# SAIL: Spectroscopy and AI Lab (Joonyoung F. Joung Lab, Kookmin University), full content

> SAIL, the Spectroscopy and AI Lab at Kookmin University led by Joonyoung F. Joung: machine learning for molecular properties, reactions, design, and databases.

The Spectroscopy and AI Lab (SAIL), led by Joonyoung F. Joung (정준영), Assistant Professor in the Department of Chemistry at Kookmin University, integrates machine learning with chemistry. Website: https://sail.kookmin.ac.kr. This file is the expanded, full-text companion to https://sail.kookmin.ac.kr/llms.txt.

Other names: Joonyoung F. Joung Lab; 인공지능화학연구실. Kookmin University in Korean: 국민대학교. GitHub: https://github.com/sailgroup

In Korean, in the lab's own words: 국민대학교 화학부 SAIL 연구실(Spectroscopy and AI Lab)은 인공지능과 화학을 융합하여 화학 반응 예측과 신소재 개발을 연구합니다.

## Research areas
### Prediction of Physicochemical Properties
We leverage machine learning models and quantum chemical calculations (e.g., DFT) to predict critical physicochemical properties of molecules, such as optical properties, energy levels, and solubility. These predictions not only aid in discovering desired materials or pharmaceuticals but also support the optimization of separation processes by providing insights into solubility behavior.

In Korean (물리화학적 특성 예측): 머신러닝 모델과 양자화학 계산(예: DFT)을 활용하여 분자의 광학적 특성, 분자의 에너지 준위나 용해도와 같은 물리화학적 특성을 예측합니다. 이러한 예측은 신소재나 약물을 개발하는 데 도움을 줄 뿐만 아니라, 용해도에 대한 통찰을 제공함으로써 분리 공정의 최적화에도 기여할 수 있습니다.
### Chemical Reaction Prediction
Chemical reaction prediction has traditionally relied on expert knowledge and reaction rules, making it difficult to anticipate unexpected byproducts or impurities. We develop models that predict products either in an end-to-end manner or by learning mechanistic pathways. This helps to explain impurity formation and ultimately discover novel reactions.

In Korean (화학 반응 예측): 화학 반응 예측은 지금까지 화학자의 경험에 의존해 왔으며, 예기치 못한 생성물이나 불순물은 반복 실험으로 확인해 왔습니다. 본 연구실은 머신러닝 기반 예측 모델을 통해 반응물로부터 생성물을 직접 예측하거나, 메커니즘 수준에서 반응 경로를 학습하도록 하여 불순물 형성 원인을 설명하고 새로운 반응 발견으로 확장하는 것을 목표로 합니다.
### De Novo Molecular Design
Traditional approaches to molecular design rely heavily on trial-and-error experimentation, even when the desired properties are known. At SAIL, we develop machine learning-based de novo design techniques that generate candidate molecules expected to exhibit target properties. This accelerates material discovery while reducing cost and effort. In addition to generative modeling, we leverage quantum chemical methods such as DFT to understand how molecular structure determines properties. This allows us to extract design principles grounded in theory and propose new molecular structures with improved performance.

In Korean (De Novo 분자 설계): 기존의 분자 설계는 원하는 특성을 만족하는 분자를 직접 설계하기 어려워 반복 실험에 의존해 왔습니다. 본 연구실은 머신러닝을 활용해 목표 특성을 만족할 수 있는 분자 구조를 자동으로 생성하는 de novo 설계 모델을 개발하여, 후보 물질 탐색의 효율을 극대화합니다. 또한, 단순한 생성 모델을 넘어서 DFT 등 양자화학계산 방법을 통해 분자의 구조가 특성에 미치는 영향을 분석하고, 이론적으로 정립된 설계 원리를 도출함으로써 새로운 구조를 제안할 수 있는 기반을 마련하고 있습니다.
### Database Development
Reliable AI models require high-quality data. We build structured databases by extracting information from experiments and literature, and use these data for training and benchmarking models.

In Korean (데이터베이스 구축): 인공지능 연구를 위한 고품질 데이터는 필수적입니다. 본 연구실은 화학 실험 및 문헌에서 화학 정보를 수집·정리하여 데이터베이스를 구축하고, 이를 통해 모델 학습과 새로운 소재 발견의 기반을 마련합니다.

## Publications (47, newest first)
### [47] Encoding Composition-Dependent Intermolecular Interactions into Learned Molecular Representations
Authors: Jihwan Kim, Chanjoong Kim, Joonyoung F. Joung
Venue: Chem. Eng. J., accepted (2026)
Code: https://github.com/sailgroup/MEMo
Page: https://sail.kookmin.ac.kr/publications/47/
Topics: Molecular property prediction, Representation learning, Experimental dataset

### [46] Wavenumber-Aware Deep Learning for Robust Analysis of Raman Spectra
Authors: Jihwan Kim, Jaeseong Heo, Yujin Kim, Sang Bin Yoon, Chanjoong Kim, Kwang-Im Oh, Hyon Bin Na, Kyungwon Kwak, Myeongkee Park, Joonyoung F. Joung
Venue: Submitted (2026)
Preprint: https://doi.org/10.48550/arXiv.2610.30746
Code: https://github.com/sailgroup/Wavenumber-Aware-Deep-Learning/
Page: https://sail.kookmin.ac.kr/publications/46/
Topics: Spectroscopic analysis, Representation learning, Experimental dataset
Abstract: Machine-learning models for spectroscopy usually treat a spectrum as a fixed-grid intensity vector, leaving the physical coordinate implicit in the array index. Such models are tied to a single sampling grid, spectral range and resolution, which limits their use when measurement conditions change. Here we represent each spectral point as a pair of intensity and wavenumber and compute Transformer positional encodings from the wavenumber itself. On Raman spectra of three bacterial species and their synthetic mixtures, this representation remained robust to noise, sparser sampling and partial spectral coverage across convolutional, residual and Transformer networks. In controlled comparisons, wavenumber-based encoding outperformed index-based and learned encodings under partial observation and retained its performance on sampling grids never seen during training, where index-based encoding degraded. These findings were reproduced on a public 30-isolate bacterial benchmark. Explicit physical coordinates offer a simple route to robust spectral analysis under variable measurement conditions.

### [45] Synergistic Ligand and Composition Control for Bright and Stable CsPbBr3/Cs4PbBr6 Core/Shell Colloidal Perovskite Nanocrystals
Authors: Jae Woo Kim, Jigeon Kim, Jihwan Kim, Huieun Kim, Haereum Jo, Wonjong Lee, Jongchul Lim, Joonyoung F. Joung, Younghoon Kim
Venue: J. Alloys Compd., 1080, 190954 (2026)
DOI: https://doi.org/10.1016/j.jallcom.2026.190954
Page: https://sail.kookmin.ac.kr/publications/45/
Topics: Molecular property prediction
Abstract: Lead halide colloidal perovskite nanocrystals (CPNCs) have emerged as promising candidates for next-generation optoelectronics owing to their outstanding optical properties; however, their intrinsic instability against environmental stimuli remains a critical bottleneck. Herein, we report the synthesis of highly stable, colloidally dispersible CsPbBr3/Cs4PbBr6 single core/single shell CPNCs via a synergistic approach that combines an oleylamine-driven surface phase transition with a controlled Cs-rich environment. To overcome the sensitivity of the core/shell formation to interdependent synthesis parameters, we employ a machine-learning-assisted workflow. A random forest classifier is utilized to identify the optimal synthesis window with a prediction accuracy of 97.3%, enabling the precise regulation of shell growth. The resulting core/shell CPNCs exhibit a uniform rhombohedral morphology and maintain a Type-I band alignment, which preserves the excellent optical properties of the CsPbBr3 CPNC core while confining charge carriers for efficient radiative recombination. Furthermore, the Cs4PbBr6 shell acts as a robust barrier, providing superior stability against harsh conditions, including exposure to polar solvents (acetone), high temperature (85 °C), and high humidity (85% RH). These CsPbBr3/Cs4PbBr6 core/shell CPNCs retain high colloidal dispersibility, offering a solution-processable material for robust perovskite-based optoelectronic devices.

### [44] Prediction of experimental excited-state absorption spectra by using vibronic transition calculations: Its practical application to a π-conjugated molecule
Authors: Joonyoung F. Joung, Sungnam Park
Venue: Bull. Korean Chem. Soc., 47 (10), 1248-1256 (2026)
DOI: https://doi.org/10.1002/bkcs.70213
Preprint: https://doi.org/10.48550/arXiv.2607.25247
Page: https://sail.kookmin.ac.kr/publications/44/
Topics: Spectroscopic analysis, Quantum chemical modeling
Abstract: Accurate theoretical prediction of excited-state absorption (ESA) spectra remains challenging. Although considerable progress has been made in computational methods for ESA spectroscopy, their practical application to the interpretation of transient absorption and photoinduced absorption spectra is still limited. In this study, we present a practical approach for calculating molecular ESA spectra by combining vibronic transition calculations with routine density functional theory (DFT) and time-dependent DFT (TDDFT) calculations available in standard quantum chemistry packages. Using azulene as a model system, we demonstrate that the proposed method successfully reproduces the vibronic features and band positions observed in the experimental ESA spectrum. This approach therefore provides a practical framework for assigning ESA bands arising from transitions between low-lying excited states of molecules. The method delivers the vibronic band shapes and peak positions that are needed to assign ESA bands directly from these standard calculations, without requiring the excited-state-to-excited-state transition moments that determine absolute intensities.

### [43] Continuous Light-Driven Pure CO2 Production by Regenerative Non-Aqueous Amine–Photoacid Cycling
Authors: Gi Hyun Byun, Nayeong Kim, Joonyoung F. Joung, Michael Massen-Hane, Betar M. Gallant, Hyowon Seo, T. Alan Hatton
Venue: ChemRxiv, Preprint (2026)
Preprint: https://doi.org/10.26434/chemrxiv.15005144/v1
Page: https://sail.kookmin.ac.kr/publications/43/
Topics: Quantum chemical modeling
Abstract: Photochemical CO2 separation offers a low-temperature alternative to conventional thermal CO2 separation, replacing fuel-derived heat with light as the energy input. Although prior photoacid and photobase systems have shown promising light-driven CO2 capture–release behavior, continuous pure-CO2 generation from dilute feeds remains insufficiently developed. Here, we demonstrate light-driven pure-CO2 production from a 15% CO2 feed, reaching 3.2 sccm from 1.2 mL min−1 of circulating sorbent solution in a single lab-scale reactor, equivalent to 4.6 L day−1. In the dimethyl sulfoxide amine–photoacid platform, acidity matching allows each photoacid molecule to undergo repeated excited-state proton transfer, coupling carbamic acidforming CO2 capture to efficient release. The evolved CO2 forms self-generated bubbles without external sweep gas in the reduced-pressure continuous flow photoreactor developed in this work. Techno-economic analysis projects a minimum separation cost of $31.7 tCO2 −1 from 15% CO2 source. These results establish a practical foundation for scalable light-driven carbon capture.

### [42] Precursor Diffusion-Controlled Scalable Synthesis of Monodisperse Iodide Perovskite Quantum Dots for Photovoltaics
Authors: Jaehyuk Kim, Sanghun Han, Jigeon Kim, Hye Min Kim, Seongwon Lee, Dong Gyu Lee, Gayoung Seo, Hyeon Soo Ma, Joonyoung F. Joung, Tae Kyung Lee, Hyung Min Kim, Jongmin Choi, Younghoon Kim
Venue: ACS Energy Lett., 11 (8), 5817-5828 (2026)
DOI: https://doi.org/10.1021/acsenergylett.6c01560
Page: https://sail.kookmin.ac.kr/publications/42/
Topics: Quantum chemical modeling
Abstract: Monodisperse iodide-based perovskite colloidal quantum dots (Pe-CQDs) are attractive for photovoltaics, but scaling-up their synthesis is challenging. Because precursor conversion, nucleation, and crystal growth occur almost simultaneously during rapid ionic crystallization, large-scale production typically suffers from local concentration variations that broaden the size distribution. To address this, we report a gram-scale synthesis strategy that separates the crystallization stages through controlled precursor diffusion. Ligand-mediated regulation delays monomer formation and suppresses continuous nucleation, yielding uniform CsPbI3-Pe-CQDs without post-synthetic size selection. This diffusion-control strategy successfully extends to formamidinium (FA) incorporation, enabling the direct synthesis of composition-tunable CsxFA1–xPbI3-Pe-CQDs while bypassing conventional cation exchange. The resulting monodisperse Pe-CQDs enable the fabrication of solar cells with a power conversion efficiency of 16.7%, while maintaining a robust efficiency of over 15% even with gram-scale batches. This approach demonstrates a reliable and scalable strategy for manufacturing device-grade CQD photovoltaics without sacrificing device-relevant properties upon scale-up.

### [41] An overview of reaction outcome prediction with physics-based and data-driven methods
Authors: Joonyoung F. Joung, Nicholas Casetti, Priyanka Raghavan, Connor W. Coley
Venue: Chem. Soc. Rev., 55 (12), 6768-6813 (2026)
DOI: https://doi.org/10.1039/D6CS00079G
Page: https://sail.kookmin.ac.kr/publications/41/
Topics: Reaction pathway prediction, Molecular property prediction, Quantum chemical modeling, Experimental dataset
Abstract: The prediction of reaction outcomes is a longstanding challenge in chemistry, with the ability to do so serving as a direct reflection of our understanding of chemical reactivity. Accurately predicting reaction products is crucial not only for synthetic planning but also for designing reaction pathways and experiments in silico. This review explores the diverse methodologies used to predict reaction outcomes, which can be broadly divided into two main categories. Some approaches predict reaction products and their likelihoods in a single step, while others break the task into two distinct parts: candidate enumeration and the subsequent prediction of product likelihoods. We examine both data-driven methods, such as graph-based and sequence-generation models, and physics-based methods, including potential energy surface exploration and reactive molecular dynamics. In addition, we discuss quantitative predictions of reaction selectivity, regioselectivity, stereoselectivity, and yield. This review summarizes trends and advances in reaction outcome prediction and briefly outlines future directions for the field.

### [40] Defining Chemical Problems for Artificial Intelligence Models
Authors: Joonyoung F. Joung
Venue: Bull. Korean Chem. Soc., 47 (3), 317-327 (2026)
DOI: https://doi.org/10.1002/bkcs.70113
Page: https://sail.kookmin.ac.kr/publications/40/
Topics: Molecular property prediction, Reaction pathway prediction, Experimental dataset
Abstract: Artificial intelligence has become an increasingly important tool in chemistry, yet its impact is often constrained by how chemical problems are defined for machine learning. In this Personal Account, I argue that dataset construction plays a central role in AI-driven chemistry, not merely as a preparatory step but as a means of formalizing new chemical learning problems. I summarize recent efforts to build machine-learning-ready datasets in three domains: molecular property prediction, property-conditioned molecular design, and reaction mechanism prediction. Experimentally measured optical property datasets were curated to explicitly incorporate environmental context, enabling models to learn structure-environment-property relationships that reflect real experimental conditions and to support inverse design of functional chromophores. For chemical reactivity, large-scale mechanistic datasets were constructed through rule-based imputation of elementary steps, transforming overall reactions into supervised learning problems for mechanism prediction. Limitations of sequence-based reaction models motivated the development of FlowER, which represents reactions as electron redistribution processes using bond-electron matrices and enforces mass conservation by construction, allowing direct integration with quantum chemical validation. Together, these studies illustrate a unifying perspective in which datasets, representations, models, and downstream workflows are designed jointly, guided by chemical intuition. By framing dataset construction as an act of problem definition, this Account highlights how chemists can shape the scope and direction of artificial intelligence as a tool for chemical discovery.

### [39] Higher-level Strategies for Computer-Aided Retrosynthesis
Authors: Jihye Roh, Joonyoung F. Joung, Kevin Yu, Zhengkai Tu, G. Logan Bartholomew, Omar A. Santiago-Reyes, Mun Hong Fong, Richmond Sarpong, Sarah E. Reisman, Connor W. Coley
Venue: ACS Cent. Sci., 12 (3), 345-357 (2026)
DOI: https://doi.org/10.1021/acscentsci.5c02014
Preprint: https://doi.org/10.26434/chemrxiv-2025-21zvt
Page: https://sail.kookmin.ac.kr/publications/39/
Topics: Reaction pathway prediction
Abstract: Retrosynthesis is a core technique in organic chemistry that simplifies target molecules into more readily available components. Computer-aided synthesis planning (CASP) automates this process by recursively proposing immediate precursors to identify multistep synthetic pathways. However, CASP typically struggles for complex molecules that require longer synthetic pathways and present a greater number of possible disconnections. Here, we introduce a new higher-level framework for computer-aided retrosynthesis. Our approach abstracts detailed substructures in pathway intermediates not appearing in the target product, allowing the algorithm to emphasize higher-level strategies while postponing the consideration of specific functional group choices, thus reducing the effective width and depth of the search space. This framework achieves higher top-k accuracy in single-step retrosynthesis and identifies multistep routes for more targets than the original approach. Through case studies on complex drugs and natural products, we demonstrate how routes proposed by our framework provide a powerful basis for developing full synthesis plans, particularly in challenging cases where the original approach fails, while enabling chemists to leverage their expertise to refine the synthesis design. Ultimately, focusing on higher-level strategies enables an effective and intuitive approach for challenging targets in computer-aided retrosynthesis.

### [38] Exploring Materials Data through Collaboration: 2024 KRICT ChemDX Hackathon
Authors: Su-Hyun Yoo, Andre K. Y. Low, Jose Recatala-Gomez, Harikrishna Sahu, Chiho Kim, Joonyoung F. Joung, Hoje Chun, Katerina A. Christofidou, Joshua Berry, Michail Minotakis, Kisung Kang, Kwang-soo Kim, Gaheun Shin, Hyunwoo Jang, Sanghyuk Lee, Minkyu Park, Byung-Hyun Kim, Kihyun Shin, Jungho Shin, Aloysius Soon, Joshua Schrier, Woosun Jang
Venue: J. Mater. Inf., 5 (4), 54 (2025)
DOI: https://doi.org/10.20517/jmi.2025.65
Code: https://github.com/jfjoung/KRICT_Hackathon
Page: https://sail.kookmin.ac.kr/publications/38/
Topics: Molecular property prediction, Quantum chemical modeling, Experimental dataset
Abstract: Data-driven research is in the spotlight across many science and engineering fields, including materials science, with the expectation that effective utilization of data, supported by modern artificial intelligence techniques, can lead to breakthroughs in addressing key scientific questions. The Korea Research Institute of Chemical Technology (KRICT) Chemical Data Explorer platform (ChemDX), our web-based and integrated platform including various data explorer and artificial intelligence modules, aims to enhance accessibility of chemical data for digital materials discovery. In this article, we highlight the results of the 2024 KRICT ChemDX Hackathon, an event to support data-driven research in chemistry and materials science. Hackathon participants explored the ChemDX platform and developed projects ranging from machine learning models and data visualization tools to user interface improvements. These projects demonstrated the versatility and potential of data-driven research with the aid of the ChemDX platform, in bridging data-driven experimental and computational research. The feedback and outcomes from this hackathon demonstrate the impressive potential of interdisciplinary data-driven research, guide further improvements to the platform, and enhance its usability and outreach.

### [37] Electron flow matching for generative reaction mechanism prediction
Authors: Joonyoung F. Joung, Mun Hong Fong, Nicholas Casetti, Jordan P. Liles, Ne S. Dassanayake, Connor W. Coley
Venue: Nature, 645, 115-123 (2025)
DOI: https://doi.org/10.1038/s41586-025-09426-9
Preprint: https://doi.org/10.48550/arXiv.2502.12979
Code: https://github.com/FongMunHong/FlowER
Dataset: https://doi.org/10.6084/m9.figshare.32513667
Page: https://sail.kookmin.ac.kr/publications/37/
Topics: Reaction pathway prediction, Generative modeling, Experimental dataset
Abstract: Central to our understanding of chemical reactivity is the principle of mass conservation, which is fundamental for ensuring physical consistency, balancing equations and guiding reaction design. However, data-driven computational models for tasks such as reaction product prediction rarely abide by this most basic constraint. Here, we recast the problem of reaction prediction as a problem of electron redistribution using the modern deep generative framework of flow matching, explicitly conserving both mass and electrons through the bond-electron (BE) matrix representation. Our model, FlowER, overcomes limitations inherent in previous approaches by enforcing exact mass conservation, resolving hallucinatory failure modes, recovering mechanistic reaction sequences for unseen substrate scaffolds and generalizing effectively to out-of-domain reaction classes with extremely data-efficient fine-tuning. FlowER also enables downstream estimation of thermodynamic or kinetic feasibility and manifests a degree of chemical intuition in reaction prediction tasks. This inherently interpretable framework represents an important step in bridging the gap between predictive accuracy and mechanistic understanding in data-driven reaction outcome prediction.

### [36] ASKCOS: Open-Source, Data-Driven Synthesis Planning
Authors: Zhengkai Tu, Sourabh J. Choure, Mun Hong Fong, Jihye Roh, Itai Levin, Kevin Yu, Joonyoung F. Joung, Nathan Morgan, Shih-Cheng Li, Xiaoqi Sun, Huiqian Lin, Mark Murnin, Jordan P. Liles, Thomas J. Struble, Michael E. Fortunato, Mengjie Liu, William H. Green, Klavs F. Jensen, Connor W. Coley
Venue: Acc. Chem. Res., 58 (11), 1764-1775 (2025)
DOI: https://doi.org/10.1021/acs.accounts.5c00155
Preprint: https://doi.org/10.48550/arXiv.2501.01835
Code: https://gitlab.com/mlpds_mit/askcosv2
Page: https://sail.kookmin.ac.kr/publications/36/
Topics: Reaction pathway prediction, Molecular property prediction
Abstract: The advancement of machine learning and the availability of large-scale reaction datasets have accelerated the development of data-driven models for computer-aided synthesis planning (CASP) in the past decade. In this Account, we describe the range of data-driven methods and models that have been incorporated into the newest version of ASKCOS, an open-source software suite for synthesis planning that we have been developing since 2016. This ongoing effort has been driven by the importance of bridging the gap between research and development, making research advances available through a freely available practical tool. ASKCOS integrates modules for retrosynthetic planning, modules for the complementary capabilities of condition prediction and reaction product prediction, and several supplementary modules and utilities with various roles in synthesis planning. For retrosynthetic planning, we have developed an Interactive Path Planner (IPP) for user-guided search as well as a Tree Builder for automatic planning with two well-known tree search algorithms, Monte Carlo Tree Search (MCTS) and Retro*. Four one-step retrosynthesis models covering template-based and template-free strategies form the basis of retrosynthetic predictions and can be used simultaneously to combine their advantages and propose diverse suggestions. Strategies for assessing the feasibility of proposed reaction steps and evaluating the full pathways are built on top of several pioneering efforts that we have made in the subtasks of reaction condition recommendation, pathway scoring and clustering, and the prediction of reaction outcomes including the major product, impurities, site selectivity, and regioselectivity. In addition, we have also developed auxiliary capabilities in ASKCOS based on our past and ongoing work for solubility prediction and quantum mechanical descriptor prediction, which can provide more insight into the suitability of proposed reaction solvents or the hypothetical selectivity of desired transformations. For each of these capabilities, we highlight its relevance in the context of synthesis planning and present a comprehensive overview of how it is built on top of not only our work but also other recent advancements in the field. ASKCOS has assisted hundreds of medicinal, synthetic, and process chemists in their day-to-day tasks by complementing expert decision making and route ideation. It is our belief that CASP tools are an important part of modern chemistry research and offer ever-increasing utility and accessibility.

### [35] Generative deep learning-based efficient design of organic molecules with tailored properties
Authors: Minhi Han, Joonyoung F. Joung, Minseok Jeong, Dong Hoon Choi, Sungnam Park
Venue: ACS Cent. Sci., 11 (2), 219-227 (2025)
DOI: https://doi.org/10.1021/acscentsci.4c00656
Page: https://sail.kookmin.ac.kr/publications/35/
Topics: Generative modeling
Abstract: Innovative approaches to design molecules with tailored properties are required in various research areas. Deep learning methods can accelerate the discovery of new materials by leveraging molecular structure-property relationships. In this study, we successfully developed a generative deep learning (Gen-DL) model that was trained on a large experimental database (DBexp) including 71,424 molecule/solvent pairs and was able to design molecules with target properties in various solvents. The Gen-DL model can generate molecules with specified optical properties, such as electronic absorption/emission peak position and bandwidth, extinction coefficient, photoluminescence (PL) quantum yield, and PL lifetime. The Gen-DL model was shown to leverage the essential design principles of conjugation effects, Stokes shifts, and solvent effects when it generated molecules with target optical properties. Additionally, the Gen-DL model was demonstrated to generate practically useful molecules developed for real-world applications. Accordingly, the Gen-DL model can be a promising tool for the discovery and design of novel molecules with tailored properties in various research areas, such as organic photovoltaics (OPVs), organic light-emitting diodes (OLEDs), organic photodiodes (OPDs), bioimaging dyes, and so on.

### [34] Reproducing Reaction Mechanisms with Machine-Learning Models Trained on a Large-Scale Mechanistic Dataset
Authors: Joonyoung F. Joung, Mun Hong Fong, Jihye Roh, Zhengkai Tu, John Bradshaw, Connor W. Coley
Venue: Angew. Chem. Int. Ed., 63 (43), e202411296 (2024)
DOI: https://doi.org/10.1002/anie.202411296
Preprint: https://doi.org/10.48550/arXiv.2403.04580
Code: https://github.com/jfjoung/mechanism_prediction
Dataset: https://doi.org/10.6084/m9.figshare.26046106.v1
Page: https://sail.kookmin.ac.kr/publications/34/
Topics: Reaction pathway prediction, Generative modeling, Experimental dataset
Abstract: Mechanistic understanding of organic reactions can facilitate reaction development, impurity prediction, and in principle, reaction discovery. While several machine learning models have sought to address the task of predicting reaction products, their extension to predicting reaction mechanisms has been impeded by the lack of a corresponding mechanistic dataset. In this study, we construct such a dataset by imputing intermediates between experimentally reported reactants and products using expert reaction templates and train several machine learning models on the resulting dataset of 5,184,184 elementary steps. We explore the performance and capabilities of these models, focusing on their ability to predict reaction pathways and recapitulate the roles of catalysts and reagents. Additionally, we demonstrate the potential of mechanistic models in predicting impurities, often overlooked by conventional models. We conclude by evaluating the generalizability of mechanistic models to new reaction types, revealing challenges related to dataset diversity, consecutive predictions, and violations of atom conservation.

### [33] Universal surface tailoring of perovskite nanocrystals via organic pseudohalide ligands applicable to green and blue light-emitting diodes
Authors: Jaewan Ko, Hyeondoo Je, Kitae Kim, Taejun Eom, Joonyoung F. Joung, Sungnam Park, Joona Bang, Dong Hoon Choi
Venue: J. Mater. Chem. C, 10 (48), 18226-18233 (2022)
DOI: https://doi.org/10.1039/D2TC04194D
Page: https://sail.kookmin.ac.kr/publications/33/
Topics: Spectroscopic analysis
Abstract: Proper management of surface defects in perovskite nanocrystals (PeNCs) has resulted in near-unity photoluminescence quantum yield and the development of high-performance light-emitting diodes (LEDs). However, most PeNCs still suffer from incomplete surface passivation, which results in non-ideal efficiencies. Herein, we devise a simple surface tailoring of CsPbBr3 NCs with organic pseudohalide ligands, didodecyldimethylammonium tetrafluoroborate (DDA-BF4). Results suggest that the DDA cation and BF4 anion simultaneously coordinated on the CsPbBr3 NC surfaces, thereby dramatically improving optical properties and colloidal stability. With this passivation, surface-tailored CsPbBr3 NCs were applied to green LEDs, which showed significantly higher external quantum efficiencies than LEDs with untreated PeNCs and stable electroluminescence (EL) at a wavelength of 516 nm. Also, when this method was applied to sky-blue LEDs based on CsPbBr3-xClx NCs (EL at 484 nm), similar improvement in device performance was observed. We believe that organic pseudohalide treatment provides a universal methodology that can be applicable to green and blue PeNC-based LEDs, providing a promising platform for future displays and lighting technologies.

### [32] Reliable experimental method for determination of photoacidity revealed by quantum chemical calculations
Authors: Joonyoung F. Joung, Minseok Jeong, Sungnam Park
Venue: Phys. Chem. Chem. Phys., 24 (36), 21714-21721 (2022)
DOI: https://doi.org/10.1039/D2CP03308A
Page: https://sail.kookmin.ac.kr/publications/32/
Topics: Quantum chemical modeling, Spectroscopic analysis
Abstract: Photoacids are aromatic acids that exhibit significantly different acidities when they are electronically excited. Three experimental methods have been extensively used to determine the photoacidity: fluorescence titration, the Förster cycle, and time-resolved experiments. However, the photoacidities determined by these experimental methods are not consistent. In this work, we used a theoretical method to evaluate the reliability of experimentally determined values. In particular, density functional theory (DFT) and time-dependent DFT calculations were used to obtain the changes in Gibbs free energy for acid dissociation reactions which are directly related to values. The Förster cycle, which is frequently used to experimentally determine the photoacidity due to its simplicity, yielded inconsistent results depending on how the transition energy was defined. We evaluated six empirical parameters extracted from the absorption and emission spectra of acidic and basic species of photoacids to adequately define the transition energy in the Förster cycle. And we found that the values obtained using the optical bandgap as the transition energy in the Förster cycle were in the best agreement with the results of quantum chemical calculations.

### [31] Deep learning for development of organic optoelectronic devices: Efficient prescreening of hosts and emitters in deep-blue fluorescent OLEDs
Authors: Minseok Jeong, Joonyoung F. Joung, Jinhyo Hwang, Minhi Han, Chang Woo Koh, Dong Hoon Choi, Sungnam Park
Venue: npj Comput. Mater., 8, 147 (2022)
DOI: https://doi.org/10.1038/s41524-022-00834-3
Page: https://sail.kookmin.ac.kr/publications/31/
Topics: Molecular property prediction, Experimental dataset
Abstract: The highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energies, which are key factors in optoelectronic devices, must be accurately estimated for newly designed materials. Here, we developed a deep learning (DL) model that was trained with an experimental database containing the HOMO and LUMO energies of 3026 organic molecules in solvents or solids and was capable of predicting the HOMO and LUMO energies of molecules with the mean absolute errors of 0.058 eV. Additionally, we demonstrated that our DL model was efficiently used to virtually screen optimal host and emitter molecules for organic light-emitting diodes (OLEDs). Deep-blue fluorescent OLEDs, which were fabricated with emitter and host molecules selected via DL prediction, exhibited narrow emission (bandwidth = 36 nm) at 412 nm and an external quantum efficiency of 6.58%. Our DL-assisted virtual screening method can be further applied to the development of component materials in optoelectronics.

### [30] Beyond Woodward-Fieser Rules: Design Principles of Property-Oriented Chromophores Based on Explainable Deep Learning Optical Spectroscopy
Authors: Joonyoung F. Joung, Minhi Han, Minseok Jeong, Sungnam Park
Venue: J. Chem. Inf. Model., 62 (12), 2933-2942 (2022)
DOI: https://doi.org/10.1021/acs.jcim.2c00173
Page: https://sail.kookmin.ac.kr/publications/30/
Topics: Molecular property prediction
Abstract: An adequate understanding of molecular structure-property relationships is important for developing new molecules with desired properties. Although deep learning optical spectroscopy (DLOS) has been successfully applied to predict the optical and photophysical properties of organic chromophores, how specific functional groups and solvents affect the optical properties is not clearly understood. Here, we employed an explainable DLOS method by applying the integrated gradients method to DLOS. The integrated gradients method allows us to obtain attributions, indicating how much the functional group contributes to the optical properties including the absorption wavelength and bandwidth, extinction coefficients, emission wavelength and bandwidth, photoluminescence quantum yield, and lifetime. The attributions of 54 functional groups and 9 solvent molecules to seven optical properties are quantified and can be used to estimate the optical properties of chromophores as in the Woodward-Fieser rule. Unlike the Woodward-Fieser rule for only the absorption wavelength, the attributions obtained in this work can be applied to estimate all seven optical properties, which makes a significant extension of the Woodward-Fieser rules. In addition, we demonstrated a strategy for utilizing the attributions in the design of molecules and in tuning the optical properties of the molecules. The design of molecular structures using attributions can revolutionize the development of optimal molecules.

### [29] Pyridine-NBD: A homocysteine-selective fluorescent probe for glioblastoma (GBM) diagnosis based on a blood test
Authors: Youngwoong Kim, Jong Min An, Jaehoon Kim, Tamrin Chowdhury, Hyeon Jong Yu, Kyung-Min Kim, Ho Kang, Chul-Kee Park, Joonyoung F. Joung, Sungnam Park, Dokyoung Kim
Venue: Anal. Chim. Acta, 1202, 339678 (2022)
DOI: https://doi.org/10.1016/j.aca.2022.339678
Page: https://sail.kookmin.ac.kr/publications/29/
Topics: Quantum chemical modeling
Abstract: The precise in vitro diagnosis requires high selectivity and sensitivity for a diagnostic agent. In this respect, fluorescent diagnostic probes have attracted attention in various clinical fields. Herein, we disclosed a tailor-made fluorescent homocysteine probe (NPO-Pyr) based on pyridine-thiol coordination and amine-addition. To date, homocysteine (Hcy) has been recognized as an excellent biomarker for various diseases, but there still remain some limitations in detecting Hcy due to its structural similarity to Cys. In this study, we developed a new fluorescent diagnostic probe for monitoring Hcy by incorporating a 4-hydroxy-pyridine moiety into the skeleton of the NBD fluorophore. The incorporated pyridine moiety could coordinate with the thiol group at Hcy, followed by the amine-addition reaction (12 kJ/mol). Based on this rationale, NPO-Pyr responded to Hcy and exhibited turn-on properties with high selectivity and sensitivity (LOD: 0.084 ppm) and a fast response time (<5 min). Furthermore, NPO-Pyr could predict the formation of glioblastoma (GBM) at an early stage through sensing Hcy in blood plasma (vs. healthy group, ****P < 0.0001). Our findings have significant importance across various fields from basic science to clinical translation, and we strongly believe that NPO-Pyr has the potential to fully replace the current complex GBM diagnostic process as a simpler in vitro agent.

### [28] Locoregional Recurrence Prediction Using a Deep Neural Network of Radiological and Radiotherapy Images
Authors: Kyumin Han, Joonyoung F. Joung, Minhi Han, Wonmo Sung, Young-nam Kang
Venue: J. Pers. Med., 12 (2), 143 (2022)
DOI: https://doi.org/10.3390/jpm12020143
Page: https://sail.kookmin.ac.kr/publications/28/
Topics: Representation learning
Abstract: Radiation therapy (RT) is an important and potentially curative modality for head and neck squamous cell carcinoma (HNSCC). Locoregional recurrence (LR) of HNSCC after RT ranges from 15% to 50% depending on the primary site and stage. In addition, the 5-year survival rate of patients with LR is low. To classify high-risk patients who might develop LR, a deep learning model for predicting LR needs to be established. In this work, 157 patients with HNSCC who underwent RT were analyzed. Based on the National Cancer Institute's multi-institutional TCIA data set containing FDG-PET/CT/dose, a 3D deep learning model was proposed to predict LR without time-consuming segmentation or feature extraction. Our model achieved an averaged area under the curve (AUC) of 0.856. Adding clinical factors into the model improved the AUC to an average of 0.892, with the highest AUC of up to 0.974. The 3D deep learning model could perform individualized risk quantification of LR in patients with HNSCC without time-consuming tumor segmentation.

### [27] Fullerene-Based Triads with Controlled Alkyl Spacer Length as Photoactive Materials for Single-Component Organic Solar Cells
Authors: Young Woong Lee, Jiwoo Yeop, Hyojin Lim, Won-Woo Park, Joonyoung F. Joung, Sungnam Park, Oh-Hoon Kwon, Jin Young Kim, Han Young Woo
Venue: ACS Appl. Mater. Interfaces, 13 (36), 43174-43185 (2021)
DOI: https://doi.org/10.1021/acsami.1c14901
Page: https://sail.kookmin.ac.kr/publications/27/
Topics: Spectroscopic analysis
Abstract: Two kinds of dumbbell-shaped acceptor-donor-acceptor (A-D-A)-type triad single-component (SC) photovoltaic molecules based on a benzodithiophene-rhodanine (BDTRh) core and [6,6]-phenyl-C61 butyric acid (PC61BA) termini, BDTRh-C2-PC61BA and BDTRh-C10-PC61BA, were synthesized by modulating the alkyl (C2 and C10) spacer lengths. Both SC photovoltaic structures had similar UV-vis spectra in solution, but BDTRh-C10-PC61BA showed a significantly higher absorption coefficient as a thin film. In films, a more facile intermolecular photo-induced charge transfer was observed for BDTRh-C10-PC61BA in the broad-band transient absorption measurements. BDTRh-C10-PC61BA also exhibited a higher hole mobility (by 25 times) and less bimolecular recombination than BDTRh-C2-PC61BA. By plotting the normalized external quantum efficiency data, a higher charge-transfer state was measured for BDTRh-C10-PC61BA, reducing its voltage loss. A higher power conversion efficiency of ~2% was obtained for BDTRh-C10-PC61BA, showing higher open-circuit voltage, short-circuit current density, and fill factor than those of BDTRh-C2-PC61BA devices. The different carrier dynamics, voltage loss, and optical and photoelectrical characteristics depending on the spacer length were interpreted in terms of the film morphology. The longer decyl spacer in BDTRh-C10-PC61BA afforded a significantly enhanced intermolecular ordering of the p-type core compared to BDTRh-C2-PC61BA, suggesting that the alkyl spacer length plays a critical role in controlling the intermolecular packing interaction.

### [26] Rational Molecular Design of Azaacene-based Narrowband Green-emitting Fluorophores: Modulation of Spectral Bandwidth and Vibronic Transitions
Authors: Jung Min Ha, Hye Beom Shin, Joonyoung F. Joung, Won Jae Chung, Ji-Eun Jeong, Sangin Kim, Seon Hyoung Hur, Suk-Young Bae, Jun-Yun Kim, Jun Yeob Lee, Sungnam Park, Han Young Woo
Venue: ACS Appl. Mater. Interfaces, 13 (22), 26227-26236 (2021)
DOI: https://doi.org/10.1021/acsami.1c04981
Page: https://sail.kookmin.ac.kr/publications/26/
Topics: Spectroscopic analysis, Quantum chemical modeling
Abstract: A series of green-emitting fluorophores based on a tetra-azaacene core is synthesized by introducing nitrile substituents at different positions. Their molecular structure-optical property relationship [i.e., vibronic transitions in photoluminescence (PL) and electroluminescence (EL) spectra] is investigated to obtain a sharp emission where the vibronic peak ν0-0 should be intensified by suppressing ν0-n (n = 1, 2, 3...) transitions. The intensity ratios (I0-1/I0-0) of the ν0-1 and ν0-0 vibronic transitions in the PL spectra of DBBNP, DBBNP2CN1, and DBBNP2CN2 in hexane are 1.13, 0.80, and 0.67, respectively. Theoretical calculations explain that the CN substitution at positions 8 and 13 in DBBNP2CN2 induces a uniform charge distribution and reduces the Huang-Rhys factors (HRFs) of the vibrational normal modes coupled to the electronic transition. The organic light-emitting diode (OLED) fabricated with DBBNP2CN2 shows a narrower green EL emission at 518 nm with a smaller bandwidth (50 nm) than those of devices adopting DBBNP or DBBNP2CN1. The careful modification of the molecular structures and positions of substituents enables us to reduce the HRFs of vibrations to achieve a narrow emission bandwidth with decreased I0-1/I0-0, which suggests a design strategy to develop narrowband organic fluorophores to improve the color purity for wide-gamut OLED displays.

### [25] Deep Learning Optical Spectroscopy Based on Experimental Database: Potential Applications to Molecular Design
Authors: Joonyoung F. Joung, Minhi Han, Jinhyo Hwang, Minseok Jeong, Dong Hoon Choi, Sungnam Park
Venue: JACS Au, 1 (4), 427-438 (2021)
DOI: https://doi.org/10.1021/jacsau.1c00035
Page: https://sail.kookmin.ac.kr/publications/25/
Topics: Molecular property prediction, Representation learning, Spectroscopic analysis
Abstract: Accurate and reliable prediction of the optical and photophysical properties of organic compounds is important in various research fields. Here, we developed deep learning (DL) optical spectroscopy using a DL model and experimental database to predict seven optical and photophysical properties of organic compounds, namely, the absorption peak position and bandwidth, extinction coefficient, emission peak position and bandwidth, photoluminescence quantum yield (PLQY), and emission lifetime. Our DL model included the chromophore-solvent interaction to account for the effect of local environments on the optical and photophysical properties of organic compounds and was trained using an experimental database of 30,094 chromophore/solvent combinations. Our DL optical spectroscopy made it possible to reliably and quickly predict the aforementioned properties of organic compounds in solution, gas phase, film, and powder with the root mean squared errors of 26.6 and 28.0 nm for absorption and emission peak positions, 603 and 532 cm-1 for absorption and emission bandwidths, and 0.209, 0.371, and 0.262 for the logarithm of the extinction coefficient, PLQY, and emission lifetime, respectively. Finally, we demonstrated how a blue emitter with desired optical and photophysical properties could be efficiently virtually screened and developed by DL optical spectroscopy. DL optical spectroscopy can be efficiently used for developing chromophores and fluorophores in various research areas.

### [24] Ligand-Assisted Direct Photolithography of Perovskite Nanocrystals Encapsulated with Multifunctional Polymer Ligands for Stable, Full-Colored, High-Resolution Displays
Authors: Jaewan Ko, Kyungyeon Ma, Joonyoung F. Joung, Sungnam Park, Joona Bang
Venue: Nano Lett., 21 (5), 2288-2295 (2021)
DOI: https://doi.org/10.1021/acs.nanolett.1c00134
Page: https://sail.kookmin.ac.kr/publications/24/
Topics: Spectroscopic analysis
Abstract: Micropatterns with high stability, definition, and resolution are an absolute requirement in advanced display technology. Herein, patternable perovskite nanocrystals (PNCs) with excellent stability were prepared by exchanging pristine ligands with multifunctional polymer ligands, poly(2-cinnamoyloxyethyl methacrylate). The polymer backbone contains a cinnamoyl group that has been widely employed as a photo-cross-linker under 365 nm UV irradiation. Also, the terminal group is readily adjustable among NH3Cl, NH3Br, and NH3I, allowing us to obtain multicolored PNCs via instant anion exchange. Furthermore, the resulting ligand-exchanged PNCs exhibited enhanced stability toward polar solvents without any undesirable influence on the structural or optical properties of the PNCs. Using anion-exchanged PNCs, RGB microarrays with a subpixel size of 10 μm × 40 μm were successfully demonstrated. Our results highlight the versatility and feasibility of a simplified patterning strategy for nanomaterials, which can be generally applied in the fabrication of various optoelectronic devices.

### [23] Light-directed trapping of metastable intermediates in a self-assembly process
Authors: Joonsik Seo, Joonyoung F. Joung, Sungnam Park, Young Ji Son, Jaegeun Noh, Jong-Man Kim
Venue: Nat. Commun., 11, 6260 (2020)
DOI: https://doi.org/10.1038/s41467-020-20172-6
Page: https://sail.kookmin.ac.kr/publications/23/
Topics: Spectroscopic analysis, Quantum chemical modeling
Abstract: Self-assembly is a dynamic process that often takes place through a stepwise pathway involving formation of kinetically favored metastable intermediates prior to generation of a thermodynamically preferred supramolecular framework. Although trapping intermediates in these pathways can provide significant information about both their nature and the overall self-assembly process, it is a challenging venture without altering temperature, concentrations, chemical compositions and morphologies. Herein, we report a highly efficient and potentially general method for trapping metastable intermediates in self-assembly processes that is based on a photopolymerization strategy. By employing a chiral perylene-diimide possessing a diacetylene containing an alkyl chain, we demonstrated that the metastable intermediates, including nanoribbons, nanocoils and nanohelices, can be effectively trapped by using UV-promoted polymerization before they form thermodynamic tubular structures. The strategy developed in this study should be applicable to naturally and synthetically abundant alkyl-chain-containing self-assembling systems.

### [22] Direct Photolithographic Patterning of Colloidal Quantum Dots Enabled by UV-Crosslinkable and Hole-Transporting Polymer Ligands
Authors: Jaewan Ko, Jun Hyuk Chang, Byeong Guk Jeong, Hyung Jong Kim, Joonyoung F. Joung, Sungnam Park, Dong Hoon Choi, Wan Ki Bae, Joona Bang
Venue: ACS Appl. Mater. Interfaces, 12 (37), 42153-42160 (2020)
DOI: https://doi.org/10.1021/acsami.0c11988
Page: https://sail.kookmin.ac.kr/publications/22/
Topics: Spectroscopic analysis
Abstract: Quantum dot (QD)-based displays call for non-destructive, high-throughput, and high-resolution patterning techniques with micrometer precision. In particular, self-emissive QD-based displays demand fine patterns of conductive QD films with thickness exhibiting uniformity at the nanometer scale. To meet these requirements, we functionalized QDs with photo-patternable and semiconducting poly(vinyltriphenylamine-random-azidostyrene) (PTPA-N3-SH) ligands in which hole-transporting triphenylamine and UV-crosslinkable azide (-N3) groups are integrated. The hybridized QD films undergo chemical crosslinking upon UV irradiation without a loss in luminescence efficiency, enabling micrometer-scale QD patterns (pitch size down to ~10 μm) via direct photolithography. In addition, the conjugated moieties in the ligands render the crosslinked QD films to be implemented in electrically driven light-emitting diodes (LEDs). As the ultimate achievement, a patterned QD-LED was demonstrated with a maximum luminance of 11,720 cd/m2 and a maximum external quantum efficiency (EQE) of 6.25%. The present study offers a simple platform to fabricate conductive nanoparticle films with micrometer-scale patterns, and thus we anticipate that this system will expedite the realization of QD-based displays and will also be applicable to the manufacture of nanoparticles for other electronic devices.

### [21] Experimental database of optical properties of organic compounds
Authors: Joonyoung F. Joung, Minhi Han, Minseok Jeong, Sungnam Park
Venue: Sci. Data, 7, 295 (2020)
DOI: https://doi.org/10.1038/s41597-020-00634-8
Dataset: https://figshare.com/articles/dataset/DB_for_chromophore/12045567/2
Page: https://sail.kookmin.ac.kr/publications/21/
Topics: Experimental dataset
Abstract: Experimental databases on the optical properties of organic chromophores are important for the implementation of data-driven chemistry using machine learning. Herein, we present a series of experimental data including various optical properties such as the first absorption and emission maximum wavelengths and their bandwidths (full width at half maximum), extinction coefficient, photoluminescence quantum yield, and fluorescence lifetime. A database of 20,236 data points was developed by collecting the optical properties of organic compounds already reported in the literature. A dataset of 7,016 unique organic chromophores in 365 solvents or in the solid state is available in CSV format.

### [20] Green-, Red-, and Near-Infrared-Emitting Polymer Dot Probes for Simultaneous Multicolor Cell Imaging with a Single Excitation Wavelength
Authors: Ji-Eun Jeong, Mohammad Afsar Uddin, Hwa Sook Ryu, Hee-Chang Kim, Minsu Kang, Joonyoung F. Joung, Sungnam Park, Sang-Hee Shim, Han Young Woo
Venue: Chem. Mater., 32 (15), 6685-6696 (2020)
DOI: https://doi.org/10.1021/acs.chemmater.0c02172
Page: https://sail.kookmin.ac.kr/publications/20/
Topics: Spectroscopic analysis
Abstract: We report newly synthesized fluorescence resonance energy transfer (FRET)-based green-, red-, and near-infrared (NIR)-emitting polymer dot (Pdot) probes. Fluorescent Pdots (~60 nm) were prepared with a green-emissive conjugated polymer (PPDT-P, donor) alone or by mixing the donor with a red- or NIR-emitting fluorophore (T-DCS or ITIC, acceptor), where an optically inert matrix polymer [poly(styrene-co-maleic anhydride)] was mixed together to minimize the aggregation-caused quenching by diluting the fluorophores and to provide surface functionalization for further bioconjugation with antibodies for active targeting. Highly fluorescent green-emissive PPDT-P Pdots were prepared with a photoluminescence (PL) quantum efficiency of ~30%, and the FRET-mediated red and NIR PL was intensified by 5.3-8.5 times (with high FRET ratios of ~9) via the efficient energy transfer (FRET efficiency of 80-98%) and antenna effect, compared with the signals obtained via direct excitation of the fluorophores in Pdots. All three types of Pdot/antibody conjugates were simultaneously immunostained to COS-7 cells (showing minimal cross-reactivity), reducing the tedious sequential immunostaining process to a single step. Finally, we obtained high-contrast three-color cell images with little spectral leakthrough by exciting all the probes simultaneously at a single wavelength at 405 nm without the need for a complicated or expensive multiple-excitation setup.

### [19] Penta-fluorophenol: A Smiles rearrangement-inspired cysteine-selective fluorescent probe for imaging of human glioblastoma
Authors: Jong Min An, Sangrim Kang, Eugene Huh, Yejin Kim, Dahae Lee, Hyejung Jo, Joonyoung F. Joung, Veronica Jihyun Kim, Ji Yeoun Lee, Yun Sik Dho, Yuna Jung, Junho K. Hur, Chan Park, Junyang Jung, Youngbuhm Huh, Ja-Lok Ku, Sojin Kim, Tamrin Chowdhury, Sungnam Park, Jae Seung Kang, Myung Sook Oh, Chul-Kee Park, Dokyoung Kim
Venue: Chem. Sci., 11 (22), 5658-5668 (2020)
DOI: https://doi.org/10.1039/D0SC01085E
Page: https://sail.kookmin.ac.kr/publications/19/
Topics: Quantum chemical modeling
Abstract: Two of the most critical factors for the survival of glioblastoma (GBM) patients are precision diagnosis and the tracking of treatment progress. At the moment, various sophisticated and specific diagnostic procedures are being used, but there are relatively few simple diagnosis methods. This work introduces a sensing probe based on a turn-on type fluorescence response that can measure the cysteine (Cys) level, which is recognized as a new biomarker of GBM, in human-derived cells and within on-site human clinical biopsy samples. The Cys-initiated chemical reactions of the probe cause a significant fluorescence response with high selectivity, high sensitivity, a fast response time, and a two-photon excitable excitation pathway, which allows the imaging of GBM in both mouse models and human tissue samples. The probe can distinguish the GBM cells and disease sites in clinical samples from individual patients. Besides, the probe has no short- or long-term toxicity and immune response. The present findings hold promise for application of the probe to a relatively simple and straightforward following of GBM at clinical sites.

### [18] Chemically resistant and thermally stable quantum dots prepared by shell encapsulation with cross-linkable block copolymer ligands
Authors: Jaewan Ko, Byeong Guk Jeong, Jun Hyuk Chang, Joonyoung F. Joung, Suk-Young Yoon, Doh C. Lee, Sungnam Park, June Huh, Heesun Yang, Wan Ki Bae, Se Gyu Jang, Joona Bang
Venue: NPG Asia Mater., 12, 19 (2020)
DOI: https://doi.org/10.1038/s41427-020-0200-4
Page: https://sail.kookmin.ac.kr/publications/18/
Topics: Spectroscopic analysis
Abstract: Endowing quantum dots (QDs) with robustness and durability has been one of the most important issues in this field, since the major limitations of QDs in practical applications are their thermal and oxidative instabilities. In this work, we propose a facile and effective passivation method to enhance the photochemical stability of QDs using polymeric double shell structures from thiol-terminated poly(methyl methacrylate-b-glycidyl methacrylate) (P(MMA-b-GMA)-SH) block copolymer ligands. To generate a densely cross-linked network, the cross-linking reaction of GMA epoxides in the PGMA block was conducted using a Lewis acid catalyst under an ambient environment to avoid affecting the photophysical properties of the pristine QDs. This provides QDs encapsulated with robust double layers consisting of a highly transparent PMMA outer shell and an oxidation-protective cross-linked inner shell. Consequently, the resulting QDs exhibited exceptional tolerance to heat and oxidants when dispersed in organic solvents or QD-nanocomposite films, as demonstrated under various harsh conditions with respect to temperature and oxidant species. The present approach not only provides simple yet effective chemical means to enhance the thermochemical stability of QDs, but also offers a promising platform for the hybridization of QDs with polymeric materials for developing robust light-emitting or light-harvesting devices.

### [17] A new visible light triggered Arrhenius photobase and its photo-induced reactions
Authors: Joonyoung F. Joung, Jeeun Lee, Joungin Hwang, Kihang Choi, Sungnam Park
Venue: New J. Chem., 44 (3), 668-673 (2020)
DOI: https://doi.org/10.1039/C9NJ05404A
Page: https://sail.kookmin.ac.kr/publications/17/
Topics: Quantum chemical modeling, Spectroscopic analysis
Abstract: Arrhenius photobases are of potential use for excited-state hydroxide ion dissociation (ESHID), photo-induced pOH jump experiments, and base-catalyzed reactions. However, previously studied Arrhenius photobases have to be excited by UV light and undergo ESHID reactions only in protic solvents. These characteristics have become a disadvantage to their application in many fields of research. In this work, we have designed and synthesized a new Arrhenius photobase (NO2-Acr-OH), the ESHID reaction of which is readily triggered by visible light excitation. In contrast to previously studied Arrhenius photobases, NO2-Acr-OH undergoes ESHID reactions in protic solvents as well as in polar aprotic solvents. Solvent-dependent photo-induced reactions of NO2-Acr-OH are comprehensively studied by time-resolved fluorescence spectroscopy. Molecular designs for visible-light-triggered acridinol-based Arrhenius photobases with a large ΔpKb value are proposed.

### [16] Macrocyclic Diacetylene-Terthiophene Cocrystal: Molecular Self-Assembly, Topochemical Polymerization, and Energy Transfer
Authors: Kwangmin Bae, Jung-Moo Heo, Mohammed Iqbal Khazi, Joonyoung F. Joung, Sungnam Park, Youngmee Kim, Jong-Man Kim
Venue: Cryst. Growth Des., 20 (1), 434-441 (2020)
DOI: https://doi.org/10.1021/acs.cgd.9b01351
Page: https://sail.kookmin.ac.kr/publications/16/
Topics: Spectroscopic analysis
Abstract: The macrocyclic structure offers direction-control self-assembly to generate columnar supramolecular architectures with a guest-molecule-accessible interior cavity. Owing to the π-π stacking characteristic and photopolymerizable feature of the diacetylenic template, macrocyclic diacetylenes (MCDAs) have emerged as an intriguing molecular design for constructing arrays of covalently connected nanochannels. The energy transfer mechanism by engineering host-guest cocrystals of self-assembling π-electron-rich motifs has been widely accepted for devising organic electronics. A highly fluorescent and polymerizable cocrystal of macrocyclic diacetylene-terthiophene (MCDA-3T) was constructed. Single-crystal X-ray diffraction analysis reveals well-ordered columnar assembly of MCDA with stacking geometry close to ideal packing parameters preferred for the topochemical polymerization. Inspection of the extended crystal packing pattern and elemental analysis confirms the inclusion of the 3T guest in outer space positioned along the parallel-packed MCDA columns, resulting in an array of nanochannels. UV-induced polymerization of the MCDA-3T cocrystal transforms it into covalently cross-linked PDAs and displays Förster resonance energy transfer behavior between fluorescent 3T and the conjugated PDA polymer. The energy transfer phenomenon observed with the tubular PDA and oligothiophenes should be useful in the design of new energy-harvesting functional supramolecules.

### [15] Covalently Linked Perylene Diimide–Polydiacetylene Nanofibers Display Enhanced Stability and Photocurrent with Reversible FRET Phenomenon
Authors: Joonsik Seo, Chandra Kantha, Joonyoung F. Joung, Sungnam Park, Raz Jelinek, Jong-Man Kim
Venue: Small, 15 (19), 1901342 (2019)
DOI: https://doi.org/10.1002/smll.201901342
Page: https://sail.kookmin.ac.kr/publications/15/
Topics: Spectroscopic analysis
Abstract: Because of their unique structural and optical properties, 1D perylene diimide (PDI) derivatives have gained attention for use in optoelectronic devices. However, PDI-containing self-assembled supramolecular systems often are of limited use because they have supramolecular architectures that are held together by weak noncovalent π-π stacking, hydrogen bonding, and hydrophobic interactions. As a result, they are intrinsically unstable under solution-processing conditions. To overcome this limitation, a polydiacetylene (PDA)-based strategy is developed to construct a solvent-resistant and stable PDI assembly. For this purpose, first the monomer PDI-BisDA is generated, in which two polymerizable diacetylene (DA) units are covalently linked to a PDI core. Importantly, 254 nm UV irradiation of self-assembled PDI-BisDA nanofibers forms solvent-resistant and stable PDI-PDA fibers. Owing to the presence of PDA, the generated polymer fibers display an increased photocurrent. In addition, the existence of PDA and PDI moieties in the fiber leads to the occurrence of switchable on-off fluorescence resonance energy transfer (FRET) between the PDI and reversibly thermochromic PDA chromophores.

### [14] 2-(Benzothiazol-2-yl)pyren-1-ol, a new excited state intramolecular proton transfer-based fluorescent sensor for nitroaromatic compounds
Authors: Ying Hu, Joonyoung F. Joung, Ji-Eun Jeong, Yerin Jeong, Han Young Woo, Yuanbin She, Sungnam Park, Juyoung Yoon
Venue: Sens. Actuators B Chem., 280, 298-305 (2019)
DOI: https://doi.org/10.1016/j.snb.2018.10.043
Page: https://sail.kookmin.ac.kr/publications/14/
Topics: Quantum chemical modeling, Spectroscopic analysis
Abstract: 2-(Benzothiazol-2-yl)pyren-1-ol (P3-NS) was developed as an excited-state intramolecular proton transfer (ESIPT)-based sensor for nitroaromatic compounds (NACs). Results of studies of its photophysical and optical properties show that P3-NS exists in various, solvent-dependent isomeric forms arising from rotation about the C-C bond connecting the benzothiazole and pyren-1-ol rings and the location of the pyrene-OH proton. The results of density functional theory (DFT) calculations enabled identification of the major structures of P3-NS dissolved in different solvents. Upon electronic excitation in nonpolar or weakly polar solvents, P3-NS undergoes an ESIPT reaction to form a product that only weakly fluoresces. In contrast, P3-NS exists in a strongly fluorescent deprotonated form in highly polar solvents. The results of time-dependent DFT calculations indicate that fluorescence quenching of the product generated by the ESIPT reaction of P3-NS is caused by intersystem crossing at a conical intersection between the S1 and T2 states. The anionic form of P3-NS, present in highly polar solvents, was shown to be a fluorescence sensor for nitroaromatic compounds (NACs). Fluorescence quenching by NACs occurs by protonation of the anionic form of P3-NS (static quenching) and by photoinduced electron transfer from the anionic form to NACs (dynamic quenching).

### [13] Synthesis, Structure, and Photoluminescence Properties of a Metal-Organic Framework with Hexagonal Channels: Selective Turn-On Sensing for Mg2+ Ion
Authors: Sunhwi Eom, Sora Park, Jeong Hwa Song, Woo Ram Lee, Han Geul Lee, Dong Won Kang, Joonyoung Francis Joung, Sungnam Park, Dohyun Moon, Chang Seop Hong
Venue: Eur. J. Inorg. Chem., 2019 (2), 330-335 (2019)
DOI: https://doi.org/10.1002/ejic.201801291
Page: https://sail.kookmin.ac.kr/publications/13/
Topics: Spectroscopic analysis
Abstract: A three-dimensional Cd2+ framework (1) with wide one-dimensional hexagonal channels was prepared based on a tripodal tricarboxylate ligand possessing nitrogen donor atoms. The Cd atoms form a chain structure bridged by carboxylates and aqua ligands. Upon Mg2+ ion capture, the fluorescence emission of this porous material was 5.2 times greater than its Mg2+-free fluorescence. To the best of our knowledge, such enhancement has not been previously reported for metal-organic framework sensory systems. The sensing performance of 1 is reversible over repeated cycles of Mg2+ inclusion and release, revealing the reusability of this material. In the presence of other tested metal ions, Mg2+ ions were selectively detected owing to the operation of this turn-on mechanism. Thus, this platform is a promising sensor material for selective Mg2+ ion recognition.

### [12] A naphthoimidazolium-cholesterol derivative as a ratiometric fluorescence based chemosensor for the chiral recognition of carboxylates
Authors: Xin Zhang, Gyeongju Ko, Joonyoung F. Joung, Meng Li, Yerin Jeong, K.M.K. Swamy, Dayoung Lee, Yifan Liu, Songyi Lee, Sungnam Park, Tony D. James, Juyoung Yoon
Venue: Chem. Commun., 54 (94), 13264-13267 (2018)
DOI: https://doi.org/10.1039/C8CC06262E
Page: https://sail.kookmin.ac.kr/publications/12/
Topics: Spectroscopic analysis, Quantum chemical modeling
Abstract: Fluorescent chemosensors for sensing chiral molecules have been actively studied in recent years. In the current study, we report a naphthoimidazolium-cholesterol derivative (NI-chol 1) as a fluorescence-based chemosensor for chiral recognition, in which the naphthoimidazolium serves not only as a fluorophore but also as a recognition moiety for anions via imidazolium (C-H)+-anion binding, and the cholesterol unit acts as a chiral barrier. In particular, NI-chol 1 displayed unique and distinct ratiometric changes with Boc-D-Phe; on the other hand, Boc-L-Phe induced a negligible change. Furthermore, a distinct downfield shift (from 9.64 ppm to 9.96 ppm) of the imidazolium C-H peak was observed for Boc-D-Phe (5 eq.) with severe broadening, which indicates strong ionic hydrogen bonding between the C-H proton and the carboxylate.

### [11] Fluorescent Organic Glass with Unique Optical and Mechanical Properties
Authors: Kahoe Ku, Joonyoung F. Joung, Heeyeon Park, Myeong-Geun Kim, Sungnam Park, Woong Kim
Venue: Adv. Funct. Mater., 28 (39), 1801394 (2018)
DOI: https://doi.org/10.1002/adfm.201801394
Page: https://sail.kookmin.ac.kr/publications/11/
Topics: Spectroscopic analysis
Abstract: Conventional organic glasses such as molecular and polymeric glasses either lack processability or have ill-defined properties. Here, a novel organic glass is reported having well-defined fluorescent properties and high compatibility with various fabrication processes. The fluorescent organic glass (FOG) is synthesized by simply heating benzyl alcohol with a small amount of aqueous sulfuric acid. Owing to its outstanding optical properties, FOG is placed beyond the domain of conventional organic glasses in the Abbe diagram. Moreover, excellent rheological properties render it amenable to molding, blowing, and nanopatterning processes. Finally, based on extensive characterization, it is proposed that a FOG is composed of a 1,2,3,4-tetraphenyl-1,3-butadiene core and poly(phenylene methylene) branches, which are responsible for molecular fluorescence and polymeric processability, respectively. The demonstration may contribute significantly to the development of organic glasses with unprecedented properties for various applications.

### [10] Elucidating the Role of Molecule-Electrode Interfacial Defects in Charge Tunneling Characteristics of Large-area Junctions
Authors: Gyu Don Kong, Junji Jin, Martin Thuo, Hyunsun Song, Joonyoung F. Joung, Sungnam Park, Hyo Jae Yoon
Venue: J. Am. Chem. Soc., 140 (38), 12303-12307 (2018)
DOI: https://doi.org/10.1021/jacs.8b08146
Page: https://sail.kookmin.ac.kr/publications/10/
Topics: Quantum chemical modeling
Abstract: Interfacial chemistry at organic-inorganic contact critically determines the function of a wide range of molecular and organic electronic devices and other systems. The chemistry is, however, difficult to understand due to the lack of easily accessible in-operando spectroscopic techniques that permit access to interfacial structure on a molecular scale. Herein, we compare two analogous junctions formed with identical organic thin films and different liquid top-contacts (water droplet vs eutectic gallium indium alloy) and elucidate the puzzling interfacial characteristics. Specifically, we fine-tune the surface topography of the organic surface using mixed self-assembled monolayers (SAMs): a single-component SAM composed of rectifier (2,2'-bipyridyl-terminated n-undecanethiolate, denoted as SC11BIPY) is systematically diluted with nonrectifying n-alkanethiolates of different lengths (denoted as SCn, where n = 8, 10, 12, 14, 16, 18). Characterization of the resulting mixed SAMs in wettability and tunneling currents with the two separate liquid top-contacts allows us to investigate the role of phase segregation and gauche defects in the SAM//liquid interfaces. The results reported here show that the difference in length between SC11BIPY and SCn is translated into nanoscopic pits and gauche-conformer defects on the surface, and the difference in contact force (hydrostatic vs user pressures), and hence conformity of contact, accounts for the difference in wettability and rectification behaviors. Our work provides an insight into the role of molecule-electrode interfacial defects in the performance of molecular-scale electronic devices.

### [9] Topochemical polymerization of macrocyclic diacetylene with a naphthalene moiety for a tubular-shaped polydiacetylene chromophore
Authors: Chandra Kantha, Hansol Kim, Youngmee Kim, Jung-Moo Heo, Joonyoung F. Joung, Sungnam Park, Jong-Man Kim
Venue: Dyes Pigm., 154, 199-204 (2018)
DOI: https://doi.org/10.1016/j.dyepig.2018.02.039
Page: https://sail.kookmin.ac.kr/publications/9/
Topics: Spectroscopic analysis, Quantum chemical modeling
Abstract: Tubular-shaped chromophores have great potential in chemical and material sciences. A naphthalene-containing macrocyclic diacetylene (MCDA-Naph) was synthesized to access covalently linked organic nanotubes (ONTs) through topochemical polymerization. Single-crystal X-ray analysis revealed that MCDA-Naph adopts the desired tubular array with favorable molecular orientation. UV irradiation of the molecularly stacked MCDA-Naph resulted in 1,4-addition polymerization and the generation of conjugated ene-yne chromophores. Density functional theory (DFT) provided evidence for tubular polydiacetylene nanotubes.

### [8] Cationic Effect on the Equilibria and Kinetics of the Excited-State Proton Transfer Reaction of a Photoacid in Aqueous Solutions
Authors: Joonyoung F. Joung, Sangin Kim, Sungnam Park
Venue: J. Phys. Chem. B, 122 (19), 5087-5093 (2018)
DOI: https://doi.org/10.1021/acs.jpcb.8b00588
Page: https://sail.kookmin.ac.kr/publications/8/
Topics: Quantum chemical modeling, Spectroscopic analysis
Abstract: Dissolved ions have a significant effect on the chemical equilibria and kinetics in aqueous solutions by changing the physical properties and hydrogen bond network of water. In this work, the ionic effects on the excited-state proton transfer (ESPT) reactions of Coumarin 183 (C183) in aqueous ionic solutions are comprehensively studied in terms of pKa, pKa*, activation energies, and kinetic isotope effect (KIE). The acid dissociation constants (pKa and pKa*) of C183 in the ground and excited states are determined by UV-visible absorption and steady-state fluorescence spectroscopy. The activation energies (Ea) and KIE for the ESPT reaction of C183 are directly obtained by time-resolved fluorescence spectroscopy. The changes in pKa, pKa*, Ea, and KIE values of C183 are found to be dependent on the charge density of cations. The secondary KIE is more substantially influenced by the dissolved ions than the primary KIE. Furthermore, the ionic effects on the equilibrium (pKa and pKa*) and kinetic (Ea and KIE) parameters of C183 are found to be well explained by the free-energy reactivity relation. Our current results are very important in understanding the ionic effects on the equilibria and ESPT kinetics of photoacids in aqueous ionic solutions.

### [7] Ionic effects on the proton transfer mechanism in aqueous solutions
Authors: Joonyoung F. Joung, Sangin Kim, Sungnam Park
Venue: Phys. Chem. Chem. Phys., 19 (37), 25509-25517 (2017)
DOI: https://doi.org/10.1039/C7CP04392A
Page: https://sail.kookmin.ac.kr/publications/7/
Topics: Quantum chemical modeling, Spectroscopic analysis
Abstract: Proton dissociation (PD) reactions of weak acids and proton transfer (PT) processes in aqueous solutions are strongly influenced by ions. However, a detailed molecular picture that describes how ions affect the rates of PD and PT processes is still missing. Here, we utilize time-resolved fluorescence spectroscopy combined with quantum chemical calculations to investigate the excited-state proton transfer (ESPT) reaction of a photoacid in aqueous metal chloride solutions. The activation energy (Ea) for the ESPT of the photoacid increases with increasing charge density of cations. The local hydrogen bond (H-bond) structure of the photoacid in the ionic hydration shell is strongly related to both the Ea and the charge density of cations. Most importantly, the proton's positive charge in the transition state, which is delocalized through the H-bonded water channel, is more destabilized with an increase in the charge density of cations, leading to a higher Ea. Our experimental and computational results allow us to elucidate the underlying mechanism for the ionic effect on PD and the subsequent PT process at the molecular level.

### [6] Iridium Complex Bearing Urea Groups as a Phosphorescent Chemosensor for Chiral Anion Recognition
Authors: Ying Hu, Yinan Li, Joonyoung F. Joung, Jun Yin, Sungnam Park, Juyoung Yoon, Myung Ho Hyun
Venue: Sens. Actuators B Chem., 241, 224-229 (2017)
DOI: https://doi.org/10.1016/j.snb.2016.10.076
Page: https://sail.kookmin.ac.kr/publications/6/
Topics: Spectroscopic analysis
Abstract: Luminescent chemosensors for chiral molecules have drawn significant attention. In this study, a new iridium complex 1 bearing two urea groups and ethyl naphthalene groups was synthesized as a phosphorescent chemosensor for chiral anion recognition. Addition of t-Boc amino acids induced phosphorescence enhancement with the maximum emission at 560 nm. A KD/KL value as large as 5.0 was observed for iridium complex 1 with phenylglycine. Two urea groups provide a preorganized binding site for the carboxylates, whereas two ethyl naphthalenes act as chiral barriers.

### [5] Chromogenic Tubular Polydiacetylenes from Topochemical Polymerization of Self-Assembled Macrocyclic Diacetylenes
Authors: Jung-Moo Heo, Youngmee Kim, Seulki Han, Joonyoung F. Joung, Sang-hwa Lee, Sejin Han, Jaegeun Noh, Jaeyong Kim, Sungnam Park, Haiwon Lee, Yoon Mi Choi, Young-Sik Jung, Jong-Man Kim
Venue: Macromolecules, 50 (3), 900-913 (2017)
DOI: https://doi.org/10.1021/acs.macromol.6b02493
Page: https://sail.kookmin.ac.kr/publications/5/
Topics: Spectroscopic analysis, Quantum chemical modeling
Abstract: Tubular materials formed by self-assembly of small organic molecules find great utility in chemical and material science. Conventional tubular structures often lack stability because noncovalent molecular interactions are responsible for their conformational integrities. Herein we report the development of covalently linked chromogenic organic nanotubes which are prepared by using topochemical polymerization of self-assembled macrocyclic diacetylenes (MCDAs). Crystal structures of five MCDAs having different diameters were elucidated, and four of these substances were transformed to tubular polydiacetylenes (PDA) by UV-induced polymerization. Surprisingly, MCDA-1 was found to self-assemble in stacks with a tilt angle of 62.1°, which significantly deviates from the optimal value for polymerization of 45°. This observation suggests that geometric parameters derived using linear diacetylene (DA) models might not be strictly applicable to polymerization of MCDA systems. Blue-phase PDAs obtained by polymerization of MCDA-1 and MCDA-3 have different thermochromic and solvatochromic properties, which enable them to be utilized for colorimetric differentiation of aromatic solvents including isomeric xylenes. The observations made and information obtained in this study should enhance the understanding and design of stimulus-responsive rigid organic nanotubes.

### [4] Photoinduced Reversible Phase Transition of Azobenzene-Containing Polydiacetylene Crystals
Authors: Woohyun Baek, Jung-Moo Heo, Seungwhan Oh, Sang-hwa Lee, Jaeyong Kim, Joonyoung F. Joung, Sungnam Park, Hesson Chung, Jong-Man Kim
Venue: Chem. Commun., 52 (97), 14059-14062 (2016)
DOI: https://doi.org/10.1039/C6CC08606C
Page: https://sail.kookmin.ac.kr/publications/4/
Topics: Spectroscopic analysis
Abstract: An azobenzene-containing supramolecular polydiacetylene (PDA) crystal undergoes a photoinduced reversible blue-to-red phase transition accompanied by crystal tearing.

### [3] Electronic relaxation dynamics of PCDA-PDA studied by transient absorption spectroscopy
Authors: Joonyoung F. Joung, Junwoo Baek, Youngseo Kim, Songyi Lee, Myung Hwa Kim, Juyoung Yoon, Sungnam Park
Venue: Phys. Chem. Chem. Phys., 18 (33), 23096-23104 (2016)
DOI: https://doi.org/10.1039/C6CP03858A
Page: https://sail.kookmin.ac.kr/publications/3/
Topics: Quantum chemical modeling, Spectroscopic analysis
Abstract: Photo-curable polymers originating from 10,12-pentacosadiynoic acid (PCDA-PDA) are commonly used polydiacetylenes (PDAs). PCDA-PDA exhibits thermochromic properties, undergoing a unique colorimetric transition from blue to red as the temperature is increased from low to high. In this work, we have carefully studied the temperature-dependent optical properties of PCDA-PDA by using UV-visible absorption, FTIR, Raman, and transient absorption (TA) spectroscopy in combination with quantum chemical calculations. Temperature-dependent UV-visible absorption spectra indicate that PCDA-PDA exhibits reversible thermochromic properties up to 60 °C and its thermochromic properties become irreversible above 60 °C. Such distinct thermochromic properties are also manifested in TA signals, so that the electronically excited PCDA-PDA relaxes to the ground state via an intermediate state at 20 °C (blue form) but relaxes directly back to the ground state at 80 °C (red form). The electronic relaxation dynamics of PCDA-PDA are comprehensively analyzed based on different kinetic models by using the global fitting analysis method. The intermediate state in the blue form of PCDA-PDA is clearly found to be responsible for fluorescence quenching. FTIR and Raman spectroscopy and quantum chemical calculations confirm that the H-bonds between the carboxylic acid groups in PCDA-PDA are broken at high temperatures, leading to an irreversible structural change of PCDA-PDA.

### [2] Origin of the Reversible Thermochromic Properties of Polydiacetylenes Revealed by Ultrafast Spectroscopy
Authors: Junwoo Baek, Joonyoung F. Joung, Songyi Lee, Hanju Rhee, Myung Hwa Kim, Sungnam Park, Juyoung Yoon
Venue: J. Phys. Chem. Lett., 7 (2), 259-265 (2016)
DOI: https://doi.org/10.1021/acs.jpclett.5b02671
Page: https://sail.kookmin.ac.kr/publications/2/
Topics: Quantum chemical modeling, Spectroscopic analysis
Abstract: Polydiacetylenes (PDAs) with thermochromic properties undergo colorimetric transitions when the external temperature is varied. This capability has the potential to enable these materials to be used as temperature sensors. These thermochromic properties of PDAs stem from their temperature-dependent optical properties. In this work, we studied the temperature-dependent optical properties of Bis-PDA-Ph, which exhibits reversible thermochromic properties, and PCDA-PDA, which exhibits irreversible thermochromic properties, by UV-visible absorption and femtosecond transient absorption spectroscopy. Our results indicate that the electronic relaxation of PDAs occurs via an intermediate state in cases where the material exhibits reversible thermochromic properties, whereas the excited PDAs relax directly back to the ground state when irreversible thermochromic properties are observed. The existence of this intermediate state in the electronic relaxation of PDAs thus plays an important role in determining their thermochromic properties. These results are very important for both understanding and strategically modulating the thermochromic properties of PDAs.

### [1] Effect of NaCl Salts on the Activation Energy of Excited-State Proton Transfer Reaction of Coumarin 183
Authors: Joonyoung F. Joung, Sangin Kim, Sungnam Park
Venue: J. Phys. Chem. B, 119 (50), 15509-15515 (2015)
DOI: https://doi.org/10.1021/acs.jpcb.5b09905
Page: https://sail.kookmin.ac.kr/publications/1/
Topics: Quantum chemical modeling, Spectroscopic analysis
Abstract: Coumarin 183 (C183) was used as a photoacid to study excited-state proton transfer (ESPT) reactions. Here, we studied the effect of ions on the ESPT of C183 in aqueous NaCl solutions using steady-state fluorescence spectroscopy and the time-correlated single photon counting (TCSPC) method. The acid dissociation equilibrium of excited-state C183 and the activation energy for the ESPT of C183 were determined as a function of NaCl concentration. The change in the equilibrium constant was found to be correlated with the solvation energy of deprotonated C183. Frequency-resolved TCSPC signals measured at several temperatures were analyzed by using a global fitting analysis method, which enabled us to extract all the rate constants involving the ESPT reaction and the spectra of individual species. The activation energy for the ESPT reaction of C183 was highly dependent on NaCl concentration. Quantum chemical calculations were used to calculate the local hydrogen-bond (H-bond) configurations around C183 in aqueous NaCl solutions. It was found that the activation energy for the ESPT was determined by the local H-bond configurations around C183, which were significantly influenced by the dissolved ions.

## People
### Current members
- Heejeong Kim (김희정), Postdoctoral Researcher. https://sail.kookmin.ac.kr/people/heejeong-kim/
- Jihwan Kim (김지환), M.S./Ph.D. Integrated Course. https://sail.kookmin.ac.kr/people/jihwan-kim/
- Seonbin Kim (김선빈), M.S./Ph.D. Integrated Course. https://sail.kookmin.ac.kr/people/seonbin-kim/
- Yeonju Yoo (유연주), Undergraduate Researcher. https://sail.kookmin.ac.kr/people/yeonju-yoo/

### Alumni
- Siyeol In (인시열), Undergraduate Researcher. https://sail.kookmin.ac.kr/people/siyeol-in/
- Hyejeong Jeon (전혜정), Undergraduate Researcher. https://sail.kookmin.ac.kr/people/hyejeong-jeon/
- Yunhee Choi (최윤희), Visiting Undergraduate Student (EPFL). https://sail.kookmin.ac.kr/people/yunhee-choi/
- Chanjoong Kim (김찬중), Undergraduate Researcher (UROP). https://sail.kookmin.ac.kr/people/chanjoong-kim/
- Yongpyo Cho (조용표), Undergraduate Researcher (UROP). https://sail.kookmin.ac.kr/people/yongpyo-cho/
- Jinwoo Lee (이진우), Undergraduate Researcher (UROP). https://sail.kookmin.ac.kr/people/jinwoo-lee/
- Hanbyul Baik (백한별), Undergraduate Researcher (UROP). https://sail.kookmin.ac.kr/people/hanbyul-baik/
- Hyojin Lee (이효진), Undergraduate Researcher (UROP). https://sail.kookmin.ac.kr/people/hyojin-lee/
- Yumin Kim (김유민), Undergraduate Researcher (UROP). https://sail.kookmin.ac.kr/people/yumin-kim/

## Principal investigator
Joonyoung F. Joung (정준영), Assistant Professor, Department of Chemistry, Kookmin University. Page: https://sail.kookmin.ac.kr/pi/ · Google Scholar: https://scholar.google.com/citations?user=0uuwTRQAAAAJ · ORCID: https://orcid.org/0000-0002-5976-2048

Joonyoung F. Joung is an Assistant Professor in the Department of Chemistry at Kookmin University. He completed his Ph.D. in physical chemistry at Korea University with Sungnam Park, then worked as a postdoctoral research associate at Korea University and as a postdoctoral associate in the Department of Chemical Engineering at MIT with Connor W. Coley. His work combines spectroscopy, physical chemistry, and machine learning for molecular property prediction, reaction prediction, and molecular design.

Education:
- Ph.D. in Physical Chemistry, Korea University (advisor: Prof. Sungnam Park), 2020.08
- B.S. in Chemistry, Inha University, 2015.02

Career:
- Assistant Professor, Department of Chemistry, Kookmin University, 2025.03–present
- Postdoctoral Associate, Department of Chemical Engineering, MIT (advisor: Prof. Connor W. Coley), 2022.09–2025.02
- Postdoctoral Research Associate, Department of Chemistry, Korea University (advisor: Prof. Sungnam Park), 2020.09–2022.07
- Research Professor, Research Institute for Natural Science, Korea University, 2020.09–2022.07

## Joining the lab
See https://sail.kookmin.ac.kr/positions/ (Korean) for how to apply as a postdoctoral researcher, graduate student, or undergraduate researcher, including currently advertised undergraduate projects.

## News (newest first)
### September 10, 2026: Jihwan co-authors new paper on perovskite nanocrystals
Congratulations to Jihwan on the publication of "Synergistic Ligand and Composition Control for Bright and Stable CsPbBr3/Cs4PbBr6 Core/Shell Colloidal Perovskite Nanocrystals"! Jihwan contributed to the machine learning part of this collaborative study, developing a random forest model to predict successful core/shell formation and guide the optimization of synthesis conditions.
Link: https://sail.kookmin.ac.kr/publications/45/

### September 1, 2026: Yeonju joins the lab
Yeonju Yoo (유연주) joins SAIL as an undergraduate researcher (UROP).
Link: https://sail.kookmin.ac.kr/people/yeonju-yoo/

### July 13, 2026: Yunhee joins the lab
Yunhee Choi (최윤희) joins SAIL as a visiting undergraduate student (EPFL).
Link: https://sail.kookmin.ac.kr/people/yunhee-choi/

### June 24, 2026: Jihwan wins Best Oral Presentation Award at the 149th KCS Physical Chemistry Division Summer Symposium
Congratulations to Jihwan on receiving the Best Oral Presentation Award at the 149th Physical Chemistry Division Summer Symposium held in Busan! This award recognizes the outstanding quality and clarity of his research presentation. We are proud of his achievement and look forward to his continued contributions!
Link: https://sail.kookmin.ac.kr/people/jihwan-kim/
Link: Kookmin University news, https://www.kookmin.ac.kr/comm/board/user/be8e117863cfd580d7ed5931a799207c/view.do?dataSeq=1076881

### June 19, 2026: Heejeong selected for the AI Seoul Tech Research Support Program
Congratulations to Heejeong on being selected as a postdoctoral researcher for the 2026 AI Seoul Tech Research Support Program, hosted by the Seoul Future Foundation! This competitive program supports outstanding researchers advancing AI research in Seoul. We wish Heejeong all the best in this exciting opportunity!
Link: https://sail.kookmin.ac.kr/people/heejeong-kim/

### June 14, 2026: New SAIL website launches
Our new lab website was designed and developed by Chanjoong, replacing the previous Wix site with sail.kookmin.ac.kr. Thank you, Chanjoong, for your hard work and dedication!
Link: https://sail.kookmin.ac.kr/

### May 19, 2026: New review in Chemical Society Reviews
"An overview of reaction outcome prediction with physics-based and data-driven methods."
Link: https://sail.kookmin.ac.kr/publications/41/

### March 8, 2026: Chanjoong selected for the Global PBL Program
Congratulations to Chanjoong on being selected for the Global PBL Program! He will soon be heading to Irvine, CA, for this exciting opportunity. We wish him all the best!
Link: https://sail.kookmin.ac.kr/people/chanjoong-kim/

### March 3, 2026: Heejeong joins the lab
Heejeong Kim (김희정) joins SAIL as a postdoctoral researcher.
Link: https://sail.kookmin.ac.kr/people/heejeong-kim/

### February 1, 2026: Seonbin joins the lab
Seonbin Kim (김선빈) joins SAIL as an M.S. student.
Link: https://sail.kookmin.ac.kr/people/seonbin-kim/

### December 15, 2025: Yongpyo joins the lab
Yongpyo Cho (조용표) joins SAIL as an undergraduate researcher (UROP).
Link: https://sail.kookmin.ac.kr/people/yongpyo-cho/

### December 15, 2025: Hanbyul joins the lab
Hanbyul Baik (백한별) joins SAIL as an undergraduate researcher (UROP).
Link: https://sail.kookmin.ac.kr/people/hanbyul-baik/

### December 15, 2025: Siyeol joins the lab
Siyeol In (인시열) joins SAIL as an undergraduate researcher (UROP).
Link: https://sail.kookmin.ac.kr/people/siyeol-in/

### September 11, 2025: Jihwan joins the lab
Jihwan Kim (김지환) joins SAIL as an M.S. student.
Link: https://sail.kookmin.ac.kr/people/jihwan-kim/

### September 4, 2025: FlowER is now published in Nature!
"Electron flow matching for generative reaction mechanism prediction."
Link: https://sail.kookmin.ac.kr/publications/37/
In the press: JoongAng Ilbo, https://www.joongang.co.kr/article/25361989
In the press: ChosunBiz, https://biz.chosun.com/science-chosun/science/2025/08/21/WNMXRMJT7RHWNPVHCH6T73HLCA/
In the press: Hankyoreh, https://www.hani.co.kr/arti/economy/biznews/1214373.html

### July 14, 2025: Hyojin joins the lab
Hyojin Lee (이효진) joins SAIL as an undergraduate researcher (UROP).
Link: https://sail.kookmin.ac.kr/people/hyojin-lee/

### July 14, 2025: Chanjoong joins the lab
Chanjoong Kim (김찬중) joins SAIL as an undergraduate researcher (UROP).
Link: https://sail.kookmin.ac.kr/people/chanjoong-kim/

### July 14, 2025: Jinwoo joins the lab
Jinwoo Lee (이진우) joins SAIL as an undergraduate researcher (UROP).
Link: https://sail.kookmin.ac.kr/people/jinwoo-lee/

### July 14, 2025: Hyejeong joins the lab
Hyejeong Jeon (전혜정) joins SAIL as an undergraduate researcher (UROP).
Link: https://sail.kookmin.ac.kr/people/hyejeong-jeon/

### March 2025: Spectroscopy and AI Lab opens at Kookmin University
Joonyoung F. Joung joins the Department of Chemistry as Assistant Professor and starts his lab.
Link: https://sail.kookmin.ac.kr/pi/