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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Comparison of Routes of Administration, Frequency, and Duration of Favipiravir Treatment in Mouse and Guinea Pig Models of Ebola Virus Disease

Favipiravir is a ribonucleoside analogue that has been explored as a therapeutic for the treatment of Ebola Virus Disease (EVD). Promising data from rodent models has informed nonhuman primate trials, as well as evaluation in patients during the 2013–2016 West African EVD outbreak of favipiravir treatment. However, mixed results from these studies hindered regulatory approval of favipiravir for the indication of EVD. This study examined the influence of route of administration, duration of treatment, and treatment schedule of favipiravir in immune competent mouse and guinea pig models using rodent-adapted Zaire ebolavirus (EBOV). A dose of 300 mg/kg/day of favipiravir with an 8-day treatment was found to be fully effective at preventing lethal EVD-like disease in BALB/c mice regardless of route of administration (oral, intraperitoneal, or subcutaneous) or whether it was provided as a once-daily dose or a twice-daily split dose. Preclinical data generated in guinea pigs demonstrates that an 8-day treatment of 300 mg/kg/day of favipiravir reduces mortality following EBOV challenge regardless of route of treatment or duration of treatments for 8, 11, or 15 days. This work supports the future translational development of favipiravir as an EVD therapeutic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

An interpretable model of pre-mRNA splicing for animal and plant genes

Pre-mRNA splicing is a fundamental step in gene expression, conserved across eukaryotes, in which the spliceosome recognizes motifs at the 3' and 5' splice sites (SSs), excises introns, and ligates exons. SS recognition and pairing is often influenced by protein splicing factors (SFs) that bind to splicing regulatory elements (SREs). Here, we describe SMsplice, a fully interpretable model of pre-mRNA splicing that combines models of core SS motifs, SREs, and exonic and intronic length preferences. We learn models that predict SS locations with 83 to 86% accuracy in fish, insects, and plants and about 70% in mammals. Learned SRE motifs include both known SF binding motifs and unfamiliar motifs, and both motif classes are supported by genetic analyses. Our comparisons across species highlight similarities between non-mammals, increased reliance on intronic SREs in plant splicing, and a greater reliance on SREs in mammalian splicing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Concept Study of Robotic Camera-Based Foreign Object Detection for EV Wireless Charging

Wireless charging of an electric vehicle (EV) is an emerging charging technology promising convenient, autonomous, and highly efficient EV charging without requiring heavy gauge cables. However, due to the strong electromagnetic field created by this process that surrounds the wireless charger, the presence of foreign objects can detrimentally interact with it, thus affecting wireless power transfer (WPT) performance or leading to harmful and unwanted safety risks. This paper presents the results for a concept study on a robotic camera-based foreign object detection (FOD) system, as a supplement to the industry-existing overlapped FOD coil array method, for EV wireless charging. A Raspberry PI 4 control board and compatible Raspberry PI Camera Module 2 are used to implement camera-based object detection. The FOD program was developed using a state-of-the-art deep learning object detection model with the OpenCV and Pytorch library and is compatible with camera module hardware. A dry-run test with Raspberry PI and a camera module was conducted and the preliminary FOD function was verified. The feasibility assessment is also validated by comparing the performance of five existing state-of-the-art deep learning object detection models for vehicles, animals, persons, and metals subsets, respectively. Satisfactory performance on the benchmark datasets is observed by the tests, but further improvements are needed in future work when detecting small-sized metallic objects. A programable robotic car is also under development as ongoing work for carrying the Raspberry PI and camera module while moving for the maintenance process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Finch: Toxicity Dose Response Curve Prediction of Chemical Compounds and Mixtures

A paradigm shift in chemical risk assessment is emphasizing mixture testing over single compound analysis, eliminating animal testing, and adopting advanced modeling approaches to understand mixture activity profiles. However, existing computational models largely focus on single chemicals, with few effective solutions for modeling complex mixtures that account for synergistic or antagonistic effects and multiple Modes of Action (MoA). Conventional methods like concentration addition (CA) and independent action (IA) are insufficient for this task as they are designed for simplistic interactions and struggle to account for the dynamic and multifaceted nature of chemical mixtures, such as overlapping MoA and non-linear interactions. Finch offers a novel approach utilizing deep learning (DL) embeddings and multi-task quantitative structure-activity relationship (QSAR) models to improve chemical exposure prediction. By leveraging molecular descriptors, physiochemical properties, and large language model (LLM) embeddings from SMILES inputs, Finch preserves critical information in a latent space thereby enhancing predictive accuracy. The multi-task learning aspect of Finch is highly advantageous, as it simultaneously optimizes multiple loss functions, leveraging all available data across tasks to develop generalized representations that effectively capture complex ingredient interactions within mixtures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

CRCNS US-France Research Proposal: Collaborative Research: Encoding reward expectation in Drosophilia

The fruit fly Drosophila melanogaster has been a valuable model for investigating the genetic and neural bases that underlie learning and memory. Early and most current studies use basic behavior conditioning protocols to study learning in controlled laboratory settings. More recently, the ability to transgenically manipulate many of the brain neurons in the fruit fly with exquisite specificity, and the recent knowledge of the synaptic ‘connectome’ of the fruit fly brain, makes these animals almost unique as a comprehensive model for studies of learning, memory and motivated behavior. In fact, the connectome has revealed many types of new connections that had until now been overlooked. Within this context, the thesis of this proposal is that studies of learning and memory will be greatly enhanced by using more sophisticated means for evaluating memory representations, such as have been developed in vertebrates, and combining those studies with information from the connectome guided by computational modelling. We propose to push beyond the boundaries of existing conditioning protocols for fruit flies to investigate more complex memory representations. In particular, we will investigate the function of reinforcement pathways in relation to the absence of expected reinforcement. More specifically, we propose a series of experiments designed to investigate the memory representations in fruit flies when an expected consequence of a Conditioned Stimulus (CS) fails to occur. Although studies have evaluated how this failure can establish extinction memory for the CS, our studies will go beyond studying extinction. Specifically, we predict that in Drosophila when a CS is associated with a failed expectation of an appetitive food reinforcement it will acquire aversive value, and vice versa for a failed expectation of an aversive reinforcer. We combine these studies with manipulations of reinforcement pathways in the CNS inspired from the connectome, iteratively knitted in with established computational models. Intellectual Merit: The concept of reinforcement expectation and incentive contrast have been influential in the development of studies of associative learning in mammals. These questions are particularly challenging to answer in vertebrates because they require exquisite cellular, temporal, and genetic specificity of experimental manipulations. The recent development of work with identified neurons and their connectomes makes the larval and adult fly brains ripe as models for pushing our understanding of neural bases for these higher- order conditioning phenomena. Broader Impacts: Public health: These analyses and the conceptual framework of prediction error processing underlying them have a profound impact on our understanding of reinforcement-related behavior in humans, including monetary rewards and the mnemonic consequences of traumatic experiences, and for pathologies of the dopamine reinforcement system. Educational: This project will provide interdisciplinary training for postdoctoral researchers, Ph.D. and undergraduate students. The PIs will act as co-supervisors or mentors of students working in the different labs via face-to-face and internet-based technologies. We will also work with ASU’s award-winning Ask- A-Biologist program. This is an online science program designed to enrich the learning experiences of students of all ages and to provide classroom material for use by K-12 teachers. We will develop an extension of a game developed under a prior NSF award, and the new game will include modules to teach K-12 students about how insects learn. We will also integrate into the AAB site a program developed by a collaborator (B Gerber) at the Leibniz Institut für Neurobiologie, Magdeburg, and now in use in schools in Germany, to teach K-12 students how to train animals using the fruit fly larval learning paradigm. Underrepresented groups: All PIs will work with their university offices of Academic Diversity and Equal Opportunity for reaching underrepresented students.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Identification and characterization of a skin microbiome on Caenorhabditis elegans suggests environmental microbes confer cuticle protection

ABSTRACT In the wild, C. elegans are emersed in environments teeming with a veritable menagerie of microorganisms. The C. elegans cuticular surface serves as a barrier and first point of contact with their microbial environments. In this study, we identify microbes from C. elegans natural habitats that associate with its cuticle, constituting a simple “skin microbiome.” We rear our animals on a modified CeMbio, mCeMbio, a consortium of ecologically relevant microbes. We first combine standard microbiological methods with an adapted micro skin-swabbing tool to describe the skin-resident bacteria on the C. elegans surface. Furthermore, we conduct 16S rRNA gene sequencing studies to identify relative shifts in the proportion of mCeMbio bacteria upon surface-sterilization, implying distinct skin- and gut-microbiomes. We find that some strains of bacteria, including Enterobacter sp. JUb101 , are primarily found on the nematode skin, while others like Stenotrophomonas indicatrix JUb19 and Ochrobactrum vermis MYb71 are predominantly found in the animal’s gut. Finally, we show that this skin microbiome promotes host cuticle integrity in harsh environments. Together, we identify a skin microbiome for the well-studied nematode model and propose its value in conferring host fitness advantages in naturalized contexts. IMPORTANCE The genetic model organism C. elegans has recently emerged as a tool for understanding host–microbiome interactions. Nearly all of these studies either focus on pathogenic or gut-resident microbes. Little is known about the existence of native, nonpathogenic skin microbes or their function. We demonstrate that members of a modified C. elegans model microbiome, mCeMbio, can adhere to the animal's cuticle and confer protection from noxious environments. We combine a novel micro-swab tool, the first 16S microbial sequencing data from relatively unperturbed C. elegans , and physiological assays to demonstrate microbially mediated protection of the skin. This work serves as a foundation to explore wild C. elegans skin microbiomes and use C. elegans as a model for skin research.

16S RNA↗
DOE OSTI2024

Cell-Free Screening, Production and Animal Testing of a STI-Related Chlamydial Major Outer Membrane Protein Supported in Nanolipoproteins

Background: Vaccine development against Chlamydia, a prevalent sexually transmied infection (STI), is imperative due to its global public health impact. However, significant challenges arise in the production of effective subunit vaccines based on recombinant protein antigens, particularly with membrane proteins like the Major Outer Membrane Protein (MOMP). Methods: Cellfree protein synthesis (CFPS) technology is an aractive approach to address these challenges as a method of high-throughput membrane protein and protein complex production coupled with nanolipoprotein particles (NLPs). NLPs provide a supporting scaffold while allowing easy adjuvant addition during formulation. Over the last decade, we have been working toward the production and characterization of MOMP-NLP complexes for vaccine testing. Results: The work presented here highlights the expression and biophysical analyses, including transmission electron microscopy (TEM) and dynamic light scaering (DLS), which confirm the formation and functionality of MOMP-NLP complexes for use in animal studies. Moreover, immunization studies in preclinical models compare the past and present protective efficacy of MOMP-NLP formulations, particularly when co-adjuvanted with CpG and FSL1. Conclusion: Ex vivo assessments further highlight the immunomodulatory effects of MOMP-NLP vaccinations, emphasizing their potential to elicitrobust immune responses. However, further research is warranted to optimize vaccine formulations further, validate efficacy against Chlamydia trachomatis, and beer understand the underlying mechanisms of immune response.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Viral Dynamic Models During COVID‐19: Are We Ready for the Next Pandemic?

Mathematical models have been used for about 30 years to improve our understanding of virus-host interaction, in particular during chronic infections. During the COVID-19 pandemic, these models have been used to provide insights into the natural history of acute SARS-CoV-2 infection, optimize antiviral treatment strategies, understand factors associated with transmission, and optimize surveillance systems. The impact of modeling has been accelerated by the availability of unprecedented multidimensional immune data from animal and human systems, which enhanced partnerships between experimentalists and theorists and led to exciting new modeling and statistical developments. In this mini review, we examine the lessons learned from the COVID-19 pandemic and discuss the main insights provided by mathematical models of viral dynamics at the different stages of the outbreak. Although we focus on respiratory infection, we also consider the new areas for development in anticipation of future acute infections from new or reemerging pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Fundamentals of wildlife dosimetry and lessons learned from a decade of measuring external dose rates in the field

Methods for determining the radiation dose received by exposed biota require major improvements to reduce uncertainties and increase precision. We share our experiences in attempting to quantify external dose rates to free-ranging wildlife using GPS-coupled dosimetry methods. The manuscript is a primer on fundamental concepts in wildlife dosimetry in which the complexities of quantifying dose rates are highlighted, and lessons learned are presented based on research with wild boar and snakes at Fukushima, wolves at Chornobyl, and reindeer in Norway. GPS-coupled dosimeters produced empirical data to which numerical simulations of external dose using computer software were compared. Our data did not support a standing paradigm in risk analyses: Using averaged soil contaminant levels to model external dose rates conservatively overestimate the dose to individuals within a population. Following this paradigm will likely lead to misguided recommendations for risk management. The GPS-dosimetry data also demonstrated the critical importance of how modeled external dose rates are impacted by the scale at which contaminants are mapped. When contaminant mapping scales are coarse even detailed knowledge about each animal’s home range was inadequate to accurately predict external dose rates. Importantly, modeled external dose rates based on a single measurement at a trap site did not correlate to actual dose rates measured on free ranging animals. These findings provide empirical data to support published concerns about inadequate dosimetry in much of the published Chernobyl and Fukushima dose-effects research. Furthermore, our data indicate that a huge portion of that literature should be challenged, and that improper dosimetry remains a significant source of controversy in radiation dose-effect research.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

Hypophosphite Is a Naturally Occurring Selective Inhibitor of Syntrophic Methanogenesis

Microbial methanogenesis is a major contributor to global warming, and methane fluxes represent a loss of energy and electrons from industrial ecosystems. The chemical space of methane control strategies is still underexplored. Most known methanogenesis inhibitors target methanogenic archaeal enzymes. However, interference with the exchange of syntrophic electron carriers (H 2 or formate) in methanogenic systems presents an additional target for methane control. Here, we show that hypophosphite (H 2 PO 2 − ), an inorganic formate analogue, is a potent and selective inhibitor of syntrophic methanogenesis versus primary fermentation in rice field sediments and cattle rumens. Hypophosphite is also generally recognized as safe and relatively nontoxic to plants and animals. Genetic screens and physiological assays in the model methanogen Methanococcus maripaludis S2 implicate formate metabolism as the target of hypophosphite inhibition. Currently, there is no known biological pathway for anaerobic hypophosphite oxidation, and hypophosphite is stable in anoxic sediments for weeks to months. Given its widespread natural occurrence, we propose that hypophosphite may modulate the carbon cycle in natural environments. Taken together, our results suggest that hypophosphite could be used as a safe, inexpensive strategy for methane control in syntrophic methanogenic ecosystems.

chemical inhibitor↗
DOE OSTI2025

Costs of Exposure to Industrial Livestock Operations

Concentrated animal feeding operations, particularly hog and poultry farms, have expanded rapidly in North Carolina in recent decades. The air pollution and water contamination they generate cause many environmental and health problems for local communities. Using the universe of farm characteristics and housing transaction data in North Carolina, we recover hedonic estimates of property value impacts from exposure to these industrial livestock operations. Furthermore, our results show large and significant negative impacts on nearby home values, particularly when those properties depend on private wells.

Concentrated Animal Feeding Operation↗
DOE OSTI2024

Advancing stem cell technologies for conservation of wildlife biodiversity

ABSTRACT Wildlife biodiversity is essential for healthy, resilient and sustainable ecosystems. For biologists, this diversity also represents a treasure trove of genetic, molecular and developmental mechanisms that deepen our understanding of the origins and rules of life. However, the rapid decline in biodiversity reported recently foreshadows a potentially catastrophic collapse of many important ecosystems and the associated irreversible loss of many forms of life on our planet. Immediate action by conservationists of all stripes is required to avert this disaster. In this Spotlight, we draw together insights and proposals discussed at a recent workshop hosted by Revive & Restore, which gathered experts to discuss how stem cell technologies can support traditional conservation techniques and help protect animal biodiversity. We discuss reprogramming, in vitro gametogenesis, disease modelling and embryo modelling, and we highlight the prospects for leveraging stem cell technologies beyond mammalian species.

Developmental Biology↗
DOE OSTI2025

Pulsar Movement Animation and its Corresponding Signal Visualization for Timing Source

The global positioning system, widely used for synchronization in energy systems, faces vulnerabilities, while Pulsars—natural cosmic clocks—offer long-term stability as potential backup timing sources. Existing research lacks sufficient exploration of Pulsar signal animation under astrophysical factors, limiting practical applications. This study establishes a mathematical model based on the rotation dynamics of dual-beam Pulsars and implements dynamic signal visualization through MATLAB. The model dynamically illustrates the relative motion between Pulsar beams and observers via timeline calculations, beam intensity modeling, and rotation matrix derivation. A case study on the millisecond Pulsar J1939+2134 reveals that observer angles influence signal peak timing, while beam widths determine signal duration, highlighting the critical role of parameter calibration for timing accuracy. Open-source code and animation results are publicly shared, providing tools for interdisciplinary research. This study validates the feasibility of Pulsar-based timing in energy systems, offering new insights to enhance synchronization robustness.

Wu, Ori [ORNL] (ORCID:0000000326723410)↗
DOE OSTI2026

Acute wood smoke exposure is associated with cell-specific hippocampal transcriptomic responses in an accelerated ovarian failure mouse model

Background Wildfire events are increasing in frequency and intensity, and aging individuals demonstrate heightened biological susceptibility to air pollution exposures including increased risk of neurological sequelae. Declining ovarian hormones levels that occur with aging in females along with associated systemic physiological and inflammatory changes may contribute to increased cerebral vulnerability to air pollution, representing a potential but underexplored mechanism. Menopause and the menopausal transition represent a period of profound physiological change that affects cardiovascular, neurological, and immune health. Methods We tested whether peri-menopausal–like hormonal status amplifies hippocampal responses to acute wood smoke (WS) using an ovary-intact, 4-vinylcyclohexene diepoxide (VCD) model of moderate accelerated ovarian failure (AOF) in female C57BL/6 mice. Animals were exposed to HEPA-filtered air (FA) or WS for 4 h/day over 2 consecutive days (∼0.5 mg/m³). Exposure characterization confirmed a complex mixture of combustion products with significant levels of both trace metals and gas release during WS exposure. Results Spatial transcriptomics (10x Visium; n = 4 sections/group) with automated cell-type annotation identified astrocytes, GABAergic and glutamatergic neurons, oligodendrocytes, revealed cell type-specific transcriptional alterations following WS exposure. Distinct transcriptional patterns were observed across all identified neuronal and glial cell populations. Conclusion Together, these findings define a cell-type specific transcriptomic framework describing how WS exposure and ovarian hormone decline interact to influence hippocampal responses and identify potential cellular pathways relevant to hippocampal vulnerability.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2024

Disturbance of hibernating bats due to researchers entering caves to conduct hibernacula surveys

Estimating population changes of bats is important for their conservation. Population estimates of hibernating bats are often calculated by researchers entering hibernacula to count bats; however, the disturbance caused by these surveys can cause bats to arouse unnaturally, fly, and lose body mass. We conducted 17 hibernacula surveys in 9 caves from 2013 to 2018 and used acoustic detectors to document cave-exiting bats the night following our surveys. We predicted that cave-exiting flights (i.e., bats flying out and then back into caves) of Townsend’s big-eared bats (Corynorhinus townsendii) and western small-footed myotis (Myotis ciliolabrum) would be higher the night following hibernacula surveys than on nights following no surveys. Those two species, however, did not fly out of caves more than predicted the night following 82% of surveys. Nonetheless, the activity of bats flying out of caves following surveys was related to a disturbance factor (i.e., number of researchers × total time in a cave). We produced a parsimonious model for predicting the probability of Townsend’s big-eared bats flying out of caves as a function of disturbance factor and ambient temperature. That model can be used to help biologists plan for the number of researchers, and the length of time those individuals are in a cave to minimize disturbing bats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Drug-induced kidney injury: challenges and opportunities

Abstract Drug-induced kidney injury (DIKI) is a frequently reported adverse event, associated with acute kidney injury, chronic kidney disease, and end-stage renal failure. Prospective cohort studies on acute injuries suggest a frequency of around 14%–26% in adult populations and a significant concern in pediatrics with a frequency of 16% being attributed to a drug. In drug discovery and development, renal injury accounts for 8 and 9% of preclinical and clinical failures, respectively, impacting multiple therapeutic areas. Currently, the standard biomarkers for identifying DIKI are serum creatinine and blood urea nitrogen. However, both markers lack the sensitivity and specificity to detect nephrotoxicity prior to a significant loss of renal function. Consequently, there is a pressing need for the development of alternative methods to reliably predict drug-induced kidney injury (DIKI) in early drug discovery. In this article, we discuss various aspects of DIKI and how it is assessed in preclinical models and in the clinical setting, including the challenges posed by translating animal data to humans. We then examine the urinary biomarkers accepted by both the US Food and Drug Administration (FDA) and the European Medicines Agency for monitoring DIKI in preclinical studies and on a case-by-case basis in clinical trials. We also review new approach methodologies (NAMs) and how they may assist in developing novel biomarkers for DIKI that can be used earlier in drug discovery and development.

Connor, Skylar (ORCID:0000000233479180)↗
DOE OSTI2024

Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS

The Marine Algae Industrialization Consortium (MAGIC) was formed to address pressing challenges in the commercialization of microalgae as a source of biofuel. The “Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS” project formally addressed two US Department of Energy Bioenergy Technologies Office (BETO) goals: (1) Model the sustainable supply of 1 million metric tonnes ash free dry weight (AFDW) cultivated algal biomass and (2) Demonstrate valuable co-products produced along with biofuel intermediates to increase value of algal biomass by 30%. To achieve these goals, the project demonstrated and validated high-value co-products to drive down the cost of biofuel by increasing the value of algae “co-products” towards increasing the selling price of total algae biomass as one of the key drivers of economics and adoption. This was accomplished through five core, interdependent tasks including: (1) strain selection to identify and deliver strains for mass culture, (2) mass culture using a hybrid cultivation system and following key operating parameters for downstream applications to provide algae feedstock, (3) recovery and conversion to evaluate two alternative methods to separate dry algae biomass into oil and residuals for downstream testing, (4) product assessment to determine biofuel, aquafeed or poultry feed product efficacy using algae biomass fractions as well as to provide critical performance data for valuation and (5) commercialization to use technoeconomic and life cycle assessments (TEA/LCA) as iterative design and assessment tools including consideration of target markets, competitors, and distribution channels to guide product assessment, development and valuation. A total of 46 peer-review publications, many open-access, provide detail of much of the work carried out and the results of the tasks. Additional reports and presentations provide other technical and public engagement material. At a high level, using a variety of approaches, more than 1000 marine microalgae strains were evaluated to ultimately identify the seven winners that were down-selected to be grown in mass culture. Strain selection demonstrated that there were no ‘super strains’ and that each candidate had strengths and limitations for specific products, growth conditions or operational considerations. Mass culture growth of these seven strains at >5000 L / 29 m 2 scale found that four them were suitable for product assessment. More than 250 kg of biomass was produced across hundreds of pond runs along with thousands of cultivation entries on the growth and biomass characteristics as well as environmental parameters. In the process, dozens of standard operating procedures were generated as was custom software to process and analyze cultivation data. Recovery and conversion of algae biomass demonstrated that a hexane solvent based extraction protocol was most effective at recovering oil (biocrude) from algae and four strains were processed to produce oil and lipid extracted algae (residuals) for downstream testing. Membrane-based oil separation was less successful, but may still be applicable to other commercial applications in the future. Product testing demonstrated that algae biocrude is of high quality and hydrotreating generated numerous fractions of high quality composition for fuel and lubricate based applications. Aquafeed studies performed at a variety of scales showed that both whole and defatted (lipid extracted algae) microalgae were suitable as a feed ingredient, but that the specifics of the fed animal and biochemical composition of the algae are critical factors when determining formulation. Similarly, poultry studies on whole and defatted microalgae generally showed positive outcomes on animal growth and health, with some microalgae providing enhanced nutritional composition of the animal product. Economic and life cycle assessments covered a wide range of possible commercialization and sustainability scenarios. Replacement value, improved product value added, consumer values marketing added valuation and improved animal health were considered as alternatives for microalgae valuation. Using the open pond system, algae productivity was identified as the key driver of commercialization economics, but combination of co-products (e.g. animal feed) with biofuel production substantially increased the total selling price of algae. Modeled microalgae selling price exceeded $\$$1500/tonne and could generate competitive biofuel selling prices below $\$$5 gallon gas equivalents using realistic algal productivities. Short (process scale) and longer (decadal trends) sustainability assessments show that marine microalgae can enhance the sustainability of energy production and lead to other realized benefits in water, fertilizer and land use for other sectors (e.g. agriculture). This project successfully demonstrated all of the components of an end-to-end process from mass microalgae cultivation and dewatering, to recovery and conversion of algae biomass components, to final product demonstration and process valuation; the combined results provide a framework for future commercialization of algae based biofuels.

09 BIOMASS FUELS↗
DOE OSTI2025

High Resolution Siting Suitability of Various Power Plant Technologies

Energy sector planning models determine the aggregate need for new generation, but these models are typically at the state or regional scale and are not equipped to address the wide range of location- and technology-specific issues that are increasingly a factor in power plant siting. These animations demonstrate the aggregate siting suitability of various power plant technology configurations, considering technology-specific factors that can prohibit development. The data presented is from the GRIDCERF (Geospatial Raster Input Data for Capacity Expansion Regional Feasibility) data package. GRIDCERF is a harmonized, open-source geospatial product that can be used to evaluate siting suitability for renewable and non-renewable power plants in the conterminous United States. The animations presented here demonstrate a curated selection of the full suite of technology configurations available. GRIDCERF provides the necessary inputs for models that simulate power plant siting for regional capacity expansion planning such as the Capacity Expansion Regional Feasibility (CERF) model.

Mongird, Kendall [Pacific Northwest National Labor↗