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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Advanced Fuels Campaign: Strategic Vision

The Advanced Fuels Campaign (AFC) is dedicated to propelling the United States to the forefront of nuclear fuel technology through a comprehensive strategic vision. The vision is structured around five key goals: driving U.S. leadership in nuclear fuel technology, expanding nuclear energy production from the existing fleet, completing the qualification basis for advanced reactor fuel technology, driving innovation in advanced nuclear fuel technology, and enabling a high-performing organization. By focusing on these goals, AFC aims to define and implement cutting-edge nuclear fuel technologies, support industry advancements, achieve critical fuel qualifications, foster innovative research, and ensure effective program management and stakeholder engagement. This strategic approach will solidify the United States’ position as a global leader in nuclear energy and fuel technology, while also preparing for the future of environmentally friendly and reliable nuclear power.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Rapidly ramp cryogenic air separation unit without loss of O2 product purity—application for low-carbon fossil-fuel plants

The rapid integration of intermittent renewable sources into the electricity grid is driving the need for low-carbon, fossil-fuel power plant capable of rapid ramping. Therefore, a cryogenic air separation unit (ASU) as part of low-carbon, fossil-fuel power plant should be capable of rapid ramping. However, highly integrated and nonlinear processes of the ASU would significantly restrict this rapid ramping. To overcome this fundamental issue, we study the basic dynamic process of a state-of-the-art double-column ASU. A flow-driven dynamic model was established in Aspen Plus Dynamics, assuming perfect flow controls, to capture the basic dynamics of ramping ASU. We find the vapor-liquid counter-current flow structure in the low-pressure column is critical to the air separation when rapidly ramping the ASU. This flow structure is established based on a complicated heat integration process. It is simplified as an apparent counter-current heat transfer process in this work, which greatly reduces the complexity for studying the dynamics of ASU. For keeping this basic flow structure, the heat integration is maintained as its heat duty follows the ASU load, through several basic feed-forward and feed-back controllers on the critical stream flowrates. Moreover, we find a fundamental issue of mismatched dynamics in the low-pressure column, resulting in a significant loss of O2 product purity when rapidly ramping down the ASU and an obvious fluctuation of O2 product purity. Based on these explorations, we propose a basic control method for rapidly ramping the ASU without loss of O2 product purity. Results show the ASU basic dynamic process successfully ramps at a rate up to 10%/min (40-100% load) while maintaining the O2 product purity within 95.2-95.6 mol%.

Cheng, Mao↗
DOE OSTI2021

AGR-5/6/7 Irradiation As Run Predictions Using PARFUME

The PARticle FUel ModEl (PARFUME), a fuel performance modeling code used for high-temperature gas-cooled reactors, was used to model the Advanced Gas Reactor (AGR)-5/6/7 irradiation test using as-run physics and thermal data. The AGR-5/6/7 irradiation test consists of the combined fifth, sixth, and seventh planned irradiations of the AGR Fuel Development and Qualification Program. The AGR-5/6/7 test train is a multi-capsule, instrumented experiment that is designed for irradiation in the 133.4-mm diameter northeast flux trap position of the Advanced Test Reactor (ATR) at Idaho National Laboratory. Each capsule contains compacts filled with uranium oxycarbide unaltered fuel particles. This report documents the calculations performed to predict the failure probability of tristructural isotropic (TRISO)-coated fuel particles during the AGR-5/6/7 experiment. In addition, this report documents the calculated fission product release fraction from the fuel. The calculations include modeling of the AGR 5/6/7 irradiation that occurred from February 2018 to July 2020 over nine ATR cycles, including six normal cycles and three power axial locator mechanism cycles, for a total of approximately 376 effective full power days (EFPD). The irradiation conditions and material properties of the AGR-5/6/7 test predicted zero fuel particle failures in Capsules 1, 3, and 4. Fuel particle failures were predicted in two of the compacts in Capsule 2 and one particle failure is predicted in each one of the compacts in Capsule 5. All compacts that exhibited fuel particle failures predicted by PARFUME were caused by localized stress concentrations in the silicon carbide (SiC) layer caused by cracking in the inner pyrolytic (IPyC) layer. In addition, shrinkage of the buffer and IPyC layer during irradiation resulted in formation of a buffer-IPyC gap. Compacts with a lower irradiation temperature and fluence experienced the smallest buffer-IPyC gap formation. Conversely, higher irradiated temperature compacts with a high fluence experienced the largest buffer-IPyC gap formation. Compact 3-6-3 experienced the largest buffer IPyC gap formation of just under 21.7 µm. The release fraction of fission products silver (Ag), cesium (Cs), and strontium (Sr) vary depending on capsule location and irradiation temperature. The maximum release fraction of Ag occurs in Capsule 3, reaching up to 59.5% for the TRISO fuel particles (compact 3-6-3). The release fraction of the other two fission products, Cs and Sr, are much smaller. A maximum Cs release fraction of 1.1% occurred in compact 3-4-3 and 4.4% for Sr in compact 3-6-3.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Supply Chain Sustainability Analysis of Renewable Hydrocarbon Fuels via Indirect Liquefaction, Ex Situ Catalytic Fast Pyrolysis, Hydrothermal Liquefaction, Combined Algal Processing, and Biochemical Conversion: Update of the 2019 State-of-Technology Cases

This technical report describes the supply chain sustainability analysis (SCSAs) for the production of renewable hydrocarbon transportation fuels via a range of conversion technologies: (1) renewable high octane gasoline (HOG) via indirect liquefaction (IDL) of woody lignocellulosic biomass (note that the IDL pathway in this SCSA represents the syngas conversion design in the 2019 SOT); (2) renewable gasoline (RG) and diesel (RD) blendstocks via ex situ catalytic fast pyrolysis of woody lignocellulosic biomass; (3) RD via hydrothermal liquefaction (HTL) of wet sludge from a wastewater treatment plant; (4) renewable hydrocarbon fuels via biochemical conversion of herbaceous lignocellulosic biomass; (5) renewable diesel via HTL of a blend of algae and woody biomass; and (6) renewable diesel via combined algae processing (CAP). This technical report focuses on the environmental performance of these six biofuel production pathways in their 2019 SOT cases. The results of these renewable hydrocarbon fuel pathways in these SCSA analyses update those for the respective 2018 SOT cases. They also provide an opportunity to examine the impact of technology improvements in both biomass feedstock production and biofuel production that have been achieved in 2019 SOTs on the sustainability performance of these renewable transportation fuels, and they reflect updates to Argonne National Laboratory’s Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET®) model, which was released in October 2019. These GREET updates include the production of natural gas, electricity, and petroleum-based fuels that can influence biofuels’ supply chain greenhouse gas (GHG) (CO₂, CH₄, and N₂O) emissions, water consumption, and air pollutant emissions. GHG emissions, water consumption, and nitrogen oxides (NO x ) emissions are the main sustainability metrics assessed in this analysis. In this analysis, we define water consumption as the amount of water withdrawn from a freshwater source that is not returned (or returnable) to a freshwater source at the same level of quality. Life-cycle fossil energy consumption and net energy balance, which is the life-cycle fossil energy consumption deducted from the renewable biofuel energy produced, are also assessed.

09 BIOMASS FUELS↗
DOE OSTI2020

First Examination of Irradiated Fuel with Pulsed Neutrons at LANSCE (Preliminary Results)

We present preliminary results on the characterization of an irradiated U-lOZr-lPd fuel sample that was prepared from the irradiated AFC-3A-R5A sample. U-lOZr metallic fuels are researched as host materials for potential transmutation fuels and the addition of palladium strives to bind lanthanides, thus preventing fuel-cladding chemical interactions (FCCI). These interactions limit the lifetime of metallic fuels and are caused by migration of lanthanide fission products to the periphery of the fuel slug, where they start to interact with the D9 or HT9 steel cladding, ultimately leading to failure of the mechanical integrity of the cladding. Neutrons offer bulk characterization of irradiated materials for which X-ray tomography methods are not suitable due to the immense gamma background emitted from the samples. In particular pulsed neutrons provide information from the ability to resolve the neutron energy using their time-of-flight and thus the potential to utilize neutron absorption resonance to characterize the spatial distribution of isotopes. This, in turn, may allow to characterize the distribution of fission and neutron capture products non-destructively and may ultimately be applied to the bulk of an irradiation capsule prior to destructive post-irradiation examination to identify regions of interest. To allow the characterization of entire irradiation capsules, a cask is under development in the advanced post-irradiation work package at LANL and progress on this development was reported elsewhere. In parallel, an irradiated U-lOZr-lPd sample cut from the AFC-3AR5A irradiation was shipped to LANL and will be fully characterized with an NSUF funded rapid turnaround experiment (RTE) in the 2020 LANSCE run cycle. The sample emits at a dose rate of ~3R/hr on contact and is therefore manageable with remote handling, without requiring a cask. The disk-shaped material is larger than samples prepared for analysis using electron or X-ray methods and is therefore an intermediate step towards characterization of bulk samples at LANSCE. However, since it covers the full diameter of the irradiated fuel slug, some insight on redistribution of elements, spatially resolved information on microstructure, e.g. phase composition and texture, will be possible using the pulsed neutron-based methods developed for fuel characterization at LANSCE. This report describes the development of procedures to handle the sample at LANSCE as well as preliminary data and results from tests conducted in December 2019 on the energy-resolved neutron imaging (ERNI) beam line at flight path 5 and the high pressure-preferred orientation diffractometer (HIPPO) at LANSCE. This effort is a collaboration between LANL, INL, and ORNL. To compare our capabilities with prior work, we present an overview of previously reported bulk characterization of irradiated or spent fuels. The overview addresses neutron diffraction and neutron absorption resonance spectroscopy, both of which have only few reported applications on irradiated or spent nuclear fuel, as well as neutron radiography. This literature review was already described in a previous report but is repeated here to put our current efforts in context of previous work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Multiscale, mechanistic modeling of cesium transport in silicon carbide for TRISO fuel performance prediction

Understanding cesium (Cs) transport in TRistructural ISOtropic (TRISO) particle fuel is crucial for predicting fission product release in high-temperature reactors. However, current challenges include significant scatter in diffusivity data and unexplained temperature-dependent diffusion regimes in the silicon carbide layer. This study addresses these challenges by developing a multiscale, mechanistic Cs transport model integrating atomistic simulations and phase field modeling. Our model quantifies temperature and grain size effects on Cs diffusivity, attributing experimentally observed regimes to a transition from bulk-dominated diffusivity at high temperatures to grain boundary-dominated diffusivity at lower temperatures. The model, validated against diffusion measurements and advanced gas reactor (AGR)-1 and AGR-2 post-irradiation fission product release data, enhances the predictive capability of the BISON fuel performance code. This study advances our understanding of Cs release from TRISO particles and its dependence on temperature and silicon carbide grain size, with implications for the safety and efficiency of high-temperature nuclear reactors.

BISON↗
DOE OSTI2025

Entrapment Behavior of Solid Surrogate Fission Products at Engineered UN Nano‐Hetero‐Interfaces Within Metallic Nuclear Fuels

Nanometric hetero-interfaces provide a wealth of scientific and engineering opportunities due to their complex and often misunderstood properties that can differ from their respective bulk constituents. In this work, the ability for engineered nanostructures within a bulk U─Mo alloy to arrest simulant fission products is investigated experimentally and computationally. Nanostructured 90 wt% U/ 10 wt% Mo (U-10Mo) with 7.1 at% Nd is consolidated using spark-plasma- sintering (SPS) techniques and is heat-treated at 500 °C under vacuum for 24, 100, 500, and 1000 h. Analysis on the sintered and heat-treated U-10Mo reveals rapid kinetics in Nd diffusion to nanocluster sites, with evidence of Nd diffusion occurring during sintering and during the following heat-treatment. The segregation behavior of Nd at two different U─Mo/UN interfaces is computationally verified using density functional theory (DFT) to reinforce experimental data.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Reducing Coke and Increasing Bio-Oil Yield during Catalytic Fast Pyrolysis of Biomass Using Phosphorus-Modified Zeolite Catalysts

Catalytic fast pyrolysis (CFP) is a promising strategy for producing hydrocarbon transportation fuels from biomass feedstocks. However, catalyst development is needed to increase bio-oil yields and enhance process economics. In this work, we demonstrate how post synthetic modification of formed ZSM-5 with phosphorus shifts CFP selectivity from coke and light gases toward the desired bio-oil product. Microscale experiments demonstrated reduced coke production relative to unmodified ZSM-5 and identified an optimal P loading. Extensive catalyst characterization revealed that P interacted with Al sites to reduce the acid site density, with preferential binding to the strongest acid sites. Insights from the microscale experiments were leveraged to produce kilogram quantities of formed P-ZSM-5 for evaluation in a larger semi-integrated process. These experiments generated liters of bio-oil that was hydrotreated and fractionated into gasoline, diesel, and jet cuts. The phosphorus-modified ZSM-5 improved CFP bio-oil yield, resulting in an 11% relative increase in the carbon yield from biomass to aviation fuel and a 14% decrease in the minimum fuel selling price. These results highlight the impact targeted changes in catalyst acidity, achieved by adding 2.5 wt % P, can have on the carbon efficiency and feasibility of fuel production from biomass feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2022

Understanding the structure and composition of recalcitrant oligosaccharides in hydrolysate using high-throughput biotin-based glycome profiling and mass spectrometry

Novel Immunological and Mass Spectrometry Methods for Comprehensive Analysis of Recalcitrant Oligosaccharides in AFEX Pretreated Corn Stover. Lignocellulosic biomass is a sustainable alternative to fossil fuel and is extensively used for developing bio-based technologies to produce products such as food, feed, fuel, and chemicals. The key to these technologies is to develop cost competitive processes to convert complex carbohydrates present in plant cell wall to simple sugars such as glucose, xylose, and arabinose. Since lignocellulosic biomass is highly recalcitrant, it must undergo a combination of thermochemical treatment such as Ammonia Fiber Expansion (AFEX), dilute acid (DA), Ionic Liquid (IL) and biological treatment such as enzyme hydrolysis and microbial fermentation to produce desired products. However, when using commercial fungal enzymes during hydrolysis, only 75–85% of the soluble sugars generated are monomeric sugars, while the remaining 15–25% are soluble recalcitrant oligosaccharides that cannot be easily utilized by microorganisms. Previously, we successfully separated and purified the soluble recalcitrant oligosaccharides using a combination of charcoal and celite-based separation followed by size exclusion chromatography and studies their inhibitory properties on enzymes. We discovered that the oligosaccharides with higher degree of polymerization (DP) containing methylated uronic acid substitutions were more recalcitrant towards commercial enzyme mixtures than lower DP and neutral oligosaccharides. Here, we report the use of several complementary techniques that include glycome profiling using plant biomass glycan specific monoclonal antibodies (mAbs) to characterize sugar linkages in plant cell walls and enzymatic hydrolysate, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) using structurally-informative diagnostic peaks offered by negative ion post-secondary decay spectra, gas chromatography followed by mass spectrometry (GC–MS) to characterize oligosaccharide sugar linkages with and without derivatization. Since oligosaccharides (DP 4–20) are small, it is challenging to mobilize these molecules for mAbs binding and characterization. To overcome this problem, we have applied a new biotin-coupling based oligosaccharide immobilization method that successfully tagged most of the low DP soluble oligosaccharides on to a micro-plate surface followed by specific linkage analysis using mAbs in a high-throughput system. This new approach will help develop more advanced versions of future high throughput glycome profiling methods that can be used to separate and characterize oligosaccharides present in biomarkers for diagnostic applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

AGR Irradiated Specimen Air/Moisture Heating Test Plan

The Advanced Gas Reactor (AGR) program has a need to perform high-temperature oxidation testing of tristructural isotropic (TRISO)-coated particle fuel and reactor core materials to evaluate their performance under conditions relevant to air- and moisture-ingress events in high-temperature gas-cooled reactors (HTGRs). The objectives of these tests are to assess the impact of oxidizing environments on fission product release from exposed fuel kernels, compact matrix, and nuclear grade graphite, and to determine the impact of oxidizing environments on TRISO coating integrity. The program is currently developing a capability for testing irradiated fuel, matrix, and graphite specimens inside a hot cell. The Air/Moisture Ingress Experiment (AMIX) system will be capable of temperatures up to 1650°C in atmospheres containing oxygen or moisture with varying concentrations. The system will be capable of collecting fission gases as well as condensable fission products, in order to quantify total released inventory from the heated specimens. A basis for establishing experimental test matrices, and the test matrices themselves, are presented in this document. This includes considerations on specific objectives for the tests, types of oxidizing environments that should be tested, and the expected availability of irradiated specimens from the various AGR program irradiation experiments. This document only briefly discusses post-test analysis of the heated specimens, and it is recognized that in many cases the post-test analysis may be extensive. It is expected that this will be a “living” document, subject to revision as data are collected and scoping calculations are performed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Three-dimensional microstructural characterization of FBR MOX fuel and the contribution of microstructural features to the thermal conductivity of the fuel

Combination of microstructural characterization, property measurements, and phase field modeling is used to investigate fast breeder reactor (FBR) mixed oxide (MOX) fuel irradiated to burnup of 13.7% fissions per initial metal atom (FIMA). Here, the fuel was characterized at different radial locations, which revealed that grey phase can be present in the central region if it nucleates on five metal precipitates (FMPs). In addition, in the mid-radial region FMPs do not diffuse out of the region once formed and the size of Pd–Te precipitates is dictated by the porosity present in the region. Thermal conductivity measurements were conducted as a function of radial location and the microstructure of the fuel was correlated with the observed trend. Reconstructions of the 3D solid and gaseous fission product structures in different regions of the fuel were used to simulate the effective thermal conductivity (ETC) of the respective regions and determine which microstructural feature has the strongest impact on thermal conductivity. Based on conducted assessment, FMPs and Pd-Te precipitates improve local conductivity of central and mid-radial regions even in the presence of grey phase, but defects are primary contributor to the degradation of thermal conductivity on the periphery of the fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

VERIFICATION OF TRISO FUEL BURNUP USING MACHINE LEARNING ALGORITHMS

Pebble Bed Reactors are fueled with fuel pebbles that are circulated multiple times through the reactor vessel before discharge. During the normal operation of a PBR, ejected pebbles are returned to the reactor or discharged depending on the fuel burnup and physical condition of the pebbles. The burnup measurement is usually based on detected radiation signatures of fission products accumulated in the pebble fuel over burnup. Previous research has shown that height of photopeaks of fission products, such as 134Cs, 137Cs, 154Eu, etc., can be used independently or in combination to infer or predict the level of burnup in the fuel. However, it remains challenging to measure such complex sources due to self-shielding effects, strong radiation background and intervening materials. Another operational challenge is the required high throughput of burnup measurement, which necessitates limited measurement time and thus impacts quality of measured gamma-ray spectra. Hence, advanced spectral analysis methods are needed to analyze the noisy gamma spectra and predict the burnup values. We propose to use machine learning (ML) method to interpret gamma-ray spectra and predict the burnup values of the pebbles. ML has achieved widespread success and adoption across a few domains that require pattern recognition and analysis in varied data types. In this work, we apply three proven ML approaches - multilayer perceptrons, convolutional neural networks, and transformers - to the task of predicting fuel burnup from measured gamma spectra, and compile a dataset of simulated spectra for training and validation of the ML models. In this paper, we will discuss the network architecture of these three ML approaches and compare the performance of the simplest of these (MLP) to a standard linear regression.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Renewable Diesel Production through Stand-Alone and Co-Hydrotreating of Catalytic Fast Pyrolysis Oil

Catalytic Fast Pyrolysis (CFP) of biomass followed by hydrotreating can be used for the production of renewable transportation fuels, such as sustainable aviation fuel and renewable diesel, which can reduce the dependence on fossil fuels and help achieve greenhouse gas reduction goals. Stand-alone hydrotreating of CFP oil and co-hydrotreating of the CFP oil with straight-run diesel (SRD) showed potential to produce high-quality diesel products in this study. Stand-alone hydrotreating of CFP oil produced a diesel fraction with oxygen content < 0.1 wt.% and an indicated cetane number (ICN) of 45. Co-hydrotreating of CFP oil and SRD using a 1:4 volumetric ratio produced diesel products with 0.1 wt.% of oxygen and ICNs of 42-45. Compared to CoMo/Al2O3, NiMo/Al2O3 was a more attractive catalyst for co-hydrotreating of two streams, leading to a higher carbon efficiency, a higher selectivity of cycloalkanes, a higher ICN, and enhanced desulfurization. Compared to stand-alone hydrotreating of CFP oil, co-hydrotreating with SRD could be achieved at a less severe operating condition and it produced hydrotreated products with a higher carbon efficiency. Synergy between CFP oil and SRD during co-hydrotreating process was suggested by the better experimental results in comparison with theoretical interpolation results. Co-hydrotreating gave high biogenic carbon incorporations of 91%-97% as determined by C-14 analysis.

biomass↗
DOE OSTI2026

Innovating High Throughput Hydrogen Stations: Cooperative Research and Development Final Report, CRADA Number CRD-18-00773

Hydrogen stations today serve the emerging market of light duty fuel cell vehicles, primarily in California with over 30 public retail locations. There has been a steady increase in the number of stations open and hydrogen dispensed, especially in the last two years. From 2015 to 2016, the annual amount of hydrogen dispensed increased from 27,400 kg to 109,200 kg, a nearly fourfold increase in just one year. One station dispensed nearly 12,000 kg in the second quarter of 2017. Despite the significant progress, gaps exist between current infrastructure capabilities and future requirements. For example, fuel cell vehicle applications such as buses, medium-duty, and heavy-duty trucks will gain market share and this must be considered as future customers at hydrogen stations. The expected number of light duty fuel cell vehicles in California alone are expected to grow from approximately 4,000 to over 13,000 by 2020, and 37,000 by 2023. To serve the multiple mobile fuel cell technologies and increased demand, hydrogen stations will have to increase output, decrease cost, and improve reliability. To address these challenges, the project team will demonstrate a hydrogen-focused integrated renewable energy production, storage, and transportation fuel distribution/retailing system. The proposed R&D tasks address key challenges related to light duty station/component reliability and development and validation of high flow rate system models for new applications like medium and heavy-duty truck fueling.

08 HYDROGEN↗
DOE OSTI2021

Verification of Triso Fuel Burnup Using Machine Learning Algorithms

Pebble Bed Reactors are fueled with fuel pebbles that are circulated multiple times through the reactor vessel before discharge. During the normal operation of a PBR, ejected pebbles are returned to the reactor or discharged depending on the fuel burnup and physical condition of the pebbles. The burnup measurement is usually based on detected radiation signatures of fission products accumulated in the pebble fuel over burnup. Previous research has shown that height of photopeaks of fission products, such as 134 Cs, 137 Cs, 154 Eu, etc., can be used independently or in combination to infer or predict the level of burnup in the fuel. However, it remains challenging to measure such complex sources due to self-shielding effects, strong radiation background and intervening materials. Another operational challenge is the required high throughput of burnup measurement, which necessitates limited measurement time and thus impacts quality of measured gamma-ray spectra. Hence, advanced spectral analysis methods are needed to analyze the noisy gamma spectra and predict the burnup values. We propose to use machine learning (ML) method to interpret gamma-ray spectra and predict the burnup values of the pebbles. ML has achieved widespread success and adoption across a few domains that require pattern recognition and analysis in varied data types. In this work, we apply three proven ML approaches - multilayer perceptrons, convolutional neural networks, and transformers - to the task of predicting fuel burnup from measured gamma spectra, and compile a dataset of simulated spectra for training and validation of the ML models. In this paper, we will discuss the network architecture of these three ML approaches and compare the performance of the simplest of these (MLP) to a standard linear regression.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Controlling Product Selectivity in Photochemical CO 2 Reduction with the Redox Potential of the Photosensitizer

The ability to selectively reduce CO 2 to a particular product or mixture of products is expected to play a key role in mitigation strategies aiming to alleviate the devastating impact of this greenhouse gas in our climate and oceans. Among those, the production of liquid solar fuels from CO 2 and H 2 O will likely need cascade strategies involving multiple catalysts carrying out different functions. This will require that the catalysts doing the initial CO 2 reduction steps deliver the right product or products to downstream catalysts. CO, H 2 and formate are the most common products in CO 2 reduction by molecular catalysts. Here, in this work, we demonstrate control over the selectivity of C 1 products in photochemical CO 2 reduction with the same catalyst, simply by changing the redox potential of the photosensitizer and/or the water concentration. Turnover numbers for CO generation with one of the photosensitizers under anhydrous conditions reached 85,000, one of the largest values reported to date. A combination of experimental results and DFT calculations show that control of the selectivity is achieved, in part, due to the interplay between regimes under kinetic or thermodynamic control. These regimes are largely dictated by the proton sources and the CO 2 reduction byproducts generated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Biohydrogen: prospects for industrial utilization and energy resiliency in rural communities

Biohydrogen (bioH 2 ) production in rural regions of the United States leveraged from existing biomass waste streams serves two extant needs: rural energy resiliency and decarbonization of heavy industry, including the production of ammonia and other H 2 -dependent nitrogenous products. We consider bioH 2 production using two different strategies: (1) dark fermentation (DF) and (2) anaerobic digestion followed by steam methane reforming of the biogas (AD-SMR). Production of bioH 2 from biomass waste streams is a potentially ‘greener’ pathway in comparison to natural gas-steam methane reforming (NG-SMR), especially as fugitive emissions from these wastes are avoided. It also provides a decarbonizing potential not found in water-splitting technologies. Based on literature on DF and AD of crop residues, woody biomass residues from forestry wastes, and wastewaters containing fats, oils, and grease (FOG), we outline scenarios for bioH 2 production and displacement of fossil fuel derived methane. Finally, we compare the costs and carbon intensity (CI) of bioH 2 production with those of other H 2 production pathways.

08 HYDROGEN↗