A5062273115- Organic Electronics and Photovoltaics
- Machine Learning in Materials Science
- Advanced biosensing and bioanalysis techniques
- Various Chemistry Research Topics
- Block Copolymer Self-Assembly
- Advanced Polymer Synthesis and Characterization
- Green IT and Sustainability
- X-ray Diffraction in Crystallography
- Conducting polymers and applications
- Biosensors and Analytical Detection
- Crystallization and Solubility Studies
- Advanced Biosensing Techniques and Applications
- 3D Printing in Biomedical Research
- Analytical Chemistry and Chromatography
- Microfluidic and Capillary Electrophoresis Applications
- Computational Drug Discovery Methods
- Microfluidic and Bio-sensing Technologies
- Organic and Molecular Conductors Research
- Innovative Microfluidic and Catalytic Techniques Innovation
- Thermal properties of materials
- Organic Light-Emitting Diodes Research
- Perovskite Materials and Applications
University of Illinois Urbana-Champaign
2023-2025
Korea University
2020-2021
KIST Europe
2021
Korea Institute of Science and Technology
2021
Bottlebrush block copolymers (BBCPs), characterized by densely grafted side chains along their backbone, have emerged as promising materials for structural color applications. Their unique architecture prevents entanglement and facilitates rapid assembly kinetics, enabling the formation of various photonic crystals with high tunability from visible to infrared range. However, accessing non-1D structures has been largely limited synthetic approaches. In this paper, we report large modulation...
A ternary approach in organic photovoltaics (OPVs) is simple and reliable to effectively tune the optical, electrical, morphological properties of photoactive layer for high efficiency as well long-term stability under 1 sun. However, there have been few papers reporting benefits systems recycling energy indoor light, which has narrow emission spectra weak illumination compared outdoor light. In this study, by using two compatible donor polymers (PM7 PM7 D1) with slightly different band gaps...
Control of polymorphic behavior is crucial for designing functional organic semiconductor devices as even a slight structural difference may translate to dramatically different electronic properties. One route controlling structure through stimulus-induced polymorph transitions, which allows switching those However, despite advances in predicting crystal structures, the molecular design characteristics governing transition mechanism remains unknown. Here, we systematically investigate series...
AI-guided closed-loop experimentation has recently emerged as a promising method to optimize objective functions,1,2 but the substantial potential of this traditionally black-box approach reveal new scientific knowledge remained largely untapped. Here, we report approach, dubbed Closed-Loop Transfer (CLT), that integrates experiments with physics-based feature selection and supervised learning yield in parallel optimization functions. CLT surprisingly revealed high-energy regions triplet...
Technologies for the detection and isolation of circulating tumor cells (CTCs) are essential in liquid biopsy, a minimally invasive technique early diagnosis medical intervention cancer patients. A promising method CTC capture, using an affinity-based approach, is use functionalized hydrogel microparticles (MP), which have advantages water-like reactivity, biologically compatible materials, synergy with various analysis platforms. In this paper, we demonstrate feasibility capture by...
Encoded hydrogel microparticles synthesized via flow lithography have drawn attention for multiplex biomarker detection due to their high capability and solution-like hybridization kinetics. However, the current methods preparing particles cannot achieve a flexible, rapid probe-set modification, which is necessary production of various combinations target panels in clinical diagnosis. In order accomplish unmet needs, streptavidin was incorporated into encoded take advantage...
This paper presents a novel approach for predicting Power Conversion Efficiency (PCE) of Organic Photovoltaic (OPV) devices, called GLaD: synergizing molecular Graphs and Language Descriptors enhanced PCE prediction. Due to the lack high-quality experimental data, we collect dataset consisting 500 pairs OPV donor acceptor molecules along with their corresponding values, which utilize as training data our predictive model. In this low-data regime, GLaD leverages properties learned from large...