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At least 937 records · Page 52

Development of genetic tools for the thermophilic filamentous fungus Thermoascus aurantiacus

Abstract Background Fungal enzymes are vital for industrial biotechnology, including the conversion of plant biomass to biofuels and bio-based chemicals. In recent years, there is increasing interest in using enzymes from thermophilic fungi, which often have higher reaction rates and thermal tolerance compared to currently used fungal enzymes. The thermophilic filamentous fungus Thermoascus aurantiacus produces large amounts of highly thermostable plant cell wall-degrading enzymes. However, no genetic tools have yet been developed for this fungus, which prevents strain engineering efforts. The goal of this study was to develop strain engineering tools such as a transformation system, a CRISPR/Cas9 gene editing system and a sexual crossing protocol to improve the enzyme production. Results Here, we report Agrobacterium tumefaciens -mediated transformation (ATMT) of T. aurantiacus using the hph marker gene, conferring resistance to hygromycin B. The newly developed transformation protocol was optimized and used to integrate an expression cassette of the transcriptional xylanase regulator xlnR , which led to up to 500% increased xylanase activity. Furthermore, a CRISPR/Cas9 gene editing system was established in this fungus, and two different gRNAs were tested to delete the pyrG orthologue with 10% and 35% deletion efficiency, respectively. Lastly, a sexual crossing protocol was established using a hygromycin B- and a 5-fluoroorotic acid-resistant parent strain. Crossing and isolation of progeny on selective media were completed in a week. Conclusion The genetic tools developed for T. aurantiacus can now be used individually or in combination to further improve thermostable enzyme production by this fungus.

09 BIOMASS FUELS↗

Addressing deep array effects and impacts to wake steering with the cumulative-curl wake model

Abstract. Wind farm design and analysis heavily rely on computationally efficient engineering models that are evaluated many times to find an optimal solution. A recent article compared the state-of-the-art Gauss-curl hybrid (GCH) model to historical data of three offshore wind farms. Two points of model discrepancy were identified therein: poor wake predictions for turbines experiencing a lot of wakes and wake interactions between two turbines over long distances. The present article addresses those two concerns and presents the cumulative-curl (CC) model. Comparison of the CC model to high-fidelity simulation data and historical data of three offshore wind farms confirms the improved accuracy of the CC model over the GCH model in situations with large wake losses and wake recovery over large inter-turbine distances. Additionally, the CC model performs comparably to the GCH model for single- and fewer-turbine wake interactions, which were already accurately modeled. Lastly, the CC model has been implemented in a vectorized form, greatly reducing the computation time for many wind conditions. The CC model now enables reliable simulation studies for both small and large offshore wind farms at a low computational cost, thereby making it an ideal candidate for wake-steering optimization and layout optimization.

17 WIND ENERGY↗

Nuclear Thermal Energy Storage Configurations for Industrial Combined Heat and Power Supply: Conceptual Study and Engineering Designs

The industries examined in this report primarily rely on moderate-temperature heat provided by gas- or coal-fired boilers and combined heat and power (CHP) plants, delivered through standard process steam systems. High-temperature energy demands are often industry-specific and typically exceed the capabilities of high-temperature gas-cooled reactors (HTGRs). While it is technically feasible to replace process steam from fossil-based heat sources with nuclear energy, certain industries, such as methanol production and pulp and paper, face technoeconomic challenges in integrating nuclear energy without major changes or a technological shift. This is mainly due to the limited external energy demand remaining after the use of internal byproducts, waste heat recovery, and simple efficiency improvements. Achieving full decarbonization of these processes with nuclear energy would require significant technological advancements, involving experimental technology and substantial investments, making widespread adoption in existing industrial plants unlikely in the near term. This study reviews TES options in the context of enabling a flexible CHP supply while maintaining a steady nuclear heat input. Heat storage systems that interface between the reactor primary fluid and the CHP system offer superior performance and flexibility. Specifically, steam extraction downstream of the reheater with a two-tank molten-salt TES appears as the best solution regarding thermodynamic system benefits and system drawbacks. Using selected system configurations, a conceptual design of an industrial energy park was developed for industries with varying energy demands, such as steel production plants utilizing electric arc furnaces (EAFs) and chemical plants, as well as for those with constant energy demands, like petroleum refineries. This design highlights the capabilities of TES and explores its potential business cases. The study also conceptually develops the potential for integrating additional energy sources with nuclear systems through the implementation of TES. The potential of the HTGR-TES-CHP system was also evaluated considering key uncertainties such as industrial demand profiles, external grid access availability, and eligible tax credit levels, using the Holistic Energy Resource Optimization Network. Sensitivity of net present value to these uncertainties was analyzed to determine the optimal number of nuclear reactors (and CHP systems) and the suitable TES capacity. The results were interpreted from a decision-maker’s perspective, focusing on three key areas: deployment strategy (oversized units vs. undersized units with TES support), industrial process characteristics (thermal-intensive single profiles vs. electricity-intensive combined profiles), and operational goals (maximizing profits vs. minimizing natural gas (NG) consumption or external grid dependence). The optimization results indicate that the HTGR-TES-CHP system significantly reduces reliance on NG boilers for individual industrial processes by 9-60% (in NG capacity factor), with an average reduction of 38%, compared to standalone NG boiler operation case (Business As Usual [BAU]). For combined industrial processes, the reduction ranges from 37-77%, with an average of 60%. Additionally, the system greatly reduces dependence on external grids. In meeting industrial electrical demands, a 33-100% self-sufficient internal electricity supply is achieved for single industrial process, with an average of 74%, compared to the BAU scenario, where 100% of electricity is imported. For combined processes, 35-100% of internal electricity demands are met by the reactor, with an average of 73%. At last, the relative NG price levels at which the proposed HTGR-TES-CHP system can cost-effectively enter the market currently dominated by existing NG boilers were estimated. For a moderate HTGR CAPEX level ($\$$2500/kWth, $\$$6329/kWe), the analysis suggests that NG prices must be 2.5 to 7 times higher than HTGR variable operating and maintenance costs for single industrial process, and 5.5 to 9.5 times higher for a combined process scenario. Tax credit modeling shows that the Investment Tax Credit significantly reduces the price threshold needed to break even, making the system competitive with NG boilers in certain cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Drivers of Natural Variation in Water-Use Efficiency Under Fluctuating Light Are Promising Targets for Improvement in Sorghum

Improving leaf intrinsic water-use efficiency ( iWUE ), the ratio of photosynthetic CO 2 assimilation to stomatal conductance, could decrease crop freshwater consumption. iWUE has primarily been studied under steady-state light, but light in crop stands rapidly fluctuates. Leaf responses to these fluctuations substantially affect overall plant performance. Notably, photosynthesis responds faster than stomata to decreases in light intensity: this desynchronization results in substantial loss of iWUE . Traits that could improve iWUE under fluctuating light, such as faster stomatal movement to better synchronize stomata with photosynthesis, show significant natural diversity in C 3 species. However, C 4 crops have been less closely investigated. Additionally, while modification of photosynthetic or stomatal traits independent of one another will theoretically have a proportionate effect on iWUE , in reality these traits are inter-dependent. It is unclear how interactions between photosynthesis and stomata affect natural diversity in iWUE , and whether some traits are more tractable drivers to improve iWUE . Here, measurements of photosynthesis, stomatal conductance and iWUE under steady-state and fluctuating light, along with stomatal patterning, were obtained in 18 field-grown accessions of the C 4 crop sorghum. These traits showed significant natural diversity but were highly correlated, with important implications for improvement of iWUE . Some features, such as gradual responses of photosynthesis to decreases in light, appeared promising for improvement of iWUE . Other traits showed tradeoffs that negated benefits to iWUE , e.g., accessions with faster stomatal responses to decreases in light, expected to benefit iWUE , also displayed more abrupt losses in photosynthesis, resulting in overall lower iWUE . Genetic engineering might be needed to break these natural tradeoffs and achieve optimal trait combinations, e.g., leaves with fewer, smaller stomata, more sensitive to changes in photosynthesis. Traits describing iWUE at steady-state, and the change in iWUE following decreases in light, were important contributors to overall iWUE under fluctuating light.

54 ENVIRONMENTAL SCIENCES↗

Combined Precursor Engineering and Grain Anchoring Leading to MA-Free, Phase-Pure, and Stable α-Formamidinium Lead Iodide Perovskites for Efficient Solar Cells

a-Formamidinium lead iodide (a-FAPbI 3 ) is one of the most promising candidate materials for high-efficiency and thermally stable perovskite solar cells (PSCs) owing to its outstanding optoelectrical properties and high thermal stability. However, achieving a stable form of a-FAPbI 3 where both the composition and the phase are pure is very challenging. In this work, we report on a combined strategy of precursor engineering and grain anchoring to successfully prepare methylammonium (MA)-free and phase-pure stable a-FAPbI 3 films. The incorporation of volatile FA-based additives in the precursor solutions completely suppresses the formation of non-perovskite d-FAPbI 3 during film crystallization. Grains of the desired a-phase are anchored together and stabilized when 4-tert-butylbenzylammonium iodide is permeated into the a-FAPbI 3 film interior via grain boundaries. This cooperative scheme leads to a significantly increased efficiency close to 21% for FAPbI 3 perovskite solar cells. Moreover, the stabilized PSCs exhibit improved thermal stability and maintained ~90 % of their initial efficiency after storage at 50 degrees C for over 1600 hours.

14 SOLAR ENERGY↗

Writing the Programs of Programmable Catalysis

It has long been known that non-steady state and periodic catalytic reactor operation in terms of temperature, pressure, and composition can lead to higher overall productivity and/or product selectivity than the best steady operation. Recently, the emergence of catalysts whose intrinsic properties can be made to oscillate with time, introduces advanced forcing capabilities that can be “programmed” into the catalysts to broaden the scope and applicability of periodic operation to surface chemistry. In this work, an algorithmic approach is implemented to significantly accelerate the discovery and optimization of periodic steady states of catalytic reactors. Decomposition of complex dynamics into fundamental mechanistic fast–slow steps is seen to improve conceptual understanding of the relationship between binding energy oscillation protocols and overall catalytic rates. Finding structured forcing protocols, optimally tailored to the multiple time scales of a given individual mechanism, requires an efficient search of high-dimensional parameter spaces. Here, this is enabled here through active learning (Bayesian optimization, enhanced by our proposed Bayesian continuation). Implementation of these methods is shown to accelerate the evaluation of catalyst programs by up to several orders of magnitude. Faster screening of programmable catalysts to discover periodic steady states enables the optimization of catalytic operating protocols and thus opens the possibility for catalyst engineering based on optimal forcing programs to control rate and product selectivity, even for complex multistep catalytic mechanisms.

catalysis↗

Solution-phase sample-averaged single-particle spectroscopy of quantum emitters with femtosecond resolution

Here, the development of many optical quantum technologies depends on the availability of solid-state single quantum emitters with near-perfect optical coherence. However, a standing issue that limits systematic improvement is the significant sample heterogeneity and lack of mechanistic understanding of microscopic energy flow at the single emitter level and ultrafast timescales. Here we develop solution-phase single-particle pump-probe spectroscopy with photon correlation detection that captures sample-averaged dynamics in single molecules and/or defect states with unprecedented clarity at femtosecond resolution. We apply this technique to single quantum emitters in two-dimensional hexagonal boron nitride, which suffers from significant heterogeneity and low quantum efficiency. From millisecond to nanosecond timescales, the translation diffusion, metastable-state-related bunching shoulders, rotational dynamics, and antibunching features are disentangled by their distinct photon-correlation timescales, which collectively quantify the normalized two-photon emission quantum yield. Leveraging its femtosecond resolution, spectral selectivity and ultralow noise (two orders of magnitude improvement over solid-state methods), we visualize electron-phonon coupling in the time domain at the single defect level, and discover the acceleration of polaronic formation driven by multi-electron excitation. Corroborated with results from a theoretical polaron model, we show how this translates to sample-averaged photon fidelity characterization of cascaded emission efficiency and optical decoherence time. Our work provides a framework for ultrafast spectroscopy in single emitters, molecules, or defects prone to photoluminescence intermittency and heterogeneity, opening new avenues of extreme-scale characterization and synthetic improvements for quantum information applications.

36 MATERIALS SCIENCE↗

Drying of strawberries with airborne ultrasound and other integrated dehydration mechanisms

This article presents a comprehensive investigation into the drying of strawberries using multiple dehydration methods with an emphasis on energy efficiency and sustainability. Initially, an airborne ultrasonic transducer with a frequency of 21 kHz was employed in batch operations to examine the effects of controlling parameters, including applied power, distance from the transducer plate, sample thickness, and sample holder type. The Energy Ratio, defined as the ratio of thermal energy required to evaporate moisture to ultrasonic energy, was observed to reach up to 2.2, particularly during the initial stages of drying. Subsequently, the Smart Dryer integrated airborne ultrasound (US) dehydration, slot jet reattachment (SJR) nozzle convective drying, infrared (IR) drying, and their combinations, enabling a systematic exploration of various drying conditions on the drying time and quality of strawberries. The integration of airborne US with SJR nozzles and IR drying demonstrates a promising approach for optimizing drying processes. This method not only preserves the quality of dried strawberries but also improves the energy factor to 0.88, reducing drying time by 89% compared with other conditions. Key quality attributes of the dried strawberries, such as color and water activity, were evaluated to understand the influence of each drying method. The findings highlight the potential of these integrated drying techniques as sustainable solutions for efficient and high-quality strawberry dehydration.

42 ENGINEERING↗

A Decision Support System to Compile Environmental Mitigations from Hydropower Licensing Documents

The process of deciphering, extracting, and compiling information from texts dense with domain-specific terminology and technical jargon is a challenging endeavor. It demands considerable expertise and deep knowledge in the respective field, resulting in a labor-intensive process when executed by humans. Furthermore, the task of identifying multiple class labels in extensive texts presents a challenge due to intra- and inter-reader variability, making the process time-consuming and costly.We’re introducing a user-friendly graphical interface, fortified with a BERT model-powered decision support system. This advanced system aims to augment efficiency, curtail data collection time, and sustain high precision in data acquisition. It is instrumental in deciphering and synthesizing intricate texts teeming with a spectrum of expressions, even within similar mitigation categories. Such tasks traditionally demand substantial human effort and specialized knowledge in the domain.Our system is specifically engineered for the task of extracting environmental mitigation information to promote sustainable hydropower development from licenses issued by the Federal Energy Regulatory Commission (FERC). These license documents are comprehensive, each containing over 15,000 words and requiring the identification of 135 different class labels. We anticipate that our system will boost reading speed, improve the consistency of classification outputs among readers, and contribute to the development of a robust scientific database of environmental mitigations associated with the 2,000+ non-federal hydropower facilities licensed by FERC in the United States.

Yoon, Hong-Jun [ORNL] (ORCID:0000000254505878)↗

Technology Demonstration of a High-Pressure Swirl Oxy-Coal Combustor

This technical report presents the exploration of the design and prototyping of a High-Pressure Swirl Oxy-coal Combustor. Pressurized oxy-coal combustion systems have the potential to improve efficiency along with an increased carbon capture rate. Reduction of flue gas at higher pressure, smaller system size, and capital cost reductions render high-pressure oxy-coal systems particularly attractive as next-generation energy-producing systems. High-pressure oxy-coal combustion systems are a recent concept, and thus operability issues of combustor designs for such systems are not fully understood. Significant challenges exist to maintain oxy-coal combustion stability at elevated pressure and a high CO 2 diluent environment. Although a body of knowledge exists for high-pressure oxygen combustion in rocket engines (or similar applications), it is yet to be strategized how these fundamental concepts can be translated to low-temperature CO 2 diluent combustion regimes. The realization of the pressurized oxy-coal based systems requires combustor components to be designed and demonstrated for an operating pressure over 10 bar. However, pressurized oxy-coal combustor design information at this pressure range and scale relevant to validate those proposed systems is currently limited. Experimental data from MWth scale oxy-coal combustors are needed to identify the optimal trade-off between net efficiency and systems size. The proposed effort is aimed at demonstrating a 1 MWth down-fired swirl Oxy-Coal combustor and investigate the interrelation between combustor operating conditions (pressure; flame stability; flue gas recirculation ratio) and conversion efficiencies to minimize oxygen requirements. One of the key challenges is to configure burner design (i.e., swirl number and injector) and operating conditions for high-pressure oxy-coal combustion systems. These experiments differ from current systems partly due to the high theoretical flame temperature and related burner operability issues associated with oxy-combustion. An ASPEN PLUS® model study for 550 MWe TIPS and ENEL pressurized oxy-coal systems with CO 2 recirculation was performed to evaluate system design, subsystems sizing, and operating condition determination. The system analysis effort included TRL and technology gap determination of subsystems and critical components. This information was scaled to develop design requirements (design pressure and flue gas recirculation: RR Flue Gas = $\frac{m_{flue}}{m_{total}}$) for the 1 MWth combustor. The effects of a wide range of carbon dioxide recirculation ratios on the thermal efficiency of ENEL and TIPS cycles are studied. The pressure of 10 bar and 80 bar are used for ENEL and TIPS cycles, respectively. The thermal efficiency of ENEL is significantly higher than the efficiency of TIPS at a pressure of less than 10 bar. The insights from system analysis were then used to design a 1 MWth swirl oxy-coal combustor. Flame temperature analysis and material strength analysis was performed to determine the combustor thickness. The structural integrity of the combustor was validated by finite element analysis using Abacus® and Hypermesh®. Feasibility of igniters and secondary burners are investigated in successful high-pressure oxy-methane combustion. The secondary burners are designed in such a way that it can operate between 100 to 500 kW firing input. Three generations of the pintle injector were designed based on swirl numbers (S=0, 0.9, and 1.2). Key pintle injector parameters such as pintle size, pintle orifice size, spray pattern were investigated by cold flow tests. Information from these tests was used to modify injector design for smooth and successful operation. A 5 mm pintle orifice size was decided upon as the optimum size for oxy-coal operation for the combustor. Shadow sizing experiments were performed to identify the atomization rate of each injector. Different coal water slurry mixtures (30 – 50% coal by wt% in the mixture) at various total momentum ratios (TMR) were investigated for this purpose. These experiments provided decisive information to choose the best design of the injector. The injector with 1.2 swirl provided higher atomization in all cases than other designs. The mean equivalent droplet size of the jet was similar at different TMR and mixture ratios using this injector, thus making it suitable for use in most cases. Therefore, the 1.2 swirl-pintle injector was chosen for the shakedown test. The combustor and other sub-systems, including feed systems and control and data acquisition, have been manufactured, assembled, and integrated. The total system integration and installation began on July 1, 2020. The shake-down tests and initial operational capability demonstration are expected to be completed by September 30, 2020.

01 COAL, LIGNITE, AND PEAT↗

Techno-Economic Analysis of Greenfield Geothermal Hybrid Power Plants using a Solar or Natural Gas Steam Topping Cycle

The relatively low generation costs associated with wind, solar PV, and natural gas power plants make it challenging for geothermal power plants to produce and sell the power that has the reliability and sustainability characteristics that are greatly needed in US power markets. This is especially true for geothermal resources with low to medium temperatures, which results in relatively low thermal efficiency and generation costs that are higher than those for wind, solar PV, and natural gas. This analysis evaluates solar thermal- and natural gas combustion waste heat recovery-based topping cycle hybridization of geothermal binary power plants. This approach provides several benefits that may allow geothermal power plants to generate power at more competitive costs. First, the addition of solar thermal energy or natural gas combustion waste heat input to a geothermal power plant provides additional heat input that can be converted to electrical power. Second, the temperature level of the heat obtained from concentrating solar collectors or natural gas combustion exhaust is higher than that of geothermal heat, which provides opportunities for improving the efficiency of the conversion of thermal energy to electrical power. Third, the ease with which solar thermal systems integrate with energy storage and the flexibility of natural gas means power generation can occur during peak demand periods.

14 SOLAR ENERGY↗

Are the U.S. Biorefineries Over the Hurdle of 2000 Ton Daily Throughput Yet?

The efficient utilization of lignocellulosic biomass for biofuel and biochemical production is hindered by material handling issues such as clogging and segregation among other challenges. Preprocessing methods such as drying, screening, and milling have improved conversion yield but have not sufficiently enhanced flowability, especially herbaceous biomass. The poor flowability of herbaceous biomass is rooted in some particle attributes that remain less altered by those methods, e.g., irregular particle shape, high roughness, and high compressibility, making it hard to scale up throughput to a key benchmark for a biorefinery – 2000 ton per day. Applying additional preprocessing methods like pelletization and torrefaction to drastically change those particle attributes can improve flow and handling but has not been comprehensively verified through test. The flowability of herbaceous biomass feedstock formats generated by three different preprocessing methods was recently assessed at Idaho National Laboratory’s Biomass Feedstock National User Facility: first, loose particles size reduced from as-received materials; second, pellets produced from an efficient densification process; and third, powders milled from torrefied pellets. Benchmarking tests including static angle of repose, basic flow energy measured in a powder rheometer, and discharge flow in an adjustable hopper, were conducted to evaluate those feedstock formats. Beyond the capacity of existing experimental apparatuses, a digital engineering approach involving flow simulations and AI models were used to identity the material attributes and processing parameters that have dominant influences on flow throughput. Techno-economic analysis focusing on hopper flow as a typical material handling operation was conducted for those feedstock formats. Perspectives will be discussed on whether the 2000-ton daily throughput for a biorefinery is achievable at an acceptable cost by using any of the tested preprocessing methods.

09 - BIOMASS FUELS↗

Systematic engineering for production of anti-aging sunscreen compound in Pseudomonas putida

Sunscreen has been used for thousands of years to protect skin from ultraviolet radiation. However, the use of modern commercial sunscreen containing oxybenzone, ZnO, and TiO 2 has raised concerns due to their negative effects on human health and the environment. In this study, we aim to establish an efficient microbial platform for production of shinorine, a UV light absorbing compound with anti-aging properties. First, we methodically selected an appropriate host for shinorine production by analyzing central carbon flux distribution data from prior studies alongside predictions from genome-scale metabolic models (GEMs). We enhanced shinorine productivity through CRISPRi-mediated downregulation and utilized shotgun proteomics to pinpoint potential competing pathways. Simultaneously, we improved the shinorine biosynthetic pathway by refining its design, optimizing promoter usage, and altering the strength of ribosome binding sites. Finally, we conducted amino acid feeding experiments under various conditions to identify the key limiting factors in shinorine production. The study combines meta-analysis of 13 C-metabolic flux analysis, GEMs, synthetic biology, CRISPRi-mediated gene downregulation, and omics analysis to improve shinorine production, demonstrating the potential of Pseudomonas putida KT2440 as platform for shinorine production.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancement of the spin–orbit torque efficiency in W/Cu/CoFeB heterostructures via interface engineering

Here, the spin-torque ferromagnetic resonance signal and the spin Hall magnetoresistance induced by the spin Hall effect of W/Cu/CoFeB heterostructures with different Cu layer thicknesses (t Cu ) have been systemically studied. The effective spin mixing conductance $g^{↑↓}_{eff}$, the interfacial spin transparency T, and the real spin–orbit torque efficiency ( J s J c ) real show a significant increase compared to the W/CoFeB heterostructure. ( J s J c ) real reaches its maximum of ~0.54, increased up to ~50% at the optimized tCu ~ 0.52 nm according to our theoretical prediction. More importantly, the intrinsic spin Hall angle of W, $θ^{int}_{SH}$ ~ 0.79 ± 0.20, has also been obtained after the correction of the inverse spin Hall effect and T. This suggests that the Cu insertion improves the interface quality and, therefore, assists the spin transport in the heterostructures, which potentially improves the performance of next-generation spintronic devices.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Integrated Metrics for County-Level Resilience Ranking Using Entropy and TOPSIS

In the face of atypical weather events, power infrastructure failures, and limited resources for resilience investment, energy decision-makers need data-driven metrics to allocate resilience investments and maximize the reduction of power outage impacts. For state-level planning, for instance, ranking the resilience of each county is key to ensuring effective distribution of resources. In such cases, resilience for each spatial unit is multifaceted and is captured by a set of indicators (i.e., metrics) that can be combined into an overall score that reduces the complexity of power outage dynamics to a single decision metric. However, weighting of these indicators is often addressed by simplifying assumptions (i.e., equal weights) or semi-subjective methods that rely on user-defined weights that can introduce biases (e.g., weighted average score). Within the disaster risk reduction and resilience engineering community, a recurring challenge in multicriteria decision-making is the objective weighting of indicators for composite indices. To address this issue, we have leveraged a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) combined with an entropy-based weighting approach to calculated the integrated scores. This method objectively determines the importance of each metric, better discerns between spatial units (i.e., counties), and offers a more reliable ranking of counties according to their relative resilience attributes. By improving methods for integrating resilience indicators, our approach helps planners and decision-makers prioritize resources more effectively for more efficient resilience investments.

Bhusal, Narayan [Oak Ridge National Laboratory (OR↗

Fuel Effects on Advanced Compression Ignition Load Limits

In order to increase the efficiency of light-duty gasoline engines, the Co-Optimization of Fuels and Engines (Co-Optima) initiative from the U.S. Department of Energy is investigating multi-mode combustion strategies. Multi-mode combustion can be describe as using conventional spark-ignited combustion at high loads, and at the part-load operating conditions, various advanced compression ignition (ACI) strategies are being investigated to increase efficiency. Of particular interest to the Co-Optima initiative is the extent to which optimal fuel properties and compositions can enable higher efficiency ACI combustion over larger portions of the operating map. Extending the speed-load range of these ACI modes can enable greater part-load efficiency improvements for multi-mode combustion strategies. In this manuscript, we investigate fuel effects for six different fuels, including four with a research octane number (RON) of 98 and differing fuel chemistries, iso-octane, and a market representative E10 fuel, on the load limits for two different ACI strategies: spark-assisted compression ignition (SACI) and partial fuel stratification-gasoline compression ignition (PFS-GCI) operation. Experimental results show that limits to intake boosting limit high load operation for most fuels, but high smoke emissions for high particulate matter index (PMI) fuels under SACI conditions could also be a limitation. Contrastingly, low load is limited by combustion efficiency, but these effects have more pronounced variation with fuel chemistry for PFS-GCI than with SACI. Additional, distinct effects affecting autoignition timing and peak heat release at higher speeds were identified for fuels having different low temperature heat release (LTHR) propensities for both ACI modes.

33 ADVANCED PROPULSION SYSTEMS↗

Flux REaction TArget Prioritization (Flux RETAP) v1

Metabolic engineering is evolving rapidly as a result of new advances in synthetic biology and automation, as well as the irruption of machine learning (ML). ML has been shown to provide the predictive power synthetic biology lacked and needed, and to be able to effectively guide the metabolic engineering process. However, current technical limitations prevent the independent application of ML approaches to metabolic engineering without the use of previous biological knowledge in the form of a prioritized list of desirable engineering targets. Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale metabolic models (GSMs) for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing metabolite production. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production in the literature accessible to us, 50% of targets that experimentally improved taxadiene production in E. coli and ~60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets which can also be utilized in ML pipelines.

Czajka, Jeffrey [Battelle Memorial Institute, Paci↗

Complete Evaluation of ION Cost Reduction Opportunities for LWRS Pathways

The Light Water Reactor Sustainability (LWRS) Program, sponsored by the U.S. Department of Energy (DOE), plays a pivotal role in enhancing the sustainability, safety, and economic viability of the nation's fleet of nuclear power plants. This program collaborates extensively with industry, vendors, suppliers, regulatory agencies, and research and development organizations within the nuclear energy sector. The overarching goals of the LWRS program are twofold: to provide innovative science and technology-based solutions to the nuclear industry, surpassing current performance models, and to manage the aging of systems, structures, and components (SSCs) to extend the operational lifetimes of nuclear power plants safely, efficiently, and economically. The program focuses on five research and development pathways: Plant Modernization: This pathway seeks to enhance the economic viability of nuclear power plants in evolving energy markets through innovation, efficiency improvements, and digital transformation. The integration of digital technologies into plant operations is a central theme, aiming to create a seamless digital environment that improves plant economics and safety. Flexible Plant Operation and Generation: Research efforts in this pathway explore opportunities for light-water reactors (LWRs) to directly supply energy to industrial processes, diversifying revenue generation approaches and improving economic sustainability.

42 ENGINEERING↗