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All Journal Buletin Ilmiah Sarjana Teknik Elektro Journal of Mechanical Engineering, Science, and Innovation
Muhdi, Krisna Dwipa
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Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering Mechanical Engineering

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Quantum Mechanics Approach for Metal-Organic Frameworks Deformation Effect on Carbon Capture Performance: A Density Functional Theory Study Muhdi, Krisna Dwipa; Fikri, Ahmad Atif
Journal of Mechanical Engineering, Science, and Innovation Vol 5, No 1 (2025): (April)
Publisher : Mechanical Engineering Department - Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.jmesi.2025.v5i1.7415

Abstract

Increasing carbon dioxide (CO₂) emissions from fossil fuel combustion demand the development of effective and efficient carbon capture technologies. Metal-Organic Frameworks (MOFs) are excellent candidates as adsorbent materials because they have uniform pores, specific surface area, and can modified according to purpose. However, performance of MOFs may decrease due to structural deformation during  adsorption-desorption process, especially under extreme conditions. This study uses a quantum mechanical approach, namely Density Functional Theory (DFT), to analyze effect of deformation, specifically hMOF-13, on its performance in CO₂ adsorption. Through modeling the atomic structure of hMOF-13, an understanding of the quantum interactions between atoms, changes in position of atoms and cells due to deformation is obtained. Simulation results show that mechanical deformation of hMOF-13 decreases CO₂ adsorption performance through pore narrowing and electrostatic charge redistribution. In addition, excessive deformation can trigger structural failures that reduce regeneration cycles and lower carbon capture efficiency. Insights from this study can guide the subsequent development of MOFs with enhanced mechanical resistance, contributing to the optimization of industrial-scale carbon capture processes. By improving the structural stability of MOFs, industries can achieve higher adsorption efficiency, longer material life, and reduced operational costs, making carbon capture technology more feasible and sustainable.
Sensor Fusion of Laser and Inertial Units with Kalman-KMeans-Fuzzy Framework for Real-Time Railway Geometry Monitoring Fikri, Ahmad Atif; Subhan, Muhammad Ferindin Nuha; Suryanto, Heru; Muhdi, Krisna Dwipa; Pratama, Daniel Febrian; Iqbal, Ahmad
Buletin Ilmiah Sarjana Teknik Elektro Vol. 7 No. 3 (2025): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/biste.v7i3.13780

Abstract

Maintaining railway track geometry integrity is essential to ensuring transportation safety and predictive maintenance. Conventional manual inspection methods are limited by low sampling frequency, subjective interpretation, and delayed anomaly detection. This study introduces a real-time, embedded monitoring system using VL53L0X infrared laser sensors and an MPU6050 IMU to measure gauge, cross-level height, and inclination. Sensors are mounted on a lightweight aluminum trolley and sampled every 0.5 seconds using an Arduino-based platform. A Kalman Filter reduces measurement noise, with tuned covariance matrices based on field calibration. Filtered outputs are clustered via K-Means (K = 2), validated by the Elbow Method and Silhouette Score (>0.6). Maintenance categories are assigned through a fuzzy logic system, with a ±1 mm sensitivity analysis confirming >85% decision stability. Field results demonstrate a measurement noise, achieving RMSE and MAE values of 0.8165 mm and 0.3175 mm for gauge and height, and 0.3086° and 0.0952° for inclination, respectively and a SNR gain from 0.5 dB to 21.7 dB. The low-cost, modular setup supports scalable, condition-based maintenance and demonstrates robustness in noisy environments. This approach offers a practical foundation for future integration with predictive analytics and digital twin technologies in smart rail infrastructure.
Co-Authors Abda Abda Ahmad Atif Fikri Bello, Nasir Garba Heru Suryanto Irham Fadlika Pratama, Daniel Febrian Saeful, Albarrobi Nabila Subhan, Muhammad Ferindin Nuha