Hyunseung Yang

Covalently Interconnected Three- Dimensional Graphene Oxide Solids

The creation of three-dimensionally engineered nanoporous architectures via covalently interconnected nanoscale building blocks remains one of the fundamental challenges in nanotechnology. Here we report the synthesis of ordered, stacked macroscopic three-dimensional (3D) solid scaffolds of graphene oxide (GO) fabricated via chemical cross-linking of two-dimensional GO building blocks. The resulting 3D GO network solids form highly porous interconnected structures, and the controlled reduction of these structures leads to formation of 3D conductive graphene scaffolds. These 3D architectures show promise for potential applications such as gas storage; CO2 gas adsorption measurements carried out under ambient conditions show high sorption capacity, demonstrating the possibility of creating new functional carbon solids starting with two-dimensional carbon layers.

Efficient colorimetric pH sensor based on responsive polymer-quantum dot integrated graphene oxide.

In this paper, we report the development of a versatile platform for a highly efficient and stable graphene oxide (GO)-based optical sensor that exhibits distinctive ratiometric color responses. To demonstrate the applicability of the platform, we fabricated a colorimetric, GO-based pH sensor that responds to a wide range of pH changes. Our sensing system is based on responsive polymer and quantum dot (QD) hybrids integrated on a single GO sheet (MQD-GO), with the GO providing an excellent signal-to-noise ratio and high dispersion stability in water. The photoluminescence emissions of the blue and orange color-emitting QDs (BQDs and OQDs) in MQD-GO can be controlled independently by different pH-responsive linkers of poly(acrylic acid) (PAA) (pKa=4.5) and poly(2-vinylpyridine) (P2VP) (pKa=3.0) that can tune the efficiencies of Förster resonance energy transfer from the BQDs to the GO and from the OQDs to the GO, respectively. As a result, the color of MQD-GO changes from orange to near-white to blue over a wide range of pH values. The detailed mechanism of the pH-dependent response of the MQD-GO sensor was elucidated by measurements of time-resolved fluorescence and dynamic light scattering. Furthermore, the MQD-GO sensor showed excellent reversibility and high dispersion stability in pure water, indicating that our system is an ideal platform for biological and environmental applications. Our colorimetric GO-based optical sensor can be expanded easily to various other multifunctional, GO-based sensors by using alternate stimuli-responsive polymers.

Efficient temperature sensing platform based on fluorescent block copolymer-functionalized graphene oxide.

Efficient temperature-sensing platform was demonstrated using temperature-responsive, fluorescent P7AC-b-PNIPAM-b-PSN3 block copolymer-anchored graphene oxide sheets (FGO). FGO exhibited extraordinary stability in water and showed fast optical on-off switching behavior in response to temperature change.

Surface Engineering of Graphene Quantum Dots and Their Applications as Efficient Surfactants

The surface properties of graphene quantum dots (GQDs) control their dispersion and location within the matrices of organic molecules and polymers, thereby determining various properties of the hybrid materials. Herein, we developed a facile, one-step method for achieving systematic control of the surface properties of highly fluorescent GQDs. The surfaces of the as-synthesized hydrophilic GQDs were modified precisely depending on the number of grafted hydrophobic hexylamine. The geometry of the modified GQDs was envisioned by conducting simulations using density functional theory. In stark contrast to the pristine GQDs, the surface-modified GQDs can effectively stabilize oil-in-water Pickering emulsions and submicron-sized colloidal particles in mini-emulsion polymerization. These versatile GQD surfactants were also employed in liquid-solid systems; we demonstrated their use for tailoring the dispersion of graphite in methanol. Finally, the particles produced by the GQD surfactants were fluorescent due to luminescence of the GQDs, which offers great potential for various applications, including fluorescent sensors and imaging.

Anisotropically functionalized carbon nanotube array based hygroscopic scaffolds.

Creating ordered microstructures with hydrophobic and hydrophilic moieties that enable the collection and storage of small water droplets from the atmosphere, mimicking structures that exist in insects, such as the Stenocara beetle, which live in environments with limited amounts of water. Inspired by this approach, vertically aligned multiwalled carbon nanotube forests (NTFs) are asymmetrically end-functionalized to create hygroscopic scaffolds for water harvesting and storage from atmospheric air. One side of the NTF is made hydrophilic, which captures water from the atmosphere, and the other side is made superhydrophobic, which prevents water from escaping and the forest from collapsing. To understand how water penetrates into the NTF, the fundamentals of water/NTF surface interaction are discussed.

Efficient image understanding based on the Markov random field model and error backpropagation network

Image labeling is a process of recognizing each segmented region, properly exploiting the properties of the regions and the spatial relationships between regions. In some sense, image labeling is an optimization process of indexing regions using the constraints as to the scene knowledge. This paper further investigates a method of efficiently labeling images using the Markov random field (MRF). MRF model is defined on the region adjacency graph and the labeling is then optimally determined using simulated annealing. The MRF model parameters are automatically estimated using the error backpropagation network. The authors analyze the proposed method through experiments using the real natural scene images.<<ETX>>

Not all frames are equal: aggregating salient features for dynamic texture classification

Many recent studies have proposed methods for the classification of dynamic textures (DT). A method involving local binary patterns on three orthogonal planes (LBP-TOP) has shown promising results and generated considerable interest. However, LBP-TOP and most of its variants suffer from drawbacks caused by the accumulation process in the TOP technique. This process uses features from all frames in the DT sequence, including irrelevant frames, and thus disregards the distinct characteristics of each frame. To overcome this problem, we propose a codebook-based DT descriptor that aggregates salient features on three orthogonal planes. Given a DT sequence, only those frame features that are highly correlated with each cluster are selected and aggregated from the perspective of visual words. The proposed DT descriptor removes the feature from outlier frames that suddenly or rarely appear in a particular context, thus enhancing the emphasis of the salient features. Experimental results using public DT and dynamic scene datasets demonstrate the superiority of the proposed method over comparative approaches. The proposed method also yields outstanding results compared to the state-of-the-art DT representation.

Dynamic social formations of pedestrian groups navigating and using public transportation in a virtual city

Most prior crowd simulations do not have groups of people moving in a social manner. In our work, we use a two-level steering system based on two classes: group agent and pedestrian agent. By interpolating the current and desired slot positions of the group agent according to formation templates, dynamic social group formations can be achieved and can also adapt to the width of passageways using our robust and optimized ray casting technique. Based on this interpolation approach, slot-locking keeps subgroups in a group shoulder-to-shoulder regardless of the current formation assuming sufficient surrounding space exists. At times pal social gestures between adjacent members may occur. We also introduce the social FIFO queue to be used in situations such as waiting for the bus. In the subway scene, we describe a seating strategy for passengers entering the subway car and being aware of your presence. In an immersive evaluation using an Oculus DK2 head-mounted display, participants validated the realism of dynamic social group behavior for navigation and making use of public transportation.

Building an automated engagement recognizer based on video analysis

This paper presents a process to build a classifier in a data-driven way for recognizing engagement of children in a robot-based math quiz game. The process consists of collecting video recordings from HRI experiments; annotating the social signals and engagement states via video analysis; extracting feature vectors from the annotations and training classifiers. We conducted an experiment with 7 participants of

Design of an adaptive accelerometer-based handwriting recognition system based on metacognitive framework

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