Exploring metabolic effects of dipeptide feed media on CHO cell cultures by in silico model-guided flux analysis

There is a growing interest in perfusion or continuous processes to achieve higher productivity of biopharmaceuticals in mammalian cell culture, specifically Chinese hamster ovary (CHO) cells, towards advanced biomanufacturing. These intensified bioprocesses highly require concentrated feed media in order to counteract their dilution effects. However, designing such condensed media formulation poses several challenges, particularly regarding the stability and solubility of specific amino acids. To address the difficulty and complexity in relevant media development, the biopharmaceutical industry has recently suggested forming dipeptides by combining one from problematic amino acids with selected pairs to compensate for limitations. In this study, we combined one of the lead amino acids, L-tyrosine, which is known for its poor solubility in water due to its aromatic ring and hydroxyl group, with glycine as the partner, thus forming glycyl-L-tyrosine (GY) dipeptide. Subsequently, we investigated the utilization of GY dipeptide during fed-batch cultures of IgG-producing CHO cells, by changing its concentrations (0.125 × , 0.25 × , 0.5 × , 1.0 × , and 2.0 ×). Multivariate statistical analysis of culture profiles was then conducted to identify and correlate the most significant nutrients with the production, followed by in silico model-guided analysis to systematically evaluate their effects on the culture performance, and elucidate metabolic states and cellular behaviors. As such, it allowed us to explain how the cells can more efficiently utilize GY dipeptide with respect to the balance of cofactor regeneration and energy distribution for the required biomass and protein synthesis. For example, our analysis results uncovered specific amino acids (Asn and Gln) and the 0.5 × GY dipeptide in the feed medium synergistically alleviated the metabolic bottleneck, resulting in enhanced IgG titer and productivity. In the validation experiments, we tested and observed that lower levels of Asn and Gln led to decreased secretion of toxic metabolites, enhanced longevity, and elevated specific cell growth and titer. KEY POINTS: • Explored the optimal Tyr dipeptide for the enhanced CHO cell culture performance • Systematically analyzed effects of dipeptide media by model-guided approach • Uncovered synergistic metabolic utilization of amino acids with dipeptide.

Preparation of Non-Isocyanate Polyurethanes from Mixed Cyclic-Carbonated Compounds: Soybean Oil and CO2-Based Poly(ether carbonate)

This study presents the synthesis and characterization of non-isocyanate polyurethanes (NIPU) derived from the copolymerization of cyclic-carbonated soybean oil (CSBO) and cyclic carbonate (CC)-terminated poly(ether carbonate) (RCC). Using a double-metal cyanide catalyst, poly(ether carbonate) polyol was first synthesized through the copolymerization of carbon dioxide and propylene oxide. The terminal hydroxyl group was then subjected to a substitution reaction with a five-membered CC group using glycerol-1,2-carbonate and oxalyl chloride, yielding RCC. Attempts to prepare NIPU solely using RCC and diamine were unsuccessful, possibly due to the low CC functionality and the aminolysis of RCC's linear carbonate repeating units. However, when combined with CSBO, solid NIPUs were successfully obtained, exhibiting good thermal stability along with enhanced mechanical properties compared to conventional CSBO-based NIPU formulations. Overall, this study underscores the potential of leveraging renewable resources and carbon capture technologies to develop sustainable NIPUs with tailored properties, thereby expanding their range of applications.

Action Recognition of Taekwondo Unit Actions Using Action Images Constructed with Time-Warped Motion Profiles

Taekwondo has evolved from a traditional martial art into an official Olympic sport. This study introduces a novel action recognition model tailored for Taekwondo unit actions, utilizing joint-motion data acquired via wearable inertial measurement unit (IMU) sensors. The utilization of IMU sensor-measured motion data facilitates the capture of the intricate and rapid movements characteristic of Taekwondo techniques. The model, underpinned by a conventional convolutional neural network (CNN)-based image classification framework, synthesizes action images to represent individual Taekwondo unit actions. These action images are generated by mapping joint-motion profiles onto the RGB color space, thus encapsulating the motion dynamics of a single unit action within a solitary image. To further refine the representation of rapid movements within these images, a time-warping technique was applied, adjusting motion profiles in relation to the velocity of the action. The effectiveness of the proposed model was assessed using a dataset compiled from 40 Taekwondo experts, yielding remarkable outcomes: an accuracy of 0.998, a precision of 0.983, a recall of 0.982, and an F1 score of 0.982. These results underscore this time-warping technique's contribution to enhancing feature representation, as well as the proposed method's scalability and effectiveness in recognizing Taekwondo unit actions.

A self-powered photodetector through facile processing using polyethyleneimine/carbon quantum dots for highly sensitive UVC detection

Ultraviolet C (UVC) photodetectors have garnered considerable attention recently because the detection of UVC is critical for preventing skin damage in humans, monitoring environmental conditions, detecting power aging in facilities, and military applications. As UVC detectors are "solar-blind", they encounter less interference than other environmental signals, resulting in low disturbance levels. This study employed a natural precursor (glucose) and a one-step ultrasonic reaction procedure to prepare carbon quantum dots (CQDs), which served as a convenient and environmentally friendly material to combine with polyethyleneimine (PEI). The prepared materials were used to develop a self-powered, high-performance UVC photodetector. The thickness of the constitutive film was investigated in detail based on the conditions of the electron transport pathway and trap positions to further improve the performance of the PEI/CQD photodetectors. Under the optimized conditions, the photodetector could generate a strong signal (1.5 mA W-1 at 254 nm) and exhibit high detectability (1.8 × 1010 Jones at 254 nm), an ultrafast response, and long-term stability during the power supply sequence. The developed solar-blind UVC photodetector can be applied in various ways to monitor UVC in an affordable, straightforward, and precise manner.

Environmentally Robust Triboelectric Tire Monitoring System for Self-Powered Driving Information Recognition via Hybrid Deep Learning in Time-Frequency Representation

Developing a robust artificial intelligence of things (AIoT) system with a self-powered triboelectric sensor for harsh environment is challenging because environmental fluctuations are reflected in triboelectric signals. This study presents an environmentally robust triboelectric tire monitoring system with deep learning to capture driving information in the triboelectric signals generated from tire-road friction. The optimization of the process and structure of a laser-induced graphene (LIG) electrode layer in the triboelectric tire is conducted, enabling the tire to detect universal driving information for vehicles/robotic mobility, including rotation speeds of 200-2000 rpm and contact fractions of line. Employing a hybrid model combining short-term Fourier transform with a convolution neural network-long short-term memory, the LIG-based triboelectric tire monitoring (LTTM) system decouples the driving information, such as traffic lines and road states, from varied environmental conditions of humidity (10%-90%) and temperatures (50-70 °C). The real-time line and road state recognition of the LTTM system is confirmed on a mobile platform across diverse environmental conditions, including fog, dampness, intense sunlight, and heat shimmer. This work provides an environmentally robust monitoring AIoT system by introducing a self-powered triboelectric sensor and hybrid deep learning for smart mobility.

Rational Design of Naphthol Groups Functionalized Bipolar Polymer Cathodes for High Performance Alkali-Ion Batteries

Redox-active organic compounds gather significant attention for their potential application as electrodes in alkali ion batteries, owing to the structural versatility, environmental friendliness, and cost-effectiveness. However, their practical applications of such compounds are impeded by insufficient active sites with limited capacity, dissolution in electrolytes, and sluggish kinetics. To address these issues, a naphthol group-containing triarylamine polymer, namely poly[6,6'-(phenylazanediyl)bis(naphthol)] (poly(DNap-OH)) is rationally designed and synthesized, via oxidative coupling polymerization. It is capable of endowing favorable steric structures that facilitate fast ion diffusion, excellent chemical stability in organic electrolytes, and additional redox-active sites that enable a bipolar redox reaction. By exploiting these advantages, poly(DNap-OH) cathodes demonstrate remarkable cycling stability in both lithium-ion batteries (LIBs) and potassium-ion batteries (PIBs), showcasing enhanced specific capacity and redox reaction kinetics in comparison to the conventional poly(4-methyltriphenylamine) cathodes. Overall, this work offers insights into molecular design strategies for the development of high-performance organic cathodes in alkali-ion batteries.

Hierarchical PtCuMnP Nanoalloy for Efficient Hydrogen Evolution and Methanol Oxidation

The higher amount of Pt usage and its poisoning in methanol oxidation reaction in acidic media is a major setback for methanol fuel cells. Herein, a promising dual application high-performance electrocatalyst has been developed for hydrogen evolution and methanol oxidation. A low Pt-content nanoalloy co-doped with Cu, Mn, and P is synthesized using a modified solvothermal process. Initially, ultrasmall ≈2.9 nm PtCuMnP nanoalloy is prepared on N-doped graphene-oxide support and subsequently, it is characterized using several analytical techniques and examined through electrochemical tests. Electrochemical results show that PtCuMnP/N-rGO has a low overpotential of 6.5 mV at 10 mA cm-2 in 0.3 m H2 SO4 and high mass activity for the hydrogen evolution reaction. For the methanol oxidation reaction, the PtCuMnP/N-rGO electrocatalyst exhibits robust performance. The mass activity of PtCuMnP/N-rGO is 6.790 mA mg-1 Pt , which is 7.43 times higher than that of commercial Pt/C (20% Pt). Moreover, in the chronoamperometry test, PtCuMnP/N-rGO shows exceptionally good stability and retains 72% of the initial current density even after 20,000 cycles. Furthermore, the PtCuMnP/N-rGO electrocatalyst exhibits outstanding performance for hydrogen evolution and methanol oxidation along with excellent anti-poisoning ability. Hence, the developed bifunctional electrocatalyst can be used efficiently for hydrogen evolution and methanol oxidation.

Redesign of Anode Catalyst for Sustainable Survival of Fuel Cells

Polymer electrolyte membrane fuel cells (PEMFCs) suffer from severe performance degradation when operating under harsh conditions such as fuel starvation, shut-down/start-up, and open circuit voltage. A fundamental solution to these technical issues requires an integrated approach rather than condition-specific solutions. In this study, an anode catalyst based on Pt nanoparticles encapsulated in a multifunctional carbon layer (MCL), acting as a molecular sieve layer and protective layer is designed. The MCL enabled selective hydrogen oxidation reaction on the surface of the Pt nanoparticles while preventing their dissolution and agglomeration. Thus, the structural deterioration of a membrane electrode assembly can be effectively suppressed under various harsh operating conditions. The results demonstrated that redesigning the anode catalyst structure can serve as a promising strategy to maximize the service life of the current PEMFC system.

Surface-Reconstructed Ru-Doped Nickel/Iron Oxyhydroxide Arrays for Efficient Oxygen Evolution

The generation of an active phase through dynamic surface reconstruction is a promising strategy for improving the activity of electrocatalysts. However, studies investigating the reconstruction process and its impact on the intrinsic properties of the catalysts are scarce. Herein, the surface reconstruction of NiFe2 O4 interfaced with NiMoO4 (Ru-NFO/NMO) facilitated by Ru doping is reported. The electrochemical and material characterizations demonstrate that Ru doping can regulate the electronic structure of NFO/NMO and induce the high-valence state of Ni3.6+ δ , facilitating the surface reconstruction to highly active Ru-doped NiFeOOH/NiOOH (SR-Ru-NFO/NMO). The optimized SR-Ru-NFO/NMO exhibits promising performance in the oxygen evolution reaction, displaying a low overpotential of 229 mV at 10 mA cm-2 and good stability at varying current densities for 80 h. Density functional theory calculations indicate that Ru doping can increase the electron density and optimize intermediate adsorption by shifting the d-band center downward. This work provides valuable insights into the tuning of electrocatalysts by surface reconstruction and offers a rational design strategy for the development of highly active oxygen evolution reaction electrocatalysts.

Quantification of the Carbon-Coating Effect on the Interfacial Behavior of Graphite Single Particles

The effect of carbon coating on the interfacial charge transfer resistance of natural graphite (NG) was investigated by a single-particle measurement. The microscale carbon-coated natural graphite (NG@C) particles were synthesized by the simple wet-chemical mixing method using a phenolic resin as the carbon source. The electrochemical test results of NG@C using the conventional composite electrodes demonstrated desirable rate capability, cycle stability, and enhanced kinetic property. Moreover, the improvements in the composite electrodes were confirmed with the electrochemical parameters (i.e., charge transfer resistance, exchange current density, and solid phase diffusion coefficient) analyzed by a single-particle measurement. The surface carbon coating on the NG particles reduced the interfacial charge transfer resistance (Rct) and increased the exchange current density (i0). The Rct decreased from 81-101 (NG) to 49-67 Ω cm2 (NG@C), while i0 increased from 0.25-0.32 (NG) to 0.38-0.52 mA cm-2 (NG@C) after the coating process. The results suggested both electrochemically and quantitatively that the outer uniformly coated surface carbon layer on the graphite particles can improve the solid-liquid interface and other kinetic parameters, therefore enhancing the rate capabilities to obtain the high-power anode materials.

Intense pulsed light annealing of solution-based indium-gallium-zinc-oxide semiconductors with printed Ag source and drain electrodes for bottom gate thin film transistors

In this study, an intense pulsed light (IPL) annealing process for a printed multi-layered indium-gallium-zinc-oxide (IGZO) and silver (Ag) electrode structure was developed for a high performance all-printed inorganic thin film transistor (TFT). Through a solution process using IGZO precursor and Ag ink, the bottom gate structure TFT was fabricated. The spin coating method was used to form the IGZO semiconductor layer on a heavily-doped silicon wafer covered with thermally grown silicon dioxide. The annealing process of the IGZO layer utilized an optimized IPL irradiation process. The Ag inks were printed on the IGZO layer by screen printing to form the source and drain (S/D) pattern. This S/D pattern was dried by near infrared radiation (NIR) and the dried S/D pattern was sintered with intense pulsed light by varying the irradiation energy. The performances of the all-printed TFT such as the field effect mobility and on-off ratio electrical transfer properties were measured by a parameter analyzer. The interfacial analysis including the contact resistance and cross-sectional microstructure analysis is essential because diffusion phenomenon can occur during the annealing and sintering process. Consequently, this TFT device showed noteworthy performance (field effect mobility: 7.96 cm2/V s, on/off ratio: 107). This is similar performance compared to a conventional TFT, which is expected to open a new path in the printed metal oxide-based TFT field.

Enhancing Reliability and Safety in Industrial Applications: Assessing the Applicability of Energy b-Value to Composites

This study investigates the fracture behavior of glass fiber-reinforced plastic (GFRP) under various loading conditions using acoustic emission (AE) testing. Using fracture tests and time series analysis of AE signals, parameters such as b-value, improved b-value (Ib-value), and energy b-value (be-value) were examined to understand crack initiation, growth, and structural failure. The stress-strain curve revealed distinct responses during tensile and step loading, and time series analysis highlighted variations in amplitude, AE energy, and Kaiser and Felicity effects. Under tensile loading, the Ib-value exhibited a linear decrease, while step loading introduced complexities, including the Felicity effect. The be-value, incorporating energy considerations, fluctuated, providing insights into micro-cracks and macro-cracks. Statistical analysis demonstrated a consistent decrease in the be-value, emphasizing its potential for long-term monitoring. This study provides a comprehensive technique for assessing composite material fracture behavior, enhancing understanding for critical applications in hydrogen storage vessels and pressure pipes as well as advancing reliability and safety in industrial sectors.

Comparison of skin dose in IMRT and VMAT with TrueBeam and Halcyon linear accelerator for whole breast irradiation

With the increasing use of flattening filter free (FFF) beams, it is important to evaluate the impact on the skin dose and target coverage of breast cancer treatments. This study aimed to compare skin doses of treatments using FFF and flattening filter (FF) beams for breast cancer. The study established treatment plans for left breast of an anthropomorphic phantom using Halcyon's 6-MV FFF beam and TrueBeam's 6-MV FF beam. Volumetric modulated arc therapy (VMAT) with varying numbers of arcs and intensity modulated radiation therapy (IMRT) were employed, and skin doses were measured at five points using Gafchromic EBT3 film. Each measurement was repeated three times, and averaged to reduce uncertainty. All plans were compared in terms of plan quality to ensure homogeneous target coverage. The study found that when using VMAT with two, four, and six arcs, in-field doses were 19%, 15%, and 6% higher, respectively, when using Halcyon compared to TrueBeam. Additionally, when using two arcs for VMAT, in-field doses were 10% and 15% higher compared to four and six arcs when using Halcyon. Finally, in-field dose from Halcyon using IMRT was about 1% higher than when using TrueBeam. Our research confirmed that when treating breast cancer with FFF beams, skin dose is higher than with traditional FF beams. Moreover, number of arcs used in VMAT treatment with FFF beams affects skin dose to the patient. To maintain a skin dose similar to that of FF beams when using Halcyon, it may be worth considering increasing the number of arcs.

Self-Assembled Monolayer-Based Hole-Transporting Materials for Perovskite Solar Cells

Ever since self-assembled monolayers (SAMs) were adopted as hole-transporting layers (HTL) for perovskite solar cells (PSCs), numerous SAMs for HTL have been synthesized and reported. SAMs offer several unique advantages including relatively simple synthesis, straightforward molecular engineering, effective surface modification using small amounts of molecules, and suitability for large-area device fabrication. In this review, we discuss recent developments of SAM-based hole-transporting materials (HTMs) for PSCs. Notably, in this article, SAM-based HTMs have been categorized by similarity of synthesis to provide general information for building a SAM structure. SAMs are composed of head, linker, and anchoring groups, and the selection of anchoring groups is key to design the synthetic procedure of SAM-based HTMs. In addition, the working mechanism of SAM-based HTMs has been visualized and explained to provide inspiration for finding new head and anchoring groups that have not yet been explored. Furthermore, both photovoltaic properties and device stabilities have been discussed and summarized, expanding reader's understanding of the relationship between the structure and performance of SAMs-based PSCs.

Enhancing Structural Health Monitoring with Acoustic Emission Sensors: A Case Study on Composites under Cyclic Loading

This study conducts an in-depth analysis of the failure behavior of woven GFRP under cyclic loading, leveraging AE sensors for monitoring damage progression. Utilizing destructive testing and AE methods, we observed the GFRP's response to varied stress conditions. Key findings include identifying distinct failure modes of GFRP and the effectiveness of AE sensors in detecting broadband frequency signals indicative of crack initiation and growth. Notably, the Felicity effect was observed in AE signal patterns, marking a significant characteristic of composite materials. This study introduces the Ibe-value, based on statistical parameters, to effectively track crack development from inception to growth. The Ibe-values potential for assessing structural integrity in composite materials is highlighted, with a particular focus on its variation with propagation distance and frequency-dependent attenuation. Our research reveals challenges in measuring different damage modes across frequency ranges and distances. The effectiveness of Ibe-values, combined with the challenges of propagation distance, underscores the need for further investigation. Future research aims to refine assessment metrics and improve crack evaluation methods in composite materials, contributing to the field's advancement.

Changes in Flight Altitude of Black-Tailed Gulls According to Temporal and Environmental Differences

In this study, GPS trackers were attached to black-tailed gulls (Larus crassirostris) breeding on five islands in Republic of Korea during April and May 2021, and their flight frequency, behavioral range, and flight altitude were compared during and after the breeding season. During the breeding season, the flight frequency was lowest on Dongman Island (28.7%), where mudflats were distributed nearby, and the range of activity was narrow. In contrast, it tended to be high on Gungsi Island (52%), where the breeding colony was far from land, resulting in a wider range of activity. Although the flight frequency on Dongman Island increased post-breeding season (42.7%), it decreased on other islands. The mean flight altitude during the breeding season was lowest on Dongman Island and highest on Napdaegi Island. In most breeding areas, the mean flight altitude during the post-breeding season was higher than that during the breeding season. However, the lead flight altitude was lower during the non-breeding season compared to that in the breeding season. The home range expanded after the breeding season, with no significant difference in lead time between the breeding and non-breeding seasons. Our findings reveal that black-tailed gulls exhibit varying home ranges and flight altitudes depending on season and geographical location. As generalists, gulls display flexible responses to environmental changes, indicating that flight behavior adapts to the evolving environment over time and across regions.

Development of deoxidation process for off-grade titanium sponge using magnesium metal with wire mesh strainer type of crucible

In this study, the deoxidation process for off-grade titanium (Ti) sponge using magnesium (Mg) metal with a wire mesh strainer type of crucible was developed. Ti hydride (TiH2) feedstock, which was prepared by hydrogenating off-grade Ti sponge, was deoxidized using Mg in a molten magnesium chloride-potassium chloride salt at 933 K under an argon and 20% hydrogen (H2) mixed gas atmosphere. After deoxidation, the residual Mg-containing salt was separated in situ from the crucible to investigate the feasibility of minimizing salt loss during the leaching and production of pure TiH2. The results showed that the presence of residual Mg-containing salt inside the crucible strongly influenced whether a mixture of Ti and TiH2 or pure TiH2 was produced. When the salt was not sufficiently separated, a mixture of Ti and TiH2 was obtained and its oxygen (O) concentration was 0.121 mass% under certain conditions. Meanwhile, pure TiH2 was obtained by increasing the H2 gas flow rate during deoxidation. Therefore, these results demonstrate that the decrease of O concentration to below 0.180 mass% and the minimal loss of the salt are feasible.

Improvement in energy performance from the construction of inlet guide vane and diffuser vane geometries in an axial-flow pump

Advanced inlet guide vane (IGV) and diffuser vane (DV) geometries were constructed in an effort to increase the energy performance of an axial-flow pump at the best efficiency point (BEP). DV setting angles were also investigated to increase energy performance at the off-design points. By integrating the advantages of an adjustable IGV, combinations of adjustable IGV and DV geometries were constructed and thoroughly analyzed by way of energy loss. The asymmetrical geometry of the IGV, upgraded through the use of a hydrofoil profile, resulted in higher hydraulic performance compared to that of the reference model. The efficiency and total head at the BEP increased significantly with the implementation of the new DV, by 1.456% and 5.756% over those of the reference model, respectively. Using the new DV reduced the unsteady turbulent flow behind the trailing edge of the DV under all flow rate conditions, resulting in a reduction in vibration and noise. The positive setting angles of the DV increased the energy performance in the high-flow-rate region, whereas the negative DV setting angles produced a good performance in the low-flow-rate region. Combining an adjustable IGV with an adjustable DV model resulted in a significant increase in the total head, with more optimal energy performance provided by the positive IGV setting angles. At the BEP and under high-flow-rate conditions, the low-velocity zone is closely related to high entropy generation. Furthermore, these high-entropy generation regions follow the trajectory of the low-velocity zones. However, the low-velocity zone is not strongly associated with the high-entropy generation region when operating under low-flow-rate conditions.

A facile method of treating spent catalysts via using solvent for recovering undamaged catalyst support

The process of washing and removing crude oil from spent catalysts is a serious issue in both catalyst regeneration and precious metals recovery. In this work, five different solvents with various polar and aromatic properties were chosen to evaluate their impact on the catalyst support structure and crude oil recovery from oil-contaminated spent catalysts. After the deoiling process, the spent catalyst was analyzed by scanning electron microscopy, X-ray diffraction (XRD), Fourier transform-infrared spectroscopy, elemental analyzer, contact angle measurement, gas chromatography-mass spectrometry, inductively coupled plasma-atomic emission spectroscopy, and Brunauer Emmet Teller (BET) method. Our findings demonstrate that p-xylene and kerosene are more effective in removing oil than other solvents. This is due to crude oil's similar polarity and molecular nature with kerosene and p-xylene. Considering the economical reason, kerosene is a better choice for deoiling spent catalyst compared to p-xylene as it is more affordable than p-xylene. XRD data show that the structure of the catalyst support was unaltered by the solvent treatment process, while BET data reveals that the surface area and pore volume are significantly enhanced after the deoiling process. These results imply that deoiling is a very crucial step for the recycling, regeneration, and reuse of spent catalysts. Our work is significant in developing sustainable approaches for managing spent catalysts, and minimizing waste and environmental pollution.

Stochastic lithofacies and petrophysical property modeling for fast history matching in heterogeneous clastic reservoir applications

For complex and multi-layered clastic oil reservoir formations, modeling lithofacies and petrophysical parameters is essential for reservoir characterization, history matching, and uncertainty quantification. This study introduces a real oilfield case study that conducted high-resolution geostatistical modeling of 3D lithofacies and petrophysical properties for rapid and reliable history matching of the Luhais oil reservoir in southern Iraq. For capturing the reservoir's tidal depositional setting using data collected from 47 wells, the lithofacies distribution (sand, shaly sand, and shale) of a 3D geomodel was constructed using sequential indicator simulation (SISIM). Based on the lithofacies modeling results, 50 sets of porosity and permeability distributions were generated using sequential Gaussian simulation (SGSIM) to provide insight into the spatial geological uncertainty and stochastic history matching. For each rock type, distinct variograms were created in the 0° azimuth direction, representing the shoreface line. The standard deviation between every pair of spatial realizations justified the number of variograms employed. An upscaled version of the geomodel, incorporating the lithofacies, permeability, and porosity, was used to construct a reservoir-flow model capable of providing rapid, accurate, and reliable production history matching, including well and field production rates.

Construction of a uniform zeolitic imidazole framework (ZIF-8) nanocrystal through a wet chemical route towards supercapacitor application

Exploring larger surface area electrode materials is crucial for the development of an efficient supercapacitors (SCs) with superior electrochemical performance. Herein, a cost-effective strategy was adopted to synthesize a series of ZIF8 nanocrystals, and their size effect as a function of surface area was also examined. The resultant ZIF8-4 nanocrystal exhibits a uniform hexagonal structure with a large surface area (2800 m2 g-1) and nanometre size while maintaining a yield as high as 78%. The SCs performance was explored by employing different aqueous electrolytes (0.5 M H2SO4 and 1 M KOH) in a three-electrode set-up. The SC performance using a basic electrolyte (1 M KOH) was superior owing to the high ionic mobility of K+. The optimized ZIF8-4 nanocrystal electrode showed a faradaic reaction with a highest capacitance of 1420 F g-1 at 1 A g-1 of current density compared to other as-prepared electrodes in the three-electrode assembly. In addition, the resultant ZIF8-4 was embedded into a symmetric supercapacitor (SSC), and the device offered 350 F g-1 of capacitance with a maximum energy and power density of 43.7 W h kg-1 and 900 W kg-1 at 1 A g-1 of current density, respectively. To determine the practical viewpoint and real-world applications of the ZIF8-4 SSC device, 7000 GCD cycles were performed at 10 A g-1 of current density. Significantly, the device exhibited a cycling stability around 90% compared to the initial capacitance. Therefore, these findings provide a pathway for constructing large surface area ZIF8-based electrodes for high-value-added energy storage applications, particularly supercapacitors.

Photo-Rechargeable Asymmetric Supercapacitors Exceeding Light-to-Charge Storage Efficiency over 21% under Indoor Light

Photo-rechargeable energy storage devices are appealing for substantial research attention because of their possible applications in the Internet of Things (IoT) and low-powered miniaturized portable electronics. However, due to the incompatibility of the photovoltaics and energy storage systems (ESSs), the overall light-to-storage efficiency is limited under indoor light conditions. Herein, a porous carbon scaffold MnO-Mn3 O4 /C microsphere-based monolithic dye-sensitized photo-rechargeable asymmetric supercapacitor (DSPC) is fabricated. The integrated DSPC has a high areal specific capacitance of 281.9 mF cm-2 at the discharge rate of 0.01 mA cm-2 . The light-to-electrical conversion efficiency of the DSSC is 27.6% under the 1000 lux compact fluorescent lamp (CFL). The DSPC shows an outstanding light-to-charge storage efficiency of 21.6%, which is higher than that reported ever. Furthermore, the fabricated polymer gel electrolyte-based quasi-solid state (QSS) DSPC shows similar overall conversion efficiency with superior cycling capability. This work shows a convenient fabrication process for a wireless power pack of interest with outstanding performance.

A Synthetic Time-Series Generation Using a Variational Recurrent Autoencoder with an Attention Mechanism in an Industrial Control System

Data scarcity is a significant obstacle for modern data science and artificial intelligence research communities. The fact that abundant data are a key element of a powerful prediction model is well known through various past studies. However, industrial control systems (ICS) are operated in a closed environment due to security and privacy issues, so collected data are generally not disclosed. In this environment, synthetic data generation can be a good alternative. However, ICS datasets have time-series characteristics and include features with short- and long-term temporal dependencies. In this paper, we propose the attention-based variational recurrent autoencoder (AVRAE) for generating time-series ICS data. We first extend the evidence lower bound of the variational inference to time-series data. Then, a recurrent neural-network-based autoencoder is designed to take this as the objective. AVRAE employs the attention mechanism to effectively learn the long-term and short-term temporal dependencies ICS data implies. Finally, we present an algorithm for generating synthetic ICS time-series data using learned AVRAE. In a comprehensive evaluation using the ICS dataset HAI and various performance indicators, AVRAE successfully generated visually and statistically plausible synthetic ICS data.

Investigation of Corrosion Behavior of Oxygen-Free Copper Canisters in Groundwater Chemistry of Deep Geological Repositories

The disposal of nuclear waste represents a paramount concern for human safety, and the corrosion resistance of containers within the disposal environment stands as a critical factor in ensuring the integrity of such waste containment systems. In this report, the corrosion behavior of copper canisters was monitored in Olkiluoto-simulated/-procured groundwater (South Korea) with different temperatures. The exposure of copper in the procured groundwater at 70 °C revealed a 3.7-fold increase in corrosion vulnerability compared with room temperature conditions, with a current density of 12.7 μA/cm2. During a three-week immersion test in a controlled 70 °C chamber, the canister in the Korean groundwater maintained a constant weight. In contrast, its counterpart in the simulated groundwater revealed continuous weight loss, indicating heightened corrosion. An X-ray diffraction (XRD) analysis identified corrosion byproducts, specifically Cu2Cl3(OH) and calcite (CaCO3), in the simulated groundwater, confirming its corrosive nature. The initial impedance analysis revealed distinct differences: Korean groundwater exhibits high pore resistance and diffusion effects, while the simulated groundwater shows low pore resistance. Consequently, the corrosion of copper canisters in the Korean environment is deemed relatively stable because of significant differences in ion concentrations.

Numerical Study of Flow and Heat Transfer Characteristics for Al2O3 Nanofluid in a Double-Pipe Helical Coil Heat Exchanger

To numerically investigate the flow and heat transfer characteristics of a water/Al2O3 nanofluid in a double-pipe helical coil heat exchanger, we simulated a two-phase Eulerian model to predict the heat transfer coefficient, Nusselt number, and pressure drop at various concentrations (i.e., volume fraction) and under diverse flow rates at the steady state. In this simulation, we used the k-epsilon turbulence model with an enhanced wall treatment method. The performance factor of the nanofluid was evaluated by accounting for the heat transfer and pressure drop characteristics. As a result, the heat transfer was enhanced by increasing the nanofluid concentration. The 1.0 vol.% nanofluid (i.e., the highest concentration) showed a heat transfer coefficient 1.43 times greater than water and a Nusselt number of 1.38 times greater than water. The pressure drop of nanofluids was greater than that of water due to the increased density and viscosity induced using nanoparticles. Based on the relationship between the Nusselt number and pressure drop, the 1.0 vol.% nanofluid was calculated to have a performance factor of 1.4 relative to water, indicating that the enhancement rate in heat transfer performance was greater than that in the pressure drop. In conclusion, the Al2O3 nanofluid shows potential as an enhanced working fluid in diverse heat transfer applications.

Optimization of Aging Temperature and Heat-Treatment Pathways in Additively Manufactured 17-4PH Stainless Steel

This study investigates the tensile behaviors of additively manufactured (AM) 17-4PH stainless steels heat-treated within various temperature ranges from 400 °C to 700 °C in order to identify the effective aging temperature. Despite an aging treatment of 400-460 °C increasing the retained austenite content, an enhancement of the tensile properties was achieved without a strength-ductility trade-off owing to precipitation hardening by the Cu particles. Due to the intricate evolution of the microstructure, aging treatments above 490 °C led to a loss in yield strength and ductility. A considerable rise in strength and a decrease in ductility were brought about by the increase in the fraction of precipitation-hardened martensitic matrix in aging treatments over 640 °C. The impact of heat-treatment pathways on aging effectiveness and tensile anisotropy was then examined. Direct aging at 482 °C for an hour had hardly any effect on wrought 17-4PH, but it increased the yield strength of AM counterparts from 436-457 to 588-604 MPa. A solid-solution treatment at 1038 °C for one hour resulted in a significant drop in the austenite fraction, which led to an increase in the yield (from 436-457 to 841-919 MPa) and tensile strengths (from 1106-1127 to 1254-1256 MPa) with a sacrifice in ductility. Improved strength and ductility were realized by a solid-solution followed by an aging treatment, achieving 1371-1399 MPa. The tensile behaviors of AM 17-4PH were isotropic both parallel and perpendicular to the building direction.

Effects of the Electrical Properties of SnO2 and C60 on the Carrier Transport Characteristics of p-i-n-Structured Semitransparent Perovskite Solar Cells

Recently, metal halide perovskite-based top cells have shown significant potential for use in inexpensive and high-performance tandem solar cells. In state-of-the-art p-i-n perovskite/Si tandem devices, atomic-layer-deposited SnO2 has been widely used as a buffer layer in the top cells because it enables conformal, pinhole-free, and highly transparent buffer layer formation. In this work, the effects of various electrical properties of SnO2 and C60 layers on the carrier transport characteristics and the performance of the final devices were investigated using a numerical simulation method, which was established based on real experimental data to increase the validity of the model. It was found that the band alignment at the SnO2/C60 interface does, indeed, have a significant impact on the electron transport. In addition, as a general design rule, it was suggested that at first, the conduction band offset (CBO) between C60 and SnO2 should be chosen so as not to be too negative. However, even in a case in which this CBO condition is not met, we would still have the means to improve the electron transport characteristics by increasing the doping density of at least one of the two layers of C60 and/or SnO2, which would enhance the built-in potential across the perovskite layer and the electron extraction at the C60/SnO2 interface.

Phantom study of layered sensor module for photon-counting BMD detector

In this study, we perform bone mineral density (BMD) calculation by designing a layered sensor module (LSM) that divides high- and low-energy spectra from a single shot of X-rays. Gamma-ray evaluation supports this mechanism; low-energy gamma rays are absorbed in the front detector, whereas high-energy gamma rays are absorbed in the rear detector. In this phantom study, LSM divides a single shot of X-ray into two spectra with different distributions of energy, thereby affording X-ray images with different properties, such as contrast and gray scale. The region of interest (ROI) is classified by the Prewitt operator to sort the pixels for BMD calculation or Rs value. The calculated final value is 1.2051 g/cm2 with a standard deviation (SD) of 0.3690 g/cm2, as obtained from our previous study. An improved SD results from the layered structure with two channels for signal processing, the introduction of Rs value, and the use of Prewitt filter to sort reliable data. Overall, this study displays the feasibility of LSM for BMD calculation with a small error, thereby enabling the diagnosis of osteoporosis with novel mechanism.

Debottlenecking and reformulating feed media for improved CHO cell growth and titer by data-driven and model-guided analyses

Designing and selecting cell culture media along with their feeding are a key strategy to maximize culture performance in biopharmaceutical processes. However, the sensitivity of mammalian cells to their culture environment necessitates specific nutritional requirements for their growth and the production of high-quality proteins such as antibodies, depending on the cell lines and operational conditions employed. In this regard, previously we developed a data-driven and in-silico model-guided systematic framework to investigate the effect of growth media on Chinese hamster ovary (CHO) cell culture performance, allowing us to design and reformulate basal media. To expand our exploration for media development research, we evaluated two chemically defined feed media, A and B, using a monoclonal antibody-producing CHO-K1 cell line in ambr15 bioreactor runs. We observed a significant impact of the feed media on various aspects of cell culture, including growth, longevity, viability, productivity, and the production of toxic metabolites. Specifically, the concentrated feed A was inadequate in sustaining prolonged cell culture and achieving high titers when compared to feed B. Within our framework, we systematically investigated the major metabolic bottlenecks in the tricarboxylic acid cycle and relevant amino acid transferase reactions. This analysis identified target components that play a crucial role in alleviating bottlenecks and designing highly productive cell cultures, specifically the addition of glutamate to feed A and asparagine to feed B. Based on our findings, we reformulated the feeds by adjusting the amounts of the targeted amino acids and successfully validated the effectiveness of the strategy in promoting cell growth, life span, and/or titer.

Highly Efficient and Stable Inverted Perovskite Solar Cell Using Pure δ-FAPbI3 Single Crystals

Pure δ-formamidinium lead triiodide (δ-FAPbI3 ) single crystal for highly efficient perovskite solar cell (PCS) with long-term stability is prepared by a new method consisting of liquid phase reaction of FAI and PbI2 in N,N-dimethyl formamide and antisolvent crystallization using acetonitrile. In this method, the incorporation of any impurity into the crystal is excluded by the molecular recognition of the crystal growth site. This pure crystal is used to fabricate α-FAPbI3 inverted PSCs which showed excellent power conversion efficiency (PCE) due to much-reduced trap-states. The champion device exhibited a high PCE of 23.48% under the 1-Sun condition. Surface-treated devices with 3-(aminomethyl)pyridine showed a significantly improved PCE of 25.07%. In addition, the unencapsulated device maintained 97.22% of its initial efficiency under continuous 1-Sun illumination for 1,000 h at 85 °C in an N2 atmosphere ensuring long-term thermal and photo stabilities of PSCs, whereas the control device kept only 89.93%.

Performance Improvement of an STS304-Based Dispensing Needle via Electrochemical Etching

In this study, we explored the formation of micro-/nanosized porous structures on the surface of a needle composed of STS304 and examined the effect of conventional needles and needles capable of liquid ejection. Aqua regia, composed of HCl and HNO3, was electrochemically etched to form appropriately sized micro-/nanoporous structures. We observed that when dispensing liquids with low surface tension, they do not immediately fall downward but instead spread over the exterior surface of the needle before falling. We found that the extent of spreading on the surface is influenced by an etched porous structure. Furthermore, to analyze the effect of surface tension differences, we dispensed liquids with varying surface tensions using etched needles. Through the analysis, it was confirmed that, despite the low surface tension, the ejected droplet volume and speed could be stably maintained on the etched needle. This indicates that the spreading phenomenon of the liquid on the needle surface just before ejection can be controlled by the micro/nanoporous structure. We anticipate that these characteristics of etched needles could be utilized in industries where precision dispensing of low-surface-tension liquids is essential.

Changes in the Optical Properties of Rubber Exposed to High-Pressure Hydrogen Using Pulsed Terahertz Waves

In this study, we investigated how high-temperature, high-pressure hydrogen affects the optical properties of three kinds of sealing rubber (chloroprene rubber, ethylene propylene diene monomer, and acrylonitrile butadiene rubber) using pulsed terahertz waves. The optical properties of the rubber samples were analyzed before and after exposure to hydrogen (80 °C and 200 bar) for 72 h. The results showed that the terahertz waves had a shorter time delay and a lower signal intensity for all rubber types. The exposure response intensity, refractive index, and absorption rate also changed in the frequency domain. Raman and Fourier transform infrared spectroscopy were used for comparison, and a few peak shifts were observed. However, the Raman spectra had low signal quality, and the laser damaged the specimen. The study demonstrates that terahertz waves can be used as a non-contact non-destructive testing technique to evaluate the changes in sealing rubbers after hydrogen exposure.

Exploring the source of ammonia generation in electrochemical nitrogen reduction using niobium nitride

In this study, niobium nitride (NbN) is prepared via the urea-glass route by annealing a mixture of NbCl5 and urea at 650 °C under a flow of N2, and is used as a catalyst for the electrochemical nitrogen reduction reaction (NRR). The as-prepared NbN exhibits a maximum production rate of 5.46 × 10-10 mol s-1 cm-2 at -0.6 V vs. RHE, along with an apparent FE of 16.33% at -0.3 V vs. RHE. In addition, the leaching of NbN is confirmed by ICP-OES, where the leached amount of Nb is almost identical to the amount of N measured by UV-vis. Moreover, 1H NMR experiments are performed using 15N2 as the feeder gas; the dominant detection of 14NH4+ peaks strongly suggests that the produced NH3 originates from the leaching of NbN rather than via an electrocatalytic process. Hence, for a comprehensive understanding of NH3 generation, especially when utilizing transition metal nitride (TMN)-based NRR catalysts, a thorough investigation employing multiple analytical methods is imperative.

Fe2O3/Ni Nanocomposite Electrocatalyst on Cellulose for Hydrogen Evolution Reaction and Oxygen Evolution Reaction

A key challenge in the development of sustainable water-splitting (WS) systems is the formulation of electrodes by efficient combinations of electrocatalyst and binder materials. Cellulose, a biopolymer, can be considered an excellent dispersing agent and binder that can replace high-cost synthetic polymers to construct low-cost electrodes. Herein, a novel electrocatalyst was fabricated by combining Fe2O3 and Ni on microcrystalline cellulose (MCC) without the use of any additional binder. Structural characterization techniques confirmed the formation of the Fe2O3-Ni nanocomposite. Microstructural studies confirmed the homogeneity of the ~50 nm-sized Fe2O3-Ni on MCC. The WS performance, which involves the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER), was evaluated using a 1 M KOH electrolyte solution. The Fe2O3-Ni nanocomposite on MCC displayed an efficient performance toward lowering the overpotential in both the HER (163 mV @ 10 mA cm-2) and OER (360 mV @ 10 mA cm-2). These results demonstrate that MCC facilitated the cohesive binding of electrocatalyst materials and attachment to the substrate surface. In the future, modified cellulose-based structures (such as functionalized gels and those dissolved in various media) can be used as efficient binder materials and alternative options for preparing electrodes for WS applications.

Utilizing Machine Learning and Diode Physics to Investigate the Effects of Stoichiometry on Photovoltaic Performance in Sequentially Processed Perovskite Solar Cells

Organic-inorganic metal halide perovskite solar cells are renowned for their extensive solution processability, although the production of uniformly crystalline perovskite films can necessitate intricate deposition methods. In our study, we harmonized Shockley diode-based numerical analysis with machine learning techniques to extract the device characteristics of perovskite solar cells and optimize their photovoltaic performance in light of the experimental variables. The application of the Shockley diode equation facilitated the extraction of photovoltaic parameters and the prediction of power conversion efficiencies, thus aiding the understanding of device physics and charge recombination. Through machine learning, specifically Gaussian process regression, we trained models on current-voltage curves sensitive to variations in fabrication conditions, thereby pinpointing the optimal settings for enhanced device performance. Our multifaceted approach not only clarifies the interplay between experimental conditions and device performance but also streamlines the optimization process, diminishing the need for exhaustive trial-and-error experiments. This methodology holds substantial promise for advancing the development and fine-tuning of next-generation perovskite solar cells.

Recent Progress in Functional Nanomaterials towards the Storage, Separation, and Removal of Tritium

Tritium is a sustainable next-generation prime fuel for generating nuclear energy through fusion reactions to fulfill the increasing global energy demand. Owing to the scarcity-high demand tradeoff, tritium must be bred inside a fusion reactor to ensure sustainability and must therefore be separated from its isotopes (protium and deuterium) in pure form, stored safely, and supplied on demand. Existing multistage isotope separation technologies exhibit low separation efficiency and require intensive energy inputs and large capital investments. Furthermore, tritium-contaminated heavy water constitutes a major fraction of nuclear waste, and accidents like the one at Fukushima Daiichi leave behind thousands of tons of diluted tritiated water, whose removal is beneficial from an environmental point of view. In this review, the recent progress and main research trends in hydrogen isotope storage and separation by focusing on the use of metal hydride (e.g., intermetallic, and high-entropy alloys), porous (e.g., zeolites and metal organic frameworks (MOFs)), and 2-D layered (e.g., graphene, hexagonal boron nitride (h-BN), and MXenes) materials to separate and store tritium based on their diverse functionalities are discussed. Finally, the challenges and future directions for implementing tritium storage and separation are summarized in the reviewed materials.

A thematic review on livestock manure treatment strategies focusing on thermochemical conversion

Livestock manure (LSM) management is emerging as a challenge due to increasing livestock consumption. Owing to the decreased agricultural land area, it is necessary to ensure LSM utilization in non-agricultural fields. LSM can be a valuable resource if managed as a circulating resource. This study discusses research trends based on a literature review and classifies LSM treatments. The analysis of each treatment is presented according to research trends, and implications for the future LSM processing are discussed. "Biological treatment" accounted for the largest portion at 48%, "manure management," which suggests improvement in manure treatment through systematic thinking or LSM management practices, accounted for 16%, and "thermochemical conversion" accounted for 11%. In addition, "life cycle assessment (LCA) research," "solid-liquid separation approach," and "nutrient-recovery/losses" were derived. Studies on biological treatments are increasing. Although anaerobic digestion (AD) is the most used method, it has the disadvantages of long processing time and waste generation after processing. As a key supplement, thermochemical conversion (TCC) technology, which could overcome the disadvantages of AD, was reviewed.

Flexible Metasurface for Microwave-Infrared Compatible Camouflage via Particle Swarm Optimization Algorithm

Metamaterials have the powerful ability to freely control multiband electromagnetic (EM) waves through elaborately designed "artificial atoms" and are hence in the limelight in various fields. Typically, camouflage materials manipulate wave-matter interactions to achieve the desired optical properties, in particular, various techniques are used for multiband camouflage materials in both infrared (IR) and microwave (MW) ranges to overcome the scale difference between these bands. However, in the context of components required for microwave communications, simultaneous control of IR emission and MW transmission is required, which is challenging owing to differences in the wave-matter interactions in these two bands. Herein, the state-of-the-art concept of flexible compatible camouflage metasurface (FCCM) is demonstrated, which can manipulate IR signatures while maintaining MW selective transmission simultaneously. For achieving maximum IR tunability and MW selective transmission, it is performed optimization using the particle swarm optimization (PSO) algorithm. Consequently, the FCCM exhibits compatible camouflage performance with both IR signature reduction and MW selective transmission is demonstrated, with 77.7% IR tunability and 93.8% transmission achieved for a flat FCCM. Furthermore, the FCCM reached the 89.8% IR signature reduction effect even in curved situations.

Reliability Analysis of PAUT Based on the Round-Robin Test for Pipe Welds with Thermal Fatigue Cracks

Thermal fatigue cracks occurring in pipes in nuclear power plants pose a high degree of risk. Thermal fatigue cracks are generated when the thermal fatigue load caused by local temperature gradients is repeatedly applied. The flaws are mainly found in welds, owing to the effects of stress concentration caused by the material properties and geometric shapes of welds. Thermal fatigue pipes are classified as targets of risk-informed in-service inspection, for which ultrasonic testing, a volumetric non-destructive testing method, is applied. With the advancement of ultrasonic testing techniques, various studies have been conducted recently to apply the phased array ultrasonic testing (PAUT) method to the inspection of thermal fatigue cracks occurring on pipes. A quantitative reliability analysis of the PAUT method must be performed to apply the PAUT method to on-site thermal fatigue crack inspection. In this study, to evaluate the quantitative reliability of the PAUT method for thermal fatigue cracks, we fabricated crack specimens with the thermal fatigue mechanism applied to the pipe welds. We performed a round-robin test to collect PAUT data and determine the validity of the detection performance (probability of detection; POD) and the error in the sizing accuracy (root-mean-square error; RMSE) evaluation. The analysis results of the POD and sizing performance of the length and depth of thermal fatigue cracks were comparatively evaluated with the acceptance criteria of the American Society of Mechanical Engineers Code to confirm the effectiveness of applying the PAUT method.

Anomaly Detection Using an Ensemble of Multi-Point LSTMs

As technologies for storing time-series data such as smartwatches and smart factories become common, we are collectively accumulating a great deal of time-series data. With the accumulation of time-series data, the importance of time-series abnormality detection technology that detects abnormal patterns such as Cyber-Intrusion Detection, Fraud Detection, Social Networks Anomaly Detection, and Industrial Anomaly Detection is emerging. In the past, time-series anomaly detection algorithms have mainly focused on processing univariate data. However, with the development of technology, time-series data has become complicated, and corresponding deep learning-based time-series anomaly detection technology has been actively developed. Currently, most industries rely on deep learning algorithms to detect time-series anomalies. In this paper, we propose an anomaly detection algorithm with an ensemble of multi-point LSTMs that can be used in three cases of time-series domains. We propose our anomaly detection model that uses three steps. The first step is a model selection step, in which a model is learned within a user-specified range, and among them, models that are most suitable are automatically selected. In the next step, a collected output vector from M LSTMs is completed by stacking ensemble techniques of the previously selected models. In the final step, anomalies are finally detected using the output vector of the second step. We conducted experiments comparing the performance of the proposed model with other state-of-the-art time-series detection deep learning models using three real-world datasets. Our method shows excellent accuracy, efficient execution time, and a good F1 score for the three datasets, though training the LSTM ensemble naturally requires more time.

Real-time visualisation of ion exchange in molecularly confined spaces where electric double layers overlap

Ion interactions with interfaces and transport in confined spaces, where electric double layers overlap, are essential in many areas, ranging from crevice corrosion to understanding and creating nano-fluidic devices at the sub 10 nm scale. Tracking the spatial and temporal evolution of ion exchange, as well as local surface potentials, in such extreme confinement situations is both experimentally and theoretically challenging. Here, we track in real-time the transport processes of ionic species (LiClO4) confined between a negatively charged mica surface and an electrochemically modulated gold surface using a high-speed in situ sensing Surface Forces Apparatus. With millisecond temporal and sub-micrometer spatial resolution we capture the force and distance equilibration of ions in the confinement of D ≈ 2-3 nm in an overlapping electric double layer (EDL) during ion exchange. Our data indicate that an equilibrated ion concentration front progresses with a velocity of 100-200 μm s-1 into a confined nano-slit. This is in the same order of magnitude and in agreement with continuum estimates from diffusive mass transport calculations. We also compare the ion structuring using high resolution imaging, molecular dynamics simulations, and calculations based on a continuum model for the EDL. With this data we can predict the amount of ion exchange, as well as the force between the two surfaces due to overlapping EDLs, and critically discuss experimental and theoretical limitations and possibilities.

Practical Approach for Determining Material Parameters When Predicting Austenite Grain Growth under Isothermal Heat Treatment

An investigation of austenite grain growth (AGG) during the isothermal heat treatment of low-alloy steel is conducted. The goal is to uncover the effect of time, temperature, and initial grain size on SA508-III steel grain growth. Understanding this relationship enables the optimization of the time and temperature of the heat treatment to achieve the desired grain size in the studied steel. A modified Arrhenius model is used to model austenite grain size (AGS) growth distributions. With this model, it is possible to predict how grain size will change depending on heat treatment conditions. Then, the generalized reduced gradient (GRG) optimization method is employed under adiabatic conditions to characterize the model's parameters, providing a more precise solution than traditional methods. With optimal model parameters, predicted AGS agree well with measured values. The model shows that AGS increases faster as temperature and time increase. Similarly, grain size grows directly in proportion to the initial grain size. The optimized parameters are then applied to a practical case study with a similar specimen size and material properties, demonstrating that our approach can efficiently and accurately predict AGS growth via GRG optimization.

A Hybrid Deep Learning Approach: Integrating Short-Time Fourier Transform and Continuous Wavelet Transform for Improved Pipeline Leak Detection

A hybrid deep learning approach was designed that combines deep learning with enhanced short-time Fourier transform (STFT) spectrograms and continuous wavelet transform (CWT) scalograms for pipeline leak detection. Such detection plays a crucial role in ensuring the safety and integrity of fluid transportation systems. The proposed model leverages the power of STFT and CWT to enhance detection capabilities. The pipeline's acoustic emission signals during normal and leak operating conditions undergo transformation using STFT and CWT, creating scalograms representing energy variations across time-frequency scales. To improve the signal quality and eliminate noise, Sobel and wavelet denoising filters are applied to the scalograms. These filtered scalograms are then fed into convolutional neural networks, extracting informative features that harness the distinct characteristics captured by both STFT and CWT. For enhanced computational efficiency and discriminatory power, principal component analysis is employed to reduce the feature space dimensionality. Subsequently, pipeline leaks are accurately detected and classified by categorizing the reduced dimensional features using t-distributed stochastic neighbor embedding and artificial neural networks. The hybrid approach achieves high accuracy and reliability in leak detection, demonstrating its effectiveness in capturing both spectral and temporal details. This research significantly contributes to pipeline monitoring and maintenance and offers a promising solution for real-time leak detection in diverse industrial applications.

Manipulating the Cathodic Modification Effect on Corrosion Resistance of High Corrosion-Resistant Titanium Alloy

Further improving the corrosion resistance of the ASTM Grade 13 (Gr13) titanium alloy was achieved by manipulating the cathodic modification effect. The cathodic modification of Gr13 was mainly related to the Ti2Ni precipitate, where minor Ru was contained and controlled the precipitate in terms of size and distribution, which could manipulate the cathodic modification effect. Parameters such as temperature and cooling rate during the recrystallization process were designed to control precipitation behavior, where the temperature at 850 °C was selected to allow the full dissolution of the Ti2Ni precipitate. The cooling rate, as high as 160.9 °C/min, was still enough for precipitation to occur during the cooling stage, leading to the formation of the Ti2Ni precipitate along with a grain boundary. The cooling rate of water quenching was too fast to cause the diffusion process, resulting in a large amount of the β-Ti phase without the precipitate, which was pre-formed while heated at 850 °C. Aging at 600 °C caused the re-precipitation of Ti2Ni, and, at that moment, the precipitate was refined and separated, as a good aspect of the catalyst for HER. Therefore, the aged sample after water quenching showed the lowest onset potential for HER with the highest corrosion potential, indicating that its passivation ability was improved by the strengthened cathodic modification effect. This improvement was confirmed by the OCP results, where passivation survival was observed for the aged sample due to the highest cathodic modification effect. Therefore, the aged sample, which had refined and separate precipitates, showed the lowest corrosion rate.

Rosen-Type Piezoelectric Transformers Based on 0.5Ba(Zr0.2Ti0.8)O3-0.5(Ba0.7Ca0.3)TiO3 Ceramic and Doped with Sb2O3

In this study, the characteristics in the lead-free piezoelectric ceramic 0.5Ba(Zr0.2Ti0.8)O3-0.5(Ba0.7Ca0.3)TiO3 (0.5BZT-0.5BCT) were investigated to assess its potential for Rosen-type piezoelectric transformers. This piezoelectric ceramic has a piezoelectric charge coefficient d33 of 430 pC/N, an electromechanical coupling factor kp of 49%, a dielectric constant εr of 2836, a remnant polarization Pr of 4.98 μC/cm2, and a coercive electric field Ec of 2.41 kV/cm. Sb2O3 was soft doped with 0.05, 0.1, 0.15, and 0.2 mol%, respectively, and exhibited excellent physical properties at 0.1 mol%. Based on this, a piezoelectric transformer was fabricated and measured, and it showed better output characteristics than pure 0.5BZT-0.5BCT. The amplification ratio (Vout/Vin) was optimized based on the device geometry and properties of the piezoelectric material. Moreover, the output characteristics of the Rosen-type piezoelectric transformer were simulated with the PSpice program. Output values of the fabricated and simulated piezoelectric transformers for the r vibrational frequency were compared and analyzed. Accordingly, the step-up amplification ratios Vout/Vin of the fabricated and simulated devices at the vibrational frequency were compared as well. This piezoelectric transformer could replace silicon steel transformers and be used for the creation of black light and for laptop chargers.

Development of 3D Printable Calcium Phosphate Cement Scaffolds with Cockle Shell Powders

Three-dimensional (3D) printed calcium phosphate cement (CPC) scaffolds are increasingly being used for bone tissue repair. Traditional materials used for CPC scaffolds, such as bovine and porcine bone, generally contain low amounts of calcium phosphate compounds, resulting in reduced production rates of CPC scaffolds. On the other hand, cockle shells contain more than 99% CaCO3 in the form of amorphous aragonite with excellent biocompatibility, which is expected to increase the CPC production rate. In this study, 3D-printed cockle shell powder-based CPC (CSP-CPC) scaffolds were developed by the material extrusion method. Lactic acid and hyaluronic acid were used to promote the printability. The characterization of CSP-CPC scaffolds was performed using Fourier transform infrared spectra, X-ray diffraction patterns, and scanning electron microscopy. The biocompatibility of CSP-CPC scaffolds was evaluated using cell viability, Live/Dead, and alkaline phosphatase assays. In addition, CSP-CPC scaffolds were implanted into the mouse calvarial defect model to confirm bone regeneration. This study provides an opportunity to create high value added in fishing villages by recycling natural products from marine waste.

Facile one-pot synthesis of biomass-derived activated carbon as an interlayer material for a BAC/PE/Al2O3 dual coated separator in Li-S batteries

Lithium-sulfur batteries (LSB) are an attractive alternative electrochemical energy storage device compared to conventional lithium-ion batteries due to their higher theoretical capacity and energy density. Despite these advantages, it is still difficult to commercialize LSB because of poor electrochemical performance caused by the dissolution of soluble lithium polysulfides (LiPS). To solve these critical issues, a multi-functional separator was prepared using biomass-derived activated carbon (BAC) and a ceramic layer on the polyethylene (PE) separator. For this purpose, BAC was synthesized by a facile one-pot synthesis method by a specifically designed furnace using various forms of milk waste. The multi-functional separator suppresses the effect of LiPS dissolution and increases the Li+ diffusion kinetics. BAC was able to absorb the LiPS shuttle, as confirmed by UV-vis measurements and X-ray photoelectron spectroscopy (XPS). LSB cells assembled using this multi-functional separator show a higher discharge capacity of 1092.5 mA h g-1 at 0.1 C-rate, while commercial PE separators deliver a specific capacity of 811.8 mA h g-1. These novel separators were also able to suppress lithium dendrites during cycling. This work offers a novel and simple approach for streamlining the synthesis process of BAC and applying it to LSB, aiding in the development of sustainable energy sources.

Nanomaterials for Advanced Photocatalytic Plastic Conversion

As the disposal of waste plastic emerges as a societal problem, photocatalytic waste plastic conversion is attracting significant attention. Ultimately, for a sustainable future, the development of an eco-friendly plastic conversion technology is essential for breaking away from the current plastic use environment. Compared to conventional methods, photocatalysis can be a more environmentally friendly option for waste plastic reprocessing because it uses sunlight as an energy source under ambient temperature and pressure. In addition to this, waste plastics can be upcycled (i.e., converted into useful chemicals or fuels) to enhance their original value via photocatalytic methods. Among various strategies for improving the efficiency of the photocatalytic method, nanomaterials have played a pivotal role in suppressing charge recombination. Hence, in recent years, attempts have been made to introduce nanomaterials/nanostructures into photocatalytic plastic conversion on the basis of advances in material-based studies using simple photocatalysts. In line with this trend, the present review examines the nanomaterials/nanostructures that have been recently developed for photocatalytic plastic conversion and discusses the direction of future development.

Development of open access tool for automatic use factor calculation using DICOM-RT patient data

Our study recalculated the use factor of linear accelerators (LINACs) by using an in-house program based on Digital Imaging and Communications in Medicine radiation therapy (DICOM-RT). We considered the impact of advancements and changes in treatment trends, including modality, technology, and radiation dose, on the use factor, which is one of the shielding parameters. In accordance with the methodology described in the NCRP 151 report, we computed the use factor for four linear accelerators (LINACs) across three hospitals. We analyzed the results based on the treatment techniques and treatment sites for three-dimensional conformal radiation therapy (3D-CRT) and intensity modulated radiation therapy or volumetric modulated arc therapy. Our findings revealed that the use factors obtained at 45° and 90° were 14.8% and 13.5% higher than those of the NCRP 151 report. In treatment rooms with a high 3D-CRT ratio, the use factor at a specific angle differed by up to 14.6% relative to the NCRP 151 report value. Our results showed a large difference in the use factor for specific sites such as the breast and spine, so it is recommended that each institution recalculate the use factor using patient's data.

Development of Silk Fibroin-Based Non-Crosslinking Thermosensitive Bioinks for 3D Bioprinting

Three-dimensional (3D) bioprinting holds great promise for tissue engineering, allowing cells to thrive in a 3D environment. However, the applicability of natural polymers such as silk fibroin (SF) in 3D bioprinting faces hurdles due to limited mechanical strength and printability. SF, derived from the silkworm Bombyx mori, is emerging as a potential bioink due to its inherent physical gelling properties. However, research on inducing thermosensitive behavior in SF-based bioinks and tailoring their mechanical properties to specific tissue requirements is notably lacking. This study addresses these gaps through the development of silk fibroin-based thermosensitive bioinks (SF-TPBs). Precise modulation of gelation time and mechanical robustness is achieved by manipulating glycerol content without recourse to cross-linkers. Chemical analysis confirms β-sheet conformation in SF-TPBs independent of glycerol concentration. Increased glycerol content improves gelation kinetics and results in rheological properties suitable for 3D printing. Overall, SF-TPBs offer promising prospects for realizing the potential of 3D bioprinting using natural polymers.