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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A first and second law analysis of a thermoresponsive polymer desiccant dehumidification and cooling cycle

Herein, we present a theoretical description for a new desiccant air conditioning cycle that uses thermoresponsive polymers instead of traditional desiccants. We use a combined first and second law analysis to demonstrate that this new cycle has three major advantages relative to the traditional case: (i) it can regenerate at lower temperatures, (ii) it can harvest liquid water and (iii) it has significantly higher coefficients of performance (COPs). For example, this new cycle can achieve a COP of 5.1 when regenerated at 95 degrees C, whereas the traditional desiccant cycle is limited to a COP of ~ 1. The fundamental origins of these advantages can be traced to the method of regeneration. The traditional desiccant cycle regenerates by flowing hot air over the desiccant, which provides a medium for gaseous water desorption. However, this also generates entropy and places a minimum temperature constraint on the hot air. In contrast, the thermoresponsive polymer cycle regenerates through a polymer phase transition. The polymer absorbs water vapor in humid air, and then it expels liquid water when raised above its transition temperature. This regeneration method generates liquid water that can be harvested and relaxes constraints on entropy generation and minimum temperature. The minimum regeneration temperature of the thermoresponsive cycle is only limited by the transition temperature of the polymer, which can be tuned through materials science. Due to its liquid water harvesting capability, the new cycle potentially eliminates water consumption when used with evaporative cooling, or it can be directly used for atmospheric water harvesting.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Pilot Testing of a Highly Efficient Pre-combustion Sorbent-based Carbon Capture System

TDA developed and demonstrated a highly efficient pre-combustion carbon capture system. The overall objective of this work was to develop a new sorbent-based pre-combustion carbon capture technology for Integrated Gasification Combined Cycle (IGCC) power plants. In this project our goal was to demonstrate the techno-economic viability of the new technology by 1) demonstrating it in large-scale slipstream tests, and 2) carrying out a high fidelity engineering and cost analysis. TDA’s process used an advanced physical adsorbent that selectively removes CO 2 from coal-derived synthesis gas above the dew point of the gas at temperatures as high as 300°C. The sorbent consists of a mesoporous carbon whose surface was grafted with functional groups that remove CO 2 via a well-known acid-base interaction. As documented in bench-scale experiments and field tests with actual coal gas, the sorbent achieved a very high capacity for CO 2 at temperatures as high as 300°C. The sorbent bound CO 2 more strongly than common physical adsorbents, providing the chemical potential needed for the high temperature operation. However, because CO 2 does not form a true covalent bond with the surface sites (as is the case with chemical absorbents), the sorbent regeneration could be carried out with only a very small energy input. The heat input to regenerate our sorbent was only 4.9 kcal per mol of CO 2 , which is much lower than that for chemical absorbents (e.g., 29.9 kcal/mol CO 2 for sodium carbonate) and was similar to the requirements of physical solvents (e.g., 4 kcal/mol CO 2 for Selexol TM ). Because the sorbent operates above the dew point of the synthesis gas (unlike the Selexol TM process), a higher power cycle efficiency can be achieved. With previous DOE/NETL funding (Contract No. DE-FE-0000469), we demonstrated the techno-economic viability of the technology in bench-scale tests and slipstream demonstrations at the National Carbon Capture Center (NCCC), Wilsonville, Alabama and Wabash River IGCC plant in Terra Haute, Indiana. We demonstrated a stable working CO 2 capacity for over 11,650 cycles with simulated synthesis gas. We also evaluated its performance with actual synthesis gas in two test campaigns at the Wabash River IGCC Plant, Terre Haute, IN and the National Carbon Capture Center (NCCC), Wilsonville, AL. The slipstream tests clearly showed that the actual coal gas constituents and potential contaminants (e.g. trace metals, halides, tars) had no effect on the sorbent’s ability to remove CO 2 (the same sorbent beds were used in both field tests with no sign of deactivation for 2,000 cycles with over 26,750 SCF of gas treated). As expected, due to the high temperature CO 2 removal capability and low energy needed to regenerate the sorbent, the power cycle efficiency with our process was greater than 34% on a higher heating value (HHV) basis; in comparison, the same IGCC plant equipped with the Selexol TM solvent for carbon capture can only achieve 31.4% HHV efficiency. The capital cost for an IGCC system with TDA’s process is estimated as $2,417/kW e , which is 12% lower than that of the IGCC/ Selexol TM process. The levelized cost for electricity including the transport, storage and monitoring (TS&M) cost for CO 2 was calculated as $\$ $92.9/MWh (lowest reported to our knowledge), which is much better than the $105.2/MWh estimated for the IGCC/ Selexol TM process. In this project (DE-FE0013105), TDA Research, in collaboration with our partners Gas Technology Institute (GTI), Illinois Clean Coal Institute (ICCI), University of California, Irvine (UCI), University of Alberta (UOA), Siemens, NCCC and Sinopec advanced the technical maturity of the technology; scaling it up by a factor of 100. We optimized the reactor design using computational fluid dynamics (CFD); using adsorption modeling we improved the pressure swing adsorption (PSA) cycle sequence. We carried out two field test campaigns with a fully-equipped 0.1 MW e prototype unit (for a total of 844 hours) using actual synthesis gas to prove the viability of the new technology. A successful 30 day (707 hrs) evaluation was completed at NCCC under air blown gasification conditions. We demonstrated 97.3% carbon capture at 1,500 SLPM, 93% carbon capture at 1,800 SLPM, and 90% carbon capture at 2,100 SLPM in the NCCC tests. We also demonstrated the system for 137 hours at a Sinopec petrochemical plant under oxygen blown gasification, demonstrating 86% carbon capture at 2,660 SLPM. In collaboration with University of California, Irvine (UCI), we completed a techno-economic analysis (TEA) for TDA’s warm gas cleanup technology integrated to IGCC power plant. The net plant efficiencies (on a coal HHV basis) for the warm gas cleanup cases were estimated to be 34.0% for E-GasTM gasifier, 34.4% for GE gasifier, 33.4 for the Shell gasifier and 34.2 for the TRIG TM gasifier (Cases 2, 4, 6 and 8 in this study) with a catalytic combustor for CO 2 purification, which are significantly higher than those for the Cold Gas Case, or an increase of as much as 12% in the heat rate for Case 2, 6% for Case 4, 9% for Case 6, and 9% for Case 8. The 1st year cost of electricity with the transport, storage and monitoring (TS&M) costs for the CO 2 included was $\$ $129.2/MWh for the E-GasTM gasifier Warm Gas Cleanup Case, $\$ $131.9/MWh for the GE gasifier Warm Gas Cleanup Case, $\$ $146.8/MWh for the Shell Gasifier Warm Gas Cleanup Case, and $\$ $129.9/MWh for the TRIG TM gasifier Warm Gas Cleanup Case. For comparison, the costs for the baseline Cold Gas CO 2 removal with Selexol for the different gasifiers were: $\$ $146.6/MWh for the E-Gas TM gasifier, $\$ $142.2/MWh for the GE gasifier, $\$ $159.0/MWh for the Shell gasifier and $\$ $144.3/MWh for the TRIG TM gasifier. In summary, the costs for our system were 7 to 12% lower than the corresponding Cold Gas Cleanup cases. The results of this techno-economic analysis suggested that TDA’s high temperature PSA-based Warm Gas Clean-up Technology can make a substantial improvement in the IGCC plant thermal performance for achieving near zero CO 2 emissions for E-Gas TM , GE, Shell and TRIG TM gasifier based IGCC power plants. The capital expenses were estimated to be lower than that of Selexol’s™. Taken together, the higher net plant efficiency and lower capital and operating costs resulted in substantial reduction in the cost of carbon capture for the IGCC plant equipped with TDA’s high temperature PSA-based carbon capture system. Finally, in collaboration with Gas Technology Institute (GTI) we completed the environmental health and safety assessment for TDA’s warm gas carbon capture technology.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Multigrid deflation for Lattice QCD

Computing the trace of the inverse of large matrices is typically addressed through statistical methods. Deflating out the lowest eigenvectors or singular vectors of the matrix reduces the variance of the trace estimator. This work summarizes our efforts to reduce the computational cost of computing the deflation space while achieving the desired variance reduction for Lattice QCD applications. Previous efforts computed the lower part of the singular spectrum of the Dirac operator by using an eigensolver preconditioned with a multigrid linear system solver. Despite the improvement in performance in those applications, as the problem size grows the runtime and storage demands of this approach will eventually dominate the stochastic estimation part of the computation. In this work, we propose to compute the deflation space in one of the following two ways. First, by using an inexact eigensolver on the Hermitian, but maximally indefinite, operator. Second, by exploiting the fact that the multigrid prolongator for this operator is rich in components toward the lower part of the singular spectrum. We show experimentally that the inexact eigensolver can approximate the lower part of the spectrum even for ill-conditioned operators. Also, the deflation based on the multigrid prolongator is more efficient to compute and apply, and, despite its limited ability to approximate the fine level spectrum, it obtains similar variance reduction on the trace estimator as deflating with approximate eigenvectors from the fine level operator.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

When band convergence is not beneficial for thermoelectrics

Abstract Band convergence is considered a clear benefit to thermoelectric performance because it increases the charge carrier concentration for a given Fermi level, which typically enhances charge conductivity while preserving the Seebeck coefficient. However, this advantage hinges on the assumption that interband scattering of carriers is weak or insignificant. With first-principles treatment of electron-phonon scattering in the CaMg 2 Sb 2 -CaZn 2 Sb 2 Zintl system and full Heusler Sr 2 SbAu, we demonstrate that the benefit of band convergence can be intrinsically negated by interband scattering depending on the manner in which bands converge. In the Zintl alloy, band convergence does not improve weighted mobility or the density-of-states effective mass. We trace the underlying reason to the fact that the bands converge at a one k-point, which induces strong interband scattering of both the deformation-potential and the polar-optical kinds. The case contrasts with band convergence at distant k-points (as in the full Heusler), which better preserves the single-band scattering behavior thereby successfully leading to improved performance. Therefore, we suggest that band convergence as thermoelectric design principle is best suited to cases in which it occurs at distant k-points.

42 ENGINEERING↗
DOE OSTI2024

Machine Learning Discrimination and Ultrasensitive Detection of Fentanyl Using Gold Nanoparticle-Decorated Carbon Nanotube-Based Field-Effect Transistor Sensors

The opioid overdose crisis is a global health challenge. Fentanyl, an exceedingly potent synthetic opioid, has emerged as a leading contributor to the surge in opioid-related overdose deaths. The surge in overdose fatalities, particularly due to illicitly manufactured fentanyl and its contamination of street drugs, emphasizes the urgency for drug-testing technologies that can quickly and accurately identify fentanyl from other drugs and quantify trace amounts of fentanyl. In this paper, gold nanoparticle (AuNP)-decorated single-walled carbon nanotube (SWCNT)-based field-effect transistors (FETs) are utilized for machine learning-assisted identification of fentanyl from codeine, hydrocodone, and morphine. The unique sensing performance of fentanyl led to use machine learning approaches for accurate identification of fentanyl. Employing linear discriminant analysis (LDA) with a leave-one-out cross-validation approach, a validation accuracy of 91.2% is achieved. Meanwhile, density functional theory (DFT) calculations reveal the factors that contributed to the enhanced sensitivity of the Au-SWCNT FET sensor toward fentanyl as well as the underlying sensing mechanism. Finally, fentanyl antibodies are introduced to the Au-SWCNT FET sensor as specific receptors, expanding the linear range of the sensor in the lower concentration range, and enabling ultrasensitive detection of fentanyl with a limit of detection at 10.8 fg mL –1 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Model predictive control of mixing controlled compression ignition operation for low reactivity fuels

Using gasoline or other low reactivity fuels with a pilot injection or port fuel injection in a compression ignition engine has shown great potential in reducing NOx emissions while keeping high thermal efficiency compared to diesel. However, excessive combustion noise is caused by a high maximum pressure rise rate in the cylinder due to the higher fractions of premixed charge of the low-reactivity fuel. This noise can result in structural damage to engine components and as such, combustion noise limits the range of the operating parameters and makes the control of such engines challenging. In this study, a simulation environment was built up in MATLAB/Simulink leveraging a physics-based zero-dimension combustion model to capture the in-cylinder pressure time traces as well as metrics relevant to thermal efficiency and combustion noise. Here, in order to also facilitate the control of emissions, machine learning models were investigated to capture NOx emissions. A kernel-based extreme learning machine (K-ELM) performed best and had a coefficient of correlation (R-squared) of 0.998. The combustion and NOx emission models are valid for not only conventional gasoline fuel but also oxygenated alternative fuel blends at three different pilot injection strategies. In order to track key combustion metrics while keeping noise and emissions within constraints, a model predictive control (MPC) was applied for a compression ignition engine operating with a range of potential fuels and fuel injection strategies. The MPC is validated under different scenarios, including a load step change, fuel type change, and injection strategy change, with proportional–integral (PI) control as the baseline. The simulation results show that MPC reduces about 26% of ringing intensity in the transient process and 17% at the steady state for E30. Generally, MPC can optimize the overall performance through modifying the main injection timing, pilot fuel mass, and exhaust gas recirculation (EGR) fraction.

42 ENGINEERING↗
DOE OSTI2020

Synergistic Effects of Inexpensive Mixed Metal Oxides for Catalytic Hydrothermal Liquefaction of Food Wastes

Industrial wastes and natural mixed oxide materials were evaluated as inexpensive heterogeneous catalysts for catalytic hydrothermal liquefaction (CHTL) of food wastes. Red mud and red clay achieved biocrude carbon yields of 47.0 and 39.5% with higher heating values (HHVs) of 40.2 and 37.7 MJ kg –1 , respectively, which were much greater than those without the catalyst (biocrude carbon yield of 19.7% and HHV of 36.1 MJ kg –1 ). Biocrude characterization revealed that similar families of molecules were formed in the presence and absence of catalysts, implying that the main role of the catalyst is to promote rates of thermal reactions, leading to biocrude production without opening new pathways. The crystalline structures of inexpensive mixed oxides were stable under hydrothermal conditions, with modest calcium leaching (7.5%) and trace leaching of other metals. Using red clay or red mud resulted in >40% recovery of the energy in food waste as biocrude, greater than that obtained under noncatalytic conditions (18%) or from any individual constituent oxide (19–27%). The improved CHTL performance of the mixed metal oxides compared with single-metal oxides was attributed to the synergistic effects of base and acid sites present on catalyst surfaces; mixed oxides presented balanced densities of acids and bases, whereas the constituent oxides were either primarily acidic or primarily basic. Lastly, the percent of energy recovered as biocrude oil was strongly correlated with the base-to-acid site density ratio, providing an important performance predictor for CHTL conversion of food waste to bioenergy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

AI for Extreme Volcanic Climate Forcing and Feedback Forecasting in the 21st century

Our paradigm-shifting framework will apply machine learning and perform physical analysis of contemporary volcanoes to develop sound forecasts of extreme eruptions in the 21stcentury and their abrupt drying and cooling impacts on the warming climate. We will also bridge climate data driven regression models and earth system model output to trace teleconnections that exacerbate regional impacts such as Arctic amplification and western US droughts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

High-Burnup LOCA Burst Susceptibility BISON Analysis in PWRs and BWRs

Accurately assessing high-burnup fuel behavior during loss-of-coolant accidents (LOCAs) is essential for understanding fuel fragmentation, relocation, and dispersal (FFRD) risks across the US light-water reactor fleet. This work updates previous Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program multiphysics LOCA analyses for a pressurized water reactor (PWR) and a boiling water reactor (BWR) by incorporating recent model and material property advancements in the BISON fuel performance code, including a high-burnup structure (HBS) model, revised cladding burst criteria, and updated thermal–mechanical correlations. This update was needed to support ongoing industry initiatives and upcoming regulatory changes. Full-core, rod-resolved operating histories generated using Virtual Environment for Reactor Analysis (VERA) and system-level LOCA conditions obtained from TRACE were applied to statistically representative rod samples in BISON to evaluate burst behavior and FFRD susceptibility. These calculations used two cladding burst correlations and three fuel pulverization models so that the predictions of these models could be compared. The updated PWR simulations show markedly improved numerical stability as the number of crashed simulations decreased by 95% compared to the previous study, and hence higher confidence in results. The updated PWR simulations predicted cladding bursts exclusively among once-burned, high-power rods, with two different cladding burst models identifying the same burst-susceptible population. Resulting FFRD susceptibility estimates are significantly reduced compared with earlier studies, driven by cooler predicted fuel and plenum temperatures, lower hoop strains, and reduced fission gas release in the updated models. In contrast, none of the BWR rods were predicted to burst under either burst criterion, reaffirming minimal BWR FFRD susceptibility even with updated HBS and material models. Comparisons between the PWR and BWR end-of-cycle predictions are made. Comparison with prior work highlights significant shifts in PWR fuel performance metrics and confirmation of earlier BWR conclusions. Overall, the updated results underscore the importance of having high-resolution detailed modeling capability and continuously integrating evolving material models and physics into high-resolution multiphysics simulations. The unified assessment presented here strengthens confidence in predicting high-burnup LOCA behavior by improving agreement between different cladding burst correlations. These results also provide an improved foundation for future BISON model development, FFRD susceptibility calculations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Short-Term Inhibition and Long-Term Enhancement of Irreversible Trace Metal Binding to Goethite in Multi-Metal Systems

Iron (oxyhydr)oxide minerals are important sorbents of trace metals in aquatic environments. Adsorption–desorption hysteresis has been documented for trace metals after aging, suggesting that they become incorporated over time. We previously found that ion size controls the extent of irreversible metal binding of single metals to goethite. In this study, we evaluate how the presence of multiple metals influences irreversible binding. Mixed Ni–Zn and Ni–Cd solutions were aged with goethite at pH 7 for 2 days, 30 days, and 60 days, after which isotope exchange experiments were performed to assess the lability of the adsorbed metal pools. After 2 days of aging, Ni and Cd in mixed-metal systems were more labile than in single-metal systems, indicating that competitive adsorption may partially block irreversible binding on short time scales. After 60 days, all three metals had larger irreversibly bound fractions than in single-metal systems. X-ray absorption near-edge structure (XANES) spectroscopy indicates that irreversibly bound fractions correlate with incorporation into goethite. This study demonstrates that pools of coadsorbed metals are bioaccessible on a time scale of minutes. Cooperative effects promote the structural sequestration of even large trace metals, causing reactive transport models to likely overpredict metal mobility. Long-term metal entrapment processes hinder micronutrient availability, impact contaminant sequestration and critical mineral recovery, and yield complex pathways through which metal solubilization may be enhanced or hindered during redox cycling.

58 GEOSCIENCES↗
DOE OSTI2026

Improving the Performance of NEML2 with Modern Graph Compilation Backends

NEML2 vectorizes constitutive-model evaluation for large-scale multiphysics simulation, using PyTorch as its tensor backend so that a batch of material-point updates runs on CPU or GPU through a single implementation. In the two prior reports in this series it was a C++-native library, deployed through TorchScript tracing and just-in-time (JIT) compilation; it has since been rewritten from the ground up into a Python-native library deployed through Ahead-of-Time Inductor (AOTInductor), a modern PyTorch graph-compilation backend. The rewrite is driven by a persistent tension, not a language preference: NEML2 composes constitutive models at runtime from a registry of small, independently-authored pieces, and that flexibility is difficult to reconcile with the compile-time knowledge an efficient GPU kernel needs. This report documents the rewrite and the investment that accompanied it: the AOTInductor export pipeline that turns a Python-authored model into a portable, Python-free compiled artifact loadable from pure C++; the eager and compiled runtimes and the new implicit solver layer built on them; a head-to-head benchmark of legacy JIT against AOTInductor; the physics-model catalog and its worked examples; the developer tooling; and the corresponding overhaul of MOOSE’s NEML2 integration that lets MOOSE consume it. A central objective is to examine whether modern PyTorch graph-compilation backends are effective for MOOSE GPU integration. The benchmark answers directly: AOTInductor outperforms legacy JIT on every GPU scenario measured, by 1.0–4.5×. Modern graph-compilation backends are effective for MOOSE GPU integration, and AOTInductor specifically – not compilation in the abstract – is why.

Hu, Gary (Tianchen) [Argonne National Laboratory (↗
DOE OSTI2024

Source size of x rays from self-modulated laser wakefield accelerators

A comparative study of x-ray sources generated with different mechanisms from self-modulated laser wakefield acceleration (SM-LWFA) electrons was performed to compare the source size or spatial resolution for use in high energy density science applications. We examine the source size of betatron, inverse Compton scattering, and bremsstrahlung radiation with a Fresnel diffraction based formalism and a modified x-ray ray tracing model. We observe the dependence of source size on the radiation generation process, laser parameters, and compare to what is possible in other regimes of LWFA, as well as current methods. This information is significant as we begin to explore the use of light sources driven by SM-LWFA for use as a diagnostic at large-scale laser facilities where blowout regime LWFA is not possible.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

AI for Extreme Volcanic Climate Forcing and Feedback Forecasting in the 21st century

Focal Areas: Our paradigm-shifting framework will apply machine learning and perform physical analysis of contemporary volcanoes to develop sound forecasts of extreme eruptions in the 21st century and their abrupt drying and cooling impacts on the warming climate. We will also bridge climate data driven regression models and earth system model output to trace teleconnections that exacerbate regional impacts such as Arctic amplification and western US droughts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Leveraging Environmental Monitoring Results from Department of Energy Sites for Research on the Food-Energy-Water Nexus

The Annual Site Environmental Report (ASER) from a U.S. Department of Energy (DOE) Site summarizes environmental data; environmental management performance; compliance with applicable DOE, federal, state, and local regulations; and restoration and surveillance monitoring programs. The Savannah River Site (SRS) produces ASERs that include results of monitoring mercury levels in fish samples obtained in the vicinity of SRS. Mercury is a toxic trace metal and the methylated organic form is a neurotoxin that bioaccumulates in the food web, endangering humans and other organisms. In United States, power plants are the largest source of mercury emissions. Research Objective: To determine the patterns of mercury levels in fish samples reported in the SRS environmental monitoring reports. We developed box plot visualizations to make sense of the data as well as identify fish species, dates and location with outlier mercury content. The integration and visual representation of multi-year datasets can support decision making processes on environmental compliance and environmental sustainability conducted at U.S. DOE Sites. We are constructing datasets from textual, image and multivariable data sources in the multi-year ASERs of the U.S. DOE Savannah River Site (SRS https://www.srs.gov/general/pubs/ERsum/index.html). The Fish Surveillance for mercury presents a case study for the intersection of food, energy and water systems. The dataset of 864 records (2008 and 2009) of mercury levels includes water location of fish, fish species, collection date and mercury content of fish sample. The patterns of mercury levels in the fish species as well as locations provide knowledge for further investigations. A research area for future studies is the composition of microbial communities in fish guts of varying levels of mercury.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Interface stability of LiCl-rich argyrodite Li 6 PS 5 Cl with propylene carbonate boosts high-performance lithium batteries

In solid-state lithium (Li)-metal batteries (SSLMBs), sulfide-based Li-ion conductors represent one of the most popular solid electrolytes (SEs). However, the development of sulfide-based SSLMBs is significantly hampered by interfacial issues including large solid-solid contact resistance and serious side reactions at the SE/electrode interface. To address these issues, here, we demonstrated a simple and efficient strategy by using LiCl-rich argyrodite Li 6 PS 5 Cl (Li 6 PS 5 Cl-LiCl) SE and trace amount of propylene carbonate (PC) at the SE/electrode interface to facilitate the formation of stable and robust solid electrolyte interphase (SEI). Additionally, the formed SEI not only serves as a buffer layer to passivate the interfacial reactions and suppress Li dendrite growth, but also acts as a bridge for Li-ion conduction to reduce the contact resistance. As a result, the Li||Li symmetric cell exhibited long-term electrochemical cycling stability over 1000 h at a current density of 0.2 mA cm -2 . Furthermore, the assembled Li||Li 4 Ti 5 O 12 (LTO) batteries delivered a specific capacity of 175 mAh g–1 at 0.2 C, and remained an excellent specific capacity of 116 mAh g –1 after 200 cycles at a high current rate of 1 C. These features indicate a feasible strategy to enhance the interfacial property of high-performance SSLMBs.

25 ENERGY STORAGE↗
DOE OSTI2022

Unique Role of GeO 2 as a Noninvasive Promoter of Nano‐Sized Zeolite Crystals

Abstract The synthesis of zeolites with nano‐sized dimensions is often limited to a narrow design space that conventionally relies upon the design of organics to direct hierarchical materials. Here, it is demonstrated that the addition of an inorganic modifier, germanium oxide (GeO 2 ), to a zeolite growth mixture directs the formation of crystals with ultrasmall dimensions. This effect is observed for zeolites ZSM‐11 and ZSM‐5 over a range of synthesis conditions wherein the role of GeO 2 in zeolite crystallization deviates from its typical function as a heteroatom. Notably, the final products contain trace amounts of Ge, which indicates the inorganic modifier does not compete for sites in the zeolite framework based on its formation of a discrete phase that enables GeO 2 recovery. Catalytic tests using the methanol‐to‐hydrocarbons reaction reveal significant enhancement in the performance of zeolite catalysts prepared with GeO 2 compared to reported examples of nano‐sized zeolites. These findings highlight a potentially generalizable and commercially viable synthesis method to reduce mass‐transport limitations in zeolites for diverse applications.

Chemistry↗
DOE OSTI2025

The impact of argon addition on hydrogen superpermeation through palladium alloy metal foil pumps during direct internal recycling

Metal foil pumps (MFPs) are a leading technology for the direct internal recycling (DIR) of hydrogen isotopes from the plasma exhaust of fusion devices. MFPs rely on the concept of superpermeation, where plasma-generated atomic hydrogen absorbs into the metal foil, rapidly diffuses, and desorbs downstream. To date, studies of superpermeation have predominantly employed pure hydrogen or in some cases trace levels of impurities. In practice the plasma exhaust may contain significant levels of plasma enhancement gases such as argon, an inert gas with metastable states that can enhance the plasma. In this work, we systematically study the impact of Ar addition on the performance of PdCu and PdAg MFPs at low temperature. Performance was strongly dependent on the DIR fraction. At negligible DIR levels Ar addition did not significantly improve the flux over dilution effects. However, under appreciable DIR operation the flux was enhanced up to 90 % relative to pure H 2 , with the optimal concentration range being 5–10 % Ar exiting the system. Beyond 15 % addition plasma enhancement benefits were offset by dilution. Performance correlated with the atomic H emission, and benefits were more pronounced for PdAg than PdCu. Operation at significant DIR levels dramatically alters the flow dynamics resulting in concentration gradients near the MFP, creating plasma conditions that promote H 2 dissociation.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Evolution of LIBS technology to mobile instrumentation for expediting firearm-related investigations at the laboratory and the crime scene

Gunshot residue (GSR) is one of the few forensic disciplines that lack accurate screening techniques. This study proposes using a mobile LIBS instrument to detect inorganic GSR and compares performance to a previously validated laboratory instrument. The mobile LIBS is designed with advanced configurations specifically for on-site GSR analysis, including a CMOS detector and a sampling chamber that holds up to six typical GSR collection devices with separate gas flow ports to prevent cross-contamination. A significant novelty of the portable instrument is its image magnification, which allows quick searching and visualization of GSR particle morphology. The single-particle imaging and elemental composition capability is one of a kind and offers superior confirmatory features for GSR. The mobile LIBS performance was evaluated for residues collected from the hands of shooters (100 samples) and non-shooters (200 background samples), analyzed sequentially by the mobile instrument and then the laboratory instrument. Accuracies better than 98.8% were obtained by both instruments, demonstrating their suitability for trace IGSR detection from skin specimens. Implementation of this methodology is anticipated to drastically speed up response times (i.e., from several hours per sample by standard SEM-EDS practice to a few minutes by LIBS). The screening methods can be easily incorporated into workflows to improve decision-making processes at the crime scene and laboratory settings, reduce backlogs, and improve case management.

47 OTHER INSTRUMENTATION↗