Kotiba Hamad
About
- Education
- (2012) PhD, Applied Chemistry, Department of Chemistry, Damascus University, Syria.
- (2008) Master, Applied Chemistry, Department of Chemistry, Damascus University, Syria.
- (2006) High Diploma, General Chemistry, Department of Chemistry, Damascus University, Syria.
- (2005) Bachelors, Pure Chemistry, Department of Chemistry, Damascus University, Syria.
- Experience
- (2013-2015) Postdoc researcher at School of Materials Science & Engineering, Yeungnam University (S. Korea).
- (2015-2023) Assistant professor, School of Advanced Materials Science & Engineering, Sungkyunkwan University (S. Korea).
- (2023-2025) Associate professor, School of Advanced Materials Science & Engineering, Sungkyunkwan University (S. Korea).
Research
Artificial Intelligence for Materials Science
I apply artificial intelligence and machine learning to accelerate the discovery and optimization of functional materials across diverse domains. Key directions include:
- Li-ion and Mg-ion batteries: design and screen solid-state electrolytes with enhanced stability and conductivity.
- Thermoelectric materials: predict transport properties and guide the search for high-efficiency compounds.
- Perovskite materials for solar cells: rapid exploration of crystal chemistry and performance optimization.
- High-performance aluminum alloys: using AI to design optimal composition and processing conditions for enhanced mechanical and functional properties.
- Additive manufacturing (AM): optimizing processing parameters and conditions for improved performance and reliability of AM-fabricated metals.
- Triboelectric materials: AI-guided design of high-performance materials for energy harvesting and sensing applications.
Metallurgy of Lightweight Materials
My work in metallurgy focuses on lightweight alloys, particularly magnesium and its derivatives, as well as advanced steels. I investigate the influence of alloying elements (Ca, Al, Zn, Ni), grain refinement, and twinning mechanisms on ductility, formability, and corrosion resistance. Through approaches such as differential speed rolling, annealing treatments, and microstructural engineering, I aim to achieve a balance between strength and ductility. This research also extends to the biodegradability of Mg alloys for biomedical applications and the development of sustainable, corrosion-resistant structural materials.
Publications
2025
- Panchanan, S.; Dutta, S.; Dastgeer, G.; Jaafreh, R.; Hamad, K.; Seok, S. I.
Mixed‐Dimensional Cu‐Based Perovskites for Stable and Energy‐Efficient Neuromorphic Memristors
Advanced Functional Materials, 2025, e20665, Wiley-VCH GmbH: Weinheim, Germany - Chaudry, Umer Masood; Rehan Tariq, Hafiz Muhammad; Hamad, Kotiba; Khan, Muhammad Kashif; Jun, Tea-Sung
Twinning-induced texture weakening in Mg alloy and its consequent influence on ductility and formability
Materials Science and Technology, 41(2), 101-105, 2025, "SAGE Publications Sage UK: London, England" -
Jaafreh, Russlan; Kumar, Surjeet; Hamad, Kotiba; Kim, Jung-Gu
Introducing Materials Fingerprint (MatPrint): A novel method in graphical material representation and features compression
Computational Materials Science, 246, 113444, 2025, Elsevier -
Alzamer, Haneen; Jaafreh, Russlan; Kim, Jung-Gu; Hamad, Kotiba
Artificial Intelligence and Li Ion Batteries: Basics and Breakthroughs in Electrolyte Materials Discovery
Crystals, 15(2), 114, 2025, MDPI -
Chaudry, Umer Masood; Farooq, Ameeq; Sufyan, Muhammad; Tariq, Hafiz Muhammad Rehan; Malik, Abdul; Kim, Minki; Tariq, Ali; Hamad, Kotiba; Jun, Tea-Sung
Corrosion behavior of AZ31 and AZ31-0.5 Ca in different concentrations of NaCl and Na2SO4 at various temperatures
Corrosion, 81(3), 232-244, 2025, Association for Materials Protection and Performance.
2024
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Mahendradhany, AP; Park, KS; Widiantara, IP; Kim, Min Jun; Oh, JM; Kang, JH; Hamad, K; Ko, YG
Achieving high strength and ductility of multi-phase steel via hub-border architecture formed in 30 s
Journal of Alloys and Compounds, 972, 172774, 2024, Elsevier -
Jaafreh, Russlan; Pereznieto, Santiago; Jeong, Seonghun; Widiantara, I Putu; Oh, Jeong Moo; Kang, Jee-Hyun; Mun, Junyoung; Ko, Young Gun; Kim, Jung-Gu; Hamad, Kotiba
Phonon DOS‐Based Machine Learning Model for Designing High‐Performance Solid Electrolytes in Li‐Ion Batteries
International Journal of Energy Research, 2024(1), 2138847, 2024, Hindawi -
Choi, Hyung Wook; Kim, Jiwon; Bang, Hyeon-Seok; Badawy, Khaled; Lee, Ui Young; Jeong, Dong In; Kim, Yeseul; Hamad, Kotiba; Kang, Bong Kyun; Weon, Byung Mook
Tracking accelerated oxygen evolution reaction enabled by explosive reconstruction of active species based on Co x N@ NC
Journal of Materials Chemistry A, 12(12), 7067-7079, 2024, Royal Society of Chemistry -
Jaafreh, Russlan; Kim, Jung-Gu; Hamad, Kotiba
Utilizing machine learning and phonon density of states for innovative approaches to design and optimize high-performance solid-state Mg-ion electrolytes
Journal of Power Sources, 606, 234575, 2024, Elsevier -
Kumar, Surjeet; Jaafreh, Russlan; Dutta, Subhajit; Yoo, Jung Hyeon; Pereznieto, Santiago; Hamad, Kotiba; Yoon, Dae Ho
Predictive modeling of critical temperatures in magnesium compounds using transfer learning
Journal of Magnesium and Alloys, 12(4), 1540-1553, 2024, Elsevier -
Subhajit Dutta, Swagata Panchanan, Surjeet Kumar, Russlan Jaafreh, Jung Hyeon Yoo, Seok Bin Kwon, Kotiba Hamad, Ghulam Dastgeer, Dae Ho Yoon
Pure Tunable Emissions from Cesium Manganese Bromide by Monitoring the Crystal Fields Through a Sustainable Approach
Advanced Sustainable Systems, 2024, Wiley -
Kumar, Surjeet; Jaafreh, Russlan; Singh, Nirpendra; Hamad, Kotiba; Yoon, Dae Ho
Introducing MagBERT: A language model for magnesium textual data mining and analysis
Journal of Magnesium and Alloys, 12(8), 3216-3228, 2024, Elsevier -
Gurjar, Kuldeep; Kumar, Surjeet; Bhavsar, Arnav; Hamad, Kotiba
An Explainable Deep Learning-Based Classification Method for Facial Image Quality Assessment
Journal of Information Processing Systems, 20(4), 2024