Exploiting novel devices for either collecting energy or self-powered sensors is vital for Internet of Things, sensor networks, and big data. Triboelectric nanogenerators (TENGs) have been proved as an effective solution for both energy harvesting and self-powered sensing. The traditional triboelectric nanogenerators are usually based on four modes: contact-separation mode, lateral sliding mode, single-electrode mode, and freestanding triboelectric-layer mode. Since the reciprocating displacement/force is necessary for all working modes, developing efficient elastic TENG is going to be important and urgent. Here, a kind of elastic-beam TENG with arc-stainless steel foil is developed, whose structure is quite simple, and its working states depend on the contact area and separating distance as proved by experiments and theoretical calculations. This structure is different from traditional structures, e.g., direct sliding or contact-separation structures, whose working states mainly depend on contact area or separating distance. This triboelectric nanogenerator shows advanced mechanical and electrical performance, such as high sensitivity, elasticity, and ultrahigh frequency response, which encourage applications as a force sensor, sensitivity scale, acceleration sensor, vibration sensor, and intelligent keyboard.
Since pioneering work done in the late 1990s, synthesis of functional hollow materials has experienced a rapid growth over the past two decades while their applications have been proven to be advantageous across many technological fields. In the field of heterogeneous catalysis, the development of micro- and nanoscale hollow materials as catalytic devices has also yielded promising results, because of their higher activity, stability, and selectivity. Herein, the architecture and preparation of these catalysts with tailorable composition and morphology are reviewed. First, synthesis of hollow materials is introduced according to the classification of template mediated, template free, and combined approaches. Second, different architectural designs of hollow catalytic devices, such as those without functionalization, with active components supported onto hollow materials, with active components incorporated within porous shells, and with active components confined within interior cavities, are evaluated respectively. The observed catalytic performances of this new class of catalysts are correlated to structural merits of individual configuration. Examples that demonstrate synthetic approaches and architected configurations are provided. Lastly, possible future directions are proposed to advance this type of hollow catalytic devices on the basis of our personal perspectives.
Odom, Gabriel J.; Newhart, Kathryn B.; Cath, Tzahi Y.; Hering, Amanda S.(Applied Stochastic Models in Business and Industry, Wiley, 2018-05-09)[Article]
For high-dimensional, autocorrelated, nonlinear, and nonstationary data, adaptive-dynamic principal component analysis (AD-PCA) has been shown to do as well or better than nonlinear dimension reduction methods in flagging outliers. In some engineered systems, designed features can create a known multistate scheme among multiple autocorrelated, nonlinear, and nonstationary processes, and incorporating this additional known information into AD-PCA can further improve it. In simulations with one of three types of faults introduced, we compare accounting for the states versus ignoring them. We find that multistate AD-PCA reduces the proportion of false alarms and reduces the average time to fault detection. Conversely, we also investigate the impact of assuming multiple states when only one exists, and find that as long as the number of observations is sufficient, this misspecification is not detrimental. We then apply multistate AD-PCA to real-world data collected from a decentralized wastewater treatment system during in control and out of control conditions. Multistate AD-PCA flags a strong system fault earlier and more consistently than its single-state competitor. Furthermore, accounting for the physical switching system does not increase the number of false alarms when the process is in control and may ultimately assist with fault attribution.
Ogorzalek, Tadeusz L.; Hura, Greg L.; Belsom, Adam; Burnett, Kathryn H.; Kryshtafovych, Andriy; Tainer, John A.; Rappsilber, Juri; Tsutakawa, Susan E.; Fidelis, Krzysztof(Proteins: Structure, Function, and Bioinformatics, Wiley, 2018-01-04)[Article]
Experimental data offers empowering constraints for structure prediction. These constraints can be used to filter equivalently scored models or more powerfully within optimization functions toward prediction. In CASP12, Small Angle X-ray Scattering (SAXS) and Cross-Linking Mass Spectrometry (CLMS) data, measured on an exemplary set of novel fold targets, were provided to the CASP community of protein structure predictors. As HT, solution-based techniques, SAXS and CLMS can efficiently measure states of the full-length sequence in its native solution conformation and assembly. However, this experimental data did not substantially improve prediction accuracy judged by fits to crystallographic models. One issue, beyond intrinsic limitations of the algorithms, was a disconnect between crystal structures and solution-based measurements. Our analyses show that many targets had substantial percentages of disordered regions (up to 40%) or were multimeric or both. Thus, solution measurements of flexibility and assembly support variations that may confound prediction algorithms trained on crystallographic data and expecting globular fully-folded monomeric proteins. Here, we consider the CLMS and SAXS data collected, the information in these solution measurements, and the challenges in incorporating them into computational prediction. As improvement opportunities were only partly realized in CASP12, we provide guidance on how data from the full-length biological unit and the solution state can better aid prediction of the folded monomer or subunit. We furthermore describe strategic integrations of solution measurements with computational prediction programs with the aim of substantially improving foundational knowledge and the accuracy of computational algorithms for biologically-relevant structure predictions for proteins in solution. This article is protected by copyright. All rights reserved.
Cottrill, Anton L.; Wang, Song; Liu, Albert Tianxiang; Wang, Wen-Jun; Strano, Michael S.(Advanced Energy Materials, Wiley, 2018-01-15)[Article]
Thermal diodes are materials that allow for the preferential directional transport of heat and are highly promising devices for energy conservation, energy harvesting, and information processing applications. One form of a thermal diode consists of the junction between a phase change and phase invariant material, with rectification ratios that scale with the square root of the ratio of thermal conductivities of the two phases. In this work, the authors introduce and analyse the concept of a Dual Phase Change Thermal Diode (DPCTD) as the junction of two phase change materials with similar phase boundary temperatures but opposite temperature coefficients of thermal conductivity. Such systems possess a significantly enhanced optimal scaling of the rectification ratio as the square root of the product of the thermal conductivity ratios. Furthermore, the authors experimentally design and fabricate an ambient DPCTD enabled by the junction of an octadecane-impregnated polystyrene foam, polymerized using a high internal phase emulsion template (PFH-O) and a poly(N-isopropylacrylamide) (PNIPAM) aqueous solution. The DPCTD shows a significantly enhanced thermal rectification ratio both experimentally (2.6) and theoretically (2.6) as compared with ideal thermal diodes composed only of the constituent materials.
The best performing modern optoelectronic devices rely on single-crystalline thin-film (SC-TF) semiconductors grown epitaxially. The emerging halide perovskites, which can be synthesized via low-cost solution-based methods, have achieved substantial success in various optoelectronic devices including solar cells, lasers, light-emitting diodes, and photodetectors. However, to date, the performance of these perovskite devices based on polycrystalline thin-film active layers lags behind the epitaxially grown semiconductor devices. Here, a photodetector based on SC-TF perovskite active layer is reported with a record performance of a 50 million gain, 70 GHz gain-bandwidth product, and a 100-photon level detection limit at 180 Hz modulation bandwidth, which as far as we know are the highest values among all the reported perovskite photodetectors. The superior performance of the device originates from replacing polycrystalline thin film by a thickness-optimized SC-TF with much higher mobility and longer recombination time. The results indicate that high-performance perovskite devices based on SC-TF may become competitive in modern optoelectronics.
van der Voort, Pascal; De Canck, Els; Nahra, Fady; Bevernaege, Kevin; Vanden Broeck, Sofie; Ouwehand, Judith; Maes, Diederick; Nolan, Steven P.(ChemPhysChem, Wiley, 2017-11-08)[Article]
A stable Periodic Mesoporous Organosilica (PMO) with accessible sulfonic acid functionalities is prepared via a one-pot-synthesis and is used as solid support for highly active catalysts, consisting of gold(I)-N-heterocyclic carbene (NHC) complexes. The gold complexes are successfully immobilized on the nanoporous hybrid material via a straightforward acid-base reaction with the corresponding [Au(OH)(NHC)] synthon. This catalyst design strategy results in a boomerang-type catalyst, allowing the active species to detach from the surface to perform the catalysis and then to recombine with the solid after all the starting material is consumed. This boomerang behavior is assessed in the hydration of alkynes. The tested catalysts were found to be active in the latter reaction, and after an acidic work-up, the IPr*-based gold catalyst can be recovered and then reused several times without any loss in efficiency
Wang, Huixia Judy; McKeague, Ian W.; Qian, Min(Journal of the Royal Statistical Society: Series B (Statistical Methodology), Wiley, 2017-10-23)[Article]
The paper develops a new marginal testing procedure to detect significant predictors that are associated with the conditional quantiles of a scalar response. The idea is to fit the marginal quantile regression on each predictor one at a time, and then to base the test on the t-statistics that are associated with the most predictive predictors. A resampling method is devised to calibrate this test statistic, which has non-regular limiting behaviour due to the selection of the most predictive variables. Asymptotic validity of the procedure is established in a general quantile regression setting in which the marginal quantile regression models can be misspecified. Even though a fixed dimension is assumed to derive the asymptotic results, the test proposed is applicable and computationally feasible for large dimensional predictors. The method is more flexible than existing marginal screening test methods based on mean regression and has the added advantage of being robust against outliers in the response. The approach is illustrated by using an application to a human immunodeficiency virus drug resistance data set.
Staggering grid is a very effective way to reduce the Nyquist errors and to suppress the non-causal ringing artefacts in the pseudo-spectral solution of first-order elastic wave equations. However, the straightforward use of a staggered-grid pseudo-spectral method is problematic for simulating wave propagation when the anisotropy level is greater than orthorhombic or when the anisotropic symmetries are not aligned with the computational grids. Inspired by the idea of rotated staggered-grid finite-difference method, we propose a modified pseudo-spectral method for wave propagation in arbitrary anisotropic media. Compared with an existing remedy of staggered-grid pseudo-spectral method based on stiffness matrix decomposition and a possible alternative using the Lebedev grids, the rotated staggered-grid-based pseudo-spectral method possesses the best balance between the mitigation of artefacts and efficiency. A 2D example on a transversely isotropic model with tilted symmetry axis verifies its effectiveness to suppress the ringing artefacts. Two 3D examples of increasing anisotropy levels demonstrate that the rotated staggered-grid-based pseudo-spectral method can successfully simulate complex wavefields in such anisotropic formations.
Triboelectric nanogenerator (TENG) has been considered to be a more effective technology to harvest various types of mechanic vibration energies such as wind energy, water energy in the blue energy, and so on. Considering the vast energy from the blue oceans, harvesting of the water energy has attracted huge attention. There are two major types of “mechanical” water energy, water wave energy in random direction and water flow kinetic energy. However, although the most reported TENG can be used to efficiently harvest one type of water energy, to simultaneously collect two or more types of such energy still remains challenging. In this work, two different freestanding, multifunctional TENGs are successfully developed that can be used to harvest three types of energies including water waves, air flowing, and water flowing. These two new TENGs designed in accordance with the same freestanding model yield the output voltages of 490 and ≈100 V with short circuit currents of 24 and 2.7 µA, respectively, when operated at a rotation frequency of 200 rpm and the movement frequency of 3 Hz. Moreover, the developed multifunctional TENG can also be explored as a self-powered speed sensor of wind by correlating the short-circuit current with the wind speed.
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