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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

RELAP5-3D Modeling in the OECD-NEA HTTF Benchmark

Prismatic gas-cooled reactors are a technologically mature reactor concept of interest for near- to mid-term deployment. To accelerate the deployment of these reactors, the DOE's Advanced Reactor Technologies Gas-Cooled Reactor campaign is spearheading a thermal hydraulics code validation benchmark based on the High Temperature Test Facility at Oregon State University. This presentation provides an introduction to that benchmark and an overview of some of the RELAP5-3D validation activities stemming from that benchmark.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

2D-EFICACY: Control of Metastable 2D Carbide[1]Chalcogenide Heterolayers: Strain and Moire Engineering

The experimental isolation of graphene led to the discovery of an entirely new world of two-dimensional (2D) materials in which the 2D nature often leads to emergent behaviors not seen in bulk systems. 2D transition metal dichalcogenides (TMDs) exhibit physico-chemical properties that depend on the transition metal, polymorph, thickness, and presence and type of defects. Recently, a group of thin (10-100nm) transition metal carbides (TMCs), such as Mo2C, has been synthesized that exhibit a thickness-dependent superconducting critical temperature (Tc). These thin TMCs are different from MXenes, another class of 2D materials consisting of few layers of nitrides or carbides (<5nm) produced by chemical etching and delamination. The goal of this renewal proposal is to combine experiment and computation to synthesize and elucidate the guiding principles that control the growth, orientation and strain of heterostacks of thin TMCs and TMDs composed with Nb, Ti and W. We expect to stabilize metastable hybrid phases of TMCs sandwiched between TMDs (H-TMD/Cs) with unprecedented physico-chemical properties. As part of previous DOE-funded work by the Terrones/Sinnott groups, thin (10-100 nm thick) Mo2C flakes were successfully synthesized by chemical vapor deposition (CVD). By subsequently exposing Mo2C to H2S, partial chalcogenization was achieved, resulting in heterostacks of MoCx phases and MoS2. The formation of MoS2 led to a deficiency of Mo atoms in the underlying Mo2C, resulting in an inhomogeneous phase change from α-Mo2C to γ’-MoCx and then to γ-MoC. The γ’-MoCx is a strained metastable phase and the heterostack of all three phases demonstrated an increased Tc relative to that of α-Mo2C, from 4 to 6K; its interleaved layered structure consisting of superconducting and semiconducting phases is ideal for future studies of Josephson junction series arrays. Moiré patterns in these heterostacked systems could result in new phenomena, as moiré patterns in bilayer graphene showed unconventional superconductivity and moiré excitons have been observed in twisted TMD heterobilayers. The scientific hypothesis of the proposed synergistic computational and experimental research is that orientation and strain control within confined thin metastable TMCs, sandwiched by stable phases of TMCs and layered TMDs, will depend on kinetic and thermodynamic “knobs” that include fast temperature changes, chalcogen diffusion through preferred crystallographic planes, reaction times, pressure, reactive atmosphere, precursors, and surfactants, which will also tailor properties such as superconductivity, magnetism, ferroelectricity, piezoelectricity, and catalytic performance. We will develop the guiding principles for the synthesis and stabilization of metastable H-TMD/Cs based on Nb, Ti and W. In order to validate the hypothesis, four tasks are proposed: The first task will synthesize ultra-thin TMCs based on Nb, W and Ti, by: 1) adapting the CVD method used for Mo2C, 2) plasma assisted CVD, 3) defect-mediated CVD processes, and 4) cryo-milling of carbide powders. The second task will accomplish the synthesis and basic physico-chemical characterizations of H-TMD/Cs by chalcogenization of the materials synthesized in task one, and by carbonization of TMDs. H-TMD/Cs will also be investigated for their suitability in energy conversion applications such as supercapacitors, Li and multivalent ion batteries, and electrocatalysts, topics of interest to DoE. These tasks will be carried out in close conjunction with density functional theory (DFT) calculations with insights into energetics, lattice parameters, stability, phase diagrams, band structures, and density of states of H-TMD/Cs. The third task will characterize and evaluate strain and moiré patterns at the interfaces of different H-TMD/Cs by high-resolution scanning transmission electron microscopy (HR-STEM), scanning tunneling microscopy (STM), and conductive tip atomic force microscopy. Nudged elastic band calculations with DFT will be performed to understand the chalcogen diffusion process, which will provide insights into the interfaces between different phases of TMCs and TMDs. The fourth task aims at quantifying the stability and dynamics of H-TMD/Cs by in-situ TEM and Raman studies under heating, strain, and electrical biasing. Phonon calculations using DFT will provide a basis for interpreting Raman spectra. This coherent framework involving synthesis, characterization, and computation will result in a broad scientific impact for energy related applications. The ability to develop new H-TMD/Cs will enhance a range of applications that include batteries, catalysts, switches, sensors, quantum computing components and smart coatings.

2-Dimensional materials↗
DOE OSTI2024

2D-EFICACY: Control of Metastable 2D Carbide Chalcogenide Heterolayers: Strain and Moire Engineering

The experimental isolation of graphene led to the discovery of an entirely new world of two-dimensional (2D) materials in which the 2D nature often leads to emergent behaviors not seen in bulk systems. 2D transition metal dichalcogenides (TMDs) exhibit physico-chemical properties that depend on the transition metal, polymorph, thickness, and presence and type of defects. Recently, a group of thin (10-100nm) transition metal carbides (TMCs), such as Mo 2 C, has been synthesized that exhibit a thickness-dependent superconducting critical temperature (Tc). These thin TMCs are different from MXenes, another class of 2D materials consisting of few layers of nitrides or carbides (<5nm) produced by chemical etching and delamination. The goal of this renewal proposal is to combine experiment and computation to synthesize and elucidate the guiding principles that control the growth, orientation and strain of heterostacks of thin TMCs and TMDs composed with Nb, Ti and W. We expect to stabilize metastable hybrid phases of TMCs sandwiched between TMDs (H-TMD/Cs) with unprecedented physico-chemical properties. As part of previous DOE-funded work by the Terrones/Sinnott groups, thin (10-100 nm thick) Mo 2 C flakes were successfully synthesized by chemical vapor deposition (CVD). By subsequently exposing Mo 2 C to H 2 S, partial chalcogenization was achieved, resulting in heterostacks of MoCx phases and MoS 2 . The formation of MoS 2 led to a deficiency of Mo atoms in the underlying Mo 2 C, resulting in an inhomogeneous phase change from α-Mo 2 C to γ’-MoCx and then to γ-MoC. The γ’-MoCx is a strained metastable phase and the heterostack of all three phases demonstrated an increased Tc relative to that of α-Mo 2 C, from 4 to 6K; its interleaved layered structure consisting of superconducting and semiconducting phases is ideal for future studies of Josephson junction series arrays. Moiré patterns in these heterostacked systems could result in new phenomena, as moiré patterns in bilayer graphene showed unconventional superconductivity and moiré excitons have been observed in twisted TMD heterobilayers. The scientific hypothesis of the proposed synergistic computational and experimental research is that orientation and strain control within confined thin metastable TMCs, sandwiched by stable phases of TMCs and layered TMDs, will depend on kinetic and thermodynamic “knobs” that include fast temperature changes, chalcogen diffusion through preferred crystallographic planes, reaction times, pressure, reactive atmosphere, precursors, and surfactants, which will also tailor properties such as superconductivity, magnetism, ferroelectricity, piezoelectricity, and catalytic performance. We will develop the guiding principles for the synthesis and stabilization of metastable H-TMD/Cs based on Nb, Ti and W. In order to validate the hypothesis, four tasks are proposed: The first task will synthesize ultra-thin TMCs based on Nb, W and Ti, by: 1) adapting the CVD method used for Mo 2 C, 2) plasma assisted CVD, 3) defect-mediated CVD processes, and 4) cryo-milling of carbide powders. The second task will accomplish the synthesis and basic physico-chemical characterizations of H-TMD/Cs by chalcogenization of the materials synthesized in task one, and by carbonization of TMDs. H-TMD/Cs will also be investigated for their suitability in energy conversion applications such as supercapacitors, Li and multivalent ion batteries, and electrocatalysts, topics of interest to DoE. These tasks will be carried out in close conjunction with density functional theory (DFT) calculations with insights into energetics, lattice parameters, stability, phase diagrams, band structures, and density of states of H-TMD/Cs. The third task will characterize and evaluate strain and moiré patterns at the interfaces of different H-TMD/Cs by high-resolution scanning transmission electron microscopy (HR-STEM), scanning tunneling microscopy (STM), and conductive tip atomic force microscopy. Nudged elastic band calculations with DFT will be performed to understand the chalcogen diffusion process, which will provide insights into the interfaces between different phases of TMCs and TMDs. The fourth task aims at quantifying the stability and dynamics of H-TMD/Cs by in-situ TEM and Raman studies under heating, strain, and electrical biasing. Phonon calculations using DFT will provide a basis for interpreting Raman spectra. This coherent framework involving synthesis, characterization, and computation will result in a broad scientific impact for energy related applications. The ability to develop new H-TMD/Cs will enhance a range of applications that include batteries, catalysts, switches, sensors, quantum computing components and smart coatings.

2-Dimensional Materials↗
DOE OSTI2022

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy

Abstract Physics‐driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here, this work develops and experimentally implements a deep kernel learning (DKL) workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics‐based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization (BO) methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure–property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk‐ and edge plasmon discovery in MnPS 3 , a lesser‐known beam‐sensitive layered 2D material. This approach is universal, can be directly used as‐is with any specimen, and is expected to be applicable to any probe‐based microscopic techniques including other STEM modalities, scanning probe microscopies, chemical, and optical imaging.

42 ENGINEERING↗
DOE OSTI2021

Scattering Matrix Determination in Crystalline Materials from 4D Scanning Transmission Electron Microscopy at a Single Defocus Value

Recent work has revived interest in the scattering matrix formulation of electron scattering in transmission electron microscopy as a stepping stone toward atomic-resolution structure determination in the presence of multiple scattering. Here, we discuss ways of visualizing the scattering matrix that make its properties clear. Through a simulation-based case study incorporating shot noise, we shown how regularizing on this continuity enables the scattering matrix to be reconstructed from 4D scanning transmission electron microscopy (STEM) measurements from a single defocus value. Intriguingly, for crystalline samples, this process also yields the sample thickness to nanometer accuracy with no a priori knowledge about the sample structure. The reconstruction quality is gauged by using the reconstructed scattering matrix to simulate STEM images at defocus values different from that of the data from which it was reconstructed.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Differences in urban plant community compositions across an urban-rural gradient in Knoxville, TN

Urban forests, or vegetation in areas under heavy human influence, provide many ecosystem services to urban residents such as localized cooling via evapotranspiration, shade, filtering of air pollution, and the associated health benefits of natural spaces. In order to quantify the magnitude of localized cooling by trees growing in varying levels of urbanization (based on % impervious surfaces, e.g., buildings, pavement), urban forest species composition, tree size, and tree density must be characterized. As a part of Oak Ridge National Laboratory’s (ORNL) urban forest temperature study, we conducted tree censuses in five Knoxville city parks where ORNL meteorological stations are deployed. Moreover, we measured every woody plant ≥ 5 cm diameter at breast height (DBH) within a 50 m radius of each site’s meteorological station for its DBH and species identification. When possible, individuals were identified down to species. Certain genera (Quercus spp., Carya spp., Pinus spp.) were identified down to genera in interest of time. Individual and total site basal area were calculated from measured DBH data. Results show notable differences in urban plant community compositions and total woody plant basal area across sites, with more urban sites closer to downtown (West View and SEEED) having lower tree basal area than the more suburban sites (West Hills, Cumberland Estates, and Victor Ashe). We identified 54 species across all sites, with West Hills and Victor Ashe having the highest species diversity. Our results show differences in forest compositions and sizes across Knoxville, which are currently informing ORNL’s evapotranspiration estimates for each site. Data Summary: Census data for West Hills (WH), Cumberland Estates (CE), Victor Ashe (VA), West View (WV), and Socially Equal Energy Efficient Development or SEEED (SD) urban forests in Knoxville, TN, USA, including tree size based on diameter at breast height (DBH; 1.3 m), species identification (Latin and common names), and basal area per stem (BA=π×[.5*DBH]^2). Field data are summarized in this file: “Community_Composition_Data.CSV”. Site-specific data detailing each site’s coordinates, number of stems measured at DBH, average tree DBH, α-diversity (number of species present), and total site basal area (sum of individual basal areas per site) are in this file: “Site_Comparisons.CSV”.

Warren, Jeffrey [ORNL] (ORCID:0000000206804697)↗
DOE OSTI2022

The role of temperature on defect diffusion and nanoscale patterning in graphene

Graphene is of great scientific interest due to a variety of unique properties such as ballistic transport, spin selectivity, the quantum hall effect, and other quantum properties. Nanopatterning and atomic scale modifications of graphene are expected to enable further control over its intrinsic properties, providing ways to tune the electronic properties through geometric and strain effects, introduce edge states and other local or extended topological defects, and sculpt circuit paths. The focused beam of a scanning transmission electron microscope (STEM) can be used to remove atoms, enabling milling, doping, and deposition. Utilization of a STEM as an atomic scale fabrication platform is increasing; however, a detailed understanding of beam-induced processes and the subsequent cascade of aftereffects is lacking. Here, we examine the electron beam effects on atomically clean graphene at a variety of temperatures ranging from 400 to 1000 °C. We find that temperature plays a significant role in the milling rate and moderates competing processes of carbon adatom coalescence, graphene healing, and the diffusion (and recombination) of defects. The results of this work can be applied to a wider range of 2D materials and introduce better understanding of defect evolution in graphite and other bulk layered materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Stochastic Techno Economic Model

The Stochastic Techno-Economic Model or STEM is an analytical tool that estimates the logistics cost of different biomass feedstocks by incorporating uncertainty into the modeling framework. The scope of the model covers multiple stages of the biomass life cycle spanning feedstock harvest, collection, transportation and handling, preprocessing, and storage. The model determines the total logistics cost per dry metric ton ($/DM ton) for biomass and breaks down the costs for important cost categories including ownership related costs such as interest and depreciation, insurance, housing, and taxes as well as operating costs like repairs and maintenance, labor costs, and fuel and lube costs.

Burli, PralhadH↗
DOE OSTI2020

Non-autoregressive time-series methods for stable parametric reduced-order models

Advection-dominated dynamical systems, characterized by partial differential equations, are found in applications ranging from weather forecasting to engineering design where accuracy and robustness are crucial. There has been significant interest in the use of techniques borrowed from machine learning to reduce the computational expense and/or improve the accuracy of predictions for these systems. These rely on the identification of a basis that reduces the dimensionality of the problem and the subsequent use of time series and sequential learning methods to forecast the evolution of the reduced state. Often, however, machine-learned predictions after reduced-basis projection are plagued by issues of stability stemming from incomplete capture of multiscale processes as well as due to error growth for long forecast durations. To address these issues, we have developed a non-autoregressive time series approach for predicting linear reduced-basis time histories of forward models. In particular, we demonstrate that non-autoregressive counterparts of sequential learning methods such as long short-term memory (LSTM) considerably improve the stability of machine-learned reduced-order models. Further, we evaluate our approach on the inviscid shallow water equations and show that a non-autoregressive variant of the standard LSTM approach that is bidirectional in the principal component directions obtains the best accuracy for recreating the nonlinear dynamics of partial observations. Moreover-and critical for many applications of these surrogates-inference times are reduced by three orders of magnitude using our approach, compared with both the equation-based Galerkin projection method and the standard LSTM approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Tailoring P2/P3‐Intergrowth in Manganese‐Based Layered Transition Metal Oxide Positive Electrodes via Sodium Content for Na‐Ion Batteries

High-manganese content sodium-ion positive electrodes have received heightened interest as an alternative to contemporary Li-ion chemistries due to their high abundance, low toxicity, and even geographical distribution. However, these materials typically suffer from poor capacity, unstable cycling performance, and sluggish Na + kinetics. Herein, we explore a manganese-based layered transition metal oxide (Na x N 0.25 Mn 0.75 O 2 ) and show by X-ray diffraction (XRD) and high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) that careful variation of the sodium content can instigate the formation of a biphasic intergrowth. This intergrown P2/P3 material offered a higher capacity than its monophasic P2 counterpart due to the P3 structure having greater low-voltage Mn 3+/4+ redox. Further, the intergrowth material offers greatly enhanced kinetics and cycling stability when compared to single-phase P3 material, due to the stabilizing nature of the P2 structure, elucidated by galvanostatic intermittent titration technique (GITT) and operando synchrotron X-ray diffraction. These results highlight the beneficial effect that the intergrowth structure has on the electrochemical performance of high-manganese content positive electrode for future sodium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2020

Synergistic enhancement of nanocellulose foam with dual in situ mineralization and crosslinking reaction

Cellulose nanocrystals (CNCs) foams have recently gained research interests because they are renewable, abundant, biodegradable and exhibit high surface area. However, the application of CNCs-based foams is still challenging, which is attributed to its lack of effective entanglements between the CNCs particles, thus lowering foam properties. In this study, a synergistic enhancement strategy was proposed, based on the in situ mineralization with hydroxyapatite (HAP) layer onto the CNCs surface, followed by a chemical crosslinking reaction. The physical and chemical structures of the composites were analyzed with SEM, STEM, XRD, FTIR, and TGA. By controlling the amount of coated HAP and the crosslinker, it is possible to manufacture a series of CNCs-based foams that are lightweight (50–75 mg/cm 3 ), highly porous (~90%) with high water absorption (>1300%) and outstanding mechanical strength properties (as high as 1.37 MPa). Moreover, our study further indicated that these CNCs/HAP materials could increase the proliferation of rat osteoblast cells. The method developed in this study presents a novel approach to design improved networked CNCs foam, which has the potential to be used in thermal-retardant material, wastewater treatment, tissue engineering, and personal care applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

In Situ Formation of Ripplocations in Hybrid Organic–Inorganic MXenes

Abstract Inorganic–organic hybrid MXenes (h‐MXenes) are a family of 2D transition metal carbides and nitrides functionalized with alkylimido and alkylamido surface groups. Using cryogenic and room temperature scanning transmission electron microscopy (STEM) and electron energy‐loss spectroscopy (EELS), it is shown that ripplocations, a form of a fundamental defect in 2D and layered structures, are abundant in this family of materials. Furthermore, detailed studies of electron probe sample interactions, focusing on structural deformations caused by the electron beam are presented. The findings indicate that at cryogenic temperatures (≈100 K) and below a specific dose threshold, the structure of h‐MXenes remains largely intact. However, exceeding this threshold leads to electron beam‐induced deformation through ripplocations. Interestingly, the deformation behavior, required dose, and resultant structure are highly dependent on temperature. At 100 K, it is demonstrated that the electron beam can induce ripplocations in situ with a high degree of precision.

Chemistry↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
DOE OSTI2025

Reuniting crystallography with real space: Ab initio structure elucidation with 4D-STEM

Structure elucidation via single-crystal methods has historically lacked experimental access to real-space information, instead relying exclusively on diffraction-space measurements of Bragg reflections. Here we exploit the dual-space imaging power of 4D scanning transmission electron microscopy to meaningfully integrate real-space information into the crystallographic workflow. We show that virtual apertures assembled by segmentation of high-angle annular dark-field images enable i) pixel-by-pixel separation of coherent Bragg signal from clusters of closely spaced nanocrystals and ii) selective extraction of integrated intensities from thinner subregions of individual specimens, facilitating retroactive tuning of multiple scattering artifacts. This strategy empowers us to simply pick and choose whichever nanoscale regions of interest generate the highest-quality diffraction patterns, allowing us to solve several independent structures of the metal-organic framework UiO-66 from specimens whose agglomerated morphology proved intractable for conventional microcrystal electron diffraction. Our method is compatible with both rotational and serial approaches to data processing, ultimately divulging the first scanning nanobeam electron diffraction structures determined by direct methods at subangstrom resolution.

Saha, Ambarneil↗
DOE OSTI2023

Optimization of peptide amphiphile-lipid raft interaction by changing peptide amphiphile lipophilicity

Various peptide amphiphile (PA) molecules have been developed to promote bone regeneration. Previously we discovered that a peptide amphiphile with a palmitic acid tail (C 16 ) attenuates the signaling threshold of leucine-rich amelogenin peptide (LRAP)-mediated Wnt activation by increasing membrane lipid raft mobility. In the current study, we found that treatment of murine ST2 cells with an inhibitor (Nystatin) or Caveolin-1-specific siRNA abolishes the effect of C 16 PA, indicating that Caveolin-mediated endocytosis is required. Here, to determine whether hydrophobicity of the PA tail plays a role in its signaling effect, we modified the length of the tail (C 12 , C 16 and C 22 ) or composition (cholesterol). While shortening the tail (C 12 ) decreased the signaling effect, lengthening the tail (C 22 ) had no prominent effect. On the other hand, the cholesterol PA displayed a similar function as the C 16 PA at the same concentration of 0.001% w/v. Interestingly, a higher concentration of C 16 PA (0.005%) is cytotoxic while cholesterol PA at the higher concentration (0.005%) is well-tolerated by cells. Use of the cholesterol PA at 0.005% enabled a further reduction of the signaling threshold of LRAP to 0.20 nM, compared to 0.25 nM at 0.001%. Caveolin-mediated endocytosis is also required for cholesterol PA, as evidenced by Caveolin-1 siRNA knockdown experiments. We further demonstrated that the noted effects of cholesterol PA are also observed in human bone marrow mesenchymal stem cells (BMMSCs). Taken together, these results indicate that the cholesterol PA modulates lipid raft/caveolar dynamics, thereby increasing receptor sensitivity for activation of canonical Wnt signaling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Pathways for Sustainable Reaction Kinetics in Li-CO2 Batteries

Lithium-carbon dioxide (Li-CO2) batteries hold great promise for high-energy-density storage applications. However, advancing this technology as a sustainable alternative to Li-ion systems requires a deeper understanding of the underlying reaction mechanisms, which remain elusive. A key challenge stems from the added complexity introduced by the presence of oxygen (O2) in CO2 environment. In this study, we employed a stable Cu3(VBi)0.5Se4 mid-entropy catalyst and conducted a comprehensive investigation to uncover the underlying reaction mechanisms in Li-CO2 batteries under varying CO2/O2 ratios. Under pure CO2 conditions, the battery exhibits excellent rechargeability, sustaining up to 1200 cycles. However, at high current densities, the discharge potential drops significantly (below 2.0 V), primarily due to sluggish reaction kinetics caused by solid carbon formation. Interestingly, introducing O2 mitigates this limitation, leading to a 58% increase of the discharge potential (from 1.7 V to 2.7 V) at the high current density of 0.8 mA/cm2, signifying a substantial boost in energy output. Our results reveal that the reactions follow distinct pathways, shifting from surface- to solution-based mechanism, and may even exhibit coexistence of both mechanisms, depending on the CO2/O2 ratio. These findings offer new insights for designing high-performance and sustainable Li-gas batteries utilizing CO2 and O2 mixtures.

Ngo, Anh [University of illinois Chicago]↗
DOE OSTI2024

Atomic-Scale Scanning of Domain Network in the Ferroelectric HfO 2 Thin Film

Ferroelectric HfO 2 -based thin films have attracted much interest in the utilization of ferroelectricity at the nanoscale for next-generation electronic devices. However, the structural origin and stabilization mechanism of the ferroelectric phase are not understood because the film is typically nanocrystalline with active yet stochastic ferroelectric domains. Here, in this study, electron microscopy is used to map the in-plane domain network structures of epitaxially grown ferroelectric Y:HfO 2 films in atomic resolution. The ferroelectricity is confirmed in free-standing Y:HfO 2 films, allowing for investigating the structural origin for their ferroelectricity by 4D-STEM, high-resolution STEM, and iDPC-STEM. At the grain boundaries of <111>-oriented Pca2 1 orthorhombic grains, a high-symmetry mixed-(R3m, Pnm2 1 ) phase is induced, exhibiting enhanced polarization due to in-plane compressive strain. Nanoscale Pca2 1 orthorhombic grains and their grain boundaries with mixed-(R3m, Pnm2 1 ) phases of higher symmetry cooperatively determine the ferroelectricity of the Y:HfO 2 film. It is also found that such ferroelectric domain networks emerge when the film thickness is beyond a finite value. Furthermore, in-plane mapping of oxygen positions overlaid on ferroelectric domains discloses that polarization is suppressed at vertical domain walls, while it is active when domains are aligned horizontally with subangstrom domain walls. In addition, randomly distributed 180° charged domain walls are confined by spacer layers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗