Takuya Taniguchi

The mechanical motion of materials has been increasingly explored in terms of bending and expansion/contraction. However, the locomotion of materials has been limited. Here, we report walking and rolling locomotion of chiral azobenzene crystals, induced thermally by a reversible single-crystal-to-single-crystal phase transition. Long plate-like crystals with thickness gradient in the longitudinal direction walk slowly, like an inchworm, by repeated bending and straightening under heating and coo

Abstract Structural phase transitions induced by external stimuli such as temperature, pressure, electromagnetic fields, and light play crucial roles in controlling the functions of solid-state materials. Here we report a new phase transition, referred to as the photo-triggered phase transition, of a photochromic chiral salicylideneamine crystal. The crystal, which exhibits a thermal single-crystal-to-single-crystal phase transition which is reversible upon heating and cooling, transforms to the

Superelasticity is a type of elastic response to an applied external force, caused by a phase transformation. Actuation of materials is also an elastic response to external stimuli such as light and heat. Although both superelasticity and actuation are deformations resulting from stimulus-induced stress, there is a phenomenological difference between the two with respect to whether force is an input or an output. Here, we report that a molecular crystal manifests superelasticity during photo-act

Photomechanical crystals are interesting from both basic and applied perspectives, and thus it is important to develop new examples. We investigated the photomechanical bending behaviour of a photochromic crystal of a dibenzobarrelene derivative. When a plate-like crystal was irradiated with ultraviolet (UV) light at 365 nm, two-step bending was observed. In the first step, the crystal quickly bent away from the light source, with an accompanying crystal colour change from colourless to purple.

The bending deflection and blocking force of photo-bending crystals of different sizes were experimentally measured at various light intensities, and then modeled by the machine learning-based regression.

In material informatics, the representation of the material structure is fundamentally essential to obtaining better prediction results, and graph representation has attracted much attention in recent years. Molecular crystals can be graphically represented in molecular and crystal representations, but a comparison of which representation is more effective has not been examined. In this study, we compared the prediction accuracy between molecular and crystal graphs for band gap prediction. The r

Elastic moduli of molecular crystals can be predicted using pretrained neural network potential, showing sufficient agreement with experimental data.

Mechanically responsive materials are promising as next-generation actuators for soft robotics, but have scarce reports on the statistical modeling of the actuation behavior. This research reports on the development and modeling of the photomechanical bending behavior of hybrid silicones mixed with azobenzene powder. The photo-responsive hybrid silicone bends away from the light source upon light irradiation when a thin paper is attached on the hybrid silicone. The time courses of bending behavi

The structural differences between chiral and racemic crystals of enantiomers have piqued interest, as exemplified by classical Wallach’s rule. However, the mechanical and thermal disparities between these materials have not been thoroughly investigated. This study reports the structural and mechanical differences between chiral and racemic crystals of two analogous molecules. The similarity of molecular and crystal structures between the two analogues was validated through comparison with known

Organic molecular crystals exhibit various functions due to their diverse molecular structures and arrangements. Computational approaches are necessary to explore novel molecular crystals from the material space, but quantum chemical calculations are costly and time-consuming. Neural network potentials (NNPs), trained on vast amounts of data, have recently gained attention for their ability to perform energy calculations with accuracy comparable to quantum chemical methods at high speed. However

In materials informatics, the representation of the material structure is fundamentally essential to obtain better prediction results, and graph representation has attracted much attention in recent years. Molecular crystals can be graphically represented in molecular and crystal representations, but the comparison of which representation is more effective has not been examined. In this study, we compared the prediction accuracy between molecular and crystal graphs for band gap prediction. The r

An ML-based workflow doubles crystal structure prediction success by narrowing the search space for organic molecules.

Thalidomide, a famous chiral drug, can be hydrolyzed into three different compounds depending on the reaction site of hydrolysis. This work presents the reformation of thalidomide from one of the hydrolysis compounds through an intramolecular dehydration reaction in acetonitrile. The difference of dehydration behavior between hydrolysis compounds was rationalized based on molecular structures: the reformable molecule has the preferable geometric environment for intramolecular dehydration. Thalid

Predicting the crystal structures of organic molecules remains a formidable challenge due to intensive computational cost. To address this issue, we developed a crystal structure prediction (CSP) workflow that combines machine learning-based lattice sampling with structure relaxation via a neural network potential. The lattice sampling employs two machine learning models—a space group classifier and a density regressor—that reduce the generation of low-density, less-stable structures. In tests o

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.