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Journal of Material Science and Radiation
Published by Balai Publikasi Indonesia
ISSN : -     EISSN : 31235379     DOI : https://doi.org/10.56566/jmsr
Core Subject : Science,
Materials Science & Nanotechnology Physics
Journal of Material Science and Radiation (JMSR) is an open-access, peer-reviewed scientific journal dedicated to the advancement of knowledge in the fields of materials science and radiation. The journal publishes original research articles, comprehensive scientific reviews, and concise scientific communications that are relevant and up to date. JMSR covers a wide range of topics related to material and radiation studies, and promotes interdisciplinary collaboration to support innovation and sustainable development in these fields. As an open-access journal, all articles published by JMSR are freely accessible to the academic community and the general public worldwide. This policy not only enhances the visibility and accessibility of research findings but also increases the scientific impact of each published work. Copyright of all articles is retained by the journal, while authors are granted a license to distribute their work for non-commercial purposes, provided that appropriate citation and attribution are given to the original publication in JMSR.
Arjuna Subject : Ilmu Material (semua kategori) - Ilmu Material (Lain-Lain)
Articles 6 Documents
 1 
Search results for , issue "Vol. 2 No. 1 (2026)" : 6 Documents clear
Superhydrophobic Surface from Sol Gel Synthesis of Thin Sol Gel Fluorinated Silica Coating Othman, Norfazlinayati; Harun, Mohd Hamzah; Zaharuddin, Izzuddin Mohamad; Ezani, Nor Adnin Ezani Mohd; Mohamed, Mahathir; Alias, Mohd Sofian
Journal of Material Science and Radiation Vol. 2 No. 1 (2026)
Publisher : Balai Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56566/jmsr.v2i1.495

Abstract

A thin fluorinated silica coating was synthesized via a sol–gel route using silica nanoparticles as surface roughness agents functionalized with long-chain fluoroalkylsilane. The coatings were characterized for surface wettability, optical transmittance, infrared spectra, and morphology. All samples exhibited excellent optical transparency as verified by UV–visible spectroscopy. The fluorinated silica coating demonstrated markedly enhanced water repellency compared to TEOS and TEOS–FAS systems, confirming the critical role of fluorinated silica in improving hydrophobicity. These findings indicate its strong potential for application as a transparent hydrophobic coating in optoelectronic devices, lenses, and window materials
The Production of Liquid Soap Using Locally Sourced Groundnut Oil and Optimization of its Physicochemical Properties Salisu, Umar Muhammad; Ahmad, Mubarak Ibrahim; Ibrahim, Yusuf; Ahmed, Fahad; Ibrahim, Haruna Sanusi
Journal of Material Science and Radiation Vol. 2 No. 1 (2026)
Publisher : Balai Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56566/jmsr.v2i1.501

Abstract

Creating liquid soap with locally sourced oils is not just a smart choice for your wallet, but it’s also a sustainable option compared to imported soaps. This study zeroed in on making liquid soap from groundnut oil and fine-tuning its physicochemical properties like pH, viscosity, foam ability, total solids, and stability. We prepared four different formulations by tweaking the amounts of potassium hydroxide (KOH), glycerol, and sodium chloride (NaCl). The soap samples were put through standard lab tests. The results showed that all formulations had pH levels within the acceptable range (9–10), and we noticed that viscosity, foam height, and total solids increased with higher concentrations of glycerol and NaCl. Stability tests conducted over four weeks revealed that Samples B, C, and D held up well with no phase separation, while Sample C (100 g oil, 11 g KOH, 4% glycerol, 1.5% NaCl) struck the perfect balance of physicochemical properties, aligning with international liquid soap standards. The study wrapped up by confirming that groundnut oil is a great choice for producing high-quality liquid soap, providing an affordable and locally available raw material for both small-scale and industrial production. We recommend diving deeper into optimization studies, conducting microbial analyses for shelf-life evaluations, and encouraging the use of groundnut oil-based liquid soap in local industries to boost sustainability and economic growth
Research Trends Material Physics E-Module Based on Synthesis and Characterization of Barium M-Hexaferrite using PjBL Model to Enhance Student Creativity (A Review) Susilawati, Susilawati; Kosim, Kosim; Hidayatullah, Nisa; Annam, Syarful
Journal of Material Science and Radiation Vol. 2 No. 1 (2026)
Publisher : Balai Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56566/jmsr.v2i1.665

Abstract

The rapid development of material physics research, particularly in the synthesis and characterization of barium M-hexaferrite (BaFe₁₂O₁₉), has not been optimally integrated into higher education physics learning. At the same time, Project-Based Learning (PjBL) and digital e-modules have been widely reported to enhance students’ creativity, yet their application remains largely limited to basic physics topics. This study aims to map and synthesize existing research related to PjBL-based e-modules, student creativity, and BaM hexaferrite material studies, in order to identify research trends, gaps, and opportunities for interdisciplinary integration. A Hybrid Review methodology was employed, combining a Systematic Literature Review (SLR) guided by PRISMA 2020 and a Bibliometric Review. Literature published between 2018 and 2026 was collected from Scopus and SINTA databases. A total of 38 eligible articles were included for qualitative synthesis and bibliometric mapping. The SLR examined research focus, methodologies, learning outcomes, and material synthesis approaches, while the bibliometric analysis explored publication trends, keyword co-occurrence, collaboration networks, and thematic structures. The results indicate that PjBL-based e-modules are consistently effective in fostering creativity and higher-order thinking skills. However, bibliometric evidence reveals a clear separation between physics education research and BaM hexaferrite material studies, with minimal thematic overlap. This finding highlights a significant research gap and underscores the novelty of integrating BaM hexaferrite synthesis and characterization into a PjBL-oriented e-module. The study provides a strong conceptual foundation for developing research-based digital learning materials that promote authentic scientific creativity in higher education physics.
Research Trends of Polymer Film for Radiation Radiotherapy: A Review Doyan, Aris; Susilawati, Susilawati; Annam, Syarful; Ikhsan, Muhammad; Ardianti, Nuraini Rachma
Journal of Material Science and Radiation Vol. 2 No. 1 (2026)
Publisher : Balai Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56566/jmsr.v2i1.690

Abstract

Polymer-based radiation dosimeters have attracted significant attention in recent years due to their capability to measure complex radiation dose distributions in radiotherapy applications. This study aims to analyze the research trends related to polymer film and polymer gel dosimetry used in radiotherapy through a systematic literature review and bibliometric analysis. The study employed the PRISMA methodology to systematically identify and select relevant publications from the Scopus and SINTA databases. A total of 30 articles published between 2018 and 2025 were included in the analysis. Bibliometric analysis was conducted using VOSviewer to examine publication trends, keyword co-occurrence networks, and research collaboration patterns. The results indicate a steady increase in research publications related to polymer dosimetry over the past decade. Keyword clustering analysis revealed several dominant research themes, including polymer gel dosimetry, radiation polymerization, dose distribution measurement, polymer film dosimeters, and nanoparticle-enhanced polymer materials. Among these topics, polymer gel dosimetry remains the most widely studied due to its capability to record three-dimensional radiation dose distributions. However, recent studies have increasingly explored polymer film dosimeters and nanocomposite materials to improve radiation sensitivity and dosimetric performance. Overall, the findings highlight the rapid development of polymer dosimetry technologies and their growing importance in modern radiotherapy quality assurance. Future research should focus on developing advanced polymer nanocomposites and integrating imaging-based dosimetry techniques to improve radiation dose measurement accuracy and clinical applicability.
A Modified Thermal Decomposition Approach for The Synthesis of Phase-Pure YBa₂Cu₃O₇−δ Superconductor Dzul-Kifli, Nur Athirah Che; Zakaria, Nurul Zafirah; Kechik, Mohd Mustafa Awang; Kien, Chen Soo; Pah, Lim Kean; Shaari, Abdul Halim; Shabdin, Muhammad Kashfi; Doyan, Aris; Hong, Yap Siew; Hapipi, Nur Hidayah Mohd
Journal of Material Science and Radiation Vol. 2 No. 1 (2026)
Publisher : Balai Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56566/jmsr.v2i1.694

Abstract

High temperature superconductor of YBa2Cu3O7-δ (Y-123) has been synthesised using the modified thermal decomposition method (MTD). In this work, a pure Y-123 sample is produced using an acetate-based material as a precursor and sintered at 980 oC. The study on the phase formation, superconducting properties and microstructural characteristics of pure Y-123 was investigated using X-ray diffraction (XRD), four-point probe (4PP) and scanning electron microscopy (SEM) respectively. XRD analysis confirmed the formation of a single-phase orthorhombic Y-123 crystal structure with an orthorhombicity of 0.008, indicating high phase purity without detectable impurity phases. Electrical measurements revealed a sharp superconducting transition with a critical onset temperature, Tc-onset of 97.3. SEM observations showed plate-like grains with an average grain size of 2.25 µm and good grain connectivity. These results demonstrate that the modified thermal decomposition technique is an effective approach for producing phase-pure YBCO superconductors with excellent structural and superconducting properties, highlighting its potential for advanced superconducting applications
Predictive Modeling of Geohazards Using Artificial Intelligence: Earthquakes, Landslides, and Volcanic Risk Assessment Faqiri, Ahmad Fawad; Faqiri, Nasrin; Hakimi, Musawer
Journal of Material Science and Radiation Vol. 2 No. 1 (2026)
Publisher : Balai Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56566/jmsr.v2i1.706

Abstract

Geohazards such as earthquakes, landslides, and volcanic eruptions pose severe threats to human life and infrastructure, causing significant global losses every year. Existing hazard assessment methods are limited by single-hazard focus, high computational cost, sparse data integration, and poor real-time forecasting capabilities, which limit their operational use. This study aims to develop a unified artificial intelligence (AI) framework for multi-hazard forecasting by integrating convolutional neural networks (CNNs), long short-term memory (LSTM) models, random forest classifiers, and ensemble fusion techniques. A multi-source dataset consisting of seismic, geospatial, and geochemical data was processed using an 80/10/10 split train-validate-test, cross-validation, and spatial validation strategies. The results show strong performance, with earthquake classification AUC-ROC of 0.961, magnitude prediction RMSE of 0.23 Mw, landslide sensitivity AUC of 0.957, and volcanic classification accuracy of 91.2%, outperforming several state-of-the-art benchmarks. Ensemble fusion improved performance by 2.1–3.7% over individual models. The key contribution is a scalable ensemble-based AI framework that enables integrated multi-hazard forecasting on heterogeneous datasets. However, limitations include information heterogeneity and reduced cross-regional generalizability. The framework supports real-time early warning systems, disaster risk management, and land-use planning, especially in hazardous areas.

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