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At least 271 records · Page 15

Probing the shear-induced microstructure of a smectite clay aqueous suspensions using rheo-USANS and rheo-SIPLI measurements

Hypothesis: The static microstructure of aqueous sodium-montmorillonite (Na-Mt) suspensions at low ionic strengths (where Particle Size/Debye Length ≈1) exhibits both the particle–particle ordering as well as aggregation with repulsive ordered domains having characteristic optical birefringence and attractive aggregated entities larger than 20 µm resulting in ever-increasing yield stresses also known as physical aging-rejuvenation behavior. We hypothesize that the attractive particle–particle aggregation is the underlying cause behind the physical aging-rejuvenation behavior observed in Na-Mt suspensions with no contribution from structural dynamics driven by repulsive particle–particle ordering or jamming. Experiments: We investigate the shear-induced microstructure of aqueous Na-Mt suspensions in the sol and gel state using rheo-ultra-small angle neutron scattering (rheo-USANS) experiments at shear rates of 1, 50, 500, and 2000 s −1 . We also perform rheo-shear-induced polarization light imaging (rheo-SIPLI) experiments to relate ordering with shearing and aging. Findings: Shearing the suspensions at low to moderate shear rates induces particle–particle aggregation and shearing at high shear rates induces the breakage of particle–particle aggregation in the sol and gel states, suggesting the microstructural aggregation in the sol and gel state is shear sensitive and a full rejuvenation or breakage of particle–particle aggregation is only achieved at a minimum critical shear rate. The rheo-SIPLI experiments reveal that the sol and gel state exhibited strong Maltese cross patterns at a shear rate of 1000 s −1 , indicating particle–particle ordering. Post shearing, the gel exhibited temporal evolution of storage modulus without any noticeable influence on the appearance of the Maltese cross pattern indicating physical aging and particle ordering are distinct length scale phenomena in Na-Mt suspensions and the physical aging-rejuvenation behaviour is a feature of particle–particle aggregation as opposed to ordering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SITCOMTN-162: Testing the implementation of Metadetection and Cell-Based Coadds on Abell 360 LSSTComCam data

The purpose of this technote is to test the technical quality of LSSTComCam commissioning data, specifically the Rubin_SV_38_7 field, by utilizing cell-based coadds and Metadetection by measuring the tangential and cross weak lensing shear profiles of the massive cluster Abell 360 (called A360 throughout the technote). The process entails generating the cell-based coadds for Metadetection to run on, identifying and removing cluster member galaxies, applying quality cuts, calibrating the shear measurements, and validation. Cell-based coadds and Metadetection are both currently in the process of being implemented within the LSST Science Pipelines at the time of this technote. There is substantial technical value in attempting a difficult measurement prior to full implementation. Measuring the tangential shear around A360 will showcase the current abilities of these algorithms, as well as highlight where work is still needed. As seen from the resulting shear profile of A360, the cell-based coadds and Metadetection are able to work in tandem to produce a shear catalog and resulting reduced shear profile. This technote is one part of a series studying A360 in order to both stress test the commissioning camera and demonstrate the technical capabilities of the Vera Rubin Observatory. We study the quality of the PSF modeling and impact it can have on cluster WL in [Combet et al., 2025], implementation of cell-based coadds and subsequent use for Metadetect [Sheldon et al., 2023] in this technote, photometric calibration in (in prep), source selection and photometric redshifts in [Adari et al., 2025], use of Anacal [Li et al., 2024] to produce a cluster shear profile in [Li et al., 2025], and background subtraction in this field and Fornax in [Zhou et al., 2025].

79 ASTRONOMY AND ASTROPHYSICS↗

Electron-irradiation induced creep in amorphous alloys

Electron-irradiation induced creep rates in amorphous alloys, a-SiO2, Fe79B16Si5, Cu60Ta40, and Cu50Ti50, were measured at room temperature using a miniaturized beam-bending apparatus within a transmission electron microscope operated at 200 keV. The creep rates of these amorphous samples increased nearly linearly with both e-beam current density and applied stress, while a reference crystalline (c-)SiO2 sample failed to creep under the same conditions. The irradiation induced creep compliance of a-SiO2 was ~ 15 times larger than that of Fe79B16Si5 and over 1,000 times larger than that of the two Cu alloys. Molecular dynamics computer simulations were employed to simulate electron irradiation induced creep using interatomic potentials representing amorphous Cu75Zr25, Ni80P20, and SiO2 as model systems. The irradiation induced creep compliances calculated for Cu75Zr25 during 200 keV electron irradiation provided good quantitative agreement with the two Cu-based alloys, but that for a-SiO2 was ~ 180 times too small. These results indicate that unlike neutron or ion-beam induced creep in a-SiO2, creep under electron irradiation is dominated by the effects of ionization owing largely to the far higher ratio of electronic stopping to nuclear stopping for electrons than for ions.

36 MATERIALS SCIENCE↗

Climatic Drivers for the Variation of Gross Primary Productivity Across Terrestrial Ecosystems in the United States

Abstract Temperature and water stress are important factors limiting the gross primary productivity (GPP) in terrestrial ecosystems, yet the extent of their influence across ecosystems remains uncertain. This study examines how surface air temperature, soil water availability (SWA) and vapor pressure deficit (VPD) influence ecosystem light use efficiency (LUE), a critical metric for assessing GPP, across different ecosystems and climatic zones at 80 flux tower sites based on in situ measurements and data assimilation products. Results indicate that LUE increases with temperature in spring, with higher correlation coefficients in colder regions (0.79–0.82) than in warmer regions (0.68–0.78). LUE reaches a plateau earlier in the season in warmer regions. LUE variations in summer are mainly driven by SWA, exhibiting a positive correlation indicative of a water‐limited regime. The relationship between the daily LUE and daytime temperature shows a clear seasonal hysteresis at many sites, with a higher LUE in spring than in fall under the same temperature, likely resulting from younger leaves being more efficient in photosynthesis. Drought stress influences LUE through SWA in all ranges of water availability; VPD variation under moderate conditions does not have a clear influence on LUE, but extremely high VPD (exceeding the threshold of 1.6 kPa, often observed during extreme drought‐heat events) causes a dramatic reduction of LUE. Our findings provide insight into how ecosystem productivities respond to climate variability and how they may change under the influence of more frequent and severe heat and drought events projected for the future.

Environmental Sciences & Ecology↗

Operando carbon corrosion measurements in fuel cells using boron-doped carbon supports

Carbonaceous materials are the most common catalyst supports in proton exchange membrane fuel cell (PEMFCs), yet their corrosion is one of the limiting factors in achieving high durability. Herein, we doped carbon supports with boron (B) to increase the corrosion-resistance of the support. Two types of B-doped carbons were synthesized and studied as platinum support materials. Further, they varied in their morphologies, surface areas, and the types of boron species. The durability of Pt/B-doped carbon catalysts was investigated using the US-DOE catalysts’ supports accelerated stress test (AST) and a mass-spectrometer connected to the fuel cell effluent stream to quantify the mass of corroded carbon support in operando. The addition of boron to the carbon increased the stability of Pt catalysts in long-term usage of PEMFC. After 4000 AST cycles, more than 50% of initial current density was preserved for the boron-containing systems, while less than 30% of it remained with Vulcan carbon (Pt/V). Also, the Pt/B-doped carbon samples demonstrated better electrochemical active surface area (ECSA) stability when compared to Pt/V. Carbon loss measurements showed that B-doped carbons have higher resistance to electrochemical corrosion than unmodified carbon. Specifically, the substitutional boron-doped carbon demonstrated an extremely high stability and low corrosion rate.

25 ENERGY STORAGE↗

Analysis of Deformation and Fracture Mechanisms in the Harvested High-Dose Baffle-Former Bolt with Stress-Corrosion Cracks Formed While in Service

This report presents the results of advanced mechanical testing conducted on miniature tensile specimens excised from an irradiated baffle-former bolt, a commercial pressurized water reactor component. The specimens were extracted from the midsection of the bolt shank, where the estimated damage dose reached 23 displacements per atom. The mechanical testing included the following tests: (1) conventional tensile testing at room temperature, augmented by digital image correlation (DIC) to enable noncontact strain measurements, and (2) in situ tensile testing within a scanning electron microscopy (SEM) instrument equipped with energy-dispersive x-ray spectroscopy (EDS) and electron backscatter diffraction (EBSD) detectors to evaluate active deformation and fracture mechanisms. Additionally, SEM fractographic analysis revealed alterations in the fracture mechanism from a predominantly ductile fracture in nonirradiated steel to a mixed fracture mode (still dominating ductile and minor cleavage spots) in irradiated specimens derived from the baffle bolts. The findings indicate a complex strain localization behavior for in-service irradiated steel specimens. Beyond conventional necking at the macro scale and defect-free channel formation at the micro scale, DIC results identified the presence of deformation bands approximately 100 μm in width. These bands consist of chains of grains exhibiting elevated local strain levels and may be considered an intermediate or mesoscale level of strain localization. These bands become discernible near the yield stress as localized hot spots, areas of elevated strain, persisting throughout most of the experiment. The formation of mesoscale deformation bands as a strain localization mechanism may exacerbate the defect-free channel formation in irradiated materials, further promoting irradiation-assisted stress corrosion crack initiation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Generalizable machine learning potentials for quantum-accurate predictions of non-equilibrium behavior in 2D materials

Machine learning interatomic potentials (ML-IAPs) are emerging as transformative tools in materials modeling, promising quantum-level accuracy at a fraction of the computational cost. However, their ability to generalize beyond equilibrium configurations and to reliably capture defect- and temperature-driven behavior remains underexplored. Here, we develop and benchmark two state-of-the-art ML-IAPs, Spectral Neighbor Analysis Potential (SNAP) and Allegro, on a comprehensive dataset for monolayer MoSe₂. Using density functional theory (DFT) as the reference, we evaluate their performance in capturing stress–strain behavior, phase transition energetics, defect evolution, edge stability, and fracture toughness. Allegro, a deep equivariant neural network potential, surpasses both SNAP and the classical Tersoff potential in accuracy, efficiency, and transferability. Importantly, both ML potentials accurately reproduce experimental fracture measurements and ab initio predictions of inversion domain formation—phenomena well beyond their training sets. Our findings establish ML-IAPs as viable replacements for traditional force fields in the study of non-equilibrium mechanical phenomena, enabling large-scale, high-fidelity simulations in 2D materials and beyond. In conclusion, this work provides a broadly applicable framework for data-driven modeling of structural and functional transformations under extreme conditions.

2D materials↗

Versatile Liquid Crystal Elastomer Formulations Using Amine-Acrylate Chemistry and Processing for Advanced Manufacturing

This study aims to tune rheological properties of liquid crystal elastomers (LCEs) through a strategic approach, leveraging the differing reaction rates of thiols and primary and secondary amines with acrylate monomers or the inclusion of processing additives to enable amenability to advanced manufacturing. We found that varying the time of oligomerization at elevated temperatures of amine-functional monomers with acrylate-functional monomers enabled simple control of rheological properties. Additionally, we could also control rheological properties by introducing reinforcing fillers or organic solvents. By varying the oligomerization conditions, we achieved a broad range of viscosities, from 1.1 Pa s to 560 Pa s as measured at 60 °C. When the rheological properties were varied through the incorporation of various solid and liquid inclusions, viscosities could range from less than 1 Pa s to nearly 1000 Pa s when measured at 60 °C. The shape morphing capabilities that are intrinsic to LCEs and the mechanical properties were also characterized. Here, we find that the oligomerization conditions and the addition of fillers influence shape morphing and energy absorption, as characterized by the stress–strain characteristics, further suggesting their potential to be used in energy dissipation applications where performance can be turned. Last, we demonstrate how the range of accessible rheological properties grants formulations amenable to various advanced manufacturing techniques.

Liquid chromatography↗

Isomeric yield ratios of fission products: A missing piece in reactor antineutrino summation calculations

The calculation of the spectrum of antineutrinos ($\bar{v}_e$) from a reactor is a complicated problem requiring several nuclear data and physics inputs. Many of these have been investigated thoroughly to improve calculations and properly account for uncertainties. One input which has heretofore escaped consideration is the fission-yield distribution between ground and isomeric states. Here, in this work, we explore the effect of incorporating newly evaluated isomeric yield ratios (IYR) for 43 fission products into summation calculations and identify the disproportionate importance of certain isotopes, particularly at higher energies. Our analysis indicates that updated IYRs contribute to a significant increase in the $\bar{v}_e$ spectrum around and above 7 MeV, with increases of more than 50% at higher energies. Through a detailed sensitivity study, we highlight a number of isotopes for which the IYR has a substantial effect on the $\bar{v}_e$ spectrum. This work stresses the critical role of isomeric yields in calculations of reactor $\bar{v}_e$ spectra and points to the necessity for their accurate experimental determination, especially for key fission products, in order to refine our understanding and address the observed anomalies between measured and calculated $\bar{v}_e$ spectra.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Mechanisms for Microseismicity Occurrence Due to CO 2 Injection at Decatur, Illinois: A Coupled Multiphase Flow and Geomechanics Perspective

Here, we numerically investigate the mechanisms that resulted in induced seismicity occurrence associated with CO 2 injection at the Illinois Basin–Decatur Project (IBDP). We build a geologically consistent model that honors key stratigraphic horizons and 3D fault surfaces interpreted using surface seismic data and microseismicity locations. We populate our model with reservoir and geomechanical properties estimated using well-log and core data. We then performed coupled multiphase flow and geomechanics modeling to investigate the impact of CO 2 injection on fault stability using the Coulomb failure criteria. We calibrate our flow model using measured reservoir pressure during the CO 2 injection phase. Our model results show that pore-pressure diffusion along faults connecting the injection interval to the basement is essential to explain the destabilization of the regions where microseismicity occurred, and that poroelastic stresses alone would result in stabilization of those regions. Slip tendency analysis indicates that, due to their orientations with respect to the maximum horizontal stress direction, the faults where the microseismicity occurred were very close to failure prior to injection. These model results highlight the importance of accurate subsurface fault characterization for CO 2 sequestration operations.

58 GEOSCIENCES↗

Isomeric Yield Ratios of fission products: a missing piece in reactor antineutrino summation calculations

The calculation of the spectrum of antineutrinos ( $\overline{V}$ e ) from a reactor is a complicated problem requiring several nuclear data and physics inputs. Many of these have been investigated thoroughly to improve calculations and properly account for uncertainties. One input which has heretofore escaped consideration is the fission yield distribution between ground and isomeric states. In this work, we explore the effect of incorporating newly evaluated isomeric yield ratios (IYR) for 43 fission products into summation calculations and identify the disproportionate importance of certain isotopes, particularly at higher energies. Our analysis indicates that updated IYRs contribute to a significant increase in the $\overline{V}$ e spectrum around and above 7 MeV, with increases of more than 50% at higher energies. Through a detailed sensitivity study, we highlight a number of isotopes for which the IYR has a substantial effect on the $\overline{V}$ e spectrum. This work stresses the critical role of isomeric yields in calculations of reactor $\overline{V}$ e spectra and points to the necessity for their accurate experimental determination, especially for key fission products, in order to refine our understanding and address the observed anomalies between measured and calculated $\overline{V}$ e spectra.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Materials Characterization: A Primer for Solid Phase Processing Applications

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development (LDRD) Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems produced via advanced manufacturing methods, such as solid phase processing, for use in national security and advanced energy applications (Smith 2021). As a two-year LDRD investment requiring focused research, the MCPC project applied only a subset of the wide range of available destructive and nondestructive characterization methods to provide data to the predictive modeling and data analytics tasks. The purpose of this report is to review a wide range of destructive and nondestructive characterization methods that are relevant in solid-phase processing (SPP) applications, but not necessarily applied in the MCPC Project as a guide to the planning of characterization activities in future research. Particular attention is given to measured characteristics that can correlate to other material characteristics, with a particular interest in nondestructive evaluation (NDE) that can be applied to samples obtained in the MCPC Project. Destructive examinations include tensile tests, optical and electron microscopy, micro-hardness, and residual stress tests. NDE tests include surface visual inspection, eddy current examination for cracks, 4-point potential drop, ultrasound, x-ray, and computed tomography.

36 MATERIALS SCIENCE↗

PET-FBA: A lightweight enzyme allocation and thermodynamics-constrained flux analysis approach to explore Escherichia coli metabolic adaptation to intracellular acidification

Escherichia coli employs diverse strategies to adapt to acidic environments that disrupt enzyme activity and the thermodynamic feasibility of essential reactions. To understand the impact of pH stress on cell metabolism, we present the PET-FBA (pH-, Enzyme protein allocation-, and Thermodynamics-constrained Flux Balance Analysis) framework. PET-FBA extends genome-scale modeling by integrating enzyme protein costs and reaction Gibbs free energy changes. Additionally, by incorporating pH-dependent enzyme kinetics in response to intracellular acidification, this framework enables the simulation of E. coli's metabolic adjustments across varying external pH levels. The model's accuracy is validated by comparing in silico growth simulations with experimental measurements under both anaerobic and aerobic conditions, as well as in silico gene knockouts of essential genes. By explicitly incorporating pH effects, our model accurately replicates the metabolic shift towards lactate production as the primary fermentation product at low pH in anaerobic conditions. This shift is only predicted when enzyme kinetics are dynamically adjusted as a function of pH. Further analysis revealed that this shift can be attributed to the reduced protein efficiency of the acetyl-CoA branch compared to lactate dehydrogenase under acidic stress, which then becomes crucial for maintaining NAD regeneration and cell growth at low pH. Furthermore, we identified strategies for enhancing cell growth under acidic anaerobic conditions by improving the enzyme activity of lactate dehydrogenase and pyruvate formate lyase, which increases NAD production efficiency and reduces enzyme protein allocation costs. Designed as a lightweight yet versatile framework, PET-FBA enables efficient genome-scale metabolic analysis. Using E. coli as a model system, our framework provides a systematic approach to understanding metabolic responses to environmental stress, pinpointing key metabolic bottlenecks, and identifying potential targets for strain optimization.

42 ENGINEERING↗

Concurrent measurement of strain and chemical reaction rates in a calcite grain pack undergoing pressure solution: Evidence for surface-reaction controlled dissolution

Pressure solution is inferred to be a significant contributor to sediment compaction and lithification, especially in carbonate sediments. For a sediment deforming primarily by pressure solution, the compaction rate should be directly related to the rate of calcite dissolution, transport along grain contacts, and calcite reprecipitation. Previous experimental work has shown that there is evidence that deformation in wet calcite grain packs is consistent with control by pressure solution, but considerable ambiguity remains regarding the rate limiting mechanism. We present the results of laboratory compaction experiments designed to directly measure calcite dissolution and precipitation rates (recrystallization rates) concurrently with strain rate to test whether measured rates are consistent with predicted rates both in absolute magnitude and time evolution. Recrystallization rates are measured using trace element chemistry (Sr/Ca, Mg/Ca) and isotopes (87Sr/86Sr) of fluids flowing slowly through a compacting grain pack as it is being triaxially compressed. Imaging techniques are used to characterize the grain contacts and strain effects in the post-experiment grain pack. Our data show that calcite recrystallization rates calculated from all three geochemical parameters are in approximate agreement and that the rates closely track strain rate. The geochemically inferred rates are close to predicted rates in absolute magnitude. Uncertainty in grain contact dimensions makes distinguishing between surface reaction control and diffusion control difficult. Measured reaction rates decrease faster than predicted from standard pressure solution creep flow laws. This inconsistency may indicate that calcite dissolution rates at grain contacts are more complex, and more time-dependent, than suggested by geometric models designed to predict grain contact stresses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling the contributions to acoustic nonlinearity from complex dislocation networks using 3D dislocation dynamics

Nonlinear ultrasonic parameters are highly sensitive to microstructural features that affect macroscale material behavior, providing a nondestructive means to characterize their evolution. Although dislocations are known to be a strong source of acoustic nonlinearity, establishing quantitative links between the acoustic nonlinearity parameter (β), measured via Second Harmonic Generation, and dislocation morphology—such as dislocation length and density—remains an open challenge. This work advances the numerical modeling of dislocation–β relationships using 3D dislocation dynamics (DD) simulations in two approaches: a “static” method computing strain and stress fields from dislocation configurations in the absence of external loading, and a “quasi-static” method to estimate β from the curvature of dislocation lines under applied load. First, the static method is combined with finite element analysis to investigate a recent assertion that heterogeneous initial strain fields can induce higher harmonic generation in a linear elastic medium; the present results do not corroborate this outcome. Then, the quasi-static method is applied to multiple-dislocation scenarios through parametric studies, revealing behaviors not predicted by analytical models, such as the competing interactions of edge and screw dislocations and the significant influence of applied stress on β. Finally, the simulations are used to model SHG experimental results and validate the hypothesis that β can decrease during plastic deformation, despite increasing dislocation density. As the DD code used here is open-source, it provides a practical platform for future investigation into microstructure–β relationships important to the interpretation of SHG results.

Materials science↗

Understanding the L-H isotope effect at the DIII-D tokamak and advancements in synthetic turbulence diagnostics

Abstract It is determined that while heat flux differences between hydrogen and deuterium isotope experiments result from natural differences in carbon impurity content at DIII-D, it is not the origin of the low to high confinement mode (L-H) transition isotope effect. More specifically, a two times larger edge radial electric field in hydrogen compared to deuterium is uncovered and believed to play an important role. The origin of this radial electric field difference is determined to have two possible origins: differences in poloidal rotation and turbulent Reynolds stress in the closed field line region, and increased outer strike point temperatures and space potentials on open field lines. Experimental observations from both profile and turbulence diagnostics are supported by nonlinear gyrokinetic simulations using the code CGYRO. Simulations illustrated heat transport isotope effects in the plasma edge and shear layer resulting from differences in impurity content, electron non-adiabaticity, and main ion mass dependent E × B shear stabilization. Turbulence prediction comparisons from flux-matched CGYRO simulations to experimental measurements including electron temperature, density and velocity fluctuations are found to be in good agreement with available data. A dedicated DIII-D experiment in hydrogen was performed to seed more carbon than naturally occurring, to match deuterium experiments, and possibly reduce the L-H power threshold based on gyro-kinetic predictions. To our surprise, while ion temperature gradient (ITG) turbulence was stabilized, nodiscernible change in L-H power threshold were observed in these special hydrogen experiments. In particular, it is noticed that the edge radial electric field and Reynolds stress were observed as nearly unchanging in the presence of ITG stabilization. These experimental data have enabled a more comprehensive picture of the multitude of isotope effects at play in fusion experiments, and the important potential connection between the confined and unconfined plasma regions in regulating L-H transition dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Refractive index of lithium fluoride at high dynamic stresses

Alkali halides are prototypical ionic solids whose refractive index is a fundamental property related to their lattice structure and ionic polarizability. In particular, lithium fluoride (LiF) has the largest band gap of any known transparent material and maintains transparency at high pressures, making it well suited for use as an optical window in dynamic compression experiments. While empirical fits to the measured density dependence of the refractive index have been provided, a model that is valid over the entire pressure range of experiments and based on a polarization-based theoretical description is lacking. We present a refractive index model for dynamically compressed LiF based on the Lorentz-Lorenz equation, where the molecular polarizability is determined using a single oscillator model with a strain polarizability parameter Λ=0.73. Here, we show that our modeling approach provides an excellent match to the LiF refractive index data for both shock and ramp compression experiments to 900 GPa (density compression greater than threefold). Additionally, updated fits are provided to determine the refractive index correction for LiF windows used in dynamic compression experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Delamination-informed lifecycle decisions: A dielectric and machine learning framework for composite sorting and recycling

Composite materials are widely used in aerospace, marine, and automotive sectors due to their high strength-to-weight ratio and durability. However, their long-term reliability can be compromised by damage accumulation. Specifically, delamination initiation serves as a precursor to structural failure, which is often difficult to detect during damage inspection. Identifying and sorting delamination initiation in samples not only increases operational safety while providing critical information for end-of-life decisions, which influences both the service life extension value and the efficiency of fiber extraction during recycling. This research addresses two challenges: (1) developing a nondestructive, ex-situ framework to sort composite materials based on damage severity, particularly delamination, and (2) understanding how damage in composites influences resin removal during pyrolysis. Both experimental work and finite element analysis were performed to predict critical stress levels that are associated with delamination onset. Based on these results, three loading levels 50 %, 75 %, and 90 % of maximum stress, were selected for controlled experiments, generating composite samples with varying extents of damage for machine learning model training. Microscopic imaging of these samples confirmed the damage progression from matrix cracking to delamination, validating the computational predictions. We explored supervised machine learning using dielectric measurements to classify damage states. Preliminary results show an artificial neural network can identify early delamination which is a potential precursor to failure, with 94.44 % accuracy on our dataset. A parallel investigation into the effect of damage severity on pyrolysis recycling showed that heavily delaminated samples required significantly less energy for comparable matrix removal than undamaged samples.

dielectric variables↗