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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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At least 217 records · Page 12

Chemical pumps and flexible sheets spontaneously form self-regulating oscillators in solution

The synchronization of self-oscillating systems is vital to various biological functions, from the coordinated contraction of heart muscle to the self-organization of slime molds. Through modeling, we design bioinspired materials systems that spontaneously form shape-changing self-oscillators, which communicate to synchronize both their temporal and spatial behavior. Here, catalytic reactions at the bottom of a fluid-filled chamber and on mobile, flexible sheets generate the energy to “pump” the surrounding fluid, which also transports the immersed sheets. The sheets exert a force on the fluid that modifies the flow, which in turn affects the shape and movement of the flexible sheets. This feedback enables a single coated (active) and even an uncoated (passive) sheet to undergo self-oscillation, displaying different oscillatory modes with increases in the catalytic reaction rate. Two sheets (active or passive) introduce excluded volume, steric interactions. This distinctive combination of the hydrodynamic, fluid–structure, and steric interactions causes the sheets to form coupled oscillators, whose motion is synchronized in time and space. We develop a heuristic model that rationalizes this behavior. These coupled self-oscillators exhibit rich and tunable phase dynamics, which depends on the sheets’ initial placement, coverage by catalyst and relative size. Moreover, through variations in the reactant concentration, the system can switch between the different oscillatory modes. This breadth of dynamic behavior expands the functionality of the coupled oscillators, enabling soft robots to display a variety of self-sustained, self-regulating moves.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Regulatory response to a hybrid ancestral nitrogenase in Azotobacter vinelandii

Biological nitrogen fixation, the microbial reduction of atmospheric nitrogen to bioavailable ammonia, represents both a major limitation on biological productivity and a highly desirable engineering target for synthetic biology. However, the engineering of nitrogen fixation requires an integrated understanding of how the gene regulatory dynamics of host diazotrophs respond across sequence-function space of its central catalytic metalloenzyme, nitrogenase. Here, we interrogate this relationship by analyzing the transcriptome of Azotobacter vinelandii engineered with a phylogenetically inferred ancestral nitrogenase protein variant. The engineered strain exhibits reduced cellular nitrogenase activity but recovers wild-type growth rates following an extended lag period. We find that expression of genes within the immediate nitrogen fixation network is resilient to the introduced nitrogenase sequence-level perturbations. Rather the sustained physiological compatibility with the ancestral nitrogenase variant is accompanied by reduced expression of genes that support trace metal and electron resource allocation to nitrogenase. Our results spotlight gene expression changes in cellular processes adjacent to nitrogen fixation as productive engineering considerations to improve compatibility between remodeled nitrogenase proteins and engineered host diazotrophs.

59 BASIC BIOLOGICAL SCIENCES↗

Computational design of isotropic and anisotropic ultralow thermal conductivity polymer foams

Current state-of-the-art commercial polymer thermal insulation foam exhibits a thermal conductivity of 24 mW·m -1 ·K -1 (equivalently thermal resistivity of R-6/in.), similar to that of static air. To further optimize building energy efficiency, achieving even lower thermal conductivity is needed, which is, however, highly challenging. This paper presents computational evidence that demonstrates the feasibility of achieving an ultra-low thermal conductivity of less than 14.4 mW·m -1 ·K -1 (equivalently R-10/in.) using isotropic and anisotropic foam cell designs. For the isotropic design, we have identified analytical effective medium approximation (EMA) models within the accuracy of ±5% as finite element analysis (FEA) in predicting the effective thermal conductivity of foams with various porosities and filler gases. For the anisotropic design, we have developed and validated new EMA models against FEA in predicting the effective thermal conductivity of general anisotropic cuboids and Voronoi foams. For both isotropic and anisotropic designs, the design spaces for 18, 16, and 14.4 mW·m -1 ·K -1 (equivalently R-8, R-9 and R-10/in.) using various filler gases are obtained. It is found that polymer foams can be improved to achieve ultralow thermal conductivity by reducing CO 2 concentration, reducing radiation, increasing porosity, and using anisotropic pore geometry. In conclusion, these findings contribute to the development of highly efficient thermal insulation materials, enhancing building energy efficiency and promoting sustainable construction practices.

42 ENGINEERING↗

Turbo‐charging crop improvement: harnessing multiplex editing for polygenic trait engineering and beyond

Multiplex CRISPR editing has emerged as a transformative platform for plant genome engineering, enabling the simultaneous targeting of multiple genes, regulatory elements, or chromosomal regions. This approach is effective for dissecting gene family functions, addressing genetic redundancy, engineering polygenic traits, and accelerating trait stacking and de novo domestication. Its applications now extend beyond standard gene knockouts to include epigenetic and transcriptional regulation, chromosomal engineering, and transgene‐free editing. These capabilities are advancing crop improvement not only in annual species but also in more complex systems such as polyploids, undomesticated wild relatives, and species with long generation times. At the same time, multiplex editing presents technical challenges, including complex construct design and the need for robust, scalable mutation detection. We discuss current toolkits and recent innovations in vector architecture, such as promoter and scaffold engineering, that streamline workflows and enhance editing efficiency. High‐throughput sequencing technologies, including long‐read platforms, are improving the resolution of complex editing outcomes such as structural rearrangements—often missed by standard genotyping—when targeting repetitive or tandemly spaced loci. To fully realize the potential of multiplex genome engineering, there is growing demand for user‐friendly, synthetic biology‐compatible, and scalable computational workflows for gRNA design, construct assembly, and mutation analysis. Experimentally validated inducible or tissue‐specific promoters are also highly desirable for achieving spatiotemporal control. As these tools continue to evolve, multiplex CRISPR editing is poised to become a foundational technology of next‐generation crop improvement to address challenges in agriculture, sustainability, and climate resilience.

59 BASIC BIOLOGICAL SCIENCES↗

Biofuels for a sustainable future

Rapid increases of energy consumption and human dependency on fossil fuels have led to the accumulation of greenhouse gases and consequently, climate change. As such, major efforts have been taken to develop, test, and adopt clean renewable fuel alternatives. Production of bioethanol and biodiesel from crops is well developed, while other feedstock resources and processes have also shown high potential to provide efficient and cost-effective alternatives, such as landfill and plastic waste conversion, algal photosynthesis, as well as electrochemical carbon fixation. In addition, the downstream microbial fermentation can be further engineered to not only increase the product yield but also expand the chemical space of biofuels through the rational design and fine-tuning of biosynthetic pathways toward the realization of "designer fuels" and diverse future applications.

09 BIOMASS FUELS↗

A Hybrid Pathway to Biojet Fuel via 2,3-Butanediol

Production of biomass-derived sustainable alternative jet fuels (SAJF) has been considered as an important approach to decarbonize the aviation industry but still possesses various challenges in technology advancement, particularly in achieving high carbon efficiency. Here we report a hybrid pathway to SAJF from 2,3-butanediol (2,3-BDO), integrating biologically converting biomass to 2,3-BDO with catalytically upgrading of 2,3-BDO to jet-range hydrocarbons. This pathway is demonstrated to have a high carbon recovery to liquid hydrocarbons from corn stover (25–28%) (74–82% of the theoretical maximum efficiency). The catalytic conversion steps involve 2,3-BDO to C3+ olefins, oligomerization, and hydrogenation where the first two steps are the focus of this study. Under optimum reaction conditions (523 K, 115 kPa, 1.0 h-1 weight hourly space velocity), 2,3-BDO conversion and C3+ olefin selectivity are >97% and 94–98% during 40 h time on stream, respectively. To demonstrate the adaptability of this technology with bio-derived 2,3-BDO, we also investigated the impact of water and other organic coproducts (acetoin and acetic acid) inherited from the fermentation broth on the catalyst performance and product selectivities. We have shown that the catalyst can handle a significant amount of water in the liquid feed (40 wt% water/60 wt% 2,3-BDO) and maintain catalyst stability for ~40 h. Acetoin can be converted to similar C3+ olefins as 2,3-BDO with complete conversion of acetoin. Co-feeding 10 wt% acetoin with 2,3-BDO is found to have no impact on 2,3-BDO conversion, C3+ olefin selectivity, and catalyst stability. The utilization of organic coproduct like acetoin can help to improve overall carbon conversion efficiency when using real biomass-derived 2,3-BDO. On the other hand, the presence of 10 wt% acetic acid is shown to drastically inhibit methyl ethyl ketone (MEK) hydrogenation and butene oligomerization as revealed by the increased MEK and butene selectivities, implying the importance of separating organic acids when feeding bio-derived 2,3-BDO. The formed C3–C6 olefins from 2,3-BDO are further oligomerized over Amberlyst-36 catalyst to longer-chain hydrocarbons with >70 wt% jet-range hydrocarbons including predominantly iso-olefins/iso-paraffins. The overall carbon efficiency for the jet-range hydrocarbons is 19–22%, exceeding most of the reported biojet pathways, which makes it a promising approach for SAJF production.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Evaluating Material Design Principles for Calcium-Ion Mobility in Intercalation Cathodes

Multivalent-ion batteries offer an alternative to Li-based technologies, with the potential for greater sustainability, improved safety, and higher energy density, primarily due to their rechargeable system featuring a passivating metal anode. Although a system based on the Ca 2+ /Ca couple is particularly attractive given the low electrochemical plating potential of Ca 2+ , the remaining challenge for a viable rechargeable Ca battery is to identify Ca cathodes with fast ion transport. In this work, a high-throughput computational pipeline is adapted to (1) discover novel Ca cathodes in a largely unexplored space of empty intercalation hosts and (2) develop material design rules for Ca-ion mobility. One candidate from the screening, W 2 O 3 (PO 4 ) 2 , is confirmed to have a low Nudged Elastic Band (NEB) barrier of 168 meV within a one-dimensional (1D) ion percolation topology. This candidate is subsequently synthesized and electrochemically tested, achieving reversible Ca cycling with a capacity of 25 mA h/g. To further accelerate the screening for promising Ca intercalation electrodes, machine learning (ML) Random Forest (RF) and Extreme Gradient Boosting (XGB) classification models are created with local environment descriptors based on a large, structurally and chemically diverse dataset of minimum energy pathways, spanning over 5,000 density functional theory (DFT) site energy calculations. Accuracies of 92% are achieved, material design metrics are quantified, ML force-fields are leveraged in an accelerated iteration of the screening, and a total of 27 novel Ca cathode materials are highlighted for further investigation.

25 ENERGY STORAGE↗

RAVEN Theory Manual

RAVEN is a software framework able to perform parametric and stochastic analysis based on the response of complex system codes. The initial development was aimed at providing dynamic risk analysis capabilities to the thermohydraulic code RELAP-7, currently under development at Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose stochastic and uncertainty quantification platform, capable of communicating with any system code. In fact, the provided Application Programming Interfaces (APIs) allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by input files or via python interfaces. RAVEN is capable of investigating system response and explore input space using various sampling schemes such as Monte Carlo, grid, or Latin hypercube. However, RAVEN strength lies in its system feature discovery capabilities such as: constructing limit surfaces, separating regions of the input space leading to system failure, and using dynamic supervised learning techniques. The development of RAVEN started in 2012 when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework arose. RAVEN’s principal assignment is to provide the necessary software and algorithms in order to employ the concepts developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just to identify the frequency of an event potentially leading to a system failure, but the proximity (or lack thereof) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. peak pressure in a pipe) is exceeded under certain conditions. Most of the capabilities, implemented having RELAP-7 as a principal focus, are easily deployable to other system codes. For this reason, several side activates have been employed (e.g. RELAP5-3D, any MOOSE-based App, etc.) or are currently ongoing for coupling RAVEN with several different software. The aim of this document is to provide a set of commented examples that can help the user to become familiar with the RAVEN code usage.

97 MATHEMATICS AND COMPUTING↗

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗

Problems and Countermeasures of River Management in the Process of Rapid Urbanization in China

The rapid process of urbanization has led to water pollution, reduction of space areas and channel deposition. However, current river protection and management levels are not suitable for city development level and human demand. Therefore, these problems have not yet been solved. China is still in an era of rapid urbanization, which means that the influence of urbanization in rivers will increase in the future—and the task of river protection and management will be more arduous. In order to meet the challenges and opportunities brought by urbanization and promote the sustainable use and management of river, this study puts forward relevant suggestions on river protection and management, such as river management mechanisms, economic incentive instruments, technical support, transformation of development concepts, improving laws, regulations and policies and stimulating public participation.

54 ENVIRONMENTAL SCIENCES↗

Integrating science for water security governance

Hydrological extremes are intensifying globally, increasing the complexity of decisions required to ensure water security. Advances in hydrological science, modeling, and data systems have expanded the technical frontier of water research, yet uptake of scientific insights in policy and management decisions remains limited. This persistent science–policy gap is not primarily a failure of knowledge generation or robustness, but an institutional challenge shaped by how scientific and governance systems are organized, coordinated, and connected to support the effective use of scientific knowledge. These challenges are particularly pronounced in multi-level and transboundary water governance, where decisions span jurisdictions and require coordination across institutional and political boundaries. We synthesize research at the science–policy interface and evidence from water security initiatives to show how institutional arrangements, scientific tool development, and research practices enable or constrain the sustained use of scientific knowledge in water-security governance processes. Building on these insights, we develop ‘shared decision infrastructure’ as a framing to describe how scientific knowledge is embedded within the institutional, relational, and procedural arrangements that connect science to decision-making processes over time. We translate this framing into a practical intervention roadmap centered on institutional design, tool translation, sustained co-production, and outcome-oriented evaluation to support the integration of science into ongoing governance processes. By positioning science as shared decision infrastructure, the roadmap clarifies how researchers can design scientific efforts that support more coordinated, accountable, and adaptive water security decisions amid deepening uncertainty.

M whitney, Kristen [NASA Goddard Space Flight Cent↗

Modeling the effect of habitat availability and quality on endangered winter-run Chinook salmon ( Oncorhynchus tshawytscha ) production in the Sacramento Valley

Reconciliation between water uses and sustaining aquatic species populations requires an effort to identify and quantify essential habitat characteristics for ecosystem health and valuation methods to predict ecosystem response to restoration actions. This process is particularly challenging for anadromous fish species such as California's Sacramento River winter-run Chinook salmon, due to their limited geographic range and diverse life history habitat requirements. Tools, such as life-cycle models, are needed to manage population dynamics and quantify the composite effects of processes across space and time. Nevertheless, complex institutions can hinder result interpretation and communication, and limit model use in decision-making. This paper focuses on the federally endangered and endemic Sacramento River winter-run Chinook (Oncorhynchus tshawytscha) by developing a Winter-Run Habitat-based Population Model (WRHAP). Additionally, WRHAP is a conceptual, freshwater rearing stage model that includes alternative rearing habitats reported in the literature (e.g., floodplains, off-channel and tributaries), defines rules of habitat use based on instream conditions, and incorporates a juvenile growth module that combines bioenergetics modeling with empirical growth rates. Model outputs reasonably follow observed out-migration patterns and provide a realistic smolt size distribution arriving at the San Francisco Bay. This effort demonstrates the importance of currently “non-critical” habitats (as defined by the Endangered Species Act) for juvenile development, with floodplain habitat contributing to a quarter of out-migrating biomass (despite < 18% availability and <10% of total rearing days), and off-channel growth being one of the most sensitive parameters (explaining ~13% of average juvenile weight variance). The model shows the utility of a simple population model to explore relationships between habitat quality/quantity and juvenile development, and to assist water/environmental management and decision-making processes focused on species recovery.

54 ENVIRONMENTAL SCIENCES↗

Milligrams to kilograms: making microbes work at scale

Energy is one of the most complex fields of study and an issue that influences nearly every aspect of modern life. Over the past century, combustion of fossil fuels, particularly in the transportation sector, has been the dominant form of energy release. Refining of petroleum and natural gas into liquid transportation fuels is also the centerpiece of the modern chemical industry used to produce materials, solvents, and other consumer goods. In the face of global climate change, the world is searching for alternative, sustainable means of producing energy carriers and chemical building blocks. The use of biofuels in engines predates modern refinery optimization and today represents a small but significant fraction of liquid transportation fuels burnt each year. Similarly, white biotechnology has been used to produce many natural products through fermentation. The evolution of recombinant DNA technology into modern synthetic biology has expanded the scope of biofuels and bioproducts that can be made by biocatalysts. This opinion examines the current trends in this research space, highlighting the substantial growth in computational tools and the growing influence of renewable electricity in the design of metabolic engineering strategies. In short, advanced biofuel and bioproduct synthesis remains a vibrant and critically important field of study whose focus is shifting away from the conversion of lignocellulosic biomass towards a broader consideration of how to reduce carbon dioxide to fuels and chemical products.

59 BASIC BIOLOGICAL SCIENCES↗

Recent progress in the synthesis of advanced biofuel and bioproducts

Energy is one of the most complex fields of study and an issue that influences nearly every aspect of modern life. Over the past century, combustion of fossil fuels, particularly in the transportation sector, has been the dominant form of energy release. Refining of petroleum and natural gas into liquid transportation fuels is also the centerpiece of the modern chemical industry used to produce materials, solvents, and other consumer goods. In the face of global climate change, the world is searching for alternative, sustainable means of producing energy carriers and chemical building blocks. The use of biofuels in engines predates modern refinery optimization and today represents a small but significant fraction of liquid transportation fuels burnt each year. Similarly, white biotechnology has been used to produce many natural products through fermentation. The evolution of recombinant DNA technology into modern synthetic biology has expanded the scope of biofuels and bioproducts that can be made by biocatalysts. Furthermore, this opinion examines the current trends in this research space, highlighting the substantial growth in computational tools and the growing influence of renewable electricity in the design of metabolic engineering strategies. In short, advanced biofuel and bioproduct synthesis remains a vibrant and critically important field of study whose focus is shifting away from the conversion of lignocellulosic biomass toward a broader consideration of how to reduce carbon dioxide to fuels and chemical products.

09 BIOMASS FUELS↗

Bioplastic design using multitask deep neural networks

Abstract Non-degradable plastic waste jeopardizes our environment, yet our modern lifestyle and current technologies are impossible to sustain without plastics. Bio-synthesized and biodegradable alternatives such as polyhydroxyalkanoates (PHAs) have the potential to replace large portions of the world’s plastic supply with cradle-to-cradle materials, but their chemical complexity and diversity limit traditional resource-intensive experimentation. Here, we develop multitask deep neural network property predictors using available experimental data for a diverse set of nearly 23,000 homo- and copolymer chemistries. Using the predictors, we identify 14 PHA-based bioplastics from a search space of almost 1.4 million candidates which could serve as potential replacements for seven petroleum-based commodity plastics that account for 75% of the world’s yearly plastic production. We also discuss possible synthesis routes for the identified promising materials.

36 MATERIALS SCIENCE↗

Enhanced Laplace Pressures for Functional Surfaces: Wicking, Switchability, and Selectivity

Abstract Wetting functionalities of rough surfaces are largely determined by the Laplace pressure generated across liquid–gas interfaces formed within surface structures. Typically, rough wetting surfaces create negative Laplace pressures, enabling capillary wicking, while rough non‐wetting surfaces create positive Laplace pressures, exhibiting fluid repellency. Here, with microfabricated reentrant structures, it is shown that the same surface can exhibit either a negative or positive Laplace pressure, regardless of its intrinsic wettability. This material‐independent Laplace pressure duality enables or enhances a range of wetting functionalities including wicking, switchability, and selectivity. On the same surface, capillary rise, capillary dip, and the combination of the two which leads to further enhancement of the total sustainable capillary height and Laplace pressure, the driving force for wicking is demonstrated. Further, active switching of wetting states between the hemiwicking and the repellent Cassie state on reentrant structures is shown. Moreover, with a water‐hexane mixture system, selective wetting of reentrant structures are demonstrated, that is, water can be selectively wicked or repelled in the presence of hexane, and vice versa. These functionalities are achieved, which would typically require complex chemical coatings, solely using surface structures, thus largely expanding the design space for a wide range of thermofluidic applications.

36 MATERIALS SCIENCE↗

A comprehensive review on the loss of wellbore integrity due to cement failure and available remedial methods

With the recent abrupt fluctuations in oil pricing and the need of complying with environmental and social requirements, nowadays it is an urgent call for the oil and gas industry to produce the hydrocarbon without any loss as well as in a safe manner. Cements are placed in the annular space of casing to provide zonal isolation in between wellbore and surface during the operational life cycle of the well or even after the abandonment. But this is not what happens most of the time. Cement degrades or loses its integrity through debonding either from the casing or formation and generates cracks or fractures due to varied reasons throughout the life of the well. Multiple causes contribute to the loss of wellbore integrity – either by physical, mechanical, or chemical processes. These failures lead to sustained casing pressure (SCP) and contamination of surrounding environment. To combat this issue or to restore the well integrity, multiple remedial actions have also been either implemented in the industry or proposed based on experimental research to prevent the damage or to seal the leakage in the cement sheath. Here, this paper will provide an extensive review of the underlying reasons of cement failure and the available remedial actions to minimize the loss of well integrity issue. These information are not only useful to know about the different corrective options available for us to implement in industry but also it will provide us a knowledge base regarding how we can enhance the performance of the exiting systems to battle the cement integrity problem more efficiently.

02 PETROLEUM↗