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Spinodal electronic phase separation during insulator-metal transitions

Electronic phase transitions such as insulator-metal transitions are common in strongly correlated systems. Here, using a combination of thermodynamic linear-stability analysis and phase-field simulations and employing VO 2 as a prototypical example, we predict that an insulator-metal transition driven by photoexcitation may involve an intermediate, modulated charge density state with a temperature-dependent characteristic wavelength. It is shown that such an intermediate two-phase electronic state is formed through a spinodal mechanism and that its formation can be generic for insulator-metal transitions driven by fast stimuli. This transient electronic phase separation is expected to stimulate future experimental and computational efforts.

36 MATERIALS SCIENCE↗

Spontaneous fission of the odd- Z isotope 255 Db

Experiments conducted at Lawrence Berkeley National Laboratory's 88-Inch Cyclotron Facility aimed to produce and study the decay of the previously unobserved isotope 255 Db. This isotope was produced in the 206 Pb( 51 V, 2⁢n) 255 Db reaction, separated from unreacted beam material and reaction by-products with the Berkeley Gas-filled Separator, and then implanted into a double-sided silicon-strip detector at the BGS focal plane. Decay properties of 255 Db were determined from the analysis of evaporation residue (EVR) fission and EVR-α–α correlations. The properties of this new isotope of dubnium differ dramatically from those of its neighboring Db isotopes. 255 Db was found to decay primarily by spontaneous fission (SF) with a small α-decay branch, where the average half-life of the observed decays was t 1/2 = 2.6$^{+0.4}_{– 0.3}$ ms. Theoretical calculations were performed using the Wentzel-Kramers-Brillouin approximation, with parameters calculated within a self-consistent microscopic approach, to see if these unique properties could be reproduced. A SF half-life estimate is obtained that closely matches the measured value, while simultaneously pointing out the sensitivities that need to be further constrained in future work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Field-Aged Glass/Backsheet and Glass/Glass PV Modules: Encapsulant Degradation Comparison

Ethylene vinyl acetate (EVA) is the predominant encapsulant in crystalline-silicon photovoltaic (PV) modules; however, its degradation is a subject of major concern, which causes significant power loss under field conditions. This article presents a comparison of EVA degradation in field-aged PV modules with glass/backsheet (G/B) and glass/glass (G/G) architectures. Modulelevel characterization included UV fluorescence imaging and I-V measurements. Material analytical techniques, including colorimetry, differential scanning calorimetry, thermogravimetric analysis, Fourier transform infrared spectroscopy, and Raman spectroscopy, were performed to correlate the module performance parameters with EVA material properties. An intense EVA discoloration in G/G modules was observed, which was corroborated by higher module Isc and Pmax degradation rates compared with its counterpart G/B modules. Higher power degradation was accompanied by a significant increase in EVA crosslinking, vinyl acetate content, yellowness index, and presence of functional groups containing unsaturated moieties that are linked to degradation products of photothermal reaction, and a higher decrease in the degree of crystallinity. The absence of a polymeric backsheet in hermetically sealed G/G modules, which restricts photobleaching and enhances the entrapment of volatile acetic acid and other degradation by-products, plays a major role in causing higher EVA degradation in G/G modules. This article concludes that EVA might have been a good choice of an encapsulant for the G/B modules over the decades, but it may prove to be an inappropriate choice for the G/G modules because of potential degassing, corrosion, and/or discoloration issues. Ionomers or polyester-based encapsulants like polyolefins could be best suited for G/G modules as it appears to be a current trend in the industry.

14 SOLAR ENERGY↗

Mitigating Algorithmic Bias in Cancer Site Classification Models

Purpose Integrating artificial intelligence in cancer diagnostics has improved tumor classification beyond rule-based systems. Despite these advancements, these models may still encode demographic biases. We conducted a large-scale, applied bias-probing study of a deep learning–based cancer site classifier to quantify race information encoded in document embeddings. We then evaluated how performance changes when race-correlated embedding dimensions are removed in a post-training sensitivity analysis. Methods The cancer site classifier was trained using 3.5 million electronic cancer pathology reports from six of the National Cancer Institute's SEER registries. We trained a hierarchical self-attention network to generate 400-dimensional document embeddings. These embeddings were used to train two downstream, gradient-boosted decision tree classifiers: one to classify the cancer sites and another to predict racial categories. We identified overlapping features by intersecting the top 50 feature-importance rankings from the site and race models and computed their cumulative feature importance in each model. As a post hoc sensitivity analysis, we progressively pruned these overlapping dimensions, retrained the site model, and compared overall macro-F1 and accuracy, race-stratified macro-F1, and group fairness metrics on the basis of demographic parity and equalized odds before and after pruning. Results The analysis revealed minimal feature overlap between the cancer site and race prediction models, and the cumulative importance scores indicated a negligible influence of racial information on clinical predictions. Post-training pruning of overlapping features did not compromise the models' diagnostic accuracy, with a 0.07% loss in accuracy. Conclusion Our findings demonstrate that HiSAN-generated embeddings from SEER data can be used effectively in cancer site classification without significant demographic bias influencing the outcomes. Post-training pruning therefore functions as a practical audit and sensitivity check.

Shivanna, Abhishek [ORNL] (ORCID:0009000665228593)↗

DES-Y3 galaxies & ACT DR4 CMB lensing tomography

We present a measurement of the cross-correlation between the \maglim galaxies selected from the Dark Energy Survey (DES) first three years of observations (Y3) and cosmic microwave background (CMB) lensing from the Atacama Cosmology Telescope (ACT) Data Release 4 (DR4), reconstructed over $\sim 436$ $\sqdeg$ of the sky. Our galaxy sample, which covers $\sim 4143$ $\sqdeg$, is divided into six redshift bins spanning the redshift range of $0.20<z<1.05$. We adopt a blinding procedure until passing all consistency and systematics tests. After imposing scale cuts for the cross-power spectrum measurement, we reject the null hypothesis of no correlation at 9.1$\sigma$. We constrain cosmological parameters from a joint analysis of galaxy and CMB lensing-galaxy power spectra considering a flat \LCDM model, marginalized over 23 astrophysical and systematic nuisance parameters. We find the clustering amplitude $S_8\equiv \sigma_8 (\Omega_m/0.3)^{0.5} = 0.75^{+0.04}_{-0.05}$. In addition, we co nstrain the linear growth of cosmic structure as a function of redshift. Our results are consistent with recent DES Y3 analyses and suggest a preference for a lower $S_8$ compared to results from measurements of CMB anisotropies by the \textit{Planck} satellite, although at a mild level ($< 2 \sigma$) of statistical significance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Hall Effect Study of the Metamagnetic Transition in the Sr 4 (Ru 0.99 Fe 0.01 ) 3 O 10 Nanosheet

Sr 4 (Ru 0.99 Fe 0.01 ) 3 O 10 shows a ferromagnetic (FM) transition at T C ~ 105 K with the magnetic easy axis in the ab plane, followed by a metamagnetic transition (MMT) at low temperatures when the magnetic field H is applied along the c axis, which is in sharp contrast to that of the pure Sr 4 Ru 3 O 10 , where the easy axis is along the c axis and the MMT is in the ab plane. Here, we studied the MMT in the Sr 4 (Ru 0.99 Fe 0.01 ) 3 O 10 nanosheet by the Hall effect. It was found that the ordinary Hall coefficient of Sr 4 (Ru 0.99 Fe 0.01 ) 3 O 10 is almost the same as that of the pure Sr 4 Ru 3 O 10 , while a sudden increase in the Hall resistance R xy is observed below ~50 K, above which the R xy presents the conventional anomalous Hall effect up to T C . Analysis of the results indicates that the MMT has no direct correlation to the electronic structure but closely relates to the magnetic moment locking, where the magnetic-field-induced breakdown of the locked moments is responsible for the MMT.

36 MATERIALS SCIENCE↗

Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™

Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool.

environmental monitoring↗

Near-Field Passive Wireless Sensor for High-Temperature Metal Corrosion Monitoring

This work focuses on the fabrication and evaluation of a passive wireless sensor for the monitoring of the temperature and corrosion of a metal material at high temperatures. An inductor–capacitor (LC) resonator sensor was fabricated through the screen printing of Ag-based inks on dense polycrystalline Al 2 O 3 substrates. The LC design was modeled using the ANSYS HFSS modeling package, with the LC passive wireless sensors operating at frequencies from 70 to 100 MHz. The wireless response of the LC was interrogated and received by a radio frequency signal generator and spectrum analyzer at temperatures from 50 to 800 °C in real time. The corrosion kinetics of the Cu 110 was characterized through thermogravimetric (TGA) analysis and microscopy images, and the oxide thickness growth was then correlated to the wireless sensor signal under isothermal conditions at 800 °C. The results showed that the wireless signal was consistent with the corrosion kinetics and temperature, indicating that these two characteristics can be further deconvoluted in the future. In addition, the sensor also showed a magnitude- and frequency-dependent response to crack/spallation events in the oxide corrosion layer, permitting the in situ wireless identification of these catastrophic events on the metal surface at high temperatures.

36 MATERIALS SCIENCE↗

Effects of strain, disorder, and Coulomb screening on free-carrier mobility in doped cadmium oxide

Here, the interplay of stress, disorder, and Coulomb screening dictating the mobility of doped cadmium oxide (CdO) is examined using Raman spectroscopy to identify the mechanisms driving dopant incorporation and scattering within this emerging infrared optical material. Specifically, multi-wavelength Raman and UV-vis spectroscopies are combined with electrical Hall measurements on a series of yttrium (X = Y) and indium (X = In) doped X:CdO thin-films. Hall measurements confirm n-type doping and establish carrier concentrations and mobilities. Spectral fitting along the low-frequency Raman combination bands, especially the TA+TO(X) mode, reveals that the evolution of strain and disorder within the lattice as a function of dopant concentration is strongly correlated with mobility. Coupling between the electronic and lattice environments was examined through analysis of first- and second-order longitudinal–optical phonon–plasmon coupled modes that monotonically decrease in energy and asymmetrically broaden with increasing dopant concentration. By fitting these trends to an impurity-induced Fröhlich model for the Raman scattering intensity, exciton–phonon and exciton–impurity coupling factors are quantified. These coupling factors indicate a continual decrease in the amount of ionized impurity scattering with increasing dopant concentration and are not as well correlated with mobility. This shows that lattice strain and disorder are the primary determining factors for mobility in donor-doped CdO. In aggregate, the study confirms previously postulated defect equilibrium arguments for dopant incorporation in CdO while at the same time identifying paths for its further refinement.

42 ENGINEERING↗

Systematic study of projection biases in weak lensing analysis

We present a systematic study of projection biases in the weak lensing analysis of the first year of data from the Dark Energy Survey (DES) experiment. In the analysis we used a $\Lambda$CDM model and three two-point correlation functions. We show that these biases are a consequence of projecting, or marginalizing, over parameters like $h$, $\Omega_b$, $n_s$ and $\Omega_\nu h^2$ that are both poorly constrained and correlated with the parameters of interest like $\Omega_m$, $\sigma_8$ and $S_8$. Covering the relevant parameter space we show that the projection biases are a function of where the true values of the poorly constrained parameters lie with respect to the parameter priors. For example, biases in the position of the posteriors can exceed the 1.5$\sigma$ level if the true values of $h$ and $n_s$ are close to the top of the prior's range and the true values of $\Omega_b$ and $\Omega_\nu h^2$ are close to the bottom of the range of their priors. We also show that in some cases the 1D credible intervals can be over-specified by as much as 30% and coverage can be as low as 27%. Finally we estimate these projection biases for the analysis of three and six years worth of DES data.

79 ASTRONOMY AND ASTROPHYSICS↗

Local lattice distortions and electronic orders in strongly correlated systems by resonant total x-ray scattering: A case study of A Pt 2 X 2 intermetallics ( A = U , Ce, or La and X = Si or Ge)

Revealing local lattice distortions in physical systems is nontrivial, largely because such structural features often are not necessarily amenable to traditional crystallographic investigations. This poses limits to our understanding of the underlying physic, particularly in the case of strongly correlated systems where structural, electronic and magnetic degrees of freedom are intertwined. Using resonant total x-ray scattering coupled to differential pair distribution function analysis, we reveal the presence of pronounced local lattice distortions in the square net Pt planes in the prototypical strongly correlated APt 2 X 2 intermetallics (A = U, Ce or La and X = Si or Ge). The distortions are present before charge density wave, magnetic, Kondo lattice coherence and/or superconducting orders emerge in these materials and, as density functional calculations suggest, are likely to affect them. Finally, our study sheds light on the poorly known interactions between electronic orders and structural disorder in strongly correlated systems and also demonstrates an advanced experimental approach to determine it that is relevant to any physical system showing deviations from perfect crystallinity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Southern Stellar Stream Spectroscopic Survey (S{sup 5}): Chemical Abundances of Seven Stellar Streams

We present high-resolution Magellan/MIKE spectroscopy of 42 red giant stars in seven stellar streams confirmed by the Southern Stellar Stream Spectroscopic Survey (S {sup 5}): ATLAS, Aliqa Uma, Chenab, Elqui, Indus, Jhelum, and Phoenix. Abundances of 30 elements have been derived from over 10,000 individual line measurements or upper limits using photometric stellar parameters and a standard LTE analysis. This is currently the most extensive set of element abundances for stars in stellar streams. Three streams (ATLAS, Aliqa Uma, and Phoenix) are disrupted metal-poor globular clusters, although only weak evidence is seen for the light-element anticorrelations commonly observed in globular clusters. Four streams (Chenab, Elqui, Indus, and Jhelum) are disrupted dwarf galaxies, and their stars display abundance signatures that suggest progenitors with stellar masses ranging from 10{sup 6} to 10{sup 7} M {sub ⊙}. Extensive description is provided for the analysis methods, including the derivation of a new method for including the effect of stellar parameter correlations on each star’s abundance and uncertainty. This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile.

79 ASTRONOMY AND ASTROPHYSICS↗

High-Precision Characterization of Seismicity from the 2022 Hunga Tonga-Hunga Ha'apai Volcanic Eruption

The earthquake swarm accompanying the January 2022 Hunga Tonga-Hunga Ha'apai (HTHH) volcanic eruption includes a large number of posteruptive moderate-magnitude seismic events and presents a unique opportunity to use remote monitoring methods to characterize and compare seismic activity with other historical caldera-forming eruptions. We compute improved epicentroid locations, magnitudes, and regional moment tensors of seismic events from this earthquake swarm using regional to teleseismic surface-wave cross correlation and waveform modeling. Precise relative locations of 91 seismic events derived from 59,047 intermediate-period Rayleigh- and Love-wave cross-correlation measurements collapse into a small area surrounding the volcano and exhibit a southeastern time-dependent migration. Regional moment tensors and observed waveforms indicate that these events have a similar mechanism and exhibit a strong positive compensated linear vector dipole component. Precise relative magnitudes agree with regional moment tensor moment magnitude ($M_w$) estimates while also showing that event sizes and frequency increase during the days after the eruption followed by a period of several weeks of less frequent seismicity of a similar size. The combined information from visual observation and early geologic models indicate that the observed seismicity may be the result of a complex series of events that occurred after the explosive eruption on 15 January, possibly involving rapid resupply of the magma chamber shortly after the eruption and additional faulting and instability in the following weeks. In addition, we identify and characterize an $M_w$ 4.5 event five days before the paroxysmal explosion on 15 January, indicating that additional seismic events preceding the main eruption could have been identified with improved local monitoring. As a result, our analysis of the HTHH eruption sequence demonstrates the value of potentially utilizing teleseismic surface-wave cross correlation and waveform modeling methods to assist in the detailed analysis of remote volcanic eruption sequences.

58 GEOSCIENCES↗

Non-Gaussianity constraints with anisotropic μ distortion measurements from Planck

ABSTRACT Primordial non-Gaussianity can source μ-distortion anisotropies that are correlated with the large-scale temperature and polarization signals of the cosmic microwave background (CMB). A measurement of μT and μE correlations can therefore be used to constrain it on wavelengths of perturbations not directly probed by the standard CMB anisotropies. We carry out a first rigorous search for μ-distortion anisotropies with Planck data, applying the well-tested constrained ILC component-separation method combined with the needlet framework. We correlate the reconstructed μ map with the CMB anisotropies to derive constraints on the amplitude fNL of the local form bispectrum, specifically on the squeezed configurations with effective wavenumbers $k_s \simeq {740}\, \mathrm{Mpc^{-1}}$ and $k_L \simeq {0.05}\, \mathrm{Mpc^{-1}}$, improving previously estimated constraints by more than an order of magnitude. This enhancement is owing to the fact that we are able to use the full multipole information by carefully controlling biases and systematic effects in the analysis. We also for the first time incorporate constraints from measurements of μE correlations, which further tighten the limits. A combination of the derived Planck μT and μE power spectra yields |fNL| ≲ 6800 (95 per cent c.l.) on this highly squeezed bispectrum. This is only ≃3 times weaker than the anticipated constraint from Litebird. Furthermore we show that a combination of Litebird with Planck can improve the expected future constraint by ${\simeq}20{{\%}}$. These limits can be used to constrain multifield inflation models and primordial black hole formation scenarios, thus providing a promising novel avenue forward in CMB cosmology.

Rotti, Aditya (ORCID:0000000341245226)↗

Cycle-to-cycle variability in spark-assisted compression ignition engines near optimal mean combustion phasing

Stoichiometric spark-assisted compression ignition (SACI) combustion with exhaust gas recirculation (EGR) dilution has demonstrated higher part-load thermal efficiencies compared to spark-ignited engines, while maintaining ultra-low tailpipe emissions. However, SACI is often characterized by high cyclic variability in heat release or torque output, which poses a challenge to its implementation in light-duty vehicles. This paper presents an experimental investigation of cyclic variability in stoichiometric SACI combustion under EGR-dilute conditions, while maintaining mean combustion phasing (θ 50 ) near optimal timing for thermal efficiency. The present work focuses on SACI conditions where the flame-based heat release fraction is between approximately 10% and 40% of the overall heat release, and therefore contributes significantly to the combustion process. For the SACI conditions examined, the variability in θ 50 was driven by variability in autoignition timing, which in turn correlated with the start of measurable heat release (θ 02 ). High variability in θ 50 caused unstable work output due to very late combustion with poor or no end-gas autoignition. The use of a high ignition energy dual-coil offset ignition system had negligible impact in reducing θ 50 variability. Analysis of experimental data from close to 1000 operating conditions showed that the magnitude of θ 50 variability correlates with the flame-based heat release fraction ([Formula: see text]), for a large range of intake pressures, spark timings and exhaust gas recirculation levels. For the SACI conditions examined, combustion phasing variability was largely determined by flame-based combustion and particularly the initial flame formation (θ IGN-02 ), and minimally by the end-gas autoignition heat release. The analysis also demonstrated that θ 50 variability is amplified as the contribution of the flame to the overall heat release increases.

Engineering↗

Observation of Enhanced Long-Range Elliptic Anisotropies Inside High-Multiplicity Jets in p p Collisions at s = 13 TeV

A search for collective effects inside jets produced in proton-proton collisions is performed via correlation measurements of charged particles using the CMS detector at the CERN LHC. The analysis uses data collected at a center-of-mass energy of s = 13 TeV , corresponding to an integrated luminosity of 138 fb − 1 . Jets are reconstructed with the anti- k T algorithm with a distance parameter of 0.8 and are required to have transverse momentum greater than 550 GeV and pseudorapidity | η jet | < 1.6 . Two-particle correlations among the charged particles within the jets are studied as functions of the particles’ azimuthal angle and pseudorapidity separations ( Δ ϕ * and Δ η * ) in a jet coordinate basis, where particles’ η * , ϕ * are defined relative to the direction of the jet. The correlation functions are studied in classes of in-jet charged-particle multiplicity up to N ch j ≈ 100 . Fourier harmonics are extracted from long-range azimuthal correlation functions to characterize azimuthal anisotropy for | Δ η * | > 2 . For low- N ch j jets, the long-range elliptic anisotropic harmonic, v 2 * , is observed to decrease with N ch j . This trend is well described by Monte Carlo event generators. However, a rising trend for v 2 * emerges at N ch j ≳ 80 , hinting at a possible onset of collective behavior, which is not reproduced by the models tested. This observation yields new insights into the dynamics of jet evolution in the vacuum. © 2024 CERN, for the CMS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A High-Quality Genome-Scale Model for Rhodococcus opacus Metabolism

Rhodococcus opacus is a bacterium that has a high tolerance to aromatic compounds and can produce significant amounts of triacylglycerol (TAG). Here, we present iGR1773, the first genome-scale model (GSM) of R. opacus PD630 metabolism based on its genomic sequence and associated data. The model includes 1773 genes, 3025 reactions, and 1956 metabolites, was developed in a reproducible manner using CarveMe, and was evaluated through Metabolic Model tests (MEMOTE). We combine the model with two Constraint-Based Reconstruction and Analysis (COBRA) methods that use transcriptomics data to predict growth rates and fluxes: E-Flux2 and SPOT (Simplified Pearson Correlation with Transcriptomic data). Growth rates are best predicted by E-Flux2. Flux profiles are more accurately predicted by E-Flux2 than flux balance analysis (FBA) and parsimonious FBA (pFBA), when compared to 44 central carbon fluxes measured by 13C-Metabolic Flux Analysis (13C-MFA). Under glucose-fed conditions, E-Flux2 presents an R2 value of 0.54, while predictions based on pFBA had an inferior R2 of 0.28. We attribute this improved performance to the extra activity information provided by the transcriptomics data. For phenol-fed metabolism, in which the substrate first enters the TCA cycle, E-Flux2’s flux predictions display a high R2 of 0.96 while pFBA showed an R2 of 0.93. We also show that glucose metabolism and phenol metabolism function with similar relative ATP maintenance costs. These findings demonstrate that iGR1773 can help the metabolic engineering community predict aromatic substrate utilization patterns and perform computational strain design.

Roell, Garrett W.↗

Connecting mechanical properties to hydrogen defects in PAN-based carbon fibers

Atomic-level defects dictate the mechanical properties of carbon fibers and strong correlations have been established between the crystallite sizes and mechanical properties. We recently demonstrated similar correlations with hydrogen content, but reliably quantifying the hydrogen content is not possible using only inelastic neutron scattering experiments. Here, we present prompt-gamma activation analysis (PGAA) experiments collected on 20 commercially available carbon fibers to quantify the hydrogen content of carbon fibers and find correlations between fiber modulus and hydrogen content. We then evaluate the role of hydrogen defect type and connect the PGAA results to both newly acquired and recently reported inelastic neutron scattering experiments. In conclusion, we find that intercalated hydrogen defects are preferentially removed at carbonization temperatures required for high-modulus fibers, potentially giving rise to voids within the carbon fibers that undermine their tensile strength.

36 MATERIALS SCIENCE↗