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DOE OSTI2022

Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™

Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool.

environmental monitoring↗

DOE OSTI2023

Genesis of Active Pt/CeO 2 Catalyst for Dry Reforming of Methane by Reduction and Aggregation of Isolated Platinum Atoms into Clusters

Atomically dispersed metal catalysts offer the advantages of efficient metal utilization and high selectivities for reactions of technological importance. Such catalysts have been suggested to be strong candidates for dry reforming of methane (DRM), offering prospects of high selectivity for synthesis gas without coke formation, which requires ensembles of metal sites and is a challenge to overcome in DRM catalysis. However, investigations of the structures of isolated metal sites on metal oxide supports under DRM conditions are lacking, and the catalytically active sites remain undetermined. Data characterizing the DRM reaction-driven structural evolution of a cerium oxide- supported catalyst, initially incorporating atomically dispersed platinum, and the corresponding changes in catalyst performance are reported. X-ray absorption and infrared spectra show that the reduction and agglomeration of isolated cationic platinum atoms to form small platinum clusters/nanoparticles are necessary for DRM activity. Density functional theory calculations of the energy barriers for methane dissociation on atomically dispersed platinum and on platinum clusters support these observations. Here the results emphasize the need for in-operando experiments to assess the active sites in such catalysts. The inferences about the catalytically active species are suggested to pertain to a broad class of catalytic conversions involving the rate-limiting dissociation of light alkanes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Substitution or Shared Utilization? Intrahousehold Vehicle Use in Mixed-Powertrain Households

While previous research has focused heavily on understanding the factors deriving alternative fuel vehicle adoption rates, there remains a significant gap in understanding how households distribute mileage across different powertrains. This study utilizes data from the 2022 Next Generation National Household Travel Survey to investigate vehicle miles traveled within a sample of 150 plug-in electric vehicle (PEV)-owning households (in which at least one battery electric vehicle is present), characterizing how different powertrains are integrated into daily mobility. Leveraging a Seemingly Unrelated Regression (SUR) framework the study jointly models the utilization of PEVs, hybrid electric vehicles (HEV), and internal combustion engine vehicles (ICEVs) while accounting for household-level substitution effects. The results provide evidence of an asymmetric substitution effect. In households with mixed-powertrain configurations, the ICEV captures a substantially higher share of household miles (compared with the PEV), acting as a utility sponge. Conversely, the model identifies specific socioeconomic and geographic cohorts that prioritize PEV as the primary household workhorse, indicating a systematic sorting effect. Although the sample size limits broader generalizability, these findings suggest that PEVs are used for frequent, specific routine-intensive roles, whereas the ICEV remains a specialized utility vehicle. These insights highlight distinct intrahousehold vehicle use behaviors that are often obscured by aggregate fleetwide statistics.

25 ENERGY STORAGE↗

DOE OSTI2023

Modeling of Reactor Design and Optimization for Scale-Up of the Catalyxx Process for Ethanol Conversion to Higher Alcohol Biofuels

This report summarizes the results of a collaborative efforts between Oak Ridge National Laboratory (ORNL) and Catalyxx Inc. to investigate scale-up of Catalyxx’s Ethanol upgrading to higher alcohols process. The study was funded by the U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) under CRADA (Cooperative Research and Development Agreement) No: NFE-20-08396. The project is part of the Direct Funding Opportunity (DFO) for Computational Science to Enable Bioenergy program which utilized computational toolsets developed by the Consortium for Computational Physics and Chemistry, a multi-laboratory consortium in BETO. The report here summarizes a packed-bed reactor modeling effort spanning the range from lab to industrial scale (from 4 gram to 5-ton catalyst beds), and examining reactor design, process optimization strategies, and suggested design and operating conditions for Catalyxx’s ethanol upgrading plants. The results in this report have been shared in monthly steering meetings and presentations are available in the shared data house owned by Catalyxx. The modeling effort helped to define optimum operation conditions for maximum alcohol selectivity and yield: i.e., temperature control scenarios ranging from adiabatic to isothermal, feed rate, pressure, and inlet H 2 /Ethanol ratio. The modeling results were verified at lab-(4 gram) and pre-pilot (4 kg) scales and has been used to evaluate a 5-ton packed-bed reactor and identify operating conditions to maximize the butanol yield. Special focus was given to understanding mass-transfer effects in the pre-pilot and pilot-scale reactors, over the domain of flow rate, pressure, feed composition, pellet size, shape, porosity, bed voidage, and reactor dimensions (i.e., length/diameter). Modeling was also used to evaluate innovative reactor design concepts such as water removal to improve alcohol selectivity and yield, and a reactor with an additional side inlet to facilitate quenching. These concepts were thoroughly explored, and potential benefits were disclosed. The results in this report are summarized and described qualitatively to protect the IP rights of Catalyxx. The details have been shared with the Catalyxx team in the regular steering meetings. At the end of the project, Catalyxx Inc. announced a successful demonstration of pilot scale operation in Seville, Spain.

02 PETROLEUM↗

DOE OSTI2024

Spatial Progression of Polysulfide Reactivity with Lithium Nitrate in Li–Sulfur Batteries

LiNO 3 is a commonly used electrolyte additive in Li-S batteries, but the intricacies of its stabilizing effect on these batteries are not well-understood due to the complex chemical nature of Li-S electrolytes. This complexity often hampers clear characterization and interpretation of data. In this study, we explore the reactivity of LiNO 3 in Li-S batteries through in operando sulfur K-edge spectroscopy. To remove ambiguities, a sulfur-free electrolyte with LiNO 3 as the sole salt is used. This allows a precise elucidation of the reaction mechanism between LiNO 3 and polysulfides. Here, we observe that the reaction is chemical in nature and progresses spatially, influenced by the polysulfide concentration gradient across the electrolyte. Polysulfides are electrochemically generated in situ on the cathode side, leading to high local concentration. As a result, they cannot be fully oxidized by LiNO 3 and forms sulfites initially which are gradually further oxidized into sulfonates and sulfates. Conversely, polysulfides on the anode side have lower local concentration as they are not generated in situ but diffused from the cathode side. Their reaction with LiNO 3 leads to highly oxidized species like sulfonates and sulfates. These reaction products are not reduced during electrochemically cycling, suggesting their capabilities of passivating the electrodes and contributing to the cycle stabilities of Li-S batteries.

25 ENERGY STORAGE↗

DOE OSTI2021

Impact of ion fluxes across thylakoid membranes on photosynthetic electron transport and photoprotection

In photosynthetic thylakoid membranes the proton motive force (pmf) not only drives ATP synthesis, in addition it is central to controlling and regulating energy conversion. As a consequence, dynamic fine-tuning of the two pmf components, electrical (Δψ) and chemical (ΔpH), is an essential element for adjusting photosynthetic light reactions to changing environmental conditions. Good evidence exists that the Δψ/ΔpH partitioning is controlled by thylakoid potassium and chloride ion transporters and channels. However, a detailed mechanistic understanding of how these thylakoid ion transporter/channels control pmf partitioning is lacking. In this work, we combined functional measurements on potassium and chloride ion transporter and channel loss-of-function mutants with extended mathematical simulations of photosynthetic light reactions in thylakoid membranes to obtain detailed kinetic insights into the complex interrelationship between membrane energization and ion fluxes across thylakoid membranes. The data reveal that potassium and chloride fluxes in the thylakoid lumen determined by the K + /H + antiporter KEA3 and the voltage-gated Cl – channel VCCN1/Best1 have distinct kinetic responses that lead to characteristic and light-intensity-dependent Δψ/ΔpH oscillations. These oscillations fine-tune photoprotective mechanisms and electron transport which are particularly important during the first minutes of illumination and under fluctuating light conditions. By employing the predictive power of the model, we unravelled the functional consequences of changes in KEA3 and VCCN1 abundance and regulatory/enzymatic parameters on membrane energization and photoprotection.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

FY25 Electric Grid Security Annual Report

Sandia’s Electric Grid Security program advances a national vision of energy dominance and accessibility, while applying our national security -emphasis on ensuring of a secure, resilient, and affordable electric system for all users. Our achievements reflect a strategic approach combining technology development; modeling, simulation, and data analytics; and partnered demonstrations and outreach to further the adoption of advanced grid and storage technologies. Our FY25 efforts leverage the strengths of our partnerships—spanning Sandia’s core science and technology competencies as well as external technology leaders—to develop the solutions today which enable the grid of tomorrow. Key accomplishments in this report that support our strategy span our technical program areas and include: • New open-source analytical tools for systems -level planning and optimization, including significant advances to the QuESt analytical environment; • Further advancement of artificial intelligence and machine learning to enhanced grid operations and planning as we rise to the challenge of new large loads; • Development of solid-state power conversion technologies and a new medium-voltage research lab; • New technologies to assess wildfire vulnerabilities and mitigate potential impacts; • Advanced applications of new cybersecurity technologies with industry partners; • Contributions to understanding the impacts of electromagnetic pulses and geomagnetic disturbances on grid components; and • Digital twin development for hybrid microgrids with multiple generators, storage, and loads. This report indicates key areas of research and engagement and summarizes the impact of Sandia’s contributions through notable accomplishments, journal publications, patents, and technical conferences and presentations. It is provided with the hope that readers discover ways we can further team to create our modern grid and apply the outcomes of our efforts. The bulk of work described herein is funded by several offices within the U.S. Department of Energy (USDOE), including the Office of Electricity (OE); Cybersecurity, Energy Security, and Emergency Response (CESER); former offices such as the Office of Energy Efficiency and Renewable Energy (EERE), the Grid Deployment Office (GDO), the Office of Clean Energy Demonstrations (OCED), and other key programs at USDOE. As we continue to state in these annual reports, the contributors to our successes are too numerous to name here, though our team wishes to express our deep gratitude to the numerous program and project sponsors at the US Department of Energy, who often function equally as technical collaborators; our many partners in industry, academia, utilities, and other national labs; and fellow researchers and business partners at Sandia whose leadership and creativity have enabled the accomplishments described herein.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Revisiting Theoretical Tools and Approaches for the Valorization of Recalcitrant Lignocellulosic Biomass to Value-Added Chemicals

Biorefinery processes for converting lignocellulosic biomass to fuels and chemicals proceed via an integrated series of steps. Biomass is first pretreated and deconstructed using chemical catalysts and/or enzymes to liberate sugar monomers and lignin fragments. Deconstruction is followed by a conversion step in which engineered host organisms assimilate the released sugar monomers and lignin fragments, and produce value-added fuels and chemicals. Over the past couple of decades, a significant amount of work has been done to develop innovative biomass deconstruction and conversion processes that efficiently solubilize biomass, separate lignin from the biomass, maximize yields of bioavailable sugars and lignin fragments and convert the majority of these carbon sources into fuels, commodity chemicals, and materials. Herein, we advocate that advanced in silico approaches provide a theoretical framework for developing efficient processes for lignocellulosic biomass valorization and maximizing yields of sugars and lignin fragments during deconstruction and fuel and chemical titers during conversion. This manuscript surveys the latest developments in lignocellulosic biomass valorization with special attention given to highlighting computational approaches used in process optimization for lignocellulose pretreatment; enzyme engineering for enhanced saccharification and delignification; and prediction of the genome modification necessary for desired pathway fine-tuning to upgrade products from biomass deconstruction into value-added products. Physics-based modeling approaches such as density functional theory calculations and molecular dynamics simulations have been most impactful in studies aimed at exploring the molecular level details of solvent-biomass interactions, reaction mechanisms occurring in biomass-solvent systems, and the catalytic mechanisms and engineering of enzymes involved in biomass degradation. More recently, with ever increasing amounts of data from, for example, advanced mutli-omics experiments, machine learning approaches have begun to make important contributions in synthetic biology and optimization of metabolic pathways for production of biofuels and chemicals.

09 BIOMASS FUELS↗

DOE OSTI2026

General-Purpose Heat Source Radioisotope Thermoelectric Generator Flight Unit 5 Refurbished (GPHS-RTG F5R) Electrically Heated Thermal Vacuum Testing

Idaho National Laboratory (INL) has been tasked with the evaluation and refurbishment of the General Purpose Heat Source (GPHS) Radioisotope Thermoelectric Generator (RTG) Flight Unit 5 (GPHS-RTG F5R or F5R) that was defueled in 2005. This paper describes the testing of F5R in the thermal vacuum chamber and evaluation of the data demonstrating the generator meets updated Cassini-Huygens requirements. The generator produced 260 We of power at the specified 4100 Wth heat source inventory. This power exceeded the power requirement for 250 We , confirming system integrity and demonstrating that the generator is capable of potential NASA missions.

30 - DIRECT ENERGY CONVERSION↗

DOE OSTI2026

GPHS-RTG F5R Electrically Heated Thermal Vacuum Testing

30 - DIRECT ENERGY CONVERSION↗

DOE OSTI2022

Shade triggers posttranscriptional PHYTOCHROME-INTERACTING FACTOR-dependent increases in H3K4 trimethylation

The phytochrome (phy)-PHYTOCHROME-INTERACTING FACTOR (PIF) sensory module perceives and transduces light signals to direct target genes (DTGs), which then drive the adaptational responses in plant growth and development appropriate to the prevailing environment. These signals include the first exposure of etiolated seedlings to sunlight upon emergence from subterranean darkness and the change in color of the light that is filtered through, or reflected from, neighboring vegetation (“shade”). Previously, we identified three broad categories of rapidly signal-responsive genes: those repressed by light and conversely induced by shade; those repressed by light, but subsequently unresponsive to shade; and those responsive to shade only. Here, we investigate the potential role of epigenetic chromatin modifications in regulating these contrasting patterns of phy-PIF module-induced expression of DTGs in Arabidopsis (Arabidopsis thaliana). Using RNA-seq and ChIP-seq to determine time-resolved profiling of transcript and histone 3 lysine 4 trimethylation (H3K4me3) levels, respectively, we show that, whereas the initial dark-to-light transition triggers a rapid, apparently temporally coincident decline of both parameters, the light-to-shade transition induces similarly rapid increases in transcript levels that precede increases in H3K4me3 levels. Together with other recent findings, these data raise the possibility that, rather than being causal in the shade-induced expression changes, H3K4me3 may function to buffer the rapidly fluctuating shade/light switching that is intrinsic to vegetational canopies under natural sunlight conditions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Improved receiver noise calibration for ADMX axion search: 4.54 to 5.41 μeV

Axions are a well-motivated candidate for dark matter. The preeminent method to search for axion dark matter is known as the axion haloscope, which makes use of the conversion of axions to photons in a large magnetic field. Because of the weak coupling of axions to photons, however, the expected signal strength is exceptionally small. To increase signal strength, many haloscopes make use of resonant enhancement and high gain amplifiers, while also taking measures to keep receiver noise as low as possible such as the use of dilution refrigerators and ultra-low-noise electronics. In this paper, we derive the theoretical noise model based on the sources of noise found within a typical axion haloscope receiver chain, using the Axion Dark Matter eXperiment (ADMX) as a case study. We present examples of different noise calibration measurements at 1280 MHz taken during ADMX’s most recent data-taking run. These new results shed light on a previously unidentified interaction between the cavity and Josephson Parametric Amplifier as well as provide a better understanding of the systematic uncertainty on the system noise temperature used in the axion search analysis for this data-taking run. Finally, the consistency between the measurements and the detailed model provide suggestions for future improvements within ADMX and other axion haloscopes to reach a lower noise temperature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Proactive Regulatory Approaches to Electrification and Load Growth: Workshop Report

On July 10 and 11, 2024, Pacific Northwest National Laboratory and RMI led a workshop in Aurora, Colorado, to explore novel and proactive approaches to electrification and load growth while minimizing risks and costs to customers. Over the next decade, a unique opportunity exists to invest strategically in the electricity system to enable electrification across the transportation, industrial, and building sectors and respond to data and technology-based load growth. However, current utility and regulatory planning practices are insufficient to identify and enable the right investments, and work must be done to reduce the risk and decisional uncertainty faced by utility regulatory commissions and utilities. Ensuring timely electrification investments may require new approaches to address risk, uncertainty, prudence, and cost recovery. Understanding the decision-making process and information needs of utilities and regulators is critical. New policies (or application of policies), financial tools, systems analysis, regulatory mechanisms, and enhanced process transparency may be required. The workshop's goal was to identify proactive regulatory approaches for electrification and load growth that minimize costs and risks to customers. Our intention was that the conversations and the resulting solutions and takeaways would be specific and tactical rather than general and theoretical and that together we would create actionable next steps for key actors in the system, including utilities, regulators, thought leaders, researchers, and the U.S. Department of Energy (DOE). This report is intended to provide workshop attendees with a record and summary of the discussion and proposals raised at the workshop and to provide interested entities who did not attend, such as other regulators, policymakers, utilities, and U.S. DOE offices, with an understanding of what was discussed and with ideas to explore in their organizations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Thermophilic Geobacillus WSUCF1 Secretome for Saccharification of Ammonia Fiber Expansion and Extractive Ammonia Pretreated Corn Stover

A thermophilic Geobacillus bacterial strain, WSUCF1 contains different carbohydrate-active enzymes (CAZymes) capable of hydrolyzing hemicellulose in lignocellulosic biomass. We used proteomic, genomic, and bioinformatic tools, and genomic data to analyze the relative abundance of cellulolytic, hemicellulolytic, and lignin modifying enzymes present in the secretomes. Results showed that CAZyme profiles of secretomes varied based on the substrate type and complexity, composition, and pretreatment conditions. The enzyme activity of secretomes also changed depending on the substrate used. The secretomes were used in combination with commercial and purified enzymes to carry out saccharification of ammonia fiber expansion (AFEX)-pretreated corn stover and extractive ammonia (EA)-pretreated corn stover. When WSUCF1 bacterial secretome produced at different conditions was combined with a small percentage of commercial enzymes, we observed efficient saccharification of EA-CS, and the results were comparable to using a commercial enzyme cocktail (87% glucan and 70% xylan conversion). It also opens the possibility of producing CAZymes in a biorefinery using inexpensive substrates, such as AFEX-pretreated corn stover and Avicel, and eliminates expensive enzyme processing steps that are used in enzyme manufacturing. Implementing in-house enzyme production is expected to significantly reduce the cost of enzymes and biofuel processing cost.

Bhalla, Aditya↗

DOE OSTI2026

Observing dark matter decays to gravitons via graviton-photon conversion

Since dark matter is only known to have gravitational interactions, it may plausibly decay to gravitons on cosmological timescales. Although such a scenario can be easily realized, there are currently no known limits on this possibility based on indirect-detection methods. We propose a new search strategy that exploits the Gertsenshtein effect, whereby the gravitons produced in dark matter decays can convert to photons in large-scale magnetic fields along the line of sight to an observer. These conversions primarily occur within cosmological filaments which occupy a large (order unity) volume fraction and contain ∼ 10 – 100 nG fields with ∼ Mpc coherence lengths. Thus, dark matter decays to gravitons predict an irreducible population of extragalactic photons, which we constrain using the extragalactic gamma-ray background measured by the Fermi-LAT telescope. Using this method, we derive the first-ever constraints on the dark matter lifetime in the 0.1 GeV - 10 8 GeV mass range, contingent on the assumed filament magnetic field strength. We also make projections for the Advanced Particle-astrophysics Telescope, which can improve sensitivity to this dark matter decay channel by an order of magnitude beyond those we set using Fermi-LAT data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Assessing Nutrient and Carbon Responses to Agricultural Conservation Practices in Two Midwest Watersheds

The United States is undertaking efforts to transition to a low-carbon economy in response to the heightened impacts of climate change, which are largely attributed to decades of carbon-intensive development. A concerted effort by the energy sector to achieve net-zero carbon emissions is aimed at strategically reducing the carbon footprint of the energy supply chain, particularly in the production of feedstocks for biofuels. The production of biofuels relies heavily on land use and management practices in biomass cultivation. Among other factors, soil organic carbon (SOC) plays a crucial role in the biofuel carbon cycle, impacting land productivity, greenhouse gas emissions, and water quality. The process of carbon drawdown during plant growth and storage helps to mitigate the release of carbon dioxide (CO 2 ) into the atmosphere. Another key parameter is the release of nitrous oxide (N 2 O) — a potent greenhouse gas with a global warming potential 273 times that of CO 2 — from soil. While prioritizing low-carbon production, sustainable bioenergy also necessitates improved water quality and ecosystem services. Agricultural conservation practices can contribute to enhanced soil health and reduce nutrient and sediment loss into streams. However, studies that explore the broader impact of these practices on soil carbon storage and N 2 O emissions at a watershed scale are limited. Specifically, our understanding of how low-carbon feedstock production and management affect nutrient cycle dynamics is incomplete. This study assesses watershed responses to land management practices in two agriculturally dominant watersheds: the Raccoon River watershed and the Southfork of Iowa River watershed. The study focuses on carbon and nutrient dynamics, characterizing spatial and temporal variations in SOC, N 2 O, and nutrient loadings to examine the relationship between nutrient and carbon responses and agricultural conservation practices. The study employs the newly developed Soil Water Analysis Tool for Carbon (SWAT-C) model, calibrated using 20 years’ of climate and water monitoring data, to simulate and evaluate two agricultural conservation practices: no-till and crop residue harvest with cover crop planting. We compared the calibrated SWAT-C model with a historical baseline model, which allowed us to analyze various aspects of the watershed, including stream flow, suspended sediments, nitrogen, phosphorus, organic carbon, SOC at different depths, and N 2 O emissions from topsoil. Our SWAT-C modeling results indicate that, compared with results from the historical baseline model, no-till practices are positively correlated with SOC accumulation, reduced N 2 O emissions, and decreased soil loss. We also observed no change or slightly increased nitrogen and phosphorus loss to water bodies in the watersheds compared with the baseline. Conversely, crop residue harvest with cover crop planting improved water quality by reducing nutrient and soil losses but also increased N 2 O emissions. This SWAT-C modeling study establishes the groundwork for further smaller-scale and/or sub-basin-level assessments of nitrogen, phosphorus, and carbon cycles. It provides valuable science-based insights to inform policy decisions — particularly in the context of transitioning to biofuel feedstock production in these watersheds — by addressing concerns about nutrient exports to local water bodies and, ultimately, the Mississippi River.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Microwave-Assisted Gasification of Biochar: Effect of Operational Parameters and Biochar Composition on Syngas Production

The utilization of microwave-assisted gasification for biomass/plastic is a promising route toward clean energy production, contributing to a reduction in carbon footprint. This method facilitates the conversion of biomass into syngas with enhanced hydrogen (H2) yield, surpassing conventional heating approaches. However, the gasification of biochar, a byproduct resulting from the initial rapid pyrolysis of biomass, appears as a rate-determining step in biomass gasification. To ensure high conversion efficiency, particularly in pilot or larger scales, the maintenance of high biochar reactivity is essential, which can be achieved by introducing catalysts to minimize biochar formation. Furthermore, given the susceptibility of biochar to microwave heating, gaining a comprehensive understanding of its behavior in the presence of microwave-active catalysts under microwave conditions is crucial to obtain valuable insights into the underlying mechanisms, thereby improving overall biomass gasification efficiency. In the previous study, magnetite (Fe3O4) was selected for microwave-assisted gasification for biomass/plastic due to its dual role as a catalyst and microwave absorber and demonstrated considerably enhanced hydrogen production. Herein, Fe3O4 is rationally modified with metal promoters and their synergistic effect toward biochar gasification performance is investigated. The data shows that metal promoted Fe3O4 shows a higher syngas yield than that of pristine Fe3O4 in biochar.

Mai, Duy Hien↗

DOE OSTI2020

Use of a segmented cell for the combinatorial development of platinum group metal-free electrodes for polymer electrolyte fuel cells

The development of novel platinum group metal (PGM)-free catalysts is a difficult task, particularly when coupled with the integration into a cathode catalyst layer (CCL). The optimization of such PGM-free electrode structures is often non-linear and iterative, making it a demanding task due to the high number of parameters that affect performance. To accelerate both materials discovery and electrode development, this work demonstrates the application of a high-resolution segmented cell (SC) with 121 segments of 0.413 cm 2 size for combinatorial high-throughput PGM-free catalyst screening and CCL optimization. The approach utilizes three flow-field strips with active areas of 4.45 cm 2 each, distributed over 11 segments. Electrodes with identical catalyst material and fabrication method result in reproducible data with typically less than 10% variation between each segment and match in performance with differential single cell data. High throughput testing of combinatorial sample sets, with varied PGM-free electrocatalyst materials or electrode composition, demonstrated the ability to rapidly discern high performing outliers, and establish or confirm trends in electrode optimization. The results indicated significant performance benefits of electrodes with ionomer content of 45 wt% over lower values, and of water rich inks with 82% water content over those with 50%.

30 DIRECT ENERGY CONVERSION↗