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At least 127 records · Page 7

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DOE OSTI2025

Machinable, high‐conductivity NaSICON through mitigation of humidity effects during solid‐state synthesis

The Na + super ion conductor (NaSICON, Na 1+x Zr 2 Si x P 3-x O 12 ) is a solid electrolyte well-known for fast, selective Na + transport at low temperatures, uniquely enabling sodium-based batteries. Producing high-quality NaSICON from solid-state methods, especially when cost-effective, potentially hygroscopic precursors are used, is not trivial. To understand and eliminate the influence of humidity during processing, a scheme was developed to reproducibly yield a high Na + conductivity (3.75 mS/cm at 25°C, 81.7 mS/cm at 150°C), high density (97%), and machinable NaSICON without the use of binders, sintering aids, or dopants. Controlled humidity studies over 20%–50% RH coupled with thermal, structural, and electrical analysis reveal that calcination temperatures < 1000°C leave NaSICON processing susceptible to water absorption at > 20% RH due to the presence of hygroscopic Na 3 PO 4 and Na 2 CO 3 during shaping, pressing, and sintering. Water absorption results in NaSICON with lower densities, machinability, and Na+ conductivity, due to impaired intergranular Na+ transport. At the other extreme, fully converting precursor to the NaSICON phase at 1230°C before pressing and sintering leads to poor conductivity and density. By calcining at 1000°C, excellent quality NaSICON may be produced under a range of laboratory environments, enabling low-cost production of high-conductivity, machinable NaSICON necessary the ever-growing energy storage market.

NaSICON↗

DOE OSTI2024

Simplified Universal Equations for Ionic Conductivity and Transference Number

Nernst-Einstein equation can provide a reasonable estimate of the ionic conductivity of dilute solutions. For concentrated solutions, alternate methods such as Green–Kubo relations and Einstein relations are more suitable to account for ion-ion interactions. Such computations can be expensive for multicomponent systems. Simplified mathematical expressions like the Nernst-Einstein equation do not exist for concentrated multicomponent mixtures. Newman’s treatment of multicomponent concentrated solutions yields a conductivity relation in terms of species concentration and Onsager phenomenological coefficients. However, the estimation of these phenomenological coefficients is not straightforward. Here, mathematical formulations that relate the phenomenological coefficients with the friction coefficients are developed, leading to simplified, ready-to-use expressions of conductivity and transference numbers that can be used for a wide range of ionic mixtures. This approach involves spectral decomposition of the matrix of Onsager phenomenological coefficients. The general analytical expressions for conductivity and transference number are simplified for binary electrolytes, and numerical solutions are provided for ternary and quaternary mixtures with ion dissociation.

Electrochemistry↗

DOE OSTI2025

Specific conductivity and salinity of the Parker River, PIE LTER, Plum Island Sound MA, August-November 2022

This dataset contains specific conductivity and calculated salinity data of Parker River water at a tidal brackish wetland dominated by Typha angustifolia at the upper estuary of the Plum Island Sound in Newbury, Massachusetts (MA) within the Plum Island Ecosystems Long Term Ecological Research site (PIE LTER). Measurements were taken to evaluate temporal changes in surface water salinity in high frequency to characterize boundary conditions of soil and plant responses to changes in salinity. A PVC pipe was installed in a low elevation spot in the creek bank so that the bottom of the pipe sat on the sediment surface allowing flushing with water during flooding. Raw measurements were collected using an Onset HOBO U24-002 Saltwater Conductivity/Salinity data logger. The specific conductance and salinity measurements were corrected and calculated respectively using Onset’s HOBOware software and reference specific conductivity measurements taken in tandem with the first and last points recorded by the HOBO sensor. These reference measurements were taken using a HACH HQ14D Portable Conductivity Meter. Because of the installation design, only data one hour before and after high tide are used. Metadata files Typha_ctd_salinity_dd.csv and Typha_ctd_salinity_flmd.csv contain detailed information on data variables, sampling and QA/QC methods, and site location.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Upland tidal brackish marsh specific conductivity and salinity measurements, PIE LTER, Plum Island Sound, MA, 2023

This dataset includes raw and corrected specific conductivity, temperature, and calculated salinity measurements collected at 10 cm depth in a Typha angustifolia-dominated tidal brackish wetland at the upper estuary of Plum Island Sound in Newbury, Massachusetts (MA) within the Plum Island Ecosystems Long Term Ecological Research (PIE LTER) site. Measurements were taken to evaluate temporal variation in porewater salinity (a proxy for porewater sulfate concentration) in high frequency to assess soil and plant responses to changes in salinity. Measurements were collected using an Onset HOBO U24-002 Saltwater Conductivity/Salinity data logger deployed in a well. Specific conductivity was corrected using non-linear temperature compensation, and salinity was calculated using the Practical Salinity Scale 1978 via Onset's HOBOware software. Reference conductivity measurements to correct for sensor drift were taken at the start and end of each deployment using a HACH HQ14D Portable Conductivity Meter. Data were then filtered in MATLAB to remove values logged while the sensor was out of the well or during post-deployment equilibration. Detailed metadata, including variable descriptions, sampling methods, QA/QC procedures, and site information, are provided in the files: Typha_ctd_salinity_dd.csv and Typha_MI_ctd_salinity_2023_flmd.csv.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Upland tidal brackish marsh specific conductivity and salinity measurements, PIE LTER, Plum Island Sound, MA, May-December 2022

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Specific conductivity and salinity of the Parker River, PIE LTER, Plum Island Sound MA, March-November 2023

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Low RF loss DC conductive ceramic for RF windows

Charging of RF windows has historically been problematic, frequently resulting in damage to the window severe enough that the window needs to be replaced. Many attempts have been made to prevent charging and therefore improve window lifetime, the most successful and common of which is coating the window with titanium nitride (TiN). Surface coatings such as TiN rely on the secondary electron yield of the coating material being lower than that of the ceramic window material, reducing the number of electrons emitted from a variety of mechanisms. An alternative approach is to introduce a small amount of DC conductivity to the ceramic itself, turning the traditionally insulating window into a mildly conductive one. This allows any charge on the surface of the window to drain rather than build until a discharge happens. A magnesium titanate ceramic has been developed with a small DC conductivity and used to make RF windows. Several window assemblies have been produced and tested, including 1.3 GHz waveguide and 650 MHz coaxial designs. The results of the conductive ceramic window test program will be presented.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY24

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline collaboration to provide engineers with experience in both numerical simulations and experimental methods. This work uses and provides feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development. TRUST currently includes five testbeds and their associated engineering analysis baseline models (EABMs): 1. contact thermal conductivity, (CTC) 2. nonlinear dynamics, (ND) 3. sensors in environments for accelerometers, (SEA) 4. sensors in environments for fiber optic displacement gages, and (SEFOD) 5. sensors in environments for thermocouples (SETC). The TRUST project uses single-feature testbeds to quantify uncertainties in specific models and experiments and to identify capability development needs that can help to reduce these uncertainties. Each testbed is designed, configured, and tested in collaboration with groups with design and experimental capability: E-14 and MPA-CINT. The complementary simulations are conducted using W-13 analysis tools and stored in model repositories with plans for incremental progress toward EABM requirements. W-13 extends and exercises the testbed simulations in collaboration with experimentalists for uncertainty quantification of current and future materials, geometries, and environments. Additionally, TRUST is intended to provide engineers in W-13 and E-14 with experience in both numerical simulations and experimental methods through cross-discipline collaborations. Following the introduction to the TRUST project, the remainder of this report focuses on experimental and analytical efforts conducted in Fiscal Year (FY) 2024 relevant to the TRUST Contact Thermal Conductance (CTC) testbed.

42 ENGINEERING↗

DOE OSTI2025

Uncovering Structure–Conductivity Relationships in Anion Exchange Membranes (AEMs) Using Interpretable Machine Learning

Anion exchange membranes (AEMs) play a vital role in the performance of water electrolyzers and fuel cells, yet their discovery and optimization remain challenging due to the complexity of structure–property relationships. In this study, we introduce a machine learning framework that leverages conditional graph neural networks (cGNNs) and descriptor-based models and a hybrid graph neural network (HGARE) to predict and interpret ionic conductivity. The descriptor-based pipeline employs principal component analysis (PCA), ablation, and SHAP analysis to identify factors governing anion conductivity, revealing electronic, topological, and compositional descriptors as key contributors. Beyond prediction, dimensionality reduction and clustering are performed by employing t-SNE and KMeans as well as SOM, which reveal distinct membranes clusters, some of which were enriched with high anion conductivity. Among graph-based approaches, the graph convolutional (GCN) achieved strong predictive performance, while the Hybrid Graph Autoencoder-Regressor Ensemble (HGARE) achieved the highest accuracy. Additionally, atom-level saliency maps from GCN provide spatial explanations for conductive behavior, revealing the importance of polarizable and flexible regions. This work contributes to the accelerated and data-driven design of high-performance AEMs.

Naghshnejad, Pegah [Department of Chemical Enginee↗

DOE OSTI2024

Waveguide including a conductive channel embedded in a substrate and with vias connected to an antenna and a circuit component

Waveguides and methods for manufacturing a waveguide that include forming a first channel in a first layer of dielectric material, the first channel comprising one or more walls; forming a second channel in a second layer of dielectric material, the second channel comprising one or more walls; depositing electrically conductive material on the one or more walls of the first channel; depositing electrically conductive material on the one or more walls of the second channel; arranging the first layer adjacent to the second layer to form a stack with the first channel axially aligned with and facing the second channel; and heating the stack so that the conductive material on the one or more walls of the first channel and the conductive material on the one or more walls of the second channel connect to form the waveguide.

Krueger, Daniel Scott↗

DOE OSTI2025

Overcoming the Conductance versus Crossover Trade-off in State-of-the-Art Proton Exchange Fuel-Cell Membranes by Incorporating Atomically Thin Chemical Vapor Deposition Graphene

Permeance–selectivity trade-offs are inherent to polymeric membranes. In fuel cells, thinner proton exchange membranes (PEMs) could enable higher proton conductance and increased power density with lower area-specific resistance (ASR), smaller ohmic losses, and lower ionomer cost. However, reducing thickness is accompanied by an increase in undesired species crossover harming performance and long-term efficiency. Here, we show that incorporating atomically thin monolayer graphene synthesized via scalable chemical vapor deposition (CVD) and tunable defect density into PEMs (Nafion, ~5–25 μm thick) can allow for reduced H 2 crossover (~34–78% of Nafion of a similar thickness) while maintaining adequate areal proton conductance for applications (>4 S cm –2 ). In contrast to most prior work using >50 μm symmetric Nafion sandwich structures, we elucidate the interplay of graphene defect density and Nafion proton transport resistance on the performance of Nafion|graphene composite membranes and find high-quality low-defect density CVD graphene (G) supported on Nafion 211 (~25 μm); i.e., N211|G has a high areal proton conductance (~6.1 S cm –2 ) and the lowest H 2 crossover (~0.7 mA cm –2 ). Fully functional centimeter-scale N211|G fuel-cell membranes demonstrate performance comparable to that of state-of-the-art Nafion N211 at room temperature as well as standard operating conditions (~80 °C, ~150–250 kPa-abs) with H 2 /air (power density ~0.57–0.63 W cm –2 ) and H 2 /O 2 feed (power density ~1.4–1.62 W cm –2 ) and markedly reduced H 2 crossover (~53–57%).

25 ENERGY STORAGE↗

DOE OSTI2025

Database of Nonaqueous Proton-Conducting Materials

This work presents the assembly of 48 papers, representing 74 different compounds and blends, into a machine-readable database of nonaqueous proton-conducting materials. SMILES was used to encode the chemical structures of the molecules, and we tabulated the reported proton conductivity, proton diffusion coefficient, and material composition for a total of 3152 data points. The data spans a broad range of temperatures ranging from -70 to 260 °C. To explore this landscape of nonaqueous proton conductors, DFT was used to calculate the proton affinity of 18 unique proton carriers. The results were then compared to the activation energy derived from fitting experimental data to the Arrhenius equation. It was found that while the widely recognized positive correlation between the activation energy and proton affinity may hold among closely related molecules, this correlation does not necessarily apply across a broader range of molecules. This work serves as an example of the potential analyses that can be conducted using literature data combined with emerging research tools in computation and data science to address specific materials design problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Mapping Thermal Conductivity at the Atomic Scale: A Step toward the Thermal Design of Materials

We describe a spatial decomposition of the thermal conductivity, termed site-projected thermal conductivity, which quantifies the thermal conduction activity at each atomic site—a critical parameter for the thermal design of materials. The method is based on the Green–Kubo formula and the harmonic approximation and requires the force-constant and dynamical matrices, as well as a relaxed structural model. Throughout the study, it uses high quality models previously tested and compared to many experiments. It discusses the method and underlying approximations for amorphous silicon, carries the detailed analysis for amorphous silicon, and then examines an amorphous-crystal silicon interface and representative carbon materials. This study identifies the sites and local structures that reduce heat transport, and quantify these (estimate the spatial range) over which these “thermal defects” are effective. It identifies filamentary structures in the amorphous silicon network which impact heat transport and electronic structure (the Urbach edge) and electronic transport.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Hydraulic constraints to stomatal conductance in flooded trees

Stomatal closure is a pervasive response among trees exposed to flooded soil. We tested whether this response is caused by reduced hydraulic conductance in the soil-to-leaf hydraulic continuum (k total ), and particularly by reduced root hydraulic conductance (k root ), which has been widely hypothesized. We tracked stomatal conductance at the leaf level (g s ) and canopy scale (G s ) along with physiological conditions in two temperate tree species, Magnolia grandiflora and Quercus virginiana, that were subjected to flood and control conditions in a greenhouse experiment. Flooding reduced g s , G s , k root and k total . Path analysis showed strong support for direct effects of k total on g s and for flood duration on k total , but not k root on k total . A process-based model that accounted for the k total reduction predicted the timeseries of G s in flood and control treatment trees reasonably well (predicted versus observed G s R 2 = 0.80 and 0.51 for M. grandiflora and Q. virginiana, respectively). However, accounting only for k root reduction in flooded trees was insufficient for predicting observed G s reduction. Together, these results suggest that hydraulic constraints were not limited to roots and highlight the need to account for flooding effects on k total when projecting forest ecosystem function using process-based models.

Plant stress↗

DOE OSTI2025

Additively-manufactured Al-0.3Zr-0.2Ce-0.2Cu alloy with high creep resistance and electrical conductivity

Here, a new, solute-lean Al-0.3Zr-0.2Ce-0.2Cu (wt.%) alloy is developed for additive manufacturing that overcomes the classical tradeoff between conductivity and creep resistance. The rapid-cooling-enabled supersaturation of Zr, and its uniform distribution in α-Al matrix, along with formation of submicron (Ce,Cu)-rich intermetallic particles on solidification lead to unusually high creep resistance at 200 °C. Near-zero secondary creep rates are achieved up to the alloy yield stress (YS) of 65 MPa at 200 °C in as-fabricated state. The Zr-solute-induced dislocation-climb suppression mechanism underlying this improvement also restricts dynamic recovery above YS, as noted from appreciable primary creep and its transitioning to near-zero secondary creep rates. A combination of relatively coarse, epitaxially-grown α-Al grains, low Zr concentration in α-Al, and the impurity-scavenging effect of Ce to purify α-Al matrix produces high electrical conductivity of ∼48 %IACS. Aging precipitation of L1 2 -Al 3 Zr nanoprecipitates doubles the YS (to ∼150 MPa) at room temperature and increases alloy conductivity to ∼58 %IACS, but loss of solid-solution Zr out of α-Al matrix leads to activation of dislocation climb, degrading the creep properties as compared to the supersaturated Al-Zr solid solution in the as-fabricated state. Compared to L1 2 -Al 3 Zr nanoprecipitates, submicron (Ce,Cu)-rich particles formed on solidification are more effective at impeding dislocation climb, producing a threshold stress for dislocation creep of ∼ 50 MPa at 200 °C. The new alloy design concepts, especially solute-induced dislocation-climb suppression for creep resistance, explored here may pave way for the design of new metallic alloys for thermal/electrical conductors and other high-temperature applications.

Additive Manufacturing↗

DOE OSTI2025

Development of a conduction-based model for analyzing frozen startup of alkali-metal heat pipes

One key area of interest in heat pipe modeling/simulation is to analyze the startup behavior of the liquid-metal heat pipes (LMHPs) from a frozen state. This so-called ‘frozen startup’ process involves a complex set of nonlinear mass and heat transport phenomena, including phase transitions from solid to liquid and vapor, multiphase interactions, microporous wick flow, and compressible vapor dynamics. The complexity of these processes makes it challenging to simulate LMHP’s frozen startup using conventional numerical methods or commercial computational fluid dynamics (CFD) software. This paper presents a simplified conduction-based modeling approach that can provide practical insights into the entire LMHP frozen startup process, while alleviating the challenges of modeling its complex physics. The theoretical foundation and physical assumptions of the proposed model are based solely on heat-conduction equation, allowing for a more tractable simulation without sacrificing essential physical accuracy. The proposed model was implemented in a commercial CFD software, and its prediction was compared with the experimental data obtained from sodium heat-pipe startup experiments. The comparison highlights the proposed model's ability to capture the transient thermal behavior of LMHP during frozen startup. This study not only validates the conduction-based frozen startup modeling method but also shows its potential as a practical and efficient tool for understanding the startup performance of the LMHP systems.

Microreactor↗

DOE OSTI2025

Mapping of fracture and ionic conductivity changes in ion implanted solid electrolytes: Insights from molecular dynamics

Ion implantation emerges as a promising technique to address the persistent challenge of lithium (Li) filament growth in solid-state electrolytes as it can induce compressive stresses inhibiting crack growth and deflect dendrites, de facto mitigating early electrolyte failure. In this study, we examine the potential paradox of ion implantation: while aiming to enhance electrolyte performance, the radiation damage associated with implantation might inadvertently compromise both the ionic conductivity and the intrinsic fracture toughness of the material, rendering the material unsuitable for battery applications. Specifically, we employed molecular dynamics simulations to examine the scope of the downsides of ion implantation, specifically: (i) reduced ionic conductivity (due to radiation-induced amorphization) and (ii) mechanical stability (due to radiation-induced embrittlement) in ion-implanted Li 7 La 3 Zr 2 O 12 (LLZO) solid-state electrolytes. We explore how radiation damage impacts LLZO’s crystalline structure, Li-ion diffusion, and fracture properties at various temperatures and radiation damage levels. The study aims to provide insights into the competing effects of ion implantation and suggest potential engineering strategies for developing more robust solid-state electrolytes with improved conductivity and dendrite resistance.

Conductivity↗

DOE OSTI2024

Design of a first-of-A-kind instrumented advanced test reactor irradiation Capsule experiment for In situ thermal conductivity measurements of metallic fuel

Metallic fuel undergoes dramatic microstructural changes early in life due to fission gas swelling until ~2–3 at% burnup which affects the conductivity of the material, however the evolution of metallic fuel thermal conductivity during this early phase burnup has never been successfully measured in situ. The Irradiated Material Properties Accelerated Characterization Test (IMPACT) experiment will be the first in a series of experiments to irradiate advanced nuclear metallic fuel specimens with novel embedded thermal conductivity probes in ATR. In the current work the IMPACT experiment final design and supporting analysis is reported in detail. Results are evaluated for various reactor operational conditions to meet the functional requirements of the experiment. Finally, the first iteration of this IMPACT experiment will provide data regarding thermal properties evolution in uranium-zirconium (U10Zr) fuel, but this experiment vehicle is envisioned for future advanced fuels and structural materials irradiations in ATR.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗