Ning Wang | Molecule Dynamics | Best Researcher Award | 13229

Mr. Ning Wang | Molecule Dynamics | Best Researcher Award 

Mr. Ning Wang, Peking University, China

Mr. Ning Wang is a Master’s student in Materials Physics and Chemistry at Peking University, Shenzhen Graduate School. His research focuses on AI-driven advancements in materials science, including machine learning applications in molecular simulations and atomic interaction modeling. He has conducted research at the Matter Lab, University of Toronto, and has multiple publications in computational materials science. His work includes the development of the Egsmole model for molecular orbital learning, machine learning-accelerated crystal growth simulations, and AI-driven material discovery tools. He has received several academic awards and actively contributes to open-source projects in computational chemistry.

Profile

Scopus

Early Academic Pursuits 🎓

Ning Wang’s academic journey began with a strong foundation in materials science and engineering. His undergraduate studies at Northeastern University (2018–2022) were marked by excellence, earning him prestigious awards such as the National Scholarship (2020) and the First-Class University Scholarship. His early exposure to materials research set the stage for his specialization in computational materials science and AI-driven simulations. His research at the Key Lab of Electromagnetic Processing of Materials, where he investigated 5A90 Al-Li alloys, demonstrated his keen analytical skills and commitment to advancing materials science.

Building on this foundation, he pursued a Master’s degree in Materials Physics and Chemistry at Peking University, Shenzhen Graduate School. His summer research stint at the Matter Lab, University of Toronto (2024), under Prof. Alan Aspuru-Guzik, further refined his expertise in AI applications for materials science. His dedication to the field was evident in his research on molecular orbital learning using machine learning, where he introduced groundbreaking methodologies for enhanced computational simulations.

Professional Endeavors 🏗️

Ning Wang’s professional trajectory has been characterized by a blend of theoretical research and practical application. His work at Peking University’s Pan Group focused on machine learning-accelerated simulations of silver single crystal growth. He developed a robust dataset comprising over 70,000 data points using density functional theory (DFT) calculations and trained machine learning models to predict material behaviors accurately.

Additionally, his involvement with DP Technology in 2023 saw him enhancing the DeepPot model with Transformer-M architecture, achieving significant improvements in energy prediction. His participation in the AI4S Cup further demonstrated his ability to apply AI-driven techniques to real-world material challenges, such as predicting attributes of OLED materials.

Contributions and Research Focus 🔬

Ning Wang’s research is at the intersection of artificial intelligence, computational chemistry, and materials science. His key contributions include:

  • Egsmole Model: A novel equivariant graph neural network designed for molecular orbital learning, ensuring symmetry adherence in molecular simulations.
  • GDGen Methodology & Pygdgen: A gradient descent-based approach for generating optimized atomic configurations, significantly improving computational simulations.
  • Machine Learning-Accelerated Crystal Growth: Developing AI-driven force fields to predict and optimize silver single crystal growth, bridging experimental and theoretical insights.
  • DeepPot Enhancement: Integrating Transformer-M architecture to improve atomic interaction modeling, reducing prediction errors and enhancing computational efficiency.
  • XMaterial Plugin: Connecting ChatGPT with the Materials Project database, enabling seamless AI-driven material searches without requiring coding expertise.

His ability to merge AI with materials science has resulted in impactful publications, including works in the Journal of Alloys and Compounds and Computer Physics Communications. His research papers focus on novel AI methodologies for predicting molecular properties, optimizing atomic interactions, and accelerating material discovery.

Accolades and Recognition 🏆

Ning Wang’s contributions have earned him significant recognition in the scientific community:

  • National Scholarship (2020): Awarded to the top 1% of students, recognizing academic excellence.
  • First-Class University Scholarship (2020): Honoring outstanding research contributions during his undergraduate studies.
  • 3rd Prize in DP Technology Hackathon (2023): Acknowledging his innovative approach to enhancing DeepPot models with AI.
  • Acceptance at Prestigious Conferences: His research on AI-driven atomic interactions and molecular simulations has been presented at the International Conference on Electronic Information Engineering and Computer Science.
  • Publication in High-Impact Journals: His papers in Journal of Alloys and Compounds and Computer Physics Communications highlight his thought leadership in AI-driven materials research.

Publishing Top Notes

Author: Tao, Y., Jiang, W., Yang, Q., Cao, X., Wang, N.

Journal: Nano Energy

Year:  2025

Author: Zhu, Q., Sun, E., Sun, Y., Cao, X., Wang, N.

Journal: Nanomaterials

Year: 2024

Author: Zhang, Z., Zhang, H., Ma, J., Wang, N.

Journal: Construction and Building Materials

Year: 2024

 

 

 

Linhan He | Chemistry and Materials | Best Researcher Award

Ms. Linhan He | Chemistry and Materials | Best Researcher Award | 13181

Ms. Linhan He, Shenyang ligong university, China

Ms. Linhan He is affiliated with Shenyang Ligong University in China. Her academic and professional background reflects a strong focus on innovation and research. As a representative of Shenyang Ligong University, she contributes to advancements in her field and actively participates in academic and collaborative initiatives to foster knowledge and technology development.

Profile

Scopus

🌟 Early Academic Pursuits

Linhan He’s academic journey began with a deep curiosity and passion for chemistry, materials science, and physics. Currently pursuing a master’s degree in Optical Engineering at Shenyang Ligong University, Linhan has shown an unwavering commitment to expanding the boundaries of scientific knowledge. His education has been marked by a rigorous focus on advanced computational chemistry and quantum mechanics. Throughout his academic career, Linhan has demonstrated exceptional analytical skills and a passion for exploring complex concepts, laying a solid foundation for his future contributions to science and technology.

🏗️ Professional Endeavors

Despite being early in his career, Linhan has actively engaged in research that bridges theoretical exploration and practical application. His primary research interests include optoelectronic materials, computational modeling, and the properties of two-dimensional nanomaterials. Linhan’s role as a student-researcher at Shenyang Ligong University has positioned him to collaborate with leading academics and researchers in the field. His professional endeavors are not limited to academia; he has also actively sought opportunities to contribute to interdisciplinary projects, further broadening his expertise and impact.

🔬 Contributions and Research Focus

Linhan He’s research primarily focuses on the electronic and electrical properties of bilayer silicene nanoribbons, a promising material in the field of nanotechnology and flexible electronics. His notable contributions include:

  1. Published Works: Linhan has published two peer-reviewed papers in high-impact journals.
    • “The Effect of Carbon Chain Doping at Different Positions on the Electrical Properties of Bilayer Silicene Nanoribbons” (Journal of Materials Science, 2024).
    • “Electronic Properties of Bilayer Silicene Nanoribbons Modulated by External Electric Field and Carbon Adsorption” (Journal of Physics and Chemistry of Solids, 2025).
  2. Research Methodologies: Using computational simulations and quantum mechanics, Linhan has investigated innovative approaches to improve the performance and efficiency of nanomaterials.
  3. Interdisciplinary Approach: Linhan’s research intersects physics, chemistry, and material science, emphasizing the real-world applicability of theoretical findings.

🏆 Accolades and Recognition

Linhan’s dedication to research excellence has earned him recognition in the scientific community. Though still in the early stages of his career, he has already gained accolades for his publications and academic achievements. His research papers are cited in respected databases such as the Science Citation Index (SCI), showcasing the significance of his contributions. Linhan’s work reflects a rare combination of creativity and rigor, earning him a nomination for the prestigious Best Researcher Award.

🌍 Impact and Influence

Linhan He’s research in bilayer silicene nanoribbons is expected to have a far-reaching impact on fields such as flexible electronics, energy storage, and nanotechnology. By improving the understanding of the electronic properties of advanced materials, his work contributes to the development of next-generation devices.

His research has already gained international attention, with publications in globally recognized journals, indicating its relevance to the scientific community at large. Linhan’s dedication to creating innovative solutions ensures that his work resonates beyond academia, influencing industry practices and technological advancements.

🌱 Legacy and Future Contributions

As a rising star in the field of optical engineering and materials science, Linhan He is poised to make significant contributions in the years to come. He envisions applying his research to create sustainable, high-performance materials for electronics and other applications. Linhan is also passionate about mentoring young scientists and fostering a culture of innovation within his academic and professional communities.

With a focus on interdisciplinary collaboration and applied research, Linhan aims to expand his expertise into emerging areas such as artificial intelligence-driven materials design and environmentally friendly nanotechnology solutions. His journey is a testament to the power of curiosity and perseverance in shaping the future of science.

Publication Top Notes

Author: Qian, Z., Wu, L., Wang, Z., Zhao, K., Zhang, Q.

Journal: Materials Science in Semiconductor Processing

Year: 2024

Author: He, L., Wu, L., Wang, S., Liu, Y., Shen, L.

Journal: Materials Science

Year: 2024

Author: Wang, S., Wu, L., Wang, Z., Liu, Y., Shen, L.

Journal: Materials Today Communications

Year: 2024