The flow-induced conformation dynamics of nanosheets are simulated using a Brownian Dynamics (BD) formulation applied to a bead-rod sheetlike molecular model. This is the first-ever use of BD to simulate flow-induced dynamics of two-dimensional structures. Using this framework, we simulate dilute suspensions of coarse-grained nanosheets and compute conformation dynamics for simple shear flow. The data show power law scaling relationships between nanosheet parameters (such as bending moduli and molecular weight) and the resulting intrinsic viscosity and conformation. For nonzero bending moduli, an effective dimension of 2.77 at equilibrium is calculated from the scaling relationship between radius of gyration and molecular weight. We also find that intrinsic viscosity varies with molecular weight with an exponent of 2.12 ± 0.23; this dependence is significantly larger than those found for linear polymers. Weak shear thinning is observed at high Weissenberg number (Wi). This simulation method provides a computational basis for developing manufacturing processes for nanosheet-derived materials by relating flow forces and nanosheet parameters to the resulting material morphology.

The morphology dynamics of two-dimensional nanosheets under extensional flow are investigated using a coarse-grained model. Nanosheets (graphene, BNNS, MX 2 ) are promising materials for a variety of materials and electronics applications. Extensional flow fields are often present during dispersion processing, such as spin coating. Both nanosheet properties (e.g., moduli, size) and processing parameters (e.g., extension rate) can have a significant impact on the nanosheet morphology and thus, the structure and properties of the bulk material. Our previously developed dimensionless Brownian dynamics methodology is used to explore biaxial extensional flow. Nanosheets exhibit a flat conformation under extensional flow for high bending moduli and an extended "washrag" conformation for low bending moduli. Intrinsic extensional viscosity increases with strain before reaching a plateau. The intrinsic viscosity exhibits a weak power law with nanosheet molecular weight. These simulation results allow for experimental control over morphology as a function of nanosheet properties and flow type and strength.

Using coarse-grained Brownian dynamics simulations, we study the relationship between hydrodynamic radius ([Formula: see text] and the lateral size ([Formula: see text] of dispersed nanosheets. Our simulation results show that the bending modulus of the nanosheets has a significant impact on the exponent of this power-law relationship between the radius of gyration (and thus [Formula: see text] and [Formula: see text] The exponent can vary from 0.17 to 1. This sheds light on the interpretation of dynamic light scattering (DLS) measurements, such that DLS data can capture both nanosheet lateral size and modulus (which is, in turn, affected by nanosheet thickness).

The China Earthquake Administration established a network for intensity rapid report and earthquake early warning (IRREEW) in 2016–2020, which consists of approximately 5000 conventional strong-motion and approximately 10,000 low-cost micro-electro-mechanical system (MEMS) seismometers. These seismographs, particularly MEMS stations, can provide a large amount of near-field waveform data suitable for rapid source inversion. Compared with conventional strong-motion data, MEMS recordings have rarely been used in the previous source inversions, because the MEMS technology is newly applied in earthquake monitoring, and the seismograph has a relatively lower signal-to-noise ratio and more severe baseline shifts. However, from waveform comparisons at collocated MEMS and strong-motion stations, we find that they are highly consistent with each other, particularly at frequencies above 0.04 Hz. To explore the application prospect of MEMS data to source inversion, we inverted both MEMS and strong-motion data for three strong earthquakes recorded by the IRREEW network during 2021–2022 to determine their rupture processes. In applications to the 2021 Mw 6.1 Yangbi earthquake, the 2022 Mw 6.6 Menyuan earthquake, and the 2022 Mw 6.6 Luding earthquake, the MEMS data equally well constrain the rupture model. The resulting source information, including the moment magnitude, rupture direction, and rupture dimension, are consistent with those obtained from the strong-motion inversions. Because the low-cost MEMS instruments can be deployed densely around seismically active regions, they can provide urgent waveform data for rapid determination of rupture process, which is crucial for simulation of strong ground motions, and assessments of earthquake and related disasters.

<p>The fault geometry closely controls earthquake rupture process. Previous seismic inversion of the fault geometry is to derive the multiple-point moment tensor solutions. Because of the trade-off between the moment tensor and rupture velocity, the inversion has high instabilities. In contrast, geodetic inversion has less unknowns, since there is no need to solve for rupture velocity. But from the elastic dislocation theory, the relations between the surface deformation and sub-fault parameters (i.e. strike, dip and rake) are nonlinear. In this study, we develop a linear technique to invert geodetic data for sub-fault moment tensors. From the sub-fault moment tensor solutions, the strike, dip, rake, and their spatial variations can be estimated, which provide valuable information for assessing the complexities in fault geometry. We applied this technique to several significant earthquakes, i.e., the 2008 Mw7.9 Wenchuan earthquake, the 2015 Mw7.8 Gorkha earthquake, and the 2017 Mw6.5 Jiuzhaigou earthquake. The results of the 2008 Wenchuan earthquake suggest that the strike, dip and rake are all variable from southwest to northeast, which are well consistent with the aftershock distributions and mechanisms. The dip variations of the 2015 Gorkha earthquake suggest the earthquake has ruptured a listric fault (dep decreases with depth). Particularly, a dip anomaly appears in the northeast corner of the rupture area, indicating a geometric barrier accounting for the slip gap between the mainshock and largest Mw7.3 aftershock. For the 2017 Jiuzhaigou earthquake, two right-stepping and left-lateral strike-slip segments were distinguished. Accordingly, a compressional step-over was identified between the two segments.</p>