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Shallow waters hold ecological and economic importance. Traditional reflectance forward models, such as Hydrolight and Monte Carlo (MC), are difficult to access or time-consuming. Two-stream models show great performance in radiative transfer simulation, but most of them are applied in other mediums, or ignore the asymmetry scattering characteristic of shallow water. In this article, we propose a general multilayer analytical radiative transfer (GMART)-based model considering the realistic volume scattering function (VSF) of water bodies, which is theoretically applicable to various shallow waters. GMART results are validated against Hydrolight and MC. The mean absolute percentage error (MAPE) of GMART and Hydrolight remote sensing reflectance ( $R_{\text {rs}}$ ) among different combinations of the bottom depth, solar zenith angle, and wind speed spans in ranges of 5.37%–28.86%, 3.37%–39.28%, and 4.91%–26.73%, with root mean square error (RMSE) values from $1.73\times 10^{-4}$ to $4.49\times 10^{-3}$ , from $2.68\times 10^{-4}$ to $1.85\times 10^{-2}$ , and from $1.59\times 10^{-4}$ to $2.92\times 10^{-3}\,\,sr^{-1}$ , respectively, for the coral, sand, and seagrass bottom. Comparisons of the bidirectional reflectance function (BRF) with Hydrolight and MC indicate the capacity of GMART to compute bidirectional reflectance. In addition, a comparison with field measurements is carried out. The minimum MAPE and RMSE between the modeled and measured normalized $R_{\text {rs}}$ among several stations in the Sanya coastal area are 13.99%, and 0.061, respectively. The mean MAPE and RMSE among the six stations are 21.38% and 0.083, respectively. The field validation underscores the feasibility of the model in shallow water radiative transfer. Compared with MC, the computational efficiency of GMART is much higher. The new model is shown to be an alternative and efficient tool capable of addressing shallow water-related challenges across diverse environmental conditions.

Bathymetric inversions constitute a key preliminary step when characterizing coral topography. The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) is poised to provide true values for satellite-derived bathymetry (SDB) in the absence of measured data. Nevertheless, the influences of the different available algorithms and atmospheric correction (AC) processes applied to construct SDB over coral reef waters are still poorly understood. In this article, three empirical-based bathymetric algorithms [the linear ratio model (LRM), polynomial ratio model (PRM), and exponential ratio model (ERM)] and three ACs [AC for the operational land imager (OLI) lite (ACOLITE), sea-viewing wide field-of-view sensor (SeaWiFS) data analysis system (SeaDAS), and sentinel 2 (atmospheric) correction (Sen2Cor)] are evaluated with Sentinel-2A/B multispectral imagery to achieve fine-spatial-resolution bathymetric information. The bathymetry estimates produced by fusing the Sentinel-2A/B and ICESat-2 datasets using the three models exhibit sufficient accuracies, with low percent errors and mean absolute errors (MAEs) between 0.44 and 0.74 m and root-mean-square errors (RMSEs) between 0.61 and 0.96 m. In all cases, the PRM outperforms the ERM and LRM. The AC method comparisons show that the performance of ACOLITE is better than those of Sen2Cor and SeaDAS. The obtained depth estimates are less sensitive to the impacts of the AC methods in relatively shallow waters than in relatively deep waters, and ACOLITE performs more stably. Overall, the PRM coupled with the ACOLITE method performs best. With depths extracted from ICESat-2, high-spatial-resolution SDB data capable of supporting the long-range goal of coral topography analyses are attainable even without in situ datasets.

Mapping bathymetry with satellite-based imagery for optically shallow waters is important for the management of coastal areas. However, mapping ultrahigh-spatial-resolution bathymetry (spatial resolution < 5 m) for a wide range of coastal optically shallow waters is limited by high cost and the absence of in situ data. Therefore, in this study, a new downscaled bathymetric mapping approach [downscaled bathymetric mapping approach-red-green-blue (DBMA-RGB)] was established using freely accessed Landsat -8 (L8) (spatial resolution = 30 m) and cost-effective Google Earth Pro-exported ultrahigh-spatial-resolution RGB imagery. The new approach introduced the scale-invariance assumption that the log-ratio model (LRM) that is calibrated at a high scale is valid at a low scale. To reduce the inversion errors from L8 imagery, a theoretical maximum detection depth (MDD) model was proposed for the optimization-based inversion method, which is the foundation of DBMA-RGB for working without in situ bathymetric data. The theoretical MDDs overall matched the true MDDs except for the abnormal values, with root mean square error and correlation coefficient values of 3.30 m and 0.68, respectively. In addition, a set of correction coefficients was obtained to improve the accuracy of the water depth derived from L8 imagery. Finally, the DBMA-RGB was applied to the RGB imagery of 16 coastal areas around the world, incorporating the bathymetric results from L8 imagery. The comparison results indicated that the DBMA-RGB yielded similar results to the LRM calibrated using in situ bathymetric data. In summary, DBMA-RGB demonstrated its feature in accurately mapping ultrahigh-spatial-resolution bathymetry for a wide range of coastal optically shallow waters without in situ bathymetric data.

ABSTRACTKnowledge about the optical features of benthic objects is essential for quantifying spectral signatures, remote sensing-based mapping, and ecological monitoring in coral reefs. However, the spectral identification of benthic species and the accurate measurement of the in situreflectance spectra of relevant research objects remain underexplored. An underwater radiation measuring system suitable for coral reef environments was specifically designed to obtain in situreflectance spectra and match benthic photographs of various substrate targets. This instrument has the advantages of obtaining hyperspectral, dual-channel simultaneous measurements, and automatically adjusting the integration time according to the light intensity. Based on in situhyperspectral datasets, the linear discriminant analysis (LDA) was used for exploring and discriminating spectral characteristics from three taxonomic ranks, which include typical substrates of six community groups, nine coral families, and six Acroporidaespecies. In situfull-resolution (1-nm) spectra provided the best discrimination ability with mean accuracies of 97.5%, 90.9%, and 91.6% for typical substrates, coral families, and coral species, respectively. The spectral abilities of remote sensors were assessed by applying the spectral response functions of three multispectral sensors (Landsat 8 OLI, Sentinel-2A, and World View-2) to the full-resolution spectra. Discrimination analyses of the simulated spectra demonstrated that the spectral separations of typical substrates might be apparent, with overall classification accuracies of 89.6%, 88.2%, and 90.4% for the Landsat 8 OLI, Sentinel-2A, and World View-2 sensors, respectively. The spectral separation for different corals, however, may not be effective when using multispectral sensors. The discrimination analyses of families and species produced overall classification accuracies of 67.1% and 69.6%, respectively, for the Landsat 8 OLI, 56.0% and 56.0% for the Sentinel-2A sensor, and 64.5% and 61.8% for the World View-2 sensor. In summary, this method has the potential for identifing substrate targets in communities and taxonomic coral groups by applying in situhyperspectral datasets. Furthermore, multispectral satellite sensors are currently inadequate for spectrally separate corals, while spectral discrimination is possible and practical for different substrate targets with visual spectral differences.

In order to effectively remove grease for the detection of sulfonamides, a non-toxic and low-cost hierarchical porous zirconia material was synthesized using the dual template method. The lipid impurities in an animal-derived food matrix can be absorbed by hierarchical zirconia. A ZrO2prepolymer was synthesized by mixing amphiphilic triblock copolymer poly(ethylene glycol)-block-poly(propylene glycol)-block-poly(ethylene glycol) (P123) with tannin extract as the double template and Zr(SO4)2as the metal source. After aging, drying and calcination at high temperature, the prepolymer transforms into a hierarchical porous structure. The synthesized materials were characterized using SEM, XRD, FT-IR, and BET. The results show that the material has an abundant pore structure and hierarchical pore structure. The adsorption conditions were optimized. The hierarchical porous ZrO2synthesized by this method is relatively uniform, and is characterized by large specific surface area as well as high lipid impurity adsorption capacity. Through the optimization experiment of adsorption conditions, we found that hierarchical porous ZrO2can reach the maximum adsorption capacity in 60 min under weak acidic conditions. The samples are used for actual sample testing such as HPLC of sulfadiazine (SD), sulfamethazine (SM2), sulfamethoxydiazine (SMD), sulfamethoxazole (SIZ) and sulfadimethoxine (SDM), and the recovery experiment of sulfonamides in chicken was carried out. The recoveries were 80.9–97.6% and the detection limit was 3.8–17.6 μg L−1. This work provides a new strategy for oil removal using hierarchical porous materials.

Based on a DrivAer model with notchback, the characteristics of convective and acoustic pressure fluctuations on the side window, as well as their contributions to interior noise were studied. Firstly, a full-size DrivAer clay model was produced with a real glass set on the front left window, and the rest parts with thick clay. In this way, the side glass becomes the exclusive transmission path for the exterior convective and acoustic pressures into acoustic cabin inside. In this study, the acoustic pressure fluctuation on the side window surface was calculated by solving the acoustic perturbation equation (APE) based on the calculation results of convective pressure fluctuation with the incompressible Detached Eddy Simulation (DES). Furthermore, with the convective and acoustic pressure fluctuations as power inputs, the interior noise was calculated with Statistical Energy Analysis (SEA). The calculated interior noise level shows good agreement with the tested results in the wind tunnel, which indirectly validates the reliability of the calculated acoustic pressures with APE method. The contributions of the convective and acoustic pressure fluctuations to the interior noise show that the acoustic pressure fluctuation takes much higher transmission efficiency than the convective one, especially at the high frequency range above the coincidence frequency of the glass, the contribution of acoustic pressure fluctuation is absolutely dominant.

Supplemental Digital Content is available in the text.

Optimization-based semi-analytical methods (OSMs) and empirical methods (EMs) have been developed to derive bathymetry maps from satellite-based multispectral data of coral reefs, allowing for the management, monitoring, and protection of coral reefs. However, OSMs are often criticized due to the time-consuming requirements of iterative computations, yet they are praised for working without the need for in situ bathymetry data. EMs are praised for their time-saving characteristics and criticized for their need for in situ measurements. To estimate the water depth from multispectral data quickly without in situ bathymetry data, we provide a new EM that combines our previously developed OSM called the unmixing-based multispectral optimization process exemplar method (UMOPE) and an EM called Stumpf’s ratio method (SRM). In the new method, reflectance values from a small number of sampled pixels and the corresponding water depths estimated by UMOPE are used to determine the regression parameters for SRM. Thus, SRM determines the upper limit of accuracy for the new method, and UMOPE determines the possibility of reaching the upper limit. The new method was evaluated using three types of imagery of Xisha Islands, namely, WorldView-2 imagery with three traditional visible bands (WV-2a), Landsat 8 imagery with four visible bands, and WV-2 imagery with six visible bands (WV-2b). The results show that the new method can perform as well as SRM for Landsat 8 data and WV-2b data with similar root mean square error values at different depths. The lack of a coastal band in WV-2a imagery may cause large errors for the new method in deep water regions, especially when the water-leaving reflectance is noise perturbed. We found that even though the depths estimated by UMOPE are not error free at different ranges of water depth, if the regression line between the depths estimated by UMOPE and the measured depths is near the 1:1 line, the new method can perform as well as SRM. The new method may facilitate the rapid estimation of bathymetry from free Landsat 8 data of optically shallow waters around the world without in situ bathymetry data.

Additively manufactured Titanium alloys, specifically Ti-6Al-4V (Ti64) produced through laser based powder bed fusion (PBF-LB), hold great promise for applications in the medical, marine, and aerospace industries. However, PBF-LB Ti64 often exhibits inferior fatigue integrity due to defects introduced during the additive manufacturing process. This study focuses on the initiation mechanism of fatigue cracks, which are pivotal for assessing the fatigue life of as-built PBF-LB components. PBF-LB defects are intricately linked to contour process parameters (e.g., laser power and scan velocity) as well as build orientation. We investigate how these building variables affect the near-surface defect characteristics and fatigue crack initiation. Image-based methods are employed to perform qualitative and quantitative fatigue analyses. The specimens are periodically scanned using micro-CT before and during the fatigue testing, with final fracture surfaces examined using a scanning electron microscope (SEM). A set of efficient image analysis protocols has been proposed to track the crack evolution in 4D along the entire gauge section volume and establish correlations between crack initiation sites and initial defects. Furthermore, a convolutional network-based finite element solver (FEA-Net) has been utilized to directly predict fatigue crack initiation locations. Our findings reveal that the contour building strategies significantly influence near-surface defects and fatigue crack initiation. Importantly, FEA-Net accurately predicts crack initiation sites based solely on cross-section images, showcasing the potential of image-based approaches for advancing our understanding of PBF-LB component fatigue behavior.

•Dark-grown cottonseed sprouts' nutrition and free gossypol content were determined.•Dark cultivation for 9 days showed higher protein, aspartic acid, and serine.•Seven cotton germplasms were selected as candidates for sprouts application.•Metabolic and transcriptomic variances in sprouts under light and dark studied.•The molecular mechanism of flavonoids and gossypol accumulation were investigated.

Supplemental Digital Content is available in the text.

Mechanical strain plays a great role in growth and differentiation of osteoblast. A previous study indicated that integrin-β (β1, β5) mediated osteoblast proliferation promoted by mechanical tensile strain. However, the involvement of integrin-β in osteoblastic differentiation and extracellular matrix (ECM) formation induced by mechanical tensile strain, remains unclear. After transfection with integrin-β1 siRNA or integrin-β5 siRNA, mouse MC3T3-E1 preosteoblasts were cultured in cell culture dishes and stimulated with mechanical tensile strain of 2500 microstrain (με) at 0.5 Hz applied once a day for 1 h over 3 or 5 consecutive days. The cyclic tensile strain promoted osteoblastic differentiation of MC3T3-E1 cells. Transfection with integrin-β1 siRNA attenuated the osteoblastic diffenentiation induced by the tensile strain. By contrast, transfection with integrin-β5 siRNA had little effect on the osteoblastic differentiation induced by the strain. At the same time, the result of ECM formation promoted by the strain, was similar to the osteoblastic differentiation. Integrin-β1 mediates osteoblast differentiation and osteoblastic ECM formation promoted by cyclic tensile strain, and integrin-β5 is not involved in the osteoblasts response to the tensile strain.

Fluorescence spectrometry was used to investigate the binding interactions of bovine serum albumin (BSA) with three stilbene estrogens (hexestrol, diethylstilbestrol and dienoestrol). Further research into the binding ratios between stilbene estrogens and actual milk samples was carried out by equilibrium dialysis method. Meanwhile, the effect of protein on the extraction efficiency of stilbene estrogens in milk samples was investigated in detail. The results show that stilbene estrogens strongly bound with the milk samples. In 70% (v/v) ethanol–water extracting solution, a slow but full denaturation of the protein matrix of the sample takes place, which causes the drugs bonded with protein to be released. Then an appropriate amount of K2HPO4was added to the above extraction solution to form a stable aqueous two phase system. Following on, the fat-soluble stilbene estrogen residues were extracted into the upper phase with high extraction efficiency. Purification steps were omitted in this work because the fat-soluble impurities were extracted less in 70% (v/v) ethanol–water solution than in hydrophobic solvents, such as liquid–liquid extraction procedure. The proposed approach was satisfactorily applied to the quick determination of stilbene estrogen residues in milk by high performance liquid chromatography (HPLC). Overall recoveries were 83.2–93.8% with RSD values less than 4.52%, and the detection limits were in the range of 11.7 ng g−1to 20.7 ng g−1. The sample preparation method was straightforward, efficient, economically advantageous and environmentally-friendly.

In pork samples, the extraction efficiency of pyrethroids was related to the interactions between pyrethroids and proteins. These interactions were explored using the fluorescence quenching method. This showed that the binding interactions between pyrethroids and proteins are strongly hydrophobic. It was found that a slow but full protein denaturation took place in the 80% (volume fraction) isopropanol (IPA) aqueous solution, causing protein unfolding and the release of pyrethroids. Based on this, a highly efficient extraction method for pyrethroids in pork samples is proposed using 80% IPA solution as extraction solvent. A clean-up step using primary secondary amine (PSA) was applied, followed by the final determination by gas chromatography (GC) with an electron capture detector (ECD). The analytical process was validated in the pork sample matrix by analysing spiked blank samples. The mean recoveries of this method were 79.0–90.5% with limits of detection (LOD) between 0.008 and 0.014 μg g−1. This paper proposes a new strategy by full denaturation of protein and releasing of bound drugs to enhance the extraction efficiency of pyrethroids in pork samples.

We established new methods for cloning cDNA ends that start with reverse transcription (RT) and soon proceed with the synthesis of the second cDNA strand, avoiding manipulations of fragile RNA. Our 3′-end cloning method does not involve poly-dT primers and polymerase chain reactions (PCR), is low in efficiency but high in fidelity and can clone those RNAs without a poly-A tail. We also established a cDNA protection assay to supersede RNA protection assay. The protected cDNA can be amplified, cloned and sequenced, enhancing sensitivity and fidelity. We report that RT product using gene-specific primer (GSP) cannot be gene- or strand-specific because RNA sample contains endogenous random primers (ERP). The gene-specificity may be improved by adding a linker sequence at the 5′-end of the GSP to prime RT and using the linker as a primer in the ensuing PCR. The strand-specificity may be improved by using strand-specific DNA oligos in our protection assay. The CDK4 mRNA and TSPAN31 mRNA are transcribed from the opposite DNA strands and overlap at their 3′ ends. Using this relationship as a model, we found that the overlapped sequence might serve as a primer with its antisense as the template to create a wrong-template extension in RT or PCR. We infer that two unrelated RNAs or cDNAs overlapping at the 5′- or 3′-end might create a spurious chimera in this way, and many chimeras with a homologous sequence may be such artifacts. The ERP and overlapping antisense together set complex pitfalls, which one should be aware of.

A novel method for the analysis of 6 pyrethroids in fish samples, based on the use of a modified QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) approach followed by gas chromatography (GC) method, is reported. In previous reports, it is surprising to find that only acetonitrile was used as the original QuEChERS extraction solvent. In the present work, the QuEChERS method was modified by replacing the traditional acetonitrile with isopropanol. It showed that the use of isopropanol improved the extraction efficiency of the QuEChERS. For the pyrethroids in the protein–matrix samples, the overall recoveries of 75.8–89.4% for the modified QuEChERS method are better than those of 68.9–84.8% for the original QuEChERS method. Fluorescence quenching spectra of BSA with pyrethroids showed that the strong binding interaction between pyrethroids pesticides and protein decreased the extraction efficiency of pyrethroids from fish samples. However, in the 80% (volume fraction) isopropanol aqueous solution, a slow protein denaturation might take place, which would cause the unfolding of protein and the release of pyrethroids. This resulted in the high extraction efficiency of pyrethroids from protein matrix samples. The method was used satisfactorily for the determination of 6 pyrethroid pesticides in spiked fish samples. This paper proposes a new strategy by slowing down the protein denaturation and releasing bound pesticides to enhance the extraction efficiency of pyrethroids in fish samples.

Abstract: This paper proposes two quantitative criteria for removing railroad wheels from service, based on real-time structural health monitoring trends that are developed using data collected from trains while in service. The data is collected using wheel impact load detectors (WILDs). These impact load trends are able to distinguish wheels with a high probability of failure from high-impact wheels with a low probability of failure. The trends indicate the critical wheels that actually need to be removed, while at the same time allowing wheels that aren’t critical to remain in service. As a result, the safety of the railroad will be much improved by being able to identify and remove wheels that have high likelihood of causing catastrophic failures.

Previous studies showed that sodium ferulate, the effective component of Chinese herb, can inhibit platelet aggregation and decrease serum lipid. However, it is still unknown if sodium ferulate could prevent atherosclerogenesis. The experiments were designed to study its effects and mechanisms on atherosclerogenesis. Blood samples and thoracic aortas obtained from Japanese rabbits fed by high-lipid or high-lipid plus sodium ferulate forage were analyzed and compared. Simultaneously, vascular endothelial cells were cultured and treated by hyperlipidemic serum solely or plus sodium ferulate. Cellular ultrastructure, nitric oxide (NO) production, and cytokines expressions were studied and compared. In vivo experiment, aorta atherosclerotic plaque area of sodium ferulate-treated rabbits was much smaller than that of high-lipid–fed rabbits and serum triglyceride was correlated positively with the plaque area in both groups. In vitro, endothelial cells incubated with hyperlipidemic serum exhibited pronounced ultrastructural abnormalities, transforming growth factor β1expression and NO release were significantly decreased, while basic fibroblast growth factor expression was increased. Interestingly, the treatment group results clearly demonstrated that sodium ferulate was effective to protect cells from detrimental effects of hyperlipidemic serum and to help maintain normal NO and cytokines expressions. We concluded that sodium ferulate could inhibit rabbit aorta atherosclerogenesis, possibly through decreasing the serum lipid concentration and preventing vascular endothelial cells from the injury of hyperlipidemic serum.

Additive manufacturing (AM) has been extensively investigated in recent years to explore its application in a wide range of engineering functionalities, such as mechanical, acoustic, thermal, and electrical properties. A data-driven approach is proposed to investigate the influence of major fabrication parameters in the laser-based additively manufactured Ti–6Al–4V. Two separate laser-based powder bed fusion techniques, i.e., selective laser melting (SLM) and direct metal laser sintering (DMLS), have been investigated and several data regarding the tensile properties of Ti–6Al–4V alloy with their corresponding fabrication parameters are collected from open literature. Statistical data analysis is performed for four fabrication parameters (scanning speed, laser power, hatch spacing, and powder layer thickness) and three postfabrication parameters (heating temperature, heating time, and hot isostatically pressed or not) which are major influencing factors and have been investigated by several researchers to identify their behavior on the static mechanical properties (i.e., yielding strength, ultimate tensile strength, and elongation). To identify the behavior of the relationship between the input and output parameters, both linear regression analysis and artificial neural network (ANN) models are developed using 53 and 100 datasets for SLM and DMLS processes, respectively. The linear regression model resulted in an average R squared value of 0.351 and 0.507 compared to 0.908 and 0.833 in the case of nonlinear ANN modeling for SLM and DMLS based modeling, respectively. Both local and global sensitivity analyses are carried out to identify the important factors for future optimal design. Based on the current study, local sensitivity analysis (SA) suggests that SLM is most sensitive to laser power, scanning speed, and heat treatment temperature while DMLS is most sensitive to heat treatment temperature, hatch spacing, and laser power. In the case of DMLS fabricated Ti–6Al–4V alloy, laser power, and scan speed are found to be the most impactful input parameters for tensile properties of the alloy while heating time turned out to be the least affecting parameter. The global sensitivity analysis results can be used to tailor the alloy's static properties as per the requirement while results from local sensitivity analysis could be useful to optimize the already tailored design properties. Sobol's global sensitivity analysis implicates laser power, heating temperature, and hatch spacing to be the most influential parameters for alloy strength while powder layer thickness followed by scanning speed to be the prominent parameters for elongation for SLM fabricated Ti–6Al–4V alloy. Future work would still be needed to eradicate some of the limitations of this study related to limited dataset availability.

A new medium, used to generate lead hydride, was optimized as 0.3% (w/v) oxalic acid-2% (w/v) ammonium cerium (III) nitrate-8% (w/v) potassium tetrahydroborate-1% (w/v) sodium hydroxide solution; 950°C is used for atomization. The characteristic concentration (0.0044 absorbance) obtained under these conditions was 0.04 ng ml−1. The application of this medium to soil and ferromagano-brass samples is illustrated.

The probabilistic fatigue properties of additively manufactured (AM) Ti-6Al-4V using selective laser melted (SLM) process is analyzed considering the effects of process parameters. The Probabilistic Physics-guided Neural Network (PPgNN) is proposed for the modeling. With this developed model, both mean and variance of the fatigue life can be learned. The PPgNN contains constraints on model parameters to obtain the probabilistic stress-life relationships (P-S-N curves) with the physics-consistent curvature and nonconstant variance. The PPgNN model is also able to be trained using the data set with missing data for more reliable predictions. Experimental fatigue data are collected from extensive literatures for AM Ti-6Al-4V in as-built and annealed condition subjected to various process parameters (scanning speed, laser power, hatch space, layer thickness, heat temperature, heat time). The PPgNN model is validated using the experimental data. Next, a group of models with the same architecture and training data but different initial neural network biases and weights are obtained to account for the the randomness of NN. Following this, the predictive performance is compared between models training using all data (both complete and incomplete) and only complete data. Finally, global sensitivity analysis using the Delta Moment-Independent Measure is conducted to investigate the importance of process parameters. By only varying one process parameter and keeping the remaining ones fixed, the effect of each parameter on probabilistic fatigue lives is studied.

Metal diborides are a class of ceramic materials with crystal structures consisting of hexagonal sheets of boron atoms alternating with planes of metal atoms held together with mixed character ionic/covalent bonds. Many of the metal diborides are ultrahigh-temperature ceramics such as HfB2, TaB2, and ZrB2, which have melting points above 3000 °C, high mechanical hardness and strength at high temperatures, and high chemical resistance, while MgB2is a superconductor with a transition temperature of 39 K. Here, we demonstrate that this diverse family of non-van der Waals (vdW) materials can be processed into stable dispersions of quasi-two-dimensional (2D) nanosheets using ultrasonication-assisted exfoliation. We generate quasi-2D nanosheets of the metal diborides AlB2, CrB2, HfB2, MgB2, NbB2, TaB2, TiB2, and ZrB2and use electron and scanning probe microscopy techniques to characterize their structures, morphologies, and compositions. The exfoliated layers have a distribution of lateral dimensions from tens of nanometers up to several micrometers and a distribution of thicknesses from as low as 2–3 nm up to tens of nanometers, all while retaining their hexagonal atomic structure and chemical composition. We exploit the convenient solution-phase dispersions of exfoliated CrB2nanosheets to incorporate them directly into polymer composites. In contrast to the hard and brittle bulk CrB2, we find that CrB2nanocomposites remain very flexible and simultaneously provide increases in the elastic modulus and the ultimate tensile strength of the polymer. The successful liquid-phase production of quasi-2D metal diborides enables their processing using scalable low-temperature solution-phase methods, extending their use to previously unexplored applications, and reveals a new family of non-vdW materials that can be efficiently exfoliated into quasi-2D forms.

Life prediction in energy infrastructure such as gas pipelines is important to maintain the integrity of such systems. This paper explores a life prediction model for polyethylene materials in natural gas distribution pipelines under creep damage. The model uses a power law equation to describe the crack growth rate and an asymptotic solution for the stress intensity factor (SIF) calculation considering local geometry variations. The SIF solution considers the effect of stress concentration introduced by common damages in pipes such as rock impingement and slit. An effective initial crack size model is proposed for the life prediction of plastic pipes considering the intrinsic initial defect. Large loading-induced plastic deformation is included by a correction factor in the crack growth model. The model is calibrated and validated using experimental data on Aldyl-A pipes with different types of damage. Due to the stochastic nature of the crack growth process, uncertainty quantification is performed, and Monte Carlo (MC) simulation is used to estimate the failure probability. The predicted probabilistic life distributions under different loading conditions are compared with the experimental data. Some conclusions and future work are drawn based on the proposed study and experimental validation.