Polymers which enrich semiconducting single‐walled carbon nanotubes (SWNTs) and are also removable after enrichment are highly desirable for achieving high‐performance field‐effect transistors (FETs). We have designed and synthesized a new class of alternating copolymers containing main‐chain fluorene and hydrofluoric acid (HF) degradable disilane for sorting and preferentially suspending semiconducting nanotube species. The results of optical absorbance, photoluminescence emission, and resonant Raman scattering show that poly[(9,9‐dioctylfluorenyl‐2,7‐diyl)‐alt‐co‐1,1,2,2‐tetramethyl‐disilane] preferentially suspends semiconducting nanotubes with larger chiral angle (25°–28°) and larger diameter (1.03 nm–1.17 nm) (specifically (8,7), (9,7) and (9,8) species) present in HiPCO nanotube samples. Computer simulation shows that P1 preferentially interacts with (8,7) (semiconducting) over (7,7) (metallic) species, confirming that P1 selects larger diameter, larger chiral angle semiconducting tubes. P1 wrapped on the surface of SWNTs is easily washed off through degradation of the disilane bond of the alternating polymer main chain in HF, yielding “clean” purified SWNTs. We have applied the semiconducting species enriched SWNTs to prepare solution‐processed FET devices with random nanotube network active channels. The devices exhibit stable p‐type semiconductor behavior in air with very promising characteristics. The on/off current ratio reaches up to 15 000, with on‐current level of around 10 μA and estimated hole mobility of 5.2 cm2 V−1 s−1.

In the present work, combining with the Geiger-Nuttall law, a two-parameter empirical formula is proposed to study the two-proton (2p) radioactivity. Using this formula, the calculated 2p radioactivity half-lives are in good agreement with the experimental data as well as the calculated ones obtained by Goncalves et al. ([Phys. Lett. B 774, 14 (2017)]) using the effective liquid drop model (ELDM), Sreeja et al. ([Eur. Phys. J. A 55, 33 (2019)]) using a four-parameter empirical formula and Cui et al. ([Phys. Rev. C 101: 014301 (2020)]) using a generalized liquid drop model (GLDM). In addition, this two-parameter empirical formula is extended to predict the half-lives of 22 possible 2p radioactivity candidates, whose the 2p radioactivity released energy Q2p>0, obtained from the latest evaluated atomic mass table AME2016. The predicted results have good consistency with ones using other theoretical models such as the ELDM, GLDM and four-parameter empirical formula.

Reinforced concrete (RC) buildings are commonly used around the world. With recent earthquakes worldwide, rapid structural damage inspection and repair cost evaluation are crucial for building owners and policy makers to make informed risk management decisions. To improve the efficiency of such inspection, advanced computer vision techniques based on convolutional neural networks have been adopted in recent research to rapidly quantify the damage state (DS) of structures. In this article, an advanced object detection neural network, named YOLOv2, is implemented, which achieves 98.2% and 84.5% average precision in training and testing, respectively. The proposed YOLOv2 is used in combination with the classification neural network, which improves the identification accuracy for critical DS of RC structures by 7.5%. The improved classification procedures allow engineers to rapidly and more accurately quantify the DSs of the structure, and also localize the critical damage features. The identified DS can then be integrated with the state‐of‐the‐art performance evaluation framework to quantify the financial losses of critical RC buildings. The results can be used by the building owners and decision makers to make informed risk management decisions immediately after the strong earthquake shaking. Hence, resources can be allocated rapidly to improve the resiliency of the community.

There has been little study on the effect of composition or molecular weight on the biodegradation rate of photo-cross-linked biodegradable aliphatic polyesters though such information is important for tissue engineering scaffolds. We have synthesized a new series of photopolymerizable linear poly(epsilon-caprolactone-co-lactide-co-glycolide) diacrylates with different molecular weights (Mn = 1800, 4800, and 9300 Da) and compositions (20%, 40%, and 60% epsilon-CL) and studied their biodegradation rates. The resultant oligomers were amorphous and appeared as viscous liquids at room temperature. Liquid-to-solid polymerization was carried out by UV irradiation in the presence of a photoinitiator. The photocuring yield was high (greater than 95%), and the photo-cross-linked polymers were amorphous and rubbery. Mechanical measurements showed that the polymers can be stretchable or rigid; the high molecular weight/low epsilon-CL network has a strain of 176% and a modulus of 1.66 MPa while the low molecular weight/high epsilon-CL network has a strain of 21% and a modulus of 12.3 MPa. In a 10 week in vitro biodegradation study, the polymers exhibited a two-stage degradation behavior. In the first stage, the polymer weight and strain remained almost constant, but a linear decrease in the Young's modulus (E) and ultimate stress (sigma) were observed. Lower oligomer molecular weight or epsilon-CL content correlated with a faster decrease in Young's modulus. In the second stage, which began when the Young's modulus dropped below 1 MPa, there was rapid weight loss and strain increase. The lower the epsilon-CL content, the earlier the second stage happened. Low molecular weight and high epsilon-CL content correlated with a longer modulus half-life (time for the modulus to degrade to 50% of its initial value). The degradation results suggest principles that may be helpful in predicting the biodegradation behavior of similar polymeric cross-linked networks. Films formed from these new polymers have excellent biocompatibility with smooth muscle cells.

In this study, based on the Gamow-like model, we systematically analyze two-proton ( ) radioactivity half-lives of nuclei near or beyond the proton drip line. It is found that the calculated results can reproduce experimental data well. Furthermore, using this model, we predict the half-lives of possible radioactivity candidates whose radioactivity is energetically allowed or observed but not yet quantified in the latest table of evaluated nuclear properties, i.e., NUBASE2016. The predicted results are in good agreement with those from other theoretical models and empirical formulas, namely the effective liquid drop model (ELDM), generalized liquid drop model (GLDM), Sreeja formula, and Liu formula.

Structural bolts are critical components used in different structural elements, such as beam-column connections and friction damping devices. The clamping force in structural bolts is highly influenced by the bolt rotation. Much of the existing vision-based research about bolt rotation estimation relies on traditional computer vision algorithms such as Hough transform to assess static images of bolts. This requires careful image preprocessing, and it may not perform well in the situation of complicated bolt assemblies, or in the presence of surrounding objects and background noise, thus hindering their real-world applications. In this study, an integrated real-time detect-track method, namely, RTDT-bolt, is proposed to monitor the bolt rotation angle. First, a real-time convolutionalneural-networks-based object detector, named YOLOv3-tiny, is established and trained to localize structural bolts. Then, the target-free object tracking algorithm based on optical flow is implemented to continuously monitor and quantify the rotation of structural bolts. In order to enhance the tracking performance against background noise and potential illumination changes during tracking, the YOLOv3-tiny is integrated with the optical flow tracking algorithm to redetect the bolts when the tracking gets lost. Extensive parameter studies were conducted to identify optimal tracking performance and examine the potential limitations. The results indicate that the RTDT-bolt method can greatly enhance the tracking performance of bolt rotation, which can achieve over 90% accuracy using the recommended range for the parameters.

In this paper, the nuclear magnetic resonance (NMR) measurements are carried out to evaluate the micro‐cracking characteristics of sandstones during the creep stage under the different levels of creep stresses. The variations in the parameters, including transverse relaxation time (T2) spectra distribution, percentage of the pore distribution, incremental value of porosity and ultrasonic P wave velocity are analysed. The results show that, during the creep stage, small pores in the rocks gradually evolve into large pores, resulting in an increase in damage of rocks. With the increase of the loading ratio, the increasing rate of porosity increases sharply, implying that the damage degree becomes more serious under the high loading ratio. When the loading ratio is larger than 0.7, the increasing rate of porosity and the decreasing rate of the P wave velocity both increases rapidly. During the creep stage, the relationship between micro‐crack and macro‐creep characteristics of rocks is established based on the analysis of the deformation and the porosity evolution during creep. It is found that, as the loading ratio increases, the increasing rate of porosity is linear with the creep strain. The NMR method offers a feasible option to identify micro‐cracking process of rocks during the creep stage, which can directly reflect the damage mechanism of rock caused by creep. The porosity of rocks is an effective parameter to evaluate the damage of rocks. The damage evolution of the specimen is highly anisotropic and is heavily related to the loading ratio during the creep stage. The relationship between the damage parameter and the loading ratio is exponential.

This work discusses the results from tests conducted to investigate the uniaxial compression and creep behavior of red sandstone. An original untreated sample and an 800°C treated sample were selected to carry out the experiments. High temperature had an obvious influence on the mechanical properties of the red sandstone. The relationship between creep strain and instantaneous strain, as well as the instantaneous deformation modulus and creep viscosity coefficient, was analyzed. High temperature reduced the ability of the red sandstone to resist instantaneous deformation and creep deformation. Acoustic emission (AE) technology was also used in the loading process of uniaxial compression and creep tests, providing a powerful means for damage evolutionary analysis of the red sandstone.