Fatriansyah, Jaka Fajar
Department Of Metallurgical And Materials Engineering, Faculty Of Engineering, Universitas Indonesia, Kampus Depok, West Java 16424, Indonesia

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Simulation of Melt Viscosity Effect on the Rate of Solidification in Polymer Jaka Fajar Fatriansyah; Hanindito Haidar Satrio; Muhammad Joshua Yuriansyah Barmaki; Arbi Irsyad Fikri; Mochamad Chalid
Indonesian Journal of Chemistry Vol 19, No 2 (2019)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (227.644 KB) | DOI: 10.22146/ijc.27195

Abstract

Phase field model has been successfully derived from ordinary metal phase field equation to simulate the behavior of semi-crystalline polymer solidification phenomenon. To obtain the polymer phase field model, a non-conserved phase field equation can be expanded to include the unique polymer parameters, which do not exist in metals, for example, polymer melt viscosity and diffusion coefficient. In order to expand this model, we include free energy density and non-local free energy density based on Harrowel-Oxtoby and Ginzburg-Landau theorem for polymers. The expansion principle for a higher order of binary phase field parameter was employed to obtain fully modified phase field equation. To optimize the final properties of the products, the solidification phenomenon in polymers is very important. Here, we use our modified equation to investigate the effect of melt viscosity on the rate of solidification by employing ordinary differential equation numerical methods. It was found that the rate of solidification is related to the melting temperature and the kinetic coefficient.
Synthesis and Characterization of Lignin-Based Polyurethane as a Potential Compatibilizer Salma Ilmiati; Jana Hafiza; Jaka Fajar Fatriansyah; Elvi Kustiyah; Mochamad Chalid
Indonesian Journal of Chemistry Vol 18, No 3 (2018)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (672.597 KB) | DOI: 10.22146/ijc.27176

Abstract

Lignin is one of the most abundant biopolymer on earth. It has polar and non-polar side due to its hyperbranched structure, but the polarity of lignin has a higher tendency than non-polarity. Lignin has potential to be compatibilizer if the portion of non-polar can be increased. This research is focused on investigate the synthesis of lignin-based polyurethane to enhance the portion of non-polarity in lignin. Lignin-based polyurethane was prepared by reacting variation 4,4'-Methylenebis(cyclohexyl isocyanate) (HMDI) and polyethylene glycol (PEG), then lignin was added to the reaction. In this study, the structure of lignin-based polyurethane was confirmed by NMR and FTIR. NMR and FTIR showed that lignin successfully grafted. NMR, also used to investigate the variation molar mass of PEG and isocyanate contents effects to polarity of lignin-based polyurethane. The polarity of lignin-based polyurethane decrease as the composition of HMDI and molecular weight of PEG increase. This result also occurs on the sessile drop test that used to determine surface tension of lignin-based polyurethane. The thermal properties of lignin-based polyurethane also investigate using STA. Based on STA, enhancement of composition of HMDI and PEG increase thermal degradation and resistance of lignin-based polyurethane.
Modeling of Hydrogen Adsorption Phenomenon in Amorphous Silica Using Molecular Dynamics Method Muhammad Hanif Abdurrahman; J. F. Fatriansyah; D. Dhaneswara; F. R. Kuskendrianto; M. B. Yusuf
Indonesian Journal of Energy Vol 3 No 1 (2020): Indonesian Journal of Energy
Publisher : Purnomo Yusgiantoro Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33116/ije.v3i1.44

Abstract

Hydrogen is one of the future source energy because it has environmentally friendly. However, there are still some problems in the storage method of hydrogen. In several studies, it was found that Silicon based material is a promising candidate as a hydrogen storage medium. In this study, the effect of various temperature and pressure to the adsorption of hydrogen on amorphous silica with molecular dynamics simulation using Lennard-Jones potential. In this simulation, the temperature that i used are 233, 253, 273 and 293 K with pressure at each temperature are 1, 2, 5, 10, and 15 atm. The simulations had successfully visualized and indicate that amorphous silica has a good hydrogen storage capability where temperature and pressure affect the amount of hydrogen adsorbed. At low temperature (233 K), the hydrogen concentrations are relatively high than at higher temperature. The best result of hydrogen capacity is 0.048116% that occurred at high pressure (15 atm) with low temperature (233 K) condition.*The paper has been selected from a collaboration with IPST and 7th ICFCHT 2019 for a conference entitled "Innovation in Polymer Science and Technology (IPST) 2019 in Conjunction with 7th International Conference on Fuel Cell and Hydrogen Technology (ICFCHT 2019) on October 16th - 19th at The Stones Hotel Legian, Bali, Indonesia"
Preface of Volume 1 Issue 1 on Journal of Materials Exploration and Findings (JMEF) Fatriansyah, Jaka Fajar
Journal of Materials Exploration and Findings (JMEF) Vol. 1, No. 1
Publisher : UI Scholars Hub

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The Optimization Of Failure Risk Estimation On The Uniform Corrosion Rate With A Non-Linear Function Hartoyo, Fernanda; Fatriansyah, Jaka Fajar; Mas'ud, Imam Abdillah; Digita, Farhan Rama; Ovelia, Hanna; Asral, Datu Rizal
Journal of Materials Exploration and Findings (JMEF) Vol. 1, No. 1
Publisher : UI Scholars Hub

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Failures in the oil and gas pipeline system are conditions that must be avoided and anticipated because the losses due to the failures can occur at a very high level. Internal corrosion is one of the significant causes of the failures in pipeline systems. In addition, this type of corrosion is due to the high content of carbon dioxide and other corrosive substances in crude oil and natural gas. Therefore, an optimal inspection scheduling system is required to prevent the possibility of pipeline failures due to corrosion and to avoid any overspending on the budget due to excessive inspection scheduling. Risk-based testing (RBI) is one of the best methods to define a test planning system by using an optimal risk assessment. In this article, a Monte Carlo random number generator is applied by using a huge number of random iterations to approximate the actual risk value of a pipeline system with a limited sample at the scene. The nonlinear corrosion rate function is used for comparison with the commonly used linear corrosion rate function based on ASTM G-16 95. Once a risk value is estimated, the value is monitored based on an assessment of the risk matrix for each corrosion rate function by using the RBI method. The results show that the nonlinear corrosion rate function provides a more accurate approach to estimating the actual risk value and ultimately leads to an optimal inspection planning system.
Investigating Features and Output Correlation Coefficient of Natural Fiber-Reinforced Poly(lactic acid) Biocomposites Federico, Andreas; Surip, Siti Norasmah; Wan Jaafar, Wan Nor Raihan; Fatriansyah, Jaka Fajar; Pradana, Agrin Febrian
Journal of Materials Exploration and Findings (JMEF) Vol. 1, No. 1
Publisher : UI Scholars Hub

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Abstract

Polylactic acid (PLA) material has the potential to be applied in various industrial fields, but this material has shortcomings in terms of mechanical properties, especially mechanical strength, due to brittleness nature of PLA. The manufacture of PLA composite material with the addition of natural fibers as a reinforcing phase is one of the methods to increase the impact strength and maintain the biodegradable properties of the material. However, in theory, there are many factors that affect the mechanical properties of composite materials, thus making the mechanical properties of composites more complex than monolithic materials. The mechanical properties of these composite materials can be predicted using deep learning by paying attention to the relationship between factors, and between factors and their mechanical properties. This relationship has an important role in creating a predictive model with good accuracy. Therefore, correlation analysis is an important thing to do. Correlation analysis was applied using Python programming language to determine the relationship between the impact strength of natural fiber-reinforced PLA biocomposites with its feature information: chemical composition, density, dimensions, surface chemical treatment of natural fibers, matrix-reinforcement volume fraction, and the type of processing used to manufacture the material.