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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 523 records · Page 29

Make Selenium Reactive Again: Activating Elemental Selenium for Synthesis of Metal Selenides Ranging from Nanocrystals to Large Single Crystals

The inertness of elemental selenium is a significant obstacle in the synthesis of selenium-containing materials at low reaction temperatures. Over the years, several recipes have been developed to overcome this hurdle; however, most of the methods are associated with the use of highly toxic, expensive, and environmentally harmful reagents. As such, there is an increasing demand for the design of cheap, stable, and nontoxic reactive selenium precursors usable in the low-temperature synthesis of transition metal selenides with vast applications in nanotechnology, thermoelectrics, and superconductors. Herein, a novel synthetic route has been developed for activating elemental selenium by using a solvothermal approach. By comprehensive 77 Se NMR, Raman, and infrared spectroscopies and gas chromatography–mass spectrometry, we show that the activated Se solution contained HSe – , [Se–Se] 2– , and Se 2– ions, as well as dialkyl selenide (R 2 Se) and dialkyl diselenide (R–Se–Se–R) species in dynamic equilibrium. This also corresponded to the first observation of naked Se 2 2– in solution. The versatility of the developed Se precursor was demonstrated by the successful synthesis of (i) the polycrystalline room-temperature modification of the β-Ag 2 Se thermoelectric material; (ii) large single crystals of superconducting β-FeSe; (iii) CdSe nanocrystals with different particle sizes (3–10 nm); (iv) nanosheets of PtSe 2 ; and (v) mono- and dibenzyl selenides and diselenides at room temperature. In conclusion, The simplicity and diversity of the developed Se activation method holds promise for applied and fundamental research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemical Insights into PbSe– x %HgSe: High Power Factor and Improved Thermoelectric Performance by Alloying with Discordant Atoms

Thermoelectric generators can convert heat directly into usable electric power but suffer from low efficiencies and high costs, which have hindered wide-scale applications. Accordingly, an important goal in the field of thermoelectricity is to develop new high performance materials that are composed of more earth-abundant elements. The best systems for midtemperature power generation rely on heavily doped PbTe, but the Te in these materials is scarce in the Earth’s crust. PbSe is emerging as a less expensive alternative to PbTe, although it displays inferior performance due to a considerably smaller power factor S 2 σ, where S is the Seebeck coefficient and σ is electrical conductivity. In this report we present a new p-type PbSe system, Pb 0.98 Na 0.02 Se–x%HgSe, which yields a very high power factor of ~20 μW·cm –1 ·K –2 at 963 K when x = 2, a 15% improvement over the best performing PbSe–x%MSe materials. The enhancement is attributed to a combination of high carrier mobility and the early onset of band convergence in the Hg-alloyed samples (~550 K), which results in a significant increase in the Seebeck coefficient. Interestingly, we find that the Hg 2+ cations sit at an off-centered position within the PbSe lattice, and we dub the displaced Hg atoms “discordant”. DFT calculations indicate that this feature plays a role in lowering thermal conductivity, and we believe that this insight may inspire new design criteria for engineering high performance thermoelectric materials. The high power factor combined with a decrease in thermal conductivity gives a high figure of merit ZT of 1.7 at 970 K, the highest value reported for p-type PbSe to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Symmetry Breaking in Tetrahedral Chiral Plasmonic Nanoparticle Assemblies

Self-assembled plasmonic structures combine the specificity and tunability of chemical synthesis with collective plasmonic properties. In this work we systematically explore the effects of symmetry breaking on the chiroptical response of an assembly of plasmonic nanoparticles using simulation. The design is based on a tetrahedral nanoparticle frame with two different types of nanoparticles, where chirality is induced by targeted stimuli that change the distance along one edge of the assembly. Here, we show that the intensity, spectral position, and handedness of the CD response are tunable with small structural changes, making it usable as a nanoscale plasmonic ruler. We then build upon this initial design to show that the symmetry breaking principle may also be used to design a chiral pyramid using a mixture of different nanoparticle materials, which affords tunability over a broad spectral range, and retrieves nanoscale conformational changes over a range of length scales.

36 MATERIALS SCIENCE↗

River Regulation Alleviates the Impacts of Climate Change on US Thermoelectricity Production

Climate change and anthropogenic activities can both influence stream temperature, which is a critical indicator of thermoelectric power generation potential. Previous studies emphasized the vulnerability of power-generation systems to climate warming (ref 1, 2). Despite the fact that two-thirds of the global rivers are regulated by dams (ref 3), the relative impacts of water management and climate change on stream temperature and thermoelectric production have not yet been evaluated. Using an integrated modeling system applied to the conterminous United States, simulations confirm the dominant role of climate change in shaping the future trends of stream temperature. However, water management, reservoir regulation in particular, can mitigate the stream temperature warming and reduce the frequency and magnitude of extreme high stream temperatures through redistribution of the seasonal streamflow. Moreover, water management can alleviate the loss of power plant usable capacity from climate change to the level of reduced warming from emission mitigation. By regulating the flow and temperature regimes, water management is a promising adaptation measure to alleviate climate change induced effects in the water-energy nexus.

Zhang, Xiao↗

Quantifying the Impact of Lagged Hydrological Responses on the Effectiveness of Groundwater Conservation

Many irrigated agricultural areas seek to prolong the lifetime of their groundwater resources by reducing pumping. However, it is unclear how lagged responses, such as reduced groundwater recharge caused by more efficient irrigation, may impact the long-term effectiveness of conservation initiatives. Here, we use a variably saturated, simplified surrogate groundwater model to: 1) analyze aquifer responses to pumping reductions, 2) quantify time lags between reductions and groundwater level responses, and 3) identify the physical controls on lagged responses. We explore a range of plausible model parameters for an area of the High Plains Aquifer (USA) where stakeholder-driven conservation has slowed groundwater depletion. We identify two types of lagged responses that reduce the long-term effectiveness of groundwater conservation, recharge-dominated and lateral-flow-dominated, with vertical hydraulic conductivity (K Z ) the major controlling variable. When high K z allows percolation to reach the aquifer, more efficient irrigation reduces groundwater recharge. By contrast, when low K z impedes vertical flow, short term changes in recharge are negligible, but pumping reductions alter the lateral flow between the groundwater conservation area and the surrounding regions (lateral-flow-dominated response). For the modeled area, we found that a pumping reduction of 30% resulted in median usable lifetime extensions of 20 or 25 years, depending on the dominant lagged response mechanism (recharge- vs. lateral-flow-dominated). These estimates are far shorter than estimates that do not account for lagged responses. To conclude, results indicate that conservation-based pumping reductions can extend aquifer lifetimes, but lagged responses can create a sizable difference between the initially perceived and actual long-term effectiveness.

54 ENVIRONMENTAL SCIENCES↗

Research to Confront Climate Change Complexity: Intersectionality, Integration, and Innovative Governance

Abstract Climate impacts increasingly unfold in interlinked systems of people, nature, and infrastructure. The cascading consequences are revealing sometimes surprising connections across sectors and regions, and prospects for climate responses also depend on complex, difficult‐to‐understand interactions. In this commentary, we build on the innovations of the United States Fifth National Climate Assessment to suggest a framework for understanding and responding to complex climate challenges. This approach involves: (a) integration of disciplines and expertise to understand how intersectionality shapes complex climate impacts and the wide‐ranging effects of climate responses, (b) collaborations among diverse knowledge holders to improve responses and better encompass intersectionality, and (c) sustained experimentation with and learning about governance approaches capable of handling the complexity of climate change. Together, these three pillars underscore that usability of climate‐relevant knowledge requires transdisciplinary coordination of research and practice. We outline actionable steps for climate research to incorporate intersectionality, integration, and innovative governance, as is increasingly necessary for confronting climate complexity and sustaining equitable, ideally vibrant climate futures.

54 ENVIRONMENTAL SCIENCES↗

Vulnerability of US thermoelectric power generation to climate change when incorporating state-level environmental regulations

This study explores the interactions between climate and thermoelectric generation in the U.S. by coupling an Earth System Model with a thermoelectric power generation model. We validated model simulations of power production for selected power plants (~44% of existing thermoelectric capacity) against reported values. In addition, we projected future usable capacity for existing power plants under two different climate change scenarios. Results indicate that climate change alone may reduce average thermoelectric generating capacity by 2%-3% by the 2060s. Reductions up to 12% are expected if environmental requirements are enforced without waivers for thermal variation. This study concludes that the impact of climate change on the U.S. thermoelectric power system is less than previous estimates due to an inclusion of a spatially-disaggregated representation of environmental regulations and provisional variances that temporarily relieve power plants from permit requirements. This work highlights the significance of accounting for legal constructs in which the operation of power plants are managed, and underscores the effects of provisional variances in addition to environmental requirements.

climate change↗

Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functions

Abstract Despite recent advances in high-throughput combinatorial mutagenesis assays, the number of labeled sequences available to predict molecular functions has remained small for the vastness of the sequence space combined with the ruggedness of many fitness functions. While deep neural networks (DNNs) can capture high-order epistatic interactions among the mutational sites, they tend to overfit to the small number of labeled sequences available for training. Here, we developed Epistatic Net (EN), a method for spectral regularization of DNNs that exploits evidence that epistatic interactions in many fitness functions are sparse. We built a scalable extension of EN, usable for larger sequences, which enables spectral regularization using fast sparse recovery algorithms informed by coding theory. Results on several biological landscapes show that EN consistently improves the prediction accuracy of DNNs and enables them to outperform competing models which assume other priors. EN estimates the higher-order epistatic interactions of DNNs trained on massive sequence spaces-a computational problem that otherwise takes years to solve.

Aghazadeh, Amirali (ORCID:0000000302230873)↗

Shifts in evolutionary lability underlie independent gains and losses of root-nodule symbiosis in a single clade of plants

Abstract Root nodule symbiosis (RNS) is a complex trait that enables plants to access atmospheric nitrogen converted into usable forms through a mutualistic relationship with soil bacteria. Pinpointing the evolutionary origins of RNS is critical for understanding its genetic basis, but building this evolutionary context is complicated by data limitations and the intermittent presence of RNS in a single clade of ca. 30,000 species of flowering plants, i.e., the nitrogen-fixing clade (NFC). We developed the most extensive de novo phylogeny for the NFC and an RNS trait database to reconstruct the evolution of RNS. Our analysis identifies evolutionary rate heterogeneity associated with a two-step process: An ancestral precursor state transitioned to a more labile state from which RNS was rapidly gained at multiple points in the NFC. We illustrate how a two-step process could explain multiple independent gains and losses of RNS, contrary to recent hypotheses suggesting one gain and numerous losses, and suggest a broader phylogenetic and genetic scope may be required for genome-phenome mapping.

59 BASIC BIOLOGICAL SCIENCES↗

Operating advanced scientific instruments with AI agents that learn on the job

Advanced scientific user facilities, such as next generation X-ray light sources and self-driving laboratories, are revolutionizing scientific discovery by automating routine tasks and enabling rapid experimentation and characterizations. However, these facilities must continuously evolve to support new experimental workflows, adapt to diverse user projects, and meet growing demands for more intricate instruments and experiments. This continuous development introduces significant operational complexity, necessitating a focus on usability, reproducibility, and intuitive human-instrument interaction. In this work, we explore the integration of agentic AI, powered by Large Language Models (LLMs), as a transformative tool to achieve this goal. We present our approach to developing a human-in-the-loop pipeline for operating advanced instruments including an X-ray nanoprobe beamline and an autonomous robotic station dedicated to the design and characterization of materials. Specifically, we evaluate the potential of various LLMs as trainable scientific assistants for orchestrating complex, multi-task workflows, which also include multimodal data, optimizing their performance through optional human input and iterative learning. We demonstrate the ability of AI agents to bridge the gap between advanced automation and user-friendly operation, paving the way for more adaptable and intelligent scientific facilities.

Large Language Models↗

Efficient thermal management of Li-ion batteries with a passive interfacial thermal regulator based on a shape memory alloy [A passive interfacial thermal regulator based on shape memory alloy and its application to battery thermal management]

The poor performance of lithium-ion batteries in extreme temperatures is hindering their wider adoption in the energy sector. A fundamental challenge in battery thermal management systems (BTMSs) is that hot and cold environments pose opposite requirements: thermal transmission at high temperature for battery cooling, and thermal isolation at low temperature to retain the batteries’ internally generated heat, leading to an inevitable compromise of either hot or cold performances. Here, we demonstrate a thermal regulator that adjusts its thermal conductance as a function of the temperature, just as desired for the BTMS. Without any external logic control, this thermal regulator increases battery capacity by a factor of 3 at an ambient temperature (T ambient ) of -20 °C in comparison to a baseline BTMS that is always thermally conducting, while also limiting the battery temperature rise to 5 °C in a very hot environment (T ambient = 45 °C) to ensure safety. The result expands the usability of lithium-ion batteries in extreme environments and opens up new applications of thermally functional devices.

25 ENERGY STORAGE↗

Assessing cathode–electrolyte interphases in batteries

The cathode-electrolyte interphase plays a pivotal role in determining the usable capacity and cycling stability of electrochemical cells, yet it is overshadowed by its counterpart, the solid-electrolyte interphase. This is primarily due to the prevalence of side reactions, particularly at low potentials on the negative electrode, especially in state-of-the-art Li-ion batteries where the charge cutoff voltage is limited. However, as the quest for high-energy battery technologies intensifies, there is a pressing need to advance the study of cathode-electrolyte interphase properties. Here, we present a comprehensive approach to analyse the cathode-electrolyte interphase in battery systems. We underscore the importance of employing model cathode materials and coin cell protocols to establish baseline performance. Additionally, we delve into the factors behind the inconsistent and occasionally controversial findings related to the cathode-electrolyte interphase. In conclusion, we also address the challenges and opportunities in characterizing and simulating the cathode-electrolyte interphase, offering potential solutions to enhance its relevance to real-world applications.

25 ENERGY STORAGE↗

The challenges and opportunities of battery-powered flight

Aircraft, and the aviation ecosystem in which they operate, are shaped by complex trades among technical requirements, economics and environmental concerns, all built on a foundation of safety. This Perspective explores the requirements of battery-powered aircraft and the chemistries that hold promise to enable them. The difference between flight and terrestrial needs and chemistries are highlighted. Safe, usable specific energy rather than cost is the major constraint for aviation. We conclude that battery packs suitable for flight with specific energy approaching 600 kilowatt hours per kilogram may be achievable in the next decade given sufficient investment targeted at aeronautical applications.

25 ENERGY STORAGE↗

Mitochondrial ATP generation is more proteome efficient than glycolysis

Metabolic efficiency profoundly influences organismal fitness. Nonphotosynthetic organisms, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. Although respiration is more energy efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (that is, faster). Through quantitative flux analysis and proteomics, we find, however, that mitochondrial respiration is actually more proteome efficient than aerobic glycolysis. This is shown across yeast strains, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which promotes hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth but outgrow respiratory cells during oxygen limitation. Here, we accordingly propose that aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metagenome-assembled genome extraction and analysis from microbiomes using KBase

Uncultivated Bacteria and Archaea account for the vast majority of species on Earth, but obtaining their genomes directly from the environment, using shotgun sequencing, has only become possible recently. In order to realize the hope of capturing Earth’s microbial genetic complement and to facilitate the investigation of the functional roles of specific lineages in a given ecosystem, technologies that accelerate the recovery of high-quality genomes are necessary. We present a series of analysis steps and data products for the extraction of high-quality metagenome-assembled genomes (MAGs) from microbiomes using the U.S. Department of Energy Systems Biology Knowledgebase (KBase) platform (http://www.kbase.us/). Overall, these steps take about a day to obtain extracted genomes when starting from smaller environmental shotgun read libraries, or up to about a week from larger libraries. In KBase, the process is end-to-end, allowing a user to go from the initial sequencing reads all the way through to MAGs, which can then be analyzed with other KBase capabilities such as phylogenetic placement, functional assignment, metabolic modeling, pangenome functional profiling, RNA-Seq and others. While portions of such capabilities are available individually from other resources, the combination of the intuitive usability, data interoperability and integration of tools in a freely available computational resource makes KBase a powerful platform for obtaining MAGs from microbiomes. While this workflow offers tools for each of the key steps in the genome extraction process, it also provides a scaffold that can be easily extended with additional MAG recovery and analysis tools, via the KBase software development kit (SDK).

59 BASIC BIOLOGICAL SCIENCES↗

Datasets for characterizing extreme events relevant to hydrologic design over the conterminous United States

Despite the close linkage between extreme floods and snowmelt, particularly through rain-on-snow (ROS), hydrologic infrastructure is mostly designed based on standard precipitation Intensity-Duration-Frequency curves (PREC-IDF) that neglect snow processes in runoff generation. For snow-dominated regions, such simplification could result in substantial errors in estimating extreme events and infrastructure design risk. To address this long-standing problem, we applied the Next Generation IDF (NG-IDF) technique to estimate design basis extreme events for different durations and return periods in the conterminous United States (CONUS) to distinctly represent the contribution of rain, snowmelt, and ROS events to the amount of water reaching the land surface. A suite of datasets were developed to characterize the magnitude, trend, seasonality, and dominant mechanism of extreme events for over 200,000 locations. Infrastructure design risk associated with the use of PREC-IDF was estimated. Accuracy of the model simulations used in the analyses was confirmed by long-term snow data at over 200 Snowpack Telemetry stations. The presented spatially continuous datasets are readily usable and instrumental for supporting site-specific infrastructure design.

54 ENVIRONMENTAL SCIENCES↗

An open source knowledge graph ecosystem for the life sciences

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. However, tackling complex biomedical integration problems requires flexibility in the way knowledge is modeled. Moreover, existing KG construction methods provide robust tooling at the cost of fixed or limited choices among knowledge representation models. PheKnowLator (Phenotype Knowledge Translator) is a semantic ecosystem for automating the FAIR (Findable, Accessible, Interoperable, and Reusable) construction of ontologically grounded KGs with fully customizable knowledge representation. The ecosystem includes KG construction resources (e.g., data preparation APIs), analysis tools (e.g., SPARQL endpoint resources and abstraction algorithms), and benchmarks (e.g., prebuilt KGs). We evaluated the ecosystem by systematically comparing it to existing open-source KG construction methods and by analyzing its computational performance when used to construct 12 different large-scale KGs. With flexible knowledge representation, PheKnowLator enables fully customizable KGs without compromising performance or usability.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗