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All Journal Journal of Materials Exploration and Findings International Journal of Innovation in Mechanical Engineering and Advanced Materials
Gerald Ensang Timuda
Institut Teknologi Bandung
Automotive Engineering Energy Engineering Materials Science & Nanotechnology Mechanical Engineering

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Characteristics of Sodium Lithium Titanate Synthesized at Different Solid-State Reaction Temperature for Lithium-Ion Battery Anode Yahya, Ilham Nur Dimas; Sofyan, Nofrijon; Khaerudini, Deni Shidqi; Timuda, Gerald Ensang; Priyono, Slamet
Journal of Materials Exploration and Findings Vol. 2, No. 3
Publisher : UI Scholars Hub

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Abstract

The effect of sintering temperature on the characteristics of sodium lithium titanate (NaLiTi3O7/NaLTO) synthesized at different solid-state reaction temperature and its performance as lithium-ion battery anode has been investigated. The precursors for the synthesis consisted of LiOH.H2O, TiO2, and NaHCO3. The synthesis was performed via solid-state reaction method. The precursors were mixed and sintered at variation temperatures of 900oC, 1000oC, and 1100oC for 2 hours under atmosphere condition. The final product was characterized using X-ray diffraction (XRD) and particle size analyzer (PSA). The XRD analysis showed the main phase of NaLTO with some impurities. PSA analysis showed that the sintering temperature has a significant effect on changes in particle size where the sample at a temperature of 1100oC has the largest particle size of 74.62 µm. The battery was fabricated by firstly mixing NaLTO powder with polyvinylidene fluoride (PVDF) and acetylene black (AB) in a ratio of 85:10:5 wt.% and the mix was then deposited onto copper foil to form NaLTO a sheet. The NaLTO sheet was cut into circular discs with a diameter of 14 mm and were arranged in a sequence of separator, metallic lithium, and electrolyte to form a coin cell in a glove box. Characterization using cyclic voltammetry (CV) and charge-discharge (CD) showed that the NaLTO sintered at 1000oC provided good electrochemical performance with the largest diffusion coefficient of 3.948 x 10-10 m2/s, Coulombic efficiency reached 100%, and a high specific capacity of 65.83 mAh/g.
Mechanical Properties Analysis of Stainless Steel 304 Linear Guide Rail Using Autodesk Inventor and MATLAB Azizi, Muhammad; Kurniawan, Kurniawan; Khaerudini, Deni Shidqi; Timuda, Gerald Ensang; Darsono, Nono; Chollacoop, Nuwong
International Journal of Innovation in Mechanical Engineering and Advanced Materials Vol 7, No 1 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijimeam.v7i1.25355

Abstract

This study investigates the mechanical properties of a stainless steel 304 linear guide rail using a combination of Autodesk Inventor and MATLAB. The primary objective is to analyze the von Mises stress distribution, displacement, and safety factor of the linear guide rail under varying load conditions, as well as to develop a model representing the relationship between stress and strain. A detailed 3D model of the guide rail was created using Autodesk Inventor, followed by finite element analysis (FEA) to evaluate stress and strain distribution across different sections of the rail. The simulation was conducted to assess the structural response under multiple loading scenarios, ensuring its reliability for real-world applications. Furthermore, a linear regression analysis was performed using MATLAB to establish a predictive model correlating stress and strain, enabling more accurate forecasting of the material's mechanical behavior. The results revealed that the maximum von Mises stress obtained from the simulation was 23.595 MPa, with a corresponding maximum displacement of 0.397 mm. The safety factor analysis confirmed the rail's structural integrity, with a minimum safety factor of 10.595, well above the failure threshold. These findings indicate that the linear guide rail meets the necessary mechanical performance requirements for its intended application.
Correlation Analysis of Battery Capacity, Range, and Charging Time in Electric Vehicles Using Pearson Correlation and MATLAB Regression Sanusi, Yasa; Pudjiwati, Sri; Tarigan, Kontan; Ginting, Dianta; Adnan, Farrah Anis Fazliatun; Timuda, Gerald Ensang; Darsono, Nono; Chollacoop, Nuwong; Khaerudini, Deni Shidqi
International Journal of Innovation in Mechanical Engineering and Advanced Materials Vol 7, No 3 (2025): Article in Press
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijimeam.v7i3.31800

Abstract

The increasing adoption of electric vehicles (EVs) reflects growing global awareness of climate change and air pollution challenges. As a sustainable alternative to conventional internal combustion vehicles, EVs produce zero tailpipe emissions and can significantly reduce carbon emissions—particularly when powered by renewable energy sources. However, one of the primary barriers to widespread EV adoption remains the high cost of battery components, which are essential to vehicle performance and energy storage. In Indonesia, two dominant battery types used in EVs are Lithium Ferro Phosphate (LFP) and Nickel Manganese Cobalt (NMC), each offering distinct advantages. LFP batteries are recognized for their thermal stability and longer life cycles, making them suitable for everyday use, while NMC batteries offer higher energy density and are preferred for performance-focused and long-distance applications. This study aims to evaluate the correlation between battery capacity, driving range, and charging time for LFP and NMC batteries using Pearson correlation and regression analysis through MATLAB simulation. The results indicate a strong and statistically significant correlation among the key parameters, with a Pearson coefficient of 0.576 for battery capacity and range, and an R-square value of 0.99 for the regression model, demonstrating high predictive accuracy. Furthermore, the analysis reveals that LFP batteries have a higher average energy efficiency of 7.53 km/kWh compared to 6.84 km/kWh for NMC batteries, indicating more consistent performance in energy usage. These findings offer valuable insights for optimizing battery selection in EV applications and contribute to strategic planning for the development of more efficient electric vehicle systems. The combination of statistical and simulation-based analysis provides a robust foundation for future research and policy-making in the field of electric mobility.
OPTIMIZATION OF MACHINING PARAMETERS ON THE SURFACE ROUGHNESS OF ALUMINUM IN CNC TURNING PROCESS USING TAGUCHI METHOD Putra, Yunata Mandala; Timuda, Gerald Ensang; Darsono, Nono; Chollacoop, Nuwong; Khaerudini, Deni Shidqi
International Journal of Innovation in Mechanical Engineering and Advanced Materials Vol 5, No 2 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijimeam.v5i2.21679

Abstract

In this research, Taguchi method is employed by focusing on spindle speed, feed rate, and depth of cut to optimize the CNC turning parameters for aluminum alloy 6063. The main goal of this study is to improve the surface roughness of the material. A L9 orthogonal array is used for experimentation, and the results are subsequently analyzed using ANOVA (Analysis of Variance). A spindle speed of 1300 rpm, a feed rate of 0.5 m/min, and a depth of cut of 1.5 mm are the optimal conditions to achieve the minimum average surface roughness (Ra). The main effect plot of the signal-to-noise (S/N) ratio provides significant evidence supporting the primary research goal. Furthermore, the ANOVA table reveals that spindle speed contributes 59.71%, feed rate contributes 29.80%, while depth of cut only contributes minimally at 0.72%. Based on the research findings, spindle speed and feed rate can be adjusted to control surface roughness. Both factors are highly significant in influencing the surface roughness of the material. The prediction equation from the linear regression analysis is Ra = 1.745 – 0.001024 spindle speed + 0.3000 feed rate – 0.0233 depth of cut. A coefficient of determination or R-squared value of 0.9115 indicates that the independent variables can explain 91.15% of the variation in the dependent variable. The experimental and predicted surface roughness (Ra) values have a predicted error percentage of 2.26%.
Study of Eigenvalues and Matrix Eigenvectors Using MATLAB: Vibration Systems of Multi-Purpose Vehicle (MPV) Octaviani, Ana Nur; Khaerudini, Deni Shidqi; Feriyanto, Dafit; Timuda, Gerald Ensang; Darsono, Nono; Chollacoop, Nuwong
International Journal of Innovation in Mechanical Engineering and Advanced Materials Vol 6, No 3 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/ijimeam.v6i3.25351

Abstract

Vehicle vibration is a critical factor influencing both passenger comfort and vehicle performance. In this study, we analyze the multi-degree-of-freedom (MDOF) vibrational behavior of a multi-purpose vehicle (MPV) using matrix eigenvalue and eigenvector methods. The vehicle’s dynamics are modeled by developing a set of equations of motion that account for the forces acting on the front and rear tires, car body, and pitch angle. MATLAB is utilized to numerically compute the system’s eigenvalues and eigenvectors, representing the natural frequencies and vibration modes of the vehicle, respectively. The analysis focuses on the vehicle’s response to a 50 mm displacement at the front tire, simulating the effect of road disturbances. The resulting vibrations in the front and rear tires, car body, and vehicle pitch are illustrated over a 1-second time frame. The findings show that the front tire experiences the largest oscillation amplitude of ±1 mm, while the rear tire exhibits a much smaller displacement of ±0.04 mm. The overall car body displacement reaches a maximum amplitude of ±1.3 mm, indicating partial damping of the front tire vibrations. However, the results reveal that the vehicle’s suspension system lacks effective damping, as the vibrations do not decrease over time. This behavior could negatively impact ride comfort and safety, particularly on uneven roads. The study concludes that improvements to the vehicle’s suspension system are necessary to enhance damping performance. The presented MATLAB-based approach offers a valuable tool for analyzing and optimizing vehicle vibration systems.
Co-Authors Adnan, Farrah Anis Fazliatun Azizi, Muhammad Chollacoop, Nuwong Dafit Feriyanto Deni Shidqi Khaerudini Ginting, Dianta Ilham Nur Dimas Yahya Kurniawan Kurniawan Nofrijon Sofyan, Nofrijon Nono Darsono, Nono Octaviani, Ana Nur Pudjiwati, Sri Putra, Yunata Mandala Sanusi, Yasa Slamet Priyono Tarigan, Kontan