Shooting flexible electronics

The trends of the future electronic devices should be miniaturized,flexible,stable,portable,light,and highly integrated.Although flexible electronic products(i.e.,flexible display products^[1-3],batteries^[4,5],cell phones[6])have been commercially available recently,which represents the starting of a new era in electronics,these progresses are still in their infancy and more efforts are required to boom their multifunction and speed up their marketization from lab.Considering their low-cost and mass-productive synthesis technologies,rich species,high performances,and especially,the excellent flexibility and stability,organic materials(insulating,conductive and semiconducting)have triggered the tide of the development of"plastic electronics",especially in transistors,an indispensable logic device in these logic-control based devices(i.e.,intelligent electronics).     

A smooth homotopy method for incomplete markets

Mathematical Programming - In the general equilibrium with incomplete asset markets (GEI) model, the excess demand functions are typically not continuous at the prices for which the assets have...     

Fully asynchronous stochastic coordinate descent: a tight lower bound on the parallelism achieving linear speedup

Mathematical Programming - We seek tight bounds on the viable parallelism in asynchronous implementations of coordinate descent that achieves linear speedup. We focus on asynchronous coordinate...     

Preface: Mechanics of soft materials and flexible structures

Acta Mechanica Sinica -     

Quantized-states-based adaptive control against unknown slippage effects of uncertain mobile robots with input and state quantization

An adaptive tracking design strategy based on quantized state feedback is developed for uncertain nonholonomic mobile robots with unknown wheel slippage effects. All state variables and control torques are assumed to be quantized by the state and input quantizers, respectively, in a network control environment. Thus, the quantized state feedback information is only available for the tracking control design. An approximation-based adaptive controller using quantized states is recursively designed to ensure the robust adaptive tracking against unknown wheel slippage effects where the quantized-states-based adaptive mechanism is derived to compensate for unknown wheel slippage effects, system nonlinearities, and quantization errors. The boundedness of the quantization errors and estimated parameters in the closed-loop system is analyzed by presenting some theoretical lemmas. Based on these lemmas, we prove the uniform ultimate boundedness of closed-loop signals and the convergence of the trajectory tracking error in the presence of wheel slippage effects. Simulations verify the effectiveness of the resulting tracking scheme.     

Sonochemical conversion of CO2 into hydrocarbons: The Sabatier reaction at ambient conditions

In this study, we investigated an alternative method for the chemical CO₂ reduction reaction in which power ultrasound (488 kHz ultrasonic plate transducer) was applied to CO₂-saturated (up to 3%) pure water, NaCl and synthetic seawater solutions. Under ultrasonic conditions, the converted CO₂ products were found to be mainly CH₄, C₂H₄ and C₂H₆ including large amount of CO which was subsequently converted into CH₄. We have found that introducing molecular H₂ plays a crucial role in the CO₂ conversion process and that increasing hydrogen concentration increased the yields of hydrocarbons. However, it was observed that at higher hydrogen concentrations, the overall conversion decreased since hydrogen, a diatomic gas, is known to decrease cavitational activity in liquids. It was also found that 1.0 M NaCl solutions saturated with 2% CO₂ + 98% H₂ led to maximum hydrocarbon yields (close to 5%) and increasing the salt concentrations further decreased the yield of hydrocarbons due to the combined physical and chemical effects of ultrasound. It was shown that CO₂ present in a synthetic industrial flue gas (86.74% N₂, 13% CO₂, 0.2% O₂ and 600 ppm of CO) could be converted into hydrocarbons through this method by diluting the flue gas with hydrogen. Moreover, it was observed that in addition to pure water, synthetic seawater can also be used as an ultrasonicating media for the sonochemical process where the presence of NaCl improves the yields of hydrocarbons by ca. 40%. We have also shown that by using low frequency high-power ultrasound in the absence of catalysts, it is possible to carry out the conversion process at ambient conditions i.e., at room temperature and pressure. We are postulating that each cavitation bubble formed during ultrasonication act as a “micro-reactor” where the so-called Sabatier reaction -$C{O}_2+4H_2\stackrel{\mathit{Ultrasonication}}{\to }C{H}_4+2H_{2}O$ - takes place upon collapse of the bubble. We are naming this novel approach as the “Islam-Pollet-Hihn process”.     

Transfer learning in deep neural network based under-sampled MR image reconstruction

In Magnetic Resonance Imaging (MRI), the success of deep learning-based under-sampled MR image reconstruction depends on: (i) size of the training dataset, (ii) generalization capabilities of the trained neural network. Whenever there is a mismatch between the training and testing data, there is a need to retrain the neural network from scratch with thousands of MR images obtained using the same protocol. This may not be possible in MRI as it is costly and time consuming to acquire data. In this research, a transfer learning approach i.e. end-to-end fine tuning is proposed for U-Net to address the data scarcity and generalization problems of deep learning-based MR image reconstruction. First the generalization capabilities of a pre-trained U-Net (initially trained on the human brain images of 1.5 T scanner) are assessed for: (a) MR images acquired from MRI scanners of different magnetic field strengths, (b) MR images of different anatomies and (c) MR images under-sampled by different acceleration factors. Later, end-to-end fine tuning of the pre-trained U-Net is proposed for the reconstruction of the above-mentioned MR images (i.e. (a), (b) and (c)). The results show successful reconstructions obtained from the proposed method as reflected by the Structural SIMilarity index, Root Mean Square Error, Peak Signal-to-Noise Ratio and central line profile of the reconstructed images.