The title molecule, C8H12NO5PS2, exhibits a crystallographic mirror plane that is perpendicular to the ring and bisects the sulfamoyl and thiophosphate ester groups. In the crystal, molecules are ...linked by N-H...O hydrogen-bonding interactions reminiscent of carboxylic acid hydrogen bonding pairs, forming chains parallel to the b-axis direction.
All-atom molecular dynamics (MD) simulations were used to study shock wave loading in oriented single crystals of the highly anisotropic triclinic molecular crystal ...1,3,5-triamino-2,4,6-trinitrobenzene (TATB). The crystal structure consists of planar hydrogen-bonded sheets of individually planar TATB molecules that stack into graphitic-like layers. Shocks were studied for seven systematically prepared crystal orientations with limiting cases that correspond to shock propagation exactly perpendicular and exactly parallel to the graphitic-like layers. The simulations were performed for initially defect-free crystals using a reverse-ballistic configuration that generates explicit, supported shocks. Final longitudinal stress components are between ≈8.5 and ≈10.5 GPa for the 1.0 km s–1 impact speed studied. Orientation-dependent properties are reported including shock speeds, stresses, temperatures, compression ratios, and local material strain rates. Spatiotemporal maps of the temperature, stress tensor, material flow, and molecular orientations reveal complicated processes that arise for specific shock directions. The results indicate that TATB shock response is highly sensitive to crystal orientation, with significant qualitative differences for the time evolution of the stress tensor and temperature, elastic/inelastic compression response, defect formation and growth, critical von Mises stress, and strain rates during shock rise that span nearly an order of magnitude. A variety of inelastic deformation mechanisms are identified, ranging from crumpling of graphitic-like layers to dislocation-mediated plasticity to intense shear strain localization. To our knowledge, these are the first systematic MD simulations and analysis of explicit shock wave propagation along nontrivial crystal directions in a triclinic molecular crystal.
We present a machine learning framework to train and validate neural networks to predict the anisotropic elastic response of a monoclinic organic molecular crystal known as β$$ \beta $$‐HMX in the ...geometrical nonlinear regime. A filtered molecular dynamic (MD) simulations database is used to train neural networks with a Sobolev norm that uses the stress measure and a reference configuration to deduce the elastic stored free energy functional. To improve the accuracy of the elasticity tangent predictions originating from the learned stored free energy, a transfer learning technique is used to introduce additional tangential constraints from the data while necessary conditions (e.g., strong ellipticity, crystallographic symmetry) for the correctness of the model are either introduced as additional physical constraints or incorporated in the validation tests. Assessment of the neural networks is based on (1) the accuracy with which they reproduce the bottom‐line constitutive responses predicted by MD, (2) the robustness of the models measured by detailed examination of their stability and uniqueness, and (3) the admissibility of the predicted responses with respect to mechanics principles in the finite‐deformation regime. We compare the training efficiency of the neural networks under different Sobolev constraints and assess the accuracy and robustness of the models against MD benchmarks for β$$ \beta $$‐HMX.
Featured Cover Vlassis, Nikolaos N.; Zhao, Puhan; Ma, Ran ...
International journal for numerical methods in engineering,
09/2022, Letnik:
123, Številka:
17
Journal Article
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The cover image is based on the Original Article Molecular dynamics inferred transfer learning models for finite‐strain hyperelasticity of monoclinic crystals: Sobolev training and validations ...against physical constraints by Nikolaos Vlassis et al., https://doi.org/10.1002/nme.6992.
The high-speed direct-drive blower is a high-efficiency, energy-saving, and environmentally friendly blower, and it is widely applied in industrial fields. The temperature changes significantly ...affect the performance of the high-speed direct-drive blower, and it is crucial to monitor its temperature. Infrared and visible light cameras are simultaneously used to measure and characterize temperature information. The measurement method can have both the temperature information of the infrared image and the contrast information of the structure and contour of the visible light image. This article establishes an image fusion representation and probabilistic generation model of infrared and visible images. Then, the information of the infrared and visible images is fused under the Bayesian framework. A hierarchical prior model using the Haar wavelet transform is proposed. The joint maximum a posteriori criterion is chosen, and an appropriate alternate optimization algorithm is designed to achieve information fusion. The proposed method is validated in industrial scenarios of high-speed direct-drive blowers. The experimental results demonstrate the robustness and effectiveness of the proposed method.
The thermo-mechanical response of shock-induced pore collapse has been studied using non-reactive all-atom molecular dynamics (MD) and Eulerian continuum simulations for the molecular crystal ...1,3,5-triamino-2,4,6-trinitrobenzene (TATB). Three crystal orientations, bracketed by the limiting cases with respect to the crystal structure anisotropy in TATB, are considered in the MD simulations, while an isotropic constitutive model is used for the continuum simulations. Simulations with three impact speeds from 0.5 km/s to 2.0 km/s are investigated. Results from MD and continuum simulations are in agreement in terms of shock wave speeds, temperature distributions, and pore-collapse mechanisms. However, differences arise for other quantities that are also important in hotspot ignition and growth, for example, the skewness of high-temperature distributions and the local temperature field around the post-collapse hotspot, indicating the urgent need to incorporate anisotropic crystal plasticity and strength models into the continuum descriptions. The deformation mechanisms of TATB crystals in the shock-induced pore collapse MD simulations were studied using Strain Functional Analysis. This new approach maps discrete quantities from atomistic simulations onto continuous fields via a Gaussian kernel, from which a unique and complete set of rotationally invariant Strain Functional Descriptors (SFD) is obtained from the high-order central moments of local configurations, expressed in a Solid Harmonics polynomial basis by SO(3) decomposition. Coupled with unsupervised machine learning techniques, the SFD successfully identifies and distinguishes the deformations presented in the MD simulations of shock-compressed TATB crystals. It enables automated detection of disordered structures in the system and can be readily applied to materials with any symmetry class.
We present a machine learning framework to train and validate neural networks
to predict the anisotropic elastic response of the monoclinic organic molecular
crystal $\beta$-HMX in the geometrical ...nonlinear regime. A filtered molecular
dynamic (MD) simulations database is used to train the neural networks with a
Sobolev norm that uses the stress measure and a reference configuration to
deduce the elastic stored energy functional. To improve the accuracy of the
elasticity tangent predictions originating from the learned stored energy, a
transfer learning technique is used to introduce additional tangential
constraints from the data while necessary conditions (e.g. strong ellipticity,
crystallographic symmetry) for the correctness of the model are either
introduced as additional physical constraints or incorporated in the validation
tests. Assessment of the neural networks is based on (1) the accuracy with
which they reproduce the bottom-line constitutive responses predicted by MD,
(2) detailed examination of their stability and uniqueness, and (3)
admissibility of the predicted responses with respect to continuum mechanics
theory in the finite-deformation regime. We compare the neural networks'
training efficiency under different Sobolev constraints and assess the models'
accuracy and robustness against MD benchmarks for $\beta$-HMX.
We present a machine learning framework to train and validate neural networks to predict the anisotropic elastic response of the monoclinic organic molecular crystal \(\beta\)-HMX in the geometrical ...nonlinear regime. A filtered molecular dynamic (MD) simulations database is used to train the neural networks with a Sobolev norm that uses the stress measure and a reference configuration to deduce the elastic stored energy functional. To improve the accuracy of the elasticity tangent predictions originating from the learned stored energy, a transfer learning technique is used to introduce additional tangential constraints from the data while necessary conditions (e.g. strong ellipticity, crystallographic symmetry) for the correctness of the model are either introduced as additional physical constraints or incorporated in the validation tests. Assessment of the neural networks is based on (1) the accuracy with which they reproduce the bottom-line constitutive responses predicted by MD, (2) detailed examination of their stability and uniqueness, and (3) admissibility of the predicted responses with respect to continuum mechanics theory in the finite-deformation regime. We compare the neural networks' training efficiency under different Sobolev constraints and assess the models' accuracy and robustness against MD benchmarks for \(\beta\)-HMX.
The title mol-ecule, C8H12NO5PS2, exhibits a crystallographic mirror plane that is perpendicular to the ring and bis-ects the sulfamoyl and thio-phosphate ester groups. In the crystal, mol-ecules are ...linked by N-H⋯O hydrogen-bonding inter-actions reminiscent of carb-oxy-lic acid hydrogen bonding pairs, forming chains parallel to the b-axis direction.
Betatrophin is regarded as a liver-produced hormone induced by insulin resistance (IR). However, it remains largely unknown how IR regulates betatrophin expression. To study whether IR could regulate ...betatrophin expression and the corresponding molecular mechanisms, betatrophin levels were examined in 6 in vitro IR models which were established using human hepatocytes L02 with different agents, including tumor necrosis factor-α, interleukin-1β, dexamethasone, palmitate, high glucose and insulin and betatrophin levels were elevated only in the insulin group. These results suggest that it is insulin, not IR that promotes betatrophin expression. In the meantime, PI3K/Akt pathway was activated by insulin and suppressed by above agents that caused IR. Insulin-upregulated betatrophin expression was suppressed by PI3K/Akt inhibitors and IR, suggesting that insulin upregulates and IR decreases betatrophin production through PI3K/Akt pathway. Consistently, the treatment of insulin in mice dose-dependently upregulated betatrophin levels, and the administration of metformin in IR mice also stimulated betatrophin production since published study showed metformin improved PI3K/Akt pathway and IR. In humans, compared with those without insulin treatment, serum betatrophin levels were increased in type 2 diabetic patients with insulin treatment. In conclusion, insulin stimulates betatrophin secretion through PI3K/Akt pathway and IR may play an opposite role.
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