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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Amorphous boron nitride: synthesis, properties and device application

Amorphous boron nitride (a-BN) exhibits remarkable electrical, optical, and chemical properties, alongside robust mechanical stability, making it a compelling material for advanced applications in nanoelectronics and photonics. This review comprehensively examines the unique characteristics of a-BN, emphasizing its electrical and optical attributes, state-of-the-art synthesis techniques, and device applications. Key advancements in low-temperature growth methods for a-BN are highlighted, offering insights into their potential for integration into scalable, CMOS-compatible platforms. Additionally, the review discusses the emerging role of a-BN as a dielectric material in electronic and photonic devices, serving as substrates, encapsulation layers, and gate insulators. Finally, perspectives on future challenges, including defect control, interface engineering, and scalability, are presented, providing a roadmap for realizing the full potential of a-BN in next-generation device technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Arctic sea ice albedo: Spectral composition, spatial heterogeneity, and temporal evolution observed during the MOSAiC drift

The magnitude, spectral composition, and variability of the Arctic sea ice surface albedo are key to understanding and numerically simulating Earth’s shortwave energy budget. Spectral and broadband albedos of Arctic sea ice were spatially and temporally sampled by on-ice observers along individual survey lines throughout the sunlit season (April–September, 2020) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. The seasonal evolution of albedo for the MOSAiC year was constructed from spatially averaged broadband albedo values for each line. Specific locations were identified as representative of individual ice surface types, including accumulated dry snow, melting snow, bare and melting ice, melting and refreezing ponded ice, and sediment-laden ice. The area-averaged seasonal progression of total albedo recorded during MOSAiC showed remarkable similarity to that recorded 22 years prior on multiyear sea ice during the Surface Heat Budget of the Arctic Ocean (SHEBA) expedition. In accord with these and other previous field efforts, the spectral albedo of relatively thick, snow-free, melting sea ice shows invariance across location, decade, and ice type. In particular, the albedo of snow-free, melting seasonal ice was indistinguishable from that of snow-free, melting second-year ice, suggesting that the highly scattering surface layer that forms on sea ice during the summer is robust and stabilizing. In contrast, the albedo of ponded ice was observed to be highly variable at visible wavelengths. Notable temporal changes in albedo were documented during melt and freeze onset, formation and deepening of melt ponds, and during melt evolution of sediment-laden ice. While model simulations show considerable agreement with the observed seasonal albedo progression, disparities suggest the need to improve how the albedo of both ponded ice and thin, melting ice are simulated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Nek5000 developments in support of industry and the NRC

This year, the Nuclear Energy Advanced Modeling Simulation program (NEAMS) thermal-hydraulics verification and validation (V&V) work has focused in three areas of Nek5000 V&V-driven development. First, in a close collaborative effort with the U. S. Nuclear Regulatory Commission (NRC) staff, we have continued V&V efforts for the HYMERES-2 project using the OECD/NEA sponsored testing in the PSI PANDA facility. This year’s focus of ANL-NRC collaboration involves Nek5000 setups and validation for a range of problems relevant to and including the HYMERES-2 benchmark from PSI. The primary outcome of this year efforts is a more efficient geometry and inlet modeling simplification after a careful sensitivity study of the inlet profiles and pipe geometries. The resulting modeling choice of a short recycling/fully-developed turbulent inlet is within the experimental uncertainty estimate. This finding simplifies the next step of the cross-V&V HYMERES-2 project. In addition, the ANL team continue to provide assistance to the NRC staff in the form of Nek5000 application support in general and on the use of the HPC platforms of ALCF and INL in particular. This supports the NRC’s assessment of Nek5000 for use with the NRC Blue CRAB code suite. Second, we have implemented and tested more robust model of URANS, namely the k – τ model, a variant of the k-ω model, along with other improvements to RANS Nek5000 modeling in general. Because of its demonstrated robustness and stability, the k – τ model is the only RANS model that has been implemented in the new GPU version of the Nek5000 code, nekRS. Lastly, we report the initial implementation of Jacobian-free Newton Krylov approach to the direct Newton method for steady fluid solvers aimed at acceleration of RANS modeling and at IC improvement for LES campaigns. Also leveraging the Exascale Computing Project (ECP) ANL/CEED & SMR team’s software development effort to support NEAMS problems at large scale of the advanced computing architectures, NekRS, a GPU variant of Nek5000, built on top of kernels from libParanumal using OCCA for portability, has been successfully run on the full system of Summit (4608 nodes, 27648 GPUs).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Scale up production of carbon fibers from petroleum mesophase pitch

This work investigates the scale-up of pitch precursors for the carbon fiber market using mesophase pitch formulated and produced by Advanced Carbon Products Technologies’ (ACPT’s) patented mesophase pitch processing technology. Through use of its patented process, ACPT developed strategic materials by converting petroleum-based pitch into a high-value, low-cost, carbon-rich feedstock for carbon fiber and other materials critical to our national security. The team successfully developed processing criteria for the tailored mesophase pitch material that can be processed further into precursor and carbon fiber. Processability of the mesophase pitch into precursor and carbon fiber was demonstrated at scale. The resulting materials sequester the carbon that would otherwise be burned and released into the atmosphere, making this an environmentally friendly way to produce these materials in the United States.Pitch-based carbon fibers offer a promising pathway toward cost-effective, high-performance materials for structural and high-modulus composite applications; however, adoption has been limited by challenges in precursor processability and scale-up. In this work, tailored isotropic and mesophase petroleum-derived pitch materials were developed and evaluated for precursor and carbon fiber production through a collaborative effort between Oak Ridge National Laboratory (ORNL) and ACPT. Processing conditions were established at ORNL’s Carbon Fiber Technology Facility to enable stable melt-blowing of pitch-based precursors under continuous operation. Mesophase pitch precursor fibers were produced following oxidation and carbonization, corresponding to a diameter shrinkage of approximately 12%–13% and an estimated mass yield of about 75%–80%. Continuous melt-blowing steady-state operation was demonstrated over time, indicating robust process stability. Melt-blowing was achieved at throughput rates of approximately 20 lb/h⁻¹, validating the commercial viability of petroleum-derived pitch feedstocks for fiber production. Further studies are required to tailor carbon fiber microstructure and properties for specific composite applications.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Data-Driven Tailoring Optimization of Thermoset Polymers Using Ultrasonics and Machine Learning

Thermoset polymers are highly demanded for their structural robustness, thermal stability, and chemical resistance. Tailoring the properties of these polymers for high-performance applications is often preferred to designing brand-new polymers. However, the traditional destructive techniques used to characterize their properties as a function of manufacturing parameters are expensive and time-consuming. A novel non-destructive, data-driven method leveraging ultrasonics and machine learning techniques to tailor the properties of thermosets as a function of the manufacturing parameters is demonstrated. Thermoset epoxy samples with varying curing temperatures (15–40 °C) and curing agent amounts (±40%) were manufactured and tested. Their curing kinetics were monitored by determining the sound speed in the material in real time, while the longitudinal modulus of the samples was determined post-cure. Machine learning models were developed using a k-nearest neighbors algorithm. These models were implemented to predict the curing and final elastic properties using the manufacturing parameters, i.e., stoichiometry and curing temperature, and vice versa. Understanding and modeling how these parameters affect the cure kinetics and final properties will allow for efficient and reliable optimization of thermoset tailoring and manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Integrated Molten Salt Reactor Modeling Capabilities in NEAMS Thermal Hydraulics Tools

The DOE neams program supports a full range of computational thermal fluids analysis capabilities and code developments for a broad range of advanced reactor concepts. The research and development approach under the thermal fluids technical area synergistically combines three length and time scales in a hierarchical multi-scale approach. To enable multi-scale thermal fluids capability using these codes, a key joint effort has been underway to develop an integrated system- and engineering-scale thermal fluids analysis capability, through integration of SAM and Pronghorn codes, both based on the MOOSE framework. This report summarizes recent advances in developing an integrated system- and engineering-scale modeling capability for the msr concept, which has gained significant interest in recent years. A consistent framework was established by coupling Pronghorn and SAM through the Saline interface, with thermophysical properties provided by the Molten Salt Thermal Property Database (MSTDB-TP). Further improvements were made to the coupling schemes and domain-overlapping strategies, enhancing the stability and robustness of multi-code simulations. Verification and validation efforts demonstrate the accuracy of this integration across a range of benchmark problems, including one-dimensional heated pipe flows, three-dimensional natural convection loops with evolving isotopic compositions, and \gls{msre} demonstration cases. Within Pronghorn, new capabilities were introduced to model corrosion and noble-metal plating phenomena, supported by an extended thermal-hydraulics framework and refined turbulence treatments. To capture two-phase flow behavior, a multiphase Euler–Euler model was implemented in Pronghorn, including advanced closure relations, high-resolution advection techniques, and capillary force reconstruction. Preliminary verification cases confirm the fidelity of the approach, while planned validation efforts target canonical multiphase benchmarks and application to msr components such as the msre pump bowl. Finally, updates to SAM’s msr mass transfer modeling were extended to consider noble gas migration into porous structures like graphite. The point kinetics model was updated to include reactivity feedback contributions from any defined species, such as xenon. The gas transport model was expanded for applicability to gas mixtures, bubble efflux phenomena, and species transport between liquid and gas phases. A selection of multi-scale Sherwood number correlations from MOSCATO/NekRS and multi-phase correlations from literature have been added for improved accuracy in calculating mass transfer coefficients. A companion effort on developing system-level redox corrosion has also been incorporated into SAM. Collectively, these enhancements strengthen the predictive capability of SAM and Pronghorn for simulating MSR thermal-hydraulics, corrosion, multiphase behavior, and fission-product transport, providing a more complete toolset for design, safety analysis, and licensing support of next-generation \gls{msr}s.

42 - ENGINEERING↗
DOE OSTI2024

Design of Star‐Shaped Trimer Acceptors for High‐Performance (Efficiency > 19%), Photostable, and Mechanically Robust Organic Solar Cells

Abstract High power conversion efficiency (PCE), long‐term stability, and mechanical robustness are prerequisites for the commercial applications of organic solar cells (OSCs). In this study, a new star‐shaped trimer acceptor (TYT‐S) is developed and high‐performance OSCs with a PCE of 19.0%, high photo‐stability (t 80% lifetime = 2600 h under 1‐sun illumination), and mechanical robustness with a crack‐onset strain (COS) of 21.6% are achieved. The isotropic molecular structure of TYT‐S affords efficient multi‐directional charge transport and high electron mobility. Furthermore, its amorphous structure prevents the formation of brittle crystal‐to‐crystal interfaces, significantly enhancing the mechanical properties of the OSC. As a result, the TYT‐S‐based OSCs demonstrate a significantly higher PCE (19.0%) and stretchability (COS = 21.6%) than the linear‐shaped trimer acceptor (TYT‐L)‐based OSCs (PCE = 17.5% and COS = 6.4%) and the small‐molecule acceptor (MYT)‐based OSCs (PCE = 16.5% and COS = 1.3%). In addition, the increased molecular size of TYT‐S, relative to that of MYT and dimer (DYT), suppresses the diffusion kinetics of the acceptor molecules, substantially improving the photostability of the OSCs. Finally, to effectively demonstrate the potential of TYT‐S, intrinsically stretchable (IS)‐OSCs are constructed. The TYT‐S‐based IS‐OSCs exhibit high device stretchability (strain at PCE 80% = 31%) and PCE of 14.4%.

Chemistry↗
DOE OSTI2023

TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones

Tropical cyclones (TCs) are among the most destructive weather systems. Realistically and efficiently detecting and tracking TCs are critical for assessing their impacts and risks. In particular, the eye is a signature feature of a mature TC. Therefore, knowing the eyes’ locations and movements is crucial for both operational weather forecasts and climate risk assessments. Recently, a multilevel robustness framework has been introduced to study the critical points of time-varying vector fields. The framework quantifies the robustness (i.e., structural stability) of critical points across varying neighborhoods. By relating the multilevel robustness with critical point tracking, the framework has demonstrated its potential in cyclone tracking. An advantage is that it identifies cyclonic features using only 2D wind vector fields, which is encouraging as most tracking algorithms require multiple dynamic and thermodynamic variables at different altitudes. A disadvantage is that the framework does not scale well computationally for datasets containing a large number of cyclones. Herein this paper introduces a topologically robust physics-informed tracking framework (TROPHY) for TC tracking. The main idea is to integrate physical knowledge of TC to drastically improve the computational efficiency of multilevel robustness framework for large-scale climate datasets. First, during preprocessing, we propose a physics-informed feature selection strategy to filter 90% of critical points that are short-lived and have low stability, thus preserving good candidates for TC tracking. Second, during in-processing, we impose constraints during the multilevel robustness computation to focus only on physics-informed neighborhoods of TCs. We apply TROPHY to 30 years of 2D wind fields from reanalysis data in ERA5 and generate a number of TC tracks. In comparison with the observed tracks, we demonstrate that TROPHY can capture TC characteristics (e.g., frequency, intensity, duration, latitudes with maximum intensity, and genesis) that are comparable to and sometimes even better than a well-validated TC tracking algorithm that requires multiple dynamic and thermodynamic scalar fields.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Design of Sodium Chalcohalide Solid Electrolytes with Mixed Anions for All‐Solid‐State Sodium‐Ion Batteries

Solid-state sodium-ion batteries (SSNIBs) have emerged as a promising alternative to lithium-ion systems for grid-scale energy storage, owing to sodium's abundance and the improved safety of solid-state designs. Among various solid-state electrolytes (SSEs), halide-based Na + SSEs offer high electrochemical stability but are limited by low ionic conductivity and poor thermal stability. Herein, a novel class of sodium hafnium chalcohalide SSEs is reported with a dual-anion (S 2− /Cl − ) framework, with a high ionic conductivity of 4.5 × 10 −4 S cm −1 . The incorporation of sulfur enhances Na⁺ mobility by reducing the migration barrier through increased anion polarizability and expanded diffusion pathways. Additionally, S 2− contributes to stronger interatomic bonding, leading to higher cohesive energy density, improved thermal stability, and mechanical robustness. These SSEs exhibit minimal sulfur oxidation and excellent chemical/electrochemical interface stability with different cathode materials, such as O3-layered NaNi 1/3 Fe 1/3 Mn 1/3 O 2 , P2/O3 layered Na 0.85 Mn 0.5 Ni 0.4 Fe 0.1 O 2 , and Na 3 V 2 (PO 4 ) 3 cathodes. As a result, SSNIBs with P2/O3 layered Na 0.85 Mn 0.5 Ni 0.4 Fe 0.1 O 2 employing the sodium hafnium chalcohalide SSEs demonstrate outstanding cycling performance, achieving a capacity retention of 88.5% after 200 cycles at 0.1 C. This study establishes a new design strategy for high-performance SSEs, demonstrating that mixed-anion frameworks offer a viable route to overcome the intrinsic limitations of single-anion electrolytes in next-generation SSNIBs.

DFT calculation↗
DOE OSTI2025

A cost-effective all-in-one halide material for all-solid-state batteries

All-solid-state batteries require advanced cathode designs to realize their potential for high energy density and economic viability. Integrated all-in-one cathodes, which eliminate inactive conductive additives and heterogeneous interfaces, hold promise for substantial energy and stability gains but are hindered by materials lacking sufficient Li + /e − conductivity, mechanical robustness and structural stability. Here, in this work, we present Li 1.3 Fe 1.2 Cl 4 , a cost-effective halide material that overcomes these challenges. Leveraging reversible Fe 2+ /Fe 3+ redox and rapid Li + /e − transport within its framework, Li 1.3 Fe 1.2 Cl 4 achieves an electrode energy density of 529.3 Wh kg −1 versus Li + /Li. Critically, Li 1.3 Fe 1.2 Cl 4 shows unique dynamic properties during cycling, including reversible local Fe migration and a brittle-to-ductile transition that confers self-healing behaviour. This enables exceptional cycling stability, maintaining 90% capacity retention for 3,000 cycles at a rate of 5 C. Integration of Li 1.3 Fe 1.2 Cl 4 with a nickel-rich layered oxide further increases the energy density to 725.6 Wh kg −1 . By harnessing the advantageous dynamic mechanical and diffusion properties of all-in-one halides, this work establishes all-in-one halides as an avenue for energy-dense, durable cathodes in next-generation all-solid-state batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

Zeolite-Stabilized Di- and Tetranuclear Molybdenum Sulfide Clusters Form Stable Catalytic Hydrogenation Sites

Supercages of faujasite (FAU)-type zeolites serve as a robust scaffold for stabilizing dinuclear (Mo 2 S 4 ) and tetranuclear (Mo 4 S 4 ) molybdenum sulfide clusters. The FAU-encaged Mo 4 S 4 clusters have a distorted cubane structure similar to the FeMo-cofactor in nitrogenase. Both clusters possess one unpaired electron per Mo atom. Additionally, they show identical catalytic activity per sulfide cluster. Their catalytic activity is stable (> 150 h) for ethene hydrogenation, while layered MoS 2 structures deactivate significantly under the same reaction conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Ruthenium-lead oxide for acidic oxygen evolution reaction in proton exchange membrane water electrolysis

Developing an active and stable anode catalyst for the proton exchange membrane water electrolyzer (PEM-WE) is a critical objective to enhance the economic viability of green hydrogen technology. However, the expensive iridium-based electrocatalyst remains the sole practical material with industrial-level stability for the acidic oxygen evolution reaction (OER) at the anode. Ruthenium-based catalysts have been proposed as more cost-effective alternatives with improved activity, though their stability requires enhancement. The current urgent goal is to reduce costs and noble metal loading of the OER catalyst while maintaining robust activity and stability. Here, in this study, we design a Ru-based OER catalyst incorporating Pb as a supporting element. This electrocatalyst exhibits an OER overpotential of 201 mV at 10 mA.cm -2 , simultaneously reducing Ru noble metal loading by similar to 40%. Normalization of the electrochemically active surface area unveils improved intrinsic activity compared to the pristine RuO 2 catalyst. During a practical stability test in a PEM-WE setup, our developed catalyst sustains stable performance over 300 h without notable degradation, underscoring its potential for future applications as a reliable anodic catalyst.

Electrocatalysis↗
DOE OSTI2020

Efficient, Thermally Stable, and Mechanically Robust All-Polymer Solar Cells Consisting of the Same Benzodithiophene Unit-Based Polymer Acceptor and Donor with High Molecular Compatibility

All-polymer solar cells (all-PSCs) are a highly attractive class of photovoltaics for wearable and portable electronics due to their excellent morphological and mechanical stabilities. Recently, new types of polymer acceptors (P A s) consisting of non-fullerene small molecule acceptors (NFSMAs) with strong light absorption have been proposed to enhance the power conversion efficiency (PCE) of all-PSCs. However, polymerization of NFSMAs often reduces entropy of mixing in PSC blends and prevents the formation of intermixed blend domains required for efficient charge generation and morphological stability. One approach to increase compatibility in these systems is to design P A s that contain the same building blocks as their polymer donor (P D ) counterparts. Here, a series of NFSMA-based P A s [P(BDT2BOY5-X), (X = H, F, Cl)] are reported, by copolymerizing NFSMA (Y5-2BO) with benzodithiophene (BDT), a common donating unit in high-performance P D s such as PBDB-T. All-PSC blends composed of PBDB-T PD and P(BDT2BOY5-X) P A show enhanced molecular compatibility, resulting in excellent morphological and electronic properties. Specifically, PBDB-T:P(BDT2BOY5-Cl) all-PSC has a PCE of 11.12%, which is significantly higher than previous PBDB-T:Y5-2BO (7.02%) and PBDB-T:P(NDI2OD-T2) (6.00%) PSCs. Additionally, the increased compatibility of these all-PSCs greatly improves their thermal stability and mechanical robustness. For example, the crack onset strain (COS) and toughness of the PBDB-T:P(BDT2BOY5-Cl) blend are 15.9% and 3.24 MJ m -3 , respectively, in comparison to the PBDB-T:Y5-2BO blends at 2.21% and 0.32 MJ m -3 .

14 SOLAR ENERGY↗
DOE OSTI2026

Confinement Reconstruction Unlocks Stable Ru Single Atom-Doped IrO x Anodes for Long-Term High-Rate CO 2 Electrolysis

IrO 2 is a commonly employed anode catalyst for CO 2 electrolysis in membrane electrode assembly (MEA) systems. However, under high current densities, its structural reconstruction leads to activity loss and stability degradation, limiting the industrial viability of CO 2 electrolysis. In this work, we demonstrated a confinement reconstruction strategy to precisely regulate the structural evolution during electrolysis. Ethylene glycol serves as a structural modulator, protecting the catalyst surface, suppressing soluble species formation, and promoting ordered structural evolution. Single-atom Ru acts as a stability enhancer, forming robust Ir–O–Ru bridging structures that facilitate an ordered transformation from a 4-fold [RuO 4 ]/[IrO 4 ] to a 6-fold symmetry [RuO 6 ]/[IrO 6 ] octahedral framework, thereby enhancing structural rigidity and long-term stability. As a result, in MEA-based CO 2 electrolysis, the catalyst achieves a stable operation at 200 mA cm –2 for 480 h, maintaining a CO selectivity above 80%. Theoretical calculations further elucidate that the enhanced stability originates from the suppression of oxygen vacancy formation, making the lattice-oxygen-mediated mechanism (LOM) potentially less favorable. This work provides insights into the structural evolution of the OER catalysts under high-current-density conditions, paving the way for large-scale CO 2 electrolysis commercialization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Design of robust and versatile hydrocarbon-based single-ion-conducting polymer electrolytes

Hydrocarbon-based polymers offer several advantages, including lower environmental impacts, cost effectiveness, and the ability to finely tune properties. Here, we have developed trifluoromethanesulfonimide (TFSI)-functionalized poly(norbornene) (PNB) polymers utilizing a specifically designed oxa-Michael addition of a vinyl TFSI anion to an alcohol. Our results reveal that PNB-TFSI derivatives exhibit superior thermal stability and mechanical robustness compared with Nafion. The optimized PNB-TFSI-H-48 polymer (IEC 1.86 mmol/g) exhibits equivalent performance to Nafion as an anode ionomer in a proton exchange membrane fuel cell. Exchanging the counter ion to Li + enables PNB-TFSI to be used for Li-ion battery applications. Propylene carbonate plasticized PNB-TFSI derivatives achieve an Li-ion conductivity of over 10 −5 S/cm at 30°C. This Li polymer electrolyte exhibits excellent electrochemical stability (5 V vs. Li + /Li) and good cycling in a Li symmetric cell. These results highlight the potential and rational design of PNB-TFSI polymers for next-generation energy storage and conversion technologies.

08 HYDROGEN↗
DOE OSTI2023

Multilevel Robustness for 2D Vector Field Feature Tracking, Selection and Comparison

Abstract Critical point tracking is a core topic in scientific visualization for understanding the dynamic behaviour of time‐varying vector field data. The topological notion of robustness has been introduced recently to quantify the structural stability of critical points, that is, the robustness of a critical point is the minimum amount of perturbation to the vector field necessary to cancel it. A theoretical basis has been established previously that relates critical point tracking with the notion of robustness, in particular, critical points could be tracked based on their closeness in stability, measured by robustness, instead of just distance proximity within the domain. However, in practice, the computation of classic robustness may produce artifacts when a critical point is close to the boundary of the domain; thus, we do not have a complete picture of the vector field behaviour within its local neighbourhood. To alleviate these issues, we introduce a multilevel robustness framework for the study of 2D time‐varying vector fields. We compute the robustness of critical points across varying neighbourhoods to capture the multiscale nature of the data and to mitigate the boundary effect suffered by the classic robustness computation. We demonstrate via experiments that such a new notion of robustness can be combined seamlessly with existing feature tracking algorithms to improve the visual interpretability of vector fields in terms of feature tracking, selection and comparison for large‐scale scientific simulations. We observe, for the first time, that the minimum multilevel robustness is highly correlated with physical quantities used by domain scientists in studying a real‐world tropical cyclone dataset. Such an observation helps to increase the physical interpretability of robustness.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Climate warming enhances microbial network complexity and stability

Unravelling the relationships between network complexity and stability under changing climate is a challenging topic in theoretical ecology that remains understudied in the field of microbial ecology. Here, we examined the effects of long-term experimental warming on the complexity and stability of molecular ecological networks in grassland soil microbial communities. Warming significantly increased network complexity, including network size, connectivity, connectance, average clustering coefficient, relative modularity and number of keystone species, as compared with the ambient control. Molecular ecological networks under warming became significantly more robust, with network stability strongly correlated with network complexity, supporting the central ecological belief that complexity begets stability. Furthermore, warming significantly strengthened the relationships of network structure to community functional potentials and key ecosystem functioning. Furthermore, these results indicate that preserving microbial ‘interactions’ is critical for ecosystem management and for projecting ecological consequences of future climate warming.

54 ENVIRONMENTAL SCIENCES↗