of metal–molten salt interfaces. Finally, the combination of multimodal synchrotron analysis and atomic simulation also offers an opportunity to explore a broader range of systems critical to energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Field Validation of Cloud Properties Sensor Field Campaign Report

The purpose of this campaign is to deploy Aerodyne Research Inc.’s extended wavelength cloud optical properties sensor (TWST-EN) in an operationally relevant environment with co-located, validated sensors. The Atmospheric Radiation Measurement (ARM) user facility’s Southern Great Plains (SGP) observatory is ideal for this deployment because of the variety of operational sensors that can measure some of the same cloud properties using different modalities. While cloud property sensors have long existed, they tend to be costly to produce and maintain. Our sensor measures absolute spectral radiance in the two bands and will retrieve cloud optical depth (COD), droplet effective radius, and thermodynamic phase. Our prototype is built predominantly from off-the-shelf components and uses uncooled spectrometers. A lower-cost, easy-to-use sensor such as this could allow deployment at many more sites for greater spatial coverage. Analysis and retrieval algorithm development using the data from this deployment has been a central technical objective of our U.S. Department of Energy Small Business Innovative Research (SBIR) Phase 2 contract (DE-SC0020473: Low-Cost Shortwave Spectroradiometer for Retrieval of Cloud Properties).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Tuning Optical and Electrical Properties of Vanadium Oxide with Topochemical Reduction and Substitutional Tin

Vanadium oxides are widely tunable materials, with many thermodynamically stable phases suitable for applications spanning catalysis to neuromorphic computing. The stability of vanadium in a range of oxidation states enables mixed-valence polymorphs of kinetically accessible metastable materials. Low-temperature synthetic routes to, and the properties of, these metastable materials are poorly understood and may unlock new optoelectronic and magnetic functionalities for expanded applications. In this work, we demonstrate topochemical reduction of α-V 2 O 5 to produce metastable vanadium oxide phases with tunable oxygen vacancies (>6%) and simultaneous substitutional tin incorporation (>3.5%). The chemistry is carried out at low temperature (65 °C) with solution-phase SnCl 2 , where Sn 2+ is oxidized to Sn 4+ as V 5+ sites are reduced to V 4+ during oxygen vacancy formation. Despite high oxygen vacancy and tin concentrations, the transformations are topochemical in that the symmetry of the parent crystal remains intact, although the unit cell expands. Band structure calculations show that these vacancies contribute electrons to the lattice, whereas substitutional tin contributes holes, yielding a compensation doping effect and control over the electronic properties. The SnCl 2 redox chemistry is effective on both solution-processed V 2 O 5 nanoparticle inks and mesoporous films cast from untreated inks, enabling versatile routes toward functional films with tunable optical and electronic properties. The electrical conductance rises concomitantly with the SnCl 2 concentration and treatment time, indicating a net increase in density of free electrons in the host lattice. This work provides a valuable demonstration of kinetic tailoring of electronic properties of vanadium–oxygen systems through top-down chemical manipulation from known thermodynamic phases.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Epitaxial 2D Magnet and Topological Insulator Heterostructures

I will discuss our latest advances on the epitaxial growth of 2D van der Waals (vdW) magnets and their integration with topological insulators (TI). This work is motivated by the realization of topological phases such as the quantum anomalous Hall effect and highly efficient spin-orbit torque produced by TIs. Our initial studies of MnSe2 growth on Bi2Se3 showed a tendency for the interdiffusion of Mn into the Bi2Se3. This ultimately led to the synthesis of MnBi2Se4 (MBS), a new magnetic TI. Interestingly, the vdW phase is not the thermodynamically stable phase and bulk crystals do not exist, so the epitaxial stabilization of MBS creates the opportunity to explore the magnetic and topological properties of this material. We find that MBS is a layered antiferromagnet, similar to MnBi2Te4, but a difference is that the magnetic moments lie in the plane of the film. Angle resolved photoemission experiments show the presence of a topological surface state with Dirac dispersion. For bilayers of 2D magnets and TIs, we have developed FGT films on Bi2Te3. We first optimized FGT by studying its growth on Ge(111) substrates, where we find that kinetic considerations play a major role. Using cross-sectional scanning transmission electron microscopy and scanning tunneling microscopy, we optimize the FGT films to have atomically smooth surfaces and abrupt interfaces with the Ge(111). Subsequently, we have developed the growth of FGT on Bi2Te3 for the integration of 2D magnets with Tis. Interestingly, we observe room temperature ferromagnetism in FGT/Bi2Te3 heterostructures by varying the growth conditions.

Kawakami, Roland↗