Yousef El Mourabit | Machine Learning in Physics | Best Academic Researcher Award

Published on by Global Energy Awards

Best Academic Researcher Award

Yousef El Mourabit
TIAD Laboratory, Faculty of Sciences and Technics, Sultan Moulay Slimane University
Yousef El Mourabit
Affiliation TIAD Laboratory, Faculty of Sciences and Technics, Sultan Moulay Slimane University
Country Morocco
Google Scholar ID 2WDI_wMAAAAJ&hl
Documents 38
Citations 236
h-index 8
Subject Area Machine Learning in Physics
Event Global Energy Awards

Yousef El Mourabit is a researcher affiliated with the TIAD Laboratory at the Faculty of Sciences and Technics, Sultan Moulay Slimane University, Morocco. His academic work is situated at the interdisciplinary intersection of machine learning and physics, with contributions spanning computational modeling, intelligent systems, and data-driven scientific analysis. His publication record and citation metrics demonstrate sustained scholarly activity and measurable academic influence within his research domain [1].

Abstract

This article presents an academic profile and recognition overview of Yousef El Mourabit in consideration of the Best Academic Researcher Award. The assessment highlights research output, scholarly impact, publication activity, and disciplinary relevance in machine learning applications within physics. The profile reflects both quantitative indicators and qualitative academic contributions documented through scholarly records [1].

Keywords

Machine Learning in Physics; Computational Physics; Intelligent Systems; Scientific Modeling; Data Analysis; Applied Physics; Academic Recognition; Research Evaluation

Introduction

The integration of machine learning techniques into physics research has emerged as a transformative direction in modern scientific inquiry. Researchers working within this field contribute to predictive modeling, pattern recognition, and computational optimization across physical systems. Yousef El Mourabit’s scholarly work aligns with this evolving research landscape through interdisciplinary contributions connecting artificial intelligence methods with physics-based applications [2].

Research Profile

The academic profile of Yousef El Mourabit includes 38 documented scholarly publications with 236 citations and an h-index of 8. These indicators reflect active participation in academic publishing and measurable engagement within the international research community. His institutional affiliation with Sultan Moulay Slimane University supports ongoing research and interdisciplinary collaboration in advanced scientific domains [1].

Research Contributions

Machine learning in physics has become an important interdisciplinary research area, enabling advanced analysis of complex physical systems through data-driven methodologies. This field includes the application of machine learning algorithms for interpreting physics-related data, identifying patterns, and improving predictive accuracy in scientific investigations. Researchers also develop computational approaches for scientific prediction and modeling, supporting simulations, optimization, and theoretical exploration across diverse physics domains. The integration of intelligent analytical methods into both experimental and theoretical physics has strengthened the ability to process large datasets, automate interpretation, and generate meaningful scientific insights. Collectively, these contributions connect data science with the physical sciences, creating innovative pathways for discovery, modeling, and research advancement.

Publications

The researcher’s publication portfolio includes peer-reviewed journal articles and scholarly works relevant to machine learning, computational modeling, and applied physics. These publications contribute to methodological innovation and the broader use of data-driven tools in scientific analysis [2].

Research Impact

Research impact can be evaluated through citation activity, academic visibility, and interdisciplinary relevance. With 236 citations and an h-index of 8, the scholarly record indicates continued engagement with published work by the academic community. The citation footprint suggests meaningful research dissemination and scientific influence within related disciplines [1].

Award Suitability

Based on publication activity, citation metrics, subject specialization, and interdisciplinary academic contributions, Yousef El Mourabit demonstrates strong alignment with the evaluation principles of the Best Academic Researcher Award presented within the Global Energy Awards framework. His research profile reflects both scholarly productivity and thematic relevance to emerging scientific innovation.

Conclusion

Yousef El Mourabit represents a contemporary academic researcher working at the convergence of machine learning and physics. His measurable research output, documented academic impact, and institutional contributions support recognition within an international academic award context. The profile demonstrates continued scholarly engagement and contribution to interdisciplinary scientific advancement [1].

References

  1. Google Scholar. (n.d.). Profile details: Yousef El Mourabit, Scholar ID 2WDI_wMAAAAJ.https://scholar.google.com/citations?user=2WDI_wMAAAAJ&hl=fr
  2. Yousef El Mourabit, Anouar Bouirden (2015). Ahmed Toumanari, NE Moussaid.https://scholar.google.com/citations?view_op=view_citation&hl=fr&user=2WDI_wMAAAAJ&citation_for_view=2WDI_wMAAAAJ:u5HHmVD_uO8C
  3. Global Energy Awards. (n.d.). Official event website.https://globalenergyawards.org/

Phuoc Thien Do | Machine Learning in Physics | Research Excellence Award

Published on by Global Energy Awards

Mr. Phuoc Thien Do | Machine Learning in Physics | Research Excellence Award 

Incheon National University | South Korea

Mr. Phuoc Thien Do is a Ph.D. researcher in Mechanical Engineering at Incheon National University (INU), Republic of Korea, where he is currently pursuing advanced research in the fields of soft robotics, unmanned aerial vehicles (UAVs), intelligent robotic grippers, and autonomous indoor and outdoor navigation systems. He received his M.Sc. in Mechanical Engineering from Incheon National University in 2024 and his B.Sc. in Mechanical Engineering from Ho Chi Minh City University of Technology (HCMUT), Vietnam, in 2021. His academic background reflects a strong integration of mechanical design, intelligent control, and robotics-oriented problem solving. His research primarily focuses on the development and modeling of soft robotic systems, including pneumatic actuators, tendon-driven grippers, and shape-adaptive robotic fingers with variable stiffness. He has contributed significantly to the design and kinematic modeling of soft pneumatic actuators, proposing forward kinematics-based prediction methods to accurately estimate bending motion under varying air chamber configurations. His work extends to smart material applications, particularly shape memory alloy (SMA)-actuated systems, where he has explored temperature control strategies using deep reinforcement learning to improve the performance and reliability of tendon-driven robotic grippers.

Citation Metrics (Google Scholar)

    100
      80
      60
      40
      20
      10
        0

Citations
54

Documents
4

h-index
2

Citations

h-index

i10-index

View Google Scholar Profile      View Orcid Profile      View Scopus Profile

Featured Publications

Jian Du | Machine Learning in Physics | Best Scholar Award

Published on by Global Energy Awards

Dr. Jian Du | Machine Learning in Physics | Best Scholar Award 

Politecnico di Milano | Italy

Mr. Jian Du is a fourth-year Ph.D. candidate in Petroleum and Natural Gas Engineering at China University of Petroleum–Beijing, and a visiting Ph.D. researcher at the Department of Energy, Politecnico di Milano, Italy. His research focuses on the integration of physics-based knowledge and advanced machine learning techniques to address complex industrial challenges in liquid and multi-product pipeline systems. His core interests include explainable machine learning for pipeline process monitoring, physics-informed neural networks (PINNs) for efficient simulation of complex fluid dynamics, and knowledge-embedded data science frameworks for intelligent pipeline management. Through these efforts, he aims to bridge the gap between traditional physical modeling and data-driven approaches, improving reliability, interpretability, and real-time applicability in energy transportation systems. Jian Du has made significant research contributions in the areas of contamination tracking, hydraulic transient simulation, batch tracking, corrosion prediction, and energy system forecasting. He has authored or co-authored more than 30 peer-reviewed publications, with over 17 papers as first or second author, published in leading journals such as Energy, Engineering Applications of Artificial Intelligence, Journal of Industrial Information Integration, Renewable and Sustainable Energy Reviews, and Chemical Engineering Research and Design. His cumulative journal impact factor exceeds 95, and his work includes an ESI Hot Paper and Highly Cited Paper ranked in the top 1% of the engineering field. A recurring theme in his research is the development of the “DeepPipe” framework—a series of theory-guided, physics-enhanced, and multi-modal neural networks tailored for real-time pipeline monitoring and decision support.

Citation Metrics (Scopus)

1000
  500
  400
  300
  200
  100
    50
    30
    10
      0

Citations
649

Documents
31

h-index
14

Citations

h-index

i10-index

View Scopus Profile

Featured Publications

Zihao Li | Machine Learning in Physics | Best Researcher Award

Published on by Global Energy Awards

Mr. Zihao Li | Machine Learning in Physics | Best Researcher Award

Mr. Zihao Li | Xi’an Jiaotong-Liverpool University | China

Zihao Li is an emerging talent in Data Science with a strong foundation in Information Management and Information Systems. Currently pursuing his Master’s degree at Xi’an Jiaotong-Liverpool University, he has demonstrated exceptional leadership and problem-solving skills through impactful academic projects and professional roles. His undergraduate studies at Shandong University of Finance and Economics were marked by consistent academic excellence, innovative thinking, and multiple scholarships for outstanding performance. Zihao has led diverse project teams, designing and implementing systems such as a community second-hand furniture trading platform and a ride-hailing application, showcasing his technical expertise in frameworks like Spring Boot and JavaWeb. His extracurricular engagements, including positions in academic and management organizations, highlight his ability to manage operations, coordinate teams, and strategize effectively. With a blend of analytical acumen, technological proficiency, and collaborative leadership, Zihao stands out as a promising contributor to advancing data-driven research and innovative technology solutions.

Author Profile

ORCID

Education

Zihao Li is currently enrolled in the Data Science program at the XJTLU-JITRI Academy of Industrial Technology, Xi’an Jiaotong-Liverpool University. His academic journey began at the Shandong University of Finance and Economics, where he majored in Information Management and Information Systems. His dedication to excellence was recognized through the First-class Scholarship for two consecutive years, the Special Scholarship for Innovation and Entrepreneurship, and the Best Volunteer in Social Practice in Weifang City. This academic background has equipped him with strong technical knowledge, research capability, and a deep understanding of data-driven systems. His formal education forms a solid foundation for his contributions to applied research and innovative industrial technology development.

Experience

Zihao Li’s experience spans academic research, project leadership, and corporate strategy support. As Group Leader, he directed projects such as a community second-hand furniture trading system and a JavaWeb-based ride-hailing platform, managing team coordination, coding accuracy, testing, and documentation. Professionally, he served as Assistant Management at Shenzhou Medical Technology Co., Ltd., assisting in strategic planning, data collection, academic conference organization, and technical project execution. His extracurricular leadership roles include Vice Secretary-General of the Student Union Federation at SDUFE and Vice Minister in the Model United Nations, where he honed event planning, public speaking, and cross-team collaboration skills. This blend of hands-on project experience and organizational leadership positions him as a resourceful, multidisciplinary professional ready for advanced research challenges.

Awards and Honors

Zihao Li has been recognized for his academic excellence, innovation, and service contributions. At Shandong University of Finance and Economics, he earned the First-class Scholarship in both the 2019/2020 and 2020/2021 academic years for outstanding academic performance. His creativity and entrepreneurial mindset were celebrated with the Special Scholarship for Innovation and Entrepreneurship. His commitment to community engagement was honored through the Best Volunteer in Social Practice in Weifang City (December 2021). These distinctions reflect his dedication to both scholarly achievement and societal impact, highlighting a well-rounded profile that blends intellectual merit, leadership, and community service.

Research Focus

Zihao Li’s research interests center on data science applications, intelligent systems, and digital platform development. He is particularly focused on designing efficient, user-friendly digital trading platforms, urban mobility solutions, and integrated information management systems. His academic projects have explored optimizing system architecture, improving security protocols, and enhancing user experience through robust backend development. With a foundation in Spring Boot and JavaWeb frameworks, he aims to expand his research into big data analytics, machine learning applications, and AI-driven decision support systems. His goal is to bridge the gap between technological innovation and practical industry needs, contributing to the development of scalable, secure, and sustainable digital solutions for modern communities.

Publication

Multimodal Temporal Knowledge Graph Embedding Method Based on Mixture of Experts for Recommendation

Authors: Bingchen Liu, Guangyuan Dong, Zihao Li, Yuanyuan Fang, Jingchen Li, Wenqi Sun, Bohan Zhang, Changzhi Li, Xin Li
Journal: Mathematics
Year: 2025

Conclusion 

Zihao Li’s academic excellence, technical innovation, and leadership achievements create a strong foundation for impactful research. His commitment to bridging theoretical concepts with real-world solutions demonstrates his potential to contribute significantly to his field. With continued research outputs and global engagement, he is well-positioned to emerge as a distinguished figure in data science and applied technology research.

Bin Liu | Machine Learning in Physics | Best Researcher Award

Published on by Global Energy Awards

Prof. Bin Liu | Machine Learning in Physics | Best Researcher Award

E-Surfing Digital Life Co., Limited | China

Bin Liu is a renowned expert in the fields of AI, deep learning, Bayesian methods, reinforcement learning, and embodied intelligence. He holds a Ph.D. in Signal and Information Processing from the Chinese Academy of Sciences and has contributed significantly to the development of AI algorithms with cross-disciplinary applications spanning robotics, physics, brain-computer interfaces, and more. Currently, he serves as the Chief Robot Expert at E-Surfing Digital Life Technology Co. Ltd., China Telecom Group, and continues to lead impactful research in AI and robotics.

👨‍🎓 Profile

Google scholar

Scopus

Orcid

Early Academic Pursuits 🎓

Bin Liu began his academic journey at Beijing University of Posts and Telecommunications, earning a Bachelor’s degree in Automation. His deep interest in signal processing led him to pursue a Ph.D. at the Chinese Academy of Sciences under the mentorship of Prof. Chaohuan Hou, an IEEE Fellow and Academician of the Chinese Academy of Sciences. His doctoral research laid the foundation for his future contributions to AI and computational methods.

Professional Endeavors 💼

Bin Liu has held various prestigious positions in leading tech and academic institutions. His roles include Senior Research Fellow in AI at Midea Group, Team Leader at Zhejiang Lab, and Senior Algorithm Expert at Alibaba Group. He has also served as Associate Professor at Nanjing University of Posts and Telecommunications (NUPT) and Visiting Faculty at institutions such as Carnegie Mellon University and Duke University. His leadership positions reflect his vast influence in shaping AI research and development.

Contributions and Research Focus 🔬

Bin Liu’s research has made remarkable strides in deep learning, Bayesian inference, reinforcement learning, and robotics. He is currently focused on the development of large pre-trained AI models and embodied robot systems. His work on reinforcement learning algorithms and dynamic multi-model ensembling has contributed to solving complex AI challenges, particularly in robotics and automation.

Academic Cites 📚

Bin Liu’s research has garnered widespread recognition in the academic community, with numerous citations on platforms like Google Scholar, ResearchGate, and DBLP. His work is frequently referenced in AI conferences such as ICML, ICLR, NeurIPS, and CVPR, solidifying his stature in the global AI research community.

Research Skills 🔧

Bin Liu possesses a broad skill set, including expertise in statistical modeling, Bayesian statistics, deep learning algorithms, and robotics. His multidisciplinary approach allows him to tackle complex problems by integrating knowledge from areas such as optimization, signal processing, and reinforcement learning. He has demonstrated the ability to transform theoretical models into practical, scalable solutions for real-world applications.

Teaching Experience 📖

Beyond research, Bin Liu is deeply committed to education. He holds Adjunct Professorships at prestigious institutions like Zhejiang University and the Institute of Software, Chinese Academy of Sciences. As a Guest PhD Advisor, he mentors aspiring researchers, guiding them through advanced topics in AI and machine learning. His teaching and mentoring contribute to the next generation of AI experts and robotics innovators.

Awards and Honors 🏆

Bin Liu’s contributions to science and technology have earned him numerous accolades, including:

  1. MIT Technology Review Intelligent Computing Annual Innovator in China (April 2024)
  2. CVPR’23 SoccerNet Challenge Runner-Up (June 2023)
  3. Best Paper Award, ICACI 2018
  4. Research Achievement Award by APSCIT (2017)
  5. High-level Talent in Hangzhou City (2020)

These awards highlight his exceptional innovation and leadership in AI and technology.

Legacy and Future Contributions 🌟

Bin Liu’s long-term contributions continue to shape the trajectory of AI research and robotics. His focus on large pre-trained models and embodied AI systems will likely lead to significant breakthroughs in automation, robot-human interaction, and AI-enabled industries. His ongoing work is poised to make lasting impacts on how we integrate AI into everyday life, making him a pioneer in the evolving field of AI and robotics.

  Publications Top Notes

Annealed adaptive importance sampling method in PINNs for solving high dimensional partial differential equations

  • Authors: Zhengqi Zhang, Jing Li, Bin Liu
    Journal: Journal of Computational Physics
    Year: 2025

FADS: Fourier-Augmentation Based Data-Shunting for Few-Shot Classification

  • Authors: Shuai Shao, Yan Wang, Bin Liu, Weifeng Liu, Yanjiang Wang, Baodi Liu
    Journal: IEEE Transactions on Circuits and Systems for Video Technology
    Year: 2024

Stochastic Weight Averaging Revisited

  • Authors: Hao Guo, Jiyong Jin, Bin Liu
    Journal: Applied Sciences
    Year: 2023

Robust Dynamic Multi-Modal Data Fusion: A Model Uncertainty Perspective

  • Authors: Bin Liu
    Journal: IEEE Signal Processing Letters
    Year: 2021

A Survey on Trust Modeling from a Bayesian Perspective

  • Authors: Bin Liu
    Journal: Wireless Personal Communications
    Year: 2020

 

 

Zhihu Yang | Machine Learning in Physics | Best Researcher Award

Published on by Global Energy Awards

Dr. Zhihu Yang | Machine Learning in Physics | Best Researcher Award

Xidian University | China

Zhihu Yang is an Associate Professor at Xidian University, where he has been a faculty member at the Center for Complex Intelligent Networks since 2014. Dr. Yang received his B.Eng. in Automation from Xidian University in 2009, followed by a PhD in Pattern Recognition and Intelligent Systems from the same institution in 2014. During 2017-2018, he furthered his academic journey as a visiting scholar at the Australian National University. His research primarily focuses on the evolutionary dynamics of altruistic behavior on complex networks, contributing to the understanding of cooperation, strategy evolution, and fairness in social dilemmas.

👨‍🎓Profile

Scopus

Orcid

Early Academic Pursuits

Dr. Yang’s academic journey began at Xidian University, where he completed his Bachelor’s degree in Automation. His strong interest in complex systems and network dynamics led him to pursue a PhD in Pattern Recognition and Intelligent Systems at the same institution. His doctoral research provided a foundation for his ongoing work in the evolution of cooperation and game theory, shaping his future research endeavors. During his time as a student, he exhibited a deep curiosity about social behavior, which has been a constant theme in his subsequent work.

Professional Endeavors

After earning his PhD, Dr. Yang joined the Center for Complex Intelligent Networks at Xidian University, where he continues to contribute to cutting-edge research. His work involves interdisciplinary research at the intersection of complex networks, game theory, and social behavior. His time as a visiting scholar at the Australian National University allowed him to engage with global scholars, broadening his perspective and enriching his research. Dr. Yang’s academic career is marked by a continuous pursuit of excellence in the study of cooperation dynamics and network evolution.

Contributions and Research Focus

Dr. Yang’s research has made significant contributions to understanding the evolutionary dynamics of altruistic behavior in complex networks. Some of his most notable findings include the discovery of strategy oscillations in two-strategy games and novel insights into the interplay between role evolution and strategy evolution in spatial ultimatum games. His studies on the spatial Prisoner’s Dilemma, random migration mechanisms, and the impact of conformity on cooperation have influenced how we understand cooperation in dynamic social systems. His work offers general mechanisms for promoting fairness and cooperation across networked societies.

Research Skills 🔬

Dr. Yang possesses strong expertise in complex system modeling, evolutionary game theory, and network dynamics. His research often involves sophisticated mathematical modeling, computational simulations, and reinforcement learning to explore cooperation and strategy evolution. His skills in data analysis, algorithm design, and network theory allow him to tackle interdisciplinary challenges, making him a leading expert in understanding human behavior through mathematical and computational lenses.

Teaching Experience 📖

Dr. Yang has been actively involved in teaching and mentoring students at Xidian University. As an associate professor, he teaches courses related to complex networks, pattern recognition, and intelligent systems. He has also supervised numerous graduate students, guiding them in their research and fostering their development as independent scholars. His ability to explain complex concepts and inspire critical thinking has made him a respected educator in his field.

Legacy and Future Contributions 🚀

Dr. Yang’s legacy in the field of evolutionary dynamics is marked by his groundbreaking contributions to the understanding of cooperation and strategy evolution. His innovative work continues to shape the study of social networks and altruism in complex systems. Looking forward, Dr. Yang’s future research is likely to explore the real-world applications of his findings, especially in social behavior and networked systems. He is poised to make further contributions to the integration of AI and machine learning with evolutionary game theory, potentially influencing fields like behavioral economics, social policy, and networked decision-making.

Publications Top Notes

The double-edged sword effect of conformity on cooperation in spatial Prisoner’s Dilemma Games with reinforcement learning

  • Authors: Pai Wang, Zhihu Yang
    Journal: Chaos, Solitons & Fractals
    Year: 2024

Role polarization and its effects in the spatial ultimatum game

  • Authors: Zhihu Yang
    Journal: Physical Review E
    Year: 2023

Random migration with tie retention promotes cooperation in the prisoner’s dilemma game

  • Authors: Zhihu Yang, Liping Zhang
    Journal: Chaos: An Interdisciplinary Journal of Nonlinear Science
    Year: 2023

A Migration Mechanism With Neighbor Retention Promotes Cooperation

  • Authors: Liping Zhang, Zhihu Yang
    Journal: 2022 China Automation Congress (CAC)
    Year: 2022

Oscillation and burst transition of human cooperation

  • Authors: Zhihu Yang, Zhi Li
    Journal: Nonlinear Dynamics
    Year: 2022

 

 

Zhiqing Bai | Machine Learning in Physics | Best Researcher Award

Published on by Global Energy Awards

Ms. Zhiqing Bai | Machine Learning in Physics | Best Researcher Award

Suzhou Institute of Nano-Tech and Nano-Bionics,CAS | China

👨‍🎓 Profile

Early Academic Pursuits 🎓

Ms. Zhiqing Bai began her academic journey with a strong foundation in Textile Engineering at Donghua University, where she completed both her Master’s (2016–2018) and PhD (2018–2023) studies. Her interest in fiber sensing and wearable technology developed early on, which became the focus of her later research. Her expertise expanded as he pursued joint PhD studies in Electrical and Computer Engineering at the National University of Singapore from 2021 to 2022, broadening her understanding of smart materials and energy harvesting systems.

Professional Endeavors 🔬

Since October 2023, Bai has been serving as a Research Fellow at the Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences (CAS). Her work spans multiple innovative fields, including fiber sensing, functional iongels, tactile sensors, and the development of wearable intelligent perception systems. Bai’s research has earned recognition through various academic leadership roles, including leader positions for numerous prestigious national research projects, such as the China National Postdoctoral Program and the National Natural Science Foundation of China.

🔬 Contributions and Research Focus

Zhiqing Bai’s research is centered on advancing triboelectric nanogenerators and interactive sensing technologies. Her pioneering work includes:

  • Development of eco-friendly nanocomposite fabrics for energy harvesting.
  • Creation of polyionic ecological skins for robust self-powered sensing.
  • Exploring bionic e-skin for enhanced robotic perception.

Impact and Influence 🌟

Bai’s work has significantly advanced the fields of wearable electronics and energy harvesting, with a strong focus on improving user interaction and sensor capabilities. Her designs for biocomposite materials and eco-friendly wearable technologies are paving the way for the next generation of smart textiles. Bai’s research has already influenced both academia and industry, attracting numerous citations and establishing her as a leading innovator in functional textiles.

Academic Cites 📚

Her research has resulted in numerous high-impact papers, with many published in journals such as Nano Energy, Advanced Functional Materials, and ACS Applied Materials & Interfaces. Bai’s work has been widely cited in the fields of triboelectric nanogenerators and wearable electronics, cementing her influence in the scientific community. Her contributions to multi-directional droplet sliding sensing and bionic e-skin technology have set the foundation for future developments in robotic perception and wearable devices.

Technical Skills 🛠️

Bai’s technical expertise encompasses fiber sensing, triboelectric nanogenerators (TENGs), polymeric materials, wearable sensors, and sustainable materials. She has extensive experience in designing and fabricating stretchable electronics, transparent power sources, and eco-friendly nanocomposites. Her ability to integrate interdisciplinary knowledge, including electrical engineering, textile engineering, and material science, makes her a standout researcher in the field of smart textiles and wearable technologies.

Teaching Experience 📚

Throughout her academic career, Bai has gained significant teaching experience, particularly in her role as a Research Assistant at the Suzhou Institute of Nano-Tech and Nano-Bionics. In this capacity, she has mentored graduate students and contributed to academic seminars, sharing her expertise on energy harvesting and wearable sensor systems. Bai’s role as a leader in various national research projects also involves providing guidance to young researchers, helping them grow and succeed in cutting-edge fields.

Top Noted Publications

Constructing high-efficiency stretchable-breathable triboelectric fabric for biomechanical energy harvesting and intelligent sensing
  • Authors: Xu, Y.; Bai, Z.; Xu, G.
    Journal: Nano Energy
    Year: 2023
Constructing a versatile hybrid harvester for efficient power generation, detection and clean water collection
  • Authors: Xu, Y.; Bai, Z.; Xu, G.; Shen, H.
    Journal: Nano Energy
    Year: 2022
Constructing highly tribopositive elastic yarn through interfacial design and assembly for efficient energy harvesting and human-interactive sensing
  • Authors: Bai, Z.; He, T.; Zhang, Z.; Xu, Y.; Zhang, Z.; Shi, Q.; Yang, Y.; Zhou, B.; Zhu, M.; Guo, J. et al.
    Journal: Nano Energy
    Year: 2022
Elastic Textile Threads for Fog Harvesting
  • Authors: Nguyen, L.T.; Bai, Z.; Zhu, J.; Gao, C.; Zhang, B.; Guo, J.
    Journal: Langmuir
    Year: 2022
Enhancing Fog Harvest Efficiency by 3D Filament Tree and Elastic Space Fabric
  • Authors: Nguyen, L.T.; Bai, Z.; Zhu, J.; Gao, C.; Luu, H.; Zhang, B.; Guo, J.
    Journal: ACS Sustainable Chemistry and Engineering
    Year: 2022