World's Best Scientists 2026 revealed!

D-Index & Metrics

Materials Science

D-Index
69
Citations
15608
World Ranking
4690
National Ranking
271

Xiaoying Zhuang publication distribution in Materials Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Materials Science in 2026. The highlighted bar marks where Xiaoying Zhuang sits on this spectrum.

50–69 publications: 28 scientists 70–89 publications: 152 scientists 90–109 publications: 356 scientists 110–129 publications: 487 scientists 130–149 publications: 723 scientists 150–169 publications: 835 scientists 170–189 publications: 850 scientists 190–209 publications: 891 scientists 210–229 publications: 862 scientists 230–249 publications: 766 scientists 250–269 publications: 726 scientists 270–289 publications: 665 scientists 290–309 publications: 593 scientists 310–329 publications: 537 scientists 330–349 publications: 477 scientists 350–369 publications: 440 scientists 370–389 publications: 356 scientists 390–409 publications: 321 scientists 410–429 publications: 256 scientists 430–449 publications: 246 scientists 450–469 publications: 216 scientists 470–489 publications: 212 scientists 490–509 publications: 174 scientists 510–529 publications: 194 scientists 530–549 publications: 162 scientists 550–569 publications: 131 scientists 570–589 publications: 111 scientists 590–609 publications: 103 scientists 610–629 publications: 99 scientists 630–649 publications: 77 scientists 650–669 publications: 92 scientists 670–689 publications: 56 scientists 690–709 publications: 53 scientists 710–729 publications: 53 scientists 730–749 publications: 38 scientists 750–769 publications: 52 scientists 770–789 publications: 43 scientists 790–809 publications: 38 scientists 810–829 publications: 34 scientists 830–849 publications: 25 scientists 850–869 publications: 18 scientists 870–889 publications: 20 scientists 890–909 publications: 24 scientists 910–929 publications: 27 scientists 930–949 publications: 20 scientists 950–969 publications: 17 scientists 970–989 publications: 10 scientists 990–1,009 publications: 16 scientists 1,010–1,029 publications: 13 scientists 1,030–1,049 publications: 12 scientists 1,050–1,069 publications: 9 scientists 1,070–1,089 publications: 8 scientists 1,090–1,109 publications: 7 scientists 1,110–1,129 publications: 9 scientists 1,130–1,149 publications: 2 scientists 1,150–1,162 publications: 5 scientists 1,163+ publications: 100 scientists
50 publications 1,163+

This scientist: 175 publications — 22nd percentile

22% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,163 publications or more.

Xiaoying Zhuang D-index placement in Materials Science in 2026

The chart shows the D-index (discipline H-index) distribution of Materials Science scientists ranked by Research.com in 2026. The highlighted bar marks where Xiaoying Zhuang sits on this spectrum.

40–41 D-Index: 211 scientists 42–43 D-Index: 450 scientists 44–45 D-Index: 612 scientists 46–47 D-Index: 612 scientists 48–49 D-Index: 598 scientists 50–51 D-Index: 657 scientists 52–53 D-Index: 667 scientists 54–55 D-Index: 621 scientists 56–57 D-Index: 597 scientists 58–59 D-Index: 610 scientists 60–61 D-Index: 587 scientists 62–63 D-Index: 606 scientists 64–65 D-Index: 533 scientists 66–67 D-Index: 490 scientists 68–69 D-Index: 469 scientists 70–71 D-Index: 378 scientists 72–73 D-Index: 421 scientists 74–75 D-Index: 359 scientists 76–77 D-Index: 323 scientists 78–79 D-Index: 299 scientists 80–81 D-Index: 230 scientists 82–83 D-Index: 210 scientists 84–85 D-Index: 195 scientists 86–87 D-Index: 203 scientists 88–89 D-Index: 175 scientists 90–91 D-Index: 175 scientists 92–93 D-Index: 142 scientists 94–95 D-Index: 121 scientists 96–97 D-Index: 117 scientists 98–99 D-Index: 107 scientists 100–101 D-Index: 88 scientists 102–103 D-Index: 85 scientists 104–105 D-Index: 68 scientists 106–107 D-Index: 62 scientists 108–109 D-Index: 57 scientists 110–111 D-Index: 45 scientists 112–113 D-Index: 49 scientists 114–115 D-Index: 50 scientists 116–117 D-Index: 34 scientists 118–119 D-Index: 38 scientists 120–121 D-Index: 37 scientists 122–123 D-Index: 29 scientists 124–125 D-Index: 28 scientists 126–127 D-Index: 24 scientists 128–129 D-Index: 33 scientists 130–131 D-Index: 28 scientists 132–133 D-Index: 21 scientists 134–135 D-Index: 20 scientists 136–137 D-Index: 23 scientists 138–139 D-Index: 17 scientists 140–141 D-Index: 12 scientists 142–143 D-Index: 17 scientists 144–145 D-Index: 21 scientists 146–147 D-Index: 13 scientists 148–149 D-Index: 11 scientists 150–151 D-Index: 14 scientists 152–153 D-Index: 13 scientists 154–155 D-Index: 9 scientists 156–157 D-Index: 10 scientists 158–159 D-Index: 7 scientists 160–161 D-Index: 4 scientists 162–163 D-Index: 4 scientists 164 D-Index: 3 scientists 165+ D-Index: 98 scientists
40 D-Index 165+

This scientist: 69 D-Index — 65th percentile

65% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 165 D-Index or more.

Overview

Xiaoying Zhuang is affiliated with the University of Hannover in Germany. Their research primarily focuses on engineering and materials science, with specific engagement in multiple subfields including mechanics of materials, materials chemistry, civil and structural engineering, computational mechanics, and biomedical engineering.

The research topics Xiaoying Zhuang covers are diverse and include numerical methods in engineering, rock mechanics and modeling, nonlocal and gradient elasticity in micro and nano structures, graphene research and applications, composite structure analysis and optimization, acoustic wave phenomena research, and model reduction and neural networks.

They have published several papers with noteworthy examples such as:

  • An energy approach to the solution of partial differential equations in computational mechanics via machine learning: Concepts, implementation and applications (2020) in Computer Methods in Applied Mechanics and Engineering
  • Exceptional piezoelectricity, high thermal conductivity and stiffness and promising photocatalysis in two-dimensional MoSi2N4 family confirmed by first-principles (2020) in Nano Energy
  • Deep autoencoder based energy method for the bending, vibration, and buckling analysis of Kirchhoff plates with transfer learning (2021) in European Journal of Mechanics - A/Solids
  • First-Principles Multiscale Modeling of Mechanical Properties in Graphene/Borophene Heterostructures Empowered by Machine-Learning Interatomic Potentials (2021) in Advanced Materials
  • An efficient optimization approach for designing machine learning models based on genetic algorithm (2020) in Neural Computing and Applications

Frequent co-authors in Xiaoying Zhuang's work include Timon Rabczuk, Bohayra Mortazavi, Huilong Ren, Hehua Zhu, and Yabin Jin.

The scientist frequently publishes in venues such as arXiv (Cornell University), SSRN Electronic Journal, Computer Methods in Applied Mechanics and Engineering, Engineering Analysis with Boundary Elements, and Theoretical and Applied Fracture Mechanics.

Regarding books, Xiaoying Zhuang has contributed to Springer Nature with the book titled Computational Methods Based on Peridynamics and Nonlocal Operators, published in 2023.

Best Publications

  • An energy approach to the solution of partial differential equations in computational mechanics via machine learning: Concepts, implementation and applications

    E. Samaniego;C. Anitescu;S. Goswami;V.M. Nguyen-Thanh

  • Dual‐horizon peridynamics

    Huilong Ren;Xiaoying Zhuang;Xiaoying Zhuang;Yongchang Cai;Yongchang Cai;Timon Rabczuk;Timon Rabczuk

  • Dual-horizon peridynamics: A stable solution to varying horizons

    Huilong Ren;Xiaoying Zhuang;Xiaoying Zhuang;Timon Rabczuk

  • Exceptional piezoelectricity, high thermal conductivity and stiffness and promising photocatalysis in two-dimensional MoSi2N4 family confirmed by first-principles

    Bohayra Mortazavi;Brahmanandam Javvaji;Fazel Shojaei;Timon Rabczuk

  • A Deep Collocation Method for the Bending Analysis of Kirchhoff Plate

    Hongwei Guo;Xiaoying Zhuang;Timon Rabczuk

  • Phase field modeling of quasi-static and dynamic crack propagation: COMSOL implementation and case studies

    Shuwei Zhou;Shuwei Zhou;Timon Rabczuk;Xiaoying Zhuang;Xiaoying Zhuang

  • Deep autoencoder based energy method for the bending, vibration, and buckling analysis of Kirchhoff plates with transfer learning

    Xiaoying Zhuang;Xiaoying Zhuang;Hongwei Guo;Naif Alajlan;Hehua Zhu

  • An extended isogeometric thin shell analysis based on Kirchhoff-Love theory

    N. Nguyen-Thanh;N. Valizadeh;M. N. Nguyen;H. Nguyen-Xuan

  • A phase-field modeling approach of fracture propagation in poroelastic media

    Shuwei Zhou;Shuwei Zhou;Xiaoying Zhuang;Timon Rabczuk

  • Stochastic analysis of the fracture toughness of polymeric nanoparticle composites using polynomial chaos expansions

    Khader M. Hamdia;Khader M. Hamdia;Mohammad Silani;Xiaoying Zhuang;Pengfei He

  • Phase field modelling of crack propagation, branching and coalescence in rocks

    Shuwei Zhou;Shuwei Zhou;Xiaoying Zhuang;Xiaoying Zhuang;Hehua Zhu;Timon Rabczuk

  • A nonlocal operator method for partial differential equations with application to electromagnetic waveguide problem

    Timon Rabczuk;Huilong Ren;Xiaoying Zhuang;Xiaoying Zhuang

  • Fracture modeling using meshless methods and level sets in 3D: Framework and modeling

    X. Zhuang;X. Zhuang;C.E. Augarde;K.M. Mathisen

  • Fracture properties prediction of clay/epoxy nanocomposites with interphase zones using a phase field model

    Mohammed A. Msekh;Mohammed A. Msekh;N. H. Cuong;Goangseup Zi;P. Areias

  • First-Principles Multiscale Modeling of Mechanical Properties in Graphene/Borophene Heterostructures Empowered by Machine-Learning Interatomic Potentials.

    Bohayra Mortazavi;Mohammad Silani;Evgeny V. Podryabinkin;Timon Rabczuk

  • Machine-learning interatomic potentials enable first-principles multiscale modeling of lattice thermal conductivity in graphene/borophene heterostructures

    Bohayra Mortazavi;Evgeny V. Podryabinkin;Stephan Roche;Stephan Roche;Timon Rabczuk

  • Phase-field modeling of fluid-driven dynamic cracking in porous media

    Shuwei Zhou;Shuwei Zhou;Shuwei Zhou;Xiaoying Zhuang;Xiaoying Zhuang;Timon Rabczuk

  • Exploring Phononic Properties of Two-Dimensional Materials using Machine Learning Interatomic Potentials

    Bohayra Mortazavi;Ivan S. Novikov;Ivan S. Novikov;Evgeny V. Podryabinkin;Stephan Roche

  • An explicit phase field method for brittle dynamic fracture

    Huilong Ren;Xiaoying Zhuang;Xiaoying Zhuang;Cosmin Anitescu;Timon Rabczuk

  • The effect of weak interlayer on the failure pattern of rock mass around tunnel – Scaled model tests and numerical analysis

    Feng Huang;Feng Huang;Hehua Zhu;Qianwei Xu;Yongchang Cai

  • Phase field modeling of brittle compressive-shear fractures in rock-like materials: A new driving force and a hybrid formulation

    Shuwei Zhou;Shuwei Zhou;Xiaoying Zhuang;Xiaoying Zhuang;Timon Rabczuk

  • Isogeometric analysis of large-deformation thin shells using RHT-splines for multiple-patch coupling

    N. Nguyen-Thanh;K. Zhou;X. Zhuang;P. Areias

  • A comparative study on unfilled and filled crack propagation for rock-like brittle material

    Xiaoying Zhuang;Xiaoying Zhuang;Junwei Chun;Hehua Zhu

  • Uncertainty quantification for multiscale modeling of polymer nanocomposites with correlated parameters

    N. Vu-Bac;Roham Rafiee;Xiaoying Zhuang;Tom Lahmer

  • Efficient coarse graining in multiscale modeling of fracture

    Pattabhi R. Budarapu;Robert Gracie;Shih Wei Yang;Shih Wei Yang;Xiaoying Zhuang

  • Sensitivity and uncertainty analysis for flexoelectric nanostructures

    Khader M. Hamdia;Hamid Ghasemi;Xiaoying Zhuang;Naif Alajlan

  • Accelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials: A MTP/ShengBTE solution

    Bohayra Mortazavi;Evgeny V. Podryabinkin;Ivan S. Novikov;Ivan S. Novikov;Timon Rabczuk

  • A unified framework for stochastic predictions of mechanical properties of polymeric nanocomposites

    N. Vu-Bac;M. Silani;M. Silani;T. Lahmer;X. Zhuang

  • Outstanding strength, optical characteristics and thermal conductivity of graphene-like BC3 and BC6N semiconductors

    Bohayra Mortazavi;Bohayra Mortazavi;Masoud Shahrokhi;Mostafa Raeisi;Xiaoying Zhuang

Frequent Co-Authors

Timon Rabczuk
Timon Rabczuk Bauhaus University, Weimar
Hehua Zhu
Hehua Zhu Tongji University
Hung Nguyen-Xuan
Hung Nguyen-Xuan Ho Chi Minh City University of Technology
Bohayra Mortazavi
Bohayra Mortazavi University of Hannover
Harold S. Park
Harold S. Park Boston University
Guowei Ma
Guowei Ma University of Western Australia
Charles E. Augarde
Charles E. Augarde Durham University
Goangseup Zi
Goangseup Zi Korea University
Naif Alajlan
Naif Alajlan King Saud University
Peter Wriggers
Peter Wriggers University of Hannover

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