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At least 559 records · Page 31

Unraveling the Mechanism of Water-Mediated Sulfur Tolerance via Operando Surface-Enhanced Raman Spectroscopy

While several proton-conducting anode materials have shown excellent tolerance to sulfur poisoning, the mechanism is still unclear due largely to the inability to probe miniscule amounts of sulfur-containing species using conventional surface characterization techniques. Here we present our findings in unraveling the mechanism of water-mediated sulfur tolerance of a proton conductor under operating conditions empowered by surface-sensitive, operando surface-enhanced Raman spectroscopy (SERS) coupled with impedance spectroscopy. Contrary to the conventional view that surface-adsorbed sulfur is removed mainly by oxygen anions, it is found that –SO 4 groups on the surface of the proton conductor are converted to SO 2 by a water-mediated process, as confirmed by operando SERS analysis and density functional theory (DFT)-based calculations. Furthermore, the combination of operando SERS performed on a model electrode and theoretical computation offers an effective approach to investigate into complex mechanisms of electrode processes in various electrochemical systems, providing information vital to achieve the rational design of better electrode materials.

25 ENERGY STORAGE↗

Controlling Mass Transport in Direct Carbon Dioxide Zero-Gap Electrolyzers via Cell Compression

The development of high-performance CO 2 electrolyzers is crucial for accelerating the sustainable production of fuels and chemicals integrated with renewable energy sources. Here, we introduce a methodology to actively control mass transport inside a realistic zero-gap membrane electrode assembly of a CO 2 electrolyzer by varying the gasket thickness, which consequently changes the cell compression. This allows control over the thickness and porosity of the gas diffusion electrodes, influencing the overall electrolyzer performance, as demonstrated using Ag-deposited electrodes. At low operating voltages (<2.9 V), both high- and low-compression electrolyzers exhibit similar faradaic efficiencies and partial current densities for CO formation. However, at high voltages, the low-compression electrolyzer with high electrode porosity demonstrates superior CO selectivity and activity with suppressed H 2 formation. These experimental results are validated by the computational membrane electrode assembly (MEA) model developed by using the measured in situ electrode thicknesses and electrode porosities. Additionally, liquid electrolyte saturation at the catalyst layer is found to play a dominant role in determining the mass transport, resulting in a decreased electrolyzer performance with low electrode porosity. Finally, the systematic investigation in this study improves the understanding of the transport dynamics in MEA-based devices and provides insights into optimizing device design parameters for industry-relevant CO 2 electrolysis.

30 DIRECT ENERGY CONVERSION↗

Dynamically Unveiling Metal–Nitrogen Coordination during Thermal Activation to Design High-Efficient Atomically Dispersed CoN 4 Active Sites

We elucidate the structural evolution of CoN 4 sites during thermal activation by developing a zeolitic imidazolate framework (ZIF)-8-derived carbon host as an ideal model for Co 2+ ion adsorption. Subsequent in situ X-ray absorption spectroscopy analysis can dynamically track the conversion from inactive Co-OH and Co-O species into active CoN 4 sites. The critical transition occurs at 700 °C and becomes optimal at 900 °C, generating the highest intrinsic activity and four-electron selectivity for the oxygen reduction reaction (ORR). DFT calculations elucidate that the ORR is kinetically favored by the thermal-induced compressive strain of Co-N bonds in CoN 4 active sites formed at 900 °C. Further, we developed a two-step (i.e., Co ion doping and adsorption) Co-N-C catalyst with increased CoN 4 site density and optimized porosity for mass transport, and demonstrated its outstanding fuel cell performance and durability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Advanced Algal Biofoundries for the Production of Polyurethane Precursors

The primary goal of the BEEPs project was to develop a process that could accelerate the development of algae as bioproduction platforms, from initial chemical product concept to an economically viable market supply. Under this program we elected to develop strains of algae that could generate polyurethane precursors, while simultaneously developing basic genetic tools to enable improved algal production systems. This program was specifically designed to incorporate National Laboratories as a means to utilize the expertise and facilities for new bio-production platforms. To that end, we designed a program to collaborate with the Agile BioFoundry at Lawrence Berkeley National Laboratory (LBNL) and computational platforms at Pacific Northwest National Laboratory (PNNL). In addition to these National Laboratory partners, we also had academic partners from UC Davis and Georgia Tech, as well as commercial partners Algenesis Materials and BASF. To achieve these goals, we initially focused on developing the genetic tools and high throughput screening technologies necessary to generate and assess production of polymer precursors (succinic acid) in algae and cyanobacteria, including advanced promoters and biosensors. In parallel, we computationally identified potential production bottlenecks and then used the developed genetic tools to increase production rates and yields. Constant feedback of data was used in conjunction with machine learning, high-throughput cell sorting, and synthetic biology, for additional targeted metabolic engineering. Multiple rounds of tool design, building, testing, and learning were supplied to partners at PNNL and LBNL to develop new models and tools that could expedite bioproduction platform development and increase yield performance. We targeted, and achieved, the FOA requirement yield metric of 20 g/L, as a milestone and deliverable from at least one of our engineered strains for the production of succinic acid.

09 BIOMASS FUELS↗

Hestia-SWIFL: hourly anthropogenic fossil fuel CO2 and heat on the 2km WRF grid, version 1.1

The Hestia-SWIFL version 1.1 anthropogenic heat (AH) and fossil fuel CO2 (FFCO2) emissions data product represent emissions due to the combustion of fossil fuel and cement production within the state of Arizona from 2019 to 2022. This product was developed as part of the Southwest Urban Corridor Integrated Field Laboratory (SW-IFL) project, which aims to provide new knowledge and tools that address extreme heat, air quality, climate change and related urban environmental issues by integrating high-resolution observations, modeling, and civic engagement. The emissions are generated using a bottom-up/engineering approach and are tied to results generated by the Vulcan Project version 4, an effort to quantify space/time-resolved FFCO2 & AH emissions for the entire United States landscape. A large number of data sources are combined to best estimate the emissions at fine scales such as air quality emissions data, traffic flow data, building information, sociodemographic information, and fuel statistics. The AH product provides emissions for two emissions sources (transportation and point source emissions) in units of Watts per hour per square meter (W/m2) per year (annual files) or per hour (hourly files). The FFCO2 product provides emissions from nine individual emission sectors as well as the total, and in units of tons of carbon (tC) per grid cell per year or per hour. The output made available here places the native spatial resolution of the Hestia FFCO2 & AH emissions data product (points, lines, and polygons) into a regularized 2km x 2km grid at hourly and annual temporal resolutions, and stored in netCDF files. The exact spatial extent is defined by the ASU Weather Research Forecast (WRF) simulation grid. All data are processed using R/Python pm high-performance computing system. 2-27-2026 updates: Bugs in airport hourly profile (both AH and FFCO2) and building spatial patterns (FFCO2 only) were fixed. Hourly emissions are reprocessed for all years to reflect those changes.

54 ENVIRONMENTAL SCIENCES↗

Reduced-model scrape-off layer turbulence (nSOLT) simulations comparing three fueling scenarios

The 2D scrape-off-layer turbulence code (nSOLT) includes 1D Boltzmann neutral–plasma interactions, a model of divertor recycling (introduced here), and a fixed source of plasma concentrated at the core-side boundary. Three fueling methods are considered herein: (1) neutral injection in the far-SOL is accomplished by specifying the density of Franck–Condon distributed neutrals streaming in from the boundary. (2) Divertor recycling is modeled by injecting a fraction of the particle parallel flux in the scrape-off layer (SOL) back into the edge region as a source of plasma. (3) A constant source fuels the edge plasma from the core-side boundary to model pellet injection. For machine parameters (B, R m , and L // ) illustrative of the MAST-U device, and for a deuterium plasma, turbulent equilibria are obtained that share the same plasma fueling rate for each of the three fueling methods, with only one of the sources on in each case. In the presence of self-consistent turbulence, quasi-steady plasma and neutral (deuterium) profiles, fueling efficiencies, SOL transparencies, and heat flux widths are compared. Characteristics of the turbulent fluctuations, including skewness, cross-phases, and power spectra, are described. The calculated fueling efficiencies, SOL transparencies to neutral penetration, and many of the turbulent properties are remarkably similar for all three fueling methods despite significant differences in the plasma profiles. The nonlinear states of the three cases are dominated by separatrix-spanning vortex cells that control particle and heat losses into the SOL.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DECOVALEX-2023: Task F1 Final Report

DECOVALEX-2023 Task F is a comparison of models and methods for post-closure performance assessment (PA) of a deep geologic repository for radioactive waste. The general aims of Task F are to build confidence in the models, methods, and software used for PA and to stimulate additional research and development in PA methodologies. The task objectives are to motivate development of PA modelling skills and capabilities, to examine the influence of model choices on calculated repository performance, and to compare the uncertainties introduced by model choices to other sources of uncertainty. Task F involves no actual experiment or site. It is a PA modelling exercise that requires the conceptual development of hypothetical repository designs and geologic settings. Because three of the teams were interested in salt and the rest of the teams were interested in crystalline rock, Task F was split into two branches: Task F1 for crystalline rock and Task F2 for salt. This report is for Task F1, crystalline rock. Teams from seven countries (Canada, Czech Republic, Germany, Korea, Sweden, Taiwan, and United States) participated in Task F1. The teams worked together to define the features, events, and processes of the reference case repository and established a set of performance measures. In addition, they defined a set of benchmark problems designed to test and compare modelling capabilities for fracture flow and transport at different scales. The repository design and benchmark problems are documented in a Task Specification that evolved over time as the group honed the specifications. The benchmark problems verified that each team can aptly model flow and transport in fractured media in 1-, 2-, and 3-dimensions. Two general approaches were used for the 3-dimensional benchmarks: discrete fracture network (DFN) and equivalent continuous porous medium (ECPM). DFN modelling involves explicit meshing of each fracture while ECPM modelling aims to capture the effective porosity and directional permeability of each cell in a space-filling mesh as affected by intersecting fractures. In some models, a combination of the two is used, i.e., DFN for large known fractures and ECPM for the rest of the domain. Transport is solved by using either the advection-dispersion equation or particle tracking. Although some variation is observed among model breakthrough curves in the benchmark problems, there is strong agreement in breakthrough behaviour up to at least the 75 th percentile for all benchmarks. At the 90 th percentile, breakthrough results show larger differences, suggesting several models retain substantially higher fractions of tracer in regions of slower moving water. In addition to the flow and transport benchmarks, several teams completed the source term benchmark, verifying capabilities for modelling radionuclide decay and ingrowth, waste package breach, instant release fractions, fuel matrix degradation rates, and radionuclide solubility limitations. The reference case is conceptualized as a generic spent fuel repository at a depth of 450 m in fractured crystalline rock. The repository has 50 parallel backfilled drifts, each with 50 deposition holes 6 m apart. Each deposition hole contains a 4-PWR waste package and bentonite buffer. The rock domain is 5 km in length, 2 km in width, and 1 km in depth. It has 6 deterministic fractured deformation zones and a multitude of stochastic fractures. Teams generally used the ECPM approach for the entire rock or a hybrid approach in which the deterministic fracture zones are modelled with a DFN and the rest of the rock is modelled by ECPM. Of the reference case problems specified, only the results of the initial reference case problem are compared in this report. The initial problem focuses on transport from the deposition holes to the surface, i.e., it neglects waste package performance. Tracers are released at all waste package locations at time zero and tracked for their releases to the near field and ground surface. The water fluxes calculated at the ground surface entry and exit regions of the domain are similar for all models except for two that have considerably lower fluxes. For tracer transport, large differences are observed among models in the magnitude of tracer transported. Much of the difference appears to be due to how the repository is implemented and hence the different degrees of repository simplification. Models that exclude the drifts, buffer, and backfill from the domain tend to show greater release of tracers and radionuclides from the repository. The initial study presented here indicates that major differences in modelling important processes within the repository (e.g., diffusion through buffer and backfill) can produce broadly different release and transport results, especially when those processes are excluded. Even for the models that included all specified features, events, and processes, the results show significant differences and demonstrate the importance of examining multiple modelling approaches in performance assessment. The differences in results observed in this study are expected to motivate teams to either increase complexity in future versions of the reference case models or to improve methods to account for the effects of simplified features and processes. Either way, future improvements in these models are expected to produce results that more closely agree.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Providing Experimental Infrastructure for Accelerating Advanced Reactor Demonstrations through the National Reactor Innovation Center

A suite of experimental infrastructure projects has been developed by the National Reactor Innovation Center to accelerate advanced reactor demonstrations and facilitate their development, addressing crucial gaps in data, materials characterization, and modeling. First, the Molten Salt Thermophysical Examination Capability (MSTEC) provides a specialized platform for post-irradiation characterization of molten salt reactor fuel, coolant salts, and structural materials, essential for supporting the design and operation of advanced reactors and future commercial molten salt reactor development and licensing. The Virtual Test Bed (VTB) complements these efforts by leveraging advanced modeling and simulation tools to evaluate reactor performance and safety. Serving as a library of reference models, the VTB offers a database of multiphysics reactor models, facilitating rapid safety evaluations and includes continuous software quality assurance, crucial for accelerating deployment while maintaining reliability. Additionally, the Helium Component Test Facility (HeCTF) addresses the need for high-temperature helium-cooled reactor component testing. As the first-of-its-kind facility in the United States, HeCTF emulates high-temperature gas reactor conditions, reducing time and cost associated with component validation, thereby accelerating reactor development. Finally, In-cell Thermal Creep Frames provide a unique solution for obtaining thermal creep data from irradiated materials, critical for materials qualification and licensing. Developed by the National Reactor Innovation Center, these compact frames enable the examination of previously irradiated materials, overcoming traditional limitations and enhancing the understanding of mechanical properties crucial for reactor development. Collectively, these experimental infrastructure projects form a comprehensive framework aimed at expediting advanced reactor demonstrations, fostering innovation, and ensuring the viability of next-generation nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Rapid mapping of electrochemical processes in energy-conversion devices

Electrochemical impedance spectroscopy (EIS) is ubiquitously applied to identify physicochemical processes governing the performance of energy-conversion devices. However, deconvolution and interpretation of impedance phenomena are limited by measurement throughput and a dearth of scalable analysis methods. Here, we demonstrate an approach to quickly collect and coherently analyze large volumes of electrochemical data. In this study, we accelerate impedance characterization by combining rapid measurements in time and frequency domains, which are interpretably transformed using the distribution of relaxation times (DRT) and a new distribution of phasances (DOP) model. This method provides excellent agreement with EIS and decreases measurement time by an order of magnitude. High-throughput spectra are then distilled into detailed electrochemical maps. This approach is applied to a Li-ion battery and a protonic ceramic electrochemical cell as practical case studies, demonstrating how mapping can richly characterize physicochemical relationships that are difficult to decipher with conventional measurement and analysis methods.

25 ENERGY STORAGE↗

Improving SOFC Anode Electrocatalytic Activity Using Nanoparticle Infiltration into MIEC Compositions

Mitigating activation polarization in the anode is one of the major challenges in intermediate-temperature operation of solid oxide fuel cells (SOFCs). Liquid phase infiltration of nanoscale electrocatalysts has been shown to result in significant reductions in activation polarization in SOFC anodes. In this study, we explore liquid-phase infiltration of nickel, gadolinium doped ceria (GDC), and Ni/GDC electrocatalysts into two different types of cermet anodes: one with a conventional Ni-YSZ composition, and the other with a Ni-MIEC cermet anode where the YSZ has been doped with 3 mol% TiO 2 to impart electronic conductivity. The principal goal of this study is to explore the role of electronic transport in the MIEC phase in effective utilization of the infiltrated nanoscale electrocatalysts. The role of temperature, infiltration cycles and the type of electrocatalysts have been experimentally studied in symmetric cells using electrochemical impedance spectroscopy (EIS). Distribution of relaxation times (DRT) modeling has been used to elucidate the contributions of various charge transfer processes.

25 ENERGY STORAGE↗

Electrochemically driven phase transformation for high-efficiency heat pumping

To reduce energy consumption and improve energy utilization in space conditioning, advanced heat pumping technologies are needed. The chemical looping heat pump (CLHP) is a promising thermodynamic cycle that has theoretically shown the potential to achieve a cooling coefficient of performance (COP c ) increase of over 20% relative to conventional vapor compression systems. In this paper, the key process of the CLHP is experimentally demonstrated, and the system performance and non-ideal behavior are predicted using the component-level models. The results show the feasibility of electrochemical phase change of a working fluid; the peak COP c was 7.64 with a cooling capacity of 3.6 mW (cooling density of 2.57 W m -2 ) at both sink and source temperature of 23°C based on laboratory experiments. The COP c can theoretically reach up to 13 at a temperature lift of 15°C as long as an electrochemical cell can achieve a greater degree of conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Degradation of Anion Exchange Membranes by Cation Elimination: Impact on Water Uptake, Nanostructure, and Ionic Mobility

Anion exchange membranes (AEMs) are an attractive platform for fuel cell and electrolysis technologies since they enable the use of cheaper, nonplatinum group metal electrodes and components. However, the widespread adoption of AEM-based devices is limited by chemical degradation of the AEM in the highly alkaline medium of operation. Experimental studies report three major pathways of degradation, including substitution (S N 2), elimination (E2), and backbone cleavage. The decline in membrane performance is likely due to a cumulative effect of several pathways, which has proven to be difficult to disentangle through experiments. Here we use coarse-grained molecular simulations to isolate the impact of E2 degradation, where cationic sites are replaced by an alkene group, on AEM water uptake, nanoscale morphology, structure of the ion-conducting channels, water mobility, and ionic conductivity. Our studies focus on the well-studied model AEM polyphenylene oxide with tetraalkylammonium cationic sites (PPO-TMA). We find that about half of the hydrophobic groups resulting from the degradation retract into the hydrophobic domains of the membrane. The reduction in ion exchange capacity (IEC) and the hydrophobicity of the alkene groups decrease both the equilibrium water uptake (%WU) and the number of water molecules per cation (λ) of the membrane. Interestingly, the evolution of λ with the IEC seems to follow that of undegraded PPO-TMA membranes. Additionally, we ascribe this to the similarity between the structure of the degraded monomer and the neutral one in the polymer. We conclude that most of the performance losses originate in the lower hydration of the degraded membrane.

36 MATERIALS SCIENCE↗

liionpack: A Python package for simulating packs of batteries with PyBaMM

Electrification of transport and other energy intensive activities is of growing importance as it provides an underpinning method to reduce carbon emissions. With an increase in reliance on renewable sources of energy and a reduction in the use of more predictable fossil fuels in both stationary and mobile applications, energy storage will play a pivotal role and batteries are currently the most widely adopted and versatile form. Therefore, understanding how batteries work, how they degrade, and how to optimize and manage their operation at large scales is critical to achieving emission reduction targets. The electric vehicle (EV) industry requires a considerable number of batteries even for a single vehicle, sometimes numbering in the thousands if smaller cells are used, and the dynamics and degradation of these systems, as well as large stationary power systems, is not that well understood. As increases in the efficiency of a single battery become diminishing for standard commercially available chemistries, gains made at the system level become more important and can potentially be realised more quickly compared with developing new chemistries. Mathematical models and simulations provide a way to address these challenging questions and can aid the engineer and designers of batteries and battery management systems to provide longer lasting and more efficient energy storage systems.

25 ENERGY STORAGE↗

Adaptive Laboratory Evolution for algal strain improvement: methodologies and applications

Originally developed in bacterial and fungal models, Adaptive Laboratory Evolution (ALE) experimentally selects for targeted phenotypes by allowing cells containing beneficial random genetic mutations to replicate more quickly in the presence of environmental stress. When applied to microalgae, this technique has been used to increase growth rate, stress tolerance, substrate utilization, and product yield. This review discusses ALE experimental design parameters, and summarizes key results and lessons learned from recent microalgal ALE studies. By documenting the current state of the field, we provide insight on the ways microalgal ALE might be used to develop commercially viable biotechnology strains.

09 BIOMASS FUELS↗

Four-Dimensional Quasielastic Neutron Scattering (4D-QENS) Analysis of Correlated Ionic Conduction in Sr⁢Cl2

Methods of elucidating the mechanisms of fast-ion conduction in solid-state materials are pivotal for advancements in energy technologies such as batteries, fuel cells, sensors, and supercapacitors. In this study, we examine the ionic conduction pathways in single crystal Sr⁢Cl2, which is a fast-ion conductor above 900 K, using four-dimensional quasielastic neutron scattering (4D-QENS). We explore both coherent and incoherent neutron scattering at temperatures above the transition temperature into the superionic phase to explore the correlated motion of hopping anions. Refinements of the incoherent QENS yield residence times and jump probabilities between lattice sites in good agreement with previous studies, confirming that ionic hopping along nearest-neighbor directions is the most probable conduction pathway. However, the coherent QENS reveals evidence of de Gennes narrowing, indicating the importance of ionic correlations in the conduction mechanism. This highlights the need for improvements both in the theory of ionic transport in fluorite compounds and the modeling of coherent 4D-QENS in single crystals.

Coles, Jared [Materials Science Division, Argonne ↗

Engineering custom morpho- and chemotypes of Populus for sustainable production of biofuels, bioproducts, and biomaterials

Humans have been modifying plant traits for thousands of years, first through selection (i.e., domestication) then modern breeding, and in the last 30 years, through biotechnology. These modifications have resulted in increased yield, more efficient agronomic practices, and enhanced quality traits. Precision knowledge of gene regulation and function through high-resolution single-cell omics technologies, coupled with the ability to engineer plant genomes at the DNA sequence, chromatin accessibility, and gene expression levels, can enable engineering of complex and complementary traits at the biosystem level. Populus spp., the primary genetic model system for woody perennials, are among the fastest growing trees in temperate zones and are important for both carbon sequestration and global carbon cycling. Ample genomic and transcriptomic resources for poplar are available including emerging single-cell omics datasets. To expand use of poplar outside of valorization of woody biomass, chassis with novel morphotypes in which stem branching and tree height are modified can be fabricated thereby leading to trees with altered leaf to wood ratios. These morphotypes can then be engineered into customized chemotypes that produce high value biofuels, bioproducts, and biomaterials not only in specific organs but also in a cell-type-specific manner. For example, the recent discovery of triterpene production in poplar leaf trichomes can be exploited using cell-type specific regulatory sequences to synthesize high value terpenes such as the jet fuel precursor bisabolene specifically in the trichomes. By spatially and temporally controlling expression, not only can pools of abundant precursors be exploited but engineered molecules can be sequestered in discrete cell structures in the leaf. The structural diversity of the hemicellulose xylan is a barrier to fully utilizing lignocellulose in biomaterial production and by leveraging cell-type-specific omics data, cell wall composition can be modified in a tailored and targeted specific manner to generate poplar wood with novel chemical features that are amenable for processing or advanced manufacturing. Precision engineering poplar as a multi-purpose sustainable feedstock highlights how genome engineering can be used to re-imagine a crop species.

09 BIOMASS FUELS↗

Solid-state batteries and the critical role of interfaces

The Grand Challenge for the next generation of energy storage technologies is no longer the identification of electroactive cathode or anode materials thanks to extensive worldwide synthesis efforts along with theory and modeling like the Materials Project.1 Instead, the critical challenges revolve around assembling materials in the right architecture to achieve maximum performance and cell life at reasonable temperatures and pressures. Nowhere is this more critical than on the next generation of energy storage technologies revolving around all solid-state batteries. These batteries are the ultimate challenge for materials science requiring new ways to assemble multiple dissimilar materials such that: (1) interfaces are optimized to facilitate ion motion across the different compounds while (2) maintaining chemical stability and (3) simultaneously preserving the crystal structures of each phase during (4) large volume changes due to shuttling of lithium, at (5) room temperature and under (6) atmospheric pressure. To address these requirements will require insights and expertise from research fields outside the traditional lithium-ion battery community such as solid oxide fuel cells, synthesis science, barrier layers, interface formers, sintering, and mechanical properties.

25 ENERGY STORAGE↗