Dynamic Bonds Mediate π-π Interaction via Phase Locking Effect for Enhanced Heat Resistant Thermoplastic Polyurethane

Stimulus-responsive polymers containing dynamic bonds enable fascinating properties of self-healing,recycling and reprocessing due to enhanced relaxation of polymer chain/network with labile linkages.Here,we study the structure and properties of a new type of thermoplastic polyurethanes(TPUs)with trapped dynamic covalent bonds in the hard-phase domain and report the frustrated relaxation of TPUs containing weak dynamic bond andπ-πinteraction in hard segments.As detected by rheometry,the aromatic TPUs with alkyl disulfide in the hard segments possess the maximum network relaxation time in contrast to those without dynamic bonds and alicyclic TPUs.In situ FTIR and small-angle scattering results reveal that the alkyl disulfide facilitates stronger intermolecular interaction and more stable micro-phase morphology inπ-πinteraction based aromatic TPUs.Molecular dynamics simulation for pure hard segments of model molecules verify that the presence of disulfide bonds leads to strongerπ-πstacking of aromatic rings due to both enhanced assembling thermodynamics and kinetics.The enhancedπ-πpacking and micro-phase structure in TPUs further kinetically immobilize the dynamic bond.This kinetically interlocking between the weak dynamic bonds and strong molecular interaction in hard segments leads to much slower network relaxation of TPU.This work provides a new insight in tuning the network relaxation and heat resistance as well as molecular self-assembly in stimulus-responsive dynamic polymers by both molecular design and micro-phase control toward the functional applications of advanced materials.

Dynamic necking of a near α titanium alloy at high strain rates:Experiments and modelling

The tensile behaviour of near a Ti3Al2.5 V alloy,conceived for applications in aerospace and automotive engineering,is characterized from quasi-static to high strain rates.The material is found to present noticeable strain rate sensitivity.The dynamic true strain rate in the necking cross-section reaches values up to ten times higher than the nominal strain rate.It is also observed that beyond necking the dynamic true stress-strain curves present limited rate dependence.The experimental results at different strain rates are used to determine a suitable constitutive model for finite element simulations of the dynamic tensile tests.The model predicts the experimentally macroscopic force-time response,true stress-strain response and effective strain rate evolution with good agreement.

Detailed study of NBTI characterization in 40-nm CMOS process using comprehensive models

The impact of negative bias temperature instability （NBTI） can be ascribed to three mutually uncorrelated factors, including hole trapping by pre-existing traps （△ VHT） in gate insulator, generated traps （△ VOT） in bulk insulator, and interface trap generation （△ VIT）. In this paper, we have experimentally investigated the NBTI characteristic for a 40-nm complementary metal-oxide semiconductor （CMOS） process. The power-law time dependence, temperature activation, and field acceleration have also been explored based on the physical reaction-diffusion model. Moreover, the end-of-life of stressed device dependent on the variation of stress field and temperature have been evaluated. With the consideration of locking effect, the recovery characteristics have been modelled and discussed.

Spatial Distribution of Large-scale Landslides Induced by the 5.12 Wenchuan Earthquake

The 5.12 Wenchuan Earthquake in 2008 induced hundreds of large-scale landslides. This paper systematically analyzes 112 large-scale landslides (surface area > 50000 m2), which were identified by interpretation of remote sensing imagery and field investigations. The analysis suggests that the distribution of large-scale landslides is affected by the following four factors: (a) distance effect: 80% of studied large-scale landslides are located within a distance of 5 km from the seismic faults. The farther the distance to the faults, the lower the number of large-scale landslides; (b) locked segment effect: the large-scale landslides are mainly located in five concentration zones closely related with the crossing, staggering and transfer sections between one seismic fault section and the next one, as well as the end of the NE fault section. The zone with the highest concentration was the Hongbai-Chaping segment, where a great number of large-scale landslides including the two largest landslides were located. The second highest concentration of large-scale landslides was observed in the Nanba-Donghekou segment at the end of NE fault, where the Donghekou landslide and the Woqian landslide occurred; (c) Hanging wall effect: about 70% of the large-scale landslides occurred on the hanging wall of the seismic faults; and (d) direction effect: in valleys perpendicular to the seismic faults, the density of large-scale landslides on the slopes facing the seismic wave is obviously higher than that on the slopes dipping in the same direction as the direction of propagation of the seismic wave. Meanwhile, it is found that the sliding and moving directions of large-scale landslides are related to the staggering direction of the faults in each section. In Qingchuan County where the main fault activity was horizontal twisting and staggering, a considerable number of landslides showed the feature of sliding and moving in NE direction which coincides with the staggering direction of the seismic faults.

Reaction order and neural network approaches for the simulation of COVID-19 spreading kinetic in India

COVID-19 has created a pandemic situation in the whole world.Controlling of COVID-19 spreading rate in the social environment is a challenge for all individuals.In the present study,simulation of the lockdown effect on the COVID-19 spreading rate in India and mapping of its recovery percentage(until May 2020)were investigated.Investigation of the lockdown impact dependent on first order reaction kinetics demonstrated higher effect of lockdown 1 on controlling the COVID-19 spreading rate when contrasted with lockdown 2 and 3.Although decreasing trend was followed for the reaction rate constant of different lockdown stages,the distinction between the lockdown 2 and 3 was minimal.Mathematical and feed forward neural network(FFNN)approaches were applied for the simulation of COVID-19 spreading rate.In case of mathematical approach,exponential model indicated adequate performance for the prediction of the spreading rate behavior.For the FFNN based modeling,1-5-1 was selected as the best architecture so as to predict adequate spreading rate for all the cases.The architecture also showed effective performance in order to forecast number of cases for next 14 days.The recovery percentage was modeled as a function of number of days with the assistance of polynomial fitting.Therefore,the investigation recommends proper social distancing and efficient management of corona virus in order to achieve higher decreasing trend of reaction rate constant and required recovery percentage for the stabilization of India.