Denture fabrication plays an important role in restoring oral functions, including mastication, speech, and esthetics, while also helping to prevent temporomandibular joint disorders. Conventional denture bases are commonly fabricated using heat-cured acrylic resin; however, this method still presents several limitations, including longer fabrication time, lower accuracy, and outcomes that are highly dependent on operator performance. The development of additive manufacturing technology offers several advantages, such as high reproducibility, improved accuracy in producing complex geometries, a more efficient digital workflow, and reduced material waste. This study investigated the effect of additive manufacturing using digital light processing (DLP) on the surface roughness and topography of denture bases fabricated with different printing layer thicknesses (50 μm and 100 μm), compared with conventional heat-cured acrylic resin bases. Disc-shaped samples with a diameter of 5 mm and a thickness of 2 mm were analyzed for surface roughness using a profilometer along a 2 mm straight line, while surface topography was observed using scanning electron microscopy (SEM). The results showed significant differences in surface roughness among the groups, where the additive manufacturing group with a 50 μm layer thickness exhibited the smoothest surface (0.96±0.26 μm), followed by the conventional heat-cured group (1.75±0.31 μm), while the additive manufacturing group with a 100 μm layer thickness showed the highest roughness value (4.27±0.55 μm). SEM analysis also revealed crater-like surface defects correlated with variations in layer thickness. These defects were observed more frequently in the additive manufacturing group with a 100 μm layer thickness compared with the 50 μm layer thickness group. These findings confirm the importance of additive manufacturing parameters in determining the final properties of denture bases and indicate the potential for optimizing fabrication techniques to achieve improved denture outcomes.
Cervical cancer continues to pose a significant health risk to women, especially when diagnosis occurs at a later stage. Early screening therefore plays an important role in reducing disease progression while increasing the possibility of successful treatment. In recent years, machine learning has been increasingly applied to support disease identification through data classification approaches. This study was conducted to compare the performance of classification models on a cervical cancer dataset by applying three resampling techniques, namely Random Over Sampling (ROS), Synthetic Minority Over-sampling Technique (SMOTE), and SMOTE-ENN, to handle data imbalance. The dataset was obtained from an opensource dataset and underwent several preprocessing stages, including the division of training and testing data, missing value examination, and imputation for incomplete records. Afterward, class distribution was analyzed to confirm the imbalance condition before the resampling process was applied. ROS was implemented by duplicating minority class instances, SMOTE generated synthetic samples through interpolation, while SMOTE-ENN combined oversampling with data cleaning. All experimental scenarios were then evaluated using Gaussian Naive Bayes and AdaBoost Classifier. The findings indicate that Gaussian Naive Bayes combined with ROS produced better recall performance than AdaBoost. This suggests that Gaussian Naive Bayes demonstrates higher sensitivity in identifying positive cases, particularly after minority class representation is improved. The results also emphasize that the evaluation of machine learning models, especially in medical applications, should not rely solely on accuracy but also consider precision and recall obtaining more reliable classification outcomes.
eLOK is an e-learning platform based on a Learning Management System (LMS) used at Universitas Gadjah Mada. Currently, eLOK does not yet provide a mobile version that supports flexible access to learning anytime and anywhere. This study aims to design the UI/UX of the eLOK mobile version using a user-centered design approach and to evaluate its usability through the System Usability Scale (SUS). The participants involved in this study were 9 active students of Universitas Gadjah Mada who regularly use the eLOK website. The study identified several interface improvements, including redesigning the login page with the addition of a fingerprint login feature, modifying the menu layout, adding visual icons to the course search menu, introducing icons for assignments, materials, and videos on the course page, adding features for downloading materials and videos, and implementing a previously unavailable chat feature in the eLOK website version. Usability testing using the System Usability Scale produced an average score of 94.4, which falls into the “Best Imagine” category, indicating that the application demonstrates an excellent level of usability and aligns well with user expectations. These findings suggest that eLOK Mobile has strong potential to support more interactive, simulation-based, and practice-oriented learning. Features such as fingerprint login and chat also support user engagement and independent learning. Future development is recommended to integrate multimedia content and real-time communication tools in order to improve effectiveness, accessibility, and user performance in practice-based learning.
Stunting is a condition of chronic malnutrition that can affect children's physical growth and cognitive development. Toroh is a district in Grobogan, Central Java, listed among areas with nutritional problems, including stunting. The purpose of this study was to determine the differences in tooth maturation between stunted and non-stunted children aged 6-9 years in Toroh District. An observational, cross-sectional study was conducted on 27 stunted and 27 normal children aged 6-9 years. The nutritional status was assessed based on height-for-age (H/A), using the WHO 2007 growth curve and the Maternal and Child Health (KIA) book. Stunting was assessed when the H/A of the child was less than -2 SD and the KIA book showed a history of the H/A being always under -2 SD; and normal when the H/A was between -2 SD and +2 SD, with a history (KIA book) of no experience of H/A under -2 SD. Permanent tooth maturation was assessed using the Demirjian method on panoramic radiographs. The result was analyzed using an independent t-test at a 95% confidence level. The results indicated that the mean dental maturation score of stunted children in all age groups was significantly lower (p < 0.05) than that of normal children. Girls exhibited a higher mean dental maturation score than boys in both stunted and normal groups. It may be concluded that stunted children had delayed dental maturation compared with normal children in Toroh District, Grobogan Regency, Central Java.
Permanent metal implants are widely used in dental, cranio-maxillofacial, and orthopedic rehabilitation due to their ability to restore structural integrity and tissue function through osseointegration, which refers to the direct bond between living bone and the implant surface. This review discusses the interaction between implant metal ions and body tissue structures, with emphasis on their effects on bone regeneration, antibacterial activity, and material biocompatibility. The study was conducted through a literature review of major scientific databases, including ScienceDirect, SpringerLink, MDPI, and PubMed. The findings show that implant success is strongly influenced by material biocompatibility, surface topography, and mechanical stability. Metals such as titanium, magnesium, zinc, calcium, silver, and strontium play important roles in supporting osseointegration and biological tissue responses. Magnesium contributes to bone formation by increasing osteoblast activity and inhibiting osteoclasts, while silver and zinc act as antibacterial and anti-inflammatory agents. Calcium and strontium contribute to enhanced osteogenesis and bone mineral density. These developments are expected to improve implant durability, biocompatibility, and patient safety, while opening opportunities for the development of a new generation of biomedical implants that are more intelligent and adaptive.
Metformin, a drug commonly used by patients with diabetes, is known to have major side effects in the form of gastrointestinal intolerance, including bloating, discomfort, diarrhea, and lactic acidosis. Long-term use of metformin (>2 years) may also increase the risk of developing diabetic neuropathy by up to four times. The presence of these side effects calls for natural alternatives with lower risk, one of which is red lotus stem extract (Nymphaea rubra). The compounds contained in red lotus stem extract, such as vitamin C, minerals, phenolic compounds, and flavonoids, are known to have antidiabetic potential. This study aimed to determine the effect of Ethanolic extract of red lotus stem (Nymphaea rubra) on the blood sugar levels of mice (Mus musculus). The research subjects consisted of 25 male white mice (Mus musculus) weighing approximately ±35 g and aged 16 weeks, divided into 5 treatment groups with 5 replications. The mice were induced with alloxan at a dose of 90 mg/kgBW through a single intraperitoneal (i.p.) injection, followed by oral administration of Ethanolic extract of red lotus stem at doses of 200 mg/kgBW and 400 mg/kgBW for 14 days. Blood sugar levels were measured before alloxan induction, after induction, and 14 days after treatment using a spectrophotometer with the GOD-PAP (Glucose Oxidase-Peroxidase Aminoantipyrine) method. The results showed that the average blood sugar levels in groups P1 (200 mg/dL) and P2 (400 mg/dL) were 171.00 mg/dL (hyperglycemia) and 105.00 mg/dL (normal), respectively. Based on the percentage reduction in blood sugar levels, group T1 showed a greater reduction of 37.64% compared with group T2 at 26.31%. In conclusion, the administration of Ethanolic extract of red lotus stem was shown to affect the reduction of blood sugar levels in mice.
Current developments require learning processes to become more dynamic and adaptive. Simulations based on realistic models are known to improve students’ manual skills as well as their confidence when dealing with real clinical cases. However, learning models that fully represent actual clinical conditions remain limited. The development of an intraoral abscess incision model using glove waste as a preclinical learning medium in dentistry offers an innovative approach, not only to reduce costs and medical waste, but also to support a more ecological and sustainable learning process. This study aimed to develop an abscess incision model based on glove waste as a preclinical learning medium in dentistry while supporting efficiency and medical waste reduction. The research method included the sterilization of glove waste, fabrication of a working model using dental stone, and preparation of an abscess substitute using glove waste filled with shampoo and covered with plasticine. Two types of models were developed, consisting of abscesses positioned in different locations and abscesses with variations in large and small sizes. The feasibility of the developed models was then evaluated through surveys that assessed functionality, reproducibility, and user perception, involving dental co-assistants and oral surgery residents who acted as supervisors during simulation sessions and questionnaires. The results indicated that the model was considered effective in improving understanding, knowledge, and skills, with excellent percentages of 70.81%, 62.50%, and 70.81%, respectively. The developed model was considered representative as an abscess incision model, although several improvements are still required. This study demonstrates that an abscess incision model made from glove waste is economical, environmentally friendly, effective, and representative as a learning aid for intraoral abscess incision procedures. The model also successfully improved practitioners’ understanding, knowledge, and skills, and was considered feasible as an alternative to commercially manufactured simulation tools.
Nglanggeran Village, located in Gunungkidul Regency, Yogyakarta, has substantial potential for the development of the local cocoa industry. Cocoa production in this village is integrated and managed by Griya Cokelat Nglanggeran, a community-based enterprise that focuses on processing cocoa beans into various derivative products. Despite its strong potential, the production process still faces several inefficiencies, particularly in the cocoa powder manufacturing stage. These inefficiencies hinder productivity and reduce overall process effectiveness. To address these challenges, this study applies the Lean Manufacturing approach, which emphasizes waste reduction and value enhancement throughout the production chain. Specifically, the research utilizes Value Stream Mapping (VSM) and Process Activity Mapping (PAM) to systematically visualize the production flow, identify non-value-added (NVA) activities, and analyze existing sources of waste. In addition, Fishbone Diagram, Failure Mode and Effect Analysis combined with Simple Additive Weighting (FMEA-SAW), and Fault Tree Analysis (FTA) are employed to trace the root causes of inefficiencies and propose prioritized improvement strategies based on risk levels. The findings indicate that, of the entire set of observed production activities, 196 were classified as waste, while only 24 contributed direct value. Among the seven types of waste, motion and transportation were identified as the most dominant, leading to the need for improvements in workspace layout and material handling management. After implementing corrective measures derived from the analytical results, the total duration of NVA activities decreased significantly from 3,059,830 seconds to 261,301 seconds, representing a 76.98% improvement in process efficiency relative to the total production time. These findings demonstrate that the application of Lean Manufacturing tools can significantly optimize cocoa powder production at Griya Cokelat Nglanggeran, while also providing a feasible model for other small-scale agro-industry enterprises seeking sustainable operational efficiency.
Cancer is a condition where the body's cells continue to divide without control. Often, this cancer is detected when it has entered an advanced stage, making it difficult to treat. Rice is a staple food widely used by more than half of Indonesia's population. The position of rice, which is a staple food, can be used as a prospective treatment to overcome the increasing number of cancer cases, especially in cases of colon cancer. Rice is reported to have many beneficial chemical contents. In cytotoxicity testing using WiDr colon cancer cells, the IC50 of the ethanolic extract of baroma rice is 316.01µg/ml. Stovetop cooked baroma rice showed an IC50 value of 672 µg/ml, while magic com cooked rice showed an IC50 value of 1232 µg/ml. Raw and stove-cooked baroma rice extracts are not strong enough to trigger apoptosis in cancer cells and can arrest the cell cycle at the G1 stage. This research shows that baroma rice extract has cytotoxic properties against WiDr colon cancer cells and various other evidence regarding the advantages of baroma rice. It is hoped that this rice can become a food that can prevent colon cancer.
Ultrafine bubbles (UFBs) play a crucial role as catalysts in water treatment, pharmaceuticals, biomedical engineering, and industrial processes, particularly those involving heat transfer mechanisms. Several researchers in Indonesia have explored ultrafine bubble fluids' potential as a heat transfer medium in passive cooling system models. In this context, changes in the density of ultrafine bubble fluids serve as the primary driver for flow. Since ultrafine bubbles increase in diameter when heated, examining an optimal production model is essential to ensure their availability in the flow. This study aims to optimize the production of ultrafine bubble fluids with the lowest possible density compared to the base fluid (reference). The research investigates the effect of production time and volume variations on ultrafine bubble density in a closed-loop system. Production times of 30, 60, 90, 120, 150, and 180 minutes are tested across tank volumes of 20, 40, 50, and 60 liters. The closed-loop production model utilizes hydrodynamic cavitation to maintain continuous fluid flow, with sample collection occurring at 15-minute intervals after the initial production time to allow for stable bubble size. Observations and statistical analysis using the Response Surface Method (RSM) reveal a nonlinear relationship between production time and ultrafine bubble fluid density. The optimal density is achieved with a production time of 60 minutes for a 40-liter volume. Additionally, this closed-loop model increases the temperature of the ultrafine bubble fluid to 54.3 °C in a 20-liter volume. Heat accumulation occurs due to the continuous pump-driven flow without additional cooling systems.
Accidents are a major cause of fractures in Indonesia. One of treatments for fractures is bone screws with support plates that are placed on broken bone. Currently, many biomaterials for bone screws are being developed which have biodegradable properties so that post-operative bone healing is not required. The purpose of this study was to determine the effect of cantula fiber addition on tensile strength, wear rate, and crystallinity of nano-HA/magnesium/Shellac biocomposite for bone screw materials. Nano-HA/magnesium/Shellac/cantula fiber materials were mixed using a blender. The material was mixed with a magnesium/hydroxyapatite ratio of 70/30 and cantula fiber is added with variations of 0%, 10%, 20% and 30% of total volume. After that, the material mixture was compacted with a pressure of 300 MPa for 10 minutes. Then the sintering process was carried out at a temperature of 140 ̊C for two hours. The results showed that the highest tensile strength value was 7.86 MPa at 30% variation. The lowest wear rate was 0.31 x 10-3 mm3/Nm at 30% variation. The highhest crystallinity in XRD observations was obtained at 30% variation, which was 79.65%.
The color of denture base material is important in dentistry to achieve a natural gingival aesthetic. No universal standard for denture base color, due to it difficult for dentists and dental laboratory technicians to achieve consistent results. This study proposes a method for identifying the color of artificial gums made from heated cure polymers with coloring agents. This study also examined the effect adding color agent on the hardness of denture base material and the effect of artificial saliva immersion on coloring. New coloring agents, namely pink (P), red (M), and purple (U), were added to create new colors in this study. Seven specimens from light to dark colors were made. The resulting specimens were photographed and analyzed using Adobe Photoshop software to obtain the L*, a*, and b* values for each specimen, which were then analyzed using the CIELAB formula. The results of the material hardness test showed a significant change between the immersion and non-immersion groups (p-value 0.00<0.05), while the group between 10-day and 20-day immersion showed no significant change (p-value 0.65>0.05). In materials without added color, the hardness value is 85.3 - 86.3 HSD, while in materials with added color, the hardness value increases to 85.5 - 87.7 HSD. The results of the saliva immersion test showed changes in the range of 2.51 - 5.98 for 10 days of immersion and 0.85 - 4.22 for 20 days of immersion. Based on these results, most of the color changes are still below the clinical acceptance threshold of less than 4.1. Therefore, it can be concluded that the color changes that occur after soaking are still clinically acceptable.
Biofilms serve to protect microbes from environmental conditions. Biofilms produced by lactic acid bacteria (LAB) can even inhibit the growth of pathogens. Medium de Man Ragosa Sharpe (MRS) is a specific medium for LAB growth and biofilm formation; however, it is not effective on an industrial scale due to its high cost. Tofu wastewater serves as an alternative medium because it contains complete nutrients that support the formation of LAB biofilms. This study aimed to determine the effect of C and N formulation in tofu wastewater on the production and characterisation of biofilms produced by four Lactobacillus (LAB) strains, including Enterococcus casseliflavus F4IS5, E. casseliflavus F14IS5, and E. casseliflavus F14IS6. Glucose and ammonium sulfate were added to the tofu wastewater as carbon and nitrogen sources, respectively. The biofilm-forming ability of LAB was tested by the biofilm assay method. The LAB biofilm characteristics were tested based on adhesion, while the exopolysaccharide concentration, a component of the biofilm, was analysed using the dry weight method. The inhibitory activity of LAB biofilms against the growth of pathogenic bacteria, specifically Escherichia coli and Staphylococcus aureus, was tested using the microplate method. The highest LAB biofilm production was obtained from the E. casseliflavus F6IS4 isolate in a tofu wastewater medium supplemented with 2% glucose and 1% ammonium sulfate, with an incubation time of 48 hours. The biofilm produced was categorised as a strong biofilm, which also exhibited strong adhesion; the separate cells accounted for only 19.25%. Besides, the EPS production by the strain was 63.4%. The biofilm of E. casseliflavus F6IS4 in tofu wastewater, supplemented with 2% glucose and 1% ammonium sulfate, also exhibited the highest inhibitory activity against E. coli and S. aureus, at 2.7% and 2.1%, respectively.
Red snapper (Lutjanus bitaeniatus) is a source of animal protein with a high-water content, making it prone to spoilage. Spoilage can be prevented through preservation. Garlic can be used as a natural preservative for fish because it contains antibacterial substances, including allicin, which plays a role in inhibiting and killing spoilage bacteria, as well as other antimicrobial compounds such as alkaloids, flavonoids, saponins, and tannins. This study aims to determine the effect of garlic extract as a natural preservative on the protein profile of red snapper. The research design was divided into five parts: fresh red snapper stored for 24 hours without soaking, and three parts soaked in garlic extract at concentrations of 5%, 10%, and 20%, respectively. This type of research was experimental. The research method was the preparation of garlic extract at concentrations of 5%, 10%, and 20%. Protein concentration was calculated using the Bradford method, followed by SDS-PAGE to separate proteins based on their molecular weight. The SDS-PAGE results were analyzed using the GelAnalyzer 19.1 application to calculate the molecular weight of the proteins and the protein profiles of the treatments compared to fresh fish. The results showed that the highest protein concentration was found in the 5% garlic extract treatment compared to the 10% and 15% concentrations. The protein profiles of fresh snapper and the 5% garlic extract treatment were not significantly different from fresh red snapper, with 13 protein bands (9 major bands and four minor bands). In contrast, fresh red snapper had 16 protein bands (13 major and three minor bands). This study concludes that garlic extract immersion treatment can be used as a natural preservative, with the optimal concentration being 5% garlic extract.
A Constructed Wetland (CW) is a modified wastewater treatment system that can be applied anywhere. The advantages of CW systems are low operational costs, naturally available constituent materials and provide aesthetic value as a wastewater treatment solution. The increasing number of laundry industries causes high concentrations of phosphate pollution in the environment. Shards of tile as an adsorbent may reduce the concentration of Total Suspended Solid (TSS), Total Dissolved Solid (TDS), Chemical Oxygen Demand (COD), phosphate, Methylene Blue Active Surfactant (MBAS), and sulphate. The effect of adding tile fragments is supported by using Water Jasmine plants (Echinodorus palaefolius) and the diversity of microorganisms attached to the adsorbent. The results of this study showed a phosphate reduction efficiency of 99.96%. The presence of the bacterial genus Proteus sp. and Citrobacter sp. on the tile fragments adsorbent impacts phosphate reduction. Pollutant removal in CW systems occurs due to adsorption, sedimentation, filtration, biodegradation and precipitation.
Surface water pollution caused by the discharge of domestic wastewater, including that from hospitals, is a serious issue that threatens public health and environmental quality. Hospital wastewater typically contains high concentrations of organic matter (COD, BOD), suspended solids (TSS), and pathogenic compounds that may exceed the quality standards set by the Ministry of Environment and Forestry, as outlined in Regulation No. 68 of 2016. This study aims to evaluate the performance of a combination of a Moving Bed Biofilm Reactor (MBBR) using Kaldness K1 media and a Lamella Clarifier in reducing COD, BOD, and TSS levels, as well as stabilizing the effluent pH of hospital wastewater at the laboratory scale. The research employed an experimental approach, utilizing a laboratory wastewater treatment plant design comprising MBBR and Lamella Clarifier units. Wastewater samples were collected by grab sampling from the hospital treatment plant inlet, then diluted to varying concentrations of 20%, 30%, and 50%, and subjected to a 24-hour retention time. The analyzed parameters included COD, BOD, TSS, and pH. The treatment results were statistically analyzed using a paired t-test to assess the significance of concentration reductions before and after treatment. The results indicated that the combination of these two units achieved average reductions of BOD by 56%, COD by 34%, and TSS by 53%, with effluent pH between 7.3 and 7.6, meeting quality standards. Statistical analysis revealed significant differences (p < 0.05) between inlet and outlet conditions, indicating the system's effectiveness. Therefore, the integration of MBBR and Lamella Clarifier is considered a viable solution for efficient, stable, and regulation-compliant hospital wastewater treatment.
Acne vulgaris (AV) is a common inflammatory-skin disorder associated with bacterial infections, particularly Cutibacterium acnes, Staphylococcus aureus, and Staphylococcus epidermidis. The rising resistance to conventional antibiotics has prompted the exploration of natural compounds such as boswellic acid, which is known for its antibacterial potential. This study aimed to evaluate the antibacterial activity of boswellic acid using an in-silico approach through molecular docking against several essential bacterial target proteins implicated in acne pathogenesis. The boswellic acid ligand was obtained from the PubChem database, while the three-dimensional structures of the target proteins were retrieved from the RCSB Protein Data Bank. Blind docking was performed using AutoDock Tools version 1.5.7 and AutoDock Vina, followed by interaction analysis using Discovery Studio Visualizer and Visual Molecular Dynamics (VMD). Nine bacterial proteins involved in vital cellular processes such as metabolism, protein synthesis, biofilm formation, and DNA replication were selected, including transcriptional regulator TcaR, penicillin-binding proteins (PBPs), tyrosyl-tRNA synthetase (TyrRS), 3-ketoacyl-ACP synthase III (KAS III), CRISPR-associated protein, DNA gyrase, transcriptional regulator MarR, methylmalonyl-CoA epimerase, and accumulation-associated protein (Aap). The docking results demonstrated that all target proteins exhibited negative binding energy values (< 0), indicating thermodynamically stable and spontaneous interactions. Among these, TcaR displayed the highest binding affinity with a binding energy of −10.2 kcal/mol and formed nine conventional hydrogen bonds, reflecting a particular and stable interaction. Key interacting residues included Gln: B61, HisA:42, AsnA:20, AsnB:17, and Arg1:110. In contrast, the Aap protein formed only one covalent bond, indicating the weakest interaction. These findings suggest that boswellic acid effectively inhibits key bacterial proteins, particularly those involved in transcriptional regulation and biofilm development. Therefore, boswellic acid holds significant potential as a safe and effective topical antibacterial agent for further growth in biomedical engineering-based formulations.
We are delighted to present the December edition of our journal (Volume 16, Number 1, December 2025), which showcases a rich collection of interdisciplinary research in biomedical engineering, environmental technology, renewable energy, materials science, and applied biological sciences. The studies featured in this issue reflect the dynamic landscape of technoscientific inquiry, highlighting both fundamental advancements and practical solutions to contemporary challenges.We open this edition with an in silico exploration of boswellic acid as a potential antibacterial agent against Cutibacterium acnes and other acne–associated pathogens. Through molecular docking targeting nine key bacterial proteins, the study demonstrates that boswellic acid exhibits strong binding affinity, particularly to the transcriptional regulator TcaR, suggesting its promise as a topical antibacterial candidate. This work underscores how computational biomedicine continues to accelerate the discovery of safer and more effective dermatological agents....To close this edition, we present a study on Constructed Wetlands (CW) using roof–tile fragments and Echinodorus palaefolius for treating phosphate–rich laundry wastewater. Remarkably, the system achieved a 99.96% reduction in phosphate levels, driven by adsorption, biodegradation, and microbial interactions—particularly from Proteus and Citrobacter species.Together, the articles in this issue reflect the dedication of researchers in advancing science and engineering for societal benefit. As we close this final issue of the year, we would also like to extend our warmest wishes to all our readers, authors, and reviewers. May this holiday season bring rest, reflection, and joyful moments with your loved ones. We look forward to welcoming you again in our June 2026 edition with new research contributions and advancements across the technoscience fields. Warm regards,Editor in ChiefJurnal Teknosains
The availability of fossil fuels is increasingly diminishing, while the global energy demand continues to rise. Alternative energy sources currently available from various vegetable oils include jatropha, palm, kapok seed, coconut, and cottonseed oil as substitutes for fossil fuels. When used directly in diesel engines, these oils can lead to several issues, including high viscosity and elevated flash points, which hinder proper fuel combustion and result in carbon deposits within the combustion chamber. Several solutions have been proposed to address these issues, including blending vegetable oils with diesel fuel at various ratios, preheating the vegetable oils, mixing them with additives, and utilizing exhaust gas recirculation and combustion chamber modification. This study investigates the role of bio-additive and applied magnetic fields in influencing flame characteristics and hydrocarbon gas emissions during palm oil droplet combustion. The experimental procedure involved direct testing on palm oil by incorporating a 3% eucalyptus oil-based bio additive and applying an attractive magnetic field (U-S), with droplet diameters ranging between 0.3-0.4 mm. Thermocouples diameter of 0.12 mm were placed on both sides of the magnet with a magnetic field intensity of 1.1 Tesla, and heating wires as the heat source were positioned beneath the thermocouples. The study found that combining eucalyptus oil bio-additive and an attractive magnetic field (U-S) resulted in the shortest flame evolution time of 1760 ms. The flame height and hydrocarbon gas concentration also reached their lowest values at 5.74 mm and 296 ppm, respectively. Meanwhile, the same treatment produced of highest temperature of 846.5 °C compared to other experimental conditions.
Perovskite solar cells (PSCs) have gained significant attention due to their remarkable power conversion efficiency (PCE) and potential for low-cost, scalable production. Despite this progress, further efficiency enhancement requires systematic optimization of device architecture, particularly the thickness of functional layers. This study presents a numerical simulation using the OGMANANO simulation platform to investigate the influence of layer thickness variation, specifically in the perovskite absorber layer, electron transport layer (ETL), and hole transport layer (HTL), on the performance of planar PSCs. The simulation models a typical n-i-p structured device under standard AM1.5G illumination, evaluating key photovoltaic parameters such as short-circuit current density (Jsc), open-circuit voltage (Voc), fill factor (FF), and overall PCE. Results indicate that the optimal absorber thickness lies in the 500–600 nm range, with a peak efficiency of 22.7% achieved at 550 nm. Furthermore, ETL and HTL show optimal performance at 50 and 60 nm, respectively, minimizing recombination losses and enhancing charge transport. The study concludes that precise layer thickness control is critical for maximizing PSC efficiency. The use of OGMANANO proved effective in simulating multilayer perovskite structures, providing a reliable tool for pre-fabrication optimization in advanced solar cell design.
