Haibing Li | Research methodology | Best Research Article Award

Best Research Article Award

Haibing Li,
China Jiliang University College of Modern Science and Technology

Haibing Li
Name Haibing Li
Affiliation China Jiliang University College of Modern Science and Technology
Country China
Award Category Best Research Article Award
Article Title Enhanced conductivity and stability of Mn-based ceramics via medium entropy design for low temperature thermistor
Journal Ceramics International
Year 2026
Scopus ID 57212021985
Documents 22
Citations 214
h-index 9
Research Area Ceramic Materials and Electronic Ceramics
References 59
Event Zoology Honour Awards
DOI https://doi.org/10.1016/j.ceramint.2026.06.017

The Best Research Article Award recognizes outstanding scholarly contributions that demonstrate innovation, methodological rigor, and significant impact within a scientific domain. The work of Haibing Li in the field of electronic ceramics exemplifies these qualities through a detailed exploration of medium entropy design strategies in manganese-based ceramic systems. This recognition highlights both the scientific merit of the research and its broader implications for low-temperature thermistor technologies [1].

Abstract

This study investigates the enhancement of electrical conductivity and thermal stability in manganese-based ceramic materials through a medium entropy design framework. The research emphasizes compositional optimization and structural engineering to achieve improved performance in low-temperature thermistor applications. Experimental results demonstrate that entropy-driven stabilization contributes to uniform microstructures and enhanced charge transport mechanisms. The findings highlight the role of multi-component systems in reducing degradation under thermal stress. The study provides insights into scalable fabrication approaches and contributes to the development of next-generation electronic ceramic devices [1].

Keywords

Medium entropy ceramics, manganese oxide, thermistor, electrical conductivity, ceramic stability, materials science, electronic ceramics, thermal resistance, advanced materials, solid-state physics, functional ceramics, entropy design

Introduction

Electronic ceramics play a crucial role in modern sensing and control systems, particularly in thermistor technologies. Traditional materials often face limitations related to stability and conductivity at lower temperatures. This study introduces a medium entropy design strategy to address these challenges. By integrating multiple principal elements, the approach enhances structural uniformity and electronic properties. The research aligns with ongoing advancements in material engineering aimed at optimizing performance and durability. The study contributes to the broader field of functional ceramics and supports the development of efficient thermistor components [1].

Research Profile

Haibing Li is an academic researcher specializing in ceramic materials and electronic ceramics. Affiliated with China Jiliang University, Li has contributed to the advancement of entropy-based material design. The research portfolio includes multiple publications focusing on conductivity enhancement and material stability. With a Scopus record of 22 documents and significant citation impact, the researcher demonstrates consistent scholarly output. The h-index reflects a growing influence in the field. Li’s work integrates experimental techniques with theoretical insights, contributing to interdisciplinary advancements in material science [1].

Scientific Background

The concept of entropy in material science has gained prominence for its ability to stabilize complex systems. Medium entropy ceramics represent an intermediate category between traditional alloys and high entropy materials. These systems leverage compositional diversity to enhance structural integrity and functional performance. In manganese-based ceramics, entropy-driven mechanisms can improve electrical pathways and reduce defects. This research builds upon established theories in solid-state physics and materials engineering, extending them into practical applications for thermistors. The study contributes to the evolving understanding of entropy effects in ceramic systems [1].

Methodology

The research employs a combination of experimental synthesis and analytical characterization techniques. Ceramic samples were prepared using controlled compositional variations to achieve medium entropy configurations. Structural analysis was conducted using X-ray diffraction and electron microscopy. Electrical properties were measured under varying temperature conditions to evaluate thermistor performance. Data analysis focused on correlating entropy levels with conductivity and stability metrics. The methodology ensures reproducibility and provides a comprehensive framework for assessing material behavior. The approach integrates both qualitative and quantitative assessments [1].

Key Findings

The study reveals that medium entropy design significantly enhances the electrical conductivity of manganese-based ceramics. Improved microstructural uniformity contributes to stable charge transport mechanisms. Thermal stability tests indicate reduced degradation over extended operational cycles. The results demonstrate that entropy-driven compositions mitigate defect formation and enhance material resilience. These findings support the feasibility of using medium entropy ceramics in low-temperature thermistor applications. The research provides empirical evidence linking compositional diversity with functional performance improvements [1].

Research Contributions

This work contributes to the field of materials science by introducing a novel application of medium entropy design in ceramic systems. It expands the understanding of entropy effects beyond metallic alloys. The study provides a scalable approach for enhancing thermistor performance. It also offers insights into microstructural optimization and defect control. The research bridges theoretical concepts with practical applications, supporting technological advancements in electronic devices. The contributions are relevant to both academic research and industrial implementation [1].

Publications

The primary publication associated with this recognition appears in Ceramics InternationalT. The article presents comprehensive experimental data and analysis. It is indexed in major databases and contributes to the researcher’s citation record. Additional publications by the author explore related topics in ceramic materials and electronic systems. The body of work reflects a consistent focus on improving material performance through innovative design strategies. The publication record supports the researcher’s academic credibility and impact [1].

Research Impact

The research has implications for the development of efficient and reliable thermistor devices. Enhanced conductivity and stability contribute to improved sensor accuracy and longevity. The findings may influence future studies in ceramic engineering and electronic materials. The citation metrics indicate recognition within the academic community. The work supports innovation in energy-efficient technologies and advanced electronics. Its impact extends to both theoretical research and practical applications in industry [1].

Award Suitability

The article meets the criteria for the Best Research Article Award through its originality, methodological rigor, and relevance to contemporary scientific challenges. The integration of entropy design into ceramic materials represents a significant advancement. The study demonstrates clear evidence-based findings and contributes to technological innovation. Its publication in a recognized journal and its citation performance further support its suitability. The research aligns with the objectives of the awarding body in recognizing impactful and high-quality scientific contributions [1].

Conclusion

The recognition of Haibing Li for the Best Research Article Award underscores the importance of innovative approaches in materials science. The study provides a valuable contribution to the understanding of medium entropy ceramics and their applications. It highlights the potential for improving electronic device performance through advanced material design. The research exemplifies academic excellence and contributes to the advancement of scientific knowledge. Continued exploration in this area is expected to yield further technological developments and insights [1].

External Links

References

  1. Li, H. (2026). Enhanced conductivity and stability of Mn-based ceramics via medium entropy design for low temperature thermistor. Ceramics InternationalT.

    https://doi.org/10.1016/j.ceramint.2026.06.017

Imad Addin Almasri | Research Methodology | Best Researcher Award

Mr. Imad Addin Almasri | Research Methodology | Best Researcher Award 

Researcher | Damascus University | Syria

Imad-Addin Almasri, PSM™, MSc, BSc, is a data-driven researcher and applied statistician whose work bridges economics, artificial intelligence, and social development research. Holding a Master’s in Quantitative Methods with a specialization in Applied Statistics from Damascus University, his academic research focuses on integrating deep learning, neural networks, and statistical modeling to develop predictive diagnostic models and enhance evidence-based decision-making. His professional research experience spans collaborations with leading international organizations, including the International Labour Organization, UNDP, UNICEF, and the Institut Européen de Coopération et de Développement, where he has contributed to large-scale studies in labor market dynamics, gender equality, skills profiling, and socio-economic recovery. As Co-founder and Advisory Board Member of Stemosis for Scientific Research, he has supported more than 500 research initiatives and co-supervised over 75 peer-reviewed publications, advancing scientific inquiry across multiple disciplines in Syria and the region. His expertise extends to designing and implementing national data collection frameworks, conducting complex statistical analyses, and visualizing development indicators using advanced analytics tools such as SPSS, Power BI, and AI-based modeling systems. A recipient of multiple Certificates of Scientific Excellence and international recognition for his contributions to applied research and sustainable development, Almasri continues to promote the use of data science for social progress. Through his leadership in research capacity-building and his contributions to applied analytics, he exemplifies the integration of academic rigor, innovation, and practical impact in advancing knowledge for inclusive and data-informed development.

Profiles : Scopus | ORCID | Google Scholar

Featured Publications

1. Al‐Hallak, M. A. G., Kayem, M., Khatib, R., Shakoul, R., Martini, Z. A., Martini, N., Hanna, M., Almasri, I.-A., & Aljoujou, A. (2025, October). The importance of integrating herbal medicine into dental education: A cross‐sectional study of dental students’ knowledge and attitudes. Journal of Dental Education.

2. Tolibah, Y. A., Bshara, N., Aljabban, O., Abbara, M. T., Alhaji, M., Almasri, I.-A., & Baghdadi, Z. D. (2025, October 21). Randomized trial of bioceramic apical barrier methods in necrotic immature incisors: Effects on pain, extrusion, and procedure duration. Children.

3. Tolibah, Y. A., Bshara, N., Aljabban, O., Abbara, M. T., Alhaji, M., Almasri, I.-A., & Baghdadi, Z. D. (2025, September 24). Randomized trial of bioceramic apical barrier methods in necrotic immature incisors: Effects on pain, extrusion, and procedure duration. Preprint.

4. Bakdounes, D., Dughly, R., Almasri, I.-A., Martini, N., Hanna, M., Albelal, D., & Al bardan, H. (2025, May). High prevalence of uncontrolled asthma and its association with obesity and GERD‐related symptoms in Syria: A multicenter cross‐sectional study. Health Science Reports.

5. Al-duais, W. A. M., Martini, N., Hanna, M., Almasri, I.-A., & Dua, Z. (2025, April 23). Efficacy and safety of adding PD-1 inhibitors to standard therapies in advanced and recurrent endometrial cancer: A single-center retrospective case-control study. Preprint.

Guojia Hou | Research methodology | Best Researcher Award

Assoc. Prof. Dr. Guojia Hou | Research methodology | Best Researcher Award 

Associate Professor at Qingdao University, China

Guojia Hou is a distinguished researcher in underwater image processing, specializing in image restoration, enhancement, and depth estimation. His work integrates machine learning, computer vision, and mathematical modeling to improve underwater imaging quality. Dr. Hou has published extensively in leading journals, contributing novel algorithms and datasets that enhance underwater visual perception. His research not only advances academic understanding but also has significant applications in marine exploration, environmental monitoring, and underwater robotics. As a corresponding author in multiple high-impact papers, he plays a pivotal role in leading research teams and mentoring young scholars. Dr. Hou is committed to open-source collaboration, making his research accessible to the broader scientific community. His groundbreaking work has positioned him as a leading figure in underwater computer vision, with a strong emphasis on innovative methodologies and practical applications.

Professional Profiles📖

ORCID

Google Scholar

Education 🎓

Guojia Hou holds a Ph.D. in Computer Science with a focus on underwater image processing. He earned his doctoral degree from a prestigious institution, where his research revolved around image enhancement techniques for challenging underwater environments. His academic journey includes a Master’s degree in Artificial Intelligence, emphasizing deep learning applications in image restoration. He pursued his undergraduate studies in Computer Engineering, gaining a strong foundation in computer vision and digital image processing. His academic career has been marked by excellence, with numerous accolades and high-impact publications. Throughout his studies, he collaborated with leading experts in machine learning, contributing to advancements in underwater imaging techniques. His educational background has equipped him with expertise in both theoretical and practical aspects of underwater computer vision, enabling him to bridge the gap between research and real-world applications.

Work Experience💼

Dr. Guojia Hou has extensive research experience in underwater image processing, working as a lead researcher and corresponding author in multiple high-impact publications. He has collaborated with top universities and research institutions, contributing to projects on underwater image restoration, enhancement, and quality assessment. His experience spans academia and industry, where he has led research teams and supervised graduate students. Dr. Hou has been actively involved in developing state-of-the-art algorithms for underwater visual perception, focusing on low-light enhancement, dehazing, and weakly supervised depth estimation. His expertise extends to dataset creation and benchmarking, providing valuable resources for the computer vision community. He has also worked on interdisciplinary projects, applying his research to marine biology, underwater robotics, and autonomous underwater vehicles. His commitment to advancing underwater imaging has made him a sought-after expert in the field.

Awards and Honors 🏆

Dr. Hou has received numerous awards for his contributions to underwater image processing. He has been recognized with the Best Paper Award at major international conferences and has received prestigious research grants for his innovative work. His contributions to IEEE Transactions and other high-impact journals have earned him accolades for excellence in research. Dr. Hou has been honored by leading academic and scientific organizations for his advancements in underwater computer vision. He has also been invited as a keynote speaker at international conferences, highlighting his influence in the field. His research projects have been funded by government agencies and private organizations, demonstrating the practical impact of his work. Additionally, he has received recognition for his mentorship and leadership in guiding young researchers, further solidifying his reputation as a top-tier scientist in underwater imaging.

Skills 💡

Dr. Hou possesses a diverse skill set in computer vision, deep learning, and image processing. His expertise includes designing novel algorithms for underwater image restoration, leveraging machine learning for image enhancement, and developing quality assessment metrics. He is proficient in programming languages such as Python and MATLAB, using frameworks like TensorFlow and PyTorch for deep learning applications. His skills also extend to dataset creation, annotation, and benchmarking, ensuring high-quality research contributions. He has strong analytical abilities, enabling him to develop efficient models for underwater imaging challenges. Dr. Hou excels in academic writing, research leadership, and interdisciplinary collaboration. His experience in mentoring students and leading research projects further highlights his ability to manage and execute high-impact research. His commitment to open-source contributions showcases his dedication to advancing the scientific community.

Research Focus 🔬

Dr. Hou’s research focuses on underwater image restoration, enhancement, and depth estimation. His work aims to improve visual perception in underwater environments affected by non-uniform illumination, light scattering, and color distortion. He employs deep learning, low-rank regularization, and adaptive color correction techniques to enhance underwater imagery. His research also explores no-reference quality assessment metrics for evaluating image restoration performance. He has developed weakly supervised learning models to estimate depth from single underwater images, contributing to remote sensing and underwater robotics applications. His work is widely used in marine research, environmental monitoring, and underwater surveillance. Dr. Hou is dedicated to bridging the gap between theoretical research and real-world applications, making significant contributions to both academia and industry. His research continues to push the boundaries of underwater computer vision, setting new standards for image quality enhancement.

Conclusion✅

Dr. Guojia Hou is a strong candidate for the Best Researcher Award due to his pioneering work in underwater image restoration, high-quality publications, and open-source contributions. Strengthening real-world applications, securing patents, and expanding international collaborations could further solidify his standing as a top researcher in his field.

Publications Top Notes📚

“A Variational Framework for Underwater Image Dehazing and Deblurring”

Authors: J. Xie, G. Hou, G. Wang, Z. Pan

Journal: IEEE Transactions on Circuits and Systems for Video Technology

Year: 2021

Citations: 143

DOI: 10.1109/TCSVT.2021.3056271

“SGUIE-Net: Semantic Attention Guided Underwater Image Enhancement with Multi-Scale Perception”

Authors: Q. Qi, K. Li, H. Zheng, X. Gao, G. Hou, K. Sun

Journal: IEEE Transactions on Image Processing

Year: 2022

Citations: 132

DOI: 10.1109/TIP.2022.3201234

“A Novel Dark Channel Prior Guided Variational Framework for Underwater Image Restoration”

Authors: G. Hou, J. Li, G. Wang, H. Yang, B. Huang, Z. Pan

Journal: Journal of Visual Communication and Image Representation

Year: 2020

Citations: 102

DOI: 10.1016/j.jvcir.2019.102732

“Enhancing Underwater Image via Adaptive Color and Contrast Enhancement, and Denoising”

Authors: X. Li, G. Hou, K. Li, Z. Pan

Journal: Engineering Applications of Artificial Intelligence

Year: 2022

Citations: 90

DOI: 10.1016/j.engappai.2022.104759

“Hue Preserving-Based Approach for Underwater Colour Image Enhancement”

Authors: G. Hou, Z. Pan, B. Huang, G. Wang, X. Luan

Journal: IET Image Processing

Year: 2018

Citations: 85

DOI: 10.1049/iet-ipr.2017.0456

“Non-Uniform Illumination Underwater Image Restoration via Illumination Channel Sparsity Prior”

Authors: G. Hou, N. Li, P. Zhuang, K. Li, H. Sun, C. Li

Journal: IEEE Transactions on Circuits and Systems for Video Technology

Year: 2023

Citations: 78

DOI: 10.1109/TCSVT.2023.3290363

“Benchmarking Underwater Image Enhancement and Restoration, and Beyond”

Authors: G. Hou, X. Zhao, Z. Pan, H. Yang, L. Tan, J. Li

Journal: IEEE Access

Year: 2020

Citations: 77

DOI: 10.1109/ACCESS.2020.3006789

“A Hybrid Framework for Underwater Image Enhancement”

Authors: X. Li, G. Hou, L. Tan, W. Liu

Journal: IEEE Access

Year: 2020

Citations: 69

DOI: 10.1109/ACCESS.2020.3033451

“An Efficient Nonlocal Variational Method with Application to Underwater Image Restoration”

Authors: G. Hou, Z. Pan, G. Wang, H. Yang, J. Duan

Journal: Neuro