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DOE OSTI2016

Carcasses of invasive species are predominantly utilized by invasive scavengers in an island ecosystem

Abstract Invasive species have significantly affected ecosystems, particularly islands, and species invasions continue with increasing globalization. Largely unstudied, the influence of invasive species on island ecosystem functions, especially scavenging and decomposition, could be substantive. Quantifying carcass utilization by different scavengers and shifts in community dynamics in the presence of invasive animals is of particular interest for understanding impacts on nutrient recycling. Invasive species could benefit greatly from carcass resources within highly invaded island ecosystems, through increased invasion success and population growth, subsequently exacerbating their impacts on native species. We quantified how experimentally placed invasive amphibian, reptile, small mammal, and bird carcasses were utilized by vertebrate and invertebrate scavengers on the Big Island of Hawai'i in three island habitats: a barren lava field, a vegetated lava field, and a rainforest. We used camera traps to record vertebrate scavengers removing carcasses and elapsed time until removal. We evaluated differences in scavenging between vertebrates and invertebrates and within the vertebrate community across different habitats and carcass types. Despite the small carcass sizes (<1 kg) used in this study, 55% of carcasses were removed by vertebrate scavengers, all invasive: mongoose, rodents, cats, pigs, and a common myna. Our data indicate that invasive vertebrate scavengers in this island ecosystem are highly efficient at assimilating a range of carrion resources across a variety of habitats. Carcasses of invasive animals could contribute substantially to energy budgets of other invasive vertebrate species. This may be a critical component contributing to successful invasions especially on islands and subsequent impacts on ecosystem function.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

UV + Damp Heat Induced Power Losses in Fielded Utility N-Type Si PV Modules

A recent trend in commercial PV modules is a transition to n-type silicon cells, including passivated emitter rear totally diffused (n-PERT), tunnel oxide passivated contact (TOPCon), and silicon heterojunction (SHJ). There is evidence via lab studies that some of these cells are more susceptible to UV induced degradation (UVID), yet there is a lack of confirmation that such degradation occurs in the field. Current IEC standards designed to screen for early module failures require only minimal UV exposure (15 kWh/m2 280-400 nm, ~2-3 months equivalent outdoor exposure). Here, we investigate fielded n-PERT silicon (Si) modules from a commercial utility that show power losses of ~2%/year. We present a comprehensive picture of the physics and chemistry of degradation supported by both module and cell electronic characterization (EL, PL, IV, EQE, and DLIT) and materials-level morphological and chemical analysis (SEM, EDS, XPS, FTIR, and HPLC). All sampled site modules show short circuit current (Isc) and open circuit voltage (Voc) losses when compared to unfielded spares, with the most severely degraded also having losses in fill factor (FF). We identify two different degradation modes contributing to overall power loss: (1) external quantum efficiency (EQE) measurements show losses in the blue range of the spectra, indicative of cell surface recombination losses, and (2) variations in high series resistance (Rs) at the cell level that are correlated with compositional differences in cell metallization. Using unfielded spares, we were able to reproduce Voc, Isc, and EQE losses via a minimum UV stress of 67.5 kWh/m2 (280-400 nm), 4.5x the exposure currently required in IEC 61215-2 (MQT 10). Degradation continued with additional UV dosage equivalent to the fielded modules (405 kWh/m2 total), with power loss leveling out at an average of 6.1%. Subsequent 1000 h of 85% RH/85degrees C damp heat testing showed that cells exposed to UV underwent additional severe series resistance degradation, even those without the susceptible paste composition seen in the field, whereas non-UV exposed cells saw little change. We attribute this to higher concentrations of acetic acid generated on the UV exposed area of the module, leading to degradation of the gridline/cell interface and high Rs. This study is unique in that it reproduces field observed utility scale UVID with an accelerated test and supports the need for standards development for longer UV exposure combined with other stress factors to catch materials interplay within a module package.

14 SOLAR ENERGY↗

DOE OSTI2023

Three-dimensional phenotyping of peach tree-crown architecture utilizing terrestrial laser scanning

Tree training systems for temperate fruit have been developed throughout history by pomologists to improve light interception, fruit yield, and fruit quality. These training systems direct crown and branch growth to specific configurations. Quantifying crown architecture could aid the selection of trees that require less pruning or that naturally excel in specific growing/training system conditions. Regarding peaches [Prunus persica (L.) Batsch], access tools such as branching indices have been developed to characterize tree-crown architecture. However, the required branching data (BD) to develop these indices are difficult to collect. Traditionally, BD have been collected manually, but this process is tedious, time-consuming, and prone to human error. These barriers can be circumnavigated by utilizing terrestrial laser scanning (TLS) to obtain a digital twin of the real tree. TLS generates three-dimensional (3D) point clouds of the tree crown, wherein every point contains 3D coordinates (x, y, z). To facilitate the use of these tools for peach, we selected 16 young peach trees scanned in 2021 and 2022. These 16 trees were then modeled and quantified using the open-source software TreeQSM. As a result, “in silico” branching and biometric data for the young peach trees were calculated to demonstrate the capabilities of TLS phenotyping of peach tree-crown architecture. The comparison and analysis of field measurements (in situ) and in silico BD, biometric data, and quantitative structural model branch uncertainty data were utilized to determine the reconstructive model’s reliability as a source substitute for field measurements. Mean average deviation when comparing young tree (YT) height was approx. 5.93%, with crown volume was approx. 13.26% across both 2021 and 2022. All point clouds of the YTs in 2022 showed residuals lower than 12 mm to cylinders fitted to all branches, and mean surface coverage greater than 40% for both the trunk and primary branching orders.

09 BIOMASS FUELS↗

DOE OSTI2023

Regulatory utility of physiologically based pharmacokinetic modeling for assessing food impact in bioequivalence studies: A workshop summary report

This workshop report summarizes the presentations and panel discussion related to the use of physiologically based pharmacokinetic (PBPK) modeling approaches for food effect assessment, collected from Session 2 of Day 2 of the workshop titled “Regulatory Utility of Mechanistic Modeling to Support Alternative Bioequivalence Approaches.” The US Food and Drug Administration in collaboration with the Center for Research on Complex Generics organized this workshop where this particular session titled “Oral PBPK for Evaluating the Impact of Food on BE” presented successful cases of PBPK modeling approaches for food effect assessment. Recently, PBPK modeling has started to gain popularity among academia, industries, and regulatory agencies for its potential utility during bioavailability (BA) and/or bioequivalence (BE) studies of new and generic drug products to assess the impact of food on BA/BE. Considering the promises of PBPK modeling in generic drug development, the aim of this workshop session was to facilitate knowledge sharing among academia, industries, and regulatory agencies to understand the knowledge gap and guide the path forward. This report collects and summarizes the information presented and discussed during this session to disseminate the information into a broader audience for further advancement in this area.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Surface glycan-binding proteins are essential for cereal beta-glucan utilization by the human gut symbiont Bacteroides ovatus

The human gut microbiota, which underpins nutrition and systemic health, is compositionally sensitive to the availability of complex carbohydrates in the diet. The Bacteroidetes comprise a dominant phylum in the human gut microbiota whose members thrive on dietary and endogenous glycans by employing a diversity of highly specific, multi-gene polysaccharide utilization loci (PUL), which encode a variety of carbohydrases, transporters, and sensor/regulators. PULs invariably also encode surface glycan-binding proteins (SGBPs) that play a central role in saccharide capture at the outer membrane. Here, we present combined biophysical, structural, and in vivo characterization of the two SGBPs encoded by the Bacteroides ovatus mixed-linkage β-glucan utilization locus (MLGUL), thereby elucidating their key roles in the metabolism of this ubiquitous dietary cereal polysaccharide. In particular, molecular insight gained through several crystallographic complexes of SGBP-A and SGBP-B with oligosaccharides reveals that unique shape complementarity of binding platforms underpins specificity for the kinked MLG backbone vis-à-vis linear β-glucans. Reverse-genetic analysis revealed that both the presence and binding ability of the SusD homolog BoSGBP MLG -A are essential for growth on MLG, whereas the divergent, multi-domain BoSGBP MLG -B is dispensable but may assist in oligosaccharide scavenging from the environment. Overall, the synthesis of these data illuminates the critical role SGBPs play in concert with other MLGUL components, reveals new structure–function relationships among SGBPs, and provides fundamental knowledge to inform future (meta)genomic, biochemical, and microbiological analyses of the human gut microbiota.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Deep learning and radiomics: the utility of Google TensorFlow™ Inception in classifying clear cell renal cell carcinoma and oncocytoma on multiphasic CT

Purpose: Currently, all solid enhancing renal masses without microscopic fat are considered malignant until proven otherwise and there is substantial overlap in the imaging findings of benign and malignant renal masses, particularly between clear cell RCC (ccRCC) and benign oncocytoma (ONC). Radiomics has attracted increased attention for its utility in pre-operative work-up on routine clinical images. Radiomics based approaches have converted medical images into mineable data and identified prognostic imaging signatures that machine learning algorithms can use to construct predictive models by learning the decision boundaries of the underlying data distribution. The TensorFlow™ framework from Google is a state-of-the-art open-source software library that can be used for training deep learning neural networks for performing machine learning tasks. The purpose of this study was to investigate the diagnostic value and feasibility of a deep learning-based renal lesion classifier using open-source Google TensorFlow™ Inception in differentiating ccRCC from ONC on routine four-phase MDCT in patients with pathologically confirmed renal masses. Methods: With institutional review board approval for this 1996 Health Insurance Portability and Accountability Act compliant retrospective study and a waiver of informed consent, we queried our institution’s pathology, clinical, and radiology databases for histologically proven cases of ccRCC and ONC obtained between January 2000 and January 2016 scanned with a an intravenous contrast-enhanced four-phase renal mass protocol (unenhanced (UN), corticomedullary (CM), nephrographic (NP), and excretory (EX) phases). To extract features to be used for the machine learning model, the entire renal mass was contoured in the axial plane in each of the four phases, resulting in a 3D volume of interest (VOI) representative of the entire renal mass. We investigated thirteen different approaches to convert the acquired VOI data into a set of images that adequately represented each tumor which was used to train the final layer of the neural network model. Training was performed over 4000 iterations. In each iteration, 90% of the data were designated as training data and the remaining 10% served as validation data and a leave-one-out cross-validation scheme was implemented. Accuracy, sensitivity, specificity, positive (PPV) and negative predictive (NPV) values, and CIs were calculated for the classification of the thirteen processing modes. Results: We analyzed 179 consecutive patients with 179 lesions (128 ccRCC and 51 ONC). The ccRCC cohort had a mean size of 3.8 cm (range 0.8–14.6 cm) and the ONC cohort had a mean lesion size of 3.9 cm (range 1.0–13.1 cm). The highest specificity and PPV (52.9% and 80.3%, respectively) were achieved in the EX phase when we analyzed the single mid-slice of the tumor in the axial, coronal and sagittal plane, and when we increased the number of mid-slices of the tumor to three, with an accuracy of 75.4%, which also increased the sensitivity to 88.3% and the PPV to 79.6%. Using the entire tumor volume also showed that classification performance was best in the EX phase with an accuracy of 74.4%, a sensitivity of 85.8% and a PPV of 80.1%. When the entire tumor volume, plus mid-slices from all phases and all planes presented as tiled images, were submitted to the final layer of the neural network we achieved a PPV of 82.5%. Conclusions: The best classification result was obtained in the EX phase among the thirteen classification methods tested. Our proof of concept study is the first step towards understanding the utility of machine learning in the differentiation of ccRCC from ONC on routine CT images. We hope this could lead to future investigation into the development of a multivariate machine learning model which may augment our ability to accurately predict renal lesion histology on imaging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2018

Single-Grain Bulk YBa{sub 2}Cu{sub 3}O{sub y} Superconductors Grown by Infiltration Growth Process Utilizing the YbBa{sub 2}Cu{sub 3}O{sub y} + Liquid Phase as a Liquid Source

The top-seeded infiltration growth (IG) processed YBa{sub 2}Cu{sub 3}O{sub y} (Y-123) has several advantages compared to the same material produced by other melt process techniques. There is usually no shrinkage, a limited number of pores, and an uniform secondary phase particle dispersion in the Y-123 matrix. These characteristics of the IG process are very attractive for several industrial applications. In this paper, we produced a large single-grain Y-123 by IG and top seeded melt-growth process. Utilizing commercial YbBa{sub 2}Cu{sub 3}O{sub y} (Yb-123) and a homemade Y{sub 2}BaCuO{sub 5} (Y-211), we produced bulk YBa{sub 2}Cu{sub 3}O{sub y} samples using Yb-123 + liquid (1:1) as a liquid source. Four facet lines on the top surfaces of the as-grown samples indicated a uniform growth from the seed up to sample edges. Magnetization measurements by SQUID magnetometer showed a sharp superconducting transition with T{sub c},{sub onset} at 92.1 K. The critical current density at 77 K and self-field was 39,000 A/cm{sup 2}. Trapped field results confirmed that single grain Y-123 samples were produced utilizing the above process. Our results prove that Yb-123 + liquid (1:1) as a liquid source is effective in producing single grain Y-123 material by IG process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Dispatch optimization of concentrating solar power with utility-scale photovoltaics

Concentrating solar power (CSP) tower technologies capture thermal radiation from the sun utilizing a field of solar-tracking heliostats. When paired with inexpensive thermal energy storage (TES), CSP technologies can dispatch electricity during peak-market-priced hours, day or night. The cost of utility-scale photovoltaic (PV) systems has dropped significantly in the last decade, resulting in inexpensive energy production during daylight hours. The hybridization of PV and CSP with TES systems has the potential to provide continuous and stable energy production at a lower cost than a PV or CSP system alone. Hybrid systems are gaining popularity in international markets as a means to increase renewable energy portfolios across the world. Typically, CSP-PV hybrid systems have been evaluated using either monthly averages of hourly PV production or scheduling algorithms that neglect the time-of-production value of electricity in the market. To more accurately evaluate a CSP-PV-battery hybrid design, we develop a profit-maximizing mixed-integer linear program ($\mathcal{H}$) that determines a dispatch schedule for the individual sub-systems with a sub-hourly time fidelity. We introduce the mathematical formulation of such a model and show that it is computationally expensive to solve. To improve model tractability and reduce solution times, we offer techniques that: (1) reduce the problem size, (2) tighten the linear programming relaxation of ($\mathcal{H}$) via reformulation and the introduction of cuts, and (3) implement an optimization-based heuristic (that can yield initial feasible solutions for (($\mathcal{H}$) and, at any rate, yields near-optimal solutions). Applying these solution techniques results in a 79% improvement in solve time, on average, for our 48-h instances of (($\mathcal{H}$); corresponding solution times for an annual model run decrease by as much as 93%, where such a run consists of solving 365 instances of (($\mathcal{H}$), retaining only the first 24 h' worth of the solution, and sliding the time window forward 24 h. We present annual system metrics for two locations and two markets that inform design practices for hybrid systems and lay the groundwork for a more exhaustive policy analysis. A comparison of alternative hybrid systems to the CSP-only system reflects that hybrid models can almost double capacity factors while resulting in a 30% improvement related to various economic metrics.

14 SOLAR ENERGY↗

DOE OSTI2022

Investigation of Remanufacturing Methods Utilizing Mechanically-Generated and Gas-Atomized Feedstock Production for Directed Energy Deposition Processing Through Specific Energy Consumption Modeling

The goal of this work was to assess the energy consumption of a novel remanufacturing method that utilizes mechanically-generated feedstock for directed energy deposition. Gas-atomization is the state-of-the-art production process for directed energy deposition feedstock, and for this work was incorporated into a remanufacturing process path to provide a comparison method. Specific energy consumption models of remanufacturing utilizing both of these proposed process paths were developed and applied to a case study to investigate energy saving opportunities for future manufacturing paradigms. The energy modelling was done in three stages. First, the mechanically-generated feedstock production energy consumption model was generated from experimental observation. Second, the gas-atomized feedstock production energy consumption model was generated from a combination of experimental observation, reported estimates from the manufacturer, and data found in the literature. Lastly, the energy consumption model of directed energy deposition was derived from experimental observation and compares favorably with reported estimates in the literature. With the models, the specific energy consumption in the two process paths were compared and their application was demonstrated by estimating the energy consumption to remanufacture a bracket. The two feedstock production methods had similar specific energy consumptions. The specific energy consumption of the directed energy deposition process was the greatest component in the respective remanufacturing paths by an order of magnitude; increasing deposition rate is the most important factor for lowering the overall specific energy consumption. The analyzed remanufacturing technologies were estimated to consume less energy than replacement when repairing up to approximately 15% of the original part’s mass.

42 ENGINEERING↗

DOE OSTI2022

CO 2 utilization potential of a novel calcium ferrite based looping process fueled with coal: Experimental evaluation of various coal feedstocks and thermodynamic integrated process analysis

Here, conversion of CO 2 to CO was performed at 800-850C via reduction of calcium ferrite (CaFe 2 O 4 ) with coal followed by oxidation of reduced CaFe 2 O 4 with CO 2 to produce CO and partially oxidized Ca ferrite. The process was evaluated with several types of coals which included lignite, sub-bituminous, bituminous, anthracite and pet-coke. Reduction of CaFe 2 O 4 with sub-bituminous coal and lignite coal was more favorable than that with higher rank coals. Stable reactivity performance was demonstrated for 35-cycle test conducted with lignite coal/CaFe 2 O 4 at 800°C and with high conversion of CO 2 to CO. The rate of conversion of CO 2 to CO with reduced CaFe 2 O 4 was found to be 1st order with respect to CO 2 and had a low activation energy of 7.4 kJ/mol. Thermodynamic integrated process assessments suggest that two and three reactor process concepts can be realized and net CO 2 utilization achievable. The two reactor configuration shows the highest potential for CO 2 utilization while generating a value-added CO rich syngas stream.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Selenium utilization in thioredoxin and catalytic advantage provided by selenocysteine

Thioredoxin (Trx) is a major thiol-disulfide reductase that plays a role in many biological processes, including DNA replication and redox signaling. Although selenocysteine (Sec)-containing Trxs have been identified in certain bacteria, their enzymatic properties have not been characterized. In this study, we expressed a selenoprotein Trx from Treponema denticola, an oral spirochete, in Escherichia coli and characterized this selenoenzyme and its natural cysteine (Cys) homologue using E. coli Trx1 as a positive control. {sup 75}Se metabolic labeling and mutation analyses showed that the SECIS (Sec insertion sequence) of T. denticola selenoprotein Trx is functional in the E. coli Sec insertion system with specific selenium incorporation into the Sec residue. The selenoprotein Trx exhibited approximately 10-fold higher catalytic activity than the Sec-to-Cys version and natural Cys homologue and E. coli Trx1, suggesting that Sec confers higher catalytic activity on this thiol-disulfide reductase. Kinetic analysis also showed that the selenoprotein Trx had a 30-fold higher K{sub m} than Cys-containing homologues, suggesting that this selenoenzyme is adapted to work efficiently with high concentrations of substrate. Collectively, the results of this study support the hypothesis that selenium utilization in oxidoreductase systems is primarily due to the catalytic advantage provided by the rare amino acid, Sec. - Highlights: • The first characterization of a selenoprotein Trx is presented. • The selenoenzyme Trx exhibits 10-fold higher catalytic activity than Cys homologues. • Se utilization in Trx is primarily due to the catalytic advantage provided by Sec residue.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Utilizing fluorescent life time imaging microscopy technology for identify carriers of BRCA2 mutation

Worldwide, more than one million women are diagnosed with breast cancer every year, making it the most common female malignancy in the developed world. Germline mutations in BRCA1 and BRCA2 genes are estimated to increase the risk for developing breast cancer by up to 87%. From a clinical point of view, identification of BRCA1 and BRCA2 mutation carriers offers an opportunity to early identify or prevent the development of malignancy; therefore the ability to determine which women are more likely to carry BRCA1 or BRCA2 mutations is of great importance. The available diagnostic tests for mutation analysis of BRCA1 and BRCA2 are time- and labor-intensive, expensive, and do not allow the identification of all the functional mutations. We utilized the Fluorescent lifetime (FLT) imaging microscopy method which allows recognizing different cell populations, in order to distinguish between lymphocytes from BRCA1 and BRCA2 mutation carriers and non-carrier women by using easily obtainable lymphocyte cells from peripheral blood. Our results demonstrate that cells originated from BRCA2-mutation carriers have significantly lower FLT values compared with BRCA1 mutation carriers and control cells. This simple, inexpensive and sensitive method may be utilized in the future to detect BRCA2 mutation carriers, particularly those bearing unknown functional mutations. - Highlights: • Fluorescent lifetime imaging microscopy (FLIM) technology can be used for recognizing BRCA mutation carriers. • Cells originated from BRCA2-mutation carriers have lower FLT values compared with BRCA1 mutation carriers and control cells. • The difference in FLT values were observed regardless irradiation. • FLIM method may be more informative in the detection of BRCA2-mutation carriers than BRCA1.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

GLUT5 increases fructose utilization and promotes tumor progression in glioma

Highlights: • Glioma cell lines LN229 and U87 could utilize fructose to maintein survival and proliferation. • Knockdown GLUT5 could inhibit glioma cell proliferation in fructose medium. • GLUT5 was overexpressed in glioma tissues and was correlated with glioma malignancy and patients poor survival. Fructose is now such an important component of human diets, and several studies have found that some cancer cells could utilize fructose to overcome low glucose micro-environment, but the study on the role of fructose in glioma is rare. To explore the role of fructose in glioma, we detected the proliferation and colony formation ability of glioma cells in fructose medium, and found that the abilities of proliferation and colony formation of glioma cells in fructose medium were similar with abilities in glucose medium, however, fructose just partly restored proliferation ability of normal glial cells. To explore the mechanism, we compared the expression level of GLUT5 (Glucose transporter type 5) in these cell lines, and the results showed that glioma cell lines had higher GLUT5 expression than normal glial cell lines. And knockdown of GLUT5 could significantly inhabit cell proliferation of glioma cells in fructose medium. Furthermore, we found that GLUT5 was also higher expressed in glioma tissues, and GLUT5 expression correlated significantly with glioma malignancy and poor survival of glioma patients (p < 0.01). In addition, we also demonstrated that knockdown of GLUT5 could significantly inhabit tumor proliferation in vivo, and intake fructose could increase tumor volume prominently. Taken together, our data show that fructose can be used by glioma cells, and restrict the fructose intake or targeting GLUT5 could be efficacious strategies in glioma.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Ketohexokinase is involved in fructose utilization and promotes tumor progression in glioma

Highlights: • KHK was overexpressed in glioma and correlated with glioma malignancy and patients' poor survival. • Silencing KHK could significantly inhibit glioma cell proliferation and migration in fructose medium. • Culturing glioma cells in fructose medium could promote the expression of KHK and increase cells malignancy progression. Many studies have pinpointed that fructose could be utilized as a carbon source in some cancers, and we also defined that glioma cells could utilize fructose to maintain themselves survival and proliferation depending on GLUT5 expression recently. However, ketohexokinase (KHK), as a key enzyme involved in fructose catabolism, drew less attention in cancers, especially in glioma. In the present study, we first analyzed the expression levels of KHK in glioma tissues and the correlations of KHK expression with clinicopathological variables of patients with glioma. Meanwhile, we detected the effect of silencing KHK on the biological functions of glioma cells in fructose medium. From the results, we found that KHK was expressed at significantly higher level in glioma tissues than in non-tumor brain, and KHK expression was significantly correlated with tumor malignancy and poor survival of glioma patients (p < 0.01). Functionally, knockdown of KHK could significantly inhibit cell proliferation and migration of glioma cells in fructose medium. Furthermore, we investigated the KHK expression level after long-time treatment with fructose, and detected the change of cell biological behaviour, then we found that the expression level of KHK was significantly increased and these cells showed more malignant properties. Taken together, our results suggest that high fructose diet and KHK overexpression are correlated with glioma malignant progression and patients' poor survival, and we believe this hypothesis would open the door for novel therapeutic agents and mentalities for glioma.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Acetate-based biological platforms: Bridging carbon dioxide utilization and high-value bioproduct production in oleaginous yeasts

Acetate is emerging as a promising two-carbon substrate in the circular bioeconomy, bridging the gap between single-carbon sources and high-value biofuels and bioproducts. This review examines the key pathways for acetate production, including the electrochemical reduction of carbon dioxide, syngas fermentation, and biological acetogenesis. It focuses on acetate metabolism in oleaginous yeasts, such as Yarrowia lipolytica and Rhodotorula toruloides, which efficiently convert acetate-derived acetyl-CoA units into diverse bioproducts such as lipids, fatty alcohols, triacetic acid lactone, and carotenoids. Recent advances in metabolic engineering, transcriptomics, and metabolic flux analysis have improved the understanding of acetate assimilation in these organisms, thereby increasing their potential for industrial applications. In addition, the feasibility of a biological gas-to-liquid platform that utilizes acetate as a central intermediate for scalable biomanufacturing is discussed. Integrating acetate utilization with sustainable production strategies offers a promising path to advance the bio-based economy. Using acetate as a versatile metabolic intermediate enables the conversion of industrial emissions into biofuels and bioproducts while avoiding the energetic and toxicity constraints associated with direct fermentation of gaseous substrates.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Toward control co-design of utility-scale wind turbines: Collective vs. individual blade pitch control

A large-eddy simulation framework has been coupled with controller modules to systematically investigate the impacts of collective (CPC) and individual (IPC) pitch control strategies on utility-scale wind turbine energy production and fatigue loads. Wind turbine components were parameterized using an actuator surface model to simulate the rotor blades and the turbine nacelle. The baseline CPC and IPC algorithms, consisting of single-input single-output proportional–integral controllers and two integral controllers, respectively, were incorporated into the numerical framework. A series of simulations were carried out to investigate the relative performance of the two controllers under various turbulent inflow conditions, spanning hub-height velocities of 7 to 14 m/s. The numerical simulation results of this study showed that, in comparison to the CPC, the IPC controller could successfully reduce the damage equivalent loads of utility-scale turbines at regions 2 and 3 of turbine operation by about 3% and 40%, respectively, without any penalty on the power production of the turbine. It was also shown that, despite its minor impact on the turbulence kinetic energy of the wake, the IPC controller did not influence the recovery of the turbine wake.

17 WIND ENERGY↗

DOE OSTI2021

State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data

Nowadays, transmission system operators require higher degree of observability in real-time to gain situational awareness and improve the decision-making process to guarantee a safe and reliable operation. Digitalization of energy systems allows utilities to monitor the system dynamic performance in real-time at fast time scales. The use of such technologies has unlocked new opportunities to introduce new data driven algorithms for improving the stability assessment and control of the system. Motivated by these challenges, a group of experts have worked together to highlight and establish a baseline set of these common concerns, which can be used as motivation to propose innovative analytics and data-driven solutions. In this document, the results of a survey on 10 transmission system operators around the world are presented and it aims to understand the current practices of the participating companies, in terms of data acquisition, handling, storage, modelling and analytics. The overall objective of this document is to capture the actual needs from the interviewed utilities, thereby laying the groundwork for setting valid assumptions for the development of advanced algorithms in this field.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Carbon dioxide pipeline network transportation cost model: evaluating economic and geographic factors for efficient carbon capture, storage, and utilization

This study presents a comprehensive pipeline network modeling framework to estimate the CO 2 delivery cost for CO 2 utilization and geologic CO 2 storage across the United States. We developed a Python-based CO 2 pipeline transportation cost model leveraging Argonne National Laboratory’s pipeline engineering expertise and detailed natural gas transmission pipeline cost data across U.S. regions. Using existing road corridors as practical routing guides, the model designs pipeline networks that aggregate CO 2 from one or multiple sources and deliver it to selected destinations. It then minimizes the total transportation cost by optimizing pipeline diameters and incorporating booster pumps. A key contribution is the incorporation of up-to-date, region-specific cost factors with itemized components for materials, labor, miscellaneous construction expenses, and right-of-way acquisition. Results emphasize that regional variation and economies of scale associated with CO 2 pipeline costs are significant and should be explicitly accounted for in screening and planning studies. By combining realistic routing constraints with regionalized cost inputs, the model provides transparent design methodology and location-specific insights into source–destination delivery costs, including the effects of routing complexity along existing road networks. We demonstrate the model with two illustrative case studies – one for CO 2 storage and one for CO 2 utilization – in which the model designs pipeline networks spanning hundreds of miles across the states, collecting CO 2 from multiple sources and delivering it to designated endpoints while minimizing levelized cost of delivery via diameter and compression optimization. The model offers a practical, scalable approach for alternative design option screening and early-stage CO 2 transportation planning.

CCS↗