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DOE OSTI2022

Metabolomics Analysis of Bacterial Pathogen Burkholderia thailandensis and Mammalian Host Cells in Co-culture

The Tier 1 HHS/USDA Select Agent Burkholderia pseudomallei is a bacterial pathogen that is highly virulent when introduced into the respiratory tract and intrinsically resistant to many antibiotics. Transcriptomic- and proteomic-based methodologies have been used to investigate mechanisms of virulence employed by B. pseudomallei and Burkholderia thailandensis, a convenient surrogate; however, analysis of the pathogen and host metabolomes during infection is lacking. Changes in the metabolites produced can be a result of altered gene expression and/or post-transcriptional processes. Thus, metabolomics complements transcriptomics and proteomics by providing a chemical readout of a biological phenotype, which serves as a snapshot of an organism’s physiological state. However, the poor signal from bacterial metabolites in the context of infection poses a challenge in their detection and robust annotation. In this work, we coupled mammalian cell culture-based metabolomics with feature-based molecular networking of mono- and co-cultures to annotate the pathogen’s secondary metabolome during infection of mammalian cells. These methods enabled us to identify several key secondary metabolites produced by B. thailandensis during infection of airway epithelial and macrophage cell lines. Additionally, the use of in silico approaches provided insights into shifts in host biochemical pathways relevant to defense against infection. Using chemical class enrichment analysis, for example, we identified changes in a number of host-derived compounds including immune lipids such as prostaglandins, which were detected exclusively upon pathogen challenge. Taken together, our findings indicate that co-culture of B. thailandensis with mammalian cells alters the metabolome of both pathogen and host and provides a new dimension of information for in-depth analysis of the host–pathogen interactions underlying Burkholderia infection.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Transcriptome and metabolome integration in sugarcane through culm development

Abstract Sugarcane (Saccharum sp.) is a tropical and subtropical C4 plant with a high photosynthetic and carbon assimilation efficiency that stores sucrose. Culm biomass is also composed of bagasse fibre, a by‐product of the sugarcane industry. This high‐yielding grass, high in sucrose and lignocellulosic biomass, is considered an optimal feedstock as an alternative to fossil fuels and to produce a broad range of high‐value biomaterials. The ideal sugarcane production system would optimise the relative production of sugar and these new products. Multi‐omics correlation analysis was used to generate a global view of the essential metabolic pathways identifying critical genes involved in carbon partitioning during different stages of development. This research employed an unprecedented metabolic and transcriptomic dataset of 360 samples from a selection of 1440 culms of 24 genotypes at five different development stages. Chemical composition and metabolome analysis showed an increase through the culm development of lignin, sucrose, carbon, and amino acids such as aspartic acid, serine, alanine, methionine, threonine 3‐cyano‐L‐alanine, and citric acid. Transcriptome analysis revealed functionalities such as transcription, nucleotide transport and metabolism, and the biosynthesis of amino acids that are highly activated during the immature stage and highly down‐regulated during the most mature age.

Perlo, Virginie↗

DOE OSTI2021

Carbon‐Neutral Pathways for the United States

Abstract The Intergovernmental Panel on Climate Change (IPCC) Special Report on Global Warming of 1.5°C points to the need for carbon neutrality by mid‐century. Achieving this in the United States in only 30 years will be challenging, and practical pathways detailing the technologies, infrastructure, costs, and tradeoffs involved are needed. Modeling the entire U.S. energy and industrial system with new analysis tools that capture synergies not represented in sector‐specific or integrated assessment models, we created multiple pathways to net zero and net negative CO 2 emissions by 2050. They met all forecast U.S. energy needs at a net cost of 0.2–1.2% of GDP in 2050, using only commercial or near‐commercial technologies, and requiring no early retirement of existing infrastructure. Pathways with constraints on consumer behavior, land use, biomass use, and technology choices (e.g., no nuclear) met the target but at higher cost. All pathways employed four basic strategies: energy efficiency, decarbonized electricity, electrification, and carbon capture. Least‐cost pathways were based on >80% wind and solar electricity plus thermal generation for reliability. A 100% renewable primary energy system was feasible but had higher cost and land use. We found multiple feasible options for supplying low‐carbon fuels for non‐electrifiable end uses in industry, freight, and aviation, which were not required in bulk until after 2035. In the next decade, the actions required in all pathways were similar: expand renewable capacity 3.5 fold, retire coal, maintain existing gas generating capacity, and increase electric vehicle and heat pump sales to >50% of market share. This study provides a playbook for carbon neutrality policy with concrete near‐term priorities.

Williams, James H.↗

DOE OSTI2021

An Improved CRISPR Interference Tool to Engineer Rhodococcus opacus

Rhodococcus opacus is a non-model bacterium that is well suited for valorizing lignin. Despite recent advances in our systems-level understanding of its versatile metabolism, studies of its gene functions at a single gene level are still lagging. Elucidating gene functions in non-model organisms is challenging due to limited genetic engineering tools that are convenient to use. To address this issue, we developed a simple gene repression system based on CRISPR interference (CRISPRi). This gene repression system uses a T 7 RNA polymerase system to express a small guide RNA, demonstrating improved repression compared to the previously demonstrated CRISPRi system (i.e., the maximum repression efficiency improved from 58% to 85%). Additionally, our cloning strategy allows for building multiple CRISPRi plasmids in parallel without any PCR step, facilitating the engineering of this GC-rich organism. Using the improved CRISPRi system, we confirmed the annotated roles of four metabolic pathway genes, which had been identified by our previous transcriptomic analysis to be related to the consumption of benzoate, vanillate, catechol, and acetate. Furthermore, we showed our tool’s utility by demonstrating the inducible accumulation of muconate that is a precursor of adipic acid, an important monomer for nylon production. While the maximum muconate yield obtained using our tool was 30% of the yield obtained using gene knockout, our tool showed its inducibility and partial repressibility. In conclusion, our CRISPRi tool will be useful to facilitate functional studies of this non-model organism and engineer this promising microbial chassis for lignin valorization.

09 BIOMASS FUELS↗

DOE OSTI2022

Metabolome and RNA-seq Analysis of Responses to Nitrogen Deprivation and Resupply in Tea Plant (Camellia sinensis) Roots

Nitrogen (N) is an important contributor in regulating plant growth and development as well as secondary metabolites synthesis, so as to promote the formation of tea quality and flavor. Theanine, polyphenols, and caffeine are important secondary metabolites in tea plant. In this study, the responses of Camellia sinensis roots to N deprivation and resupply were investigated by metabolome and RNA-seq analysis. N deficiency induced content increase for most amino acids (AAs) and reduction for the remaining AAs, polyphenols, and caffeine. After N recovery, the decreased AAs and polyphenols showed a varying degree of recovery in content, but caffeine did not. Meanwhile, theanine increased in content, but its related synthetic genes were down-regulated, probably due to coordination of the whole N starvation regulatory network. Flavonoids-related pathways were relatively active following N stress according to KEGG enrichment analysis. Gene co-expression analysis revealed TCS2 , AMT1;1 , TAT2 , TS , and GOGAT as key genes, and TFs like MYB, bHLH, and NAC were also actively involved in N stress responses in C. sinensis roots. These findings facilitate the understanding of the molecular mechanism of N regulation in tea roots and provide genetic reference for improving N use efficiency in tea plant.

Xu, Wenluan↗

DOE OSTI2025

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Technoeconomic and Life Cycle Analysis of Synthetic Methanol Production from Hydrogen and Industrial Byproduct CO 2

Here CO 2 capture and utilization provides an alternative pathway for low-carbon hydrocarbon production. Given the ample supply of high-purity CO 2 emitted from ethanol and ammonia plants, this study conducted technoeconomic analysis and environmental life cycle analysis of several systems: integrated methanol-ethanol coproduction, integrated methanol-ammonia coproduction, and stand-alone methanol production systems, using CO 2 feedstock from ethanol plants, ammonia plants, and general market CO 2 supply. The cradle-to-grave greenhouse gas emissions of methanol produced from the stand-alone methanol, integrated methanol-ethanol, and integrated methanol-ammonia systems are 13.6, 37.9, and 84.6 g CO 2 -equiv/MJ, respectively, compared to 91.5 g CO 2 -equiv/MJ of conventional methanol produced from natural gas. The minimum fuel selling price (MFSP) of methanol ($\$0.61-0.64$/kg) is 61-68% higher than the average market methanol price of $\$0.38$/kg, when using a Department of Energy target renewable hydrogen production price of $\$2.0$/kg. The methanol price increases to $\$1.24-1.28$/kg when the hydrogen price is $\$5.0$/kg. Without CO 2 abatement credits, the H 2 price needs to be within $\$0.77-0.95$/kg for the MFSP of methanol to equal the average methanol market price. With a CO 2 credit of $\$35$/MT according to tax credit per metric ton of CO 2 captured and used, the methanol price is reduced to $\$0.56-0.59$/kg.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Pathways for decarbonization of the buildings sector in Ukraine

The paper focuses on Ukraine’s intention to achieve a two-thirds reduction in buildings’ energy consumption for heating and cooling by 2050, concurrently aiming for net zero greenhouse gas emissions and heightened energy security. Here, the study examines the outcomes of retrofitting existing residential, commercial, and public buildings with highly efficient materials, improving construction standards, and transitioning to advanced heating systems. However, Russia’s invasion in 2022 inflicted substantial damage, prompting a shift from retrofit and decarbonization to reconstruction. The Ukrainian government’s Reconstruction Plan emphasizes clean, sustainable, and resilient energy systems. The study employs energy system and integrated assessment models (TIMES-Ukraine and GCAM-Ukraine) to explore scenarios taking into consideration the war, reconstruction, and a net zero CO 2 pathway. Using two models allowed the inter-model comparison. The analysis addresses vital questions on energy resiliency measures and the compounding effects of decarbonization. Findings indicate that Ukraine’s energy goals can be met through strategic retrofitting and economy-wide decarbonization, emphasizing the importance of low-carbon alternatives like district heating with renewable sources. Electrification with renewables and fuel-switching emerges as crucial for achieving building decarbonization. The study offers valuable insights into navigating energy challenges amidst the war and outlines a pathway for Ukraine’s sustainable energy future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

DNS Of the ignition process of n-heptane/air premixed combustion with low-temperature chemistry in turbulent boundary layer

In the present work, three-dimensional direct numerical simulation (DNS) of n-heptane/air premixed combustion in turbulent boundary layer was performed to explore the near-wall ignition process with low -temperature chemistry. A reduced chemical mechanism with 58 species and 387 elementary reactions for n-heptane combustion was used in the DNS. The general characteristics of the ignition process near the wall were examined. Here, it was found that low-temperature ignition (LTI) dominates the upstream region, and high -temperature ignition (HTI) appears in the downstream region. The ignition process and the low-temperature chemistry pathways of the DNS are compared with those of a corresponding laminar case. It was found that the ignition process was affected by turbulence, which results in thickened reaction zones. However, the carbon flow analysis of low-temperature chemistry showed that turbulence rarely affects the low-temperature chemistry pathway. The combustion modes of various regions were scrutinized based on the budget terms of species transport equations and the chemical explosion mode analysis (CEMA). It was shown that the reaction term of RO 2 is significant during the LTI process of the upstream region, and the reaction terms of CH 2 O and CO 2 are evident in the downstream region, indicating the occurrence of HTI. It was also shown that auto-ignition is dominant in the upstream region. With increasing streamwise distance, the contribution of flame propagation increases, which takes over that of auto-ignition in the near-wall region.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2006

Microgravity and Immunity: Changes in Lymphocyte Gene Expression

Earlier studies had shown that modeled and true microgravity (MG) cause multiple direct effects on human lymphocytes. MG inhibits lymphocyte locomotion, suppresses polyclonal and antigen-specific activation, affects signal transduction mechanisms, as well as activation-induced apoptosis. In this study we assessed changes in gene expression associated with lymphocyte exposure to microgravity in an attempt to identify microgravity-sensitive genes (MGSG) in general and specifically those genes that might be responsible for the functional and structural changes observed earlier. Two sets of experiments targeting different goals were conducted. In the first set, T-lymphocytes from normal donors were activated with antiCD3 and IL2 and then cultured in 1g (static) and modeled MG (MMG) conditions (Rotating Wall Vessel bioreactor) for 24 hours. This setting allowed searching for MGSG by comparison of gene expression patterns in zero and 1 g gravity. In the second set - activated T-cells after culturing for 24 hours in 1g and MMG were exposed three hours before harvesting to a secondary activation stimulus (PHA) thus triggering the apoptotic pathway. Total RNA was extracted using the RNeasy isolation kit (Qiagen, Valencia, CA). Affymetrix Gene Chips (U133A), allowing testing for 18,400 human genes, were used for microarray analysis. In the first set of experiments MMG exposure resulted in altered expression of 89 genes, 10 of them were up-regulated and 79 down-regulated. In the second set, changes in expression were revealed in 85 genes, 20 were up-regulated and 65 were down-regulated. The analysis revealed that significant numbers of MGS genes are associated with signal transduction and apoptotic pathways. Interestingly, the majority of genes that responded by up- or down-regulation in the alternative sets of experiments were not the same, possibly reflecting different functional states of the examined T-lymphocyte populations. The responder genes (MGSG) might play an essential role in adaptation to MG and/or be responsible for pathologic changes encountered in Space and thus represent potential targets for molecular-based countermeasures

Risin, D.↗

DOE OSTI2020

Mechanistic understanding of catalytic conversion of ethanol to 1-butene over 2D-pillared MFI zeolite

Ethanol is an important C2 platform molecule for producing value-added chemicals and distillate hydrocarbon fuels (e.g., jet and diesel). Among these, catalytic upgrading of ethanol to butenes can generate valuable commodity chemicals (e.g., 1-butene) and provide C4 olefin intermediates that can be further upgraded to jet/diesel fuels. 2D zeolites offer hierarchical mesoporous structures, leading to improved mass transport and reduced diffusion length, which can help to address the coking challenges faced by ethanol conversion to hydrocarbons over 3D zeolites. In this study, we investigate the acid-catalyzed conversion of ethanol to 1-butene over the Brønsted acid sites (BAS) in 2D-pillared MFI zeolite (2D-PMFI) using ab initio molecular dynamics (AIMD) simulations, in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and calorimetric measurements. A detailed thermodynamic analysis, using quasi-harmonic approximation (QHA), on the Gibbs free energy pathway of ethanol conversion shows that the consideration of entropy is critical to accurately capture the detailed thermodynamic profiles. The formation of bulky ethoxy-ethene complex is found to be a potential rate-determining step (RDS), proceeding via stepwise mechanism. The reactivity of 2D-PMFI can be further tuned by manipulating RDS through a careful control of number of BAS and operating temperatures. The accuracy of computational model is confirmed through the comparison of calculated vibrational density of states (VDOS) against the experimental DRIFTS measurements. Overall, our study provides mechanistic insights into ethanol upgrading over the 2D-PMFI and shows the importance of evaluating entropic effects in such confined system.

Ethanol conversion, 2D-pillared zeolite, MFI, Anha↗

DOE OSTI2025

Evaluating the limitations of Bayesian metabolic control analysis

AbstractBayesian Metabolic Control Analysis (BMCA) has emerged as a promising framework for inferring metabolic control coefficients in data-limited scenarios by integrating Bayesian inference with linlog rate laws. However, its predictive accuracy and limitations remain underexplored. This study systematically evaluates BMCA’s ability to infer elasticity values, flux control coefficients (FCCs), and concentration control coefficients (CCCs) under varying data availability conditions using three synthetic metabolic network models. Our findings highlight the strengths and weaknesses of BMCA, guiding its application in metabolic engineering and emphasizing the need for methodological refinements.Author summaryUnderstanding how enzymes control metabolic pathways is crucial for optimizing biomanufacturing and synthetic biology applications. Bayesian Metabolic Control Analysis (BMCA) is a promising computational method that integrates Bayesian inference with metabolic control analysis to estimate key control parameters, even in cases with limited experimental data. However, the accuracy and limitations of BMCA remain unclear. In this study, we systematically evaluate BMCA using three synthetic metabolic networks to determine how different types of physiological data impact its predictive performance. We find that BMCA requires flux and enzyme concentration data for accurate predictions, while external metabolite concentrations contribute little. Additionally, BMCA fails to predict elasticity values beyond a magnitude of 1.5 and reliably infer allosteric regulation, even when strong regulatory interactions exist. In addition, BMCA does not accurately rank metabolic control points, which may limit its utility in identifying key enzymes in engineered pathways. Our work provides practical insights into when and how BMCA can be applied, guiding future research in metabolic modeling and control analysis.

Shin, Janis (ORCID:0000000216572455)↗

DOE OSTI2025

Biosensor-driven strain engineering reveals key cellular processes for maximizing isoprenol production in Pseudomonas putida

Synthetic biology generates vast combinatorial designs, yet high-throughput analytical methods to screen them are poorly matched to interrogate this search space. We address this challenge by developing a biosensor-driven, growth-coupled selection strategy in Pseudomonas putida for isoprenol, a potential aviation fuel precursor. We found and characterized a noncanonical signaling pathway, revealing a functional and physical complex between a hybrid histidine kinase and an alcohol dehydrogenase, whose activity is tuned by heterodimerization. Leveraging this biosensor in a pooled CRISPRi library selection, we identified key host limitations. Iterative combinatorial strain engineering derived from these hits yielded a 36-fold titer increase to ~900 milligrams per liter. Integrated omics analysis revealed that metabolic rewiring toward amino acid catabolism was crucial for this improvement. This observation was found to be beneficial by technoeconomic analysis. Our modular workflow provides a powerful strategy for optimizing complex heterologous pathways and uncovering emergent host biology.

CRISPRi↗

DOE OSTI2025

Experimental and fuel-surrogates modeling study of the high-pressure pyrolysis of specialty cetane number fuels: implications for fall-off in ethylene unimolecular dissociation

Single pulse shock tube experiments were conducted at 50 atm nominal pressure and 4 ms nominal reaction time over a temperature range of 900–1800 K, to study the pyrolysis speciation of a multi-component jet fuel, F-24, and six cetane number (CN) specialty fuels - CN30, CN35, CN40, CN45, CN50, and CN55. Gas chromatography (GC) was used to qualitatively and quantitatively analyze the post shock gases. The relationship between the formation of key pyrolysis species and the chemically controlled combustion propensity as reflected by the cetane number of each fuel was examined. A surrogate-based mechanism from the CRECK Modelling Group and chemical-functional group based optimized surrogates (CFGO) were used to simulate the pyrolysis speciation results. The model was able to capture the chemistry of most species except two important pyrolysis intermediates – ethylene and acetylene. Chemical kinetic analyses were performed to identify the important reactions which affect the chemistry of these species; however, the rate parameters of critical reactions were found to be unsuitable for simulating the present high-pressure studies. Here, to address this unsuitability, a theory-based fall-off analysis for three reactions representing the decomposition of ethylene and subsequent formation of acetylene was performed, and these are included in an updated version of the CRECK mechanism. This update resolves discrepancies between the experimental results and simulations for ethylene and acetylene. Reaction flux analyses using the updated surrogate model were also performed to identify the important reaction pathways responsible for the formation of crucial species and to provide an analysis of the chemistry of complex multi-component fuel systems. The fundamental reactions responsible for driving pyrolysis chemistry were greatly influenced by the chemical functional groups present in these fuels. In addition to updating the rate parameters of specific reactions to improve modeling, this study also emphasizes the effectiveness of the fuel-surrogate approach, where surrogates representing the chemical functional group composition of the parent fuel serve as a valuable tool for predicting the combustion chemistry of novel fuels.

Chemical Kinetics↗

DOE OSTI2026

What Is the Best Use of Biomass? A Harmonized LCA-TEA Framework Quantifying Economic and Environmental Metrics for Bioenergy Pathways

Bioresource utilization is expected to play a pivotal role in complementing existing energy pathways and enhancing energy resilience. This study develops a harmonized life cycle assessment (LCA) and techno-economic analysis (TEA) framework to evaluate the greenhouse gas (GHG) reduction potential, minimum fuel selling price (MFSP), and marginal abatement cost (MAC) of bioenergy pathways. We analyze 19 pathways, including liquid biofuels (via catalytic fast pyrolysis, Fischer–Tropsch synthesis, and gasification), bioelectricity, and biomass-to-hydrogen, with and without carbon capture and storage (CCS). The GHG impacts are assessed using the GREET 2022 model, while U.S. Billion-Ton 2016 biomass availability projections are used to estimate scale-up potential. Additionally, we evaluate the influence of a low-carbon electricity grid on pathway performance. Our results show that CCS implementation reduces carbon intensities (CI) to net-negative values for several pathways, with MAC ranging from $\$$32 to $\$$600 per metric ton (MT) CO2e avoided. Bioelectricity pathways with CCS achieve the lowest MAC ($\$$32–$\$$68/tCO2e), while liquid biofuels and hydrogen pathways remain critical for hard-to-abate sectors like aviation and heavy industry. Pathways with net-positive electricity demand benefit from a low-carbon grid, whereas those co-producing electricity experience increased MAC under lower electricity grid CI scenarios. This open-source framework provides a robust tool for harmonized evaluation of bioenergy pathways, enabling policymakers and stakeholders to identify cost-effective strategies for biomass utilization and carbon abatement at scale. The findings underscore the importance of CCS, co-product credits, and feedstock availability in optimizing bioenergy deployment for a low-carbon economy.

09 BIOMASS FUELS↗

DOE OSTI2024

The role of the iron and steel sector in achieving net zero U.S. CO 2 emissions by 2050

The U.S. steel sector is a hard-to-abate sector because of its heavy dependence on fossil fuels and its high capital requirements. In 2015, the sector was one of the major carbon emitters, contributing 10 % of the U.S. industrial CO 2 emissions. The ability to decarbonize the U.S. iron and steel sector directly affects the ability of the U.S. to achieve economy-wide net zero CO 2 by 2050. In this paper, we use the Global Change Analysis Model (GCAM) to analyze different U.S. steel sector decarbonization pathways under varying technology, policy, and demand futures. These pathways provide insights on how various low-carbon steelmaking technologies such as those using carbon capture and storage (CCS), hydrogen, or scrap could help reduce U.S. steel emissions by mid-century. In our primary decarbonization pathway, we find that nearly all of the conventional fossil-based steelmaking capacity is fully integrated with CCS by 2050. However, without CCS availability, almost all of the conventional fossil-based steelmaking is phased-out by 2050 and is replaced by hydrogen-based production. Scrap-based production continues to remain vital across both of these decarbonization pathways. Furthermore, we find that demand reduction could help reduce the required levels of CCS and hydrogen-based production in the decarbonization pathways. Implementation of advanced energy efficiency measures could help substantially reduce the sector's energy usage. Finally, we observe that addressing the embodied carbon transfer associated with steel imports will be crucial for fully decarbonizing the U.S. steel sector.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Conceptual Design and Rationale for a New Agrivoltaics Concept: Pastured-Raised Rabbits and Solar Farming

Land-use conflicts created by the growth of solar photovoltaics (PV) can be mitigated by applying the concept of agrivoltaics, that is, the co-development of land for both PV and agricultural purposes, to commercial-scale solar installations. In this study, we present a conceptual design for a novel agrivoltaic system based on pasture-fed rabbit farming and provide the technical, environmental and economic analyses to demonstrate the viability of the concept. Included in our analysis are the economic advantages to the PV operator of grazing rabbits at a density sufficient to control vegetative growth, thus reducing the economic and environmental costs of mowing; the dual-revenue stream from the sale of both rabbits and electricity, contrasted with estimates of the capital-investment costs for rabbits co-located with, and also independent of, PV; and the economic value to the rabbit farmer of higher colony-growth rates (made possible by the shading and predator protection provided by the PV arrays and of reduced fencing costs, which are the largest capital cost, by being able to leverage the PV systems for rabbit fencing. We also provide an environmental analysis that suggests that rabbit-PV farming is a pathway to a measurable reduction in agriculturally-generated greenhouse-gas emissions. Here, our calculations indicate that the co-location of solar and rabbit farms is a viable form of agrivoltaics, increasing overall site revenue by 2.5%-24.0% above projected electricity revenue depending on location and rental/ownership of rabbits, while providing a high-value agricultural product that, on a per weight basis, has significantly less environmental impact than cattle.

14 SOLAR ENERGY↗

DOE OSTI2025

Enhancing supply resilience for critical materials: case study of gallium supply in the United States

Accelerating energy technology development will increase demand for critical raw materials, such as gallium, that enable clean energy technologies. Processing of gallium is concentrated in mainland China (98 % of global production in 2023), resulting in high supply risks for importing countries. To investigate pathways for more resilient supply, we develop a material flow analysis and apply it to the United States, showing the impacts of future domestic primary raw material production and end-of-life (EoL) product recycling on reducing import reliance of raw gallium metal. We complement this analysis with a techno-economic assessment of North American gallium production costs under various demand growth scenarios. Our results indicate that sufficient domestic feedstocks exist to meet U.S. demand under most scenarios by 2035, while EoL recycling can supply up to 50 % under a low-demand growth scenario. Domestic primary production shows significant cost advantages over gallium recycling.

Cost analysis↗