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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Exploring nonlinear Rashba effect and spin Hall conductivity in Janus MXenes W 2 ⁢CO ⁢𝑋 (𝑋=S, Se, Te)

Rashba spin-orbit coupling (RSOC) facilitates spin manipulation without relying on an external magnetic field, opening up exciting possibilities for advanced spintronic devices. In this paper, we examine the effects of crystal momentum (𝑘) nonlinearity and anisotropy on the conventional Rashba effect, with a particular focus on their impact on the spin Hall conductivity (SHC) in a newly predicted family of 2D Janus materials, W 2 ⁢CO⁢𝑋 (𝑋 =S, Se, Te). Using first-principles density functional theory calculations, we confirm the dynamical and mechanical stability of the studied 2D materials. Strikingly, this materials family exhibits pronounced nonlinear Rashba spin splitting at the Γ point of Brillouin zone near the Fermi level, which cannot be adequately described by the linear-𝑘 Rashba model. Therefore, third-order momentum contributions (𝑘 3 ) must be incorporated into the Rashba Hamiltonian. Our analysis reveals that among the studied systems, W 2 ⁢COS exhibits the highest 𝑘 3 contribution of −45.9 eV Å 3 , despite having the lowest linear Rashba constant. Here, a detailed analysis of electronic structure reveals topologically nontrivial behavior in these 2D materials, yielding sizable SHC that is primarily governed by the nonlinear Rashba effect. Notably, these materials also exhibit large spin Hall angle (0.018–2.5 at E 𝐹 ), which is comparable to that of in bulk topological insulators like Bi 2 ⁢Se 3 and Bi 2 ⁢Te 3 , and surpassing those in narrow bandgap bulk semiconductors GeTe and SnTe, as well as heavy metals such as Pt. Sizable SHC, large spin Hall angles, and the ability to tune SHC via electric fields without altering the topological properties, rooted in the crystal field splitting, underscore the potential of these materials for spintronic applications.

Electronic structure↗
DOE OSTI2025

Behavior of Multiple PV Plants in Future Power Grids During Events

As the integration of multiple photovoltaic (PV) plants into power grids grows, the dynamic response of each plant and their interactions during transient events demands a deeper understanding. In this paper, the dynamic behavior of multiple PV plants connected to future power grids is comprehensively explored using site-specific high-fidelity electromagnetic transient (EMT) PV plant models and generic high-fidelity EMT PV plant models. This research demonstrates the need to employ multiple high-fidelity EMT PV plant models to understand the intricate interactions between multiple PV plants during grid events. These models, developed in Fortran within the PSCAD environment, encompass a range of operational scenarios and plant configurations, offering invaluable insights crucial for future system planning with multiple PV plants to enhance grid stability.

Marthi, Phani Ratna Vanamali [ORNL] (ORCID:0000000↗
DOE OSTI2022

Data-Driven Dynamic Modeling in Power Systems: A Fresh Look on Inverter-Based Resource Modeling

Here, this article introduces ways to identify dynamic system models using measurement data. In power system analysis, a static model represents the time-invariant input-output relationship of a system, while a dynamic model describes the behavior of the system over time. For example, how will a system transit from one steady-state operation point to another?

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Exploring Transport Behavior in Hybrid Perovskites Solar Cells via Machine Learning Analysis of Environmental-Dependent Impedance Spectroscopy

Hybrid organic–inorganic perovskites are one of the promising candidates for the next-generation semiconductors due to their superlative optoelectronic properties. However, one of the limiting factors for potential applications is their chemical and structural instability in different environments. Herein, the stability of (FAPbI3)0.85(MAPbBr3)0.15 perovskite solar cell is explored in different atmospheres using impedance spectroscopy. An equivalent circuit model and distribution of relaxation times (DRTs) are used to effectively analyze impedance spectra. DRT is further analyzed via machine learning workflow based on the non-negative matrix factorization of reconstructed relaxation time spectra. This exploration provides the interplay of charge transport dynamics and recombination processes under environment stimuli and illumination. The results reveal that in the dark, oxygen atmosphere induces an increased hole concentration with less ionic character while ionic motion is dominant under ambient air. Under 1 Sun illumination, the environment-dependent impedance responses show a more striking effect compared with dark conditions. In this case, the increased transport resistance observed under oxygen atmosphere in equivalent circuit analysis arises due to interruption of photogenerated hole carriers. The results not only shed light on elucidating transport mechanisms of perovskite solar cells in different environments but also offer an effective interpretation of impedance responses.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Effects of PLA/PHB Blend Ratio and Wood Flour Loading on the Melt Rheology and Thermomechanical Properties of Biobased Polymer Composites

The development of sustainable, biobased polymer composites is crucial for reducing supply chain dependence on fossil fuels. A major challenge lies in understanding and predicting the processability of these sustainable material alternatives, which directly impacts large-scale manufacturing. Here, this study systematically investigates the effect of poly(lactic acid) (PLA)/polyhydroxybutyrate (PHB) blend ratios and wood flour (WF) loadings on the thermal, rheological, and mechanical properties of the composites. Composites were prepared via melt compounding and characterized by using differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), oscillatory shear melt rheology, tensile testing, and scanning electron microscopy. Results showed that increasing the PHB content lowered the glass transition temperature, while higher PHB and WF loadings decreased thermal stability. Complex viscosity decreased with increasing PHB in 0 and 10% WF, whereas it increased in 20% and 30% WF for PHB-rich blends (80/20 and 70/30 PLA/PHB) due to stronger filler interactions with flexible PHB chains. At 30% WF, PHB-containing composites also showed elastic dominance with G′ higher than G″. This behavior was confirmed by van Gurp–Palmen plots, where the phase angle decreased with increasing PHB and WF loadings. WF addition also shifted Cole–Cole plots away from semicircular terminal relaxation, while time–temperature superposition validity was maintained, confirming that polymer chain dynamics continue to dominate melt behavior. Young’s modulus increased with WF loading, while tensile strength and toughness decreased due to weaker interfacial adhesion between the matrix and the filler. Interestingly, 10% WF systems containing PHB exhibited the highest toughness among all of the filled systems, indicating synergistic reinforcement from WF fillers and PHB-induced ductility. Overall, melt rheology effectively captured the internal structure and stiffness of the composites as the formulation changed, reinforcing the concept that the PLA/PHB ratio and WF content can be tuned to adjust melt elasticity and balance mechanical property trade-offs for targeted applications.

melt rheology↗
NASA NTRS1984

Interactive aircraft flight control and aeroelastic stabilization

An analytical model has been used to study the problem of integrated control system/structural dynamic design. This model utilizes the traditional typical section lifting surface with a control surface attached in 2-D unsteady incompressible flow. The studies have as their purpose the examination of the use of the location of the elastic axis of the airfoil as a design variable in the search for an actively controlled configuration that has a specified flutter margin. Items of interest include the determination of flutter speed and divergence speed as functions of a nondimensional parameter, a sub c, that measures the location (in semi-chords) of the elastic axis with respect to the airfoil midchord. All other parameters are fixed. The behavior of velocity root locus curves with changes in a sub c is illustrated. Also shown is an example of the use of sensitivity derivatives to reposition poles of the open loop system. The behavior of the actively controlled or closed loop system is also discussed. A set of examples are presented to indicate how the shear center parameter, a sub c, affects the design of the controlled system.

Weisshaar, T. A.↗
DOE OSTI2024

Formation of a constructed microbial community in a nutrient-rich environment indicates bacterial interspecific competition

ABSTRACT Understanding the organizational principles of microbial communities is essential for interpreting ecosystem stability. Previous studies have investigated the formation of bacterial communities under nutrient-poor conditions or obligate relationships to observe cooperative interactions among different species. How microorganisms form stabilized communities in nutrient-rich environments, without obligate metabolic interdependency for growth, is still not fully disclosed. In this study, three bacterial strains isolated from the Populus deltoides rhizosphere were co-cultured in complex medium, and their growth behavior was tracked. These strains co-exist in mixed culture over serial transfer for multiple growth-dilution cycles. Competition is proposed as an emergent interaction relationship among the three bacteria based on their significantly decreased growth levels. The effects of different initial inoculum ratios, up to three orders of magnitude, on community structure were investigated, and the final compositions of the mixed communities with various starting composition indicate that community structure is not dependent on the initial inoculum ratio. Furthermore, the competitive relationships within the community were not altered by different initial inoculum ratios. The community structure was simulated by generalized Lotka-Volterra and dynamic flux balance analysis to provide mechanistic predictions into emergence of community structure under a nutrient-rich environment. Metaproteomic analyses provide support for the metabolite exchanges predicted by computational modeling and for highly altered physiologies when microbes are grown in co-culture. These findings broaden our understanding of bacterial community dynamics and metabolic diversity in higher-order interactions and could be significant in the management of rhizospheric bacterial communities. IMPORTANCE Bacteria naturally co-exist in multispecies consortia, and the ability to engineer such systems can be useful in biotechnology. Despite this, few studies have been performed to understand how bacteria form a stable community and interact with each other under nutrient-rich conditions. In this study, we investigated the effects of initial inoculum ratios on bacterial community structure using a complex medium and found that the initial inoculum ratio has no significant impact on resultant community structure or on interaction patterns between community members. The microbial population profiles were simulated using computational tools in order to understand intermicrobial relationships and to identify potential metabolic exchanges that occur during stabilization of the bacterial community. Studying microbial community assembly processes is essential for understanding fundamental ecological principles in microbial ecosystems and can be critical in predicting microbial community structure and function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Explaining System-Level Prognostics with Established Machine Learning Methods

System-level prognostics is crucial for ensuring reliability and enabling predictive maintenance in complex systems with interconnected components. This study presents a framework that integrates data-driven methods to predict the remaining useful life (RUL) of a subsystem under multiple and concurrent faults within a nuclear power plant system with explainable artificial intelligence (XAI). A nuclear power plant (NPP) operation was simulated to model the degradation behavior of NPP components, and four machine learning models—Gradient Boosting Regressor (GBR), Support Vector Regressor (SVR), Fully Connected Neural Network (FCNN), and Long Short-Term Memory (LSTM)—were evaluated for prognostics with a novel system RUL parameter. The LSTM model demonstrated potential superior repeatability, while SHAP (SHapley Additive exPlanations) for explainability provided consistent and trustworthy global explanations. In contrast, LIME (Local Interpretable Model-agnostic Explanations) offered localized interpretability but showed reduced stability for sequential data. Key findings include the interplay between component-level degradation and system-wide performance, with LSTM effectively capturing these dynamics through sequence-level predictions. The XAI techniques enhanced transparency by identifying critical features influencing model predictions and aligning with domain knowledge. Furthermore, this framework has significant implications for improving trust and understanding in predictive maintenance, particularly in safety-critical industries like nuclear energy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Deep potential development of transition-metal-rich carbides

In this study, we developed DeepPot-SE type potentials according to the High-Entropy Strategy for Cr 23 C 6 , Fe 23 C 6 , W 23 C 6 , and Mo 23 C 6 systems. Predictive molecular dynamics are then conducted according to various elastic and mechanical properties. Training dataset accuracy is confirmed both numerically and visually. Elastic constants, Poisson Ratio, and bulk modulus are determined and compared to the literature with percent errors ranging between 0.45 and 13.33%. Ground-state lattice constants yield 0.111–1.375% percent error. Linear lattice constant thermal expansion trends are found from 300 to 1500 K as expected. Melting behaviors with clear melting points are observed for each binary. Here, the Birch–Murnaghan Equation of State is suitably fit, providing additional verification of the bulk modulus calculations. Polycrystalline thermal stability is also verified for each binary potential.

36 MATERIALS SCIENCE↗
NASA NTRS2003

Neural Flight Control System

The Neural Flight Control System (NFCS) was developed to address the need for control systems that can be produced and tested at lower cost, easily adapted to prototype vehicles and for flight systems that can accommodate damaged control surfaces or changes to aircraft stability and control characteristics resulting from failures or accidents. NFCS utilizes on a neural network-based flight control algorithm which automatically compensates for a broad spectrum of unanticipated damage or failures of an aircraft in flight. Pilot stick and rudder pedal inputs are fed into a reference model which produces pitch, roll and yaw rate commands. The reference model frequencies and gains can be set to provide handling quality characteristics suitable for the aircraft of interest. The rate commands are used in conjunction with estimates of the aircraft s stability and control (S&C) derivatives by a simplified Dynamic Inverse controller to produce virtual elevator, aileron and rudder commands. These virtual surface deflection commands are optimally distributed across the aircraft s available control surfaces using linear programming theory. Sensor data is compared with the reference model rate commands to produce an error signal. A Proportional/Integral (PI) error controller "winds up" on the error signal and adds an augmented command to the reference model output with the effect of zeroing the error signal. In order to provide more consistent handling qualities for the pilot, neural networks learn the behavior of the error controller and add in the augmented command before the integrator winds up. In the case of damage sufficient to affect the handling qualities of the aircraft, an Adaptive Critic is utilized to reduce the reference model frequencies and gains to stay within a flyable envelope of the aircraft.

Gundy-Burlet, Karen↗
DOE OSTI2023

Dynamics of Three-Dimensional Shock-Wave/Boundary-Layer Interactions

Advances in measuring and understanding separated, nominally two-dimensional (2D) shock-wave/turbulent-boundary-layer interactions (STBLI) have triggered recent campaigns focused on three-dimensional (3D) STBLI, which display far greater configuration diversity. Nonetheless, unifying properties emerge for semi-infinite interactions, taking the form of conical asymptotic behavior where shock-generator specifics become insignificant. The contrast between 2D and 3D separation is substantial; the skewed vortical structure of 3D STBLI reflects the essentially 2D influence of the boundary layer on the 3D character of the swept shock. As with 2D STBLI, conical interactions engender prominent spectral content below that of the turbulent boundary layer. However, the uniform separation length scale, which is crucial to normalizing the lowest-frequency dynamics in 2D STBLI, is absent. Comparatively, the spectra of 3D STBLI are more representative of the mid-frequency, convective, shear-layer dynamics in 2D, while phenomena associated with 2D separation-shock breathing are muted. Asymptotic behavior breaks down in many regions important to 3D-STBLI dynamics, occurring in a configuration-dependent manner. Aspects of inceptive regions near shock generators and symmetry planes are reviewed. Focused efforts toward 3D modal and nonmodalanalyses, moving-shock/boundary-layer interactions, fluid/structure interactions, and flow control are suggested as directions for future work.

42 ENGINEERING↗
DOE OSTI2020

Dynamic Behavior of Natural Seep Vents: Analysis of Field and Laboratory Observations and Modeling (Final Scientific/Technical Report)

In this project, we have analyzed data collected by the U.S. Department of Energy (DOE), National Energy Technology Laboratory (NETL) in a high pressure water tunnel (HPWT) and data from two research cruises to natural seeps in the Gulf of Mexico to adapt and validate a numerical model to predict the dynamics of natural seeps in the deep oceans. The HPWT data include video observations of the shrinkage rate of individual methane and natural gas bubbles under simulated deep-water conditions. Field data were collected during two cruises by the Gulf Integrated Spill Research (GISR) Consortium led by Texas A&M University and funded by the Gulf of Mexico Research Initiative (GoMRI). These data included in situ observations from a remotely operated vehicle (ROV) of gas bubbles at two natural seep sites in the Gulf and acoustic observations of the natural seep bubble flares in the ocean water column. The acoustic data were from multibeam echosounders, one mounted in a forward-looking orientation on the ROV and another mounted down-looking in the haul of the ship. All of these laboratory and field data were focused on the dynamics of natural gas bubbles at temperatures and pressures favorable for clathrate hydrate formation between the gas and water. Our analyses of this data focused on understanding the mechanisms responsible for gas bubble dissolution within the hydrate stability zone (HSZ) of the oceans. Ice-like hydrate shells may form on the bubble-water interface under these conditions, and it was unknown how this might affect the mass transfer of gas into the ocean. We were able to extract bubble shrinkage rates from the HPWT datasets. Using this data we determined that mass transfer coefficients with and without a hydrate shell match empirical values for bubbles in contaminated systems (so-called dirty bubbles contaminated by naturally occurring surfactants). We also showed that free gas, and not gas hydrate, is the dominant dissolving phase when the hydrate sub-cooling is below 11 degree Celsius (temperature difference between hydrate the hydrate formation temperature and ambient temperator) or the pressure is reducing as bubbles rise through the ocean water column. Using this mass transfer model, our numerical model of bubble dissolution matched the over 200 HPWT experiments with an average error of 10% for predicting the bubble size at the end of an experiment. From field data in the literature, we also observed that gas bubbles dissolve faster when they are initially released, following mass transfer coefficients for so-called clean-bubbles (those not yet contaminated by surfactants). Shortly after release within the HSZ, a hydrate shell forms on the bubble-water interface, and the mass transfer reduces to rates matching those of dirty bubbles. We correlated this transition time from clean to dirty bubble behavior with the initial bubble surface area and the hydrate sub-cooling. With this model for hydrate formation time and using the mass transfer coefficients deduced from the HPWT data, we validated our numerical model for predicting the rise heights of natural seep flares in the oceans. Flare heights are commonly observed in haul-mounted acoustic multibeam data. The numerical model predicts bubbles to rise high in the ocean water column owing to the slower mass transfer rates for dirty bubbles that accompany the majority of their rise time. We found that the numerical model predictions matched the observed flare heights within 5% to 10% accuracy when we compared the rise heights of the largest bubbles released from the seafloor with the bubbles acoustically visible in the multibeam data. Bubbles become acoustically transparent as they shrink to sizes of order 1 mm in diameter for the multibeam frequencies used in the field. The forward-looking multibeam on the ROV also provided data on the lateral spreading of bubbles in natural seep flares. Our analysis of this data showed that spreading follows a diffusion process, with the effective diffusivity correlating with the wobbling length scale of these ellipsoidal bubbles. When we apply this diffusivity in a random displacement model of bubble spreading, our numerical simulations match closely the lateral spread observed by the M3 in the ocean water column. Finally, we compared the seep model predictions for the acoustic properties of these natural seep plumes with that observed by the acoustic instruments in the field. The M3 and EM 302 observations were converted to relative values of target strength using a calibration we obtained in the laboratory for the M3 and using an algorithm from the manufacturer for the EM 302. Comparing the numerical seep model to these data, we obtain good agreement over the whole height of rise of these bubble flares. This further validates the numerical model. Overall, our validated seep model captures the key dynamics of gas bubbles released from natural seeps in the oceans and helps to predict the fate of methane in the water column.

03 NATURAL GAS↗
NASA NTRS1988

Helicopter stability and control modeling improvements and verification on two helicopters

A linearized model of helicopter flight dynamics is developed which includes the flapping, lead-lag, and dynamic inflow degrees of freedom (DOF). The model is a combination of analytical terms and numerically determined stability derivatives, and is used to investigate the importance of the rotor DOF to stability and control modeling. The results show that the rotor DOF can have a significant impact on some of the natural modes in a linear model. The flap and dynamic inflow DOF show the greatest influence. Flapping exhibits strong coupling to the body, dynamic inflow, and to lead-lag to a lesser extent. Dynamic inflow tends to damp the high-frequency flapping modes, and reduces the damping on coupled body-flap motion. Dynamic inflow also couples to the flapping motion to produce complex roots. With body-flap and lag regressing modes as exceptions, the results show essentially similar behavior for most modes of articulated and hingeless rotor helicopters.

Schrage, D. P.↗
DOE OSTI2022

Depletion-Driven Assembly of Polymer-Coated Nanocrystals

Depletion-driven assembly has been widely studied for micron-sized colloids, but questions remain at the nanoscale where the governing physics are impacted by stabilizing surface ligands or wrapping polymers, whose dimensions are similar to those of the colloidal core and the depletant. Here, we probe how wrapping colloidal tin-doped indium oxide nanocrystals with polymers affects their depletion-induced interactions and assembly in solutions of polyethylene glycol. Copolymers of polyacrylic acid grafted with polyethylene oxide provide nanocrystal wrappings with different effective polymer graft densities and molecular weights. (Ultra) small angle X-ray scattering, coarse-grained molecular dynamics simulation, and molecular thermodynamic theory were combined to analyze how depletant size and polymer wrapping characteristics affect depletion interactions, structure, and phase behavior. The results show how depletant molecular weight, as well as surface density and molecular weight of polymer grafts, set thresholds for assembly. These signatures are unique to depletion-driven assembly of nanoscale colloids and mirror phase behaviors of grafted nanoparticle–polymer composites. Optical and rheological responses of depletion-driven assemblies of nanocrystals with different polymer shell architectures were probed to learn how their structural differences impact properties. Finally, we discuss how these wrinkles for depletion-driven assembly at the nanoscale may provide fresh opportunities for designing responsive depletion interactions and dynamically reconfigurable materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1997

A CFD/CSD Interaction Methodology for Aircraft Wings

With advanced subsonic transports and military aircraft operating in the transonic regime, it is becoming important to determine the effects of the coupling between aerodynamic loads and elastic forces. Since aeroelastic effects can contribute significantly to the design of these aircraft, there is a strong need in the aerospace industry to predict these aero-structure interactions computationally. To perform static aeroelastic analysis in the transonic regime, high fidelity computational fluid dynamics (CFD) analysis tools must be used in conjunction with high fidelity computational structural fluid dynamics (CSD) analysis tools due to the nonlinear behavior of the aerodynamics in the transonic regime. There is also a need to be able to use a wide variety of CFD and CSD tools to predict these aeroelastic effects in the transonic regime. Because source codes are not always available, it is necessary to couple the CFD and CSD codes without alteration of the source codes. In this study, an aeroelastic coupling procedure is developed which will perform static aeroelastic analysis using any CFD and CSD code with little code integration. The aeroelastic coupling procedure is demonstrated on an F/A-18 Stabilator using NASTD (an in-house McDonnell Douglas CFD code) and NASTRAN. In addition, the Aeroelastic Research Wing (ARW-2) is used for demonstration of the aeroelastic coupling procedure by using ENSAERO (NASA Ames Research Center CFD code) and a finite element wing-box code (developed as part of this research).

Bhardwaj, Manoj K.↗
DOE OSTI2024

Investigation of acoustic waves under subsurface conditions to improve the predictions of rock mechanical properties and natural fracture characteristics

Mechanical properties and natural fracture characteristics are critical to investigate for subsurface engineering applications, including carbon storage, well drilling, and stimulation, as they govern rock stability, fluid flow, and mechanical behavior under stress. This dissertation integrates experimental and machine learning approaches to enhance the prediction and understanding of these properties by analyzing acoustic wave behavior under varied subsurface conditions. First, the influence of temperature, pore pressure, and supercritical CO2 (scCO2) saturation on poroelastic properties is examined using Gray Berea sandstone samples. The results show that temperature and pore pressure significantly affect the bulk modulus and Biot’s coefficient, while scCO2 saturation impacts rock compressibility, informing strategies for effective geological carbon storage. The study extends this understanding by experimentally evaluating the impact of reservoir depletion on the dynamic mechanical properties of the emerging Caney shale in South Oklahoma with the employment of unsupervised machine learning to predict static mechanical properties across the Caney shale. Integrating petrophysical data and chemostratigraphy, the workflow—featuring K-means clustering, principal component analysis (PCA), and inverse distance weighting (IDW)—improves stratigraphic characterization and the estimation of static-to-dynamic modulus ratios, which is vital for optimizing drilling and stimulation strategies. Finally, the work explores how natural fracture characteristics in shale influence acoustic waveforms and shear wave splitting (SWS) analysis. Experimental data on fractured samples under different stress and temperature conditions, combined with machine learning models such as K-nearest neighbors (KNN) and extreme gradient boosting (XGBoost), reveal key fracture properties impacting SWS and wave propagation. Together, these studies provide a comprehensive framework for linking acoustic wave behavior with rock properties, advancing the methods for monitoring and predicting geomechanical changes. The insights offered valuable implications for safer, more efficient CO2 injection, hydrocarbon extraction, and subsurface management.

Elkholy, Sherif↗
DOE OSTI2021

Recycled polyethylene and crumb rubber composites modified asphalt with improved aging resistance and thermal stability

Crumb rubbers (CR) and recycled Polyethylene (PE) are commonly used as modifiers to improve the asphalt properties. However, the addition of these modifiers individually may result in phase separation of PE and inadequate degradation of CR, which may not simultaneously satisfy the rheological and aging resistance of the binder blends. In this study, a type of CR/PE composites manufactured through melt extrusion procedures was adopted for the improvement of the modified binder blends. The modified binder blends after short-term (RTFO) and long-term (PAV) aging were collected for dynamic shear rheometer and bending beam rheometer tests. FTIR tests were also used to quantify the aging resistance, while differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) were applied to evaluate the thermal behaviors of the binder blends. Optical microscopy tests were used to explore the modification mechanism and visualize the microstructures of original and PAV aged binder blends. Test results showed that CR/PE composites could significantly improve the aging resistance of the binder blends. The dispersed PE particles still interacted with each other and meanwhile worked with the diffused rubbery phase, which could form a similar TPEs network. The oxidation and high-temperature aging of such binder blends would strengthen the network that resisted the aging severity of the binder blends. Furthermore, it was also revealed that CR/PE modified asphalt could sustain more heat before a rapid degradation and the well-dispersed PE particles could interact with the diffused CR particles to form a network to resist aging.

02 PETROLEUM↗
DOE OSTI2024

Constructing Crown Ether-Based Supramolecular Adhesives with Ambient-Temperature Applicable and Durable Adhesion

Supramolecular adhesives are attracting considerable attentions owing to their dynamic and reversible bonding, while the complex curing conditions and poor performance under extreme conditions severely restrict their applicability. Herein, a series of tetra-crown ether-terminated polyethylene glycol (TCE-PEG) adhesives are presented in which plenty of supramolecular interactions, including Van der Waals, hydrogen bonding, π–π staking, metal coordination, and electrostatic ones, provide strong adhesion on multiple types of substrates. Highly relevant for practical applications, ultra-strong adhesivity of TCE-PEG can be achieved without requiring additional ultraviolet radiation, heat, or chemical treatment at ambient temperature. It also exhibits durable adhesive behavior, excellent underwater stability, and low-temperature tolerance. Especially, by incorporating ionic polymer fragments of polyethyleneimine hydrochloride, additional hydrogen bonding between secondary amines and crown ether rings can be induced to enhance the lap-shear strength to 7.21 MPa due to the formation of supramolecular cross-linked network. Finally, this work pioneers a rather unique supramolecular approach for easily formed, ultra-strong crown-ether-based adhesives bearing great potential for applications in critical environments of limited heat source and unallowed solvent usage.

36 MATERIALS SCIENCE↗