Sunil Kumar Khare | Green Technology | Outstanding Scientist Award

Outstanding Scientist Award

Sunil Kumar Khare
University of Petroleum and Energy Studies, India

Sunil Kumar Khare
Affiliation University of Petroleum and Energy Studies
Country India
Scopus ID 26324209600
Documents 18
Citations 214
h-index 7
Subject Area Green Technology
Event Technology Scientists Awards
ORCID 0000-0001-5041-3012

Sunil Kumar Khare is a researcher affiliated with the University of Petroleum and Energy Studies in India whose scholarly profile encompasses green technology and data-driven engineering research. His documented work includes applications of analytics, regression modelling, pipeline network optimization, and geochemical interpretation, demonstrating an interdisciplinary orientation toward technology-enabled scientific problem solving. [1] [2] [3]

Abstract

Sunil Kumar Khare is a researcher at the University of Petroleum and Energy Studies, India, working within the broad domain of Green Technology. His scholarly record includes research involving data analytics, regression modelling, engineering optimization, and geochemical analysis. His publications demonstrate applications of computational methods to energy and geological problems, including geothermal drilling, pipeline configuration, and igneous-province characterization. These studies illustrate an interdisciplinary research profile connecting analytical techniques with practical engineering and environmental contexts. His documented scholarly output and citation record provide evidence of sustained research engagement and academic visibility. [1] [2] [3]

Keywords

Green Technology; Data Analytics; Regression Modelling; Geothermal Wells; Drilling Engineering; Pipeline Network Optimization; Sensitivity Analysis; Geochemistry; Petrogenetics; Igneous Provinces; Energy Technology; Engineering Analytics.

Introduction

Green Technology increasingly depends on analytical methods capable of improving resource efficiency, engineering decisions, and environmental understanding. Khare’s research reflects this interdisciplinary direction through studies applying data analytics to geothermal drilling, optimization to pipeline networks, and analytical methods to geological characterization, connecting computational approaches with energy and Earth-science applications. [1] [2] [3]

Research Profile

Khare’s research profile combines engineering analytics, optimization, and geoscientific investigation. His documented publications address prediction of drilling performance, multi-product pipeline configuration, and data-supported interpretation of geochemical and petrogenetic characteristics. Together, these themes indicate a research orientation toward quantitative methods that support complex energy, infrastructure, and geological systems across applied scientific contexts. [1] [2] [3]

Research Contributions

The documented research contributes analytical perspectives to energy and geological engineering problems. Regression modelling is applied to geothermal drilling-rate prediction, optimization frameworks examine pipeline configuration and objective-function sensitivity, while data analytics supports geochemical and petrogenetic interpretation. These contributions demonstrate the practical use of quantitative approaches for complex, multidisciplinary technological investigations. [1] [2] [3]

Publications

Khare’s documented publications cover three complementary areas: predictive analytics for geothermal drilling, optimization of multi-product pipeline networks, and data analytics for geochemical and petrogenetic investigation. These works illustrate the application of quantitative and computational techniques to engineering and Earth-science questions, with relevance to energy systems and technology-oriented research. [1] [2] [3]

Research Impact

The research demonstrates potential practical relevance across geothermal energy, pipeline infrastructure, and geological interpretation. Predictive modelling can support drilling analysis, optimization can inform network configuration decisions, and geochemical analytics can strengthen interpretation of complex geological datasets. The combined portfolio reflects technology-oriented research addressing diverse analytical challenges within energy-related domains. [1] [2] [3]

Award Suitability

Khare’s documented research aligns with the broad objectives of scientific recognition in technology-oriented disciplines. His work combines analytical modelling, engineering optimization, and geoscientific data analysis, while addressing energy and infrastructure applications. The breadth of these themes provides a reasonable basis for consideration under an Outstanding Scientist Award focused on applied technological research. [1] [2] [3]

Conclusion

Sunil Kumar Khare presents a multidisciplinary research profile spanning green technology, energy engineering, optimization, predictive analytics, and geoscience. His documented publications demonstrate the application of quantitative approaches to practical scientific problems. The combination of engineering and Earth-science research provides a substantive foundation for consideration for technology-focused scientific recognition. [1] [2] [3]

References

  1. Khare, S. K., et al. (2025). Data analytics and regression modelling for drilling rate of penetration prediction of geothermal wells. In Advances in Energy and Environmental Engineering. Springer.
    https://doi.org/10.1007/978-981-96-3667-9_11
  2. Khare, S. K., et al. (2024). Optimizing multi-product pipeline network configuration design: A comprehensive framework with objective function sensitivity analysis. Scopus. Publication record: 85184306294.
    https://www.scopus.com/pages/publications/85184306294
  3. Khare, S. K., et al. (2024). Data analytics for geochemical and petrogenetic study of an igneous province: A case study on Andean andesite, South America. Journal of Earth System Science.
    https://doi.org/10.1007/s12040-024-02399-9
  4. Elsevier. (n.d.). Scopus author details: Sunil Kumar Khare, Author ID 26324209600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=26324209600
  5. ORCID. (n.d.). Sunil Kumar Khare: ORCID record. ORCID.
    https://orcid.org/0000-0001-5041-3012

Wentao Shang | Green Technology | Best Researcher Award

Best Researcher Award

Wentao Shang
Affiliation Jinan University
Country China
Scopus ID 57604364900
Documents 34
Citations 812
h-index 15
Subject Area Green Technology
Event Technology Scientists Awards
ORCID 0000-0002-5168-7696

Wentao Shang is affiliated with Jinan University, China, and works across membrane science, separation technologies, computational prediction, imaging, and advanced materials. His recent scholarly record includes research on membrane distillation, nanofiltration fouling prediction, and supramolecular materials, providing a multidisciplinary basis for consideration within the field of green technology. [1] [2] [3]

Abstract

Wentao Shang is a researcher at Jinan University whose documented work connects membrane science, green technology, computational modeling, imaging, and advanced materials. His recent publications examine surface patterning for membrane distillation, multimodal convolutional neural networks for dynamic nanofiltration fouling prediction, and solution-sheared supramolecular oligomers with improved thermal-resistant adhesion. These studies demonstrate an interdisciplinary approach combining materials engineering, separation processes, experimental characterization, and data-driven analysis. With 34 documented publications, 812 citations, and an h-index of 15, his profile indicates sustained scholarly activity and measurable research visibility. The breadth and environmental relevance of these themes support consideration for a Best Researcher Award.

Keywords

Keywords: Green Technology, Membrane Distillation, Nanofiltration, Membrane Fouling, Optical Coherence Tomography, Convolutional Neural Networks, Surface Patterning, Advanced Materials, Supramolecular Oligomers, Sustainable Engineering.

Introduction

Wentao Shang’s research profile at Jinan University reflects an interdisciplinary focus connecting membrane processes, nanofiltration, imaging-based analysis, advanced materials, and sustainable engineering. His recent publications address membrane distillation, fouling prediction, and thermally resistant supramolecular materials, indicating a research trajectory relevant to emerging green technology and resource-efficient engineering. [1] [2] [3]

Research Profile

Shang is associated with research spanning membrane science, separation technologies, computational prediction, and functional materials. His publication record includes studies using surface patterning to improve membrane distillation and multimodal convolutional neural networks to model nanofiltration fouling. These themes connect experimental characterization, materials engineering, and data-driven methods for environmental applications. [1] [2]

Research Contributions

Shang’s contributions can be viewed through three complementary areas: engineering membrane surfaces for improved separation performance, applying in-situ optical coherence tomography and multimodal neural networks to characterize fouling dynamics, and investigating supramolecular materials with enhanced thermal and adhesive properties. Together, these studies demonstrate integration of experimental methods, computational analysis, and materials design. [1] [2] [3]

Publications

The documented publications associated with Shang include a 2026 review of surface patterning in membrane distillation, a 2026 Desalination article on multimodal convolutional neural networks for nanofiltration fouling prediction, and a Nature Communications study on solution-sheared supramolecular oligomers. The works collectively cover membrane engineering, machine learning, imaging, adhesion, and advanced materials. [1] [2] [3]

Research Impact

The research has potential relevance to green technology through improved membrane efficiency, fouling management, and durable functional materials. Surface-engineered membranes may support cleaner separation processes, while predictive imaging models can improve understanding of fouling development. Work on thermally resistant adhesives further broadens the profile toward resource-conscious and performance-oriented materials engineering. [1] [2] [3]

Award Suitability

The Best Researcher Award profile is supported by a combination of publication activity, citation indicators, interdisciplinary research themes, and alignment with green technology. The reported record of 34 documents, 812 citations, and an h-index of 15 provides quantitative evidence of scholarly visibility, while recent publications demonstrate continuing research activity. [1] [2] [3]

Conclusion

Wentao Shang presents a research profile combining membrane technology, computational modeling, imaging, and advanced materials. His recent work addresses practical challenges in separation efficiency, fouling prediction, and material durability. The combination of documented scholarly output and green-technology relevance provides a reasonable academic basis for consideration under the Best Researcher Award. [1] [2] [3]

References

  1. Zhang, C., Lin, Y., Lu, G., Yuan, B., Chen, P., Farid, M. U., Lee, V. P. H., Shang, W., Li, W., & An, A. K. (2026). Surface patterning in membrane distillation: Fabrication, mechanism, and performance enhancement. Separation and Purification Technology, 394(Part 3), Article 137561.
    https://www.sciencedirect.com/science/article/abs/pii/S1383586626008270
  2. Shang, W., Zeng, Y., Xiao, F., Wu, M., Wang, Y., Yang, Z., He, J., & Sun, F. (2026). A multimodal convolutional neural network trained by in-situ OCT characterization for dynamic structural prediction of nanofiltration fouling. Desalination, 639, Article 120676.
    https://www.sciencedirect.com/science/article/pii/S0011916426008325
  3. Lu, G., Ma, R., Zhao, Y., Wang, D., Shang, W., Chen, H., Khan, S. A., Li, M., & Saiz, E. (2025). Solution-sheared supramolecular oligomers with enhanced thermal resistance in interfacial adhesion and bulk cohesion. Nature Communications, 16, 7754.
    https://www.nature.com/articles/s41467-025-63123-9
  4. Elsevier. (n.d.). Scopus author details: Wentao Shang, Author ID 57604364900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57604364900
  5. ORCID. (n.d.). Wentao Shang, ORCID 0000-0002-5168-7696. ORCID.
    https://orcid.org/0000-0002-5168-7696

Da-Zhen Xu | Green Technology | Best Researcher Award

Dr. Da-Zhen Xu | Green Technology | Best Researcher Award

Senior Chemical Engineer | Nankai University | China

Dr. Dazhen Xu is a distinguished researcher at Nankai University, Tianjin, China, specializing in organic synthesis, catalysis, and radical-mediated transformations. With 47 peer-reviewed publications and over 1,231 citations, Dr. Xu has established a notable presence in the field of synthetic and organometallic chemistry. His work primarily focuses on developing innovative, sustainable, and atom-economical methodologies for the construction of complex organic molecules, particularly through metal-catalyzed and metal-free multicomponent reactions. Recent studies highlight his group’s advancements in iron- and copper-mediated transformations, including Markovnikov-selective radical hydrothiolation of alkenes, oxidative arylation and hydroxylation of indolin-2-ones, and bromocyclization of olefinic amides, which contribute significantly to green chemistry and pharmaceutical synthesis. Dr. Xu’s research integrates mechanistic insight with practical synthetic utility, leading to scalable, cost-effective protocols that minimize environmental impact. His collaborations with over 70 co-authors reflect a strong interdisciplinary approach, bridging academic research and industrial application across catalysis, materials, and medicinal chemistry. With an h-index of 23, Dr. Xu’s publications have gained international recognition for their methodological innovation and relevance to sustainable chemical processes. His contributions not only advance the frontiers of organic chemistry but also align with global goals for environmentally benign synthesis, influencing future directions in both academic research and industrial innovation.

Profiles: Scopus | ORCID

Featured Publications 

1. Wang, Y.-N., Jia, H., Yao, L., Chen, Y., Liu, H.-L., Liang, F., … Xu, D.-Z. (2025). Bifunctional iron-mediated multicomponent Markovnikov-selective radical hydrothiolation of alkenes. Organic Chemistry Frontiers, 12, 4462-4468.

2. Li, T.-Y., Xu, L.-L., Wu, D.-Q., Liu, J.-J., Yang, Y., Miao, Z., … Xu, D.-Z. (2025). Copper-Catalyzed Oxidative Arylation and Hydroxylation of Indolin-2-ones for Direct Construction of Tetrasubstituted Carbon Centers. Journal of Organic Chemistry, 90(2), 960-970.
Cited by: 1

3. Xu, L.-L., Wang, S., Sun, J., Zhang, R., Tong, J., … Xu, D.-Z. (2024). Facile access to S-aryl/alkyl dithiocarbamates via a three-component reaction under metal-free conditions. Organic & Biomolecular Chemistry, 22, 7702.
Cited by: 1

4. Zhao, T.-T., Bian, Q., Zhao, Y.-W., Xu, L.-L., Xu, D.-Z., & Zhao, W.-G. (2024). Iron-Mediated Bromocyclization of Olefinic Amides for the Synthesis of Bromobenzoxazines. Synthesis, 56, 2993-3000.
Cited by: 3

Dr. Dazhen Xu’s pioneering research in sustainable catalysis and radical chemistry is transforming the way complex molecules are synthesized, promoting greener and more efficient chemical manufacturing. His vision is to integrate eco-conscious innovation with high-impact synthetic strategies, advancing both scientific knowledge and the global transition toward sustainable chemical industries.