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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Orbital Ingredients and Persistent Dirac Surface State for the Topological Band Structure in FeTe 0.55 Se 0.45

FeTe 0.55 Se 0.45 (FTS) occupies a special spot in modern condensed matter physics at the intersections of electron correlation, topology, and unconventional superconductivity. The bulk electronic structure of FTS is predicted to be topologically nontrivial due to the band inversion between the d x z and p z bands along Γ − Z . However, there remain debates in both the authenticity of the Dirac surface states (DSSs) and the experimental deviations of band structure from the theoretical band inversion picture. Here we resolve these debates through a comprehensive angle-resolved photoemission spectroscopy investigation. We first observe a persistent DSS independent of k z . Then, by comparing FTS with FeSe, which has no band inversion along Γ − Z , we identify the spectral weight fingerprint of both the presence of the p z band and the inversion between the d x z and p z bands. Furthermore, we propose a renormalization scheme for the band structure under the framework of a tight-binding model preserving crystal symmetry. Our results highlight the significant influence of correlation on modifying the band structure and make a strong case for the existence of topological band structure in this unconventional superconductor. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Resolving the Solvation Structure and Transport Properties of Aqueous Zinc Electrolytes from Salt-in-Water to Water-in-Salt Using Neural Network Potential

Zn Cl 2 solutions are promising electrolytes for aqueous zinc-ion batteries. Here, we report a joint computational and experimental study of the structural and dynamic properties of aqueous Zn Cl 2 electrolytes with concentrations ranging from salt-in-water to water-in-salt (WIS). By developing a neural network potential (NNP) model, we perform molecular dynamics (MD) simulations with accuracy but at much larger lengths and longer timescales. The NNP predicted structures are validated by the structure factors measured by X-ray total scattering experiments. The MD trajectories provide a comprehensive and quantitative picture of the Zn 2 + solvation shell structures. Additionally, we find that the O − H covalent bonds in water are strengthened with increasing salt concentration, thus expanding the electrochemical stability window of aqueous electrolytes. In terms of dynamic properties, the calculated and experimentally measured conductivities are in good agreement. Through the analysis of the calculated cation transference number, we propose a three-stage charge carrier transport mechanism with increasing concentration: independent ion transport, strongly correlated ion transport, and small positive charge carrier diffusion through negatively charged polymeric clusters. Our study provides fundamental atomic scale insights into the structure and transport properties of the Zn Cl 2 electrolyte that can aid the optimization and development of WIS electrolytes. Published by the American Physical Society 2025

25 ENERGY STORAGE↗
DOE OSTI2025

Predicting interface structure using the minima hopping method

Here, we adapt the minima hopping method (MHM) to the problem of interfacial structure prediction and apply it to study a canonical problem, the tilt grain boundaries in SrTiO 3 . Our method employs a hybrid approach by first exploring the potential energy surface (PES) of different grain boundary samplings with an empirical force field, among which the fifteen candidates with lower energies are then refined using ab initio density functional theory (DFT) calculations. During the exploratory stage, we bias the search using a local order parameter to primarily sample various reconstructions in the vicinity of the interface, while preserving the crystallinity of the bulk regions. We further enhance the search by incorporating initial structures with rigid body displacements to account for translational variations between bulk phases, enabling the MHM to effectively generate both stoichiometric and nonstoichiometric SrTiO 3 Σ⁢3(111)[110] and Σ⁢3(112)[110] grain boundaries. From an algorithmic standpoint, MHM outperforms earlier studies based on genetic algorithms (GA) by identifying more stable interfacial structures of several SrTiO 3 grain boundaries. The performance of the present implementation of the MHM approach is primarily limited by exploring an approximate description of the PES with a rather simple Buckingham potential. This limitation leads to variations in performance when compared to approaches utilizing more advanced surrogate PES models, such as direct DFT-PES sampling or GA with the embedded atom method (EAM). Despite the present limitations, the MHM approach is able to yield interfacial structures with comparable or lower interfacial energies in specific cases, such as Σ⁢3(111)[110] Γ=1, ±0.5 and Σ⁢3(112)[110] Γ= ±1, −2, underscoring the robustness of the MHM approach even with a simple approximation of the DFT PES. The MHM interfacial structure prediction method thus offers an efficient approach to understanding the grain boundaries and heterointerfaces at the atomic scale, providing an important prerequisite for effective materials design.

density functional theory↗
DOE OSTI2025

Structure of ice VII with Hirshfeld atom refinement

In the refinement of the crystal structures of ice, the best results obtained so far have been with neutron diffraction because the most troublemaking aspects are the hydrogen atoms. In nine out of twenty ice structures, the hydrogen atoms are disordered, which makes proper refinement more difficult. In our previous paper describing the structure of ice VI we proved that, using Hirshfeld atom refinement (HAR) based on synchrotron X-ray data, it is possible to obtain results comparable with those from neutron experiments. In this work, we investigate another structure of high-pressure disordered ice, cubo-ice (ice VII). Single crystals of cubo-ice were grown under pressure in diamond anvil cells. X-ray diffraction measurements were conducted at a synchrotron source facility (APS, University of Chicago, USA) as well as on our regular in-house laboratory diffractometer with Ag radiation. The data collected were further refined with HAR. Comparison of the structural parameters obtained with those derived from neutron diffraction showed very good agreement in terms of bond lengths and fairly good agreement in terms of hydrogen atom ADPs. We were also able to perform unconstrained refinements with various split-atom models.

Chemistry↗
DOE OSTI2025

An integrated integral projection model ( IPM 2 ) to disentangle size‐structured harvest and natural mortality

Abstract Body size is one of the most important traits governing individual‐level demographic rates and modulating population‐level processes. Multiple size‐dependent demographic rates can simultaneously change population structure, so distinguishing their individual contributions to overall population dynamics remains a challenge. Disentangling size‐dependent harvest rates from other demographic rates is critical for assessing the impact of removal on populations of invasive species. Inference about invasive populations can be difficult, however, as observations are often collected opportunistically as part of removal programs, rather than experimentally designed. Yet accurate inference is essential for understanding the feasibility of population suppression and optimising management decisions. We develop an integrated integral projection model (IPM 2 ) that leverages the strengths of the integrated population model and integral projection model to enable inference about complex, size‐structured demographic rates from imperfect observations. We apply the IPM 2 in the context of invasive European green crab ( Carcinus maenas ), a species for which individual body size strongly regulates both the observation‐generating process and latent, population dynamics. The IPM 2 facilitates the distinct estimation of green crab size‐structured harvest and natural mortality rates, parameters for which no explicit data is collected and that are unidentifiable in component datasets of the integrated population model. The model represents how the green crab population changes over time, providing the first estimates of size‐structured abundance of this high‐priority species. By forecasting the stable size distribution and equilibrium population size under varying removal efforts, we demonstrate that extremely high levels of removal effort can reduce the equilibrium green crab population size. Yet these high mortality rates also shift the stable size distribution and increase the equilibrium abundance of smaller crabs, since size‐selective removal alters intraspecific interactions. The ecological outcome of this shift in size structure will be variable, as green crab size modulates only some of its interactions with other species. These results highlight the value of the IPM 2 framework for inferring complex population dynamics with information needs that outpace information in individual observational datasets, providing a path forward for accurate assessment of conservation programs.

Keller, Abigail G. [Department of Environment Scie↗
DOE OSTI2025

Serial-femtosecond crystallography reveals how a phytochrome variant couples chromophore and protein structural changes

The photoreaction and commensurate structural changes of a chromophore within biological photoreceptors elicit conformational transitions of the protein promoting the switch between deactivated and activated states. We investigated how this coupling is achieved in a bacterial phytochrome variant, Agp2-PAiRFP2. Contrary to classical protein crystallography, which only allows probing (cryo-trapped) stable states, we have used time-resolved serial femtosecond x-ray crystallography (tr-SFX) and pump-probe techniques with various illumination and delay times with respect to photoexcitation of the parent Pfr state. Thus, structural data for seven time frames were sorted into groups of molecular events along the reaction coordinate. They range from chromophore isomerization to the formation of Meta-F, the intermediate that precedes the functional relevant secondary structure transition of the tongue. Structural data for the early events were used to calculate the photoisomerization pathway to complement the experimental data. Late events allow identifying the molecular switch that is linked to the intramolecular proton transfer as a prerequisite for the following structural transitions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Quorum sensing modulates microbial community structure through regulation of secondary metabolites

Bacteria are recognized for their diverse metabolic capabilities, yet the impact of microbe-microbe interactions on multispecies community structure and dynamics is poorly understood. Cell-to-cell signaling in the form of quorum sensing (QS) often regulates secondary metabolite production and microbial interactions. Here, we examine how acylhomoserine lactone (AHL)-mediated QS impacts microbial community structure in a 10-member synthetic community of isolates from Populus deltoides . To explore the role of QS in microbial community structure and dynamics, we disrupted AHL signaling by exogenous addition of AiiA-lactonase, an enzyme that cleaves the lactone ring. Microbial community structure resulting from signal inactivation, as measured by 16S rRNA amplicon sequencing and secondary metabolite production, was assessed after successive passaging of the community. Further, we investigated the impact of quorum quenching on specific microbe-microbe interactions using pairwise inhibition assays. Our results indicate that AHL inactivation alters the relative abundance of dominant community members at later passages but does not impact the overall membership in the community. Quorum quenching significantly alters the metabolic profile in lactonase-treated communities. This metabolic alteration impacts microbe-microbe interactions through decreased inhibition of other community members. Together, these results indicate that QS impacts microbial community structure through the regulation of secondary metabolites in dominant members and that the membership of microbial communities can be relatively stable despite changes in metabolic profiles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Structural analysis of extracellular ATP-independent chaperones of streptococcal species and protein substrate interactions

ABSTRACT During infection, bacterial pathogens rely on secreted virulence factors to manipulate the host cell. However, in gram-positive bacteria, the molecular mechanisms underlying the folding and activity of these virulence factors after membrane translocation are not clear. Here, we solved the protein structures of two secreted parvulin and two secreted cyclophilin-like peptidyl-prolyl isomerase (PPIase) ATP-independent chaperones found in gram-positive streptococcal species. The extracellular parvulin-type PPIase, PrsA inStreptococcus pneumoniaeandStreptococcus mutansmaintain dimeric crystal structures reminiscent of folding catalysts that consist of two domains, a PPIase and foldase domain. Structural comparison of the two cyclophilin-like extracellular chaperones fromS. pneumoniaeandStreptococcus pyogeneswith other cyclophilins demonstrates that this group of cyclophilin-like chaperones has novel structural appendages formed by 9- and 24-residue insertions. Furthermore, we demonstrate that deletion ofprsAandslrAgenes impairs the secretion of the cholesterol-dependent pore-forming toxin, pneumolysin inS. pneumoniae. Using protein pull-down and biophysical assays, we demonstrate a direct interaction between PrsA and SlrA with Ply. Then, we developed chaperone-assisted folding assays that show that theS. pneumoniaePrsA and SlrA extracellular chaperones accelerate pneumolysin folding. In addition, we demonstrate that SlrA and, for the first time,S. pyogenes PpiA exhibit PPIase activity and can bind the immunosuppressive drug, cyclosporine A. Altogether, these findings suggest a mechanistic role for streptococcal PPIase chaperones in the activity and folding of secreted virulence factors such as pneumolysin. IMPORTANCE Streptococcal species are a leading cause of lower respiratory infections that annually affect millions of people worldwide. During infection, streptococcal species secrete a medley of virulence factors that allow the bacteria to colonize and translocate to deeper tissues. In many gram-positive bacteria, virulence factors are secreted from the cytosol across the bacterial membrane in an unfolded state. The bacterial membrane-cell wall interface is exposed to the potentially harsh extracellular environment, making it difficult for native virulence factors to fold before being released into the host. ATP-independent PPIase-type chaperones, PrsA and SlrA, are thought to facilitate folding and stabilization of several unfolded proteins to promote the colonization and spread of streptococci. Here, we present crystal structures of the molecular chaperones of PrsA and SlrA homologs from streptococcal species. We provide evidence that theStreptococcus pyogenesSlrA homolog, PpiA, has PPIase activity and binds to cyclosporine A. In addition, we show thatStreptococcus pneumoniaePrsA and SlrA directly interact and fold the cholesterol-dependent pore-forming toxin and critical virulence determinant, pneumolysin.

Microbiology↗
DOE OSTI2024

Structure Function Studies of Photosystem II Using X-Ray Free Electron Lasers

The structure and mechanism of the water-oxidation chemistry that occurs in photosystem II have been subjects of great interest. The advent of X-ray free electron lasers allowed the determination of structures of the stable intermediate states and of steps in the transitions between these intermediate states, bringing a new perspective to this field. The room-temperature structures collected as the photosynthetic water oxidation reaction proceeds in real time have provided important novel insights into the structural changes and the mechanism of the water oxidation reaction. The time-resolved measurements have also given us a view of how this reaction—which involves multielectron, multiproton processes—is facilitated by the interaction of the ligands and the protein residues in the oxygen-evolving complex. These structures have also provided a picture of the dynamics occurring in the channels within photosystem II that are involved in the transport of the substrate water to the catalytic center and protons to the bulk.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

An FDA-approved drug structurally and phenotypically corrects the K210del mutation in genetic cardiomyopathy models

Dilated cardiomyopathy (DCM) due to genetic disorders results in decreased myocardial contractility, leading to high morbidity and mortality rates. There are several therapeutic challenges in treating DCM, including poor understanding of the underlying mechanism of impaired myocardial contractility and the difficulty of developing targeted therapies to reverse mutation-specific pathologies. In this report, we focused on K210del, a DCM-causing mutation, due to 3-nucleotide deletion of sarcomeric troponin T (TnnT), resulting in loss of Lysine210. We resolved the crystal structure of the troponin complex carrying the K210del mutation. K210del induced an allosteric shift in the troponin complex resulting in distortion of activation Ca 2+ -binding domain of troponin C (TnnC) at S69, resulting in calcium discoordination. Next, we adopted a structure-based drug repurposing approach to identify bisphosphonate risedronate as a potential structural corrector for the mutant troponin complex. Cocrystallization of risedronate with the mutant troponin complex restored the normal configuration of S69 and calcium coordination. Risedronate normalized force generation in K210del patient-induced pluripotent stem cell–derived (iPSC-derived) cardiomyocytes and improved calcium sensitivity in skinned papillary muscles isolated from K210del mice. Systemic administration of risedronate to K210del mice normalized left ventricular ejection fraction. Collectively, these results identify the structural basis for decreased calcium sensitivity in K210del and highlight structural and phenotypic correction as a potential therapeutic strategy in genetic cardiomyopathies.

Research & Experimental Medicine↗
DOE OSTI2024

Structure-aware annotation of leucine-rich repeat domains

Protein domain annotation is typically done by predictive models such as HMMs trained on sequence motifs. However, sequence-based annotation methods are prone to error, particularly in calling domain boundaries and motifs within them. These methods are limited by a lack of structural information accessible to the model. With the advent of deep learning-based protein structure prediction, existing sequenced-based domain annotation methods can be improved by taking into account the geometry of protein structures. We develop dimensionality reduction methods to annotate repeat units of the Leucine Rich Repeat solenoid domain. The methods are able to correct mistakes made by existing machine learning-based annotation tools and enable the automated detection of hairpin loops and structural anomalies in the solenoid. The methods are applied to 127 predicted structures of LRR-containing intracellular innate immune proteins in the model plant Arabidopsis thaliana and validated against a benchmark dataset of 172 manually-annotated LRR domains.

Xu, Boyan↗
DOE OSTI2025

Investigation of Site Amplifications Using Ambient-Noise-Derived Shallow Velocity Structures Under a Dense Array in Oklahoma

The shear-wave velocity (V S ) structure plays an important role in characterizing site amplification. The Large-n Seismic Survey in Oklahoma (LASSO; 1820 stations) revealed large vertical ground-motion variability in a 25 km × 32 km area in northern Oklahoma. The LASSO array has a relatively simple and flat topography, typical in a sedimentary basin environment in the central United States. In this study, we use the dense array to investigate the velocity structure under the LASSO array and how vertical ground motions relate to the shallow-to-deep structures. We extract the fundamental-mode Rayleigh wave by cross-correlating one month of ambient noise (0.7–5 Hz). We use double-beamforming to measure the group and phase velocities and anisotropy. By jointly inverting the group and phase velocities, we obtain the V S structure. Here, we observe correlations between V S at depths of 0.1–1.5 km and vertical ground motions using sites on the stiffer Permian formations. The shallow Quaternary alluvium and terrace deposits can amplify vertical ground motions by a factor of 2–4.5 between 2 and 25 Hz and attenuate signals above 25 Hz. We use 1D V S profiles to simulate the SV-wave transfer functions. An average V S of 250 m/s in the upper 20–40 m may cause the observed amplification between 2 and 40 Hz. V S estimated by topographic slopes cannot predict the relative amplification. Our results highlight the large variability of site-dependent ground motion in a small local region and the importance of characterizing shallow structures to estimate seismic hazards. Small thickness variations of the shallow formation can significantly change the resonance amplitude and frequency, which likely reduces the coherency of the Rayleigh waves extracted from ambient noise.

Chang, Hilary [Massachusetts Inst. of Technology (↗
DOE OSTI2024

Deep Learning Prediction of Protein Complex Structures

Proteins interact to form protein complex to carry out biological functions such as catalytic chemical reaction. Therefore, it is important to develop computational methods to predict protein-protein interaction and the structures of protein complexes to study and enhance protein function. In this project, we successfully developed several deep learning methods to predict inter-protein contacts and the reinforcement learning and optimization methods to reconstruct protein complex structures from predicted inter-chain contacts. The methods were integrated with the MULTICOM protein complex structure prediction system and applied to predict the complex structures of biomass production-related proteins of green algae. During the two and a half years of research and development, all the specific milestones of the project were achieved successfully. 16 publications/manuscripts were produced. 10 software tools were developed. A patent application was submitted. Our MULTICOM predictors leveraging some tools developed in this project were ranked among the top predictors in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Non-destructive structural characterization of graphite components using mechanical resonance and deep learning

As compared to conventional nuclear reactors, microreactors have the potential to significantly reduce construction timelines and capital costs, decreasing the barriers for advanced nuclear reactor technologies. However, the lower power output of these microreactors (typically < 20 MWe) creates challenging economics if operation and maintenance costs cannot be sufficiently reduced. The compact size of these designs presents an opportunity for comprehensive in-situ structural health monitoring to provide real-time feedback in order to reduce operational costs associated with maintenance and downtime. Many microreactor concepts use graphite for both in-core neutron moderation and as a structural material, which has typically required some form of periodic and laborious inspection. This report provides a description and assessment of recent work with graphite to couple acoustic-based experimental measurements and characterization with machine learning models to mature structural health monitoring capabilities and generate benefits for the nuclear microreactor industry. With resilient embedded sensors in development in other programs funded by the US Department of Energy’s Office of Nuclear Energy and elsewhere, the work described herein builds upon previously funded efforts to mature non-destructive testing technology that relates measured vibrational signatures to structural changes, using a combination of new experimental measurements and machine learning processing. Building on past successful demonstrations of predictive workflows to identify structural changes in a hexagonal stainless steel test article with excellent acoustic propagation, we first performed baseline characterization on graphite samples with canonical geometries to ensure compatibility and confidence in the applied techniques for a material with distinctly different mechanical properties. In contrast to efforts in previous years, we worked exclusively with unidirectional vibration data that is more comparable to those expected from the existing embedded sensor technologies which are suitable for deployment in a reactor setting. Established acoustic and modern machine-learning-based characterization approaches were applied to the resulting datasets from these simple geometries. Both approaches were found to be highly capable of detecting even small geometric irregularities amongst nominally identical samples. As such, we then moved to testing these approaches for detection of artificial local stress perturbations introduced into a more complex geometry: a hexagonal block with drilled holes. A main outcome of this work is that a generalizable ML workflow can be used to detect and predict the characteristics of small artificial anomalies in a graphite component with a relevant geometry. While this work was performed using surficial vibration data, we expect the approach to be flexible and viable for other monitoring scenarios, such as those with different arrangements or types of sensor arrays. As compared to previously funded efforts, an existing ML workflow based on neural networks was enhanced through the addition of recently developed Fourier neural operators. As applied to previously collected and new vibration datasets, prediction accuracies of anomaly characterizations were greatly improved with minimal added computational cost. As trained on small durations of vibration data (tens of seconds) collected over a realistic number of locations, the model was able to reliably determine the presence of a subtle stress anomaly and begin to provide location estimates. Such an approach is likely to be viable for more relevant reactor damage scenarios for graphite components, such as progressive crack growth or creep.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Structural Insights into Mechanisms Underlying Mitochondrial and Bacterial Cytochrome c Synthases

Mitochondrial holocytochrome c synthase (HCCS) is an essential protein in assembling cytochrome c (cyt c) of the electron transport system. HCCS binds heme and covalently attaches the two vinyls of heme to two cysteine thiols of the cyt c CXXCH motif. Human HCCS recognizes both cyt c and cytochrome c1 of complex III (cytochrome bc1). HCCS is mutated in some human diseases and it has been investigated recombinantly by mutational, biochemical, and reconstitution studies in the past decade. Here, we employ structural prediction programs (e.g., AlphaFold 3) on HCCS and its two substrates, heme and cytochrome c. The results, when combined with spectroscopic and functional analyses of HCCS and variants, provide insights into the structural basis for heme binding, apocyt c binding, covalent attachment, and release of the holocyt c product. Results from in vitro reconstitution of purified human HCCS using cyt c and cyt c1 peptides as acceptors are consistent with the structural modeling of substrate binding. Reconstitution of HCCS and cyt c1 provides an approach to studying cyt c1 assembly, which has been refractile to recombinant in vivo reconstitution (unlike HCCS and cyt c). We propose a structural basis for release of the holocyt c product from HCCS based on in vitro studies and on cryoEM structures of the bacterial cyt c synthase (CcsBA) active site. We analyze the kinetoplastid mitochondrial synthase (KCCS), and hypothesize a molecular evolutionary path from mitochondrial endosymbiosis to the current HCCS.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Fyn–Saracatinib Complex Structure Reveals an Active State-like Conformation

Fyn is a Src-family tyrosine kinase implicated in synaptic dysfunction and neuroinflammation across multiple neurodegenerative disorders, including Alzheimer’s disease (AD) and Parkinson’s disease (PD). Saracatinib (AZD0530) is a potent Src-family inhibitor that has been explored as a repurposed therapeutic; however, its clinical utility is limited by poor kinase selectivity caused by high sequence conservation within Src-family ATP-binding sites. Here, we combine surface plasmon resonance (SPR) and X-ray crystallography to define saracatinib recognition by the Fyn kinase domain (KD). SPR single-cycle kinetics shows that saracatinib binds the isolated Fyn KD and full-length Fyn with low-nanomolar affinity, whereas dasatinib binds with subnanomolar affinity and markedly slower dissociation. We determined the crystal structure of the Fyn KD-saracatinib complex at 2.22 Å resolution. The kinase adopts an active-like conformation with the DFG motif and αC-helix in the ‘in’ state and a conserved β3 αC Lys-Glu salt bridge. Saracatinib occupies the adenine and ribose pockets, and engages the hinge through direct and water-mediated hydrogen bonding while complementing a hydrophobic back pocket by van der Waals contacts. Comparison with reported saracatinib-bound structures of other kinases suggests that the active-state geometry observed for Fyn creates a pocket not observed in inactive-like complexes, providing a structural handle for designing Fyn-selective inhibitors. Comparison with all saracatinib-bound kinase co-structures currently available in the PDB (ALK2 and PKMYT1) indicates a conserved monodentate hinge binding mode but kinase-dependent αC-helix conformations, providing a structural rationale for designing Fyn-selective analogues.

AZD0530↗
DOE OSTI2024

Feasibility of Recovering and Recycling Polymer Composites from End-of-Life Marine Renewable Energy Structures: A Review

Over the last few decades, several marine renewable energy (MRE) technologies, such as wave energy converters (WECs) and current energy converters (CECs), have been developed. As opposed to traditional materials such as metal alloys, the structure of these technologies is made up of polymer and polymer composite materials. Most structures have been made using thermoset polymer composites; however, since thermoset polymer composites are not recyclable and lack sustainability, and with recent innovations in recyclable resins, bio-based resins, and the development of additive manufacturing technologies, thermoplastic polymers are increasingly being used. Nevertheless, the methodologies for identifying end-of-life options and recovering these polymer composites, as well as the recycling and reuse processes for MRE structures, are not well-studied. Specifically, since these MRE structures are subjected to salinity, moisture, varying temperature, biofouling, and corrosion effects depending on their usage, the recyclability after seawater aging and degradation needs to be explored. Hence, this review provides an in-depth review of polymer composites used in marine applications, the hygrothermal aging studies conducted so far to understand the degradation of these materials, and the reuse and recycling methodologies for end-of-life MRE structures, with a particular emphasis on sustainability.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

Detection of supernova magnitude fluctuations induced by large-scale structure

The peculiar velocities of supernovae and their host galaxies are correlated with the large-scale structure of the Universe, and can be used to constrain the growth rate of structure and test the cosmological model. In this work, we measure the correlation statistics of the large-scale structure traced by the Dark Energy Spectroscopic Instrument Bright Galaxy Survey Data Release 1 sample, and magnitude fluctuations of type Ia supernova from the Pantheon+ compilation across redshifts z < 0.1. We find a detection of the cross-correlation signal between galaxies and type Ia supernova magnitudes. Fitting the normalised growth rate of structure f sigma_8 to the auto- and cross-correlation function measurements we find f sigma_8 = 0.384 +0.094 -0.157, which is consistent with the Planck LambdaCDM model prediction, and indicates that the supernova magnitude fluctuations are induced by peculiar velocities. Using a large ensemble of N-body simulations, we validate our methodology, calibrate the covariance of the measurements, and demonstrate that our results are insensitive to supernova selection effects. We highlight the potential of this methodology for measuring the growth rate of structure, and forecast that the next generation of type Ia supernova surveys will improve f sigma_8 constraints by a further order of magnitude.

Nguyen, A. [Swinburne U., Ctr. Astrophys. Supercom↗