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.

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.

Gaussian and GAMESS, which are calculation codes for the ab initio molecular orbital method, can be used by simply specifying a basis set name such as 6-31G. However, if an individual basis set with a common name does not have the same parameter set, the calculations with the two codes will each produce a different result. Previously, we used Gaussian and GAMESS for STO-3G calculations of hydrides containing third-period elements and compared the results [J. Comput. Chem. Jpn., 18, 194 (2019)]. In this study, we used 6-31G and 6-31G* for 36 molecules containing a first- to fourth-period element (H, Be, N, Ne, Na-Kr) and compared the results calculated using the two codes. For molecules containing a first- to third-period element (H, Be, N, Ne, Na-Ar) except Si, the optimized structure and total energy obtained with Gaussian and GAMESS were almost the same, whereas the two codes gave different results for K, Ca, and Ga-Kr because the basis parameters used in the two codes are different. On the other hand, the results for the Sc-Zn were in agreement. When the results calculated using Gaussian and GAMESS codes are compared or combined, it is necessary to severe check whether or not the input data produces a sufficiently accurate calculation result.

The amino acid sequence of a protein is closely related to its structure and function. This is especially true for particular structural features called motifs, which are well-reserved sites in genome sequences. Biological data, such as the data for biopolymers, are rapidly increasing. Constructing a database for efficient analysis is important for identifying the structure and function of unknown biological data. Here, we constructed a protein-gene motif dictionary system for several model species using NoSQL, a database management system. This dictionary stored protein sequence motifs based on PROSITE, along with their corresponding mRNA sequences. Additionally, the database stored 3D structural information of the corresponding protein sequence motifs. The protein-gene dictionary has 49,265 registered entries, 120,047 sequence motifs, and 57,452 3D structural motifs from 7 model species. Software tools with graphical user interface were also developed to assist with intuitive search and analysis using the system. As a result, we discovered that zinc protease motif had co-occurrence with the cysteine switch motif. It was followed by the cysteine switch motif with a gap of 117 to 293 amino acids, however, its 3D Euclidean distance was preserved at around 12 Å.

We have performed density functional theory (DFT) calculations of C=C epoxidation and C−H hydroxylation of propene using a model of Fe(IV)OCl–porphyrin cation radical complexes with fluorine and methyl groups as meso-substituents of the porphyrin ring. By gas-phase DFT calculations, it is found that fluorine substitution enhances the reactivity. According to detailed electronic feature analysis of the reactant complexes and transition states, electron-withdrawing groups at the meso-position stabilize the electron acceptor orbital of the complex more than the electron donation orbital of the substrate, leading to a decrease in the energy gap between these orbitals, and a lower energy barrier. More importantly, fluorine substitution for the pull effect makes hydroxylation favorable, whereas methyl substitution makes epoxidation preferable. The selective oxidation reactivity of Fe(IV)OCl–porphyrin is largely ascribed to the effect of meso-substitution on the amount of electron transfer from propene to Fe(IV)OCl–porphyrin. Additionally, we analyzed intersystem crossing between the quartet and sextet spin states using the potential energy surfaces (PESs), and the crossing seam between the quartet and sextet PESs occurs at around transition state TS1.