In order to ensure a swift set-up of research environments, we provide start-up research funds to externally hired faculty members. In FY2019, we assigned start-up grants to 10 researchers for a total budget of 30.5 million JPY who went on to successfully launch their research.
FY2019 reports on newly appointed faculty start-ups
Design of novel transition metal catalysts using prediction by DFT calculation
The reporter started the investigation of high-performance catalyst molecules for activation of inactive bonds based on estimations from computational chemistry. DFT calculation using the AFIR method gave the key transition state structure for cleavage of inactive bonds with transition metal catalysts, and these results allowed to find high-performance catalyst candidates, which possibly activate inert bonds with a low energy barrier. The above-mentioned support fund was used to purchase the laboratory table, shelves, glassware, and reagents which are necessary for setting up the laboratory and conducting synthetic experiments. Additionally, this support helped to join a conference to gather information on the most recent developments in the design of catalysts.
Theoretical investigation of potential of pore space in coordination polymer as reaction field.
I conducted theoretical research aimed at the future fusion with information science at ICReDD. The main use of the startup support was to construct my computing environment. In order to evaluate their potential use as reaction fields, the interaction between molecules and a porous coordination polymer in and out of the pore was clarified by theoretical calculations . I also attempted collaboration research with experimental researchers and published papers [2, 3], one of which led to international joint research. I am planning to use the results to incorporate information science in the near future.
-  Coordinated water as new binding sites for the separation of light hydrocarbons in metal-organic framework with open metal sites; P. Veroorts, A. Schnemann, I. Hante, J. Pirillo, Y. Hijikata, T. Toyao, K. Kon, K-i. Shimizu, T. Nakamura, S-i. Noro, R. A. Fischer; ACS Appl. Mater. Interfaces, 2020, 12, 9448 – 9456 (Press Release).
 Trans-influence across a metal–metal bond of a paddle-wheel unit on interaction with gases in a metal-organic framework; J. Pirillo and Y. Hijikata; Inorg. Chem., 2020, 59, 1193 –1203 (Supplementary Cover)
-  Topological molecular nanocarbons: All-benzene catenane and trefoil knot; Y. Segawa, M. Kuwayama, Y. Hijikata, M. Fushimi, T. Nishihara, J. Pirillo, J. Shirasaki, N. Kubota, K. Itami; Science, 2019, 365, 273 – 276 (Press release (Japanese))
Application of synthetic hydrogel to the control of cellular behavior and functions
In multicellular organisms, cellular behavior and functions are strictly regulated by the extracellular environment to achieve the formation of complex organs and to maintain their homeostasis. Thus, proper regulation of the extracellular environment has long been considered a key to successful manipulation of cellular functions in biomedical engineering. Since polymer hydrogels mimic features of the extracellular environment in various tissues and can be used for cell culture and implantation, considerable efforts have been devoted to develop hydrogels with specific biological functions.
At ICReDD, I will aim to apply chemically synthesized materials to life science and medical research to deepen our understanding of biological systems and to develop novel therapeutics of incurable diseases. For these purposes, in FY2019, I aimed to develop an application of chemically synthesized hydrogels, in collaboration with the Gong group, to biological and medical research. This start-up fund covered the costs of various cell lines, cell culture reagents, the synthesis of hydrogels, molecular cell biology analyses, PCs for data analysis, and so on.
Theoretical design of novel catalysts based on cheap and abundant elements.
In collaboration with Dr. K. Sakaushi (NIMS, Japan) we have described the current state of the art of experimental and theoretical investigations of quantum effects in proton transfer electrode processes . Our work shed light on the understanding of the fundamental mechanisms of key chemical reactions for a sustainable energy cycle, such as oxygen reduction and hydrogen evolution reactions. Several domestic trips to NIMS, Tsukuba for scientific discussions and work with Dr. K. Sakaushi were very helpful for this research. In collaboration with the experimental group of Prof. Z. Huang (Univ. of Technology Sydney, Australia) we have developed a novel effective catalyst for the oxidative dehydrogenation of alkanes to olefins and demonstrated that the highly defective hexagonal boron nitride (h-BN) exhibits outstanding performance for the oxidative dehydrogenation of ethylbenzene to styrene . We are planning to extend this research in the future and together with Dr. S. Kumar (Taketsugu group) investigate a wide variety of possible oxidative dehydrogenation reactions at the defective h-BN catalyst. The results of our research have been presented at several international meetings and helped to establish a scientific collaboration with the experimental group of Prof. Dr. Knut Asmis (Leipzig Univ., Germany) with whom I am planning to start a new project on the investigation of the catalytic processes on size-selected metal oxide clusters. A novel single-phase structure of borophene (2D layer of boron) on an Ir(111) surface has been discovered via a combination of computer simulations at ICReDD and experiments in the groups of Dr. A. Preobrajenski (Lund University, Sweden) and Prof. Dr. A. Vinogradov (St Petersburg State Univ., Russia) . This leads us to plan a new investigation of the physicochemical properties of novel stable borophene structures.
-  K. Sakaushi, A. Lyalin, and T. Taketsugu, Observations and Theories of Quantum Effects in Proton Transfer Electrode Processes, Curr. Opin. Electrochem. 19, 96-105 (2020).
-  R. Han, J. Diao, S. Kumar, A. Lyalin, T. Taketsugu, Z. Huang, et al Boron nitride for enhanced oxidative dehydrogenation of ethylbenzene, accepted in J. Energy Chem. (2020).
-  N. A. Vinogradov, A. Lyalin, T. Taketsugu, A. S. Vinogradov, and A. Preobrajenski, Single-Phase Borophene on Ir(111): Formation, Structure and Decoupling from the Support, ACS Nano 13, 14511-14518 (2019).
Development of Novel Mechano-Responsive Luminescent Amphidynamic Crystals
The structural origin of multiscale phenomena, with physical manifestations ranging from the molecular to the macroscopic scale, remains largely undocumented. During this project term, we reported the discovery of a crystalline molecular rotor with rotationally modulated triplet emission that displays macroscopic dynamics in the form of crystal moving and/or jumping, also known as salient effects.
Thanks to this start-up funding, we also could make progress on several further research projects, which regard novel concepts for manipulating molecular dynamics in solid state materials.
Development of New Functional Materials Based on the Combination of Theoretical Chemistry and Automated Synthesis
In this study, the applicant has tried to develop new functional materials using theoretical chemistry along with automated synthesis. Firstly, screening of the synthesis of various functional materials was conducted by using the Artificial Force Induced Reaction (AFIR) method. Subsequently, preliminary experiments for the synthesis of polymeric materials were conducted according to the results of the theoretical calculations. In order to determine the molecular weight of the obtained compounds, a size exclusion chromatography system was newly introduced owing to the support of ICReDD (newly appointed faculty startup). Furthermore, the applicant has collaborated with the Varnek group (Prof. Sidorov and Dr. Gimadiev) to develop a database system for chemicals storage at ICReDD, which is now available and allows us to quickly find chemicals from the storage.
Discovery of novel reactions by Artificial Intelligence
Our research project is focused on the development of approaches of novel reaction generation by Machine learning (ML) and Artificial Intelligence (AI). Recently, the interest of chemoinformatics shifted from building models to predict some specific properties towards the prediction of structures possessing a desired property. We took this challenge one step further and developed a system to predict reactions of a given type. In addition to that, we have designed a number of “chemical filters” which help with the decision if a reaction is new and feasible. Using reactions extracted from US Patent database (>2.5 million reactions, public data) we have generated novel, chemically correct Suzuki coupling reactions. To ensure the feasibility of these reactions, fast DFT calculations have been performed. Thus, the benefits of the approach we propose have been demonstrated.
To carry out the project, we have purchased three high-end calculation workstations equipped with a GPU for neural network training. As a team with an overseas PI, we collaborate extensively with his team in the University of Strasbourg (France). In addition, we work together with the team in Kazan Federal University (Russia), the leading developers of reaction data management tools. We have invited Dr. Nugmanov from that team for a short-term stay for the joint development, which further reinforces our bonds with Kazan Federal University.
On the other hand, the project also motivated us to find collaborations within ICReDD. Prof. Ito has shared with us his experimental expertise and has suggested to further focus on Buchwald-Hartwig amination, an important reaction for organic synthesis. Prof. Maeda will help with further investigations of discovered reactions with the GRRM and AFIR methodologies. Prof. Takigawa as an expert in Machine Learning develops new types of neural networks to increase the success rate of the model. From now on, further developments will be advanced in this collaboration.
Learning over chemical networks
During the FY2019 I participated in group presentations and meetings on topological data analysis applied to molecular signature matching, modeling of populations over chemical reaction networks and design of suitable differentiable descriptors for learning over chemical reaction networks. Currently I am working on how to quantify the probabilistic uncertainty while performing learning over a set of chemical compounds or chemical reaction network.
Rational Design of Asymmetric Catalysis
Since I just joined the ICReDD in January 2020, the budget was mainly spent for purchasing required glassware, a cryostat, screening apparatus, and reagents. To pursue my research projects, a small library of acid catalysts was prepared. Currently, both experimental and computational studies of acid-catalyzed reactions are performed.
Mechanical properties of self-growing double network gels
Gong and coworkers have developed a double-network hydrogel that increases in strength and mass under repetitive mechanical loading (Matsuda et al., Science, 2019). The stretching of the hydrogel breaks bonds of extended polymers and thus creates radicals that drive the radical polymerization to produce new network strands. The objective of the proposed research is to make a molecular theory to predict the mechanical properties of self-growing gels as a function of the conditions to heal the crack and reinforce and strengthen the network.
As a first step towards this goal, we started from developing a scaling theory of the swelling and deswelling of single network gels in an extension of the non-affine tube model (Panyukov and Rubinstein, 1997) and the fractal loopy globule models (Ge et al., 2016). Strands of networks behave as liquid in small length scales because they are insensitive to the connectivity to the rest of the network and they behave as solid in large length scales because their fluctuations are suppressed by the potentials due to the crosslinks and entanglements. The length scale at the crossover between the two length regimes determines the mechanical properties of polymer gels. The topological potentials (that account for entanglements) decrease upon network swelling due to the separation of the neighboring strands, whereas the crosslinking potentials (that account for crosslinking) are constant. Our theory predicts that entangled networks (where their elasticity is dominated by the topological potentials) in the preparation condition become unentangled networks (where their elasticity is dominated by the crosslinking potentials) upon swelling. Upon network deswelling, network strands produce `entanglements’, while the topology of the network is fixed. This situation is analogous to concentrated solutions of ring polymers. We used this analogy to predict that network strands form fractal loopy globules. This theory is a necessary step to develop a molecular theory of the mechanical properties of self-growling double-network gels.
In FY2019, the start-up grant was used to the travel expense of T.Y. to Duke University, NC to closely collaborate with Prof. Michael Rubinstein.