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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Mechanical Consequences of Oxygen Inhibition in Vat Polymerization

Vat polymerization is a type of additive manufacturing that is used extensively to produce micro-architected structures for mechanical applications, which brings the mechanical properties of photopolymerized resins into sharp focus. However, it is known that photopolymerization is sensitive to a number of factors, perhaps the most notorious of which is oxygen inhibition. Herein, the degree to which oxygen inhibition influences the macroscopic and microscopic properties of structures made using vat polymerization is explored. This work is motivated by an observation of lattices being >4 times softer in the experiment than predicted by simulation, which is hypothesized to be due to the material at the surface being incompletely cured. Furthermore, this hypothesis is supported by four-point bending tests in which flexural modulus is found to increase with beam thickness. Nanoindentation and bulk compression studies show that this surface softening is present for three distinct resins. Importantly, it is observed that structures post-print cured in nitrogen are stiffer than those post-print cured in air, however, regardless of the post-print curing environment, printing samples in the presence of oxygen makes them softer than samples photocured in nitrogen. Collectively, these results show the outsized influence of oxygen inhibition on micro-architected structures realized using vat polymerization.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rational Design and Reticulation of Infinite qbe Rod Secondary Building Units into Metal–Organic Frameworks through a Global Desymmetrization Approach for Inverse C 3 H 8 /C 3 H 6 Separation

Abstract The development of reticular chemistry has enabled the construction of a large array of metal–organic frameworks (MOFs) with diverse net topologies and functions. However, dominating this class of materials are those built from discrete/finite secondary building units (SBUs), yet the designed synthesis of frameworks involving infinite rod‐shaped SBUs remain underdeveloped. Here, by virtue of a global linker desymmetrization approach, we successfully targeted a novel Cu‐MOF (Cu‐ASY) incorporating infinite Cu‐carboxylate rod SBUs with its structure determined by micro electron diffraction (MicroED) crystallography. Interestingly, the rod SBU can be simplified as a unique cylindric sphere packingqbetubule made of [4 3 .6 2 ] tiles, which further connect the tritopic linkers to give a newly discovered 3,5‐connectedgfcnet. Cu‐ASY is a permanent ultramicroporous material featuring 1D channels with highly inert surfaces and shows a preferential adsorption of propane (C 3 H 8 ) over propene (C 3 H 6 ). The efficiency of C 3 H 8 selective Cu‐ASY is validated by multicycle breakthrough experiments, giving C 3 H 6 productivity of 2.2 L/kg. Density functional theory (DFT) calculations reveal that C 3 H 8 molecules form multiple C−H⋅⋅⋅π and atypical C−H⋅⋅⋅ H−C van der Waals interactions with the inner nonpolar surfaces. This work therefore highlights the linker desymmetrization as an encouraging and intriguing strategy for achieving unique MOF structures and properties.

Chemistry↗
DOE OSTI2022

Can fractal dimensions objectivize gastropod shell morphometrics? A case study from Lake Lugu (SW China)

1. Morphometrics are fundamental for the analysis of size and shape in fossils, particularly because soft parts or DNA are rarely preserved and hard parts such as shells are commonly the only source of information. Geometric morphometrics, that is, landmark analysis, is well established for the description of shape but it exhibits a couple of shortcomings resulting from subjective choices during landmarking (number and position of landmarks) and from difficulties in resolving shape at the level of micro-sculpture. 2. With the aid of high-resolution 3D scanning technology and analyses of fractal dimensions, we test whether such shortcomings of linear and landmark morphometrics can be overcome. As a model group, we selected a clade of modern viviparid gastropods from Lake Lugu, with shells that show a high degree of sculptural variation. Linear and landmark analyses were applied to the same shells in order to establish the fractal dimensions. 3. The genetic diversity of the gastropod clade was assessed. The genetic results suggest that the gastropod clade represents a single species. The results of all morphometric methods applied are in line with the genetic results, which is that no specific morphotype could be delimited. Apart from this overall agreement, landmark and fractal dimension analyses do not correspond to each other but represent data sets with different information. Generally, the fractal dimension values quantify the roughness of the shell surface, the resolution of the 3D scans determining the level. In our approach, we captured the micro-sculpture but not the first-order sculptural elements, which explains that fractal dimension and landmark data are not in phase. 4. We can show that analyzing fractal dimensions of gastropod shells opens a window to more detailed information that can be considered in evolutionary and ecological contexts. We propose that using low-resolution 3D scans may successfully substitute landmark analyses because it overcomes the subjective landmarking. Analyses of 3D scans with higher resolution than used in this study will provide surface roughness information at the mineralogical level. We suggest that fractal dimension analyses of a combination of differently resolved 3D models will significantly improve the quality of shell morphometrics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Observation of Quadratic (Charge-2) Weyl Point Splitting in Near-Infrared Photonic Crystals

Weyl points are point degeneracies that occur in momentum space of 3D periodic materials and are associated with a quantized topological charge. Here, the splitting of a quadratic (charge-2) Weyl point into two linear (charge-1) Weyl points in a 3D micro-printed photonic crystal is observed experimentally via Fourier-transform infrared spectroscopy. Using a theoretical analysis rooted in symmetry arguments, it is shown that this splitting occurs along high-symmetry directions in the Brillouin zone. This micro-scale observation and control of Weyl points is important for realizing robust topological devices in the near-infrared.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Super-Large-Scale Hierarchically Porous Films Based on Self-Assembled Eye-Like Air Pores for High-Performance Daytime Radiative Cooling

Metal-free polymer daytime radiative cooling coatings with hierarchical eye-like air pores are proposed and fabricated with a super-large-scale film-stretching method. The hierarchically porous film (HPF) can be further coated with polymethyl methacrylate (PMMA) micro-hemispheres, forming coated HPF (cHPF), which do not dramatically change the optical or thermal properties. The cHPF is slightly better with a lower solar absorptivity (2.4%) and a higher thermal emissivity over the atmospheric transparency window (90.1%). The low solar absorptivity is due to the strong scattering of the hierarchical eye-like air pores, while the molecular vibrations and the focusing effect of the PMMA micro-hemispheres contribute to the high emissivity. Further, an average mid-day temperature reduction of 7.92 °C is achieved relative to the air temperature, and the average cooling power reaches 116.0 W m -2 , which are much better than the cooling performances of the commercial cooling cushion. During the day, the cHPF-covered simulated building is up to 6.47 and 4.84 °C cooler than the ambient and the white painted counterpart, respectively. The film is durable and resistant to chemical etching, and very promising to use globally, especially in warm and tropical regions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Microscale Metal Additive Manufacturing by Solid‐State Impact Bonding of Shaped Thin Films

The deposition of device-grade inorganic materials is one key challenge toward the implementation of additive manufacturing (AM) in microfabrication, and to that end, a broad range of physico-chemical principles has been explored for 3D fabrication with micro- and nanoscale resolution. Yet, for metals, a process that achieves material quality rivalling that of established thin-film deposition methods, and at the same time, has the potential to combine high throughput production with a broad palette of processable materials, is still lacking. Here, the kinetic, solid-state bonding of metal thin films for the additive assembly of high-purity, high-density metals with micrometer-scale precision is introduced. Indirect laser ablation accelerates micrometer-thick gold films to hundreds of meters per second without their heating or ablation. Their subsequent impact on the substrate above a critical velocity forms a permanent, metallic bond in the solid state. Stacked layers are of high density (>99%). By defining thin-film layers with established lithographic methods prior to launch, a variable feature size (2–50 µm), arbitrary shape of bonded layers, and parallel transfer of up to 36 independent film units in a single shot, is demonstrated. Thus, the solid-state kinetic bonding principle as a viable and potentially versatile route for micro-scale AM of metals is established.

3D printing↗
DOE OSTI2023

Physics-informed machine-learning model of temperature evolution under solid phase processes

We model temperature dynamics during Shear Assisted Proccess Extrusion (ShAPE), a solid phase process that plasticizes feedstock with a rotating tool and subsequently extrudes it into a consolidated tube, rod, or wire. Control of temperature is critical during ShAPE processing to avoid liquefaction, ensure smooth extrusion, and develop desired material properties in the extruded products. Accurate modeling of the complicated thermo-mechanical feedbacks between process inputs, material temperature, and heat generation presents a significant barrier to predictive modeling and process design. In particular, connecting micro-structural scale mechanisms of heat generation to macro-scale predictions of temperature can become computationally intractable. In this work we use a neural network (NN) model of heat generation to bridge this gap, by combining it with a simplified model of the temperature dynamics due to conduction and convection to capture the macro scale evolution of temperature. We inform the construction of the NN heat generation model using crystal plasticity simulations at the micro-structural scale to model the effects of process inputs on generation of heat. We achieved close fits of the temperature dynamics model to a diverse experimental data-set. Further, the relationships learned by the NN model between process inputs and heat generation showed qualitative agreement with those predicted by crystal plasticity simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Review of Onsite Temperature and Solar Forecasting Models to Enable Better Building Design and Operations

Advanced building controls and energy optimization for new constructions and retrofits rely on accurate weather data. Traditionally, most studies utilize airport weather information as the decision inputs. However, most buildings are in environments that are quite different than those at the airport miles away. Tree cover, adjacent buildings, and micro-climate effects caused by the larger surrounding area can all yield deviations in air temperature, humidity, solar irradiance, and wind that are large enough to influence design and operation decisions. In order to overcome this challenge, there are many prior studies on developing weather forecasting algorithms from micro-to meso-scales. Additionally, this paper reviews and complies knowledge on common weather data resources, data processing methodologies and forecasting techniques of weather information. Commonly used statistical, machine learning and physical-based models are discussed and presented as two major categories: deterministic forecasting and probabilistic forecasting. Finally, evaluation metrics for forecasting errors are listed and discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Advanced Electrode Structures for Proton Exchange Membrane Fuel Cells: Current Status and Path Forward

Abstract Proton exchange membrane fuel cells (PEMFCs) have demonstrated their viability as a promising candidate for clean energy applications. However, performance of conventional PEMFC electrodes, especially the cathode electrode, suffers from low catalyst utilization and sluggish mass transport due to the randomly distributed components and tortuous transport pathways. Development of alternative architectures in which the electrode structure is controlled across a range of length scales provides a promising path toward overcoming these limitations. Here, we provide a comprehensive review of recent research and development of advanced electrode structures, organized by decreasing length-scale from the millimeter-scale to the nanometer-scale. Specifically, advanced electrode structures are categorized into five unique architectures for specific functions: (1) macro-patterned electrodes for enhanced macro-scale mass transport, (2) micro-patterned electrodes for enhanced micro-scale mass transport, (3) electrospun electrodes with fiber-based morphology for enhanced in-plane proton transport and through-plane O 2 transport, (4) enhanced-porosity electrodes for improved oxygen transport through selective inclusion of void space, and (5) catalyst film electrodes for elimination of carbon corrosion and ionomer poisoning. The PEMFC performance results achieved from each alternative electrode structure are presented and tabulated for comparison with conventional electrode architectures. Moreover, analysis of mechanisms by which new electrode structures can improve performance is presented and discussed. Finally, an overview of current limitations and future research needs is presented to guide the development of electrode structures for next generation PEMFCs. Graphical Abstract Development of improved electrode architectures with the control of structure on length scales ranging from millimeters to nanometers could enable a new generation of fuel cells with increased performance and reduced cost. This paper presents an in-depth review and critical analysis of recent developments and future outlook on the design of advanced electrode structures.

25 ENERGY STORAGE↗
DOE OSTI2020

Nanoscale lattice strains in self-ion implanted tungsten

Developing a comprehensive understanding of the modification of material properties by neutron irradiation is important for the design of future fission and fusion power reactors. Self-ion implantation is commonly used to mimic neutron irradiation damage, however an interesting question concerns the effect of ion energy on the resulting damage structures. The reduction in the thickness of the implanted layer as the implantation energy is reduced results in the significant quandary: Does one attempt to match the primary knock-on atom energy produced during neutron irradiation or implant at a much higher energy, such that a thicker damage layer is produced? In this work, we address this question by measuring the full strain tensor for two ion implantation energies, 2 MeV and 20 MeV in self-ion implanted tungsten, a critical material for the first wall and divertor of fusion reactors. A comparison of 2 MeV and 20 MeV implanted samples is shown to result in similar lattice swelling. Multi-reflection Bragg coherent diffractive imaging (MBCDI) shows that implantation induced strain is in fact heterogeneous at the nanoscale, suggesting that there is a non-uniform distribution of defects, an observation that is not fully captured by micro-beam Laue diffraction. At the surface, MBCDI and high-resolution electron back-scattered diffraction (HR-EBSD) strain measurements agree quite well in terms of this clustering/non-uniformity of the strain distribution. However, MBCDI reveals that the heterogeneity at greater depths in the sample is much larger than at the surface. This combination of techniques provides a powerful method for detailed investigation of the microstructural damage caused by ion bombardment, and more generally of strain related phenomena in micro-volumes that are inaccessible via any other technique.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomistic simulations and machine learning of solute grain boundary segregation in Mg alloys at finite temperatures

Understanding solute segregation thermodynamics is the first step in investigating grain boundary (GB) properties, such as strong yttrium (Y) effects on grain growth and texture evolution in micro-scale polycrystalline magnesium (Mg) alloys. To estimate the average GB segregation behavior in low-solute-concentration Mg alloys (e.g., 2 at.% Y), a state-of-the-art spectral approach is applied based on a per-site segregation energy spectrum for Y solute atoms at zero K obtained from molecular statistics (MS) simulations of ~10 4 GB sites in Mg symmetric tilt GBs (STGBs). Although selected MS simulation results are consistent with verification by density functional theory (DFT) calculations, estimates of average segregation tendency based on the zero-K energy spectrum deviate from experimental observations. To resolve this problem, thermodynamic integration (TI) methods based on molecular dynamics (MD) simulations are used to determine the per-site segregation free energies of Y at representative GB sites, which show contributions beyond harmonic approximations can be important for certain GB sites at high temperatures. A surrogate model of per-site segregation free energy is constructed from a small set of TI data points using stacking cross-validation regressors and physics-informed descriptors. This model is applied to predict the Y segregation free energy spectra for thousands of GB sites in Mg STGBs with uncertainty quantification. Finally, the average segregation tendency predicted by the spectral approach based on the free energy spectra agrees well (within the uncertainty range) with experimental observations for micro-scale polycrystalline Mg alloys at typical thermomechanical processing temperatures (500 ~ 800 K), where thermodynamic equilibrium states are likely to be achieved due to fast diffusion.

Atomistic simulations↗
DOE OSTI2024

Multimodal 3D quantification of particle stimulated nucleation in industrially manufactured aluminium AA5182 sheet

Particle stimulated nucleation is a dominant recrystallisation mechanism observed in many industrially relevant aluminium alloys during thermomechanical processing. Here, in this work, we quantify particle stimulated nucleation in 3D in an aluminium AA5182 alloy sheet cold-rolled to 75% thickness reduction. Second phase particles and nuclei are mapped in the same sample volume by conventional laboratory absorption X-ray tomography and synchrotron X-ray Laue micro-diffraction. The large second phase particles are classified as Fe- and Mg-rich phases. It is found that 84% of the nuclei are particle stimulated and 40% of the particles stimulate nucleation. The critical particle diameter is found to be 4 μm. Deviatoric elastic strains are derived from micro-diffraction data and it is found that elastic strains are present in the recrystallised nuclei. The effects of the different particle types, particle clustering, particle size and aspect ratio as well as strain inheritance are discussed. This work provides a full 3D quantification of particle stimulated nucleation behaviour in AA5182 alloy sheet deformed to high strain.

Deviatoric strain↗
DOE OSTI2022

Strain energy-based fatigue failure analyses of LB-PBF Inconel 718: Effect of build orientation

Additively manufactured Inconel 718 parts fabricated in three build orientations (horizontal, vertical, and angled at 45 degrees) are tested in fully-reversed bending fatigue mode. Damping measurements via the Impulse Excitation technique are used to assess the defects content in the microstructure and fractography analysis is performed to detect the root cause of failure. Two micro- and macro-scale methodologies of fatigue damage estimation based on the dissipated heat per cycle and the statistical estimation of micro-plastic strain energies are used to assess fatigue damage. It is shown that at a given stress level, the vertically built specimens endure the most fatigue damage before failure while the diagonally built ones sustain the least. As a result, the fatigue life is estimated for arbitrary load amplitudes via a microstructure-sensitive algorithm with acceptable accuracy as compared to the experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The role of the spatial heterogeneity and correlation length of surface wettability on two-phase flow in a CO 2 -water-rock system

This study characterized and modeled heterogeneous surface wettability in sandstone and investigated the role of spatial heterogeneity and correlation length of surface wettability on relative permeability in a supercritical CO 2 (scCO 2 )-brine-rock system. Understanding the role of wettability heterogeneity on relative permeability is essential to geological CO 2 sequestration, oil and gas recovery, and contaminated groundwater remediation. Although numerous studies have attempted to understand the influences of surface wettability, capillary number (Ca), and viscosity ratio, the role of the spatial variation and correlation length of surface wettability on two-phase flow in three-dimensional (3D) porous media has not been unraveled due to the challenges in the measurement and representation of realistic rock surface wettability. In this work, we conducted in-situ measurements of surface contact angle (CA) in a Bentheimer sandstone after CO 2 flooding using micro-computed tomography (micro-CT), and found that the pore-scale CA distribution on rock surfaces followed a log-normal distribution associated with a spatial correlation length. Based on the statistical information from CT scanning, a Gaussian random field was used to model CA distributions that had desired standard deviations and spatial correlation lengths, which were then adjusted within a certain range of values for sensitivity analyses to study their combined effects on the two-phase flow in the porous medium using the lattice Boltzmann (LB) method. The LB two-phase flow simulation was accelerated using hybrid, multicore parallel computing to overcome the challenges in simulating multiphase flow in a large 3D domain having 800 × 800 × 600 nodes. The simulation results showed that the surface wettability heterogeneity (i.e., standard deviation of CA) had a lesser effect on the relative permeability of the wetting fluid (water) but a more significant impact on the relative permeability of the non-wetting fluid (scCO 2 ). The Corey model was used to fit the LB-simulated relative permeability curves of water and scCO 2 and showed that the variations in the relative permeability curves for both water and scCO 2 increased as the standard deviation and spatial correlation length of CA increased. This study illustrated that the assumption of homogeneous surface wettability may cause errors in multiphase flow simulations. Furthermore, the impacts of both the standard deviation and spatial correlation length of CAs should be accounted for. This is the first study that explored the spatial correlation lengths associated with CA distributions on sandstone surfaces and comprehensively investigated the roles of both spatial variation and correlation length of CA on two-phase flow properties in 3D porous media. The optimized LB multiphase flow model was proved a powerful tool to study the interplays and combined effects of these statistical parameters, which had critical applications in numerous natural and engineering processes that involved multiphase flow in porous media.

58 GEOSCIENCES↗
DOE OSTI2024

Demonstration of a multi-channel fluidized bed particle–supercritical carbon dioxide heat exchanger for concentrating solar applications

High-temperature thermal energy storage in oxide particles at temperatures above 600°C can couple concentrated solar energy with high-efficiency thermal power cycles to provide dispatchable solar-driven electricity. Challenges remain in developing cost-effective primary heat exchangers, which require expensive alloys, to extract the high-temperature thermal energy from the particles to power cycle fluids, such as supercritical CO 2 (sCO 2 ) in recuperated Brayton cycles. To explore one pathway for cost-effective, high-temperature particle heat exchangers, the current study demonstrates a shell-and-plate, particle–sCO 2 heat exchanger with narrow- channel fluidized beds coupled with micro-channel sCO 2 flows in the heat exchanger walls. This study evaluates the feasibility of multiple parallel, narrow-channel fluidized beds in shell-and-plate particle–sCO 2 HXs, to achieve high bed-wall heat fluxes at elevated temperatures. A reduced-order model simulates the narrow- channel, fluidized-bed particle–sCO 2 heat exchanger to design the fluidized bed geometry, in terms of depth, height, and number of channels,for a nominal 40-kWth heat exchanger at particle and sCO 2 inlet temperatures up to 600 °C and 400 °C respectively. The resulting shell-and-plate heat exchanger design operates with bubbling fluidization of the downward-flowing oxide particles to enhance bed-wall heat transfer. The heat exchanger core is fabricated with etched sCO 2 micro-channels in thin wall plates that are diffusion bonded to spacer frames to form the shell-and-plate structure with 12 parallel, fluidized bed channels, 10.4 mm deep. The heat exchanger is tested at the National Solar Thermal Test Facility at Sandia National Laboratories with CARBOBEAD HSP particles at design particle flow rates of 0.20 kg s –1 and inlet temperatures up to 525 °C. Results show that fluidization across multiple parallel channel beds can maintain uniform particle inventory with a common freeboard zone above the heat exchanger core. Bubbling fluidization improves particle–wall heat transfer coefficients but also increases axial dispersion of particle thermal energy, which lowers the log- mean temperature difference such that total heat transfer remains relatively constant to within ±10% over a broad range of fluidization gas velocities. The axial dispersion required particle and sCO 2 flow rates to be increased by 25% over model-designed conditions to achieve the targeted 40 kWth, which indicates the importance of incorporating axial dispersion into heat exchanger design models and of deploying bed structures to suppress it. Furthermore, this study demonstrates the feasibility and preferred fluidizing gas conditions for particle heat exchangers for releasing high-temperature thermal energy storage systems.

14 SOLAR ENERGY↗
DOE OSTI2021

Iron speciation in blast furnace slag cements

Slag-containing pastes and concretes were analysed by element-specific synchrotron-based techniques to determine the speciation of iron on crushed materials through spatially resolved micro-spectroscopic studies. The investigated cement samples were hydrated either in the laboratory, or exposed to river or sea water. Metallic iron, along with minor proportions of iron sulphide and magnetite was detected in the laboratory sample. Iron sulphide, goethite, and siliceous hydrogarnet were discovered in the blended slag cements hydrated in contact with river water for up to 7 years. In contrast, no Fe(0) was observed in blended concretes exposed to sea water. Instead, iron sulphide, iron(II)-hydroxide and -oxide, hematite, magnetite, siliceous hydrogarnet, and goethite were detected as well as ilmenite (FeTiO{sub 3}) in the aggregates. The strong acceleration of Fe oxidation in samples exposed to sea water and the long-term passivation observed in the other samples indicate comparable processes as those occurring on steel bars.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Estimation of constituent properties of concrete materials with an artificial neural network based method

Multi-scale models are developed for heterogeneous concrete materials to estimate their macroscopic mechanical properties in terms of micro-structural data. One crucial challenge of those models is the identification of local properties of constituent phases. In this paper, we present an efficient method based on Artificial Neural Networks (ANN). Typical concrete materials are taken as example. A macroscopic analytical strength criterion is established from three steps of nonlinear homogenization procedure. The macroscopic strength of materials is determined as a function of the frictional coefficient and cohesion of solid cement particles at nanometer scale, intra-particle pores, inter-particle pores and aggregates (inclusions). The objective is to identify the nanoscopic frictional coefficient and cohesion of cement particle from measured macroscopic values of uniaxial compression and tensile strengths. For this purpose, a numerical method based on the ANN is developed. With the analytical macroscopic strength criterion, sensitivity studies are first realized to identify the most important micro-structural parameters influencing the macroscopic strength of concrete. A simplified analytical macroscopic strength criterion is then proposed. A large dataset is further constructed through the inversion of the analytical strength criterion by using the aggregates volume fraction, porosity, macroscopic uniaxial tensile and compressive strengths as input variables and the frictional coefficient and cohesion of cement particles as output unknowns. An ANN model containing four hidden layers and 100 neurons in each layer is constructed and trained by using this dataset. Various types of validation of the ANN model are performed. It is found that the proposed ANN based model can effectively predict the frictional coefficient and cohesion of porous cement paste at the microscopic scale with a very good accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamic fracture of glass fiber-reinforced ductile polymer matrix composites and loading rate effect

Here, the dynamic fracture of S-2 glass fiber-reinforced polymer matrix composites (FRPMCs) was investigated in this study. The matrix ductility was improved by a recently developed network topology modification technique via mixing partially reacted substructures (mPRS). The composite material was manufactured and characterized by micro-CT scanning and scanning electron microscopy (SEM). Dynamic single-edge notched bending (d-SENB) experiments were performed on the composites by using a modified split-Hopkinson pressure bar. Each specimen’s fracture process was visualized by ultrafast X-ray imaging. Such in-situ radiography enabled identifying the damage initiation below 50-micron scale and inspecting its propagation through the internal structures of opaque composites, thereby accurately quantifying the composites’ mechanical properties. Furthermore, the identical d-SENB experiments were designed and the digital image correlation (DIC) was employed to monitor the stress wave propagation on the composite specimens. The force and deflection measurements were modified and correlated to the physical damage processes. Besides, quasi-static SENB experiments were conducted to identify the loading rate effects on the composites’ fracture behaviors. The force and deflection history, bending stiffness, energy dissipation, and fracture toughness at different loading rates were quantified and compared. Finally, post-fracture analysis by micro-CT scanning and SEM provided physical observations on the variation of the fracture morphology by different loading rates.

42 ENGINEERING↗