Qiong Ye | Energy Storage | Best Researcher Award

Published on by Research Hypothesis

Dr. Qiong Ye | Energy Storage | Best Researcher Award  

Dr. Qiong Ye | Energy Storage | Postdoctoral Researcher at CY Cergy Paris University | France

Dr. Qiong Ye is an accomplished materials chemist recognized for her extensive research in inorganic chemistry, phase change materials, and energy storage technologies. Her scientific journey demonstrates a blend of theoretical insight and experimental precision in the development of advanced functional materials for sustainable energy applications. Dr. Ye earned her Ph.D. in Inorganic Chemistry from Le Mans Université, France, where she focused on the synthesis, crystallography, and thermodynamic behavior of complex oxide systems. She also completed her Master’s degree in the same institution, building a strong foundation in materials chemistry and thermodynamic studies. Currently, Dr. Qiong Ye serves as a Postdoctoral Researcher at CY Cergy Paris Université, France, where she investigates phase change materials and ionic conductors for thermal management and energy conversion systems. Her professional experience includes prior administrative leadership in Guangdong Meili Matériaux de Construction Ltd., China, where she coordinated R&D projects and material manufacturing processes before transitioning fully into academic research. Dr. Ye’s research interests encompass phase diagram analysis, solid-state chemistry, ionic conductivity, and numerical simulation of energy materials. She is particularly focused on the synthesis and structural characterization of oxide systems that enhance the performance and efficiency of energy storage and conversion devices. Her research skills include solid-state synthesis, X-ray and electron diffraction, impedance spectroscopy, thermal analysis, and computational modeling, complemented by proficiency in scientific software such as HighScore, FullProf, Jana, and Vesta. Dr. Ye’s interdisciplinary expertise bridges chemistry, physics, and materials engineering, contributing to several peer-reviewed publications in reputable journals such as Journal of Solid State Chemistry, Energy and Buildings, and The European Physical Journal Plus. Her works are indexed in Scopus and recognized for their contributions to advancing the understanding of material behavior under thermal and structural transitions. She has been involved in international collaborations promoting energy-efficient materials and sustainable technologies while demonstrating leadership in laboratory management and mentoring young researchers. Dr. Qiong Ye’s career reflects excellence, innovation, and dedication to advancing global energy materials research. Her achievements and continuous contributions to the scientific community make her a deserving candidate for academic recognition and future leadership in the field of materials chemistry.

Profile: ORCID

Featured Publications

Ye, Q. (2025). Experimental and numerical simulation study on the thermal performance of building envelope structures incorporating the solid–solid phase change material. Energy and Buildings. Citations: 12

Ye, Q. (2023). Phase diagram studies on ternary La₂O₃–MoO₃–CaO system. Journal of Solid State Chemistry. Citations: 8

Ye, Q. (2023). Phase diagram studies on ternary La₂O₃–WO₃–CaO system. Journal of Solid State Chemistry. Citations: 7

Ye, Q. (2022). You certainly know the second law of thermodynamics, do you know its connection to other laws of physics and chemistry? The European Physical Journal Plus. Citations: 15

Ye, Q. (2022). Partial re-investigation of the ternary diagram La₂O₃–Nb₂O₅–CaO, synthesis and characterization of the Ca₂La₃Nb₃O₁₄ and Ca₈La₈Nb₁₄.₄□₁.₆O₅₆ compounds. Journal of Solid State Chemistry. Citations: 10

Ye, Q. (2022). Cation-deficient Ca-doping lanthanum tungstate Ca₂.₀₆La₂.₆₁□₀.₃₃W₂O₁₂: Structure and transport property study. Journal of Solid State Chemistry. Citations: 9

Ye, Q. (2021). Investigation of phase change behavior in lanthanum-based oxide systems for energy storage applications. Materials Chemistry and Physics. Citations: 6

Assist. Prof. Dr. Ozgur Tonkal | Computer Science and Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr. Ozgur Tonkal | Computer Science and Artificial Intelligence | Best Researcher Award

Researcher | Samsun University | Turkey

Assist. Prof. Dr. Ozgur Tonkal is a distinguished academic and researcher currently serving as an Assistant Professor in the Department of Software Engineering at Samsun University, Türkiye. With an extensive background in Computer Engineering, Cybersecurity, and Software Defined Networks (SDN), he has established a strong academic and professional presence in the rapidly evolving field of information and communication technologies. Dr. Tonkal earned his Doctor of Philosophy (Ph.D.) degree in Computer Engineering from Gazi University, where he successfully completed his doctoral thesis titled “Autonomous Attack Detection and Mitigation Model by Network Traffic Aware Approach in Software Defined Networks,” which demonstrated innovative solutions for traffic-aware autonomous threat detection systems in SDN environments. He also holds a Master of Science in Computer Science from Gazi University and multiple Bachelor’s degrees from Gazi University, Karabuk University, and Anadolu University, combining expertise in computer systems education, computer engineering, and business administration. Throughout his career, Assist. Prof. Dr. Ozgur Tonkal has been recognized for his outstanding teaching, administrative leadership, and technical proficiency in cybersecurity, artificial intelligence, IoT, and computer network design. As a core faculty member, he teaches courses on Cybersecurity, IoT, Big Data, Artificial Intelligence, Computer Networks, and Web Programming while also serving as the Vice President of the Software Engineering Department, Technical Advisor to the Cybersecurity Student Community, and Manager of the University Cyber Incident Response Team. He has authored 3 documents, received 100 Citations, and holds an h-index of 2, reflecting his growing influence and scholarly impact in the field. His major research interests include Software Defined Networking (SDN), Machine Learning, Computer Networks, Cybersecurity, Big Data, and Network Security Automation. His technical expertise extends to programming in Python, MATLAB, and SQL, network system design and risk analysis, virtualization systems (Hyper-V, VMware), and machine learning applications for intrusion detection. He possesses multiple professional certifications from global institutions, including Cisco (CCNAv7, Network Security, IoT, and CyberOps Associate), Oracle (Database Design and SQL Programming), Exemplar Global (ISO/IEC 27001 ISMS Lead Auditor), and Google (Machine Learning Crash Course). His participation in the COST Action CA22168 project and contribution to international symposiums and conferences illustrate his active engagement with global research communities. In addition to his research and teaching responsibilities, he has taken on administrative roles as Acting Head of the IT Department at Samsun University and Technical Advisor for international robotics competitions, demonstrating his leadership and commitment to advancing education and innovation. Assist. Prof. Dr. Ozgur Tonkal’s scholarly works have been published in reputable journals indexed in Scopus and IEEE, with notable publications in International Journal of Imaging Systems and Technology, Electronics, and Gazi University Journal of Science Part C: Design and Technology, among others.

Profile:  Google scholar | Scopus | ORCID

Featured Publications

  1. Sertkaya, M. E., Ergen, B., Türkoğlu, M., & Tonkal, Ö. (2024). Accurate diagnosis of dementia and Alzheimer’s with deep network approach based on multi-channel feature extraction and selection. International Journal of Imaging Systems and Technology, 34. [Citations: 25]

  2. Tonkal, Ö., Polat, H., Başaran, E., Cömert, Z., & Kocaoğlu, R. (2021). Machine learning approach equipped with neighbourhood component analysis for DDoS attack detection in software-defined networking. Electronics, 10. [Citations: 40]

  3. Tonkal, Ö., Polat, H. (2021). Traffic classification and comparative analysis with machine learning algorithms in software defined networks. Gazi University Journal of Science Part C: Design and Technology, 9(1), 71–83. [Citations: 20]

  4. Tonkal, Ö. (2024). Cyber threat analytics in data science: Intrusion detection and prevention systems. In Current Studies in Data Science and Analytics. ISRES Publishing. [Citations: 10]

  5. Mercimek, T., & Tonkal, Ö. (2024). Social media criminals. In Proceedings of the 7th International Antalya Scientific Research and Innovative Studies Congress. [Citations: 5]