Enhancing the energy storage capabilities of supercapacitors (SCs) while preserving their electrochemical performance is crucial for their widespread application. Our research focuses on developing Sb-modified tin oxide (ATO) nanoparticles via a scalable hydrothermal process, offering substantial potential in this domain. The tetragonal nanoparticle structure provides abundant active sites and a highly porous pathway, facilitating rapid and efficient energy storage. Additionally, tin's varied oxidation states significantly enhance redox capacitance. Electrochemical measurements demonstrate ATO's promise as an advanced SC electrode, achieving a peak specific capacitance of 332 F/g at 3 mA/cm2, with robust redox capacitance confirmed through kinetic analysis. Moreover, the ATO electrode exhibits exceptional capacitance retention over 2000 cycles. This study establishes ATO as a leading candidate for future energy storage applications, underscoring its pivotal role in advancing energy storage technologies.

필립 풀먼(Philip Pullman)의 􋺷황금 나침반􋺸은 판타지와 디스토피아를 결합하여 상상력을 전체주의에 맞서는 힘으로 탐구한다. 소설의 중심에는 전체주의적 교회를 무너뜨리려는 라이라(Lyra)의 여정이 있으며, 이는 저항을 상징한다. 영혼의 화 신인 다이몬(daemons), 사랑과 의식을 상징하는 먼지 입자(dust) 등과 같은 환상적 장치들은 작품을 풍부하게 만들며, 억압에 맞서는 인간 정신의 반항을 은유적으로 묘사 한다. 풀먼의 소설은 청소년 디스토피아 소설의 보다 광범위한 주제와 공명하며, 급속 한 기술 및 생명공학 발전에 대한 불안감을 포착한다. 이 비평의 핵심은 풀먼의 허구 적 세계가 현대의 문제들을 어떻게 반영하고, 젊은 주인공들의 정의와 공정함을 향한 여정을 통해 상징적으로 해결하고 있는지를 조명하는 데 있다.

Thermal decomposition of low-density polyethylene (LDPE) was monitored by thermogravimetry under N2 atmosphere in the presence of solid acid catalysts such as alumina (α-Al2O3, γ-Al2O3), crystalline silica-alumina (SA, molar ratio of Si/Al = 0.19) and amorphous silica-alumina catalysts (ASA, molar ratio of Si/Al = 4.9). Crystal structure and surface area of solid acid catalysts were measured by XRD and BET, respectively. The strength and distribution of acid sites of solid acid catalysts were estimated by NH3- TPD. It was observed that total acidity strength is in the order of ASA (1.77 μmmol NH3/ g) > AS (1.42 μmol NH3/ g) > γ-Al2O3 (1.06 μmol NH3/ g) > α-Al2O3 (0.06 μmol NH3/ g). Thermal degradation behavior of LDPE with and without solid acid catalyst was monitored by TGA, where heating rates (β) of 5, 10, and 20 °C/min were employed under an inert atmosphere, and their activation energies ( Ea), onset temperatures ( Tinitial), decomposition temperatures ( Tdecomp) were calculated and compared. The activation energy ( Ea) was evaluated using the Coats-Redfern method. Solid acid catalysts with stronger acidity and higher surface area showed a decrease in activation energy and onset temperature. Activation energy of LDPE over ASA catalyst is decreased to 97.3 kJ/mol from thermal decomposition of LDPE without catalyst of 117.2 kJ/mol under heating rate of 10 °C/min. The isothermal decomposition of LDPE was monitored at 300 °C for 3 h with a heating rate of 10 °C/min, where 13.1% and 24.2% wt. loss were observed over SA and ASA, respectively, while only 0.7% wt. loss was observed for LDPE without a solid acid catalyst.

Gold nanoparticles (Au NPs) decorated carbon nanofibers (CNFs) have been prepared by an electrospinning approach and then carbonized. The prepared Au-CNFs were employed to modifying a screen printed electrode (SPE) for simultaneous determination of ascorbic acid (AA), dopamine (DA) and uric acid (UA). Au NPs are uniformly dispersed on carbon nanofibers were confirmed by the structure and morphological studies. The modified electrodes were tested in cyclic voltammetry (CV), differential pulse voltammetry (DPV) and chronoamperometry (CA) to characterize their electrochemical responses. Compared to bare SPE, the Au-CNFs/SPE had a better sensing response to AA, DA, and UA. The electrochemical oxidation signal of AA, DA and UA are well separated into three distinct peaks with peak potential separation of 280 mV, 159 mV and 439 mV between AA-DA, DA-UA and AA-UA respectively in CV studies and the corresponding peak potential separation in DPV studies are 290 mV, 166 mV and 456 mV. The Au-CNFs/SPE has a wide linear response of AA, DA and UA in DPV analysis over the range of 5–40 μM ( R2 = 0.9984), 2–16 μM ( R2 = 0.9962) and 2–16 μM ( R2 = 0.9983) with corresponding detection limits of 0.9 μM, 0.4 μM and 0.3 μM at S/N = 3, respectively. The developed modified SPE based sensor exhibits excellent reproducibility, stability, and repeatability. The excellent sensing response of Au-CNFs could reveal to a promising approach in electrochemical sensor.

Aluminum-based composites are in high demand in industrial fields due to their light weight, high electrical conductivity, and corrosion resistance. Due to its unique advantages for composite fabrication, powder metallurgy is a crucial player in meeting this demand. However, the size and weight fraction of the reinforcement significantly influence the components' quality and performance. Understanding the correlation of these variables is crucial for building high-quality components. This study, therefore, investigated the correlations among various parameters—namely, milling time, reinforcement ratio, and size—that affect the composite’s physical and mechanical properties. An artificial neural network model was developed and showed the ability to correlate the processing parameters with the density, hardness, and tensile strength of Al2024-B4C composites. The predicted index of relative importance suggests that the milling time has the most substantial effect on fabricated components. This practical insight can be directly applied in the fabrication of high-quality Al2024-B4C composites.

We investigate the evolution of initial fractal clusters at 3 kpc from the Galactic Center (GC) of the MilkyWay and show how red supergiant clusters (RSGCs)-like objects, which are considered to be the result of active star formation in the Scutum complex, can form by 16 Myr. We find that initial tidal filling and tidal over-filling fractals are shredded by the tidal force, but some substructures can survive as individual subclusters, especially when the initial virial ratio is ≤0.5. These surviving subclusters are weakly mass segregated and show a top-heavy mass function. This implies the possibility that a single substructured star cluster can evolve into multiple ‘star clusters’.

Forecasting port container throughput is crucial due to its impact on economic development. Socio-economic factors, which introduce uncertainty, are increasingly integrated into throughput forecasting. The complexity of common multivariate forecasting models significantly affects accuracy, yet few studies compare their performance on the same time series for throughput modeling. This study implements, evaluates, and compares the performance of eight multivariate forecasting models for port throughput within a proposed multiple-input single-output (MISO) system, chosen for their frequent use in container throughput research. It investigates two data preprocessing approaches: Random Forest Variable Importance Method (RF-VIM) and a Multi Lagged Value approach. The comparison uses six error metrics: normalized root mean squared error, mean absolute error, mean absolute percentage error, mean error, and root mean percentage error. Performances are discussed, and recommendations for adopting a suitable model are provided.

Sensors for monitoring human body movements have gained much attention in the recent times especially in the health-care sector as these devices offer real-time monitoring of vital physiological signs, enabling health-care professionals to evaluate health conditions and provide remote feedback. In this work, we have fabricated carbon-nanotube (CNT)/ polydimethylsiloxane (PDMS) composite sensor through simple dispersion and freezing method for monitoring flexion movements in humans. Sensors with different CNT loadings, namely 0.1 wt %, 0.5 wt %, and 1 wt % were fabricated and analyzed to find the best performing sensor. Several characterizations like Raman, X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), thermogravimetric analysis (TGA), tensile strength measurements, and piezoresistive studies were carried out to study the features of the sensors. Among the fabricated sensors, the one with the loading concentration of 0.5 wt% is found to be most sensitive for flexion applications with higher gauge factor of 533 at 60% strain level, response time of ~ 140 ms and lower hysteresis loss. The feasibility of the sensor for monitoring flexion like finger bending, wrist bending, elbow bending, and knee bending is also analyzed making it ideal for use in sports for athletes, physicians, and trainers to investigate physical performance and well-being.