Atomic layer deposition (ALD) of yttrium oxide (Y₂O₃) produces hydrophobic thin films with exceptional thermal stability (up to 600 °C) and chemical robustness, overcoming the limitations of conventional polymeric coatings and UV-dependent metal oxides. By correlating film thickness, cubic-phase crystallinity, and surface carbon/oxygen bonding states with water contact angle (CA) (>100°), we suggest that hydrophobicity is associated with low-surface-energy crystallographic orientations and possible interfacial electrostatic effects, while contributions from nanoscale roughness and surface adsorption cannot be completely excluded. A continuum model incorporating interfacial dipole layers qualitatively captures the thickness-dependent wetting transition. The apparent low surface energy of Y₂O₃ (∼18 mN m⁻¹) enables strong wettability contrast with high-surface-tension liquids, while remaining oleophilic. Capitalizing on the extreme chemical stability of Y₂O₃, spatially selective reactive-ion etching exposes underlying hydrophilic Si, generating wettability-patterned surfaces that function as passive liquid guides. Without external energy or surface gradients, water and ethylene glycol are selectively transported along independently programmed pathways by simply tuning residual Y₂O₃ thickness (0 nm vs. ∼25 nm). This all-inorganic, scalable platform offers a reliable strategy for controlled liquid manipulation under harsh environments, with potential relevance to applications requiring controlled liquid transport, including microfluidic and separation-related systems. This work provides insight into the thickness-dependent wettability of ALD-grown Y2O3 thin films and demonstrates the potential of atomic-layer-precision surface engineering for controlled liquid manipulation.

Antimony telluride (Sb2Te3) has emerged as a promising candidate for the switching component in phase change memory (PCM) owing to its rapid crystallization speed. Since the device performance of PCM is closely related to the constituent phases of the switching component, a comprehensive understanding of its nanoscale structure is essential for optimizing device fabrication process. In this study, we systematically investigate the substrate-dependent growth behavior and phase evolution of Sb2Te3 thin films grown by atomic layer deposition (ALD) on SiO2 and W substrates—representative materials commonly used as insulator and metallic plug in PCM architecture, respectively. On the SiO2 substrate, a predominant amorphous phase is observed due to the formation of SbOx and TeOx interfacial compounds, followed by polycrystalline island growth beyond a critical thickness of 10 nm. In contrast, films grown on the W substrate exhibit a pronounced out-of-plane-oriented layered structure from the initial growth stage due to the formation of a Te-terminated surface (quasi-monolayer of Te). These nanoscale observations elucidate the substrate effects on the growth behavior and phase evolution during the ALD process, offering valuable insights and practical guidelines for the ALD process of Sb2Te3.

Distribution optimal power flow (D-OPF) with peak load shaving function is crucial for guaranteeing economical and reliable operations of active distribution grids with various distributed energy resources. However, conventional D-OPF methods reduce only the power operation cost without considering carbon emission reduction, which may lead to a slowdown in achieving global carbon neutrality. To resolve this issue, this study proposes a deep reinforcement learning (DRL)-assisted D-OPF framework realizing dual-peak shaving of power and carbon emission for low-carbon active distribution system operations based on the notion of carbon emission flow (CEF). The proposed framework aims to minimize the total power operation costs of substation and gas-turbine (GT) generators. It also aims to reduce the total carbon emission cost via mitigation of peak power and carbon emission in the CEF-based D-OPF framework with both power and carbon emission peak constraints. A key feature of the proposed framework is the adoption of the DRL method for the CEF-based D-OPF problem to determine economical and eco-friendly peaks of power and carbon emission under dynamically changing distribution system operations. Furthermore, a D-OPF optimization-based reward function for the DRL agent is designed to yield no constraint violations for the D-OPF problem during the agent’s training phase. Numerical examples conducted on the IEEE 33-node and IEEE 69-node distribution systems with GT generators, solar photovoltaic systems, and energy storage systems demonstrate that, in contrast with CEF-free and CEF-integrated optimization methods with fixed power and/or carbon emission peaks, the proposed method further reduces the total carbon emission and cost.

Chemiresistive gas sensors are essential for detecting harmful gases such as NO 2 , CO, H 2 S, and volatile organic compounds, as exposure to these gases poses severe risks to human health, including fatal outcomes. Prior to recent advancements and research in two-dimensional (2D) transitional metal dichalcogenides (TMDs), metal-oxide-based gas sensors were predominantly used. [1] However, their high operating temperatures and reliance on ionized oxygen present challenges for the development of low-power and miniaturized devices. As a promising alternative material, TMDs have garnered significant attention in the field of sensors for their high surface-to-volume ratio, enabling the sensitive detection of aforementioned gas species even at room temperature. [2] Despite its immense potential, intrinsic defects or vacancies on the TMD basal plane—where strong chemisorption of gas molecules occurs—hinder the recovery rate of TMD based gas sensors, compromising their reliability and long-term performance. [3] In this work, we use Atomic Layer Deposition (ALD) to selectively deposit and passivate defects and grain boundaries of WS 2 and MoS 2 , resulting in a significant enhancement of the device’s recovery rate and longevity. We evaluate the gas-sensing properties of pristine and Al 2 O 3 -passivated MoS 2 and WS 2 when exposed to NH 3 and NO 2 gases at ppb levels. SEM analysis confirms selective nucleation and growth of Al 2 O 3 on the defects and grain boundaries. As a result, the recovery rate of passivated sensors increased significantly from 74% (pristine sensors) to 96%. Additionally, Al₂O₃-passivated sensors demonstrated superior responsiveness to NO₂ gas compared to their pristine counterparts. The effects of ALD-deposited Al₂O₃ on the 2D TMD surface were characterized using Raman and photoelectron spectroscopy, atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS), and field-emission scanning electron microscopy (FE-SEM). Our findings establish that passivation is a pivotal strategy for significantly enhancing the recovery performance and long-term reliability of 2D TMD-based gas sensors. [1] M. Swan et al., J. Sens. Actuator Networks 1 (2012) 217–253. [2] Lee, K et al., Adv. Mater. 25, 6699-6702 (2013). [3] H. Li et al., Small 8, 63–67 (2012). Figure 1

The incomplete recovery of Transition Metal Dichalcogenides (TMD) based gas sensors hinders their reliability and scalability. The leading cause of incomplete recovery is the strong chemisorption of gas analytes, such as defects or grain boundaries on the active surface of 2D TMDs. Herein, we demonstrate an improvement in the recovery rate of TMD gas sensors by selectively passivating the TMD surface defects or vacancies with Al2O3 via atomic layer deposition. Scanning electron microscopy analysis confirms that the nucleation and growth of atomic-layer-deposited Al2O3 occur along the grain boundaries and defects of the 2D MoS2 and WS2, not covering the inert basal plane. In addition, the Raman, photoluminescence, and X-ray photoelectron spectroscopy data show lower surface defect densities and a slight n-doping effect of Al2O3. This unique selectively defect-passivated TMD gas sensor shows a 400 % response toward 10 ppm of NO2, along with an increase in the recovery rate from 74 to 96 %, even at room temperature, as the number of atomic layer deposition cycles increases. Also, the recovery rate of NH3, a reducing gas, shows an increase of more than 30 %. Thus, the method proposed here is a promising strategy for improving the recovery rate of 2D TMD gas sensors.

Two-dimensional transition metal dichalcogenides (2D TMDCs) are considered promising alternatives to Si as channel materials because of the possibility of retaining their superior electronic transport properties even at atomic body thicknesses. However, the realization of high-performance 2D TMDC field-effect transistors remains a challenge owing to Fermi-level pinning (FLP) caused by gap states and the inherent high Schottky barrier height (SBH) within the metal contact and channel layer. This study demonstrates that high-quality van der Waals (vdW) heterojunction-based contacts can be formed by depositing semimetallic TiS2 onto monolayer (ML) MoS2. After confirming the successful formation of a TiS2/ML MoS2 heterojunction, the contact properties of vdW semimetal TiS2 were thoroughly investigated. With clean interfaces of the TiS2/ML MoS2 heterojunctions, atomic-layer-deposited TiS2 can induce gap-state saturation and suppress FLP. Consequently, compared with conventional evaporated metal electrodes, the TiS2/ML MoS2 heterojunctions exhibit a lower SBH of 8.54 meV and better contact properties. This, in turn, substantially improves the overall performance of the device, including its on-current, subthreshold swing, and threshold voltage. Furthermore, we believe that our proposed strategy for vdW-based contact formation will contribute to the development of 2D materials used in next-generation electronics.

Two-dimensional (2D) transition metal dichalcogenides (TMDCs) have gained significant attention for extraordinary materials properties, which can lead to their enormous potential for biosensing applications. In particular, the richness of electronic and chemical properties of 2D TMDCs, and thereby biosensing performances can be tailored by functionalization and hybridization with extrinsic materials, including substitutional doping, metal nanoparticle functionalization, and formation of 2D heterostructures. Herein, we review the functionalization and hybridization of 2D TMDCs for biosensing applications. Through this, we aim to highlight the advantages of these approaches in modulating the intrinsic properties of 2D TMDCs, make them promising materials for next-generation biosensors.

Two‐dimensional (2D) transition metal dichalcogenides (TMDs) have garnered significant attention in gas‐sensing applications due to their sensitive response to a wide range of gas molecules and their ability to operate at low temperatures, resulting in low‐power consumption. However, there are several areas that require improvement, including insufficient sensitivity at low detection limits, limited gas selectivity, low reliability, and poor recovery. To address these issues and enhance the performance of gas sensors, researchers have proposed the functionalization and hybridization of 2D TMDs. This review paper focuses on elucidating the synergistic effects of functionalization and hybridization of 2D TMDs with carbon‐related materials, metals, MOs, and metal chalcogenides. The paper presents an in‐depth analysis of the mechanisms involved in enhancing the performance of 2D TMD gas sensors and explores various synthesis methods for achieving functionalization and hybridization. Furthermore, the challenges currently faced in the field are discussed and offer insights into the future prospects of TMD nanocomposite‐based gas sensors. By comprehensively addressing these aspects, this research aims to contribute to the advancement of gas‐sensing technology using TMD nanocomposites.

Recently, two-dimensional transition metal dichalcogenides (2D TMDCs) have been researched as promising channel materials for filed effect transistors (FETs) owing to their high mobility at atomic-level thickness. As miniaturization and high performance of the electronic devices are required, however, high contact resistance at the interface between the metal electrode and 2D TMDC channel has become a major challenge.1 The high contact resistance at the metal-semiconductor interface originates from the uncontrollable high Schottky barrier height (SBH). Due to Fermi-level pinning induced by metal-induced gap state (MIGS) and defect-induced gap state (DIGS), the barrier height cannot be controlled by conventional Schottky-Mott rule, regardless of metal work function. Since MIGS occurs due to perturbation of metal wave function into the semiconductor, inserting semimetallic material as contact layer can be a solution to suppress the MIGS and further reduce the contact resistance.2 In this study, ALD TiS2 was used as semimetallic contact layer between the MoS2 channel and Ti/Au electrode for MoS2-based TFT. With the TiS2 contact layer, we could observe improvements in overall device performances, which is attributed to the semimetallic nature of TiS2. In addition, low temperature ALD TiS2 process contributed to the clean interface with vdW bonding between MoS2 and TiS2, resulting in suppression of DIGS, as well as MIGS. Owing to the ALD TiS2 contact, we could mitigate FLP and achieve metal-semiconductor interface with low Schottky barrier height, resulting in low contact resistance. References 1 K. Schauble et al., “Uncovering the effects of metal contacts on monolayer MoS2,” ACS Nano, vol. 14, no. 11, pp. 14798–14808, 2020, doi: 10.1021/acsnano.0c03515. 2 P. C. Shen et al., “Ultralow contact resistance between semimetal and monolayer semiconductors,” Nature, vol. 593, no. 7858, pp. 211–217, 2021, doi: 10.1038/s41586-021-03472-9.

This paper proposes a three-stage privacy-and safety-aware deep reinforcement learning framework for coordinating smart electric vehicle charging stations (EVCSs) integrated with a photovoltaic system/energy storage system (ESS) and Volt/VAR control in a power distribution system. The proposed framework aims to maximize the EVCS profit and minimize the network real power loss while ensuring zero ESS state of charge (SOC) and voltage violation as well as preserving the privacy of the EVCS net load schedule data. In Stage 1 with 30-min resolution, each charging station operator (CSO) agent of the EVCS performs day-ahead profitable real power charging/discharging of the ESS without violating its SOC constraint via a safety layer during training. In Stage 2, using the -differential privacy method, the CSO agents encrypt the EVCS net load schedule data delivered from Stage 1. In Stage 3 with 5-min resolution, the distribution system operator agent conducts real-time reactive power charging/discharging of the ESSs to minimize the real power loss while removing voltage violations completely via iterative safe exploration of the agent with iteration penalties during training. The proposed framework was assessed on the IEEE 33-bus system for its privacy preserving and safety performances.

2D transition metal dichalcogenides (TMDs) have attracted significant attention because of their potential in biomolecular sensing applications owing to their sensitive surface interactions with analytes. In particular, glutamic acid (GLU) as representative of amino acids (AAs) are considered not only basic metabolites in proteins and food, but also vital biomarkers of body status and diseases. In addition, monitoring GLU profiles appears to be a highly effective real-time and early diagnostic technique. In this study, a biomolecular GLU sensor that uses a 2D polycrystalline MoS2 as channel material, based on the effect of the direct surface charge transfer, was fabricated. As fundamental approach, the direct charge transfer of adsorbed GLU onto MoS2 was experimentally demonstrated for the first time. The sensor exhibited sensitive responses to GLU exposure, without any enzymes or receptors. In addition, the electrode-encapsulated MoS2 sensor showed comparably stable responses to the non-encapsulated MoS2 sensor. The results confirmed that the 2D TMDs such as polycrystalline MoS2 could be a viable platform for highly sensitive and stable biomolecular sensor applications based on direct surface interactions. In addition, this study can contribute to the extended researches such as the effect of surface functionalization by metal nanoparticles, and other types of AAs.

The wettability of metal oxides, which is directly related to the surface free energy (SFE), is used in a wide range of robust functional coatings, from hydrophilic to hydrophobic. Because wettability is significantly affected by solid surface properties, several studies on the determinant factors and their correlations have been conducted through the thin-film coating of metal oxides. Herein, we found that HfO2 thin films deposited via atomic layer deposition (ALD) are intrinsically hydrophilic. Simultaneously, a thickness-dependent wettability change is observed. These observations were investigated by measuring water contact angles (WCAs), film surface compositions, roughness, morphologies, and microcrystalline structures of the ALD-grown HfO2 thin films. It was deduced that the surface oxygen species significantly affected the intrinsic hydrophilicity of HfO2 thin films. In addition, the crystalline orientations evolved with film thickness, and thermal annealing was used to determine the thickness-dependent WCA trend. In particular, the transformation of the preferred m(-111) crystal orientation with a low SFE had a dominant impact on the SFE change in the HfO2 thin films. Considering the lack of fundamental studies on the SFE of ALD-grown HfO2 thin films, we believe that this study will help understand the wettability of HfO2 and its overall surface science.

This paper presents a multilevel deep reinforcement learning (DRL) algorithm for a privacy-preserving charging of reserved individual electric vehicles (EVs) and the secure operation of a smart EV charging station (EVCS) installed with a solar photovoltaic system and energy storage system (ESS). At the first level, at each charging pole, the DRL agent enhances the data privacy of the reserved EV arrival/departure times at smart EVCSs using a discrete differential privacy method, ensuring nonoverlapping charging periods. At the second level, at all charging poles, multiple DRL agents cooperate to maximize the revenue of smart EVCSs, completely satisfying their charging demands. At the third level, an ESS DRL agent minimizes the operational energy cost of the smart EVCS while performing privacy-preserving energy management of the smart EVCS by flattening the net energy consumption to an economical target value via charging and discharging the ESS. The simulation results evaluated for smart EVCS with four charging poles confirm the effectiveness of the proposed three-level DRL algorithm in view of the privacy-preserving performance with varying privacy costs, increasing revenue, and decreasing operational energy cost of smart EVCS.

This study proposes a two-stage learning and unlearning framework that ensures profitable and privacy-preserving charging at electric vehicle charging stations (EVCSs) integrated with solar photovoltaic and energy storage systems (ESSs). In Stage 1, a robust dueling deep Q -network method combined with an optimization-based reward function is employed to perform the following two tasks: 1) an increase in the EVCS profit via the selection of charging poles for profitable charging scheduling of the reserved EVs based on ESS operation and 2) enhancement of the robustness to adversarial perturbations. In Stage 2, a computationally efficient machine unlearning method is adopted to protect the data privacy of the reserved EVs by completely erasing their traces of private data during unlearning. The simulation results demonstrate the advantages of the proposed framework in terms of profitable charging pole utilization, robustness against adversarial perturbations, accuracy of the unlearned EV charging model, and training time.

Magnetic actuators are attractive for their fast response, large deformation capability, and low power requirement compared with other types of actuators. Roll-to-roll printing is a continuous process and offers high productivity. We fabricated the cantilever-structured magnetic actuators using the roll-to-roll gravure printing process. By applying a partial magnetic field while carrying out the roll-to-roll printing process, the vector of the magnetic layer was programmed instantaneously during printing. This technique improved productivity and reduced materials waste. The fabrication process for the actuator includes printing the sacrificial layer, printing and magnetizing the magnetic layer, and coating the structural layer. An air gap between the substrate and cantilever beam of the actuator was made by removing the sacrificial layer. The actuator samples were examined in terms of displacement, hysteresis, and durability. Our actuators can rotate up to 90° and can be actuated at 20 Hz under a magnetic field of 80 mT.

We introduced atomic layer deposition (ALD) of TiS 2 as contact layer for MoS 2 TFT to reduce the contact resistance. In this study, film properties of low temperature ALD TiS 2 according to growth temperature was analyzed. ALD grown TiS 2 showed semimetallic nature with low resistivity. In addition, change in properties of MoS 2 after TiS 2 deposition was investigated by various method. By applying ALD TiS 2 , we found significant increase in current level and V th reduction which are attributed to semimetal nature of TiS 2 . These results imply that ALD TiS 2 for contact formation is proper method to achieve high performance of MoS 2 TFT.

The introduction of robot-assisted automation, such as in machine tending systems for the automated operation of CNC machine tools, is being actively carried out at many industrial sites. The most important part of this intelligent system is the installation of a machine tending system that involves interface programming between the CNC machine tools and the industrial robot. Despite this importance, however, the machine tending system has many setup problems. It must be reprogrammed for both controllers whenever a new CNC machine tool or robot is introduced. Owing to the complex structure of the machine tending system, external engineers are required even though trivial changes have been made. To solve and remove inconveniences, there is a need to introduce a standardized and integrated system of the interface between multi-vendor CNC machine tools and industrial robots. In addition, the digital twin implemented inside the machine tool controller enables external engineers to easily change robot programming. To implement this system, an integrated development environment for: an intelligent platform that provides ISO 21919 interfaces to multi-vendors CNC machine tools, a robot platform developing application software of various robots, has been established.

Among chalcogenides for phase-change memory, Sb 2 Te 3 is attracting attention for its huge potential, along with recent demands for atomic layer deposition (ALD). We aimed to study atomic-scale thin film growth and phase transformation of ALD Sb 2 Te 3 thin films with substrate dependency. Comparatively, thin film growth trends of ALD Sb 2 Te 3 on SiO 2 and W substrate were studied by observing transformation of crystal structures, and trends in electrical resistivity. On SiO 2 , predominant amorphous phases at initial stage were observed, followed by polycrystalline island growth with randomly oriented grains. However, on crystalline W, the highly out-of-plane (00l) orientations and layer-by-layer growth was found.

We introduce a new approach for the fabrication of an ultrasensitive nitrogen dioxide (NO2) gas sensor operating at room temperature. By using atomic layer deposition (ALD), Pt nanoparticles (NPs) can be selectively decorated on surface defects of tungsten disulfide (WS2). Our study demonstrated that defect-selectively functionalized gas sensors with Pt NPs only at high-surface-energy sites, such as dangling bonds and grain boundaries, exhibit a greater enhancement in sensitivity than nonselectively functionalized sensors. Additionally, the sensing performances of WS2-based gas sensors were enhanced by controlling the particle size and varying the number of ALD cycles. Specifically, the gas response of Pt-functionalized WS2 to 10 ppm of NO2 was maximized at 150 cycles of ALD, resulting in a remarkable 10-fold increase (similar to 850%) compared to pristine WS2, and almost complete recovery (similar to 93.2%) was achieved at 200 cycles. Furthermore, even at a very low concentration level of 100 ppb, the optimized Pt/WS2 sensor showed excellent detection performance, with a response rate of 47%. Also, it exhibited excellent NO2 gas selectivity and device stability. Our defect-selective functionalization method for improving the essential performance of gas sensors is expected to be applied to a wide range of functional materials, including Ru, Pd, SnO2, and ZnO. This exhibits remarkable potential for practical applications in human health and environmental monitoring.

We present ExpanStick, a novel thumbstick that augments video game interaction using the force that the user applies at the physical limit of the gamepad. Gamers frequently manipulate a thumbstick leaning on the limit, or physical boundary around it, either to apply maximum input or to secure physical support, which makes the contact force an easily accessible input channel. The ExpanStick preserves the form factor and usability of the thumbstick, while expanding its input space. We built the ExpanStick and inserted it in a commercial gamepad as a proof-of-concept prototype. Using the prototype, we conducted a design workshop with console gamers to design the ExpanStick game interaction. Through demonstration of the interactions, we found the early use experience with the ExpanStick is positive and well accepted by the game players.