カテゴリー: 未分類

[Published online Journal of Computer Chemistry, Japan Vol.23, 24-26, by J-STAGE]
<Title:> 開始剤ラジカルの極性パラメータの算出
<Author(s):> 川内　進
<Corresponding author E-Mill:> skawauchi(at)quemix.com
<Abstract:> This paper describes a method for calculating the intrinsic e parameter of initiator radicals by applying the intrinsic Q-e scheme to the addition reaction between initiator radicals and monomers. Furthermore, DFT calculations show that there is a good relationship between the intrinsic e-value of initiator radicals and their electronegativity and Hammett constant, indicating that the e-value is a suitable parameter to describe the polar effect of initiator radicals.
<Keywords:> キーワード Radical polymerization, Initiator radical, Q-e value, polarity parameter, DFT calculation
<URL:> https://www.jstage.jst.go.jp/article/jccj/23/1/23_2024-0003/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.23, A9-A14, by J-STAGE]
<Title:> ポリマーラジカルのQ-e値の初めての算出
<Author(s):> 川内　進
<Corresponding author E-Mill:> skawauchi(at)quemix.com
<Abstract:> Using our recently derived intrinsic Q-e scheme, unknown reactivity ratios of monomer pairs can be expressed without arbitrariness using only the reactivity ratios of the target and reference monomers, resulting in a high prediction accuracy of reactivity ratios. Furthermore, the Q-e values of polymer radicals and monomers can be calculated separately for the first time. In this paper, we introduce the intrinsic Q-e scheme, followed by the calculation of Q-e values for monomers and radicals.
<Keywords:>
<URL:> https://www.jstage.jst.go.jp/article/jccj/23/1/23_2023-0026/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.23, 19-23, by J-STAGE]
<Title:> Machine Learning in Catalysis: Analysis and Prediction of CO Adsorption on Multi-elemental Nanoparticle using Metal Coordination-based Regression Model
<Author(s):> Susan Menez ASPERA, Gerardo Valadez HUERTA, Yusuke NANBA, Kaoru HISAMA, Michihisa KOYAMA
<Corresponding author E-Mill:> aspera_susan(at)shinshu-u.ac.jp
<Abstract:> Information about molecular adsorption strength is important in every catalytic reaction. The ability to compare and determine relevant molecular active sites of interaction is necessary for fast screening of potential catalysts specially in a vast spectrum of probable candidates. In this study, we used the metal-coordination of the adsorption sites as a descriptor of the adsorption energy of CO on the PtRuIr ternary alloy nanoparticle. Using multiple regression model, we are able to predict the adsorption energy and specify some important descriptors that controls the strength of CO adsorption energy. This will enable a fast prediction of CO adsorption energy on PtRuIr nanoparticles with varying compositions and possible different morphologies using only the information of the structure of the catalyst. And open up the possibility of predicting adsorption interaction of other combinations of alloys with higher number of metallic compositions for fast screening of appropriate molecule-surface interaction.
<Keywords:> multi-elemental nanoparticle alloy, machine learning, generalized coordination number, CO adsorption, PtRuIr ternary alloy, multiple regression
<URL:> https://www.jstage.jst.go.jp/article/jccj/23/1/23_2024-0006/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.23, 13-18, by J-STAGE]
<Title:> New LCAO-MO Method for Molecules in The Arbitrary Magnetic Field
<Author(s):> Katsumi NAKAGAWA
<Corresponding author E-Mill:> hbo59418(at)kwansei.ac.jp
<Abstract:> The Hartree-Fock-Slater (HFS) equation including magnetic interaction was solved full-numerically by the LCAO-MO method. Firstly, the AOs of each atom in a molecule were obtained by solving the HFS equation dedicated to the atom. This equation includes the same magnetic interaction as the equation of the molecule and virtual “well potential” to adjust the spreads of AOs. In this method, the Fock operator for the atom is expressed as a numerical matrix and the equation can be solved by a mathematical solver of the numerical eigenvalue problem. Then an MO is obtained by using these AOs as bases of the LCAO-MO method. AOs naturally have suitable complex phases for the MO to satisfy gauge invariance. To evaluate the new method, magnetic shielding constants σ were calculated for various small molecules comprising 2-3 atoms of second-row element and hydrogen atoms. The “well potential” of each atom was adjusted systematically and calculated σ showed fairly good agreement with experimental values.
<Keywords:> LCAO-MO, magnetic field, DV-Xα, well potential, complex phase, gauge invariance, magnetic shielding constant
<URL:> https://www.jstage.jst.go.jp/article/jccj/23/1/23_2024-0002/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.23, 9-12, by J-STAGE]
<Title:> キャリアの視点から見た有機太陽電池の発電機構の考察
<Author(s):> 成島　和男, 藤笠　舜大, 岡田　直之
<Corresponding author E-Mill:> narushim(at)ube-k.ac.jp
<Abstract:> Organic thin-film solar cells, which have attracted attention as a renewable energy source in recent years, provide important benefits of being light weight, flexible, inexpensive, and produced from a virtually inexhaustible resource. This report explains the power generation principle of organic thin-film solar cells by particularly addressing the movement of conduction electrons and holes, based on knowledge introduced in a paper and letters presented at this conference, augmented with findings from the calculation results reported here. The following important findings must be considered. (1) Regarding the bimolecular system of phthalocyanine and fullerene C₆₀, even in the configuration calculated for this study, some parts of the phthalocyanine molecule had low probability of electron cloud existence. (2) For this configuration, a change was found in the electronic state in the excited state compared to the ground state. The power generation mechanism of organic thin-film solar cells was considered from the carrier perspective.
<Keywords:> Organic thin-solar cells, Quantum chemistry calculations, Electron cloud, Power generation mechanism, Carrier perspective.
<URL:> https://www.jstage.jst.go.jp/article/jccj/23/1/23_2024-0004/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.23, 1-3, by J-STAGE]
<Title:> p-フェニルエチニル化合物群の π 電子共役の強さを適正に評価する量子化学計算の探索
<Author(s):> 鈴木　椋子, 千葉　康平, 奥山　克彦
<Corresponding author E-Mill:> okuyama.katsuhiko(at)nihon-u.ac.jp
<Abstract:> We searched for quantum chemical calculations that would properly evaluate strength in the π-electron conjugation of a group of p-phenylethynyl compounds determined by molecular spectroscopy with error ranges. The target molecules are tolane, 1,4-diphenylbutadiyne and 1,4-bis(phenylethynyl)benzene. Quantum chemical calculations were performed with B3LYP, CAM-B3LYP, ωB97X-D, M06-2X, and MP2 for theory, and basis sets were explored among the combinations 6-311++G(d) cc-pVDZ, and aug-cc-pVDZ. Because B3LYP calculation is considered to be unskilled at evaluating dispersion force, a dispersion force correction term is added to B3LYP calculation. The least of square of the difference in the strength between observed and calculated was given by calculations with M06-2X/aug-cc-pVDZ. It has, however, often been reported that M06-2X undergoes inappropriate structural optimization. In calculations for 1,4-diphenylbutadiyne, M06-2X was not giving systematic uniform results. Overall, ωB97X-D was a functional function corrected for long-range and dispersion force correction, and it was considered to give good results together with CAM-B3LYP corrected for dispersion force.
<Keywords:> Keyword p-phenylethynyl compounds, strength in π-electron conjugation, dispersion force correction, ωB97X-D/aug-cc-pVDZ, molecular spectroscopy
<URL:> https://www.jstage.jst.go.jp/article/jccj/23/1/23_2023-0044/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.23, 4-8, by J-STAGE]
<Title:> FMOプログラムABINIT-MPの整備状況2023
<Author(s):> 望月　祐志, 中野　達也, 坂倉　耕太, 奥脇　弘次, 土居　英男, 加藤　季広, 滝沢　寛之, 成瀬　彰, 大島　聡史, 星野　哲也, 片桐　孝洋
<Corresponding author E-Mill:> fullmoon(at)rikkyo.ac.jp
<Abstract:> In August 2023, we released the latest version of our ABINIT-MP program, Open Version 2 Revision 8. In this version, the most commonly used FMO-MP2 calculations are even faster than in the previous Revision 4. It is now also possible to calculate excitation and ionization energies for regions of interest. Improved interaction analysis is also available. In addition, we have started GPU-oriented modifications. In this preliminary report, we present the current status of ABINIT-MP.
<Keywords:> キーワードFragment molecular orbital, FMO, ABINIT-MP, Supercomputer, A64FX, SX-Aurora TSUBASA, GPU
<URL:> https://www.jstage.jst.go.jp/article/jccj/23/1/23_2024-0001/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.22, 41-49, by J-STAGE]
<Title:> スピン反転凍結軌道解析を用いた円錐交差構造の支配因子に関する理論的研究
<Author(s):> 五十幡　康弘, 吉川　武司, 中井　浩巳, 小川　賢太郎, 坂田　健
<Corresponding author E-Mill:> ikabata.yasuhiro.lz(at)tut.jp
<Abstract:> S₀/S₁極小エネルギー円錐交差(MECI)の支配因子を評価するために，スピン反転時間依存密度汎関数理論に対する凍結軌道解析(FZOA)の波動関数と励起エネルギーを導出した．スピン反転法に特有のスピン汚染を避けるため，定式化においてスピン完全法を適用した．数値計算の結果，「HOMO-LUMO交換積分がほぼ0となる」，「HOMO-LUMOギャップの上限値はHOMO，LUMOが関係するCoulomb積分によって定まる」というS₀/S₁ MECIの支配因子を発見した．本論文では，FZOAについて概説するとともに，スピン反転法におけるFZOAの定式化について述べる．導出したスピン反転FZOAの式をエチレンとウラシルに適用した結果に基づいて，励起エネルギー成分に基づく支配因子の発見，S₀/S₁ MECIの電子構造，これらの制限付き開殻法における結合係数への依存性について解説する．
<Keywords:> Conical intersection, Time-dependent density functional theory, Spin-flip method, Frozen orbital analysis, Restricted open-shell method
<URL:> https://www.jstage.jst.go.jp/article/jccj/22/2/22_2023-0021/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.22, 34-36, by J-STAGE]
<Title:> 分子軌道エネルギーを用いた機械学習によるオクタノール/水分配係数log Pの予測
<Author(s):> 寺前　裕之
<Corresponding author E-Mill:> teramae(at)gmail.com
<Abstract:> Octanol/water partition coefficient, log P, is an important parameter in classical QSAR. The new method using machine learning which we propose uses only the molecular orbital energy as an explanatory variable and does not include log P. Therefore, since the log P value can be predicted using the molecular orbital energy, we speculated that log P may not be necessary as a result if sufficient number of molecular orbital energies would be given as parameters.
<Keywords:> octanol/water partition coefficient, equilibrium geometries, eigenvalues of molecular orbital, machine learning, molecular orbital energies
<URL:> https://www.jstage.jst.go.jp/article/jccj/22/2/22_2023-0022/_article/-char/ja/

[Published online Journal of Computer Chemistry, Japan Vol.22, 37-40, by J-STAGE]
<Title:> シンボリック回帰における外挿性の検証とペロブスカイト触媒への応用
<Author(s):> 磯田　拓哉, 高橋　栞, 中野　匡彦, 中嶋　裕也, 清野　淳司
<Corresponding author E-Mill:> j-seino(at)aoni.waseda.jp
<Abstract:> The recent advances in artificial intelligence (AI) have accelerated the development of data-driven modeling. Complex machine learning models often lack interpretability. Symbolic regression, particularly in the fields of mathematics and physics, has provided alternative models that are interpretable and have excellent extrapolation capabilities. In this study, we investigated the potential of symbolic regression in chemistry, specifically in the exploration of new materials through extrapolation. We conducted fundamental verification of extrapolation and applied research on the exploration of perovskite catalysts using the recursive-LASSO-based symbolic regression. Our results suggested that symbolic regression exhibits superior extrapolation performance and interpretability compared to conventional machine learning methods.
<Keywords:> Machine Learning, Materials Informatics, Symbolic Regression, Material Science, Perovskite Catalysts.
<URL:> https://www.jstage.jst.go.jp/article/jccj/22/2/22_2023-0028/_article/-char/ja/