Now showing 1 - 10 of 17
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    Storage conditions, energy consumption, and food safety implications of domestic refrigerators in Bangkok
    (2025-12-01) ;
    Potisuwan, Cheeraphat
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    Duret, Steven
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    Derens-Bertheau, Evelyne
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    Paviet-Salomon, Yvanne
    Domestic refrigeration plays a critical role in food preservation and safety by maintaining optimal storage conditions for perishable items. This study investigated the temperature and humidity conditions, as well as the energy consumption, of domestic refrigerators in Bangkok. Data were collected through on-site investigations of 123 refrigerators using data loggers to record temperature, humidity, and electrical consumption over a five-day period. In addition, a predictive microbiological model was used to assess the potential for microbial growth under the investigated storage conditions, specifically of Listeria monocytogenes and lactic acid bacteria (LAB). Results indicated that although the overall mean temperatures of chilling compartments (5.0 ± 2.5 °C) were within the recommended range for domestic refrigeration, only about 30–40 % of individual refrigerators consistently maintained temperatures at or below 5 °C on the top and middle shelves throughout the five-day monitoring period, where fresh and ready-to-eat products are typically stored. Electrical consumption analysis revealed significant differences across refrigerator types; appliances with two doors and bottom freezers exhibited the highest annual electrical consumption, while single door refrigerators recorded the lowest. However, the specific energy consumption (SEC) did not differ significantly among refrigerator types. The microbial exposure assessment based on a test product highlighted that for over 50 % of refrigerators, L. monocytogenes load exceeds the regulation safety limits (> 10<sup>2</sup> CFU/g) within five days. These findings emphasize the need for improved temperature control, appliance design, and consumer education to ensure food safety and energy efficiency in domestic refrigeration.
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    Systematic improvement of source separation designs: the effects of visual prompts and trash bin combinations in enhancing waste separation behavior
    (2026-07-01)
    Soralump, Cheema
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    Phyo Ei, Nine Yawai
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    Nakaroengrit, Supawan
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    Asingsamanunt, Jarudej
    Source separation is essential for effective waste management, yet research on its efficiency remains limited. This study explores the effects of visual prompt design and bin combinations on waste separation behavior through a two-cycle experimental framework aimed at systematic improvement. In Cycle 1, a survey identified that environmental gain framing combined with numerical data was the most preferred design among all designed visual prompts. Implementation of this design significantly improved recyclable waste separation, with the effective capture rate (effCR) reaching 63.36%. In Cycle 2, while users preferred having more bin categories, the effCR for recyclables peaked at 79.76% in a 3-bin setup and declined to 40.74% in a 5-bin setup. This trend highlights how cognitive overload and choice paralysis negatively impact sorting accuracy as system complexity increases. Additionally, bin transparency proved critical, as the effCR for PET bottles dropped significantly from 85.65% to 35.05% when using untransparent bins. The findings indicate that while numerical environmental prompts drive initial engagement, bin transparency is essential for maintaining material-specific accuracy. However, the success of these interventions depends on keeping bin categories manageable to prevent cognitive overload. Ultimately, this integrated approach provides practical guidance for optimizing separation systems and advancing sustainable waste management practices.
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    The current state of the art in internal additive materials and quantum dots for improving efficiency and stability against humidity in perovskite solar cells
    (2022-12-01)
    Sanglee, Kanyanee
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    Part, Florian
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    Zafiu, Christian
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    Bello, Gianluca
    The remarkable optoelectronic capabilities of perovskite structures enable the achievement of astonishingly high-power conversion efficiencies on the laboratory scale. However, a critical bottleneck of perovskite solar cells is their sensitivity to the surrounding humid environment affecting drastically their long-term stability. Internal additive materials together with surface passivation, polymer-mixed perovskite, and quantum dots, have been investigated as possible strategies to enhance device stability even in unfavorable conditions. Quantum dots (QDs) in perovskite solar cells enable power conversion efficiencies to approach 20%, making such solar cells competitive to silicon-based ones. This mini-review summarized the role of such QDs in the perovskite layer, hole-transporting layer (HTL), and electron-transporting layer (ETL), demonstrating the continuous improvement of device efficiencies.
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    Machine learning of properties of lead-free perovskites with a neural network with additive kernel regression-based neuron activation functions
    (2024-07-01) ;
    Yoon, Heejoo
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    Hyojae, Lee
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    Kameda, Keisuke
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    Ihara, Manabu
    Machine learning (ML) of properties of perovskite materials, in particular of the bandgap of perovskites used in optoelectronic applications, has recently attracted increasing attention. Typically, off-the-shelf ML methods such as neural networks (NN), kernel methods or tree-based methods are used. We employ the recently proposed type of NN that uses additive Gaussian process regression to construct optimal neuron activation functions and avoids non-linear optimization to machine learn the band gap and heat of formation of lead-free inorganic halide double perovskites for solar cell applications. The method combines the high expressive power of an NN with the robustness of a linear regression. We show that better prediction quality can be obtained, in particular in the visible region relevant for most applications, compared to previous results using standard methods. Most important variables and the importance of coupling among features, in particular for bandgap prediction, can also be identified with the new method. Graphical abstract: (Figure presented.)
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    Remodelling hierarchical NiCo2O4@ZnS nanorods with multi-walled carbon nanotubes as a counter electrode for dye-sensitized solar cell applications
    (2026-12-01) ;
    Nachaithong, Theeranuch
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    Phumuen, Phatcharin
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    Wannabut, Wassana
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    Kunbuala, Neeraphat
    A hierarchical NiCo<inf>2</inf>O<inf>4</inf>@ZnS/MWCNT (NCO@Z-MWCNTs) nanocomposite was synthesized to serve as a platinum-free counter electrode for dye-sensitized solar cells (DSSCs). The nanocomposite comprised spinel NiCo<inf>2</inf>O<inf>4</inf> nanorods, ZnS associated with the surface of the nanorods, and an interconnected multi-walled carbon nanotube (MWCNT) network, and it was synthesized via a low-temperature solution-based hydrothermal method. XRD confirmed the presence of cubic NiCo<inf>2</inf>O<inf>4</inf> and zinc blende ZnS phases, while FESEM–EDS and XPS analyses verified the incorporation of ZnS and the formation of a conductive carbon framework interconnecting adjacent nanorods. ZnS, rather than acting as an isolated catalytic component, was considered to contribute additional sulfide-related surface sites and to modulate the interfacial electronic environment of the NiCo<inf>2</inf>O<inf>4</inf> nanorods, which likely facilitated redox reactions involving the I<sup>−</sup>/I<inf>3</inf><sup>−</sup> couple. Meanwhile, the MWCNT network established continuous electron transport pathways, effectively reducing interfacial resistance and enhancing charge-transfer efficiency. Thermogravimetric and electrochemical analyses revealed enhanced thermal stability, improved redox kinetics, and a significant reduction in charge-transfer resistance compared with pristine NiCo<inf>2</inf>O<inf>4</inf>.The optimized NCO@Z–MWCNT 9wt% counter electrode achieved a power conversion efficiency of 10.03% under AM 1.5 G illumination, exceeding that of the Pt reference device (9.6%). Overall, the improved performance was attributed to the combined contributions of ZnS surface modification and the conductive MWCNT network, which together enhanced charge transport and electrocatalytic activity. This work demonstrates a scalable strategy for developing cost-effective, durable, and high-performance counter electrodes for dye-sensitized solar cells.
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    The Perceptive Classification of the Wastes for Recycling and Composting for Sustainable Waste Management
    (2024-01-01)
    Leeabai, Nattapon
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    Areeprasert, Chinnathan
    The problem with municipal solid waste (MSW) in Thailand necessitates the well-planned MSW management is important. The perceptive classification of waste is the effective tool to design MSW management and waste separation campaign. It was found that the perceptive classification of the waste was significantly graded in order to the characteristics of the waste. The certain numbers of the wastes were high perceptive classification to the target category. Thus, the perceptual classification of these wastes did not prevent their separation into the designated waste bin. On the other hand, careful attention was required to increase the perception classification of aluminum foil as recyclable waste. The perceptive classification of recyclable waste on aluminum foil was too low, and it was around 37.66%. Misclassification may result from a misunderstanding of the waste type. In addition, some wastes were hardly segregated to a specific category, and there were depending on the implementation process in the MSW management system. For example, the perceptive classification of tissue paper as compostable wastes was low. To design the composting process including the input of tissue paper, the campaign to improve the perceptive classification on tissue papers was recommended. In contrast, the implementation of composting without the input of tissue paper did not need the campaign to modify the perceptive classification on tissue papers. Therefore, the significant findings of this study will be the designing tools to enable the effective and sustainability MSW management.
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    Synergistic Ni–Cu/char bimetallic catalysts for enhanced hydrogen production from corn stover bio-oil via steam reforming
    (2026-01-01)
    Wongcharee, Surachai
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    Suriyachai, Nopparat
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    Kreetachat, Torpong
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    Jadsadajerm, Supachai
    Catalytic steam reforming of biomass-derived bio-oil offers a promising route for renewable hydrogen production, yet catalyst deactivation and coke formation limit its practical application, particularly for complex whole bio-oils. Herein, hydrogen production from corn stover-derived whole bio-oil was investigated via an integrated fast pyrolysis-steam reforming process using char-supported Ni–Cu bimetallic catalysts. The optimized Ni–Cu composition exhibited enhanced hydrogen yield (∼53%) and feedstock conversion (∼78%), with low carbon deposition compared to monometallic counterparts. Elevated reforming temperatures promoted hydrocarbon cracking and suppressed coke formation. Long-term stability tests demonstrated sustained catalytic performance under steam oxygen reforming conditions. Structural characterization confirmed uniform metal dispersion and preserved catalyst porosity after reaction. The improved performance is attributed to the synergistic interaction between Ni, facilitating C–C bond cleavage, and Cu, enhancing water–gas shift activity and mitigating carbon deposition. These findings highlight the potential of char-supported Ni–Cu catalysts as a robust and coke-resistant system for scalable hydrogen production from real biomass-derived bio-oil.
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    On the Sufficiency of a Single Hidden Layer in Feed-Forward Neural Networks Used for Machine Learning of Materials Properties
    (2025-03-01)
    Thant, Ye Min
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    Manzhos, Sergei
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    Ihara, Manabu
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    Feed-forward neural networks (NNs) are widely used for the machine learning of properties of materials and molecules from descriptors of their composition and structure (materials informatics) as well as in other physics and chemistry applications. Often, multilayer (so-called “deep”) NNs are used. Considering that universal approximator properties hold for single-hidden-layer NNs, we compare here the performance of single-hidden-layer NNs (SLNN) with that of multilayer NNs (MLNN), including those previously reported in different applications. We consider three representative cases: the prediction of the band gaps of two-dimensional materials, prediction of the reorganization energies of oligomers, and prediction of the formation energies of polyaromatic hydrocarbons. In all cases, results as good as or better than those obtained with an MLNN could be obtained with an SLNN, and with a much smaller number of neurons. As SLNNs offer a number of advantages (including ease of construction and use, more favorable scaling of the number of nonlinear parameters, and ease of the modulation of properties of the NN model by the choice of the neuron activation function), we hope that this work will entice researchers to have a closer look at when an MLNN is genuinely needed and when an SLNN could be sufficient.
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    The Physical and Sound Absorption Property of Lightweight Rigid Polyurethane Composite Reinforced Bamboo Fiber for Roof Applications
    (2023-07-01)
    Roseli, Adyla Illyana
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    Hassan, Nik Normunira Mat
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    Leman, Abdul Mutalib
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    Latif, Najibah Abdul
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    Aminanda, Yulfian
    Rigid polyurethane (RPU) foams as roof insulation have become increasingly popular in Southeast Asian countries and have been extensively used for absorbing sound and reducing noise because of their good sound damping, viscoelasticity, and low density. In this study, the RPU foam composite reinforced bamboo fiber was investigated by physical characterization by SEM, TGA, and FTIR, and the sound absorption was measured by the Impedance Tube Test. The morphology result of the RPU foam composite indicates the size of the diameter pore influenced the sound absorption by adding bamboo fiber as a filler. The thermal degradation of the presence of lignin in the bamboo fiber at the temperature range of 400 °C to 500 °C and the total weight loss is 76 % at 429 °C temperature. FTIR spectrum shows that the peak at 2890 to 2935 cm-1 are indicated –CH stretching vibrations and characteristics for bamboo fiber can be used in polymer composites. The sound absorption of RPU 25 foam composite reinforced bamboo fiber was found 0.74 absorbance at a frequency of 1250 Hz. RPU foam reinforced bamboo fiber as a filler has the highest transmission loss RPU 35 is 21 dB at a frequency range of 1600 Hz. The findings indicate by increasing the content of bamboo fiber as filler, the diameter of the open pore of RPU 25 and RPU 35 foam composite had the potential for sound absorption to absorb at low frequency to achieve greater sound absorption for roof insulation.
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    Self-healing carbon fiber-reinforced polymers for aerospace applications
    (2022-08-29)
    Chuangchote, Surawut
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    Self-healing carbon fiber-reinforced polymers (CFRPs) have been explored in-depth since the 2000s. Microcapsules, vascular networks, dissolved thermoplastics, and reversible interactions can be used to give polymer matrix composites with self-healing properties. Recent improvements, particularly epoxy employed as a matrix phase in carbon fiber-reinforced polymers, are chosen and examined in terms of their repair mechanisms, validation testing methods, and any other attributes that might be relevant in aerospace applications. Extrinsic self-healing, which is pioneered in this field, paves the way for more modern approaches that take advantage of intrinsic self-molecular healing pathways. The latter appears to be the more promising self-healing carbon fiber-reinforced polymers in the long run. Self-healing carbon fiber-reinforced polymers are critical for increasing aircraft fatigue, impact, and corrosion resistance. Complex aviation composite geometries that are formerly made using time-consuming and expensive techniques (e.g. autoclave) can now be made utilizing simpler (and hence less expensive) processes, such as co-electrospinning, vacuum-assisted injection molding, or hand-lay up molding. Engines, fuselages, and aerostructures, as well as anticorrosion coatings, have profited from the usage of self-healing carbon fiber-reinforced polymers. Each area demands its own set of processes for improvement. Anyhow, carbon fiber-reinforced polymers face some problems of disposal and recycling.