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133 records · Page 8

Tunable shear thickening, aging, and rejuvenation in suspensions of shape-memory-endowed liquid crystalline particles

The morphological features of particles, notably shape anisotropy, critically influence the rheological properties of dense suspensions, spanning both natural and engineered systems. This work explores the potential of using shape memory particles to dynamically regulate suspension fluid flow through controllable shape transformations. First, we synthesize shape-memory particles with programmable anisotropy from liquid crystal elastomers, such that the stiffness and shapes of the particles can be tuned by manipulating temperature. Our findings reveal that suspensions from such particles exhibit significant tunability in shear thickening behavior, transitioning from discontinuous shear thickening to a Newtonian-like response within a narrow temperature range of 60 ° C. This capability to modulate rheological responses in situ presents an approach for addressing processing challenges in many applications where control over flow behavior is paramount. Furthermore, we also show that suspensions composed of these anisotropic particles can undergo physical aging, and evolve into a glassy state. This state can be escaped upon activation of the shape memory effect. This reversibility underscores the potential for using such materials to engineer systems that can enter or come out of kinetic arrest by leveraging internal mechanical responses to external stimuli. The insights gained here not only broaden our understanding of the interplay between particle geometry and suspension dynamics but also pave the way for leveraging ensembles of stimuli-responsive objects to precisely control collective behaviors in many-body systems.

Science & Technology - Other Topics↗

Microstructural and rheological training and memory of nanocolloidal soft glasses under cyclic shear

An intrinsic feature of disordered and out-of-equilibrium materials, such as glasses, is the dependence of their properties on their history. An important example is rheological memory, in which disordered solids obtain properties based on their deformation history. Here, in this study, we employ x-ray photon correlation spectroscopy with in situ rheometry to characterize memory formation in a nanocolloidal soft glass due to cyclic shear. During a cycle, particles undergo irreversible displacements composed of a combination of shear-induced diffusion and heterogeneous, residual strain fields. At lower shear amplitudes, the displacements resemble a random walk in which the directions in each cycle are independent of those in preceding cycles, while at high amplitude, the irreversible displacements in consecutive cycles become correlated. The magnitudes of the displacements decrease with each cycle before reaching a steady state where the microstructure has been trained to achieve enhanced reversibility even at shear amplitudes well above yielding and despite the presence of thermal fluctuations. At amplitudes below and near yielding, these decreases are monotonic, while well above yielding, they are nonmonotonic, suggesting evidence of shear banding. Accompanying this microstructural training are corresponding decreases in the dissipation during each cycle and the magnitude of the residual stress toward steady-state values. Memory of the training is revealed by measurements in which the amplitude of the shear is changed after steady state is reached. The magnitude of the particle displacements, as well as the dissipation and the change in residual stress, vary nonmonotonically with the new shear amplitude, having minima near the training amplitude, thereby revealing correlated microscopic and macroscopic signatures of memory.

Chen, Yihao [Johns Hopkins Univ., Baltimore, MD (U↗

The influence of physical and algorithmic factors on simulated far-field waveforms and source–time functions of underground explosions using unsupervised machine learning

SUMMARY Characterizing explosion sources and differentiating between earthquake and underground explosions using distributed seismic networks becomes non-trivial when explosions are detonated in cavities or heterogeneous ground material. Moreover, there is little understanding of how changes in subsurface physical properties affect the far-field waveforms we record and use to infer information about the source. Simulations of underground explosions and the resultant ground motions can be a powerful tool to systematically explore how different subsurface properties affect far-field waveform features, but there are added variables that arise from how we choose to model the explosions that can confound interpretation. To assess how both subsurface properties and algorithmic choices affect the seismic wavefield and the estimated source functions, we ran a series of 2-D axisymmetric non-linear numerical explosion experiments and wave propagation simulations that explore a wide array of parameters. We then inverted the synthetic far-field waveform data using a linear inversion scheme to estimate source–time functions (STFs) for each simulation case. We applied principal component analysis (PCA), an unsupervised machine learning method, to both the far-field waveforms and STFs to identify the most important factors that control variance in the waveform data and differences between cases. For the far-field waveforms, the largest variance occurs in the shallower radial receiver channels in the 0–50 Hz frequency band. For the STFs, both peak amplitude and rise times across different frequencies contribute to the variance. We find that the ground equation of state (i.e. lithology and rheology) and the explosion emplacement conditions (i.e. tamped versus cavity) have the greatest effect on the variance of the far-field waveforms and STFs, with the ground yield strength and fracture pressure being secondary factors. Differences in the PCA results between the far-field waveforms and STFs could possibly be due to near-field non-linearities of the source that are not accounted for in the estimation of STFs and could be associated with yield strength, fracture pressure, cavity radius and cavity shape parameters. Other algorithmic parameters are found to be less important and cause less variance in both the far-field waveforms and STFs, meaning algorithmic choices in how we model explosions are less important, which is encouraging for the further use of explosion simulations to study how physical Earth properties affect seismic waveform features and estimated STFs.

58 GEOSCIENCES↗

Hierarchically Structured Vitrimer Biocomposites for Sustainable Manufacturing

Polymers containing dynamic covalent bonds (DCBs) exhibit thermoplastic-like flow above their topology freezing temperature (T v ) while maintaining thermoset-like properties below it, making them promising for sustainable manufacturing. However, their large-scale adoption remains limited due to challenges in accurately determining T v and achieving efficient fiber-matrix bonding in composite applications. Here, hierarchically structured epoxy-anhydride-based polyester vitrimer composites reinforced with cellulosic filaments is demonstrated, where hydroxyl groups on fiber surfaces participate directly in transesterification with the matrix. Further, this dynamic interfacial bonding delivers exceptional mechanical properties, including ≈70 MPa shear strength and >10% strain-to-failure, while enabling thermal malleability. Using a combination of nuclear magnetic resonance and nano-infrared spectroscopies, direct evidence is provided that chemical bond exchange begins well below the conventionally measured T v , supporting the hypothesis that rheologically determined T v reflects a combination of chemical exchange and frictional dynamics rather than a discrete transition. The composites demonstrate excellent processability through vacuum-assisted resin transfer molding and maintain >90% of their mechanical properties after multiple thermal reforming cycles. These findings advance both the fundamental understanding of vitrimeric transitions and the practical development of sustainable, high-performance composite materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spectroscopic evidence for the Fe3+ spin transition in iron-bearing δ-AlOOH at high pressure

δ-AlOOH has emerged as a promising candidate for water storage in the lower mantle and could have delivered water into the bottom of the mantle. To date, it still remains unclear how the presence of iron affects its elastic, rheological, vibrational, and transport properties, especially across the spin crossover. In this study, we conducted high-pressure X-ray emission spectroscopy experiments on a δ-(Al 0.85 Fe 0.15 ) OOH sample up to 53 GPa using silicone oil as the pressure transmitting medium in a diamond-anvil cell. We also carried out laser Raman measurements on δ-(Al 0.85 Fe 0.15 )OOH and δ-(Al 0.52 Fe 0.48 )OOH up to 57 and 62 GPa, respectively, using neon as the pressure-transmitting medium. Evolution of Raman spectra of δ-(Al 0.85 Fe 0.15 )OOH with pressure shows two new bands at 226 and 632 cm –1 at 6.0 GPa, in agreement with the transition from an ordered ( P 2 1 nm ) to a disordered hydrogen bonding structure ( Pnnm ) for δ-AlOOH. Similarly, the two new Raman bands at 155 and 539 cm –1 appear in δ-(Al 0.52 Fe 0.48 )OOH between 8.5 and 15.8 GPa, indicating that the incorporation of 48 mol% FeOOH could postpone the order-disorder transition upon compression. On the other hand, the satellite peak ( K β') intensity of δ-(Al 0.85 Fe 0.15 )OOH starts to decrease at ~30 GPa and it disappears completely at 42 GPa. That is, δ-(Al 0.85 Fe 0.15 )OOH undergoes a gradual electronic spin-pairing transition at 30–42 GPa. Furthermore, the pressure dependence of Raman shifts of δ-(Al 0.85 Fe 0.15 )OOH discontinuously decreases at 32–37 GPa, suggesting that the improved hydrostaticity by the use of neon pressure medium could lead to a relatively narrow spin crossover. Notably, the pressure dependence of Raman shifts and optical color of δ-(Al 0.52 Fe 0.48 )OOH dramatically change at 41–45 GPa, suggesting that it probably undergoes a relatively sharp spin transition in the neon pressure medium. Together with literature data on the solid solutions between δ-AlOOH and ε-FeOOH, we found that the onset pressure of the spin transition in δ-(Al,Fe)OOH increases with increasing FeOOH content. These results shed new insights into the effects of iron on the structural evolution and vibrational properties of δ-AlOOH. The presence of FeOOH in δ-AlOOH can substantially influence its high-pressure behavior and stability at the deep mantle conditions and play an important role in the deep-water cycle

58 GEOSCIENCES↗

3D printed lignin/polymer composite with enhanced mechanical and anti-thermal-aging performance

Lignin is the most abundant natural aromatic polymer globally but is still underutilized as a renewable material, even with its versatile properties. One approach to using lignin is to incorporate it in polymer composites, but this application is often limited by the poor mechanical performance of the resultant composite due to the poor interfacial adhesion. Following the structure–property relationship, stronger interactions were designed to be enhanced by alternating the functional groups of lignin. Here, this study applied a demethylation method to hardwood lignin (Ori-Lig) to introduce more phenolic hydroxyl groups. Research studies with rheology behavior and molecular simulations demonstrated that an increased phenolic hydroxyl content could improve the adhesion between the modified lignin (OH-Lig) and the polymer matrix at the interface. The tensile performance of the samples from the fused depositional modeling (FDM) 3D printing technique was also improved due to the improved interfacial adhesion. Specifically, by adding 10 wt% of the modified lignin, the tensile strength of the 3D printed samples could reach 46.1 MPa (40.2 MPa of Polyamide 12, PA12), and Young’s Modulus could be improved to 1.73 GPa (1.48 GPa of PA12). OH-Lig also improved anti-aging performance so that the tensile strength of the OH-Lig composite after thermo-aging (100 h at 140 °C) remained ~48MPa. The enhanced mechanical performance with anti-aging properties indicated that the OH-Lig composite may replace PA12 to reduce the use of petrol-based materials. This work showed the method of purposefully designing and modifying lignin structures to fulfill the interaction requirements between lignin and polymer matrix. The as-prepared lignin could be used to prepare functional composites to achieve improved mechanical performance and targeted functions at the same time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nonlinear Shear Rheology of Entangled Polymer Rings

Steady-state shear viscosity η($\bar{γ}$) of unconcatenated ring polymer melts as a function of the shear rate $\bar{γ}$ is studied by a combination of experiments, simulations, and theory. Experiments using polystyrenes with Z ≈ 5 and Z ≈ 11 entanglements indicate weaker shear thinning for rings compared to linear polymers exhibiting power law scaling of shear viscosity η ~ $\bar{γ}$ –0.56 ± 0.02 , independent of chain length, for Weissenberg numbers up to about 10 2 . Nonequilibrium molecular dynamics simulations using the bead-spring model reveal a similar behavior with η ~ $\bar{γ}$ -0.57 ± 0.08 for 4 ≤ Z ≤ 57. Viscosity decreases with chain length for high $\bar{γ}$. In our experiments, we see the onset of this regime, and in simulations, which we extended to Wi ~ 10 4 , the nonuniversality is fully developed. In addition to a naive scaling theory yielding for the universal regime η ~ $\bar{γ}$ –0.57 , we developed a novel shear slit model explaining many details of observed conformations and dynamics as well as the chain length-dependent behavior of viscosity at large $\bar{γ}$. The signature feature of the model is the presence of two distinct length scales: the size of tension blobs and much larger thickness of a shear slit in which rings are self-consistently confined in the velocity gradient direction and which is dictated by the size of a chain section with relaxation time 1/$\bar{γ}$. These two length scales control the two normal stress differences. In this model, the chain length-dependent onset of nonuniversal behavior is set by tension blobs becoming as small as about one Kuhn segment. This model explains the approximate applicability of the Cox–Merz rule for ring polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗