Rubén Lostado Lorza | Engineering | Best Academic Researcher Award

Published on by Innovation Technologist

Best Academic Researcher Award

Rubén Lostado Lorza
University of La Rioja, Spain

               Researcher profile
Affiliation University of La Rioja
Country Spain
Scopus ID 34872962800
Documents 78
Citations 1,173
h-index 21
Subject Area Engineering
Event Global Innovation Technologist Awards
ORCID 0000-0001-5902-6078

The Best Academic Researcher Award profile recognizes the research record of Rubén Lostado Lorza, an engineering researcher affiliated with the University of La Rioja in Spain. The supplied bibliometric indicators report 78 documents, 1,173 citations, and an h-index of 21. His listed publications address computational modelling, optimization, welding processes, and biomedical engineering applications. These topics illustrate connections between numerical methods, engineering design, and the investigation of complex physical systems. The profile presents available researcher information and selected publications for academic recognition through the Global Innovation Technologist Awards. [1]

Abstract

This article summarizes the academic profile, selected research themes, and reported bibliometric indicators of Rubén Lostado Lorza. The supplied publication information highlights finite element modelling, genetic-algorithm-based optimization, response surface methodology, experimental comparison, and thermal efficiency in welding. Such approaches are relevant to engineering research because they help investigate system behaviour, compare predictive methods, and support evidence-informed design decisions. The article distinguishes reported profile metrics from interpretations of research significance and links readers to available researcher and publication records. [2]

Keywords

Engineering research; finite element modelling; computational optimization; genetic algorithms; response surface methodology; welding processes; biomedical engineering; research impact; academic recognition.

Introduction

Engineering research combines theoretical analysis, computational simulation, and experimental evidence to understand and improve technical systems. Numerical modelling can help researchers examine conditions that are difficult to isolate experimentally, while optimization techniques can identify parameter combinations that improve agreement with observed behaviour. The listed works associated with this profile span manufacturing processes and biomedical modelling, demonstrating the relevance of computational methods across different engineering contexts. Publication records and persistent researcher identifiers provide pathways for readers to verify bibliographic details. [3]

Research Profile

The supplied profile identifies the University of La Rioja as the researcher’s institutional affiliation and Engineering as the subject area. Reported indicators include 78 documents, 1,173 citations, and an h-index of 21. These figures offer a quantitative snapshot, but they may change as databases are updated and depend on indexing coverage, author matching, and citation-counting practices. The Scopus author record and ORCID profile are therefore useful reference points for checking current information. [1]

Research Contributions

The provided publications indicate two notable methodological areas:

  • Computational and biomedical modelling: The listed lumbar intervertebral disc study combines machine learning-based genetic algorithm optimization with finite element models, comparing its approach with response surface methodology and experimental data.
  • Manufacturing and thermal analysis: The welding study investigates how shielded metal arc welding parameters affect thermal efficiency using the finite element method.

Together, these subjects illustrate how simulation and optimization can be applied to different engineering problems. Detailed conclusions about performance or practical benefits require examination of the complete articles and their reported validation results. [4]

Publications

  1. “Machine learning-based GA optimization of lumbar intervertebral disc FE models: Comparison with RSM and experimental data.” Journal of the Mechanical Behavior of Biomedical Materials, listed publication date November 2026. [4]
  2. “A comprehensive investigation of the effects of welding parameters on thermal efficiency in SMAW processes using FEM.” Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, December 12, 2025. [5]

Research Impact

The supplied total of 1,173 citations and h-index of 21 indicates that the indexed publication record has received scholarly attention. Citation counts alone, however, cannot establish research quality, originality, reproducibility, or practical influence. A balanced assessment considers methodological rigour, publication context, independent validation, and the relevance of findings to subsequent research. The figures presented here should be understood as reported profile data rather than an independent bibliometric audit. [1]

Award Suitability

The profile provides relevant material for consideration under the Best Academic Researcher Award at the Global Innovation Technologist Awards. Its reported bibliometric indicators and selected engineering publications offer starting points for reviewing scholarly activity. A formal award decision should additionally consider verified authorship, contribution statements, research quality, and the award’s published eligibility and evaluation criteria. This article does not imply that an award has been conferred.

Conclusion

Rubén Lostado Lorza’s supplied research profile combines substantial reported citation activity with publications concerning computational optimization, biomedical finite element modelling, and welding-process analysis. These areas demonstrate the broad applicability of numerical and data-driven methods in engineering. Verification through the linked author identifiers and original publications remains important for maintaining an accurate and transparent academic recognition profile.

References

  1. Elsevier. (n.d.). Scopus author details: Rubén Lostado Lorza, Author ID 34872962800. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=34872962800
  2. ORCID. (n.d.). Rubén Lostado Lorza: ORCID researcher identifier.
    https://orcid.org/0000-0001-5902-6078
  3. “Machine learning-based GA optimization of lumbar intervertebral disc FE models: Comparison with RSM and experimental data.” (2026). Journal of the Mechanical Behavior of Biomedical Materials. DOI: 10.1016/j.jmbbm.2026.107602.
    https://doi.org/10.1016/j.jmbbm.2026.107602
  4. “A comprehensive investigation of the effects of welding parameters on thermal efficiency in SMAW processes using FEM.” (2025). Energy Sources, Part A: Recovery, Utilization, and Environmental Effects.
    https://doi.org/10.1080/15567036.2025.2520434
  5. Global Innovation Technologist Awards. (n.d.). Official award website.
    innovationtechnologist.com

Guoyun Lu | Engineering | Best Researcher Award

Published on by Innovation Technologist

Best Researcher Award

Guoyun Lu
Taiyuan University of Technology, China

                   Guoyun Lu
Researcher Guoyun Lu
Affiliation Taiyuan University of Technology
Country China
Scopus ID 7403460724
Documents 120
Citations 657
h-index 13
Subject area Engineering
Event Global Innovation Technologist Awards

Guoyun Lu is an engineering researcher affiliated with Taiyuan University of Technology, China. The available publication information highlights research involving structural engineering, steel construction, advanced concrete materials, impact-resistant structures and computational modelling. The Best Researcher Award profile recognises this research activity in the context of the Global Innovation Technologist Awards, using the supplied bibliometric indicators and selected recent publications as its principal points of reference. [1]

Abstract

This academic recognition profile summarises Guoyun Lu’s engineering research based on supplied Scopus metrics and three listed publications from 2026. The identified work addresses concrete-filled steel tube columns, stress-wave behaviour in welded hollow spherical joints and impact performance in hierarchical thin-walled structures. These topics connect experimental investigation with numerical simulation and, in one publication, machine-learning modelling. The profile provides a concise overview of research themes, publication activity and the potential relevance of this work to the Best Researcher Award. [1]

Keywords

Engineering research; structural engineering; steel structures; geopolymer concrete; steel-fibre reinforcement; stress-wave transmission; impact resistance; numerical simulation; machine learning; research impact.

Introduction

Engineering research supports the development and assessment of structural systems intended to withstand compression, impact and complex loading conditions. Investigations into composite columns, welded connections and lightweight protective structures contribute to understanding how materials and structural configurations respond under different mechanical demands. Lu’s supplied publication record provides examples of these research directions, linking material behaviour and structural performance with experimental and computational approaches. [2]

Research Profile

Lu’s documented research themes include steel–concrete composite members, geopolymer-based construction materials, welded structural components and thin-walled systems subjected to axial impact. The listed studies indicate engagement with experimental testing and numerical analysis, with machine-learning modelling also represented in research on square concrete-filled steel tube columns. Together, these topics illustrate an engineering-oriented approach to evaluating structural response and investigating alternative material and design strategies. Detailed methods, individual findings and author-contribution statements require verification against the full articles.

Research Contributions

The supplied publications represent three complementary areas of investigation:

  • Composite construction: examining the compression performance of square concrete-filled steel tube columns incorporating steel-fibre-reinforced geopolymer concrete.
  • Structural connections: investigating stress-wave transmission and attenuation in welded hollow spherical joint–rod components through experimental and numerical methods.
  • Impact engineering: evaluating aluminum foam-filled hierarchical thin-walled structures under axial impact.

These subjects address material efficiency, structural response and mechanical performance. The available titles establish the research scope but do not, by themselves, demonstrate specific performance improvements or establish the individual contribution of each co-author. [2]

Publications

Three 2026 publications supplied for this profile are:

  1. “Compression performance of square concrete-filled steel tube columns with steel-fibre-reinforced geopolymer concrete: Experiment, simulation and machine-learning modelling.” Journal of Constructional Steel Research, 2026. Listed co-authors include Wenjie Chang, Guoyun Lu, Dongtao Xia and Biao Li.
  2. “Experimental and numerical study of stress-wave transmission and attenuation in welded hollow spherical joint-rod components.” Journal of Constructional Steel Research, 2026. Listed co-authors include Baiqian Sun, Haixiang Zhao, Chaojie Zheng and Guoyun Lu.
  3. “Performance of Aluminum Foam-Filled Hierarchical Thin-Walled Structures Under Axial Impact.” Materials, 2026. The supplied record identifies this article as open access and lists Guoyun Lu among its co-authors.

Research Impact

The supplied bibliometric figures report 120 documents, 657 citations and an h-index of 13 for the researcher profile. These indicators offer complementary measures of publication volume and citation activity. They should be interpreted alongside disciplinary citation practices, publication dates and verified author-profile records. The three listed 2026 articles each show zero citations in the supplied snapshot; this may reflect the recency of publication and should not be interpreted as a definitive assessment of their eventual influence. [1]

Award Suitability

Lu’s reported publication and citation indicators, together with the breadth of the supplied engineering research topics, provide relevant material for consideration under the Best Researcher Award at the Global Innovation Technologist Awards. A comprehensive assessment should additionally examine article quality, research originality, documented individual contributions, practical applications and independent evidence of impact. This profile summarises the available information and does not constitute an independently verified award decision.

Conclusion

Guoyun Lu’s supplied research profile reflects activity in structural and materials engineering, particularly composite columns, welded connections and impact-resistant structures. The reported bibliometric indicators and selected 2026 publications provide a foundation for academic recognition, while full-text verification and further evidence would strengthen any assessment of research quality and broader impact.

References

  1. Elsevier. (n.d.). Scopus author details: Guoyun Lu, Author ID 7403460724. Scopus. Bibliometric figures in this article are based on the information supplied for the profile and should be checked against the live author record.
    https://www.scopus.com/authid/detail.uri?authorId=7403460724
  2. Publisher-indexed publication records supplied for Guoyun Lu (2026). Article titles and journal details include records from Journal of Constructional Steel Research and Materials. Individual DOI identifiers and complete bibliographic metadata were not supplied; verify these details against the publisher pages before publication.
  3. Global Innovation Technologist Awards. Official award website. Information about the event and award programme should be confirmed against current official announcements.
    innovationtechnologist.com

Jakob Reinhardt | Engineering | Innovative Research Award

Published on by Innovation Technologist

Innovative Research Award

Jakob Reinhardt
Technical University of Munich
Jakob Reinhardt
Affiliation Technical University of Munich
Country Germany
Google Scholar aomsnFcAAAAJ
Documents 19
Citations 168
h-index 7
Subject Area Engineering
Event Global Innovation Technologist Awards
ORCID 0000-0002-7562-4104

Jakob Reinhardt is a researcher affiliated with the Technical University of Munich in Germany, recognized for contributions to engineering and human-robot interaction research. His scholarly work has explored robotic motion strategies, ergonomic evaluation in surgical robotics, and the development of socially aware robot behavior models within collaborative environments. Reinhardt’s publications demonstrate an interdisciplinary approach that integrates robotics, computer-assisted surgery, human factors engineering, and interaction design.[1] His academic profile includes peer-reviewed journal articles, conference contributions, and collaborative research outputs indexed within Scopus and Crossref databases.[2]

Abstract

This article presents a scholarly overview of Jakob Reinhardt and his research contributions in the field of engineering, with particular emphasis on human-robot interaction, robotic behavior analysis, and ergonomics in robotic-assisted procedures. His publications have contributed to understanding adaptive robot motion strategies and user-centered interaction mechanisms within collaborative technological systems. Through peer-reviewed studies and interdisciplinary research outputs, Reinhardt has participated in advancing applied robotics and interaction design methodologies within academic and engineering environments.[3]

Keywords

Human-Robot Interaction, Engineering Research, Robotic Motion Strategies, Surgical Robotics, Interaction Design, Human Factors Engineering, Ergonomic Analysis, Collaborative Robotics, Autonomous Systems, Technical University of Munich.

Introduction

Engineering research increasingly relies on interdisciplinary integration between robotics, cognitive systems, and human-centered design methodologies. Jakob Reinhardt’s work reflects these contemporary developments by focusing on socially adaptive robotic systems and the evaluation of robotic interactions within professional and medical contexts.[4] His research activities have addressed challenges associated with robot motion communication, task urgency perception, and ergonomic performance assessment in robotic-assisted surgical procedures.[5]

The broader significance of Reinhardt’s work lies in its applicability to collaborative robotics, healthcare technologies, and intelligent interaction systems. By integrating behavioral design principles with engineering methodologies, his publications contribute to the refinement of safer and more intuitive human-robot collaboration frameworks.[6]

Research Profile

Jakob Reinhardt has contributed to engineering research through publications focused on robotic systems, interaction strategies, and medical technology evaluation. His affiliation with the Technical University of Munich has provided a platform for interdisciplinary collaboration involving robotics, artificial intelligence, ergonomics, and human-computer interaction studies.[1]

  • Research specialization in human-robot interaction and collaborative robotic behavior.
  • Contributions to ergonomic evaluation methodologies in robotic-assisted surgical environments.
  • Development of motion communication strategies for autonomous mobile robots.
  • Participation in peer-reviewed journal and conference publications within engineering disciplines.

Research Contributions

One of Reinhardt’s recognized studies evaluated surgeon posture during simulated laparoscopic and robotic-assisted cholecystectomy procedures. The research contributed to understanding ergonomic challenges associated with robotic surgical systems and highlighted considerations relevant to occupational health and medical engineering design.[7]

His publication titled Back-off: Evaluation of Robot Motion Strategies to Facilitate Human-Robot Spatial Interaction investigated adaptive motion strategies that allow robots to communicate spatial awareness and collaborative intent more effectively. The findings supported the development of socially responsive robotic systems designed for shared environments.[8]

Reinhardt also contributed to research on hesitant movement gestures for mobile robots, examining how robotic motion influences user interpretation and interaction confidence. The study demonstrated the importance of nonverbal communication mechanisms in robotic navigation and collaborative settings.[9]

Publications

  1. Surgeon posture evaluation during simulated laparoscopic and robotic-assisted cholecystectomy, International Journal of Computer Assisted Radiology and Surgery, 2026.
  2. Back-off: Evaluation of Robot Motion Strategies to Facilitate Human-Robot Spatial Interaction, ACM Transactions on Human-Robot Interaction, 2021.
  3. Design of a hesitant movement gesture for mobile robots, PLOS ONE, 2021.
  4. Investigating Perceived Task Urgency as Justification for Dominant Robot Behaviour, 2020.

Research Impact

The research impact associated with Jakob Reinhardt’s academic profile is reflected through citation activity, interdisciplinary collaboration, and contributions to applied robotics research. His studies have addressed practical engineering problems associated with interaction safety, motion interpretation, and ergonomics in robotic systems.[2]

With a documented Scopus h-index and international publication record, Reinhardt’s work demonstrates scholarly engagement within engineering and robotic interaction communities. The integration of human-centered principles into robotic system design remains a notable characteristic of his research contributions.[3]

Award Suitability

Jakob Reinhardt’s research profile aligns with the objectives commonly associated with innovation and technology-focused academic recognition programs. His contributions to robotics, interaction design, and engineering evaluation methodologies support advancements in collaborative intelligent systems and applied technological research.[6]

The interdisciplinary nature of his work, including applications in healthcare technology and human-robot collaboration, demonstrates relevance to contemporary engineering challenges and innovation-driven scientific initiatives. His publication history and citation record further support recognition within the context of the Global Innovation Technologist Awards.[4]

Conclusion

Jakob Reinhardt has contributed to engineering and robotics research through investigations into human-robot interaction, ergonomic assessment, and socially adaptive robotic systems. His scholarly publications demonstrate a sustained focus on improving collaborative robotic behavior and evaluating the practical implications of robotic technologies within professional and medical environments.[7] The combination of interdisciplinary methodology, peer-reviewed publication activity, and measurable research impact supports his recognition within international academic and technological award platforms.[8]

References

  1. ORCID. (n.d.). Jakob Reinhardt researcher profile. ORCID Registry.
    https://orcid.org/0000-0002-7562-4104
  2. Elsevier. (n.d.). Scopus author details: Jakob Reinhardt, Author ID 57201292569. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57201292569
  3. PLOS ONE. (2021). Design of a hesitant movement gesture for mobile robots.
    https://doi.org/10.1371/journal.pone.0249081
  4. ACM Transactions on Human-Robot Interaction. (2021). Back-off: Evaluation of Robot Motion Strategies to Facilitate Human-Robot Spatial Interaction.
    https://doi.org/10.1145/3418303
  5. Springer. (2020). Investigating Perceived Task Urgency as Justification for Dominant Robot Behaviour.
    https://doi.org/10.1007/978-3-030-50726-8_15
  6. Technical University of Munich. (n.d.). Research affiliation and academic activities.
  7. International Journal of Computer Assisted Radiology and Surgery. (2026). Surgeon posture evaluation during simulated laparoscopic and robotic-assisted cholecystectomy.
    https://doi.org/10.1007/s11548-026-03666-4
  8. Open Science Framework. (2020). Back-off: Evaluation of Robot Motion Strategies to Facilitate Human-Robot Spatial Interaction.
    https://doi.org/10.31234/osf.io/ws2ez
  9. Crossref. (n.d.). Publication indexing and DOI registry records for Jakob Reinhardt.

Devender Singh | Robotics and Automation | Young Innovator Award

Published on by Innovation Technologist

Mr. Devender Singh | Robotics and Automation | Young Innovator Award

Uttaranchal University | India

Mr. Devender Singh is an emerging researcher in Internet of Things (IoT), Artificial Intelligence (AI), and smart device engineering, with a strong focus on real-time monitoring systems and intelligent automation. His work integrates embedded systems, wireless communication, and cloud-based analytics to develop scalable, application-oriented solutions across domains such as smart agriculture, healthcare, surveillance, and environmental monitoring. He has contributed to multiple patents and interdisciplinary innovations, emphasizing practical deployment and societal impact. His research also extends to AI-driven diagnostics, edge computing, and blockchain-integrated IoT systems, demonstrating a commitment to advancing next-generation intelligent infrastructure and sustainable technological ecosystems.

                        Citation Metrics (Google Scholar)

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Citations
289
Documents
36
h-index
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Documents

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View Google Scholar Profile  View ORCID Profile

Featured Publications


Secure and smart healthcare system using IoT and deep learning models

– International Conference on Technological Advancements, 2022 | Cited by: 121

Mg-based metal matrix composite in biomedical applications: a review

– Materials Today: Proceedings, 2023 | Cited by: 19 

Ping Li | Mechanical Engineering | Best Researcher Award

Published on by Innovation Technologist

Assoc. Prof. Dr. Ping Li | Mechanical Engineering | Best Researcher Award

Guangzhou University, China

Dr. Ping Li is an Associate Professor of Mechanical Engineering at the School of Mechanical and Electrical Engineering, Guangzhou University, China. With a PhD from South China University of Technology, Dr. Li specializes in micro-nano functional surface fabrication, microscale interfacial fluid transport, and thermal optimization for electronic devices. His research integrates advanced microfabrication techniques with fluid dynamics and materials science, contributing significantly to the fields of microstructured surface engineering, thermal management, and photovoltaic performance optimization. He has authored numerous peer-reviewed articles in high-impact international journals and serves as a master’s student advisor.

Publication Profile 

Orcid

Educational Background 🎓

  • 2011–2015:
    PhD in Mechanical Engineering
    South China University of Technology, Guangzhou, China

    • Dissertation: Characterized Micro-structured array of ground surface and its functional properties

    • Supervisor: Prof. Jin Xie

    • Sponsored by NSFC Program

  • 2010–2011:
    M.Sc. in Mechanical Engineering
    South China University of Technology, Guangzhou, China

  • 2006–2010:
    B.Eng. in Process Equipment and Control Engineering
    University of South China, Hengyang, China

Professional Experience 💼

  • 2023–Present
    Associate Professor, Master Tutor
    Guangzhou University, School of Mechanical and Electrical Engineering

  • 2017–2023
    Lecturer, Master Tutor
    Guangzhou University, School of Mechanical and Electrical Engineering

  • 2015–2017
    Engineer
    CNPC Tubular Goods Research Institute, Xi’an, China

    • State Key Laboratory for Performance and Structure Safety of Petroleum Tubular Goods and Equipment Materials

Research Interests 🔬

  1. Micro-nano Functionalization Fabrication and Materials Processing

    • Surface microstructuring, wettability control, surface roughness analysis

  2. Microscale Interfacial Fluid Transport Phenomena

    • Capillary action, thin film flows, liquid bridge dynamics using AFM

  3. Optimization Thermal Design for Electronic Devices

    • Microfluidic heat sinks, thermal diode design, solar cell interface structures

Awards and Honors🏆✨

While not explicitly listed in the CV, the following inferred distinctions apply:

  • NSFC-sponsored PhD Research Project

  • First-authored and corresponding author roles in multiple high-impact journals such as Physics of Fluids, Nanomaterials, Langmuir, and Applied Surface Science

  • Research contributions cited in interdisciplinary fields, including thermal science, optics, and materials science

Conclusion🌟

Dr. Ping Li is a rising expert in the interdisciplinary domain of micro-nano engineering, thermal management, and interfacial physics. Through his academic and industrial experiences, he bridges theoretical modeling with practical engineering applications, particularly in microscale fabrication and energy systems. His continued research output and mentorship roles position him as a significant contributor to both academic research and engineering innovation in China.

Publications 📚

📘 Unidirectional Heat and Fluid Transfer Performances of a Thermal Diode with Fishbone-Microstructure Wicks
🧪 Journal of Materials Chemistry C, 2024
🔗 DOI: 10.1039/D4TC03236E
👥 Ping Li, Jiale Huang, Haifeng Qiu, Liangming Deng, Jiawei Liao, Tuo Jin, Yongfeng Zheng, Jianhua Xiang

🏗️ Topological Design for Isotropic Metamaterials Using Anisotropic Material Microstructures
📘 Engineering Analysis with Boundary Elements, 2024-05
🔗 DOI: 10.1016/j.enganabound.2024.01.025
👥 Jianhua Xiang, Jing Chen, Yongfeng Zheng, Ping Li, Jiale Huang, Zhipeng Chen

📐 Hierarchical Topology Optimization with Varying Micro-structural Aspect Ratios
📘 Engineering Analysis with Boundary Elements, 2023-11
🔗 DOI: 10.1016/j.enganabound.2023.07.044
👥 Yongfeng Zheng, Jianhua Xiang, Zhongyuan Liao, Ping Li, Xiwen Cai, Zhipeng Chen, Jiale Huang

🔥 Design and Thermal Performance of Thermal Diode Based on the Asymmetric Flow Resistance in Vapor Channel
📘 International Journal of Thermal Sciences, 2023-09
🔗 DOI: 10.1016/j.ijthermalsci.2023.108345
👥 Jianhua Xiang, Wenqiang Yang, Hongyan Liao, Ping Li, Zhipeng Chen, Jiale Huang

🍃 The Transitional Wettability on Bamboo-Leaf-like Hierarchical-Structured Si Surface Fabricated by Microgrinding
🧪 Nanomaterials, 2022-08-22
🔗 DOI: 10.3390/nano12162888
👥 Ping Li, Jinxin Wang, Jiale Huang, Jianhua Xiang

🧴 Study on Nitrile Oxide for Low-Temperature Curing of Liquid Polybutadiene
🧪 Materials, 2022-05-09
🔗 DOI: 10.3390/ma15093396
👥 Ping Li, Xiaochuan Wang

🔍 Evaluation on Ground Surface Accuracies of Large-Depth and Steeply Micro-Structured SiC Surfaces
📘 International Journal of Precision Engineering and Manufacturing, 2021-02-04
🔗 DOI: 10.1007/s12541-020-00442-5
👥 Ping Li, Xiaochu Liu, Junwu Chen

🧲 Influence of Lateral Movement on Level Behavior of Adhesion Force Measured Repeatedly by an Atomic Force Microscope (AFM) Colloid Probe in Dry Conditions
🧪 Materials, 2021-01-13
🔗 DOI: 10.3390/ma14020370
👥 Ping Li, Tianmao Lai

🧨 Synthesis and Curing of Allyl Urethane NIMMO-THF Copolyether with Three Functional Groups as a Potential Energetic Binder
📘 Central European Journal of Energetic Materials, 2020-03-26
🔗 DOI: 10.22211/cejem/119233
👥 Ping Li

🧪 Synthesis and Curing of AUT-PNIMMO with Three Functional Groups
📘 Polymer Korea, 2019-07-31
🔗 DOI: 10.7317/pk.2019.43.4.503
👥 Ping Li

💧 Direct Evidence of a Radius of Collection Area for Thin Film Flow in Liquid Bridge Formation by Repeated Contacts Using AFM
📘 Langmuir, 2019-05-07
👥 Ping Li