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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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Generalized Relationship Linking Water Balance and Vegetation Productivity across Site-to-Regional Scales
Evapotranspiration (ET) is a pivotal component in catchment-scale water balance and is essential for informed watershed management. Nevertheless, uncertainties in ET observation or modeling have been hindering effective water resources management. This study addresses this gap by establishing a robust, generalized linear relationship between ET and gross primary productivity (GPP) at the catchment scale. We test the linearity of the relationships between monthly GPP and ET data at 380 near-natural catchments across various climatic and landscape conditions in the contiguous U.S., yielding Pearson’s r ≥ 0.6 for 97% of the 380 catchments. We then develop a regionalization strategy to parameterize this GPP-ET relationship at the catchment scale by identifying and utilizing the linkages between the parameter values and extensively available hydroclimatic and landscape data. We demonstrate the efficacy of the proposed GPP-ET relationship and parameter regionalization strategy by their combined predictive capacity, where the predicted monthly GPP matches well with remote-sensing-based GPP product, achieving Kling-Gupta Efficient (KGE) values ≥ 0.5 for 92% of the catchments. In addition, we verify the relationship and its parameter regionalization at 35 AmeriFlux sites with KGE ≥ 0.5 for 25 sites, suggesting that the new relationship is transferable across the site, catchment, and regional scales. Furthermore, our findings are valuable for improving remote-sensing-based estimation of monthly ET and diagnosing coupled water–carbon simulations in land surface and Earth system models.
Phase change materials for thermal energy storage: A perspective on linking phonon physics to performance
Thermal energy storage is being actively investigated for grid, industrial, and building applications for realizing an all-renewable energy world. Phase change materials (PCMs), which are commonly used in thermal energy storage applications, are difficult to design because they require excellent energy density and thermal transport, both of which are difficult to predict from simple physics-based models. In this Perspective, we describe recent advances in the understanding of the equilibrium and transport properties of PCM materials that can help accelerate technology development. We then emphasize how the microscopic phonon picture of both liquids and solids enables a better understanding of novel PCM systems and their predictive power. Here, we then show how this microscopic picture can be used to understand kinetic processes, such as supercooling, and how it can impact the thermal power output in thermal energy storage systems.
Revisiting the link between magnetic properties and chemisorption at graphene nanoribbon zigzag edge
Graphene has received tremendous interest in both chemical and physical fields. Among different edges of the graphene system, the zigzag edge terminated graphene nanoribbons (ZGNRs) show unique magnetic properties in the antiferromagnetic (AFM) state. However, to date, the understanding of ZGNR chemical properties is mainly based on the partial radical concept, and in previous studies, the energy differences between the ferromagnetic (FM) and AFM states are smaller than experimental evidence. Here, we report that the strongly constrained and appropriately normed functional gives a significantly larger energy difference, which matches the experimental observation. Furthermore, utilizing the energetics in the large difference case, we propose a conceptual supplement to the previous partial radical concept: the overall stabilization of the AFM state compared to the nonmagnetic (NM) state consists of two parts that affect the adsorption energy conversely. The NM-FM energy differences will strengthen the adsorption, being in line with the previous partial radical concept. The FM-AFM energy differences will instead weaken the adsorption. Here, we perform calculations of H, OH, and LiS radical adsorption energies on ZGNRs to show that this weakening effect is numerically non-negligible: at least a ~0.2 eV difference in the adsorption energies is found. We expect that this refinement of the partial radical concept can provide a more comprehensive understanding of the chemical properties of ZGNRs. The differences in adsorption energies for the H, OH, and LiS radicals found here lead to significant changes in the predicted reactivity of the ZGNR models.
Learning effective stochastic differential equations from microscopic simulations: Linking stochastic numerics to deep learning
We identify effective stochastic differential equations (SDEs) for coarse observables of fine-grained particle- or agent-based simulations; these SDEs then provide useful coarse surrogate models of the fine scale dynamics. We approximate the drift and diffusivity functions in these effective SDEs through neural networks, which can be thought of as effective stochastic ResNets. The loss function is inspired by, and embodies, the structure of established stochastic numerical integrators (here, Euler–Maruyama and Milstein); our approximations can thus benefit from backward error analysis of these underlying numerical schemes. They also lend themselves naturally to “physics-informed” gray-box identification when approximate coarse models, such as mean field equations, are available. Existing numerical integration schemes for Langevin-type equations and for stochastic partial differential equations can also be used for training; we demonstrate this on a stochastically forced oscillator and the stochastic wave equation. Our approach does not require long trajectories, works on scattered snapshot data, and is designed to naturally handle different time steps per snapshot. We consider both the case where the coarse collective observables are known in advance, as well as the case where they must be found in a data-driven manner.
Site-specific electronic structure of covalently linked bimetallic dyads from nitrogen K-edge x-ray absorption spectroscopy
A nitrogen K-edge x-ray absorption near-edge structure (XANES) survey is presented for tetrapyrido[3,2-a:',3'-c:3'',2''-h:2''',3'''-j]phenazine (tpphz)-bridged bimetallic assemblies that couple chromophore and catalyst transition metal complexes for light driven catalysis, as well as their individual molecular constituents. We demonstrate the high N site sensitivity of the N pre-edge XANES features, which are energetically well-separated for the phenazine bridge N atoms and for the individual metal-bound N atoms of the inner coordination sphere ligands. By comparison with the time-dependent density functional theory calculated spectra, we determine the origins of these distinguishable spectral features. We find that metal coordination generates large shifts toward higher energy for the metal-bound N atoms, with increasing shift for 3d < 4d < 5d metal bonding. This is attributed to increasing ligand-to-metal σ donation that increases the effective charge of the bound N atoms and stabilizes the N 1s core electrons. In contrast, the phenazine bridge N pre-edge peak is found at a lower energy due to stabilization of the low energy electron accepting orbital localized on the phenazine motif. While no sensitivity to ground state electronic coupling between the individual molecular subunits was observed, the spectra are sensitive to structural distortions of the tpphz bridge. Here these results demonstrate N K-edge XANES as a local probe of electronic structure in large bridging ligand motifs, able to distinctly investigate the ligand-centered orbitals involved in metal-to-ligand and ligand-to-ligand electron transfer following light absorption.
Interaction-based ion selectivity exhibited by self-assembled, cross-linked zwitterionic copolymer membranes
Significance The separation of ions is challenging yet crucial for providing access to safe water resources as well as recovering valuable ions from water and wastewater. Yet, membranes rarely exhibit selectivity between ions of similar charge and size. We demonstrate that membranes, prepared by a fully scalable method that uses self-assembling zwitterionic copolymers, exhibit exceptional selectivity between salt anions of similar size and charge. We show that this unusual capability is derived from selective zwitterion–ion interactions occurring within the nanochannels, similarly to biological ion channels. We further demonstrate these membranes exhibit Cl − /F − permselectivity more than twice the values reported in previous studies, with applications in treating groundwater streams to prevent fluorosis and in wastewater treatment.
Redox signaling by glutathione peroxidase 2 links vascular modulation to metabolic plasticity of breast cancer
Redox regulation of breast cancer underlies malignant progression. Loss of the antioxidant glutathione peroxidase 2 in breast cancer cells increases reactive oxygen species, thereby activating hypoxia inducible factor-α (HIF1α) signaling. This in turn causes vascular malfunction, resulting in hypoxia and metabolic heterogeneity. HIF1α suppresses oxidative phosphorylation and stimulates glycolysis (the Warburg effect) in most of the tumor, except for one cancer subpopulation, which was capable of using both metabolic modalities. Hence, adopting a hybrid metabolic state may allow tumor cells to survive under aerobic or hypoxic conditions, a vulnerability that may be exploited for therapeutic targeting by either metabolic or redox-based strategies.
Controlling swelling in mixed transport polymers through alkyl side-chain physical cross-linking
Semiconducting conjugated polymers bearing glycol side chains can simultaneously transport both electronic and ionic charges with high charge mobilities, making them ideal electrode materials for a range of bioelectronic devices. However, heavily glycolated conjugated polymer films have been observed to swell irreversibly when subjected to an electrochemical bias in an aqueous electrolyte. The excessive swelling can lead to the degradation of their microstructure, and subsequently reduced device performance. An effective strategy to control polymer film swelling is to copolymerize glycolated repeat units with a fraction of monomers bearing alkyl side chains, although the microscopic mechanism that constrains swelling is unknown. Here we investigate, experimentally and computationally, a series of archetypal mixed transporting copolymers with varying ratios of glycolated and alkylated repeat units. Experimentally we observe that exchanging 10% of the glycol side chains for alkyl leads to significantly reduced film swelling and an increase in electrochemical stability. Through molecular dynamics simulation of the amorphous phase of the materials, we observe the formation of polymer networks mediated by alkyl side-chain interactions. When in the presence of water, the network becomes increasingly connected, counteracting the volumetric expansion of the polymer film.
Linked nitrogen and carbon dynamics reveal distinct pools and patterns in a deep, weathered bedrock rhizosphere
Nitrogen is one of the most limiting nutrients to forest productivity worldwide. Recently, it has been established that diverse ecosystems source a substantial fraction of their water from weathered bedrock, leading to questions about whether root-driven nitrogen cycling extends into weathered bedrock as well. In this study, we specifically examined nitrogen dynamics using specialized instrumentation distributed across a 16 m weathered bedrock vadose zone (WBVZ) underlying an old growth forest in northern California where the rhizosphere—composed of plant roots and their associated microbiome—extends meters into rock. We documented total dissolved nitrogen (TDN), dissolved organic carbon (DOC), inorganic nitrogen (ammonium and nitrate), and CO 2 and O 2 gases every 1.5 m to 16 m depth for 2 y. We found that TDN concentrations increased with depth, were an order of magnitude greater at 15 m than in the upper 30 cm, and that the majority of TDN throughout the weathered bedrock vadose zone was organic. We also found that TDN concentrations are influenced by depth, season, and interannual precipitation patterns. Carbon isotope composition of the DOC suggests that dissolved organic matter in the WBVZ is primarily derived from plant sources, and not the nitrogen-rich bedrock. We conclude that nitrogen dynamics in the WBVZ may be driven, in part, by an active rhizosphere, meters below the base of soil, and we argue that weathered bedrock horizons may play a key role in C-N cycling in ecosystems with deep-rooted plants.
A quantitative imaging framework for lithium morphology: Linking deposition uniformity to cycle stability in lithium metal batteries
Characterizing the morphology of lithium (Li) is crucial for developing long-lasting lithium metal batteries. It is well established that more uniform Li deposition correlates with better cell performance. Li morphology is often characterized through qualitative analysis of scanning electron microscopy (SEM) images; however, there are no widely accepted metrics to quantitatively describe deposition uniformity. Here, we propose a framework to quantify uniformity through SEM image analysis via the index of dispersion (ID) metric, which is defined and presented in the context of Li metal batteries. We also explore experimental impacts of sampling protocols onIDmeasurements. Our results demonstrate that theIDmetric is highly sensitive to variations in deposition uniformity, including the coexistence and uniformity of multiple morphologies, uniformity within a single morphology, and particle size distribution uniformity. Furthermore, it is demonstrated that uniformity, as measured by theID, can be related to the average potential of Li||Li symmetric cells over cycling. Higher capacity cycling leads to more pronounced changes in bothIDand average cell potential. Local minima/maxima are found consistently in bothIDand average cell potential immediately before cells short-circuit, which we suggest may indicate a collapse of the microstructure prior to failure. We put forward this framework as a more robust approach to quantify Li deposition uniformity, advancing the development of Li metal batteries that are safer and longer lasting.
An unusual Co–S bond links B 12 chaperones in an interprotein complex
Chaperones in trafficking pathways ensure specificity of transition metal loading and protection against adventitious side reactions. In B 12 , an essential cofactor for humans, a cobalt ion is coordinated to a >1.3 kDa tetrapyrrolic scaffold, posing logistical challenges for its translocation. In this study, we report the 3.4 Å crystal structure of the human MMACHC and MMADHC B 12 chaperones, tethered via a rarely seen covalent cobalt–sulfur bond. B 12 is bound in the base-off state to MMACHC, with Cys-261 on MMADHC serving as the upper axial ligand; the lower-axial position is vacant. The propensity of thiolato-cobalamin derivatives bound to MMACHC to undergo spontaneous decomposition via general acid catalysis or reduction/oxidation chemistry is averted in the interprotein complex with MMADHC. An exposed face in the complex suggests an exit route for B 12 . No known clinical variants localize to the interprotein interface, consistent with the cobalt–sulfur bond being key to forming the high-affinity complex.
Chronic exposure to low doses of ionizing radiation impacts the processing of glycoprotein N-linked glycans in Medaka ( Oryzias latipes )
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High-throughput small-angle X-ray scattering reveals effective structure factor transitions linked to high-concentration antibody viscosity
High-concentration monoclonal antibody (mAb) formulations are often constrained by elevated viscosity, largely driven by protein–protein interactions, which complicates manufacturing and limits subcutaneous delivery. Early viscosity risk assessment is essential during discovery, yet traditional measurements require large sample volumes, and lack high-throughput capability. Here, we develop a high-throughput small-angle X-ray scattering (SAXS) protocol to detect mAb self-association at dilute concentrations, enabling early predictive insights into high-concentration viscosity. Synchrotron SAXS measurements were conducted for 21 mAbs formulated in a histidine buffer at pH 6.0. An initial subset of 10 mAbs analyzed across 1–150 mg/mL revealed that effective structure factor transitions in the low-q region, indicative of interparticle interactions, consistently emerged below 25 mg/mL. Subsequently, 11 additional mAbs were analyzed at 1–25 mg/mL using automated liquid handling and flow cells to enable high-throughput screening. High-viscosity mAbs exhibited detectable low-q upturns at concentrations ≤10 mg/mL, whereas low-viscosity mAbs showed downturns. A classification criterion based on effective structure factor transitions accurately classified all high- and low-viscosity mAbs at 150 mg/mL, offering a scalable, sample-efficient alternative to conventional methods. These results extend recent findings on the concentration-dependent sensitivity of SAXS to short-range attractions, demonstrating that they can emerge at lower concentrations than previously reported. This study presents the most comprehensive and diverse SAXS dataset for mAbs reported to date within a single formulation, providing a valuable resource for developing and validating coarse-grained models that can more accurately capture intermolecular interactions governing high-concentration solution behavior, thereby enabling rational antibody engineering and improved developability.
Exploring how urban form and demographics are linked with pedestrian and bicycle safety
With pedestrian and bicycle safety as the focus, this study investigates the role of urban form, burdened communities (BCs), and demographics at the national level. Urban form can contribute to segregation, limiting access to crucial resources such as safe infrastructure, essential services, and economic opportunities. Leveraging recent data, this research applies six key indicators to identify BCs based on various socioeconomic and environmental factors. Here, the study creates a unique database combining 10 years of pedestrian-bicycle-involved fatal crashes with data for the 71,729 census tracts with burden indicators and census data. The data are analyzed using descriptives and rigorous zero-hurdle negative binomial models, which account for excessive zeros observed in the data. The inference-based analysis results reveal a positive correlation between burden indicators and pedestrian-bicycle-involved fatal crash occurrences, alongside a heightened risk in areas with high-intensity development. Higher Black, American Indian, or Alaska Native populations are associated with more fatal crashes. The study offers novel insights into safety dynamics across different contexts characterized by urban forms, BCs, and demographics. The study underscores the importance of targeted interventions to enhance pedestrian and bicycle safety.
Circulation characteristics of bat coronaviruses linked to bat ecological factors in Korea, 2021–2022
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