Jun-Ya Hasegawa

The accuracy and transferability of machine-learning force fields (MLFFs) critically depend on the quality of the training database. Here, we propose a dataset merging strategy for efficiently constructing a transferable MLFF for pristine and oxygen-defective CeO2 surfaces. The proposed strategy is based on three key elements: (1) initiating on-the-fly training from small, less stable slab models to accelerate early stage convergence by sampling diverse high-energy configurations; (2) sampling diverse local structures by gradually increasing the temperature during molecular dynamics simulations while avoiding excessively rapid atomic motions and unphysically short contacts; and (3) merging independently generated datasets from slab models with different thicknesses and defect conditions to improve transferability. The resulting MLFF is validated on larger slab models containing 144 atoms and applied to structural optimization of pristine and oxygen-defective surfaces as well as lattice oxygen diffusion pathways on defective surfaces. The predicted pathways and energy barriers are in good agreement with density functional theory results, particularly for pathways involving relatively large structural and energetic changes. Furthermore, the merged MLFF was applied to ideal CeO2(111) slabs containing up to 5183 atoms, yielding only weak size dependence of the predicted vacancy-migration barrier. These results highlight that systematic dataset merging across model sizes and configurations provides a practical route to constructing transferable MLFFs for complex oxide surfaces.

Metal–organic framework (MOF) catalysts are promising platforms for hydrogen energy systems, enabling CO ₂ conversion to formic acid (HCOOH), a liquid organic hydrogen carrier (LOHC) for hydrogen storage and release. Density functional theory (DFT) calculations (M06‐2X/6‐31G(d)/LANL2DZ) are performed to investigate CO ₂ hydrogenation on PCN‐250(Fe) clusters featuring frustrated Lewis pair (FLP) sites formed by linker removal. The full hydrogenation pathway, including H ₂ adsorption, activation, and HCOOH formation, is explored, with HCOOH formation identified as the rate‐determining step. Activation barriers from large and small cluster models are consistent (10.0 and 9.4 kcal mol ⁻¹ ). Secondary metal substitution at the Fe ₂ MO node is screened using first‐ and second‐row transition metals (Mn–Zn and Tc–Cd). Results show electronic effects dominate first‐row metals, whereas steric effects govern second‐row systems. Kinetic volcano analysis identifies Cu(II) and Ru(III) as optimal catalysts for efficient CO ₂ hydrogenation, supporting rational design of MOF‐based hydrogen storage and conversion systems for sustainable energy applications.

The size of the reactive metal domain, termed an ‘ensemble’, in supported metal catalysts critically influences their catalytic activity. To maximize mass‐activity (MA), a deep understanding of the optimal catalytic environment is vital for the rational catalyst design concept, yet this remains challenging due to difficulties in synthesis and analysis especially in the sub‐nanometer regime. Herein, we have successfully synthesized a series of supported Rh species ranging from single‐atoms to (sub‐)nanometer clusters and nanoparticles. Their catalytic performance in the hydroformylation of styrene was evaluated. We discovered that the optimal structures are the Rh clusters, achieving a MA as high as 305.3 mol g _Rh‐total ⁻¹ h ⁻¹ , a value that surpasses previously reported values for both heterogeneous catalysts and the homogeneous Wilkinson's catalyst. Kinetic and theoretical analyses reveal that nanometer‐sized clusters provide a specific reaction environment that facilitates the balanced co‐adsorption of styrene, CO, and H thereby promoting hydroformylation. Our study highlights that a profound understanding of the optimal active structure is the key to maximizing the MA and advancing beyond simplistic atom efficiency considerations.

Single-atom catalysts (SACs) have attracted strong attention for reducing the amount of platinum used as electrocatalysts for the oxygen reduction reaction (ORR) in fuel cells. The ORR activity reportedly depends on the coordination environment, including the interface to the electrolyte solution. Thus, to elucidate the mechanism of electrochemical reactions, it is crucial to investigate the electric double layer (EDL) that consists of a charged electrode and an electrolyte solution. This study investigated ORR using two types of SACs in an aqueous CF3SO3H solution using our original method based on 3D-RISM-SCF (three-dimensional reference interaction-site model self-consistent-field). For the electrocatalyst models of SACs, Pt coordinated to four N atoms (PtN4) and to one N atom (PtN) were used. Computational results demonstrate that H2O2 and H2O are selectively generated using PtN4 and PtN, respectively, which is consistent with experimental observations. The EDL destabilizes all reaction intermediates and thereby governs the H2O generation with PtN. The degree of destabilization varies with the type of SAC and adsorbate; thus, we examined the underlying mechanism. Charge analysis revealed that the EDL suppresses Pt-to-adsorbate electron transfer, thereby contributing to the destabilization. This suppression effect depends on the catalyst–adsorbate combination, which accounts for the variations in destabilization. Furthermore, changes in solvation structure and electrostatic potential distribution indicated that the negatively charged adsorbates undergo repulsive interactions within the spatially nonuniform electrostatic environment generated by the EDL. Consequently, the O* and OH* intermediates using both PtN and PtN4 are destabilized as the electrode potential increases. The EDL effects on electrocatalytic activity are governed by the atomic-scale structural details of the reaction center.

An In-rich Cu-In intermetallic compound (IMC), CuIn₂, was accessed through an electrochemical nonequilibrium pathway and obtained as bulk Cu₂In core/CuIn₂ shell nanoparticles. CuIn₂ is thermodynamically metastable in the Cu-In binary phase diagram and has previously been observed only at Cu/In interfaces in sputtered thin films. Here, electrochemical reduction of a mixed metal oxide precursor (Cu₂In₂O₅) under aqueous CO₂ reduction conditions enables the formation of a metastable CuIn₂ shell encapsulating a Cu₂In core. The resulting biphasic IMC particles exhibit characteristic CO₂ reduction selectivity with strongly suppressed competing H₂ evolution. Density functional theory calculations suggested that CO adsorption at Cu bridge sites on the In-rich CuIn₂(121) surface competitively inhibits H adsorption, which may contribute to the suppressed H₂ evolution. This work demonstrates a nonequilibrium electrochemical route for accessing metastable IMC phase through oxygen-elimination-induced restructuring of a mixed metal oxide precursor.

Helical 6–7–6–6 fused acridiniums were synthesised via oxidative ring contraction of a helical azaheptalene. Due to the configurationally stable helicity, helical acridiniums exhibit chiroptical properties.

Ligand design for H₂ oxidation/production activity of Ni complex via tuning dihedral angle. Tetrahedral constraint leads to H₂ oxidation while square-planar constraint switches to H₂ production.

Amino-substituted benzofuran derivatives have attracted attention in recent years due to their remarkable biological activity.

The quest for bioactive molecules has long been confined to a rather narrow chemical space, limiting the discovery of uncharted chemical structures. Identifying such compounds is essential for uncovering previously unrecognized mechanisms of action and addressing limitations in conventional drug discovery. Here we unveil molecular nanocarbons, nanometer-scale, rigid, π-extended, and carbon-rich/hydrophobic frameworks widely studied in materials science, as a previously untapped class of bioactive agents capable of modulating protein–protein interactions (PPIs). We discovered a molecular nanocarbon that inhibits structurally conserved ligand–receptor pairs in insect diapause signaling (the ligand PND and its receptor PND-2) and human immune signaling (IL-17A and its receptor IL-17RA). The discovered planar nanocarbon compound, named clionene, disrupts both interactions, outperforming the flavonoid cyanidin in potency and selectivity. Structural modeling and molecular dynamics simulations reveal that clionene binds to a hydrophobic pocket at the IL-17A/IL-17RA interface via shape complementarity and π-interactions. These findings establish molecular nanocarbons as bioactive modulators of conserved PPIs, expanding the accessible chemical space for drug discovery and opening unconventional directions in cross-kingdom therapeutic targeting.