D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Materials Science D-index 87 Citations 29,362 561 World Ranking 696 National Ranking 165

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Composite material
  • Statistics

Composite material, Mathematical optimization, Nanotechnology, Nanoindentation and Internal medicine are his primary areas of study. His research ties Chemical vapor deposition and Composite material together. His Mathematical optimization study which covers Algorithm that intersects with Genetic algorithm.

Xiaodong Li has researched Nanotechnology in several fields, including Supercapacitor, Capacitance and Oxide. His Nanoindentation study integrates concerns from other disciplines, such as Indentation, Amorphous carbon and Elastic modulus. His work carried out in the field of Internal medicine brings together such families of science as Sclerostin and Endocrinology.

His most cited work include:

  • Condition Monitoring and Fault Diagnosis of Electrical Motors—A Review (1547 citations)
  • A Review of Nanoindentation Continuous Stiffness Measurement Technique and Its Applications (1091 citations)
  • Freestanding three-dimensional graphene/MnO2 composite networks as ultralight and flexible supercapacitor electrodes. (1051 citations)

What are the main themes of his work throughout his whole career to date?

Xiaodong Li mainly focuses on Composite material, Mathematical optimization, Chemical engineering, Nanotechnology and Artificial intelligence. His Nanoindentation, Elastic modulus, Composite number, Indentation and Deformation investigations are all subjects of Composite material research. His study in Evolutionary algorithm, Evolutionary computation, Multi-objective optimization, Particle swarm optimization and Optimization problem is carried out as part of his studies in Mathematical optimization.

He does research in Particle swarm optimization, focusing on Multi-swarm optimization specifically. His Nanotechnology study frequently draws connections to adjacent fields such as Supercapacitor. His studies deal with areas such as Machine learning and Pattern recognition as well as Artificial intelligence.

He most often published in these fields:

  • Composite material (14.09%)
  • Mathematical optimization (12.09%)
  • Chemical engineering (11.09%)

What were the highlights of his more recent work (between 2018-2021)?

  • Chemical engineering (11.09%)
  • Optoelectronics (4.93%)
  • Composite material (14.09%)

In recent papers he was focusing on the following fields of study:

Xiaodong Li mostly deals with Chemical engineering, Optoelectronics, Composite material, Graphene and Composite number. His study in Chemical engineering is interdisciplinary in nature, drawing from both Carbon, Anode, Lithium and Electrochemistry. His study in Digital image correlation and Compression falls within the category of Composite material.

His Graphene study frequently links to related topics such as Oxide.

Between 2018 and 2021, his most popular works were:

  • An overview of residual stresses in metal powder bed fusion (88 citations)
  • A Survey on Cooperative Co-Evolutionary Algorithms (53 citations)
  • B4C nanoskeleton enabled, flexible lithium-sulfur batteries (37 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Composite material
  • Statistics

His main research concerns Chemical engineering, Optoelectronics, Carbon, Perovskite and Graphene. His Chemical engineering research is multidisciplinary, incorporating elements of Battery, Anode, Ion, Lithium and Electrochemistry. His study in the field of Light-emitting diode also crosses realms of Optical power.

The study incorporates disciplines such as Cathode and Electrocatalyst in addition to Carbon. His Perovskite research is multidisciplinary, relying on both Grain boundary and Energy conversion efficiency. His Graphene research is multidisciplinary, incorporating perspectives in Composite number, Composite material and Oxide.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Condition Monitoring and Fault Diagnosis of Electrical Motors—A Review

S. Nandi;H.A. Toliyat;X. Li.
IEEE Transactions on Energy Conversion (2005)

2533 Citations

A Review of Nanoindentation Continuous Stiffness Measurement Technique and Its Applications

Xiaodong Li;Bharat Bhushan.
Materials Characterization (2002)

1472 Citations

Freestanding three-dimensional graphene/MnO2 composite networks as ultralight and flexible supercapacitor electrodes.

Yongmin He;Wanjun Chen;Xiaodong Li;Zhenxing Zhang.
ACS Nano (2013)

1191 Citations

Targeted Deletion of the Sclerostin Gene in Mice Results in Increased Bone Formation and Bone Strength

Xiaodong Li;Michael S Ominsky;Qing-Tian Niu;Ning Sun.
Journal of Bone and Mineral Research (2008)

882 Citations

Benchmark Functions for the CEC'2010 Special Session and Competition on Large-Scale Global Optimization

Ke Tang;Xiaodong Li;P. N. Suganthan;Zhenyu Yang.
(2010)

857 Citations

Sclerostin antibody treatment increases bone formation, bone mass, and bone strength in a rat model of postmenopausal osteoporosis.

Xiaodong Li;Michael S Ominsky;Kelly S Warmington;Sean Morony.
Journal of Bone and Mineral Research (2009)

797 Citations

Flexible Zn2SnO4/MnO2 Core/Shell Nanocable—Carbon Microfiber Hybrid Composites for High-Performance Supercapacitor Electrodes

Lihong Bao;Jianfeng Zang;Xiaodong Li.
Nano Letters (2011)

739 Citations

Cooperatively Coevolving Particle Swarms for Large Scale Optimization

Xiaodong Li;Xin Yao.
IEEE Transactions on Evolutionary Computation (2012)

601 Citations

A non-dominated sorting particle swarm optimizer for multiobjective optimization

Xiaodong Li.
genetic and evolutionary computation conference (2003)

597 Citations

Locating and tracking multiple dynamic optima by a particle swarm model using speciation

D. Parrott;Xiaodong Li.
IEEE Transactions on Evolutionary Computation (2006)

561 Citations

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