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This study examined how HIP participation patterns differ among students in different Korean universities. Moreover, this study explored whether there is an association between the likelihood of a student belonging to a specific group and their individual characteristics along with their university’s supportive campus environment. This study analyzed the data from the 2019 wave of the Korean-NSSE (National Survey of Student Engagement), and the samples included 12,784 college seniors from 112 institutions. Furthermore, it employed latent profile analysis and multinomial logistic regression. As a result, this research identifies five distinctive HIP participation patterns. Family income and student-faculty interaction levels determine which group a student belongs to. For example, economically disadvantaged students tend to belong to a group with lower participation in study abroad programs. Finally, the supportive campus environment was strongly associated with being a member of actively participating groups compared to being in a less engaged group.

Cations with suitable sizes to occupy an interstitial site of perovskite crystals have been widely used to inhibit ion migration and promote the performance and stability of perovskite optoelectronics. However, such interstitial doping inevitably leads to lattice microstrain that impairs the long-range ordering and stability of the crystals, causing a sacrificial trade-off. Here, we unravel the evident influence of the valence states of the interstitial cations on their efficacy to suppress the ion migration. Incorporation of a trivalent neodymium cation (Nd3+) effectively mitigates the ion migration in the perovskite lattice with a reduced dosage (0.08%) compared to a widely used monovalent cation dopant (Na+, 0.45%). The photovoltaic performances and operational stability of the prototypical perovskite solar cells are enhanced with a trace amount of Nd3+ doping while minimizing the sacrificial trade-off.

The goal of this study was to develop a fuel-efficient driving strategy that evaluates upcoming longitudinal road grades under a self-driving mode. The fuel consumptions for different road terrains at varying speeds were analysed. The results revealed that 73·6% out of the 2000 road terrains examined showed minimum fuel consumption when using the suggested driving mode. The vehicle drove at a constant speed on the level plane, decelerated while climbing uphill and accelerated during downhill. A look-up table associating optimal speed variations with minimum fuel consumption was developed by analysing the relationships between speed variation, grade and speed. The suggested models showed decreases in fuel consumption of 20% and decreases in emissions of carbon dioxide, carbon monoxide, hydrocarbons and nitrogen oxides of 16·7%, 90·5%, 82·8% and 73·3%, respectively. The findings were applied to establish a driving strategy for the V2X (vehicle-to-everything) environment of connected automated vehicles.

Epitaxy technology produces high-quality material building blocks that underpin various fields of applications. However, fundamental limitations exist for conventional epitaxy, such as the lattice matching constraints that have greatly narrowed down the choices of available epitaxial material combinations. Recent emerging epitaxy techniques such as remote and van der Waals epitaxy have shown exciting perspectives to overcome these limitations and provide freestanding nanomembranes for massive novel applications. Here, we review the mechanism and fundamentals for van der Waals and remote epitaxy to produce freestanding nanomembranes. Key benefits that are exclusive to these two growth strategies are comprehensively summarized. A number of original applications have also been discussed, highlighting the advantages of these freestanding films-based designs. Finally, we discuss the current limitations with possible solutions and potential future directions towards nanomembranes-based advanced heterogeneous integration. Graphical Abstract

Bibliography: Entrich, Steve R./Bae, Sang Hoon: Extended Education at College and its Outcomes: An Introduction, IJREE – International Journal for Research on Extended Education, Vol. 8, Issue 2-2020, pp. 111-115. https://doi.org/10.3224/ijree.v8i2.02 ----- Open Access License: This contribution is available in Open Access under the Creative Commons license CC BY 4.0 (Attribution 4.0 International) as of 18.10.2021. More information about the license and the terms of use can be found here .

This research investigates a microwave transduction-based humidity sensor that is a promising candidate for real-time clinical healthcare applications and green miniaturized wearable electronic devices. Optimization of sensing material, sensing platform, and device fabrication techniques produces a carbon dots (CDs)-decorated metal organic framework (MOF)-derived porous Co3O4 (CDs-Co3O4) microwave resonator-based sensor with excellent real-time humidity detection. Inspired by the water absorption component polyacrylamide in baby diapers, the acrylamide is adopted to synthesize CDs for microwave humidity sensor. Combining CDs with MOF-derived porous Co3O4 enhances humidity sensitivity under microwave excitation, with a frequency shift of 3.40 MHz/% RH and a loss variation of 0.15 dB/% RH between 5% and 99% RH. These values are 49.7% (for frequency shift) and 20.5% (for return loss) higher than Co3O4 sensor. Moreover, CDs-Co3O4 exhibits high selectivity towards water vapor against other volatile organic compounds, and the response or recovery time are both less than 5 s. Fabricated by an integrated passive device technology, the sensing platform is miniaturized at 0.98 × 0.80 × 0.22 mm3 with superb device stability and reliability. The CDs-Co3O4 sensor remarkably monitors respiratory patterns of breathing or apnea, as well as subtle changes in the humidity levels of an approaching finger. A charge transfer process and microwave interactions are the mechanisms for improved humidity sensitivity.

The intersection management system can increase traffic capacity, vehicle safety, and the smoothness of all vehicle movement. Platoons of connected vehicles (CVs) use communication technologies to share information with each other and with infrastructures. In this paper, we proposed a deep reinforcement learning (DRL) model that applies to vehicle platooning at an isolated signalized intersection with partial detection. Moreover, we identified hyperparameters and tested the system with different numbers of vehicles (1, 2, and 3) in the platoon. To compare the effectiveness of the proposed model, we implemented two benchmark options, actuated traffic signal control (ATSC) and max pressure (MP). The experimental results demonstrated that the DRL model has many outstanding advantages compared to other models. Through the learning process, the average waiting time of vehicles in the DRL method was improved by 20% and 28% compared with the ATSC and MP options. The results also suggested that the DRL model is effective when the CV penetration rate is over 20%.

Automated driving systems have become a potential approach to mitigating collisions, emissions, and human errors in mixed-traffic environments. This study proposes the use of a deep reinforcement learning method to verify the effects of comprehensive automated vehicle movements at a non-signalized intersection according to training policy and measures of effectiveness. This method integrates multilayer perceptron and partially observable Markov decision process algorithms to generate a proper decision-making algorithm for automated vehicles. This study also evaluates the efficiency of proximal policy optimization hyperparameters for the performance of the training process. Firstly, we set initial parameters and create simulation scenarios. Secondly, the SUMO simulator executes and exports observations. Thirdly, the Flow tool transfers these observations into the states of reinforcement learning agents. Next, the multilayer perceptron algorithm trains the input data and updates policies to generate the proper actions. Finally, this training checks the termination and iteration process. These proposed experiments not only increase the speeds of vehicles but also decrease the emissions at a higher market penetration rate and a lower traffic volume. We demonstrate that the fully autonomous condition increased the average speed 1.49 times compared to the entirely human-driven experiment.

Recent advances in flexible and stretchable electronics have led to a surge of electronic skin (e-skin)–based health monitoring platforms. Conventional wireless e-skins rely on rigid integrated circuit chips that compromise the overall flexibility and consume considerable power. Chip-less wireless e-skins based on inductor-capacitor resonators are limited to mechanical sensors with low sensitivities. We report a chip-less wireless e-skin based on surface acoustic wave sensors made of freestanding ultrathin single-crystalline piezoelectric gallium nitride membranes. Surface acoustic wave–based e-skin offers highly sensitive, low-power, and long-term sensing of strain, ultraviolet light, and ion concentrations in sweat. We demonstrate weeklong monitoring of pulse. These results present routes to inexpensive and versatile low-power, high-sensitivity platforms for wireless health monitoring devices.

Remote epitaxy has drawn attention as it offers epitaxy of functional materials that can be released from the substrates with atomic precision, thus enabling production and heterointegration of flexible, transferrable, and stackable freestanding single-crystalline membranes. In addition, the remote interaction of atoms and adatoms through two-dimensional (2D) materials in remote epitaxy allows investigation and utilization of electrical/chemical/physical coupling of bulk (3D) materials via 2D materials (3D-2D-3D coupling). Here, we unveil the respective roles and impacts of the substrate material, graphene, substrate-graphene interface, and epitaxial material for electrostatic coupling of these materials, which governs cohesive ordering and can lead to single-crystal epitaxy in the overlying film. We show that simply coating a graphene layer on wafers does not guarantee successful implementation of remote epitaxy, since atomically precise control of the graphene-coated interface is required, and provides key considerations for maximizing the remote electrostatic interaction between the substrate and adatoms. This was enabled by exploring various material systems and processing conditions, and we demonstrate that the rules of remote epitaxy vary significantly depending on the ionicity of material systems as well as the graphene-substrate interface and the epitaxy environment. The general rule of thumb discovered here enables expanding 3D material libraries that can be stacked in freestanding form.

Self-driving safety is one of the major concerns raised with regard to pushing the use of automated vehicles on roads. Fully automated vehicles are forced to make appropriate decisions in an uncertain environment where driverless and human-driven vehicles share the road together. This study proposes a new model that can be used to enhance the autonomous driving behavior at a non-signalized intersection considering the traffic safety guarantee, delay time, and smooth driving. The proposed model is called the responsibility-sensitive safety-based partially observable Markov decision process model for the decision-making mechanism of automated vehicles. The model not only increases traffic safety guarantee and smooth driving, but also reduces the delay time. First, we generate some specific driving scenarios using the automated driving toolbox in MATLAB. Second, the driving strategy of automated vehicles is optimized by the partially observable Markov decision process framework using the adaptive cruise control system. Finally, the responsibility-sensitive safety algorithm is implemented under adaptive model predictive control. The proposed model performs better than the classical adaptive model predictive control. In the best case, the proposed model took a 31.60 % reduction in braking time and a 51.20 % improvement in smoothing speed control.

Understanding lattice deformations is crucial in determining the properties of nanomaterials, which can become more prominent in future applications ranging from energy harvesting to electronic devices. However, it remains challenging to reveal unexpected deformations that crucially affect material properties across a large sample area. Here, we demonstrate a rapid and semi-automated unsupervised machine learning approach to uncover lattice deformations in materials. Our method utilizes divisive hierarchical clustering to automatically unveil multi-scale deformations in the entire sample flake from the diffraction data using four-dimensional scanning transmission electron microscopy (4D-STEM). Our approach overcomes the current barriers of large 4D data analysis without a priori knowledge of the sample. Using this purely data-driven analysis, we have uncovered different types of material deformations, such as strain, lattice distortion, bending contour, etc., which can significantly impact the band structure and subsequent performance of nanomaterials-based devices. We envision that this data-driven procedure will provide insight into materials’ intrinsic structures and accelerate the discovery of materials.

Two-dimensional transition metal dichalcogenide nanoribbons are touted as the future extreme device downscaling for advanced logic and memory devices but remain a formidable synthetic challenge. Here, we demonstrate a ledge-directed epitaxy (LDE) of dense arrays of continuous, self-aligned, monolayer and single-crystalline MoS2 nanoribbons on β-gallium (iii) oxide (β-Ga2O3) (100) substrates. LDE MoS2 nanoribbons have spatial uniformity over a long range and transport characteristics on par with those seen in exfoliated benchmarks. Prototype MoS2-nanoribbon-based field-effect transistors exhibit high on/off ratios of 108 and an averaged room temperature electron mobility of 65 cm2 V−1 s−1. The MoS2 nanoribbons can be readily transferred to arbitrary substrates while the underlying β-Ga2O3 can be reused after mechanical exfoliation. We further demonstrate LDE as a versatile epitaxy platform for the growth of p-type WSe2 nanoribbons and lateral heterostructures made of p-WSe2 and n-MoS2 nanoribbons for futuristic electronics applications. Aligned arrays of single-crystalline monolayer TMD nanoribbons with high aspect ratios, as well as their lateral heterostructures, are realized, with the growth directed by the ledges on the β-Ga2O3 substrate. This approach provides an epitaxy platform for advanced electronics applications of TMD nanoribbons.

This study examined a comprehensive model including transformational leadership, individual- and organisational-level knowledge assets (i.e., work engagement and a supportive learning culture), and...

Extract ----- Abstract This study identified subgroups of elementary students based on similar patterns of participation in four different types of extended education in Korea. The study also investigated relationships between student patterns of extended education participation and their various demographic and socioeconomic characteristics, including residential location, parental education, and family income level. To achieve these aims, the study used latent profile analysis and logistic regression on a dataset of 18,186 students from 786 elementary schools provided by Statistics Korea. Results reveal five distinctive subgroups of students in terms of extended education participation: afterschool academic program users, shadow education users, moderate afterschool academic program users, ordinary users, and talent development seekers. Results also show that student socioeconomic and demographic characteristics are strongly associated with their classification into the above-mentioned subgroups. These findings signal the possibility that “educational stratification” based on student socioeconomic background may be occurring in the area of extended education. Keywords: extended education, participation, stratification, educational equality ----- Bibliography: Bae, Sang Hoon/Cho, Eunwon/Byun, Bo-Kyung: Stratification in Extended Education Participation and its Implications for Education Inequality, IJREE – International Journal for Research on Extended Education, Vol. 7, Issue 2-2019, pp. 160-177. https://doi.org/10.3224/ijree.v7i2.05

Although conventional homoepitaxy forms high-quality epitaxial layers1-5, the limited set of material systems for commercially available wafers restricts the range of materials that can be grown homoepitaxially. At the same time, conventional heteroepitaxy of lattice-mismatched systems produces dislocations above a critical strain energy to release the accumulated strain energy as the film thickness increases. The formation of dislocations, which severely degrade electronic/photonic device performances6-8, is fundamentally unavoidable in highly lattice-mismatched epitaxy9-11. Here, we introduce a unique mechanism of relaxing misfit strain in heteroepitaxial films that can enable effective lattice engineering. We have observed that heteroepitaxy on graphene-coated substrates allows for spontaneous relaxation of misfit strain owing to the slippery graphene surface while achieving single-crystalline films by reading the atomic potential from the substrate. This spontaneous relaxation technique could transform the monolithic integration of largely lattice-mismatched systems by covering a wide range of the misfit spectrum to enhance and broaden the functionality of semiconductor devices for advanced electronics and photonics.

Complex-oxide materials exhibit a vast range of functional properties desirable for next-generation electronic, spintronic, magnetoelectric, neuromorphic, and energy conversion storage devices1-4. Their physical functionalities can be coupled by stacking layers of such materials to create heterostructures and can be further boosted by applying strain5-7. The predominant method for heterogeneous integration and application of strain has been through heteroepitaxy, which drastically limits the possible material combinations and the ability to integrate complex oxides with mature semiconductor technologies. Moreover, key physical properties of complex-oxide thin films, such as piezoelectricity and magnetostriction, are severely reduced by the substrate clamping effect. Here we demonstrate a universal mechanical exfoliation method of producing freestanding single-crystalline membranes made from a wide range of complex-oxide materials including perovskite, spinel and garnet crystal structures with varying crystallographic orientations. In addition, we create artificial heterostructures and hybridize their physical properties by directly stacking such freestanding membranes with different crystal structures and orientations, which is not possible using conventional methods. Our results establish a platform for stacking and coupling three-dimensional structures, akin to two-dimensional material-based heterostructures, for enhancing device functionalities8,9.

Heterogeneous integration of single-crystal materials offers great opportunities for advanced device platforms and functional systems

Cations with suitable sizes to occupy an interstitial site of perovskite crystals have been widely used to inhibit ion migration and promote performance and stability of perovskite optoelectronics. However, the interstitial doping accompanies inevitable lattice strain to impair long-range ordering and stability of the crystals to cause a sacrificial trade-off. Here, we unravel the evident influence of the valence states of the interstitial cations on their efficacy to suppress the ion migration. Incorporation of a trivalent neodymium cation (Nd3+) effectively mitigates the ion migration in the perovskite lattice with significantly reduced dosage (0.08%) compared to a widely used monovalent cation dopant (Na+, 0.45%). Less but better, the prototypical perovskite solar cells incorporated with Nd3+ exhibits significantly enhanced photovoltaic performance and operational stability.