Exciton-to-hot electron upconversion phenomenon in Mn-doped II-VI quantum dots (QDs) produces highly energetic hot electrons with the average energy of only a fraction of 1eV below the vacuum level. The hot electron upconversion process bears a similarity to the photon upconversion in lanthanide doped nanoparticles, but the final state is the highly excited hot electron in the conduction band of the host QDs not the state that emits the higher-energy photons. The upconverted hot electrons can be utilized to perform thermodynamically and kinetically challenging reduction reactions by taking advantage of their high excess kinetic energy and long-range transfer capability. The presentation will highlight recently demonstration of the anticipated benefits of the upconverted hot electrons in several photocatalytic reduction and redox-neutral reactions. Development of new material platform for more efficient hot electron upconversion and the prospects of expanding the application of the energetic hot electrons in beyond photocatalysis will be discussed.

I will cover methodologies that my lab has developed for the identification and design of biologics, including peptide-based protein-protein interaction inhibitors, antibodies and Zinc-Finger proteins. Our methods cover modern machine learning (AI) techniques, classical protein modeling, as well as high-throughput screening technologies.

Synthetic biology is bringing together engineers, physicists and biologists to model, design and construct biological circuits out of proteins, genes and other bits of DNA, and to use these circuits to rewire and reprogram organisms. These re-engineered organisms are going to change our lives in the coming years, leading to cheaper drugs, rapid diagnostic tests, and synthetic probiotics to treat infections and a range of complex diseases. In this talk, we highlight recent efforts to harness synthetic gene networks and programmable cells to create diagnostics, therapeutics and vaccines for fighting pathogens, including SARS-CoV-2.

High concentration liquid electrolytes, such as water-in-salt electrolytes and ionic liquids, as well as solid state polymer electrolytes are rapidly emerging materials to replace the flammable organic electrolytes widely used in industrial lithium ion batteries. Molecular dynamics (MD) simulation of these systems is challenging due to a number of reasons, including lack of predictive force fields, complex polarization effects occurring both in electrolytes and on electrodes, highly correlated ion motion due to high concentration and strong electrostatic interactions, to name a few. In this talk, I’ll present our ongoing efforts to enable predictive molecular simulations of these highly charged systems. Two major advances will be highlighted – the development of predictive multi-scale force field for ILs and polymers based entirely on first-principle calculations, and the development of simulation algorithms to treat surface polarization and proper thermal equilibrium in polarizable MD simulations. New physical insights gained from the new simulation model and simulation algorithms will be discussed, which includes polarization effects on the ion adsorption at air/water and water/electrode interfaces, ion correlation in organic electrolytes, formation of ionic liquid crystals, as well as conformational dynamics in IL-polymer mixtures. Another important study investigates the molecular response to the internal charge transfer events occurring in a trans-membrane protein, representing complex interfacial systems abundant in biology. I’ll cover both the development of new simulation methods and the applications of the methods toward energy storage materials and biomolecular systems, illustrating the versatile utility of understanding the underlying physics for fundamental questions.

The functional light-driven materials often exhibit a complex morphology consisting of various grains with short and long-range order and defects stemming from imperfect chemical composition, local strain and etc. Local structural and morphological heterogeneity results in distinct carrier dynamics at different local regions of energy materials. Unfortunately, the conventional spectroscopy techniques reveal only an incomplete picture of the carrier dynamics due to the intrinsic spatially averaged nature of time-resolved techniques. In other words, true structure-function relationships in complex energy materials cannot be reliably probed using conventional time-resolved spectroscopic techniques. By utilizing time and space resolved technique, i.e., transient absorption microscopy (TAM), we were able to directly monitor local carrier dynamics of spatially heterogeneous systems. In this talk, I will briefly describe the basic operating principle of state-of-the-art ultrafast transient absorption microscopy. I will further discuss recent applications of TAM to hybrid metal halide perovskites thin films; 1) A direct monitoring of ballistic transport of non-equilibrium charge carriers in a series of MAPI perovskite thin film.1,2 2) The effect of nanoscale chemical heterogeneity in alloyed perovskite thin films.3 3) The unexpected carrier dynamics of 2D/3D mixed perovskite thin film. The direct tracking of charge carrier motion in the perovskite thin films clearly elucidates unprecedent carrier phenomena in new generation semiconductors.

There are many molecular systems with increasing complexity and scale that are currently being developed for novel solar light harvesting and energy storage devices. However, quantitatively reliable computational modeling of exciton and charge transport dynamics in most of these systems remain challenging despite recent theoretical and computational advances. This difficulty is in large part due to the lack of satisfactory and comprehensive quantum dynamics calculation methods, which are flexible enough to account for complex details of molecular systems while being efficient enough to be applied to large scale systems including the effects of disorder/fluctuations. The present talk highlights some of our on-going efforts to develop and adapt new quantum and generalized master equation approaches and integrate them for comprehensive modeling of exciton and charge transport dynamics. These include recent developments of polaron transformed quantum master equation approach so as to make them more accurate and widely applicable, and developments of new kinetic Monte Carlo simulation methods to sample solutions of master equation approaches with appropriate quantum rate kernels. The possibility of integrating these approaches in a consistent manner is also illustrated employing representative models.

Redox reactions by charge transfer from the semiconductor nanocrystals (NCs) are attractive for the chemical transformations due to their green characteristics and the readily tunable energetic and dynamics of the charge transfer and interfacial chemistry of the NCs. Despite their versatility in various photoinduced chemical processes, generation of the stable radical species using semiconductor NCs as the photocatalyst has been more challenging due to the difficulty in removing the reversible charge transfer or charge recombination even in the presence of the sacrificial charge acceptors. This presentation will discuss how cesium lead halide (CsPbX3) NCs can provide a unique pathway that effectively prevents the reversible electron transfer and generate stable N-centered radicals from amines, which cannot be achieved easily with typical semiconductor NC photocatalysts. We will discuss the stable and selective photogeneration of aminium and aminyl radicals from the same amine precursor via tunable charge carrier imbalance condition enabled by the photoinduced anion exchange that opens unconventional but highly effective pathway of removing electrons irreversibly from the NCs. The coupling between the radicals photogenerated by CsPbX3 NCs, for which II-VI semiconductor NCs are catalytically inactive, will also be discussed.

The monolayered 2D nanosheets of layered inorganic solids (layered metal oxides, layered double hydroxides, layered metal chalcogenides, layered metal carbides, metal nitrides, carbon nitrides, and graphene) have attracted intense research interest because of their unique properties and versatile functionalities. A great diversity in the chemical compositions and crystal structures of 2D inorganic nanosheets provides valuable opportunity to optimize their energy performances. The monolayered 2D inorganic nanosheets can be synthesized by soft-chemical exfoliation and/or structural transformation reactions, and employed as building blocks for exploring high-performance 2D hybrid materials. In the resulting nanohybrids, these 2D nanosheets act as energy-functional active components, hybridization substrates, conductive additives, etc. In this talk, diverse examples of 2D inorganic nanosheet-based energy-functional nanohybrids will be presented together with the relationship between chemical bonding nature and functionalities. The crucial role of interface/defect engineering in optimizing the energy performances of 2D nanosheet-based hybrids will be highlighted.

The brain is without doubt the most amazing organ in the human body. However, it is still a mystery as to how the brain and processes and stores information. The brain uses synapses for synaptic transmission. Modifications of the synaptic transmission are thought to be the basis of memory and learning. Neurons in the network can either excite or inhibit innervated neurons by depolarizing or hyperpolarizing the membrane potential of connected neurons respectively; these effects are mediated by the release of excitatory or inhibitory neurotransmitters stored in vesicles in the presynaptic terminals. The balance between neuronal excitation and inhibition plays an important role in processing complex cognitive tasks such as learning and memory. Inhibitory synaptic transmission plays a crucial role in sustaining this balance. The dynamics of inhibitory synaptic vesicles in presynaptic terminals have been poorly understood because of practical limitations such as lack of specific labeling tools of inhibitory single synaptic vesicles. We specifically labeled single GABAergic (inhibitory in mature neurons) synaptic vesicles in presynaptic terminals of cultured rat hippocampal neurons by loading quantum dots (QDs) and traced them using a real-time three-dimensional microscopy setup based on dual-focus optics. In comparison with Syt1-QD-loaded synaptic vesicles mostly derived from excitatory synapses, we found that inhibitory synaptic vesicles tend to travel shorter distance before fusion and move more straightly with a shortened fusion latency. Also, kiss-and-run (K&R) fusion was more prevalent among inhibitory synaptic vesicles than the excitatory vesicles. Furthermore, inhibitory synaptic vesicles undergoing spontaneous release showed distinguishable spatiotemporal dynamics compared with those undergoing evoked release. Interestingly, substantial amount of spontaneously labeled inhibitory synaptic vesicles undergo exocytosis under stimulation. Taken together, the observed unique dynamics of inhibitory synaptic vesicles allows for fast and efficient inhibitory synaptic transmission, providing new insights into the roles of dynamics in biological processes.

Protein aggregation, also referred to as phase separation, has been the subject of much research in biology, biophysics, and chemistry. Protein aggregation can function either to promote normal cellular metabolism or to disturb normal cellular functions. The chemical mechanism underlying protein aggregation is not clearly understood. It is well-known that many aggregated proteins are highly charged, either positively or negatively. Thus, we hypothesized that protein aggregation is mediated by small charged biomolecules: negatively charged nucleoside triphosphate (NTP) interacting with positively charged proteins and positively charged polyamine interacting with negatively charged proteins. In this study, we employed super-charged green fluorescence protein (scGFP) to study how charged proteins are aggregated through charge-charge interaction with small charged biomolecules in cells. When expressing scGFP in E-coli, positively charged (+28) GFPs were found to aggregate with NTP and negatively charged (-27) GFPs aggregated with polyamine molecules. In addition, it is known that tau protein aggregation is a main cause of neuronal dementia, Alzheimer’s disease. We showed tau proteins could be aggregated by small charged molecules. We thereby conclude that the small charged biomolecules are the main driver to induce protein aggregation in cells.

Discrimination of each cell type in multicellular organism is the most important first step to figure out the complex cell community and control their regulation. The current gond-standard method of cell distinction is through established antibodies for biomarkers on the cell surface. To surrogate the antibodies, we have developed small fluorescent probes for live cell distinction. In addition to the conventional binding targets i.e. proteins and carbohydrates: Protein Oriented Live-cell Distinction (POLD) and Carbohydrate Oriented Live-cell Distinction (COLD), we have extended the scope of biomarkers to transporters, via Gating Oriented Live-cell Distinction (GOLD) and lipid composition of the cell membrane, via Lipid Oriented Live-cell Distinction (LOLD). The intrinsically complex nature of life requires further orthogonal strategy for higher dimension of cell discrimination. Recently, we further expanded to novel chemical biology approach of Metabolism Oriented Live-cell Distinction (MOLD) to enrich the toolboxes and strategy choice. The design and mechanism elucidation for various immune cells will provide the new insight for cell selective probe development. Eventually, the multi-dimensional layer of cell distinction strategy will be the basis of characterizing extremely complex cell communities

Designing, synthesizing and controlling metal nanostructures with a superhigh precision are the keys to the reliable and widespread use of plasmonic nanostructures in optics, nanoscience, chemistry, materials science, biotechnology and medicine. Here, I will introduce the design, synthetic strategies and characterization of molecularly tunable and structurally reproducible plasmonic nanostructures including metal nanogap structures and gold nanocatenanes with strong, controllable and quantifiable plasmonic signals (e.g., quantitative surface-enhanced Raman scattering). I will then show their potential in addressing some of important challenges in plasmonics, biosensing, bioimaging and therapeutics, and discuss how these new plasmonic materials and platforms can lead us to new breakthroughs in nanochemistry, molecular computing, nanomachines/nanorobotics and next-generation disease diagnostics.

In a cell, molecules are transported from one compartment to another compartment through nanochannels in a wide variety of biological processes. To better understand the molecular transport, we considered a simple model system consisting of two nanoscale compartments connected by a carbon nanotube through which small molecules can pass. We found that osmolytes strongly interacting with molecules can induce the complete transfer of molecules to the initially empty compartment. Additionally, for water molecules, we calculated the free energy change as all the molecules were transported to the initially empty compartment. The free energy profile clearly indicates the presence of a free energy barrier, which explains that water does not spontaneously flow without external forces such as osmotic force. Our study sheds light on the method of calculating free energy for a transporting system as well as the fundamental aspects of molecular transport through a nanochannel.

서강대학교에서 20여년 동안 재직하면서 질량분석법 개발, 적외선 분광법을 이용한 기체상태 호스트-게스트 화학, 생활화학제품내 환경관련 물질 분석법 개발, 다양한 머신러닝 기법 개발 등의 연구를 수행해 왔습니다. 중앙대학교에서의 세미나에서는 20년동안 진행한 연구들을 간략히 소개하는 시간을 갖고자 합니다. 특히, 라디컬을 이용한 펩타이드 시퀀싱 질량분석 연구, 적외선 분광법을 이용한 기체상태 호스트-게스트 화학, 가습기 살균제 분석법 개발에서 비롯한 환경관련 질량분석법 활용 연구, 질량분석 스펙트럼들에 대한 머신러닝 기법을 활용한 새로운 해석법 개발에 대해 그 핵심들을 설명드리고자 합니다. 그리고, 최근 제가 진행하고 있는 동물대체시험법 관련 다양한 QSAR 모델 개발에 대한 그랜드 스킴에 대해 설명할 수 있도록 하겠습니다. 마지막으로 시간이 허용한다면 미세플라스틱에 대한 FTIR 이미지에서의 미세플라스틱 구분 소프트웨어 개발 및 최근 관심을 들여 개발하고 있는 실험실 Automation의 연구성과들을 소개하는 내용들을 발표하도록 하겠습니다.

Despite the great advance in computational chemistry, our simulation capability has been limited to a simple, ideal system due to the expensive density functional theory (DFT) calculations. Larger-scale emergent phenomena involving >100 atoms have been challenging, examples of which include the catalysis of complex catalysis, the discovery of realistic catalysts, and the kinetics of materials synthesis. In this seminar, data science accelerated computational chemistry research is presented to address the multi-scale challenges in catalysis, and energy materials research. The machine learning can be combined with the multi-scale simulation strategy to elucidate the mechanisms of unprecedentedly complex catalysis and to rapidly screen new realistic catalysts for CH4 emission reduction. The data science also enables the research of large molecule catalysis, which has previously remained an experimental-based trials-and-errors approach. Finally, a showcase of Bayesian positive-unlabeled learning will be demonstrated to assess the synthesizability of the materials, which is otherwise difficult due to the complexity of materials synthesis.

Despite the great advance in computational chemistry, our simulation capability has been limited to a simple, ideal In the last 30 years, inorganic semiconductor nanocrystals have been extensively researched because of their size-dependent optoelectronic properties, thus successfully debuting in the commercial sector. The synthetic development of nanocrystals, however, has perplexed from the complex energy landscape of the reaction. Unlike intermediates that can be isolated and characterized with atomic precision in organic synthesis, the intermediates in nanocrystal synthesis are difficult to resolve because of the co-existence of metastable states with similar energy. If one can control the energy of the metastable intermediates originating from various factors including shapes and surface-ligand interaction and isolate the singular intermediate species, the nanocrystal growth with atomic precision could be achievable. In this presentation, I will discuss the tetrapod InP nanocrystals as a crystalline “late intermediate” that warrants controlled colloidal nanocrystal growth. The use of the late intermediate with well-defined facets at the sub-10 nm scale for directional growth with atomic control and highlight the potential for the new directed approach of nanocrystal synthesis. Well-defined surface of tetrapod enable us to investigate the facet-dependent surface chemistry of InP. Finally, a geometry-driven transition from single to multi-photon emitting behavior in InP tetrapods will be discussed.

With skyrocketing interest and the achievement of tremendous research efforts, perovskite solar cells are on the verge of commercialization. However, the stabilities of precursors and devices provide challenges for commercialization. Many researchers have dealt with these issues separately. Recently, we introduced Lewis base additives that address the precursor and device stability difficulties. The added Lewis bases showed excellent interactions with Pb2+ and FA+ cations in the precursor and perovskite crystal. Therefore, the interaction between the facile Lewis base and various cations suppressed the related grain boundary defects, thus improving the ambient storage stability and the efficiency of the target device. Furthermore, we applied heptadecafluorooctanesulfonic acid tetraethylammonium salt (HFSTT), containing fluorinated long alkyl chains as hydrophobic tails and sulfonic acid groups (SO3−) as hydrophilic heads, which exhibit great synergistic potential in large-area film uniform fabrication, crystallization orientation modulation, defect passivation, and device operation stability enhancement, are introduced. The HFSTT-modified films exhibit a prominent (100) orientation and lower trap-state density as well as enhanced carrier mobilities and diffusion lengths, facilitating a champion unit device with an impressive power conversion efficiency (PCE) of 23.88% (0.14 cm2) and 22.52% (1 cm2) with a low voltage deficit around 0.341 V.

Myosin X plays an important role in migration and metastasis of cancer. In particular, myosin X plays a critical role in formation of filopodia and invadopodia in cancer. Recent studies revealed that Myosin X undergoes dimerization via this antiparallel coiled-coil and moves along actin bundle contrast with actin filaments which most Myosins move along. Moreover, Myosin X was found to contains a flexible lever arm extension. However, the stepping mechanism of this Myosin X with unparallel coiled-coil and flexible lever arm extension remains elusive. Our real-time single-molecule tracking studies of full-length Myosin X showed a broad distribution of step size, which is in contrast to well-known step sizes of Myosin V having a narrow distribution of step size. Furthermore, Myosin X showed a longer run length, along actin bundles in comparison to those moving on actin filaments. We further elucidated which functional domains of Myosin X play the crucial role for these stepping mechanism by constructing the chimera Myosins by replacing the motor domain or lever arm of Myosin X with those of Myosin V. We found that the anti-parallel coiled-coil and flexible lever arm play an important role in the broad step sizes of Myosin X along actin bundles, suggesting that an anti-parallel coiled-coil may be critical for positioning of the lever arm near the actin to allow rapid binding of a free head to the actin when coupled to a flexible lever arm that the flexible lever arm in turn allows a range of possible step sizes, especially along actin bundles.

Advanced Science Institute, Graduate Program in Nano-biomedical Engineering, Yonsei University, Korea All cells are different. Starting from the same genetic information, every cell functions differently but harmoniously, together in place via cell-cell interactions. In diseases, such functions are disrupted and cells behave abnormally with high heterogeneity. To understand diseases such as cancers that possess highly diverse genetic features, it is important to investigate their heterogeneity at the single cell level. I will present my recent works in development of novel single cell analysis platforms to address the challenges described above and discuss the future directions toward their applications for spatial multi-omics in various biological systems. Part 1. Quantifying protein isoforms in single cells by next-generation sequencing (Zhang, Sohn, et al., Comm. Biol. 2020) Compared to single cell studies quantifying nucleic acids, there are no direct biochemical reactions to amplify for proteins from single cell quantity for sequencing. Here we report a method for single cell protein isoform quantification via in situ covalent ligation between proteins of interest and single-stranded DNA oligonucleotides. We showed the separation of ubiquitinated protein isomers from budding yeast using gel electrophoresis and extracted the resolved protein-oligo conjugates to amplify single-cell quantity information for sequencing. The protocol only requires the common biochemistry lab equipment such as mini gel and Western blot cassettes. Our results revealed the heterogeneities of the ubiquitination levels of H2B in single cells from different cell-cycle stages, which have been obscured in ensemble measurements. Part 2. Protection of tissue physicochemical properties using polyfunctional crosslinkers (Park, Sohn, Chen et al., Nature Biotechnology 2019) Understanding complex biological systems requires the system-wide characterization of both molecular and cellular features. Existing methods for spatial mapping of biomolecules in intact tissues suffer from information loss caused by degradation and tissue damage. We report a tissue transformation strategy named stabilization under harsh conditions via intramolecular epoxide linkages to prevent degradation (SHIELD), which uses a flexible polyepoxide to form controlled intra- and intermolecular cross-link with biomolecules. SHIELD preserves protein fluorescence and antigenicity, transcripts and tissue architecture under a wide range of harsh conditions. We applied SHIELD to interrogate system-level wiring, synaptic architecture, and molecular features of virally labeled neurons and their targets in mouse at single-cell resolution. We also demonstrated rapid three-dimensional phenotyping of core needle biopsies and human brain cells. SHIELD enables rapid, multiscale, integrated molecular phenotyping of both animal and clinical tissues. Part 3. Molecular decrowding by tissue expansion allows precise determination of the spatial distribution of synaptic proteins at a nanometer scale by exTEM (Kim, Yoon, Macks et al., ACS Nano, under revision) To understand how the molecular machinery of synapses works, it is essential to determine an inventory of synaptic proteins at a subsynaptic resolution. Nevertheless, synaptic proteins are difficult to localize because of the low expression levels and limited access to immunostaining epitopes. Here, we report on the exTEM (epitope-exposed by expansion-transmission electron microscopy) method that enables the imaging of synaptic proteins in situ. This method uniquely combines TEM with nanoscale resolution and expandable tissue-hydrogel hybrids for enhanced immunolabeling with better epitope accessibility via molecular decrowding, allowing successful probing of the distribution of various synapse-organizing proteins. We propose that exTEM can be employed for studying the mechanisms underlying the regulation of synaptic architecture and function by providing nanoscale molecular distribution of synaptic proteins in vivo. We also envision that exTEM is widely applicable for investigating protein nanostructures located in densely packed environments by immunostaining of commercially available antibodies at nanometer resolution.

In nature, helical macromolecules such as collagen, chitin and cellulose are critical to the morphogenesis and functionality of various hierarchically structured materials. During morphogenesis, these chiral macromolecules are secreted and undergo self-templating assembly, a process whereby multiple kinetic factors influence the assembly of the incoming building blocks to produce non-equilibrium structures. A single macromolecule can form diverse functional structures when self-templated under different conditions. Collagen type I, for instance, forms transparent corneal tissues from orthogonally aligned nematic fibers, distinctively colored skin tissues from cholesteric phase fiber bundles, and mineralized tissues from hierarchically organized fibers. Nature’s self-templated materials surpass the functional and structural complexity achievable by current top-down and bottom-up fabrication methods. However, self-templating has not been thoroughly explored for engineering synthetic materials. In my seminar, I will demonstrate a facile biomimetic process to create functional nanomaterials utilizing chiral colloidal particles (M13 phage). A single-step process produces long-range-ordered, supramolecular films showing multiple levels of hierarchical organization and helical twist. Using the self-templating materials assembly processes, we have created various biomimetic supramolecular structures. The resulting materials show distinctive optical and photonic properties similar to avian skin color matrices and butterfly wing nanostructures. Through the directed evolution of the M13 phages, I will also show how resulting materials can be utilized as functional nanomaterials for biomedical, biosensor and bioenergy applications.