World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
40
Citations
5487
World Ranking
7423
National Ranking
463

Overview

Xue Z. Wang is affiliated with the University of Leeds in the United Kingdom. Their research primarily focuses on materials science, with an emphasis on materials chemistry as the main subfield of study.

Their work covers several specialized subfields, including:

  • Materials Chemistry
  • Water Science and Technology
  • Physical and Theoretical Chemistry
  • Spectroscopy
  • Analytical Chemistry

Wang's research addresses key topics such as:

  • Crystallization and Solubility Studies
  • Analytical Chemistry and Chromatography
  • Electrostatics and Colloid Interactions
  • Coagulation and Flocculation Studies
  • Image Processing Techniques and Applications
  • Chemical and Physical Properties in Aqueous Solutions
  • Spectroscopy and Chemometric Analyses

Frequent collaborators include Yang Zhang, Guangzheng Zhou, Lingyu Liu, Zihua Wang, and Xiao Juan Liu.

Wang has contributed to numerous publications in respected scientific journals. Notable publication venues with multiple contributions include:

  • Powder Technology
  • Crystals
  • Journal of Chemical & Engineering Data
  • Industrial & Engineering Chemistry Research
  • Journal of Crystal Growth

Recent papers authored or co-authored by Wang are:

  • "Solubility of Benzanilide Crystals in Organic Solvents," 2020, Journal of Chemical & Engineering Data
  • "In Situ Measurement of 3D Crystal Size Distribution by Double-View Image Analysis with Case Study on l-Glutamic Acid Crystallization," 2020, Industrial & Engineering Chemistry Research
  • "Characterization of particle size distribution in slurries using ultrasonic attenuation spectroscopy: Addressing challenges of unknown physical properties," 2021, Powder Technology
  • "Solubility of Dimethyl 2,2'-Azobis(2-methylpropionate) in 15 Pure Solvents and in a Methanol + Water Binary Solvent System," 2020, Journal of Chemical & Engineering Data
  • "Deep learning-based image analysis for in situ microscopic imaging of cell culture process," 2023, Engineering Applications of Artificial Intelligence

Best Publications

  • Multi-scale segmentation image analysis for the in-process monitoring of particle shape with batch crystallisers

    J. Calderon De Anda;X.Z. Wang;K.J. Roberts

  • A new approach to near-infrared spectral data analysis using independent component analysis.

    J. Chen;X. Z. Wang

  • Knowledge discovery from process operational data using PCA and fuzzy clustering

    Y.M. Sebzalli;X.Z. Wang

  • Crystal growth measurement using 2D and 3D imaging and the perspectives for shape control

    Xue Z. Wang;Kevin J. Roberts;Caiyun Ma

  • Data Mining and Knowledge Discovery for Process Monitoring and Control

    Xue Zhang Wang;C. McGreavy

  • Classifying organic crystals via in-process image analysis and the use of monitoring charts to follow polymorphic and morphological changes

    J. Calderon De Anda;X.Z. Wang;X. Lai;K.J. Roberts

  • Statistical Process Control Charts for Batch Operations Based on Independent Component Analysis

    Hamza Albazzaz;Xue Z. Wang

  • Agent-based information flow for process industries' supply chain modelling

    R. García-Flores;X.Z. Wang;G.E. Goltz

  • Application of wavelets and neural networks to diagnostic system development, 1, feature extraction

    B.H. Chen;X.Z. Wang;S.H. Yang;C. McGreavy

  • Real-Time Measurement of the Growth Rates of Individual Crystal Facets Using Imaging and Image Analysis: A Feasibility Study on Needle-shaped Crystals of L-Glutamic Acid

    X.Z. Wang;J. Calderon De Anda;K.J. Roberts

  • Dimension reduction of process dynamic trends using independent component analysis

    R.F Li;X.Z Wang

  • Robust PID based indirect-type iterative learning control for batch processes with time-varying uncertainties

    Tao Liu;Xue Z. Wang;Xue Z. Wang;Junghui Chen

  • A multi-agent system for chemical supply chain simulation and management support

    Rodolfo García-Flores;Xue Zhong Wang

  • Real-time product morphology monitoring in crystallization using imaging technique

    J. Calderon De Anda;X. Z. Wang;X. Lai;K. J. Roberts

  • Nano(Q)SAR: Challenges, pitfalls and perspectives.

    Ratna Tantra;Ceyda Oksel;Tomasz Puzyn;Jian Wang

  • Morphological Population Balance for Modeling Crystal Growth in Face Directions

    Cai Y. Ma;Xue Z. Wang;Kevin J. Roberts

  • Multi-dimensional population balance modeling of the growth of rod-like L-glutamic acid crystals using growth rates estimated from in-process imaging

    Cai Y. Ma;Xue Z. Wang;Kevin J. Roberts

  • (Q)SAR Modelling of Nanomaterial Toxicity - A Critical Review

    Ceyda Oksel;Cai Y. Ma;Jing J. Liu;Jing J. Liu;Terry Wilkins

  • Synthesis and characterization of doped nano-sized ceria–zirconia solid solutions

    Xiaole Weng;Xiaole Weng;Ben Perston;Xue Z. Wang;Isaac Abrahams

  • Model identification of crystal facet growth kinetics in morphological population balance modeling of l-glutamic acid crystallization and experimental validation

    Chao Y. Ma;Xue Z. Wang

  • Neural network based fault diagnosis using unmeasurable inputs

    S.H. Yang;B.H. Chen;X.Z. Wang

Frequent Co-Authors

Jawwad A. Darr
Jawwad A. Darr University College London
Albert Frederick Carley
Albert Frederick Carley Cardiff University
Yu Qian
Yu Qian South China University of Technology
David A. Winkler
David A. Winkler La Trobe University
Panagiotis D. Christofides
Panagiotis D. Christofides University of California, Los Angeles
Junghui Chen
Junghui Chen Chung Yuan Christian University
Antonio Marcomini
Antonio Marcomini Ca Foscari University of Venice
Ihtesham Ur Rehman
Ihtesham Ur Rehman Lancaster University
Jonathan C. Knowles
Jonathan C. Knowles University College London
David J. Morgan
David J. Morgan Cardiff University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Best Scientists Citing Xue Z. Wang

Trending Scientists