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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Ecologically inspired metrics for transitioning to a sustainable and resilient circular economy with application to multilayer plastic films

Current Circular Economy (CE) frameworks applied to product chains exhibit notable shortcomings. These include neglecting the resilience and robustness of design, requiring detailed economic and environmental data for impact assessment, and relying on qualitative rather than quantitative metrics capturing certain CE design aspects. In the current contribution, we addressed these shortcomings by developing an Ecologically inspired (Eco-inspired) Framework using the mathematical foundations of Ecological Network Analysis (ENA). While ENA metrics have previously found application in designing circular economies, particularly in Industrial Symbiosis (IS) networks, our adaptation tailors these metrics for use in product-level CE, recognizing the inherent distinctions between product-level CE and IS. Our Eco-inspired Framework comprises three key categories to provide holistic and granular-level metrics for designing product-level CE. The first set of metrics assesses circularity and resource efficiency. The second set gauges network intensity and robustness as complementary indicators ensuring a CE is both sustainable and resilient. The third group of metrics evaluates enhancement potential of CE strategies through introducing quantitative metrics for measuring the degree of closed-loop strategies and average circularity level of a CE design. The three comprehensive set of indicators within the Eco-inspired Framework uniquely captures various facets of circular design, whether originating from technological innovations and recovery improvement at the end of life (EoL), shifts in human consumption patterns, alterations in product design, or changes in business models. The framework’s application is tested in designing a CE for multilayer Polyethylene-Polyamide (PE-PA) films. Using the Eco-inspired Framework, we identified the best strategy for designing a resilient and sustainable CE for PE-PA films. A diverse set of EoL strategies along with a reduction in product consumption can improve circularity and resilience by 650% and 255%, respectively, and mitigate greenhouse gas emissions by 90%. The framework minimizes trade-offs between sustainability and circularity goals and offers insights on how to enhance each strategy for achieving a resilient and sustainable CE for products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Bio-inspired multiscale design for perovskite solar cells

Metal halide perovskite semiconductors have attractive light-harvesting and charge-carrier transport properties for photovoltaics. Perovskite solar cells (PSCs) and modules have demonstrated their commercial promise with high power conversion efficiencies, but still face stability challenges. In this Review, we explore how biomaterials offer design inspiration for the development of durable and efficient PSCs at three different scales. At the molecular level, bio-inspired molecular interactions are harnessed towards crystallization control and degradation prevention, which offers an enhancement in long-term maximum-power-point tracking stability. At the microstructural level, self-healing and strength-enhancing strategies, utilizing dynamic bonds and interfacial reinforcement, can help PSCs to recover from physical damage and maintain high performance. At the device level, macroscopic functionalities, such as moth-eye-inspired structures tailored to different layers, can collectively enable antireflection, radiative cooling and self-cleaning to optimize light management, heat dissipation and encapsulation in PSCs. Bio-inspired PSC research can combine improved efficiency and lifetime, with abundant, biocompatible alternatives to conventional stabilizers. Future efforts should focus on screening bioinspired molecules to optimize film crystallization and stability, developing self-healing mechanisms triggered by operational stress, designing cost-efficient biomicrostructures, and integrating multifunctional encapsulation to enhance the efficiency and lifespan of PSCs.

Duan, Tianwei↗
DOE OSTI2025

Relativistic gas accretion onto supermassive black hole binaries from inspiral through merger

Accreting supermassive black hole binaries are powerful multimessenger sources emitting both gravitational and electromagnetic (EM) radiation. Understanding the accretion dynamics of these systems and predicting their distinctive EM signals is crucial to informing and guiding upcoming efforts aimed at detecting gravitational waves produced by these binaries. To this end, accurate numerical modeling is required to describe both the spacetime and the magnetized gas around the black holes. In this paper, we present two key advances in this field of research. First, we have developed a novel 3D general relativistic magnetohydrodynamics (GRMHD) framework that combines multiple numerical codes to simulate the inspiral and merger of supermassive black hole binaries starting from realistic initial data and running all the way through merger. Throughout the evolution, we adopt a simple but functional prescription to account for gas cooling through photon emission. Next, we have applied our new computational method to follow the time evolution of a circular, equal-mass, nonspinning black hole binary for ∼200 orbits, starting from a separation of 20⁢𝑟 𝑔 and reaching the postmerger evolutionary stage of the system. We have shown how mass continues to flow toward the binary even after the binary “decouples” from its surrounding disk, but the accretion rate onto the black holes diminishes. We have identified how the minidisks orbiting each black hole are slowly drained and eventually dissolve as the binary compresses. We confirm previous findings that the system’s luminosity decreases by a factor of a few during inspiral; however, we observe an abrupt increase by ∼50% in this quantity at the time of merger, likely accompanied by an equally abrupt change in spectrum. Lastly, we have demonstrated that during the inspiral, fluid ram pressure regulates the fraction of the magnetic flux transported to the binary that attaches to the black holes’ horizons.

Accretion disk & black-hole plasma↗
DOE OSTI2025

Ensuring continued operation of INSPIRE as a cornerstone of the HEP information infrastructure

The INSPIRE platform — the most widely-used discovery service specifically tailored to the needs of researchers in High Energy Physics (HEP) — has become a central component of the information infrastructure for the discipline. Despite this, INSPIRE's continued sustainability is frequently endangered by resource constraints, recently made more acute by the loss of support from historical funders changing their research priorities. If the European particle physics community wishes to ensure INSPIRE's long-term sustainability, the community should secure international support and ensure appropriate funding.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Voltage Calculations in Secondary Distribution Networks via Physics-Inspired Neural Network Using Smart Meter Data

The increasing penetration of distributed energy resources (DERs) leads to voltage issues across distribution networks, necessitating voltage calculations by utilities. Electric model-free voltage calculation offers an enticing solution. However, most researches mainly focus on primary distribution networks ignoring secondary distribution networks and commonly overlook extreme voltage case calculations, which require the model’s extrapolation abilities. Here, in addressing the gaps, this paper presents a customized physics-inspired neural network (PINN) model, the structure of which is inspired by the derived coupled power flow model of primary-secondary distribution networks. To ensure precision and rapid convergence, a crafted training framework for the PINN model is proposed. The PINN’s “structure-mimetic” design enables superior extrapolation for unseen scenarios and enhances physical information awareness. We demonstrate this through two applications: hosting capacity analysis and customer-transformer connectivity. The effectiveness and advantages of the proposed PINN model are validated on two public testing systems and one utility distribution feeder model.

Distribution network↗
DOE OSTI2024

Exploring dark forces with multimessenger studies of extreme mass ratio inspirals

Abstract The exploration of dark sector interactions via gravitational waves (GWs) from binary inspirals has been a subject of recent interest. We study dark forces using extreme mass ratio inspirals (EMRIs), pointing out two issues of interest. Firstly, the innermost stable circular orbit (ISCO) of the EMRI, which sets the characteristic length scale of the system and hence the dark force range to which it exhibits enhanced sensitivity, probes force mediator masses that complement those studied with supermassive black hole (SMBH) or neutron star binaries. The LISA mission (the proposedμAres detector) will probe mediators with massesm V ∼ 10 -16 eV (m V ∼ 10 -18 eV), corresponding to ISCOs of 10 6 M ⊙ (10 8 M ⊙ ) central SMBHs. Secondly, while the sensitivity to dark couplings is typically limited by the uncertainty in the binary component masses, independent mass measurements of the central SMBH through reverberation mapping campaigns or the motion of dynamical tracers enable one to break this degeneracy. Our results therefore highlight the necessity for coordinated studies, loosely referred to as “multimessenger”, between futureμHz- mHz GW observatories and ongoing and forthcoming SMBH mass measurement campaigns, including OzDES-RM, SDSS-RM, and SDSS-V Black Hole Mapper.

Astronomy & Astrophysics↗
DOE OSTI2024

INSURE: An Information Theory iNspired diSentanglement and pURification modEl for Domain Generalization

Domain Generalization (DG) aims to learn a generalizable model on the unseen target domain by only training on the multiple observed source domains. Although a variety of DG methods have focused on extracting domain-invariant features, the domain-specific class-relevant features have attracted attention and been argued to benefit generalization to the unseen target domain. To take into account the class-relevant domain-specific information, in this paper we propose an Information theory iNspired diSentanglement and pURification modEl (INSURE) to explicitly disentangle the latent features to obtain sufficient and compact (necessary) class-relevant feature for generalization to the unseen domain. Specifically, we first propose an information theory inspired loss function to ensure the disentangled class-relevant features contain sufficient class label information and the other disentangled auxiliary feature has sufficient domain information. Additionally, we further propose a paired purification loss function to let the auxiliary feature discard all the class-relevant information and thus the class-relevant feature will contain sufficient and compact (necessary) class-relevant information. Moreover, instead of using multiple encoders, we propose to use a learnable binary mask as our disentangler to make the disentanglement more efficient and make the disentangled features complementary to each other. We conduct extensive experiments on five widely used DG benchmark datasets including PACS, VLCS, OfficeHome, TerraIncognita, and DomainNet. The proposed INSURE achieves state-of-the-art performance. We also empirically show that domain-specific class-relevant features are beneficial for domain generalization. The code is available at https://github.com/yuxi120407/INSURE .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

NeuroCoreX: Brain-Inspired Computing from Code to Circuit

NeuroCoreX is an open-source codebase that enables the implementation of brain-inspired, energy-efficient neuromorphic computing models on FPGA hardware. Designed to support real-time learning, all-to-all neural connectivity, and flexible network architectures, NeuroCoreX offers a hands-on, accessible platform for exploring biologically inspired models of neural computation. It empowers researchers, students, and developers to implement and experiment with adaptive systems—bringing the power of neuromorphic computing to a broader community through a low-cost, scalable, and reconfigurable framework.

Gautam, Ashish [Oak Ridge National Laboratory (ORN↗
DOE OSTI2026

Center for Bio-Inspired Energy Science (CBES) (Final Report)

The goal of the EFRC on Bio-Inspired Energy Science (CBES) has been to create and understand materials and systems inspired by biology, seeking to innovate on energy utilization and its environmental implications. In the most recent two-year funding cycle (2022–2024), we extended strategic projects from each of the five tasks from the previous cycle. This work offers important advances in how soft matter can be used to convert and store energy. We briefly summarize selected key accomplishments from each task below.

10 SYNTHETIC FUELS↗
DOE OSTI2025

Bio-inspired interlocking metasurfaces

Interlocking metasurfaces (ILMs) are patterned arrays of mating features that enable the joining of bodies by constraining motion and transmitting force. They offer an alternative to traditional joining solutions such as mechanical fasteners, welds, and adhesives. This study explores the development of bio-inspired ILMs using a problem-driven bioinspired design (BID) framework. We develop a taxonomy of attachment solutions that considers both biological and engineered systems and derive conventional design principles for ILM design. We conceptualize two engineering implementations to demonstrate concept development using the taxonomy and ILM conventional design principle through the BID framework: one for rapidly assembled bridge truss members and another for modular microrobots. These implementations highlight the potential of BID to enhance performance, functionality, and tunability in ILMs.

attachment↗
DOE OSTI2025

Nature-inspired lotus-shaped fins combined with hybrid nanoparticles and metal foam for high-performance latent heat thermal energy storage

Latent heat thermal energy storage (LHTES) systems play a critical role in renewable energy integration by providing high energy density and nearly isothermal operation during phase transitions. However, their performance is often limited by slow melting/charging rates, which motivates the search for enhanced heat transfer designs. This study investigates the melting behavior of RT-82 phase change material (PCM) using novel lotus-shaped fins combined with copper metal foam and conductive graphene nanoparticles and carbon nanotubes. A two-dimensional enthalpy-porosity model in ANSYS Fluent was developed to simulate the charging/melting process, capturing non-thermal equilibrium between the foam and PCM/nano-PCM. In this study, effects of fin geometry, nanoparticle concentration, and foam porosity on melting dynamics and cost-performance trade-offs were investigated. Results showed that natural convection accelerated melting by ~12% compared to conduction-only scenarios. Optimized lotus-shaped fins with higher fin density (T3F4 and T3F10) achieved up to 63% faster melting relative to sparse configurations. Graphene nanoparticles improved thermal conductivity, with a 6% volume fraction, by reducing melting time by ~6.9%, while their combination with 75% porosity foam achieved a maximum reduction in the melting time of ~51% compared to pure PCM. Cost-performance analysis identified T3F4 as the most balanced design, offering rapid thermal response without excessive material costs, while moderate-density designs like T3S6 provided economical alternatives with acceptable performance. These results highlight the performance enhancement that can be achieved by integrating bio-inspired fins, nanoparticles, and foams, into compact and efficient LHTES for solar heating, building thermal management, and industrial waste-heat recovery applications.

25 ENERGY STORAGE↗
DOE OSTI2024

Control-inspired design and power optimization of an active mechanical motion rectifier based power takeoff for wave energy converters

Ocean waves have high energy density and are persistent and predictable. Yet, converting wave energy to a useable form remains challenging. A significant hurdle is the oscillatory nature of waves resulting in the alternating loads, which necessitate the use of rectification at some stage of the energy conversion. This research effort presents a novel design of active mechanical motion rectifier (AMMR) for the power takeoff (PTO), which provides enhanced controllability and better power performance when compared to passive mechanical motion rectifiers (MMR). Inspired by transistors used in synchronous electrical rectifiers, the proposed design uses controllable electromagnetic clutches in the mechanical transmission to allow active engagement-disengagement control; thus, rectifying the oscillatory motion into a unidirectional rotation for high energy conversion efficiency and allowing the generator in unidirectional rotation to control the bidirectional wave capture structure for maximizing the power output. A semi-analytical computational approach is developed to efficiently evaluate the optimal power achieved using the proposed AMMR-based PTO and active control. It is found that the AMMR-based PTO design yields a higher optimal power than the previous passive MMR design across the wave spectrum. The influences of generator inertia and reactive power are discussed. Furthermore, the effects of control parameters on the power output and the optimal trajectories are analyzed. Wave tank tests with the AMMR prototype demonstrated the effectiveness of AMMR based PTO design and validated the numerical analysis.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Bio-Inspired Energy-Efficient Nanofabricated Electrical Contacts

Nanoscale electrical contacts, especially those between materials of dissimilar electronic properties, often represent one of the main causes of drops in energy transfer efficiency. They are also among the sources of above-threshold noise, and their performance often decreases over the lifetime of the nanodevices. Scale-down limitations from mesoscopic to nanoscale devices, and likewise, of nanoscale to quantum-scale devices are also impeded by contacts’ quality. Making more reliable, energy-efficient electrical contacts is among the goals of the nanoelectronics research within the framework of energy-efficient electronic systems. This report focuses on the design, nanofabrication, and testing of novel shapes of electrical contacts. Lithography and nanofabrication were utilized to mimic the approximate shape of insect setae for mesoscale contacts design. The contacts are tested for elementary charge transport via I–V curves and for the broadband, 1/f noise. Tests show that contacts design leads to a measurable decrease in the energy necessary to operate a contact as a switch by at least 12–20%, depending on temperature, while broadband noise shows measurably lower power spectra, for bio-inspired contacts. The proposed method is open to modifications and improvements as required by various on-chip applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Bio‐Inspired Cascade Photocatalysis on Fe Single‐Atom Carbon Nitride Upcycles Plastic Wastes for Effective Acetic Acid Production

Plastic imposes a critical threat to the environment, ecosystems, and human health because of the low utilization efficiency of plastics. Here, we demonstrate a sustainable, highly efficient cascade photocatalysis for upcycle plastics to value-added acetic acid using Fe single-atom catalysts (Fe@C 3 N 4 SAC) at ambient conditions. Inspired by Phanerochaete chrysosporium microbial, the defective Fe@C 3 N 4 SAC acts as a bifunctional cascade photocatalyst for both Fenton-like and CO 2 reduction reactions. During the reaction, hydroxyl radicals (*OH) form and subsequently oxidize plastics into CO 2 intermediates. These CO 2 intermediates are then photo-reduced to CH 3 COOH on the same catalyst via cascade photocatalysis. The mechanism is confirmed by in situ multimodal microscopy and spectroscopies, with density functional theory calculations. A state-of-art CH 3 COOH yield of 63.8 mg h −1 gcat −1 from PVC, 12.7 mg h −1 gcat −1 from PE, 5.4 mg h −1 gcat −1 from PET, and 5.3 mg h −1 gcat −1 from PP are directly obtained under AM1.5G solar irradiation and further validated under real sunlight (≈0.6 sun), achieving 5.6 mg h −1 gcat −1 from PET, using low-cost Fe@C 3 N 4 SAC in a sealed reactor by enhancing the photon transport and utilization efficiency. The techno-economic analysis shows it is promising to practically mitigate plastic based on broader social welfare assessments.

cascade photocatalysis↗
DOE OSTI2025

Enhanced Interfacial Strength in Carbon Fiber Composites via Mussel‐Inspired Sizing Polymers

Composite materials possess a high strength-to-weight ratio. A key determinant of their mechanical performance is the interfacial strength between the fibers and the matrix. Sizing agents are commonly used to improve this interface by promoting better adhesion, though optimizing this interaction remains a significant challenge. Here, this study evaluates the use of poly(catechol-styrene) (PCS), a mussel-inspired sizing agent, to enhance fiber–matrix bonding in carbon fiber composites. Woven carbon fiber laminates were dip-coated with varying concentrations of PCS (0.05 and 0.1 wt%) and subsequently fabricated using vacuum-assisted resin transfer molding followed by compression molding. Interlaminar shear strength (ILSS) tests showed improvements of 4% and 8% for the 0.05% and 0.1% PCS treatments, respectively. These results indicate that PCS is effective in reinforcing interfacial adhesion, thereby improving the mechanical integrity of carbon fiber-reinforced composites.

Carbon fiber composites↗
DOE OSTI2026

NuGraph2 with context-aware inputs: physics-inspired improvements in semantic segmentation

Graph neural networks have recently shown strong promise for event reconstruction tasks in Liquid Argon Time Projection Chambers, yet their performance remains limited for underrepresented classes of particles, such as Michel electrons. In this work, we investigate physics-informed strategies to improve semantic segmentation within the NuGraph2 architecture. We explore three complementary approaches: (i) enriching the input representation with context-aware features derived from detector geometry and track continuity, (ii) introducing auxiliary decoders to capture class-level correlations, and (iii) incorporating energy-based regularization terms motivated by Michel electron energy distributions. Experiments on MicroBooNE public datasets show that physics-inspired feature augmentation yields the largest gains, particularly boosting Michel electron precision and recall by disentangling overlapping latent space regions. In contrast, auxiliary decoders and energy-regularization terms provided limited improvements, partly due to the hit-level nature of NuGraph2, which lacks explicit particle- or event-level representations. Our findings highlight that embedding physics context directly into node-level inputs is more effective than imposing task-specific auxiliary losses, and suggest that future hierarchical architectures such as NuGraph3, with explicit particle- and event-level reasoning, will provide a more natural setting for advanced decoders and physics-based regularization. The code for this work is publicly available on Github at https://github.com/vitorgrizzi/nugraph_phys/tree/main_phys.

Other Experiments↗
DOE OSTI2024

Higher-order tails and RG flows due to scattering of gravitational radiation from binary inspirals

Abstract We establish and develop a novel methodology to treat higher-order non-linear effects of gravitational radiation that is scattered from binary inspirals, which employs modern scattering-amplitudes methods on the effective picture of the binary as a composite particle. We spell out our procedure to study such effects: assembling tree amplitudes via generalized-unitarity methods and employing the closed-time-path formalism to derive the causal effective actions, which encompass the full conservative and dissipative dynamics. We push through to a new state of the art for these higher-order effects, up to the third subleading tail effect, at order$$ {G}_N^5 $$ G N 5 and the 5-loop level, which corresponds to the 8.5PN order. We formulate the consequent dissipated energy for these higher-order corrections, and carry out a renormalization analysis, where we uncover new subleading RG flow of the quadrupole coupling. For all higher-order tail effects we find perfect agreement with partial observable results in PN and self-force theories, where available.

Physics↗
DOE OSTI2025

High compressive energy absorption and shape recovery behavior of additively manufactured textile-inspired cylindrical braided metamaterials

Mechanical metamaterials (MMs) are engineered structures with unique mechanical properties that arise from their unique spatial arrangement or lattice-like structure. The most commonly designed MMs such as honeycomb and re-entrant auxetics are prone to failure at the sharp corners and weak joints due to the increased stress concentration under deformation. To mitigate this challenge, braided MM structures involving intertwining threads of nylon—forming curved unit cells—have been studied. These textile-inspired cylindrical braided metamaterials (CBMMs) with contrasting unit cells, namely diamond and regular CBMMs, were fabricated by 3D printing. The layer-by-layer deposited structure built by fused filament fabrication delivered an assembly of overlapped threads that are fused at the contact point. To understand deformation behavior of these MMs, finite element models were developed for various load scenarios including quasi-static compression, cyclic and creep loads at room temperature. Stress distribution, deformation mechanisms, and failure modes were analyzed and validated by experiments to analyze the geometries and associated performance. The diamond CBMMs showed stress softening at 30 % compressive strain, withstanding a load of ∼440 N, whereas the regular CBMMs at 50 % strain experienced ∼250 N. The diamond CBMMs delivered higher creep resistance under sustained load and better energy absorption under cyclic loading than the regular CBMMs. The latter, however, exhibited 94 % shape recovery in contrast to 88 % recovery in former prototype during their first cyclic load. In conclusion, this study helps design mechanical lightweight devices that endure significant sustained load and exhibit enhanced energy absorption and shape recovery characteristics in cyclic loading.

Creep↗