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  • ICMS 2019
  • The 5th International Conference on Molecular Simulation
  • November 3-6, 2019 / Lotte Hotel Jeju, Korea

Program

Important Dates
Abstract Submission
March 1 ~ July 31, 2019
Acceptance Notification
August 14, 2019
Early Registration
(TBA)
Final Program Announcement
October 2, 2019
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Keynote Speaker

The list of speakers is not final, and is subject to change.

Theory & Methodology

  • Ryo Akiyama
  • Kyushu University, Japan
  • "Asakura-Oosawa theory: On the Origin of Excluded Volume Effects in a Crowding Media and the Progress."
    Biography and Abstract
Biography
Ryo Akiyama received his Bachelor and M. Eng. from Hokkaido University and his Ph.D. for physics from Nagoya University (1996). He did postdoctoral researches at Institute for Molecular Science and Cornell University. He moved to Kyushu University and is studying chemical physics and biophysics in the chemistry department since 2003. His current interests are various mediator-effects and they are studied based on methods of statistical mechanics, such as integral equation theories for liquid.
Abstract
Idea of depletion interaction was proposed by Asakura(1927-2016) and Oosawa(1922-2019) in 1954. Nowadays, the importance of the idea is recognized in a broad range of fields, such as colloidal dispersion, crowding problems in the cytoplasm, and so on. Let us think about the effective interaction between two colloidal particles. In Asakura-Oosawa theory, the depletants are excluded by the colloidal particles, but the depletants don't interact each other. So, the behaviors of depletants are “ideal gas” in this statistical mechanics theory. This modeling is reasonable in a dilute depletants solution. However, this simple model becomes worse as the packing fraction of depletants becomes higher. It is because that the excluded volume effect between depletants also becomes significant. In this talk, the recent progress of the related integral equation theory and of applications of the idea will be discussed.
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  • Chris Chipot
  • CNRS/University of Illinois, France
  • "Bridging microsecond computer simulations and millisecond biological events"
    Biography and Abstract
Biography
Chris Chipot received his PhD in Theoretical Chemistry in 1994 from the Henri Poincaré University, in France, conducting research on intermolecular potentials with a fellowship from the Roussel Uclaf Institute. Following a post-doctorate in the Department of Pharmaceutical Chemistry of the University of California in San Francisco, he became a National Research Council post-doctoral fellow at the NASA Ames Research Center. He joined the CNRS in 1996 at the University of Lorraine, where he worked on the modeling of the biological membranes by means of computer simulations, while developing original approaches for free-energy calculations and the exploration of rare events. His developments also extend to the accurate description of intermolecular interactions, including induction phenomena. He received his habilitation in 2000, and was promoted research director in 2006. Since 2012, he has been directing an Associate International Laboratory established between the CNRS and the University of Illinois at Urbana-Champaign, where he is affiliated to the Department of Physics.
Abstract
In a matter of three decades, free-energy calculations have emerged as an indispensable tool to tackle deep biological questions that experiment alone has left unresolved. In spite of recent advances on the hardware front that have pushed back the limitations of brute-force molecular dynamics simulations, opening the way to time and size scales hitherto never attained, they represent a cogent alternative to access with unparalleled accuracy the thermodynamics and possibly the kinetics that underlie the complex processes of the cell machinery. From a pragmatic perspective, the present lecture will draw a picture of how the field has been shaped and invigorated by milestone developments, application, and sometimes rediscovery of foundational principles laid down years ago to reach new frontiers in the exploration of intricate biological phenomena. Through a series of illustrative examples, distinguishing between alchemical and geometrical transformations, I will discuss how far free-energy calculations have come, what are the current hurdles they have to overcome, and the challenges they are facing for tomorrow.
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  • Jhih-Wei Chu
  • National Chiao Tung University, Taiwan
  • "Multiscale Decomposition of Mechanical Properties in Biomolecules"
    Biography and Abstract
Biography
Dr. Chu received his bachelor’s degree in chemical engineering from National Taiwan University in Taiwan and his PhD in chemical engineering from MIT. His research aims to elucidate of the manner by which the composing details of a complex molecular system determine the functional activities. He focuses on the problems of protein dynamics, protein conformational changes, and protein allostery. He develops and applies multiscale computational methods based on physical chemistry principles with emphasis on close collaborations with experimental counter parts.
Abstract
Biomolecules such as protein and nucleic acids duplexes are of vital importance in biology. A key question for such systems is how do subtle differences in the chemical composition cause extended variation in structure and mechanical properties in the system. In this work, all-atom molecular dynamics simulations and multiscale coarse grained modeling were conducted to resolve the structures and mechanical couplings in dsDNA, dsRNA, and an enzyme system. The multiscale computational framework developed here allowed quantitative comparison of the strengths of mechanical couplings for the different interactions in a molecule as well as across different systems. It was thus established that dsRNA has significantly higher strengths for mechanical couplings in backbone and sugar puckering than those of dsDNA. For nucleobase interactions of hydrogen bonding and stacking, on the other hand, dsDNA exhibited stronger mechanical couplings. Moreover, we showed that the mechanical couplings in the protein structure can be utilized to capture the patterns of sequence correlation in a multiple sequence alignment.
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  • Seung Soon Jang
  • Georgia Institute of Technology, USA
  • "Multicompartment Micelle Nanoreactors: Multiscale Modeling Approach"
    Biography and Abstract
Biography
Prof. Seung Soon Jang obtained his B.S. (1992), M.S. (1994), and Ph.D. (1999) in Seoul National University, Korea. After his education, Dr. Jang worked at Samsung Electronics for two years as a senior engineer, and then joined the Materials and Process Simulation Center (MSC) of California Institute of Technology as a postdoc and then became research director. Dr. Jang joined the School of Materials Science and Engineering at the Georgia Institute of Technology in July 2007 as an assistant professor and was promoted to a tenured associate professor in 2013. His research interest is to investigate various nanoscale systems using the multiscale modeling methods to achieve molecular architecture-nanoscale structure-property relationship, which makes fundamental improvement in new material development for various applications. So far, he has made more than 120 peer-reviewed journal publications and more than 90 invited presentations for various topics.
Abstract
In recent years, research in industrial applications of polymeric materials has begun to explore the field of immobilized catalysis. In particular, the idea of catalysts bound to a micelle backbone, creating a nanoscale molecular reactor (commonly referred to as nanoreactor), has become an area of great interest. From a computational perspective, investigating the potential of micelles as nanoreactors requires analyzing the miscibility of block copolymers, both on a fully atomistic and on a mesoscale basis. The model proposed by Flory and Huggins offers an interaction parameter χ which quantifies the favorability of mixing between two polymers. This interaction parameter depends on many process conditions, not least of which are the temperature and composition of a solution, in order to properly estimate the strength of the interaction between a given pair of polymer molecules. Extensive work has already been completed in this group to establish a robust method of estimating the χ-value for a given pair of molecules; this information is necessary for preparing coarse-grained modeling and simulations (e.g., micellization simulations). In our present work, we apply miscibility analysis to a relatively nascent technology in immobilized catalysis science, viz. the multicompartment micelle nanoreactor. This technology offers a way to harness both the enhanced reactivity of homogeneous catalysis and the ease of separation traditionally enjoyed by heterogeneous catalysis. Through the use of mesoscale calculations, we will study the feasibility of a three-compartment micelle nanoreactor. For this purpose, we have developed a systematic strategy to calculate χ parameters, which has been applied and validated through mesoscale simulations of micelle consisting of triblock copolymers. We hope to demonstrate that this triblock copolymer can form a micelle capable of reaction compartmentalization and tandem catalysis, two hugely promising capabilities for highly selective multistep-catalyzed reactions.
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  • YounJoon Jung
  • Seoul National University, Korea
  • "Charging dynamics of an ionic liquid electric double layer capacitor studied by molecular simulation"
    Biography and Abstract
Biography
YounJoon Jung graduated from Seoul National University summa cum laude with a Bachelor's degree in Chemistry in 1994, and received a Master’s degree in 1997 from the same university. He obtained his Ph. D from Massachusetts Institute of Technology in 2002, where he worked under the guidance of Robert J. Silbey. His Ph. D. work focused on developing theoretical formulations of the single molecule spectroscopy and electron transfer reactions in condensed media. He was awarded with Miller Fellowship from the University of California, Berkeley, where he worked as a Miller Research Fellow with David Chandler from 2002 to 2005. After working as a research associate with George Schatz and Mark Ratner at Northwestern University, he joined the Seoul National University in 2006. He was a visiting scholar at the University of California, Berkeley in 2012. He served as Vice Director of Center for Space-Time Molecular Dynamics from 2013 to 2016. He is a recipient of Kook Joe Shin Award from the Korean Chemical Society this year. He is a theoretical chemist, specialized in statistical mechanics. He uses both statistical mechanical theories and computer simulation methods to elucidate structure and dynamics of complex chemical systems, including glass transitions, ionic liquids, polymeric systems, and interfacial phenomena. Currently, he is developing a novel approach to non-equilibrium statistical mechanics.
Abstract
We investigate the charging phenomena of an electric double layer capacitor (EDLC) by conducting both equilibrium and non-equilibrium molecular dynamics (MD) simulations. A graphene electrode and 1-ethyl-3-methylimidazolium thiocyanate ([EMIM]+[SCN]−) ionic liquid were used as a system for the EDLC. We clarify the ionic layer structure and show that an abrupt change of the ionic layers leads to a high differential capacitance of the EDLC. The charging simulations reveal that the charging dynamics of the EDLC is highly dependent on the rearrangement of the ionic layer structure. Particularly, the electrode charge during the charging process is consistent with the perpendicular displacement of ionic liquid molecules. From this property, we analyze the contribution of each molecular ion to the electrode charge stored during charging. Charging of the EDLC is largely dependent on the desorption of the co-ions from the electrode rather than the adsorption of the counter-ions. In addition, the contribution of bulk ions to the charge stored in the EDLC is as important as that of ions adjacent to the electrode surface contrary to the conventional viewpoint. From these results, we identify the charging mechanism of the EDLC and discuss the relevance to experimental results. Our findings in the present study are expected to play an important role in designing an efficient EDLC with a novel perspective on the charging of the EDLC.
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  • Zhong-Yuan Lu
  • Jilin University, China
  • "Integrating coarse-grained dynamics simulation toolkits for polymer systems in GALAMOST"
    Biography and Abstract
Biography
Zhong-Yuan Lu received his PhD from Jilin University, China, in 1999. After a three-year post-doctoral work at the Department of Physics in University of Wuppertal, Germany, he joined the institute of Theoretical Chemistry at Jilin University in 2003 as an associate professor and has been a professor since 2005.
Abstract
We have developed a GPU-accelerated molecular simulation toolkit (GALAMOST) for use in coarse-grained simulations of polymer systems with several unique simulation tools proposed by us. A stochastic reaction model for use in coarse-grained dynamics simulations has been developed to cope with the problems related to the coupling between polymerization and chain diffusion. A soft patchy particle model, which is suitable to describe "soft" particles formed by star-like polymers and dendrimers, has been proposed to study their self-assembly structures. GALAMOST is written with CUDA and C++ languages for particularly running on NVIDIA GPUs. By the boost of GPUs, GALAMOST could enable researchers to investigate polymer systems at larger temporal and spatial scales with very low cost.
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Big data & Machine learning

  • Michele Ceriotti
  • Ecole Polytechnique Fédérale de Lausanne, Switzerland
  • (TBA)
    Biography and Abstract
[ Biography and Abstract ] will be announced
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  • Hyunju Chang
  • Korea Research Institute of Chemical Technology, Korea
  • (TBA)
    Biography and Abstract
[ Biography and Abstract ] will be announced
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  • Yousung Jung
  • Korea Advanced Institute of Science and Technology, Korea
  • "Exploring solid-state chemical space by machine learning"
    Biography and Abstract
Biography
Yousung Jung has received the B.S. degree from Seoul National University and Ph.D. in Theoretical Chemistry from University of California, Berkeley with Martin Head-Gordon. After a postdoctoral work at Caltech with Rudy Marcus, he joined the faculty at KAIST in 2009. His research interests involve the developments of density functional methods and their applications for the discovery of new energy materials. He is now combining these efforts with machine learning techniques to significantly further expand the search space and increase the prediction accuracy towards reliable materials design. He is the recipient of Pole Medal (2018, Asia-Pacific Association of Theoretical and Computational Chemists), KCS Young Physical Chemist Award (2017), Chemical Society of Japan Distinguished Lectureship Award (2015), and KCS-Wiley Young Chemist Award (2013).
Abstract
Discovery of a new material with desired properties is the ultimate goal of materials research. To date, a generally successful strategy has been to use chemical intuition and empirical rules to design new materials, but these conventional approaches require a significant amount of time and cost due to almost unlimited combinatorial possibilities of inorganic materials to explore in chemical space. A promising way to significantly accelerate the latter process is to incorporate all available knowledge and data to plan the synthesis of the next material. In this talk, I will present a few initial frameworks we have developed along this line to perform machine-learned density functional calculations, to predict the properties of a material using simple representations, and to generate new materials for a target property using materials deep generative model.
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  • Alexandre Tkatchenko
  • University of Luxembourg, Luxembourg
  • "Towards Universal Machine-Learning/Physics Model of Molecular Properties in Chemical Space"
    Biography and Abstract
Biography
Alexandre Tkatchenko is a Professor of Theoretical Chemical Physics at the University of Luxembourg and Visiting Professor at the Berlin Big Data Center. He obtained his bachelor degree in Computer Science and a Ph.D. in Physical Chemistry at the Universidad Autonoma Metropolitana in Mexico City. In 2008−2010, he was an Alexander von Humboldt Fellow at the Fritz Haber Institute of the Max Planck Society in Berlin. Between 2011 and 2016, he led an independent research group at the same institute. Tkatchenko has given more than 200 invited talks, seminars and colloquia worldwide, published more than 140 articles in peer-reviewed academic journals (h-index=55), and serves on the editorial boards of Physical Review Letters and Science Advances (an open-access journal in the Science family). He received a number of awards, including the Gerhard Ertl Young Investigator Award of the German Physical Society, and two flagship grants from the European Research Council: a Starting Grant in 2011 and a Consolidator Grant in 2017. His group pushes the boundaries of quantum mechanics, statistical mechanics, and machine learning to develop efficient methods to enable accurate modeling and obtain new insights into complex materials.
Abstract
"Mindless" learning from data has led to paradigm shifts in a multitude of disciplines. Can machine learning enable similar breakthroughs in _understanding_ (quantum) molecules and materials? Here, the two main challenges are: (1) the disproportionately large size of chemical space, even when only counting small organic drug-like candidates, (2) the complex nature of quantum interactions on different length and time scales. Aiming towards a unified machine learning (ML) model of quantum interactions, I will discuss the potential and challenges for using ML techniques in chemistry and physics. ML methods can not only accurately estimate molecular properties of large datasets, but they can also lead to new insights into chemical similarity, aromaticity, reactivity, and molecular dynamics [1]. However, to do so one needs to carefully unify spatial and temporal physical symmetries with purpose-designed ML methods [2,3]. While the potential of machine learning for revealing insights into complex quantum-chemical systems is high, many challenges remain. I will conclude my talk by discussing these challenges.

[1] K.T. Schütt, F. Arbabzadah, S. Chmiela, K.R. Müller, and A. Tkatchenko, Quantum-chemical insights from deep tensor neural networks. Nature Commun. 8, 13890 (2017).

[2] S. Chmiela, A. Tkatchenko, H.E. Sauceda, I. Poltavsky, K.T. Schütt, and K.-R. Müller, Machine Learning of Accurate Energy-Conserving Molecular Force Fields. Science Adv. 3, 1603015 (2017).

[3] S. Chmiela, H. E. Sauceda, K. R. Mueller, and A. Tkatchenko, Towards exact molecular dynamics simulations with machine-learned force fields. Nature Commun. 9, 3887 (2018).
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  • Koji Tsuda
  • The University of Tokyo, Japan
  • "Expanding the horizon of automated metamaterials discovery via quantum annealing"
    Biography and Abstract
Biography
Koji Tsuda received B.E., M.E., and Ph.D degrees from Kyoto University, Japan, in 1994, 1995, and 1998, respectively. Subsequently, he joined former Electrotechnical Laboratory (ETL), Tsukuba, Japan, as Research Scientist. When ETL was reorganized as AIST in 2001, he joined newly established Computational Biology Research Center, Tokyo, Japan. In 2000–2001, he worked at GMD FIRST (currently Fraunhofer FIRST) in Berlin, Germany, as Visiting Scientist. In 2003–2004 and 2006–2008, he worked at Max Planck Institute for Biological Cybernetics, Tübingen, Germany, first as Research Scientist and later as Project Leader. Currently, he is Professor at Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, the University of Tokyo. He is also affiliated with National Institute of Material Science (NIMS) and RIKEN Center for Advanced Intelligence Project.
Abstract
Complexity of materials designed by machine learning is currently limited by the inefficiency of classical computers. We show how quantum annealing can be incorporated into automated materials discovery and conduct a proof-of-principle study on designing complex thermofunctional metamaterials consisting of SiO2, SiC, and Poly(methyl methacrylate). The difficulty of this black-box optimization problem grows exponentially in the number of variables. Our quantum-classical hybrid algorithm consists of a factorization machine, an atomistic simulator, and a D-Wave 2000Q quantum annealer. Apart from the computational time needed for simulation, quantum annealing reduced the processing time to near zero regardless of the problem size. Our method was used to design complex structures of wavelength selective radiators showing much better concordance with the thermal atmospheric transparency window in comparison to existing human-designed alternatives. This result shows that quantum annealing can be used effectively in real-world design problems and indicates the direction of further applications.
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Soft matter

  • Changbong Hyeon
  • Korea Institute of Advanced Study, Korea
  • "Polymer physics perspective to chromatin inside cell nuclei"
    Biography and Abstract
Biography
Changbong Hyeon received his B.S. and M.S. degrees from Seoul National University and a Ph.D. in Chemical Physics from the University of Maryland at College Park. Following post-doctoral work at the Center for Theoretical Biological Physics in the University of California at San Diego, he joined the Chemistry department at Chung-Ang University in 2008 as an assistant professor and has been a professor at the Korea Institute for Advanced Study since 2010. His current research interests are in molecular motors, genome dynamics, and many other molecular/subcellular processes.
Abstract
Interphase chromatins are a polymer subjected to many physical constraints. We first illustrate dynamical arrest in a highly confined space by modeling chromosomes inside a nucleus as a homopolymer confined to a sphere of varying sizes. The onset of glassy dynamics might be the reason for the segregated chromosome organization in humans, whereas chromosomes of budding yeast are equilibrated with no clear signature of such organization. Modeling chromosomes using a model of heteropolymer based on the information of Hi-C data, we study its dynamics at different time and length scales. The local chromosome structures, exemplified by topologically associated domains, are highly dynamic with fast relaxation time (≲ 1 sec), whereas the long-range spatial reorganization of chromatin compartment is realized on a much longer time scale (≳ hour), providing the dynamic basis of cell-to-cell variability. Even when the dynamics is passive, the hierarchical organization of chromosome can explain many facets of chromatin dynamics. Active forces, modeled as a scalar noise, speed up the chromatin chain relaxation and push active loci towards the surface of chromosome territory, promoting the phase separation between inactive and active loci. Our findings of chromatin dynamics under passive condition can be used as a benchmark to understand the effects of other physical constraints on chromatin dynamics.
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  • Nobuyuki Matubayasi
  • Osaka University, Japan
  • "All-Atom Simulation of Polymer toward Rational Design of Separation Membrane"
    Biography and Abstract
Biography
1995: Ph.D., Rutgers University
1995: Assistant Professor, Kyoto University
2003: Associate Professor, Kyoto University
2014: Professor, Osaka University
Abstract
Polymer is effective as a material for separation membrane. The performance as a separation membrane is often governed by the dissolution free energy of the permeant, which reflects sensitively the atomic-level interaction between the permeant and polymer and the mode of aggregation of the polymer medium (crystalline vs amorphous, for example). The purpose of the present work is to formulate and apply a free-energy method with all-atom MD for assessing the extent of absorption of a small molecule into polymer. To do so, we treat the polymer as a solvent and the permeant as a solute and develop a theory of solutions to accurately and efficiently compute the free energy of dissolution. It is demonstrated that all-atom treatment is predictive for the free energy of water dissolution irrespective of the hydrophobicity and hydrophilicity of the polymer, and the computed free energy is discussed in connection to the structures of the polymers and their interactions with water.
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  • Devarajan Thirumalai
  • University of Texas at Austin, USA
  • "Human Chromosome Dynamics exhibits out of equilibrium Glassy Dynamics"
    Biography and Abstract
Biography
Thirumalai obtained his Ph.D from the University of Maryland in 1982, and did his post-doctoral work in Columbia University. In 1985 he joined the University of Maryland becoming a Distinguished University Professor. Since 2016 he is the Collie-Welch Professor in The University of Texas, at Austin.
Abstract
The structural organization of the condensed chromosomes is being revealed using chromosome conformation capture experiments and super-resolution imaging techniques. Fingerprints of their three-dimensional organization on length scale from about hundred kilo base pairs to millions of base pairs have emerged using advances in Hi-C and super-resolution microscopy. I will describe using a minimal Chromosome Copolymer Model (CCM) with two loci types corresponding to euchromatin and heterochromatin that the dynamics is similar to that observed in glasses. Chromosome organization is hierarchical involving the formation of chromosome droplets (CDs) on short genomic scale followed by coalescence of the CDs, reminiscent of Ostwald ripening. Glassy landscapes for the condensed active chromosomes might provide a balance between genomic conformational stability and biological functions.
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  • Arun Yethiraj
  • University of Wisconsin-Madison, USA
  • "Polymers in ionic liquids"
    Biography and Abstract
Biography
Arun Yethiraj was born in India and received his B. Tech. in Chemical Engineering at the Indian Institute of Technology, Bombay. He received an M.S. at Louisiana State University, a Ph.D. at North Carolina State University, working with Professor Carol Hall, and did postdoctoral research at the University of Illinois, working with Professor Kenneth Schweizer. He joined the faculty of the Chemistry department of the University of Wisconsin in 1993. His research is in the statistical mechanics of complex fluids. He is a senior editor of The Journal of Physical Chemistry. His hobbies include tennis, guitar, and marathon running.
Abstract
Ionic liquids have generated considerable excitement for their varied potential applications and their interesting physical properties. The viability of ionic liquids (ILs) in materials applications is limited by their lack of mechanical integrity, which may be provided by mixing them with a polymeric material. Recent experiments on polymers in ILs have unearthed a wealth of interesting phenomena that raise fundamental questions. This talk focuses on computational studies of PEO in imidazolium ILs. We develop a physically motivated first principles force field for PEO and [BMIM] [BF4]; this force field is in quantitative agreement with experiment with no adjustable parameters. Based on the same quantum calculations we develop a hierarchy of united atom models with decreasing resolution and increasing computational efficiency. Microsecond simulations are required to obtain converged properties of the polymer, which displays a combination of ring-like and extended conformations. The simulations show the existence of a lower critical solution temperature which arises from conformational restrictions on the polymer molecules at low temperatures
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  • Yaroslava G. Yingling
  • North Carolina State University, USA
  • (TBA)
    Biography and Abstract
[ Biography and Abstract ] will be announced
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Solid & Nanotechnology

  • Yun Hee Jang
  • Daegu Gyeongbuk Institute of Science and Technology, Korea
  • (TBA)
    Biography and Abstract
[ Biography and Abstract ] will be announced
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  • Jianwen Jiang
  • National University of Singapore, Singapore
  • "Computational Membrane Separations"
    Biography and Abstract
Biography
His research expertise is computational materials modeling and statistical thermodynamics, currently focused on nanoporous and membrane materials for energy, environmental, and pharmaceutical applications (e.g. carbon capture, water desalination and drug delivery). He has published over 200 technical manuscripts, as well as over 10 invited reviews and book chapters. He is a Fellow of the Royal Society of Chemistry (RSC), on the editorial boards of Scientific Reports, Frontier in Materials, Advances in Materials Research, and Colloid and Interface Science Communications, among others. He received the IES Prestigious Engineering Achievement Award from the Institution of Engineers, Singapore.
Abstract
Membranes are commonly utilized in chemical separations, and the fundamental understanding of membrane properties and separation processes is indispensable. With ever increasing computational power and resources, computations have become an indispensable tool in membrane science and engineering.

In this presentation, recent computational studies will be discussed for a wide variety of separations by both crystalline and amorphous membranes. For the crystalline membranes, the focus is on metal-organic frameworks (MOFs), which provide a wealth of opportunities for engineering new membrane materials and have been considered as versatile candidates for many important applications. I will discuss the current status of computational studies for biofuel pervaporation, CO2 capture, water desalination, etc. in MOF membranes. For the amorphous membranes, polymeric membranes will be discussed for gas and liquid separations, particularly the recently emerging organic solvent nanofiltration (OSN) through microporous polymer membranes.

The presentation will demonstrate that computations at an atomic/molecular level can secure the quantitative interpretation of experimental observations, provide microscopic insights from the bottom-up, and facilitate the development of new membranes.
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  • Byeong-Joo Lee
  • Pohang University of Science and Technology, Korea
  • "Computational Materials and Process Design of Advanced Alloys"
    Biography and Abstract
Biography
Byeong-Joo Lee received his BS, MS and Ph.D (1989) degrees in Materials Science and Engineering from Seoul National University. He has been a principal researcher at Korea Research Institute of Standards and Science until 2002 and joined Pohang University of Science and Technology (POSTECH) in 2002.
He is known with the development of thermodynamic database TCFE2000 and its upgraded versions for computational thermodynamics and with the development of the second nearest-neighbor MEAM and 2NNMEAM+Qeq interatomic potential formalisms for atomistic simulations on metallic, semiconducting and oxide systems.
He is an associate editor of the journal CALPHAD (1998~), a fellow of the Korean Academy of Science and Technology (2017~) and the National Academy of Engineering of Korea (2019~).
Abstract
Computational approaches such as first-principles calculations, atomistic simulations, phase field simulations, computational thermodynamics and finite element method simulations are widely used in metals and materials community. Even with their successful applications to understand materials phenomena and design new materials or processes, the gap between computational approaches and experimental data, which originates from the difference between computational and experimental conditions, limits the wider application of computational approaches. In this talk, some successful examples of computational materials and process design will be outlined, focusing on how to utilize the results of computational approaches. It will be emphasized that to notice the governing mechanism in materials phenomena from the effects of individual experimental variables on simulation results is more important rather than to make an effort to obtain a good agreement between simulations and experiments in phenomenological issues. It will be also emphasized that research efforts to extend the applicability of the computational approaches are continuously required.
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  • Aiichiro Nakano
  • University of Southern California, USA
  • "Toward exascale quantum-dynamical simulations and learning of nanosystems"
    Biography and Abstract
Biography
Aiichiro Nakano is a professor of Computer Science with joint appointments in Physics & Astronomy, Chemical Engineering & Materials Science, Biological Sciences, and the Collaboratory for Advanced Computing and Simulations at the University of Southern California (USC). He received a Ph.D. in physics from the University of Tokyo, Japan, in 1989. He has authored 401 refereed articles, including 262 journal papers, in the areas of scalable scientific algorithms, high-end parallel supercomputing, massive data visualization and analysis, and computational materials science.
Abstract
We have developed a divide-conquer-recombine algorithmic framework to make nonadiabatic quantum molecular dynamics (NAQMD) and reactive molecular dynamics (RMD) simulations scalable on the Nation’s first exascale supercomputer called Aurora A21. I will describe scalable NAQMD and RMD simulations, supported by machine-learning approaches, to study the growth, optical and mechanical control of material phases, and emergent physical properties and their optimization in various nanosystems including atomically-thin layered materials. This work was supported by U.S. Department of Energy and Office of Naval Research.
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Biological Systems

  • Xuhui Huang
  • Hong Kong University of Science and Technology, Hongkong
  • "Constructing Markov State Models to Elucidate the Functional Conformational Changes of Complex Biomolecules"
    Biography and Abstract
Biography
Xuhui Huang obtained his Ph.D. degree from Columbia University in 2006 with Prof. Bruce Berne. He did his postdoc research at Stanford University with Profs. Michael Levitt (Nobel Laureate in Chemistry) and Vijay Pande, He joined HKUST at an assistant professor in 2010, and received an early promotion to the tenured Associated Professor at Jan 2015, and between 2017 to 2019, he was the endowed Padma Harilela Associate Professor of Science at HKUST. At July 2019, he was promoted to full professor. His research is focused on developing and applying statistical mechanics-based algorithms to model conformational dynamics of complex biological systems. He has received a series of awards including the American Chemical Society OpenEye Outstanding Junior Faculty Award (2014); School Research Award, HKUST School of Science (2013), Hong Kong Research Grant Council Early Career Award (2013); and American Chemical Society CCG Excellence Award (2006). In 2017, he was selected as a founding member and currently serves as Vice President of Young Academy of Sciences of Hong Kong.
Abstract
Simulating biologically relevant timescales at atomic resolution is a challenging task since typical atomistic simulations are at least two orders of magnitude shorter. Markov State Models (MSMs), a kinetic network model, built from molecular dynamics (MD) simulations provide one means of overcoming this gap without sacrificing atomic resolution by extracting long time dynamics from short MD simulations through the coarse graining on the phase space and time. In this talk, I will demonstrate the power of kinetic network models by applying it to simulate the complex conformational changes, that occurs at tens to hundreds of microsecond timescales for a large RNA Polymerase II complex containing nearly half million atoms. Furthermore, I will introduce a new efficient dynamic clustering algorithm for the automatic construction of MSMs for multi-body systems. We have successfully applied this new algorithm to model the protein-ligand recognition and self-assembly of co-polymers. Finally, I will introduce a new algorithm using the projection operator approach to identify optimal kinetic lumping and recover slowest conformational dynamics of complex systems.
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  • Jaeyoung Sung
  • Chung-Ang University, Korea
  • "Chemical Dynamics in Living Cells"
    Biography and Abstract
Biography
Director, National Creative Research Initiative Center for Chemical Dynamics in Living Cells
Review Board Member, National Research Foundation of Korea
Winner of The 1st Kook-Joe Shin Academic Excellent Prize from KCS
Visiting Scholar, Massachusetts Institute of Technology
Postdoctoral Associate, Massachusetts Institute of Technology
Distinguished Ph.D. Dissertation Award, Seoul National University
Ph. D., M.S., B.S., Department of Chemistry, Seoul National University
Abstract
We introduce a new type of kinetic network model and kinetic theory for biological networks, enabling an accurate quantitative description of chemical dynamics of complex biological networks. An advantage of this approach is its applicability to biological networks producing biomolecules with arbitrary lifetime distributions to which the classical chemical kinetics, chemical master equation, and chemical Langevin equation are not directly applicable. Another advantage of our approach is that it enables quantitative investigation into biological networks composed of complicated chemical processes, e.g., multi-step or multi-channel reactions whose rates have both intrinsic and extrinsic fluctuation. We demonstrate the advantages of our approach by providing an unprecedented quantitative explanation of non-classical chemical dynamics observed in various biological systems including single enzymes, in vivo motor-protein multiplexes, and cell systems with various gene networks. Time-permitting, we will also discuss how cell signal response is related to the structure and dynamics of a signaling network and the lifetime distribution of biomolecules constituting the network.
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  • Yuan-Chung Cheng
  • National Taiwan University, Taiwan
  • "Molecular Modeling of Light Harvesting in Large Photosynthetic Pigment-Protein Complexes"
    Biography and Abstract
Biography
Prof. Yuan-Chung Cheng received his Ph.D. from the Department of Chemistry in the Massachusetts Institute of Technology in 2006, and he then worked as a Postdoctoral Research Associate from 2006 to 2009 in the University of California, Berkeley. In 2009, he returned to the Department of Chemistry in the National Taiwan University as an Assistant Professor, and he was promoted to the rank of Associated Professor in 2015. Prof. Cheng’s research interests covers a broad range in Theoretical Physical Chemistry, with an emphasis on the development of theoretical tools for quantum dynamics in condensed-phase molecular systems.
Abstract
Sophisticated pigment-protein complexes (PPCs) enable photosynthetic organisms to achieve remarkable near-unity quantum efficiency in the light reactions of photosynthesis, and a clear understanding of the molecular architecture and mechanisms responsible for the high efficiency could have significant implications in artificial photosynthesis and light harvesting. In this talk, I will present our theoretical investigations into excitation energy transfer (EET) in several photosynthetic systems. In particular, I will illustrate a first-principle approach that combines quantum chemistry calculations and molecular dynamics (MD) simulations to model chromophore-protein interactions in chlorophyll-binding PPCs. The theoretical framework, when carefully parameterized, is able to yield excellent agreement with experimental multidimensional electronic spectra in the water-soluble chlorophyll binding protein, leading to unprecedented details of energy relaxation processes in the PPC. We further apply the approach to investigate energy transfer dynamics in the dimeric Photosystem II core complex to reveal energy transfer pathways and the functional role of the dimeric structure in the complex . More importantly, the results allowed us to identify several key elements that play important roles in the speedup of energy trapping in photosynthesis. In summary, we have developed an effective approach that combines quantum chemical calculations, MD simulations, and the quantum dynamic method for describing spectra and energy transfer dynamics in PPCs. This framework should be applicable to general organic molecular aggregates and useful for the design of efficient light-harvesting materials.
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  • Shigehiko Hayashi
  • Shigehiko Hayashi Kyoto University, Japan
  • (TBA)
    Biography and Abstract
[ Biography and Abstract ] will be announced
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