A5066416766- Quantum Dots Synthesis And Properties
- Chalcogenide Semiconductor Thin Films
- Advanced Semiconductor Detectors and Materials
- Machine Learning in Materials Science
- X-ray Diffraction in Crystallography
- Semiconductor materials and interfaces
- Organic Light-Emitting Diodes Research
- Copper-based nanomaterials and applications
- Electronic and Structural Properties of Oxides
- Electron and X-Ray Spectroscopy Techniques
- Organic Electronics and Photovoltaics
- Molecular Junctions and Nanostructures
- Photocathodes and Microchannel Plates
- Luminescence Properties of Advanced Materials
- Thin-Film Transistor Technologies
- Force Microscopy Techniques and Applications
- Solid State Laser Technologies
- Aluminum Alloy Microstructure Properties
- ZnO doping and properties
- Radiation Detection and Scintillator Technologies
- Glass properties and applications
- Advanced Materials Characterization Techniques
- Semiconductor materials and devices
- Advanced Electron Microscopy Techniques and Applications
- Nuclear Physics and Applications
Samsung (South Korea)
2024
Seoul National University
2017-2021
Seoul Institute
2017-2018
Changwon National University
2001-2013
Oak Ridge National Laboratory
2007
Korea Atomic Energy Research Institute
2007
Massachusetts Institute of Technology
1996
Tohoku University
1995
A ruthenium polypyridyl complex has been synthesized and examined as an emitter material in thin film electroluminescent devices. This exhibits photoluminescent effects well several reversible one-electron oxidation reduction processes. Electroluminescent devices fabricated from this either via spin coating methods or self-assembly techniques exhibit relatively high efficiencies luminance levels some cases 100 cd/m2.
Abstract Semiconducting inorganic materials with band gaps ranging between 0 and 5 eV constitute major components in electronic, optoelectronic photovoltaic devices. Since the gap is a primary material property that affects device performance, large band-gap databases are useful selecting optimal each application. While there exist several theoretically compiled by density-functional-theory calculations, they suffer from computational limitations such as underestimation metastable magnetism....
Abstract The ultimate transparent electronic devices require complementary and symmetrical pairs of n-type p-type semiconductors. While several oxide semiconductors like InGaZnO ZnO are available being used in consumer electronics, there practically no oxides that comparable to the counterpart spite tremendous efforts discover them. Recently, high-throughput screening with density functional theory calculations attempted identify candidate oxides, but none suggested materials was verified...
The neural network interatomic potential (NNP) is anticipated to be a promising next-generation atomic for its self-learning capability and universal mathematical structure. While various examples demonstrate the usefulness of NNPs, we find that NNP suffers from highly inhomogeneous feature-space sampling in training set. As result, underrepresented configurations, often critical simulations, cause large errors even though they are included Using Gaussian density function (GDF) quantifies...
Using all-atom simulation of vapor deposition, we theoretically investigate how the molecular orientation depends on various factors such as substrate temperature, shape, and material composition.
Neural network potentials (NNPs) are gaining much attention as they enable fast molecular dynamics (MD) simulations for a wide range of systems while maintaining the accuracy density functional theory calculations. Since NNP is constructed by machine learning on training data, its prediction uncertainty increases drastically atomic environments deviate from points. Therefore, it essential to monitor level during MD judge soundness results. In this work, we propose an estimator based replica...
The universal mathematical form of machine-learning potentials (MLPs) shifts the core development interatomic to collecting proper training data. Ideally, set should encompass diverse local atomic environments but conventional approach is prone sampling similar configurations repeatedly, mainly due Boltzmann statistics. As such, practitioners handpick a large pool distinct manually, stretching period significantly. Herein, we suggest novel method optimized for gathering yet relevant...
We investigate the atomic energy mapping inferred by machine-learning potentials, in particular neural network potentials. first show that transferable can be defined within density functional theory, which means core of potentials is to deduce a reference atomic-energy function from given set total energies. By utilizing invariant points feature space at has fixed value, we examine Examples on Si consistently support NNPs are capable learning correct However, also find potential vulnerable...
The interfaces between amorphous organic layers play an important role in the efficiency and lifetime of light emitting diodes (OLEDs). However, atomistic understanding interface morphology is still poor. In this study, we theoretically investigate interfacial structure films using molecular dynamics simulations that mimic vapor-deposition processes. We find molecularly sharp are formed by process as thickness spans only a mono- or double-layer terms lie-down geometry. Interestingly, more...
Water-dispersible CdS quantum dots (QDs) were synthesized in a simple one-pot noninjection route. The X-ray diffraction (XRD) pattern of the nanoparticles shows cubic structure with particle size order 5-7 nm which was good agreement transmission electron microscopic (TEM) studies. Selected area (SAED) recognized CdS. energy dispersive X- ray spectroscopy (EDAX) analysis confirms presence Cd and S elements samples. optical properties are characterized by Ultraviolet-Visible (UV-Vis)...
Adsorption of PH3 onto Si(100) and hydrogen desorption therefrom at various adsorption temperatures Ta have been investigated by the temperature-programmed-desorption (TPD) method, which includes measurements on repeatedly adsorbed surfaces to obtain surface phosphorus coverage. The TPD peak showed a shift toward higher for above 400 °C, can be correlated onset resultant concentrated atoms during exposure. A support this correlation is given further analysis line shape, clarified that...
We report a novel OLED material discovery process and several applications based on AI technology. This in which six modules that generate molecular structures with active learning algorithm, predict multiple properties, analyze novelty, synthetic scheme, relative synthesizability device characteristics are linked one after another. Also, we introduce some cases materials designed by this were actually synthesized applied to devices for evaluation confirm the improvement of characteristics.