Browse Articles

Water hyacinth conversion to biochar for soil nutrient enhancement in improving agricultural product

Enhancing charge carrier dynamics with an N-type polymer guest for printable ternary organic solar modules

The ternary strategy offers a promising route to enhance the power conversion efficiencies (PCEs) of organic solar cells (OSCs). In this contribution, we focus on the state-of-the-art binary system PM6:L8-BO and reveal how the n-type polymer guest (PYIT) in the PM6:L8-BO:PYIT ternary system enhances carrier dynamics, thereby improving both efficiency and scalability for large-area printable OSC modules. These benefits are primarily attributed to two key factors: (i) the excellent miscibility of the PYIT guest with the host materials, coupled with the chain-dominant structure and high crystallinity nature of the PYIT polymer, which creates additional pathways for carrier transport and charge transfer; (ii) the incorporation of PYIT, which limits the excessive aggregation of L8-BO, improves molecular packing, and reduces film defects, thereby enhancing exciton dynamics. These optimizations lead to an increase in PCEs from 17.58% in the binary system to 18.59% in the ternary OSC, with improvements across all photovoltaic parameters. More importantly, the PM6:L8-BO:PYIT ternary system exhibits excellent compatibility with large-area printing processes, as demonstrated by a doctor blading OSC module achieving 15.57% PCE over an area of 11.7 cm2. This work highlights the potential of the ternary methodology in tuning the physical properties of OSCs while enhancing both performance and scalability.

CCN1 promotes APRIL/BAFF signaling in esophageal squamous cell carcinoma but attenuates it in esophageal adenocarcinoma

Special issue APL organic and hybrid photodetectors

Using a citizen science approach to assess nanoplastics pollution in remote high-altitude glaciers

Abstract Nanoplastics are suspected to pollute every environment on Earth, including very remote areas reached via atmospheric transport. We approached the challenge of measuring environmental nanoplastics by combining high-sensitivity TD-PTR-MS (thermal desorption-proton transfer reaction-mass spectrometry) with trained mountaineers sampling high-altitude glaciers (“citizen science”). Particles < 1 μm were analysed for common polymers (polyethylene, polyethylene terephthalate, polypropylene, polyvinyl chloride, polystyrene and tire wear particles), revealing nanoplastic concentrations ranging 2–80 ng mL − 1 at five of 14 sites. The dominant polymer types found in this study were tire wear, polystyrene and polyethylene particles (41%, 28% and 12%, respectively). Lagrangian dispersion modelling was used to reconstruct possible sources of micro- and nanoplastic emissions for those observations, which appear to lie largely to the west of the Alps. France, Spain and Switzerland have the highest contributions to the modelled emissions. The citizen science approach was found to be feasible providing strict quality control measures are in place, and is an effective way to be able to collect data from remote and inaccessible regions across the world.

Sliding ferroelectricity influenced by charge doping in bilayer antiferromagnetic H–ScO2

Sliding ferroelectricity has been extensively studied as it provides an approach to designing van der Waals ferroelectric materials with nonpolar components. In this work, we demonstrate the sliding ferroelectricity of bilayer H–ScO2, which is formed by an interlayer antiferromagnetic configuration of monolayer H–ScO2 ferromagnetic material. The out-of-plane polarization results from charge transfer between the layers, causing an unequal charge distribution within them and yielding a polarization value of ±1.26 pC/m. We found that increasing the doping concentration suppresses the polarization value. This phenomenon results from the differing occupancy ratios of electrons and holes in the conduction and valence bands after introducing electron or hole doping into the system. The closer the number of electrons in the conduction band is to that in the valence band, the more pronounced the suppression of polarization. Our work offers a perspective for the design of advanced van der Waals ferroelectric materials.

Psychometric study of the Maslach Burnout Inventory-Student Survey on Thai university students

Abstract The Maslach Burnout Inventory-Student Survey (MBI-SS) is a widely used instrument to assess burnout levels, which provides valuable insight into their psychological well-being. Accurate measurement of burnout is crucial for developing interventions aimed at reducing stress and promoting mental health among students. This study aims to validate the MBI-SS when applied among Thai university students and to examine whether the psychometric properties of the scale are consistent with the original conceptual framework. A total of 413 undergraduate students from Thailand participated in the study, with 57.63% females and 42.37% males, and a mean age 21.75 years (SD = 2.40). The MBI-SS was translated into Thai by following rigorous procedures to maintain accuracy and cultural relevance. The factorial structure of the MBI-SS Thai version was evaluated using confirmatory factor analysis (CFA) for both a three-factor model and second-order factor model. The Thai version of the MBI-SS demonstrated a three-dimensional structure consistent with the original inventory, with excellent model fit indices. All item factor loadings exceeded the recommended threshold, and the instrument showed high internal consistency, establishing it a valuable tool for future research and practical application in educational settings aimed at addressing and reducing student burnout.

Continuous and spontaneous directional droplet transport on bioinspired serial-wedge-shaped groove with wettability gradient

We propose a serial-wedge-shaped groove with a wettability gradient to achieve continuous directional transport of droplets. Molecular dynamics simulations demonstrate that this design provides a sustained driving force and reduces energy barriers at junctions, facilitating continuous droplet motion. Moreover, higher temperatures and greater wettability gradients are shown to enhance the efficiency of continuous transport. Theoretical analysis further reveals that increasing surface hydrophobicity, width ratio, and droplet size can reduce energy barriers, thereby improving transport performance. These findings are expected to improve the understanding of continuous directional droplet transport and shed light on its manipulation.

Numerical analysis of the hydraulic fracture propagation behavior encountering gravel in conglomerate reservoirs

A hydrothermal coupling model for permafrost subgrade considering temperature gradient and its application

Quantitative efficiency of optoacoustic ultrasonic treatment in SLM, DED, and LBW applications

Integrating machine learning and structure-based approaches for repurposing potent tyrosine protein kinase Src inhibitors to treat inflammatory disorders

The burden of prostate cancer in the North Africa and Middle East Region from 1990 to 2021

Willingness to pay a premium for eco-label products in China: a mediation model based on quality value

A kurtosis-ESPRIT algorithm for RealTime stability assessment in droop controlled microgrids

Abstract Although detailed analytical models for droop-controlled microgrids are available, they are computationally complex and do not consider real-time variations in microgrid parameters and operating conditions. This paper proposes Kurtosis-Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) to identify the dominant modes in droop-controlled inverter-based microgrids (IBMGs) using local real-time measurements. In the proposed approach, a short-duration small disturbance is applied to the selected DG’s active power droop gain, and then, the system’s dominant modes are estimated from its local measurements. Additionally, a kurtosis measure is proposed as a quick measure to assess the estimation signal’s characteristics and evaluate the presence and prominence of significant modes within the signal. The effectiveness of the developed approach is validated via MATLAB/SIMULINK simulations. Four case studies were conducted to verify the robustness of the proposed algorithm as follows: under different values of active power droop gains, several variations of lines’ X/R ratios, various levels of noise, and under large load changes and topological disturbances. Besides, a controller-in-the-loop (CIL) experiment was conducted using OPAL-RT to provide a real-time validation of the results. The modes obtained from the proposed algorithm are validated against the analytically derived modes and the estimation accuracy is compared to the recent methods: Prony, Matrix Pencil, and Subspace Identification techniques. Results show higher estimation accuracy for the proposed approach with a robust performance in noisy environments, across varying load conditions, and under different network configurations.

Prognostic assessment of early-stage liver cirrhosis induced by HCV using an integrated model of CX3CR1-associated immune infiltration genes

Physics-informed deep learning quantifies propagated uncertainty in seismic structure and hypocenter determination

Basic psychological needs satisfaction, coping functions, and emotional experiences in competitive athletes: a multi-states theory perspective

Language style (mis)matching: Consuming entertainment media from someone unlike you is linked to positive attitudes

Impact of driving characteristic parameters and vehicle type on fuel consumption and emissions performance over real driving cycles

With the growing need for sustainable transportation solutions, understanding the relationship between driving characteristic parameters, vehicle type, and their impact on emissions and fuel consumption over real driving scenarios is becoming increasingly important. In this paper, four conventional vehicles and one hybrid vehicle with different technologies were compared in four distinct routes in Tehran city. Nineteen real driving cycles were generated using widely employed K-means and PCA algorithms. The vehicles were simulated on MATLAB/Simulink according to their specifications. Twelve driving characteristic parameters, fuel consumption, CO, NOx, HC, and CO2 of vehicles with different powertrains, engines, and body styles were calculated over real and standard driving cycles. Notable findings show that driving characteristic parameters exhibit distinct influences on fuel consumption and emissions, depending on the specific driving conditions and vehicle type. Additionally, the hybrid vehicle achieved 39% and 26% fuel savings compared to gasoline and dual fuel vehicles, respectively. However, it emitted significantly higher levels of CO and HC. In contrast, the turbocharged vehicle increased CO and HC emissions compared to the naturally aspirated vehicle, but consumed less fuel (approximately 6%) and emitted lower amounts of CO2 (approximately 19%). In real driving cycles, the sedan vehicle generally exhibited slightly lower values compared to petrol SUV due to lower weight and drag coefficient.