Heung Soo Kim

Bio: Heung Soo Kim is an academic researcher from Dongguk University. The author has contributed to research in topics: Composite laminates & Composite number. The author has an hindex of 46, co-authored 372 publications receiving 10036 citations. Previous affiliations of Heung Soo Kim include Catholic University of Daegu & Inha University.

Electrical, optical, and structural properties of indium–tin–oxide thin films for organic light-emitting devices

Abstract: High-quality indium–tin–oxide (ITO) thin films (200–850 nm) have been grown by pulsed laser deposition (PLD) on glass substrates without a postdeposition annealing treatment. The structural, electrical, and optical properties of these films have been investigated as a function of target composition, substrate deposition temperature, background gas pressure, and film thickness. Films were deposited from various target compositions ranging from 0 to 15 wt % of SnO2 content. The optimum target composition for high conductivity was 5 wt % SnO2+95 wt % In2O3. Films were deposited at substrate temperatures ranging from room temperature to 300 °C in O2 partial pressures ranging from 1 to 100 mTorr. Films were deposited using a KrF excimer laser (248 nm, 30 ns full width at half maximum) at a fluence of 2 J/cm2. For a 150-nm-thick ITO film grown at room temperature in an oxygen pressure of 10 mTorr, the resistivity was 4×10−4 Ω cm and the average transmission in the visible range (400–700 nm) was 85%. For a 170-n...

A Review of Piezoelectric Energy Harvesting Based on Vibration

Abstract: This paper reviews energy harvesting technology from mechanical vibration. Recent advances on ultralow power portable electronic devices and wireless sensor network require limitless battery life for better performance. People searched for permanent portable power sources for advanced electronic devices. Energy is everywhere around us and the most important part in energy harvesting is energy transducer. Piezoelectric materials have high energy conversion ability from mechanical vibration. A great amount of researches have been conducted to develop simple and efficient energy harvesting devices from vibration by using piezoelectric materials. Representative piezoelectric materials can be categorized into piezoceramics and piezopolymers. This paper reviews key ideas and performances of the reported piezoelectric energy harvesting from vibration. Various types of vibration devices, piezoelectric materials and mathematical modeling of vibrational energy harvestings are reviewed.

Transparent conducting aluminum-doped zinc oxide thin films for organic light-emitting devices

Abstract: Aluminum-doped zinc oxide (AZO) thin films (∼3000 A) with low electrical resistivity and high optical transparency have been grown by pulsed-laser deposition on glass substrates without a postdeposition anneal. Films were deposited at substrate temperatures ranging from room temperature to 400 °C in O2 partial pressures ranging from 0.1 to 50 mTorr. For 3000-A-thick AZO films grown at room temperature in an oxygen pressure of 5 mTorr, the electrical resistivity was 8.7×10−4 Ω cm and the average optical transmittance was 86% in the visible range (400–700 nm). For 3000-A-thick AZO films deposited at 200 °C in 5 mTorr of oxygen, the resistivity was 3.8×10−4 Ω cm and the average optical transmittance in the visible range was 91%. AZO films grown at 200 °C were used as an anode contact for organic light-emitting diodes. The external quantum efficiency measured from these devices was about 0.3% at a current density of 100 A/m2.

Review of nanocellulose for sustainable future materials

Abstract: Cellulose, the chain of glucose residues easily obtained from nature, is the most common natural polymer. Owing to its own unique material properties, compared to the conventional usage, nanocellulose (NC) with a crystalline structure can be considered to be used in various industrial applications. As a novel sustainable future material, we review the recent achievements of NC from the view point of material extraction and the composite processes to some extended important applications. While the mechanical properties of NCs and the energy consumption during their composite processing are the key considerations, their application potentials have never been limited to mechanical or commodity products as conventional celluloses. In the latter part of this review, emerging engineering applications of NCs such as energy storage, flexible electronics, and smart materials will be further discussed for readers searching future high-end eco-friendly functional materials. Also some suggestions for potential applications will be also discussed.

Molecular organic light-emitting diodes using highly conducting polymers as anodes

Abstract: Films fabricated from commercially available poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS) aqueous dispersions have been widely used in many electronic and optoelectronic applications. Previous attempts to utilize them as anodes in organic light-emitting diodes (OLEDs) were not satisfactory due to their low conductivity. In this letter we report on the fabrication and characterization of an OLED device made using a highly conductive form of PEDOT:PSS as anode and demonstrate its superior performance relative to that of a similar device using the commercial conducting polymer as an anode. An external electroluminescence quantum efficiency of ∼0.73% was measured at 100 A/m2.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

3D bioprinting of tissues and organs

Abstract: Additive manufacturing, otherwise known as three-dimensional (3D) printing, is driving major innovations in many areas, such as engineering, manufacturing, art, education and medicine. Recent advances have enabled 3D printing of biocompatible materials, cells and supporting components into complex 3D functional living tissues. 3D bioprinting is being applied to regenerative medicine to address the need for tissues and organs suitable for transplantation. Compared with non-biological printing, 3D bioprinting involves additional complexities, such as the choice of materials, cell types, growth and differentiation factors, and technical challenges related to the sensitivities of living cells and the construction of tissues. Addressing these complexities requires the integration of technologies from the fields of engineering, biomaterials science, cell biology, physics and medicine. 3D bioprinting has already been used for the generation and transplantation of several tissues, including multilayered skin, bone, vascular grafts, tracheal splints, heart tissue and cartilaginous structures. Other applications include developing high-throughput 3D-bioprinted tissue models for research, drug discovery and toxicology.

American Society for Testing and Materials

Abstract: The American Society for Testing and Materials (ASTM) is an independent organization devoted to the development of standards.

Transfer of large-area graphene films for high-performance transparent conductive electrodes

Abstract: Graphene, a two-dimensional monolayer of sp2-bonded carbon atoms, has been attracting great interest due to its unique transport properties. One of the promising applications of graphene is as a transparent conductive electrode owing to its high optical transmittance and conductivity. In this paper, we report on an improved transfer process of large-area graphene grown on Cu foils by chemical vapor deposition. The transferred graphene films have high electrical conductivity and high optical transmittance that make them suitable for transparent conductive electrode applications. The improved transfer processes will also be of great value for the fabrication of electronic devices such as field effect transistor and bilayer pseudospin field effect transistor devices.