Journal of Computer Chemistry, Japan

[Published online Journal of Computer Chemistry, Japan -International Edition Vol.7, -, by J-STAGE]
<Title:> Density Functional Study of σ Bond Cleavage in P P Multiple Bond of Phosphinophosphinidene
<Author(s):> Toshiaki MATSUBARA, Keisuke SHIRASAKA
<Corresponding author E-Mill:> matsubara(at)kanagawa-u.ac.jp
<Abstract:> Recently, the synthesis of phosphinophosphinidene, which is a phosphorus analog of carbene, has been reported. Subsequent experimental reports have shown that phosphinophosphinidene acts as an electron acceptor. Because the terminal phosphorus atom inherently acts as an electron donor, chemical reactions may lead to the σ bond cleavage at the phosphorus atom through charge-transfer interaction. In this study, we explore the possibility of the σ bond cleavage in H H, C H, O H, N H, and B H bonds by means of the density functional method using the model molecules, H₂, CH₄, H₂O, NH₃ and BH₃. For H₂ and CH₄, the H H and the C H bonds were found to be broken at the single site of the terminal phosphorus atom by the charge-transfer interactions. The potential energy barrier of about 22 24 kcal/mol is similar to that for carbene, suggesting the possibility of σ bond cleavage in phosphinophosphinidene. In contrast, for H₂O and NH₃, the O H and N H bonds are broken at the two sites of both phosphorus atoms by the abstraction of hydrogen as a proton. In the case of BH₃, cleavage of the B H bond occurs easily at both the single and dual sites of the phosphorus atoms.
<Keywords:> Density functional method, Phosphinophosphinidene, σ Bond cleavage, Reaction mechanism
<URL:> https://www.jstage.jst.go.jp/article/jccjie/7/0/7_2020-0003/_html

[Published online Journal of Computer Chemistry, Japan -International Edition Vol.7, -, by J-STAGE]
<Title:> Materials Informatics Approach to Predictive Models for Elastic Modulus of Polypropylene Composites Reinforced by Fillers and Additives
<Author(s):> Yuko IKEDA, Michihiro OKUYAMA, Yukihito NAKAZAWA, Tomohiro OSHIYAMA, Kimito FUNATSU
<Corresponding author E-Mill:> tomohiro.oshiyama(at)konicaminolta.com
<Abstract:> Advanced processes are useful when developing polymer composites because there are an enormous number of possible combinations of fillers and additives to realize polymers with desired properties. Materials informatics is a data-driven approach to find novel materials or a suitable combination of materials from material data sheets. Here, we used materials informatics to construct a predictive model for the elastic modulus of polypropylene composites. To apply materials informatics to existing experimental data, we described explanatory variables by a combination of 0 and 1 representing polypropylene, or by the content ratio of filler and additive, without using materials property data. We constructed a predictive model for the elastic modulus of polypropylene composites using a partial least square regression model with dummy variables. To validate the predictive model, comparisons were made between measured and predicted elastic moduli for eight new polypropylene composites. The residual was less than 300 MPa for the range 1,000 3,000 MPa. We improved the accuracy of the prediction for composites with high filler content ratio by applying a nonlinear support vector regression model. The predictive model is therefore useful for identifying suitable combinations of polypropylene, filler and additive to achieve a desired elastic modulus.
<Keywords:> Materials informatics, Elastic modulus, Polypropylene composite, PLS, SVR, Dummy variables
<URL:> https://www.jstage.jst.go.jp/article/jccjie/7/0/7_2020-0007/_html

[Published online Journal of Computer Chemistry, Japan Vol.19, 172-174, by J-STAGE]
<Title:> 導電性高分子系太陽電池のキャリア発生と発電機構に関する検討
<Author(s):> 中村　潤之介, 原岡　壮馬 , 成島　和男
<Corresponding author E-Mill:> narushim(at)ube-k.ac.jp
<Abstract:> Organic solar cells are flexible elements that offer benefits such as low cost, light weight, and applicability. For this study, quantum chemistry calculations of cells using conductive polymers were performed. Poly (3,4-ethylenedioxythiophene)-poly (styrenesulfonate)(PEDOT:PSS), phthalocyanine and fullerene C₆₀ were used as semiconductors. Generation of carriers (conduction electrons and holes) was expected in both the ground state and the excited state. When MgAg and Al were selected for the electrodes, the energy diagram was found to have an ideal step structure. The organic solar cell was designed from the energy diagram of the whole layer that constituted the solar cell.
<Keywords:> Organic solar cells, Conductive polymer, Quantum chemistry calculations, Generation of carriers, Energy diagram
<URL:> https://www.jstage.jst.go.jp/article/jccj/19/4/19_2021-0007/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.19, 164-166, by J-STAGE]
<Title:> 人工知能を用いた打音試験による片状及び球状黒鉛鋳鉄の材質判定
<Author(s):> 篠原　美月, 内田　希, 岩見　祐貴, 平本　雄一, 加藤　雅也, 菅野　利猛
<Corresponding author E-Mill:> mitsuki_shinohara(at)gmail.com
<Abstract:> Tapping test is an inspection method that determines the presence or absence of abnormality in a specimen based on the difference in the sound when tapping a material. This method is used to inspect buildings and railway vehicles. It is considered that this method can be used for quality evaluation of cast iron. However, although the tapping test has the advantage of being able to be performed non-destructively and simply, it also has the disadvantage of requiring a worker who can distinguish sounds. In order to solve this problem, we introduced a neural network and studied whether it is possible to judge the quality of cast iron by learning the tapping sound of cast iron.
<Keywords:> Flake graphite cast iron, Spheroidal graphite cast iron, Neural network, Tapping test
<URL:> https://www.jstage.jst.go.jp/article/jccj/19/4/19_2021-0016/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.19, 167-168, by J-STAGE]
<Title:> 人工知能による片状黒鉛鋳鉄の黒鉛組織の判定
<Author(s):> 池原　瑞生, 内田　希, 岩見　祐貴, 加藤　雅也, 菅野　利猛
<Corresponding author E-Mill:> s183195(at)stn.nagaokaut.ac.jp
<Abstract:> The graphite structure of flake graphite cast iron is classified into 5 types of A,B,C,D,E or 6 types including chill. In usually, type A is good quality and type D is poor quality. As the proportion of D-type graphite increases, the tensile strength decreases.Inspection of graphite structure is one of the quality evaluations. However, there is no method for numerically determining the graphite structure of flake graphite cast iron. In this study, we created an AI that determines 6 types of graphite structure from A to chill using a Convolutional Neural Network (CNN).The created AI judged the graphite structure photographs that not used for learning with an average correct answer rate of 97.5%. In addition, when the graphite structure of one sample was analyzed by AI, it was confirmed numerically that the graphite structure deteriorated.
<Keywords:> Convolutional Neural Network, Flake graphite cast iron, Graphite structure
<URL:> https://www.jstage.jst.go.jp/article/jccj/19/4/19_2021-0017/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.19, 169-171, by J-STAGE]
<Title:> 位相幾何的データ分析によるブロックコポリマー準安定構造の自由エネルギー推定
<Author(s):> 本武　陽一, 山中　貞人, 青柳　岳司, 大西　立顕, 福水　健次
<Corresponding author E-Mill:> mototake(at)ism.ac.jp
<Abstract:> Block copolymers with repulsive sub-chains form a variety of domain structures called microphase-separated structures. Most microphase-separated structures have a periodic patterned structure while in a stable state. On the other hand, metastable states with an acyclic structure and sufficiently long lifetimes are often observed around the configuration space of the periodic structures. In this study, we focused on the double gyroid structure a type of microphase-separated structure and built a model to predict free energy using topological data analysis (TDA), which has recently proven useful for analyzing acyclic compound structures such as the amorphous structure of glass. The model obtained can predict the free energy of the metastable state of the double-gyroid structure using persistent homology, which is one of the features of TDA.
<Keywords:> topological data analysis, Persistent homology, Double-gyroid, Microphase separation, Block copolymers
<URL:> https://www.jstage.jst.go.jp/article/jccj/19/4/19_2021-0009/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.19, 151-153, by J-STAGE]
<Title:> Ni-ZSM-5によるメタノール酸化反応の理論的研究
<Author(s):> 田中　靖也, Mahyuddin　Muhammad Haris, 塩田　淑仁, 吉澤　一成
<Corresponding author E-Mill:> s.tanaka(at)ms.ifoc.kyushu-u.ac.jp
<Abstract:> Ni-ZSM-5 is a promising catalyst for the conversion of methane to methanol. In many methane oxidation catalysts, the problem is that the oxidation reaction continues after methane oxidation (over-oxidation). The ease of over-oxidation is an important factor in evaluating the performance of methane oxidation catalysts. In the present study, we performed density functional theory (DFT) calculation to evaluate the two reaction pathways for the oxidation of methanol to formaldehyde by Ni-ZSM-5. DFT calculations indicated that the activation energies for the C-H bond cleavage are more than 40 kcal/mol in the reaction pathways. After methane oxidation the second step reaction corresponding to the methanol oxidation by [Ni-O-Ni]²⁺ is unlikely to occur.
<Keywords:> Keyword Methanol, Formaldehyde, Over-oxidation, Ni-ZSM-5, DFT calculation
<URL:> https://www.jstage.jst.go.jp/article/jccj/19/4/19_2021-0004/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.19, -, by J-STAGE]
<Title:> Performance Research of Clustering Methods for Detecting State Transition Trajectories in Hemoglobin
<Author(s):> Kei TAKAMI, Yukichi KITAMURA, Masataka NAGAOKA
<Corresponding author E-Mill:> kitamura.yuhkichi(at)shizuoka.ac.jp
<Abstract:> The time-series clustering method is one of unsupervised machine learning techniques that classify time-series data. In this article, we applied three methods to the clustering analysis for 200 molecular dynamics (MD) trajectories of human adult hemoglobin (HbA), and have reported their clustering performances for detecting the T-R state transition trajectories (Traj_T-R). By compared with their silhouette indices, we have discussed the proper clustering conditions.
<Keywords:> Keyword Time-series clustering method, Dynamic time warping distance, Silhouette analysis, Hemoglobin, Allostery regulation
<URL:> https://www.jstage.jst.go.jp/article/jccj/19/4/19_2021-0014/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.19, 158-160, by J-STAGE]
<Title:> ヘテロ原子を含んだ単分子接合の導電性に関するグラフ理論的研究
<Author(s):> 岡澤　一樹, 辻　雄太, 吉澤　一成
<Corresponding author E-Mill:> kazunari(at)ms.ifoc.kyushu-u.ac.jp
<Abstract:> Single-molecule junctions have unique electron transport properties that are not found in solids or polymers. Graph theoretical approaches have been used to predict whether conductivity in single-molecule junctions. In this paper, the change in single-molecule conductivity when carbon atoms in alternant hydrocarbons are replaced with heteroatoms is investigated by using the graph-theoretic path-counting method. The results predicted by graph theory are consistent with those obtained by using nonequilibrium Green’s function combined with the H ckel method.
<Keywords:> Heteroatom-containing single-molecular junction, π-conjugated system, Graph theory, H ckel method
<URL:> https://www.jstage.jst.go.jp/article/jccj/19/4/19_2021-0013/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.19, 161-163, by J-STAGE]
<Title:> 分子動力学シミュレーションによる嗅覚受容体タンパク質mOR-EGと香り分子オイゲノールの結合解析
<Author(s):> 岡本　千怜, 安藤　耕司
<Corresponding author E-Mill:> ando_k(at)lab.twcu.ac.jp
<Abstract:> Molecular dynamics (MD) simulations were used to analyze the effect of the odorant molecule eugenol on the olfactory receptor protein mOR-EG and the dynamic correlation between amino acid residues around the binding site due to ligand binding. When eugenol hydrogen-bonded with Ser 113 of mOR-EG, the dynamic correlation with amino acid residues 213-218 on the adjacent α-helix increased within 10 ps. In particular, the correlation between Ser 113 and Leu 217 showed characteristic oscillations between 10 ps and 30 ps. The correlation with Leu 217 shifted toward residues closer to the G protein over time. Correlation with amino acids on the other side of the membrane was also observed, suggesting the contribution of collective protein motion
<Keywords:> Molecular dynamics simulation, Olfactory receptor, Membrane protein, Dynamical cross correlation
<URL:> https://www.jstage.jst.go.jp/article/jccj/19/4/19_2021-0005/_article/-char/ja/