Removal Efficiency of Bottom Ash and Sand Mixtures as Filter Layers for Fine Particulate Matter.

Permeable pavement is a technology that allows rainwater to infiltrate into the pavement. Permeable pavements not only help reduce surface runoff by allowing rainwater to infiltrate into the pavement, but also improve water quality with the filter layer that removes particulate matter pollutants. This study evaluated the particulate matter removal efficiency of bottom ash-sand mixtures as filter layers for removing fine (≤10 µm) or ultrafine (≤2.5 µm) particulate matter in the laboratory. Five filter media were tested: silica sand, bottom ash, and bottom ash-sand mixtures with 30:70, 50:50, and 70:30 ratios. The mixed filters exhibited more consistent and stable particulate matter removal efficiency over time than either the uniform sand or bottom ash filter. The 50:50 bottom ash-sand mixture demonstrated removal rates of 58.05% for 1.8 µm particles, 93.92% for 10 µm particles, and 92.45% for 60 µm particles. These findings highlight the potential of bottom ash-sand mixtures as effective filter media for removing PM10 road dust, although field validation with actual pavement systems is necessary.

A Low-Cost Lightweight Deflectometer with an Arduino-Based Signal Interpretation Kit to Evaluate Soil Modulus.

This research presents an innovative solution aimed at addressing the cost and accessibility challenges associated with soil stiffness analysis in construction projects. Traditional lightweight deflectometer (LWD) systems have limitations due to their high cost and proprietary nature, prompting the need for a more widely accessible technology. To fulfill this purpose, a low-cost, open-source LWD onboard sensor signal interpretation system, utilizing Electro-Mechanical and Micro-Electro-Mechanical-System (MEMS) technology-based sensors in conjunction with an Arduino® Uno and ADS1262 Breakout Board, has been developed. This system efficiently processes raw signal data into deflection and force units, enabling precise soil property analysis. Thorough enhancements, calibration, and alignment procedures have been applied and validated through field tests, which have produced highly satisfactory results. By significantly reducing costs while maintaining accuracy, this developed system has the potential to popularize quality control and assurance practices in the construction industry. This open-source approach not only enhances affordability but also broadens accessibility, making soil property analysis more efficient and attainable for a wider range of construction projects.

Prediction Models Based on Regression and Artificial Neural Network for Moduli of Layers Constituted by Open-Graded Aggregates.

The impermeable cover in urban area has been growing due to rapid urbanization, which prevents stormwater from being naturally infiltrated into the ground. There is a higher chance of flooding in urban area covered with conventional concretes and asphalts. The permeable pavement is one of Low-Impact Development (LID) technologies that can reduce surface runoff and water pollution by allowing stormwater into pavement systems. Unlike traditional pavements, permeable pavement bases employ open-graded aggregates (OGAs) with highly uniform particle sizes. There is very little information on the engineering properties of compacted OGAs. In this study, the moduli of open-graded aggregates under various compaction energies are investigated based on the Plate Load Test (PLT) and Light-Weight Deflectometer (LWD). Artificial Neural Network (ANN) and Linear Regression (LR) models are employed for estimation of the moduli of the aggregates based on the material type and level of compaction. Overall, the moduli from PLT and LWD steeply increase until the number of roller passes reaches 4, and they gradually increase until the number of roller passes becomes 8. A set of simple linear equations are proposed to evaluate the moduli of open-graded aggregates from PLT and LWD based on the material type and the number of roller passes.

Dependence potential of tramadol: behavioral pharmacology in rodents.

Tramadol is an opioid analgesic agent that has been the subject of a series of case reports suggesting potential for misuse or abuse. However, it is not a controlled substance and is not generally considered addictive in Korea. In this study, we examined the dependence potential and abuse liability of tramadol as well as its effect on the dopaminergic and serotonergic systems in rodents. In animal behavioral tests, tramadol did not show any positive effects on the experimental animals in climbing, jumping, and head twitch tests. However, in the conditioned place preference and self-administration tests, the experimental animals showed significant positive responses. Taken together, tramadol affected the neurological systems related to abuse liability and has the potential to lead psychological dependence.

Long-term operation of biomass-to-liquid systems coupled to gasification and Fischer-Tropsch processes for biofuel production.

Long-term operation of the biomass-to-liquid (BTL) process was conducted with a focus on the production of bio-syngas that satisfies the purity standards for the Fischer-Tropsch (FT) process. The integrated BTL system consisted of a bubbling fluidized bed (BFB) gasifier (20 kW(th)), gas cleaning unit, syngas compression unit, acid gas removing unit, and an FT reactor. Since the raw syngas from the gasifier contains different types of contaminants, such as particulates, condensable tars, and acid gases, which can cause various mechanical problems or deactivate the FT catalyst, the syngas was purified by passing through cyclones, a gravitational dust collector, a two-stage wet scrubber (packing-type), and a methanol absorption tower. The integrated system was operated for 500 h over several runs, and stable operating conditions for each component were achieved. The cleaned syngas contained no sulfur compounds (under 1 ppmV) and satisfied the requirements for the FT process.

Gas-phase synthesis and characterization of CH4-loaded hydroquinone clathrates.

A CH(4)-loaded hydroquinone (HQ) clathrate was synthesized via a gas-phase reaction using the alpha-form of crystalline HQ and CH(4) gas at 12 MPa and room temperature. Solid-state (13)C cross-polarization/magic angle spinning (CP/MAS) NMR and Raman spectroscopic measurements confirm the incorporation of CH(4) molecules into the cages of the HQ clathrate framework. The chemical analysis indicates that about 69% of the cages are filled by CH(4) molecules, that is, 0.69 CH(4) per three HQ molecules. Rietveld refinement using synchrotron X-ray powder diffraction (XRD) data shows that the CH(4)-loaded HQ clathrate adopts the beta-form of HQ clathrate in a hexagonal space group R3 with lattice parameters of a = 16.6191 A and c = 5.5038 A. Time-resolved synchrotron XRD and quadrupole mass spectroscopic measurements show that the CH(4)-loaded HQ clathrate is stable up to 368 K and gradually transforms to the alpha-form by releasing the confined CH(4) gases between 368-378 K. Using solid-state (13)C CP/MAS NMR, the reaction kinetics between the alpha-form HQ and CH(4) gas is qualitatively described in terms of the particle size of the crystalline HQ.

Hydrogen molecules trapped in interstitial host channels of alpha-hydroquinone.

Easy come, easy go: Hydroquinone forms a channel structure of cages with hydrogen-bonded hexagons. These may provide an ideal route for the fast inclusion and facile release of hydrogen molecules (see figure), which can lead to reversible hydrogen storage under mild conditions.