Ryan Nur Iman

Solar cell technology has advanced rapidly in efficiency and material innovation. As a renewable energy source, solar cells help mitigate the global energy crisis. Perovskite-based solar cells have recently achieved efficiencies above 25%, surpassing conventional silicon cells. Among emerging materials, chalcogenide perovskites show great promise due to their superior stability compared to halide perovskites. However, they remain in the exploration stage, making accurate predictions of their electrical properties, especially bandgap, essential for assessing potential in solar cell applications. This study predicts bandgap values using computational methods, emphasizing efficiency and cost reduction compared to experimental approaches. Key features derived from collected data include oxidation state, electronegativity, coordination number, ionic radius, and density. Several machine learning (ML) algorithms: AdaBoost Regressor, gradient boosting regressor, support vector regressor, CatBoost Regressor, and k-neighbor regressor, were implemented using Python. The research process involved data collection, preprocessing (feature scaling, fusion, reduction, and selection), model training and testing with 5-fold cross-validation, and hyperparameter optimization to achieve optimal results. Among the tested models, CatBoost Regressor yielded the best performance, achieving a coefficient of determination (R2) of 69.34%, a mean absolute error (MAE) of 23.1%, and root-mean-square error (RMSE) of 29.49%, demonstrating its effectiveness in predicting chalcogenide perovskite bandgaps.

Coal remains a primary energy source, widely used for fuel and electricity generation, but it is also a major contributor to global carbon emissions, responsible for over 40% of the 15.3 billion tons of CO₂ emitted in 2021. In response, researchers are exploring strategies to reduce coal usage in briquette production. One promising alternative is biomass-based briquettes, designed to offer comparable performance to traditional charcoal while being more sustainable. This study investigates the thermal and mechanical properties of briquettes made from rice husk (RH) and coffee husk (CH), focusing on how particle size affects their heating value. RH and CH are rich in lignin, cellulose, and hemicellulose, crucial for briquette structure, while tapioca flour, used as a binder, provides amylose and amylopectin to enhance bonding. The carbonization process was conducted at 400°C for 60 minutes. Researchers used a 25% CH to 75% RH blend and evaluated three mesh sizes (60, 80, and 100). Briquettes were assessed based on calorific value, moisture content, shatter index, volatile matter, fixed carbon, density, ash content, and combustion rate. The results showed that the 100-mesh sample had the highest density, moisture content, volatile matter content, and burning rate with the value of 662.81 Kg/m3, 6.7%, and 7.07%, respectively. In contrast, the 60-mesh sample had the highest ash content (5.01%), as well as the lowest fixed carbon (82.04%) and shatter index (4.36%). These findings indicate that mesh size significantly affects the thermal and mechanical properties of the briquettes.

This work aimed to study the natural dye extracted from Indonesian wild plants (Rivina humilis L) using different solvents. The natural dye was extracted using the maceration method. Three different solvents, namely, aquades, acetone, and ethanol 96%, were used to extract natural dye from Rivina...

This work aimed to observe the influence of calorific value and proximate properties in the fabrication of rice husk (RS) and coffee shell (CH) briquettes composite. Rice and coffee husks contain cellulose, hemicellulose, and lignin. These contents are necessary for the adhesive to bind the...

This report aimed to know the performance of local mineral-based composite ceramic. The materials used consist of Indonesian local minerals, which are jarosite and manganite minerals as sources of oxide iron and Mangan. The materials were synthesized using the precipitation method, whereas composite ceramic was fabricated using a screen printing method and fired at 600 oC using a furnace. The results of the characterizations indicate that the sample forms three phases on diffraction peaks. The differences in the resistance values in ambient and ethanol environments indicate that the sample has very different responses. The high porosity of the sample greatly support the gas adsorption process. Thus, the sample has a high level of sensitivity. With the above characteristics, the composite ceramic which was fabricated has the potential to be applied to gas sensors, especially ethanol gas sensors.

We reported the methylene blue (MB) degradation by the photocatalysis method. This work aimed to know the effectiveness of degradation using a MgFe2O4:TiO2 composite. Synthesis of the composite used the sol-gel method. We synthesized three samples with ratios between MgFe2O4 and TiO2. Those were 100:0, 50:50, and 75:25, respectively. Sample (75:25) degraded MB of 47.23% with a reaction rate of 5.326 x 10-3 minute-1 under solar radiation. Whereas, without solar radiation, a sample showed a lower reaction rate. It happened because the sunlight produced photon energy to produce OH* radical so that it could activate the sample to absorb the dye. Reusable test resulted 19.73% degradation of MB for 100:0, 17.03% for 50:50, and 20.59% for 75:25 for 120 minutes. The XRD result for 75:25 has three phases, which are MgFe2O4 with cubic structure, TiO2 with tetragonal structure, and Fe2O3 with hexagonal structure. This work indicated that the sol-gel method could synthesize composite structures, and the sample may be used to remove methylene blue.

Preliminary studies about fabrication of Mn_(x)Zn_(2-x)FeO₄ (x = 0 dan 0.1) had been done to identify the effect of adding Mn₂O₃ 10%mol towards gas sensor sensitivity. Gas sensor ceramics that fabricated through local nature mineral-based is Yarosite mineral. The fabrication of Mn_(x)Zn_(2-x)FeO₄ thick film semiconductor by using Screen Printing method and firing at temperature 800 °C for 2 hours. Through electrical properties test it is known that the adding of Mn₂O₃ materials made semiconductor thick film faster to response ethanol gases rather than without Mn₂O₃ materials. Thick film Mn_0.1Zn_1.9FeO₄ has lower operating temperature and higher conductivity than Zn₂FeO₄ thick film. Electrical resistance test indicated that by adding Mn₂O₃ 10%mol, it is sufficiently effective to obtain new properties of Mn_0.1Zn_1.9FeO₄ thick film and it can be used as ethanol gas sensor.