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Optimal electron transfer with the catalyst through modulation of a graphene support with non-covalent adsorbents for achieving maximized activity and stability.

Three-dimensional (3D) nanoarchitectures have offered unprecedented material performances in diverse applications like energy storages, catalysts, electronic, mechanical, and photonic devices. These outstanding performances are attributed to unusual material properties at the nanoscale, enormous surface areas, a geometrical uniqueness, and comparable feature sizes with optical wavelengths. For the practical use of the unusual nanoscale properties, there have been developments for macroscale fabrications of the 3D nanoarchitectures with process areas over centimeter scales. Among the many fabrication methods for 3D structures at the nanoscale, proximity-field nanopatterning (PnP) is one of the promising techniques that generates 3D optical holographic images and transforms them into material structures through a lithographic process. Using conformal and transparent phase masks as a key factor, the PnP process has advantages in terms of stability, uniformity, and reproducibility for 3D nanostructures with periods from 300 nm to several micrometers. Other merits of realizing precise 3D features with sub-100 nm and rapid processes are attributed to the interference of coherent light diffracted by phase masks. In this review, to report the overall progress of PnP from 2003, we present a comprehensive understanding of PnP, including its brief history, the fundamental principles, symmetry control of 3D nanoarchitectures, material issues for the phase masks, and the process area expansion to the wafer-scale for the target applications. Finally, technical challenges and prospects are discussed for further development and practical applications of the PnP technique.

To date, researchers have shown that nanostructured solid solutions of transition metal electrocatalysts can improve hydrogen evolution reaction (HER) activity in alkaline media. However, there are few reports that focus on mass producing efficient electrocatalysts for the HER based on continuous 3-dimensional (3D) nanopatterning. Herein, a 3D-nanopatterned solid solution of Ni–Mo is synthesized to provide efficient electrocatalytic activity in alkaline electrolytes. Experimentally, it is found that the electrochemically active surface area (ECSA) is 65 times higher than that of 2D Ni–Mo. Additionally, the charge transfer resistance (Rct) of 3D Ni–Mo (0.6 Ω) is 16 times lower than that of 2D Ni–Mo (10.3 Ω), which shows that 3D Ni–Mo allows the fast transport of ions and facilitates the H* desorption process; thus, the above result contributes to the improved kinetics for HER activity. Moreover, the 3D-nanopatterned Ni–Mo electrocatalyst requires a minimum overpotential of 39 mV to achieve a 10 mA cm−2 current density, which is very close to that of the benchmark Pt/C electrocatalyst (30 mV) for the HER in alkaline media. In addition, the 3D-nanopatterned Ni–Mo electrocatalyst exhibits 94.7% faradaic efficiency during the HER. The as-prepared 3D-nanopatterned Ni–Mo is a free-standing electrocatalyst that can be synthesized at the inch scale or even larger and will be useful for practical applications in future renewable energy devices.

Increasing the specific capacity and cycle life of graphitic carbon anodes is crucial for realizing high-performance lithium ion batteries. Herein, we introduce a new class of graphitic carbon anodes comprising highly ordered three-dimensional nanostructures decorated with SnO2 nanoparticles. The inch-scale, nanostructured graphitic carbon matrices are prepared by supported pyrolysis of epoxy templates patterned by advanced optical lithography. During the subsequent decoration process, the SnO2 nanoparticles are densely formed on the matrix without agglomeration since the periodic nanostructured matrix provides a homogeneous site for nucleation and growth. The surface coverage of the decorated SnO2 nanoparticles and the mass relative to the graphitic carbon are >80% and ∼50 wt%, respectively. The resulting nanostructured C/SnO2 composite monoliths can be assembled solely into LIB coin cells without the aid of binders and conducting agents. The achieved specific capacity and retention are 692 mAh g−1 and 87.31% (at 70th cycle), respectively, which is superior to those of nanostructured carbon anodes prepared in a similar way.

Purpose The purpose of this paper is to examine how college students’ social media use affects their school e-mail avoidance and campus involvement. Design/methodology/approach The study employed face-to-face interviews and self-administered survey/quantitative data. Findings Communication and business students are more involved on campus and likely to use social media as the primary communication medium than other majors. Social media and text messages are not the culprits of school e-mail avoidance. University departments, student organizations, and faculty advisors’ e-mails are most likely to be avoided. Social media users can be categorized as either “instant communicators” or “online content curators.” Facebook is the only social media brand conducive to campus involvement. Research limitations/implications This study only used one university’s students as sample. In examining school e-mail avoidance, it only focused on the source of e-mail. The study is limited by its sole reliance on quantitative behavioral data. Practical implications University administrators and academic advisors need to reconsider the e-mail communication to students, target at the instant communicator social media users, and use Facebook to create a strong sense of community and campus involvement for their students. Marketers can utilize the two social media user groups in selecting social media in targeting to students. Originality/value The study offered empirical evidence to explain how social media affect students’ school e-mail avoidance and the role of campus media and specific social media outlet on campus involvement. It advances the knowledge of media choice of students and the social media user groups.

This study explored the factors that may influence the viewership of online in-stream video advertising on YouTube, based on viewing context, viewing device, advertising appeals, video characterist...

ZnO is a potential thermoelectric material because of its non-toxicity, high thermal stability, and relatively high Seebeck coefficient (S) of metal oxides. However, the extremely low figure of merit (zT), which comes from a high thermal conductivity (κ) over 40 W m-1 K-1, limits the thermoelectric application of ZnO. In particular, below 500 K, ZnO exhibits a nearly negligible zT (

Enhancing the filler-to-matrix contact area by incorporating large graphene flakes (GFs) is considered a viable approach for improving the mechanical properties of polymer composites. Graphene oxide (GO) flakes have been initially pursued for this application owing to the advantage of producing large-sized GFs. However, the defective nature of GO makes it technically challenging to precisely assess their dimensional effect on resulting mechanical properties, limiting their versatility as reinforcing materials. Therefore, it is highly desired to fabricate GFs with minimum defects and large lateral size. In this paper, we report the fabrication of high-quality edge functionalized non-oxidized graphene flakes (f-NOGFs) by the liquid exfoliation of graphite intercalation compounds. As-prepared f-NOGFs are over 1 μm in lateral size and contain less than 6.25% of impurity oxygen. By using size-sorted f-NOGFs, we systematically studied the relationship between mechanical properties and lateral sizes in f-NOGFs-incorporated epoxies. We identify that epoxy composites containing 0.6 wt% of f-NOGFs with a lateral size of 1 μm present outstanding mechanical properties; elastic modulus of 3.65 GPa, ultimate tensile strength of 95.74 GPa and toughness of 2.52 MJ m−3. The study presented in this paper could provide better understanding for optimization of the mechanical reinforcement of graphene-polymer composites.

This paper makes an attempt to call attention and point to the importance of Manchu historical records, but at the same time warns against the pitfalls of uncritical utilisation of these historical sources (the possibility of falsification and the fabrication of historical material). The authors focus on volume 20 of the 親征平定朔漠方略 Qinzhengpingdingshuo-mofanglue (Beye dailame wargi amargi babe necihiyeme toktobuha bodogon i bithe. orici debtelin) written in Manchu. This Manchu historical document is of prime importance in the historical enquiry of the period. It gives a clear picture of the military strategy of the time and provides accurate facts concerning the exact names of persons and places, the system of administration, wartime munitions mobilisation, and much more.

This article reviews the characteristics of terms used by the Mongols to express taboos concerning food and examines their food-related culture based on sources from the Mongolian Empire (Plano Carpini’s Historia Mongalorum, Marco Polo’s Il milione, Chinggis Khan’s Yeke Jasag, Rashīd ad-Dīn’s Jāmiʿ al-tawārīkh, and the Yuan Dynasty’s 飮食須知 Yin shi xu zhi). The Mongols left behind fairly strict food-related taboos in the form of eating habits. To better understand Mongolia’s food-related taboo expressions, we have examined five mediaeval sources written in various languages in which diverse food taboos are recorded.

Modelling of the force transmitted through vibration isolation elements in terms of the displacement and the velocity is very useful in transfer path or vibration power analysis of dynamic systems. Modelling using the complex stiffness in the frequency domain can be a good solution for linear elements, and force-state mapping can be a good solution for non-linear elements. In this study, it is noted that conventional force-state mapping with a linear part simply consisting of a linear spring and a viscous damper does not work sufficiently well for vibration isolation elements typically made of rubber materials; therefore, modelling of the linear part using the complex stiffness is proposed. The non-linear force-state model with the complex stiffness model for the linear part is applied to a set of simulation data for validation of the proposed approach and to another set of data measured from a cabin mount of an excavator for illustration. A form of the fractional polynomial function of the frequency is utilized for curve fitting of the linear complex stiffness in the frequency domain. The constraints for stability and causality on the coefficients and the order of this form are discussed. Procedures for the construction of the whole model are presented. Based on the modelling of the simulated and measured data, it is claimed that the suggested modelling is promising as a representation of the frequency- and amplitude-dependent complex stiffness of vibration isolation elements.

Various models of a seated human body have been developed in the literature so far based on measurements of apparent mass in the vertical Z -direction alone or fore-and-aft X -direction alone. As the authors observed that accelerations in both X and Z directions are equally significant in tests on an excavator working in a quarry, 3×3 apparent inertia matrix was experimentally obtained as functions of frequency by exciting the seated human body in the Z – X plane, i.e. providing two translational motions in the Z and X axes and one angular motion about the Y -axis. A subject in slightly slouched posture was sitting on a seat without backrest and the hands were on lap. Five resonances were found in the frequency range of interest, i.e. up to 20 Hz, below 1 Hz and at 3, 5.25, 8, 9.5 Hz, which is one more than four resonances found in previous researches. The resonance at 8 Hz was newly found in only pitch component of the apparent inertia matrix. Since the experiment was carried out only for one subject, it may not be guaranteed that the new resonance is generally applicable. A 5-degree-of-freedom (dof) model with 23 parameters is proposed for the description of the apparent inertia matrix of a seated human body. The 8 geometric parameters were included in the model in order to describe the couplings between coordinates. The model yielded the resonances at 0.61, 3.3, 5.1, 8.8 and 9.8 Hz, which are near to observations of the experiment. The parameters of the models may not necessarily represent the physical values of a human body because only the apparent inertia matrix at human body–seat interface was reflected. The model may not be perfect because the apparent inertia matrix was obtained from only one subject. Yet, the observations and the model in this research could be a guideline or reference in future researches to obtain more perfect models. Since the vibration responses in the Z – X plane at the human–seat interface can be predicted using the proposed 5-dof model, this model could be used for evaluation of a seat system by computer simulations from the aspect of ride comfort and health.

In general, three-dimensional ground reaction forces (GRFs) and ground reaction moments (GRMs) that occur during human gait are measured using a force plate, which are expensive and have spatial limitations. Therefore, we proposed a prediction model for GRFs and GRMs, which only uses plantar pressure information measured from insole pressure sensors with a wavelet neural network (WNN) and principal component analysis-mutual information (PCA-MI). For this, the prediction model estimated GRFs and GRMs with three different gait speeds (slow, normal, and fast groups) and healthy/pathological gait patterns (healthy and adolescent idiopathic scoliosis (AIS) groups). Model performance was validated using correlation coefficients (r) and the normalized root mean square error (NRMSE%) and was compared to the prediction accuracy of the previous methods using the same dataset. As a result, the performance of the GRF and GRM prediction model proposed in this study (slow group: r = 0.840–0.989 and NRMSE% = 10.693–15.894%; normal group: r = 0.847–0.988 and NRMSE% = 10.920–19.216%; fast group: r = 0.823–0.953 and NRMSE% = 12.009–20.182%; healthy group: r = 0.836–0.976 and NRMSE% = 12.920–18.088%; and AIS group: r = 0.917–0.993 and NRMSE% = 7.914–15.671%) was better than that of the prediction models suggested in previous studies for every group and component (p