Dong Won Chun

Radiation chemistry enables the synthesis of colloidal nanoparticles without chemical reducing agents, yielding metal nanoparticles via simple and direct processes. Aliphatic alcohols are widely used to promote the formation of nanoparticles in radiolytic synthesis by inhibiting the reoxidation of these metal nanoparticles by scavenging hydroxyl radicals. However, the role of the scavenger has been limited to simply accelerating the formation of the nanoparticles without altering their nature. Herein, the role of radical scavengers is investigated in determining the type of metal nanoparticles formed, with the scavenger concentration playing a crucial role. It is found that the addition of isopropyl alcohol controls the formation of hexagonal close‐packed (hcp) palladium hydride (PdH_x) nanoparticles that are previously synthesized for the first time via radiation chemistry by increasing the concentrations of hydrated electrons and hydrogen radicals. This discovery reveals a more active role for radical scavengers in radiolytic syntheses, and this strategy can be used for the cost‐effective mass production of hcp PdH_x nanoparticles.

The excessed Ni will embed full-hesuler TiNi₂Sb nanoprecipitates into the matrix, which can improve the thermoelectric performance by scattering low-energy carriers and phonons.

Controlling the contact properties of a copper (Cu) electrode is an important process for improving the performance of an amorphous indium-gallium-zinc oxide (a-IGZO) thin-film transistor (TFT) for high-speed applications, owing to the low resistance-capacitance product constant of Cu. One of the many challenges in Cu application to a-IGZO is inhibiting high diffusivity, which causes degradation in the performance of a-IGZO TFT by forming electron trap states. A self-assembled monolayer (SAM) can perfectly act as a Cu diffusion barrier (DB) and passivation layer that prevents moisture and oxygen, which can deteriorate the TFT on-off performance. However, traditional SAM materials have high contact resistance and low mechanical-adhesion properties. In this study, we demonstrate that tailoring the SAM using the chemical coupling method can enhance the electrical and mechanical properties of a-IGZO TFTs. The doping effects from the dipole moment of the tailored SAMs enhance the electrical properties of a-IGZO TFTs, resulting in a field-effect mobility of 13.87 cm²/V·s, an on-off ratio above 10⁷, and a low contact resistance of 612 Ω. Because of the high electrical performance of tailored SAMs, they function as a Cu DB and a passivation layer. Moreover, a selectively tailored functional group can improve the adhesion properties between Cu and a-IGZO. These multifunctionally tailored SAMs can be a promising candidate for a very thin Cu DB in future electronic technology.

Herein, real‐time observations of dehydrogenation of a Mg₂FeH₆–MgH₂ composite by means of in situ transmission electron microscopy (TEM) with advanced spatial (≈0.8 Å) and temporal (25 frames s⁻¹) resolution are reported. Careful control and systematic variations of the reaction temperature and electron dose rate enable detailed and direct visualization of the characteristic decomposition of Mg₂FeH₆ into Mg and Fe, which occurs on the nanometer scale under optimal experimental conditions defined to minimize the electron‐beam‐driven Mg oxidation and dehydrogenation that take place in TEM. First, the formation of nanostructured fine Fe clusters in Mg metal and their growth via coalescence during dehydrogenation are verified. Additionally, fine monitoring of the in situ diffraction patterns acquired during decomposition of the composite allows separate evaluations of the desorption kinetics of the two coexisting phases, which confirm the synergetic dehydrogenation of this dual‐phase system. It is envisioned that these findings will provide useful guidelines for reducing the gaps between nanoscale and bulk‐scale research and designing hydrogen sorption conditions to enable efficient operation of a solid‐state hydrogen storage system.

Metastable phases—kinetically favoured structures—are ubiquitous in nature^1,2. Rather than forming thermodynamically stable ground-state structures, crystals grown from high-energy precursors often initially adopt metastable structures depending on the initial conditions, such as temperature, pressure or crystal size^1,3,4. As the crystals grow further, they typically undergo a series of transformations from metastable phases to lower-energy and ultimately energetically stable phases^1,3,4. Metastable phases sometimes exhibit superior physicochemical properties and, hence, the discovery and synthesis of new metastable phases are promising avenues for innovations in materials science^1,5. However, the search for metastable materials has mainly been heuristic, performed on the basis of experiences, intuition or even speculative predictions, namely ‘rules of thumb’. This limitation necessitates the advent of a new paradigm to discover new metastable phases based on rational design. Such a design rule is embodied in the discovery of a metastable hexagonal close-packed (hcp) palladium hydride (PdH_x) synthesized in a liquid cell transmission electron microscope. The metastable hcp structure is stabilized through a unique interplay between the precursor concentrations in the solution: a sufficient supply of hydrogen (H) favours the hcp structure on the subnanometre scale, and an insufficient supply of Pd inhibits further growth and subsequent transition towards the thermodynamically stable face-centred cubic structure. These findings provide thermodynamic insights into metastability engineering strategies that can be deployed to discover new metastable phases.

We studied the variation in electrical conductivity of exfoliated RuO₂ nanosheets and the modulation in the contact resistance of individual nanosheet devices using charge transfer doping effects based on surface metal nanoparticle decorations. The electrical conductivity in the monolayer and bilayer RuO₂ nanosheets gradually increased due to the surface decoration of Cu, and subsequently Ag, nanoparticles. We obtained contact resistances between the nanosheet and electrodes using the four-point and two-point probe techniques. Moreover, the contact resistances decreased during the surface decoration processes. We established that the surface decoration of metal nanoparticles is a suitable method for external contact engineering and the modulation of the internal properties of nanomaterials.

Metastable phases—kinetically favored structures—are ubiquitous in nature. Rather than forming thermodynamically stable ground-state structures, crystals grown from high-energy precursors often initially adopt metastable structures depending on the initial conditions such as temperature, pressure, or crystal size. As the crystals grow further, they typically undergo a series of transformations from metastable to lower-energy phases and ultimately energetically stable phases, as described by Wilhelm Ostwald. Metastable phases, however, sometimes provide superior chemical and physical properties, and hence, discovering and synthesizing novel metastable phases are promising avenues for achieving innovations in materials science. The most common strategy for synthesizing a metastable material involves manipulating thermodynamic conditions such as temperature and pressure during the course of synthesis. However, the search for metastable materials has mainly been heuristic, on the basis of experiences, intuitions, or even speculative predictions. This limitation necessitates the advent of a new paradigm to discover novel metastable phases, i.e., by “rational design and synthesis” instead of a “rule of thumb,” and based on ab initio methods, i.e., the calculation of thermodynamic and kinetic properties of materials with various compositions, crystal structures, and crystal sizes. The design rule is embodied in the discovery of a metastable hexagonal close-packed (HCP) palladium hydride (PdH_x), synthesized in a liquid cell environment using a transmission electron microscope (TEM). The metastable HCP structure is stabilized through a unique interplay among the precursor concentrations in the solution: a sufficient supply of hydrogen (H) favors the HCP structure on the sub-nanometer scale, and an insufficient supply of Pd inhibits further growth and subsequent transition toward the thermodynamically stable face-centered cubic (FCC) structure. The crystal structure was modulated (HCP or FCC) by adjusting the H concentration inside the TEM liquid cell, providing strong evidence for the crucial role of the H concentration. Monte Carlo simulations reveal that an unexpected inhomogeneous distribution of interstitial H atoms, distinct from the predominant occupation at the octahedral interstitial sites, is key to stabilizing nanoscale HCP PdH_x. Furthermore, insufficient Pd brings a multi-step nucleation and growth pathway, deduced from in situ liquid cell TEM combined with atomic electron tomography, which maintains the metastable phase intact. These findings provide new thermodynamic insights into metastability-engineering strategy to be deployed in discovering new metastable phases.

Light element identification is necessary in materials research to obtain detailed insight into various material properties. However, reported techniques, such as scanning transmission electron microscopy (STEM)-energy dispersive X-ray spectroscopy (EDS) have inadequate detection limits, which impairs identification. In this study, we achieved light element identification with nanoscale spatial resolution in a multi-component metal alloy through unsupervised machine learning algorithms of singular value decomposition (SVD) and independent component analysis (ICA). Improvement of the signal-to-noise ratio (SNR) in the STEM-EDS spectrum images was achieved by combining SVD and ICA, leading to the identification of a nanoscale N-depleted region that was not observed in as-measured STEM-EDS. Additionally, the formation of the nanoscale N-depleted region was validated using STEM–electron energy loss spectroscopy and multicomponent diffusional transformation simulation. The enhancement of SNR in STEM-EDS spectrum images by machine learning algorithms can provide an efficient, economical chemical analysis method to identify light elements at the nanoscale.