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In this study, an adaptive finite element method (FEM) is developed for structural eigenproblems of cracked Euler-Bernoulli beams via the superconvergent patch recovery displacement technique. This research comprises the numerical algorithm and experimental results for free vibration problems (forward eigenproblems) and damage detection problems (inverse eigenproblems). Design/methodology/approach The weakened properties analogy is used to describe cracks in this model. The adaptive strategy proposed in this paper provides accurate, efficient, and reliable eigensolutions of frequency and mode (i.e. eigenpairs as eigenvalue and eigenfunction) for Euler-Bernoulli beams with multiple cracks. Based on the frequency measurement method for damage detection, utilizing the difference between the actual and computed frequencies of cracked beams, the inverse eigenproblems are solved iteratively for identifying the residuals of locations and sizes of the cracks by the Newton-Raphson iteration technique. In the crack detection, the estimated residuals are added to obtain reliable results, which is an iteration process that will be expedited by more accurate frequency solutions based on the proposed method for free vibration problems. Findings Numerical results are presented for free vibration problems and damage detection problems of representative non-uniform and geometrically stepped Euler-Bernoulli beams with multiple cracks to demonstrate the effectiveness, efficiency, accuracy and reliability of the proposed method. Originality/value The proposed combination of methodologies described in the paper, leads to a very powerful approach for free vibration and damage detection of beams with cracks, introducing the mesh refinement, that can be extended to deal with the damage detection of frame structures.

We describe the combinatorial synthesis and cheminformatics modeling of aminoglycoside antibiotics-derived polymers for transgene delivery and expression. Fifty-six polymers were synthesized by polymerizing aminoglycosides with diglycidyl ether cross-linkers. Parallel screening resulted in identification of several lead polymers that resulted in high transgene expression levels in cells. The role of polymer physicochemical properties in determining efficacy of transgene expression was investigated using Quantitative Structure-Activity Relationship (QSAR) cheminformatics models based on Support Vector Regression (SVR) and ‘building block’ polymer structures. The QSAR model exhibited high predictive ability, and investigation of descriptors in the model, using molecular visualization and correlation plots, indicated that physicochemical attributes related to both, aminoglycosides and diglycidyl ethers facilitated transgene expression. This work synergistically combines combinatorial synthesis and parallel screening with cheminformatics-based QSAR models for discovery and physicochemical elucidation of effective antibiotics-derived polymers for transgene delivery in medicine and biotechnology.

Predicting the effective mechanical property of heterogeneous materials by image based modeling and deep learning. Computer Methods in Applied Mechanics and Engineering

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The mechanism responsible for deformation-induced crystalline-to-amorphous transition (CAT) in silicon is still under considerable debate, owing to the absence of direct experimental evidence. Here we have devised a novel core/shell configuration to impose confinement on the sample to circumvent early cracking during uniaxial compression of submicron-sized Si pillars. This has enabled large plastic deformation and in situ monitoring of the CAT process inside a transmission electron microscope. We demonstrate that diamond cubic Si transforms into amorphous silicon through slip-mediated generation and storage of stacking faults (SFs), without involving any intermediate crystalline phases. By employing density functional theory simulations, we find that energetically unfavorable single-layer SFs create very strong antibonding interactions, which trigger the subsequent structural rearrangements. Our findings thus resolve the interrelationship between plastic deformation and amorphization in silicon, and shed light on the mechanism underlying deformation-induced CAT in general.

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Four linear polyurea elastomers synthesized from two different diisocyanates, two different chain extenders and a common aliphatic amine-terminated polyether were used as models to investigate the effects of both diisocyanate structure and aromatic disulfide chain extender on hard segmental packing and self-healing ability. Both direct investigation on hard segments and indirect investigation on chain mobility and soft segmental dynamics were carried out to compare the levels of hard segmental packing, leading to agreed conclusions that correlated well with the self-healing abilities of the polyureas. Both diisocyanate structure and disulfide bonds had significant effects on hard segmental packing and self-healing property. Diisocyanate structure had more pronounced effect than disulfide bonds. Bulky alicyclic isophorone diisocyanate (IPDI) resulted in looser hard segmental packing than linear aliphatic hexamethylene diisocyanate (HDI), whereas a disulfide chain extender also promoted self-healing ability through loosening of hard segmental packing compared to its C-C counterpart. The polyurea synthesized from IPDI and the disulfide chain extender exhibited the best self-healing ability among the four polyureas because it had the highest chain mobility ascribed to the loosest hard segmental packing. Therefore, a combination of bulky alicyclic diisocyanate and disulfide chain extender is recommended for the design of self-healing polyurea elastomers.