Kinetically controlled morphology and composition of colloidal nanoparticles: cation exchange reactions from copper sulfide to transition metal (Mn, Zn, Fe, and Co) sulfides.

The cation exchange reaction is a powerful method for generating nanomaterials with unique structures because of the easy control of the size, morphology, composition, and crystal structure of the nanoparticles. This study investigated the kinetically controlled morphology and composition of colloidal nanoparticles (NPs) through cation exchange reactions, specifically focusing on variations from copper sulfide to transition metal sulfides, including Co, Fe, Zn, and Mn sulfides. In the cation exchange reaction, Co exhibited the fastest exchange rate, followed by Fe, Mn, and Zn.

Morphology Control of Au-Ni Hybrid Nanoparticles: Exploring Heterostructures and Optical Tuning.

Hybrid nanoparticles (NPs) have attracted considerable attention because of their ability to provide diverse properties by integrating the inherent properties of multiple components; however, synthetic strategies to control their morphology remain unexplored. In this study, a new method was used to control the morphology and optical properties of Au-Ni heterostructure (ANH) NPs. Unique morphological changes were observed by varying the Au/Ni precursor ratio from 2:1 to 1:4, exhibiting a shape transformation from dumbbell-like to quasi-spherical owing to the Ni NP size expansion, whereas the Au NP maintained their size.

Design of Eu(TTA)phen-incorporated SiO-coated transition metal oxide nanoparticles for efficient luminescence and magnetic performance.

The development of multifunctional nanoparticles (NPs) combining individual properties, such as magnetic, luminescence, and optical properties, has attracted significant research interest. In this study, europium (Eu)-incorporating iron oxide nanoparticles (IONPs) with Eu(TTA)phen (ET-SIOPs) were successfully designed and shown to have luminescence and magnetic properties. The proposed synthetic method has three steps: (1) IONP synthesis, (2) SiO layer coating (1st coating), and (3) Eu-SiO layer coating (2nd coating).

Monocular depth estimation network with single-pixel depth guidance.

Due to the scale ambiguity problem, the performance of monocular depth estimation (MDE) is inherently restricted. Multi-camera systems, especially those equipped with active depth cameras, have addressed this problem at the expense of increased hardware costs and space. In this Letter, we adopt a similar but cost-effective solution using only single-pixel depth guidance with a single-photon avalanche diode.

How Do Colloidal Nanoparticles Move in a Solution under an Electric Field?: Light Scattering Analysis.

Understanding the dynamics of colloidal nanoparticles (NPs) in a solution is the key to assembling them into solids through a solution process such as electrophoretic deposition. In this study, newly developed analysis with light scattering is used to examine NP dynamics induced by a non-uniform electric field. We reveal that the symmetric directions of moving NP aggregates are due to dielectrophoresis between the cylindrical electrodes, while the actual NP deposition is based on the charge of NPs (electrophoresis).

Contact Enhancement in Nanoparticle Assemblies through Electrophoretic Deposition.

A strong interparticle connection needs to be realized to harvest unique nanoscale features of colloidal nanoparticles (NPs) in film structures. Constructing a strong contact and adhesion of NPs on a substrate is an essential process for improved NP film properties, and therefore, its key factors should be determined by understanding the NP deposition mechanism. Herein, we investigated the critical factors leading to the robust and strong adherence of the film structure and revealed that the NP deposition mechanism involved the role of surfactant ligands during electrophoretic deposition (EPD).

Leveraging Nitrogen Linkages in the Formation of a Porous Thorium-Organic Nanotube Suitable for Iodine Capture.

We report the synthesis, characterization, and iodine capture application of a novel thorium-organic nanotube, TSN-626, [ThO(OH)(CHNO)(CHO)(HO)]·3HO. The classification as a metal-organic nanotube (MONT) distinguishes it as a rare and reduced dimensionality subset of metal-organic frameworks (MOFs); the structure is additionally hallmarked by low node connectivity. TSN-626 is composed of hexameric thorium secondary building units and mixed O/N-donor isonicotinate ligands that demonstrate selective ditopicity, yielding both terminating and bridging moieties.

Active Learning Configuration Interaction for Excited-State Calculations of Polycyclic Aromatic Hydrocarbons.

We present the active learning configuration interaction (ALCI) method for multiconfigurational calculations based on large active spaces. ALCI leverages the use of an active learning procedure to find important electronic configurations among the full configurational space generated within an active space. We tested it for the calculation of singlet-singlet excited states of acenes and pyrene using different machine learning algorithms.

Electrophoretic Deposition of Aged and Charge Controlled Colloidal Copper Sulfide Nanoparticles.

Colloidal nanoparticles (NPs) have been recently spotlighted as building blocks for various nanostructured devices. Their collective properties have been exhibited by arranging them on a substrate to form assembled NPs. In particular, electrophoretic deposition (EPD) is an emerging fabrication method for such nanostructured films.

Advancement of Actinide Metal-Organic Framework Chemistry via Synthesis of Pu-UiO-66.

We report the synthesis and characterization of the first plutonium metal-organic framework (MOF). Pu-UiO-66 expands the established UiO-66 series, which includes transition metal, lanthanide, and early actinide elements in the hexanuclear nodes. The thermal stability and porosity of Pu-UiO-66 were experimentally determined, and multifaceted computational methods were used to corroborate experimental values, examine inherent defects in the framework, decipher spectroscopic signatures, and elucidate the electronic structure.

Automation of Active Space Selection for Multireference Methods via Machine Learning on Chemical Bond Dissociation.

Predicting and understanding the chemical bond is one of the major challenges of computational quantum chemistry. Kohn-Sham density functional theory (KS-DFT) is the most common method, but approximate density functionals may not be able to describe systems where multiple electronic configurations are equally important. Multiconfigurational wave functions, on the other hand, can provide a detailed understanding of the electronic structures and chemical bonds of such systems.

Modeling adsorption properties of structurally deformed metal-organic frameworks using structure-property map.

Structural deformation and collapse in metal-organic frameworks (MOFs) can lead to loss of long-range order, making it a challenge to model these amorphous materials using conventional computational methods. In this work, we show that a structure-property map consisting of simulated data for crystalline MOFs can be used to indirectly obtain adsorption properties of structurally deformed MOFs. The structure-property map (with dimensions such as Henry coefficient, heat of adsorption, and pore volume) was constructed using a large data set of over 12000 crystalline MOFs from molecular simulations.

Work function engineering of SnO single crystal microplates with thermal annealing.

We synthesized black SnO single-crystal microplates via a sonochemical process and engineered the work function of the SnO microplates using thermal treatments. The as-synthesized SnO microplates have a wide (001) plane, as is clearly evident from TEM images and diffraction patterns. Surface potential measurements on the SnO microplates show that the work function changes as the annealing temperature increases.

Ultraflat Au nanoplates as a new building block for molecular electronics.

We demonstrate the charge transport properties of a self-assembled organic monolayer on Au nanoplates with conductive probe atomic force microscopy (CP-AFM). Atomically flat Au nanoplates, a few hundred micrometers on each side, that have only (111) surfaces, were synthesized using the chemical vapor transport method; these nanoplates were employed as the substrates for hexadecanethiol (HDT) self-assembled monolayers (SAMs). Atomic-scale high-resolution images show (√3 x √3) R30° molecular periodicity, indicating a well-ordered structure of the HDT on the Au nanoplates.

Effect of BCAA intake during endurance exercises on fatigue substances, muscle damage substances, and energy metabolism substances.

The increase rate of utilization of branched-chain amino acids (BCAA) by muscle is reduced to its plasma concentration during prolonged exercise leading to glycogen. BCAA supplementation would reduce the serum activities of intramuscular enzymes associated with muscle damage. To examine the effects of BCAA administration on fatigue substances (serotonin, ammonia and lactate), muscle damage substances (CK and LDH) and energy metabolism substances (FFA and glucose) after endurance exercise.